Price indices are useful for calculating inflation over time.  The consumer price index (CPI) measures changes in prices for the overall economy.  Researchers can also use price indices to understand the evolution of the price of health care over time.  For instance, the Bureau of Labor Statistics also calculates a CPI for Medical Care and Medical Care Services.

The question of how to calculate a price index is far from trivial however.  To calculate the change in the price of any good between years 1 and T, one could simply use the following formula:

• P_simple=p_iT/p_i1

However, a price index indicates the change in prices for a basket of goods.  If you are considering the change in price of 10 medical services, how much weight to you give to each one?

Economists have generally come up with the solution: the goods that make up a large share of total expenditures should be weighed more than those that make up a small share.  For instance, let us imagine a simple example where you have two expenses: food and medical care.  The price of food goes up by 10% and the price of medical care goes up by 20%.  Let us assume that food makes up a larger share of your budget than medical expenses and that the initial value of the price index is 1.0 (i.e., T=1).  Thus, if 80% of your income goes to food and 20% of your income goes to medical expenses, than the value of the price index one year from now would be would be 80%*1.1+20%*1.2=1.12.

Sounds easy right?  Not so fast.

I said that 80% of the person’s budget was made up by food, but does that figure refer to your budget expenditures in the first time period or the second time period?  Let us assume the following:

• P_food,1=$1; Q_food,1=800; E_food,1=$800;
• P_food,2=$1.1; Q_food,2=800; E_food,2=$880;
• P_med,1=$100; Q_med,1=2; E_med,1=$200;
• P_med,2=$120; Q_med,2=3; E_med,2=$360;

Above, P, Q and E refers to price, quantity and expenditures respectively; the first subscript in the formulas above refers to the good (food or medicine) and the second subscript refers to the time period (1 or 2).  In the example, 80% of the person’s budget in period 1 is for food and 20% is for medical supplies.  If we use the budget shares in the first period to weight the price changes, then we could calculate the price index as:

• (800*$1.1+2*$120)/(800*$1+2*$100)=1.120

This method is known as the Laspeyres price index.  The general formula is: [Σ p_itq_i0]/[Σ p_i0q_i0].

An alternative measure is the Paasche  price index.  In this case, we weight the price changes depending on the bundle of goods in the last time period under consideration.  In the example, our price index would be:

• (800*$1.1+3*$120)/(800*$1+3*$100)=1.127

The price index is higher now.  Why?  In the last period, the quantity of medical care we purchased increase (for 2 to 3) compared to the quantity of food purchased (stayed the same at 800).  This means that the Paasche price index will put relatively more weight on the price changes for medicine.  Since the price of medicine increased faster than the price of food, the overall price index level be higher in this example than in the case of the Laspeyres price index.  The general formula for the Paasche price index is: [Σ p_itq_iT]/[Σ p_i0q_iT].

However, both the Laspeyres and Paasche indices do not take into account substitution effects between goods. Goods are weighed statically based on the quantity purchased in either the first period (Laspeyres) or last period (Paasche). To solve this problem, one can use the Fisher price index. This index does account for individuals substituting across different types of goods. To calculate the Fischer index, one simply takes the geometric mean of the Laspeyres and Paasche indices. According to the example above, this means the price index would be:

• P_f=(P_p*P_l)^0.5=(1.120*1.127)^0.5=1.123

One can also chain the Fisher index calculations from each year in order to produce a chain-weighted Fisher price index, but I’ll save that explanation for another day.

John Kay offers a European perspective on the debate of between the superiority of a market economy against a centrally planned economy.  Is there empirical evidence that a market economy is superior?  John Kay says yes:

“The fall of the Berlin Wall in November 1989 …marked the end of the most extensive controlled experiment in the history of social sciences – the division of Germany into two economic zones, one centralised and planned, the other a market economy. After forty years, the gap in living standards between the two was so extreme that the experiment was terminated.”

Why is capitalism so successful over the long run?  Kay gives 3 reasons:

• Prices act as signals; the operation of the price mechanism is a better guide to resource allocation than central planning
• Markets function as a process of discovery, the chaotic process of experimentation through which a market economy adapts to change…Centralised systems experiment too little. They find reasons why new proposals will fail – and mostly they are right in their suspicions, because most experiments do fail. But market economies thrive on a continued supply of unreasonable optimism.
• Markets yield benefits from the diffusion of political and economic power… A one sentence description of why some countries are poor and others rich is that the politics and economics of poor countries are dominated by rent-seeking and the politics and economics of rich countries are not.

But isn’t a market economy one motivated solely by greed?  Can a country motivated solely by greed be successful?  According to Kay, “This is the economic environment of Nigeria and Haiti, and it does not work.”  Instead, the greed must be tempered through the mechanisms of trust relationships and reputation.  To get a broader perspective, Kay concludes with the following:

“Markets are not a well-oiled machine: they more closely resemble a constantly changing, adaptive biological system. Pluralism is their motive force, their essence is chaotic, their development inherently uncertain. If we could predict the evolution of markets, we would not need markets in the first place.”

Source: Kay, John (2009) “The Rationale of the Market Economy: A European Perspective,” Capitalism and Society: Vol. 4: Iss. 3, Article 1.

Most economists focus on the concept of “economic efficiency.” The basic concept of economic efficiency is to maximize the overall resources available to society.  However, often times economists ignore the importance of equity (i.e., the distribution of resources within a society).

Tyler Cowen reminds us that seeking economic efficiency blindly is not ideal, especially in the case of natural disasters as the one that hit Haiti.  Below is an excerpt:

I still believe that foreign aid does not raise economic growth rates, on average.  But aid can alleviate human misery, such as when a visiting doctor gives vaccines or hands out medicine.  (In fact per capita income may fall, as a result, if some “weaklings” are kept alive.)…

Imagine U.S. troops liberating Buchenwald.  Would any commentators say the following?  ”Don’t give him that blanket, sell it to him!”  “Hey buddy, get a job!”  ”Moral hazard: they’ll just go get captured again.”  etc.  I don’t think so.

In the past, this blog has reported the average salaries of recent economics PhD graduates.  For Econ PhD graduates in 2009, we can update these figures as follows using more recent data.  For instance, below are the average (median) starting salaries of recent economics grads by the type of institution by which they were hired.

• University: $92,600 ($89,500)
• College: $77,100 ($70,000)
• Policy/Applied Research: $85,800 ($90,000)
• Central bank: $105,700 ($110,000)
• Private Firm: $115,500 ($120,000)

Of the people in the survey, the percentage of individuals who accepted jobs at the following types of institutions were:

• University: 63.6%
• College: 8.6%
• Policy/Applied Research: 10.2%
• Central bank: 6.2%
• Private Firm: 11.4%

Here are some writing tips from “Writing Economics” by Robert Neugeboren with Mireille Jacobson:

• Outline. Organize your ideas into an argument with the help of an outline.
• Define the important terms.
• Use the Active Voice.
• Put Statements in Positive Form.  Don’t write “Many day-traders did not pay attention to the warnings of experts.” Instead use “Many day-traders ignored the warnings of experts.”
• Omit Needless Words.
• Stick to One Tense in Summaries.
• Summaries and Repetition.  “When writing up your empirical results focus only on what is important
  and be as clear as possible. You may feel that you are repeating yourself and that the reader may be offended at how closely you are leading him or her through your tables and graphs but, to paraphrase John Kenneth Galbraith, both smart and dumb readers will appreciate your pointing things out directly and clearly. The dumb readers need the help, and the smart ones will take silent pleasure in the knowledge that they didn’t need your assistance!”
• Edit yourself, remove what is not needed, and keep revising until you get down to a simple, efficient way of communicating.

The American Economic Association annual meeting will be in Atlanta this year.  Joseph Stiglitz will give the keynote address on “Homoeconomicus: The Impact of the Economic Crisis on Economic Theory.”  

I will be attending the conference from January 2 to January 5.  Posting will return after I return.

Capitalism has taken a beating the past few years.  From the mortgage crisis to Bernie Madoff’s ponzi scheme, from a falling stock market to rising unemployment, capitalism does not seems like the best economic system at present.  In fact, Michael Moore even made a movie satirically titled Capitalism: A Love Story.

Yet now is not the time to abandon capitalism.  It offers the best hope to jump start the economy and–more importantly–generate long term progress.  The Economist offers 3 reasons why capitalism must be praised:

1. Creates cooperation between sometimes antagonistic parties.  ”…companies in fact depend on persuading large numbers of people—workers and bosses, shareholders and suppliers—to work together to a common end. This involves getting lots of strangers to trust each other.”
2. Increases innovation.  ”Business people do not just invent clever products that solve nagging problems, …[t]hey also create organisations that manufacture these products and then distribute them about the world.”
3. Maintains political pluralism.  ”Only 202 of the 500 biggest companies in America in 1980 were still in existence 20 years later.”

Most importantly, however, is that capitalism is provides a more open society.  Anyone can earn a living, even if you don’t come from money or are a recent immigrant.  Although of course, privileged individuals do better in any society, capitalism doesn’t preclude individuals from occupations if they are from certain backgrounds or castes.  Further, capitalistic governments tend to meddle less in individuals affairs and uphold individual freedoms.  Least we forget, the Nazi’s were from the National Socialist party. [Although to be fair, socialist governments can uphold individual freedoms and capitalist countries can also oppress minorities as well.]

A paper by the Indepenent Instiute claims that businessmen are more honest than preachers, politicians, and professors.  Although businessmen can make untrue claims just like these other professions, because customers can “test drive” the products sold, the truth regarding the  product will come out eventually. This gives the businessmen an incentive to be honest up front in order to maintain long term relationships with customers and suppliers.

In the words of Winston Churchill, ”The inherent vice of capitalism is the unequal sharing of blessings. The inherent virtue of Socialism is the equal sharing of miseries.”

The first American Nobel laureate in economics died on Sunday at age 94. The N.Y. Times has an obituary.  Here are other economists’ comments.

On Tuesday, President Obama unveiled a plan to use repaid TARP monies to fund a job creation program.  The question is, can the government actually create jobs?

Initially, one would say yes.  If the government hires more workers, this is job creation.  If the government hires more contractors, this is job creation.  If the government gives subsidies to businesses to increase employment, this is job creation.  Isn’t it?

One must first wonder where the government is getting the money to pay for the job creation programs.  Let us assume that it is from taxpayers.  In this case, the government is taking money from individuals to ‘create jobs.’  However, by increasing taxes, consumers have less money to spend on goods and services.  When consumers buy less stuff, firms will cut jobs.  The net effect likely will be a wash.  The government ‘creates’ jobs by paying money itself and destroys jobs by raising taxes.

What if the government funds the job creation with debt?  If the debt is only purchased by Americans, we have the same problem.  Consumers purchase government debt rather than buying products.  Again the net effect is likely a wash.

Now let us think expand our thinking.  Assume we live in a global economy where foreigners buy our bonds.  In this case, the government may be able to create jobs somewhat in the short run .  Foreigners will have less money to buy American exports if they buy our bonds, but likely only a fraction of foreigners income is spent on American goods.  Thus, the extra money the government receives from foreigners can create American jobs in the short run.  Subsequent generations, however, will have to pay back the loans from foreigners in the form of higher taxes.  Thus, increased job creation now comes at the expense of decreased job creation in the future.

Let us also think about business cycles in the creation of jobs.  The U.S. just went through a bad economic downturn.  Individuals and firms were saving more and buying/investing less.  Thus, firms had a smaller market to which they could sell goods.  If the government taxes (or borrows) from individuals and firms, and decides to spend all this money on ‘job creation,’ employment could actually increase.  Currently, the marginal propensity to spend will likely be higher for the government than for consumers or firms.  However, increased marginal propensity to consume implies a decreased marginal propensity to save.  With lower savings rates, there are fewer funds available to investors to invent new ideas, invest in new technologies and provide the foundation for long-run technical growth.  Interest rates will rise.  Currently, the Federal Reserve has held down interest rates by printing more money, but this will likely cause inflation in the near- to medium-term.

As any economist knows, there is no free lunch.  The government may be able to create jobs in the short run to counteract dips in the business cycle, but these debts must be repaid in the long-run.  Thus, in the long-run the government does not create jobs.  Innovative individuals and firms create jobs.  Further, this post has not even discussed the problem that the government will likely misallocate funds and may hire the wrong type of workers for long term economic growth.

If the government really could create jobs in the long-run, then the government might be able to maximize job growth by spending ad infinitum.

“The curious task of economics is to demonstrate to men how little they know about what they imagine they can design.”

• F. A. Hayek, The Fatal Conceit.

Economist Tsung-Mei Cheng has developed three Universal Laws of Health Care Systems.  These are:

1. No matter how good the health care in a particular country, people will complain about it.
2. No matter how much money is spent on health care, the doctors and hospitals will argue it is not enough.
3. The last reform always failed.

Source: The Healing of America, p. 26-27.

“Despite the spectacular failure of Fannie Mae and Freddie Mac, some economists insist that Fannie and Freddie need to be kept in place but somehow, just made safer. This optimistic advocacy—which assumes that Fannie and Freddie are like airplanes that need better landing gear—is in spite of the fact that between 1992 and 2008 Fannie and Freddie had their own regulator, the Office of Federal Housing Enterprises Oversight, that failed to stop the meltdown of Fannie and Freddie that has cost the U.S. taxpayer about $100 billion and counting.  Somehow, this time will be different.”

• Roberts, Russell (2009) “How Little We Know,” The Economists’ Voice: Vol. 6: Iss.11, Article 3.

Claudia Goldin and Lawrence Katz have a nice list of the Ten Most Important Rules of Writing Your Job Market Paper.  However, these tips can be used for almost any type of non-fiction writing.  Some of my favorites include:

Rule #1: You will probably not have a Nobel Prize winning idea.

• Theorem #1: It is always possible to transform a good idea into a great paper and a superb presentation.
• Theorem #2: Even if your idea is Nobel-worthy, you can always make it into a poorly written paper and a lousy presentation. This theorem will probably never be needed; see Rule #1.

Rule #3: Your paper is an exercise in persuasion (we mean in positive not normative economics). Your readers are your audience. They have better things to do than read your paper. Make them interested in your thesis and convinced of your argument.

Rule #4: No great paper—no matter how well constructed, brilliant, and well written—first emerged from the author’s printer in that form. It was rewritten at least 10 times. Rewriting is the true art of writing.

Rule #5: No author—no matter how careful and humble—can see all (or even most) of his or her writing errors. Trade papers with another student. Be tough; there will be some initial pain, but gratitude will follow.

Rule #6: Most paragraphs have too many sentences and most sentences have too many words. Repetition is boring. We repeat: repetition is boring. Cut, cut, and then cut again.

Rule #8: Verbalizing your argument is more difficult than writing it. Giving a presentation will reveal where your argument falls flat and will show you how to redraft the paper. Give many presentations before sending out your paper. Give them to a workshop, friends, a dog or cat, even the wall. The presentation will force you to confront inconsistencies in your argument.

Currently, organic farming supplies less than 3% of America’s food, but this figure is on the rise.  Does organic farming provide a “sustainable” of how to grow food in the next millennium?  

Paul Roberts thinks not.  Eliminating chemical fertilizers and pesticides would reduce crop yields.  Thus, the amount of additional farmland that would be needed to be brought online to replace lost productivity would be immense.  Vaclav Smil claims that an expansion of organic farming would “require complete elimination of all tropical rainforests, conversion of a large part of tropical and subtropical grasslands to cropland, and the return of a substantial share of the labor force to field farming.”   

“Local” farming is viable either.  Most eaters live in cities while most growers are on distant farms.  Growing massive amounts of food in urban areas is not economically viable.  Columbia Professor Dickson Dispommier claims that a 30-story glass skyscraper using nonsoil farming could produce enough food on a single city block to feed 50,000 people, but the farm would cost $200 million to build.

Dr. Bruce Douglas’s perspective on taking money out of health care:

“Health care is a ’service,’ provided by health care practitioners, that does not belong in the competitive, so-called free enterprise marketplace. Of course, doctors have to be paid, but the payment should not come directly from the patient. Reception areas in doctors’ offices should be places where patients register for care, provide their insurance information, fill out a history form, and wait to be seen by their doctor. Receptionists should enter the information in a computer and be fed all the information that has been stored, privately, about that patient, that the doctor needs in order to give the patient undivided, preventive-oriented attention.  Money should not be mentioned, directly or indirectly, because health care, at any level, cannot be equated in dollars and cents.“

Is this a realistic view for an effective health care system?  The patient doesn’t pay and the doctor doesn’t worry about cost?  Actually, yes…if the insurer limits the phyisicans choices regarding what is insurable.  In other words, this is managed care.  The patient pays nothing or little, the physicians can prescribe whatever they want regardless of price, but the physician choice is limited to treatments that are approved by the managed care organization.  However, Dr. Douglas does not support significant limitations on the physicians treatment choices.  He describes the the growth of HMOs as “rationing raised its ugly head.” 

If on the other hand, the doctor means that insurance should pay for whatever they want, doctors should prescribe whatever they want, and patients shouldn’t pay anything, well then this is a  recipe for significant cost inflation.  When insurance only covered severe hospital stay, patients would pay for most of medical care out of their own pocket.  If this was the case, then the doctor’s recommendations would be accepted or rejected by the patient based on affordability and other factors.  

Dr. Douglas’s solution is for a single payer system.  However, even a Medicare-for-all system will face the same dilemma.  Either, the single payer system will limit cost, but will have to ration care, or it will decide to cover all services but the cost of health care will increase.  

Today, Elinor Ostrom of Indiana University and Oliver E. Williamson of the University of California, Berkeley won the Nobel prize in Economics.  Dr. Ostrom won “for her analysis of economic governance, especially the commons” and Dr. Williamson “for his analysis of economic governance, especially the boundaries of the firm.”

According to the N.Y. Times:

The prize committee, in making the awards, seemed to be influenced by the credit crisis and the severe recession that in the minds of many mainstream economists has highlighted the shortcomings of a unregulated marketplace, in which “economic actors,”left to their own devices, will act in their own self-interests and in doing so, will enhance everyone’s well-being.  The committee, in effect, said that theory was too simplistic and ignored the unstated relationships and behaviors that develop among companies that are competitors but find ways to resolve common problems. “Both scholars have greatly enhanced our understanding of non-market institutions” other than government, the committee said.

“Basically there is a common understanding that develops even among competitors when they are dealing with each other,” Mr. Shiller said, adding “when people make business contact, even competitors, they can’t anticipate everything, so an element of trust comes in.”

More details on the Nobel laureates, see the NobelPrize.org.

Tyler Cowen gives a nice example of Dr. Williamson’s work in practice:

“Let’s say you privatize a water system in Africa and write a 30-year contract with a private French company to run the thing.  As the contract nears its end, and if renewal is not obvious, the company has an incentive to “asset strip,” or at the very least not maintain the value of the pipes.  Alternatively, the government might signal, in advance, that it has every intention of renewing the contract.  The company then has the incentive to lower quality to consumers, since it expects renewal a and faces weaker competitive constraints.”

Marketplace has an interview with Dr. Williamson who reveals one of the most important benefits of a Nobel prize: a free university parking space.

“…the lessons of history makes me mindful of a lesson I learned as an operations-research student at the Naval Postgraduate School some years ago. While trying to develop a mathematical model to explain the complexities of naval warfare, I realized that it was simply impossible to develop the perfect model. No amount of mathematical artistry would be sufficient to explain the virtually infinite number of variables in human behavior. The great lesson for all those who use mathematical models as tools to understand the real world is that models provide insights, not answers. I hope our economics community has finally learned that lesson — at least until they forget it again during the next boom cycle.”

• Captain Thomas R. Beall, U.S. Navy, retired.

Ben Bernanke declared today that “From a technical perspective, the recession is very likely over at this point.” What has made him make this declaration.

If he using the stockmarket as an indication, the recession may be over. Stocks are still down 30% from the beginning of the year in 2008. However, the S&P 500 is up about 50% since the beginning of the year. Thus, according to the stock market, the recession may be over. However, unemployment is at 9.6%. Further, economists predict that unemployment will reach 10% by the end of the year.

Economic growth may be on the rise, but changes in employment levels historically have lagged behind changes in overall economic production. Economic activity may be growing, but unemployment will likely remain high for the near-term future.

Then again–as recent history has shown us–economists are not good at predicting the future. Instead, you should just take from this post that nobody knows what will happen next.

Why is medical care so expensive? It depends on who you ask. Victor Fuchs (1996) polled 46 health economists, 44 economic theorists and 42 practicing physicians. Fuchs asked if they agreed with the following statement: “The primary reason for the increase in the health sector’s share of GDP over the past 30 years is technological change in medicine.”

• Health Economists: 81% agree,
• Practicing Physicians: 68% agree,
• Economic Theorists: 37% agree.

Is technological change the force driving increased health care costs? It depends who you ask.

The Immigration Policy Center believes not.  Some evidence they give includes:

• Ku (AJPH 2009) reports that “immigrants’ medical costs averaged about 14% to 20% less than those who were US born.”
• Four out of five people in America who have no insurance are U.S. citizens.  
• The UCLA Center for Health Policy Research found that in 2005 one out of every five uninsured Californias were undocumented.
• Undocumented overuse of the emergency room may be a myth.  In 2006, 20% of U.S.-citizen adults and 22% of U.S.-citizen children had visited the emergency room within the past year.  In contrast, 13% of noncitizen adults and 12% of noncitizen children had used emergency room care.  

Price elasticity estimates how consumer demand changes as prices change.  For instance, the price elasticity of medical service is defined as the percentage change in quantity of medical care demanded divided by the percentage change in price of the same commodity.  Most academics believe that the price elasticity for medical services is between 0 and -1.  This means that if prices increase by 10%, the demand for medical services decreases, but by less than 10%.  This means that medical goods are inelastic.

One can also measure the income elasticity for medical services.  Income elasticity measures the percentage change in the demand for medical services as income increases.  If the income elasticity is greater than 1, medical services are a luxury good.  This means that as people get richer, they want more of the good.  Estimates of income elasticity range from 0 to about 1.6; meaning that researchers do not know if medical services are elastic or inelastic with respect to income.

A paper by Borger et al. (2008) reviews of the findings of previous research regarding price and income elasticities of medical care.  Click on the following links for a listing of empirical estimates of price elasticities and income elasticities.

• How to cure Hepatitis: Ban it.
• An Oxymoron or: How to cut health care cost using mandatory volunteering.
• Taking a cigarette break at work.
• Death to the Public Plan! Viva Co-ops?
• A bureaucrat is already rationing your health care.

I just recently returned from my honeymoon in Tokyo, Japan and Bali, Indonesia.  One thing anyone visitng Tokyo will notice is that it is very clean .  Further, Japan has the most advanced toilets in the world.  On the other hand, most Balinese burn their trash.  Why is Tokyo so clean when other world cities are not? 

Let us assume that the average cleanliness of a city equals:

• C=100-L/S

The variables above represent (C)leanliness, (L)ittering and street (S)weeping.  The maximum cleanliness level is 100. We can see that there are two ways that a society can have clean streets. 

1. Reduce littering.  It is possible that different societies have different preferences for the amount of littering they will do.  Japan is a fairly formal culture individuals may go out of their way not to offend anyone by littering; or individuals may just have a natural affinity for cleanliness.
2. Increase street sweeping frequency.  For any given level of littering, more frequent street sweeping will result in a cleaner society.

If a poilcy maker has a goal to increase cleanliness in an area, how best should they accomplish this?  Let assume the following cost function:

• c=f(L₀-L)+g(S)

Decreasing littering involves some cost.  Likely, the cost of decreasing littering exhibits decreasing returns.  Similarly, there are decreasing returns from increased street sweeping.  Everyone knows that vaccuuming your house twice per week doesn’t quite make a room twice as clean as vaccuuming only once per week would have. 

Thus, we are left with the old dilemma of prevention versus treatment.  “Preventing” littering involves educating individuals and convincing them not to litter in the first place.  “Treating” littering simply involves cleaning up the littering after it takes place.  I predict that preventing littering is a more cost effective alternative for all but the lowest cleanliness levels.

Regardless of how the Japanese do it, Japan is clean.

Most experts believe that health care demand is fairly inelastic. If you are sick, you will not be very price sensitive. There are exceptions to this rule (e.g., elective surgery such as plastic surgery, purchases of eyeglasses) but most studies find that patients are fairly insensitive to changes in health care prices. For instance, the RAND Health Insurance Experiment found that the price elasticity of medical expenditures is -0.2.

An working paper by Amanda Kowalski claims that medical care and prices have an elastic relationship. “My main results show that the price elasticity of expenditure on medical care is -2.3 across the .65 to .95 quantiles of the expenditure distribution, with a point-wise 95% confidence interval at the .80 quantile of -2.5 to -2.0. Although I allow the price elasticity estimate to vary with expenditure, I find a fairly stable elasticity across the estimated quantiles. This estimate is an order of magnitude larger than the RAND estimate of the mean elasticity of -0.2.”

Kowalski uses claims and patient level data from a large employer’s database. Since price and quantity are often correlated, one needs a random shock to quantity in order to identify this elasticity. For an instrument, Kowalski uses whether or not a family member has an injury. When a family member has an injury, this will not affect the medical expenditures of other family members (assuming they are not also injured). However, an injury will use up a large portion of a family’s deductible and thus lower coinsurance rates from 100% (during the deductible) to 20% (after the deductible is used up).

One may worry that sickness risk is correlated among family members. For instance, if you investigated a family of extreme snowboarders, the probability any one person is injured is high. It is possible that we can observe one person’s injury in the data which will be correlated with a high probability of injury for their spouse and child. If the other family members are covered under an employed spouse’s health plan, the injury may not show up in the data, but some medical expenditures will.

To check whether or not sorting in mating along the health risk dimension occurs, Kowalski looks at couples who each have their own deductible. Thus, the injury of a partner will not affect their spouse’s coinsurance rate. Kowalski finds that price elasticity in this case is not statistically different from zero and, as predicted, the instrument has little power.

One possible explanation for the large elasticity is that partners may leave the insurance coverage after their spouse gets injured. If their spouse is seriously injured, they may have to stay home to take care of them. However, before leaving their coverage, they may decide to have all of their major medical procedures done. Because the data are only from 2003 and 2004, intertemporal price elasticity could be a problem. Kowalski does find that some evidence that inter-temporal shifting is not driving her results, however.

• Amanda E. Kowalski “Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care” NBER WP #15085.

The N.Y. Times Magazine has a nice piece on rationing health care, but nothing too new if you’ve been a loyal reader of the Healthcare Economist. Below is an excerpt.

“Health care is a scarce resource, and all scarce resources are rationed in one way or another. In the United States, most health care is privately financed, and so most rationing is by price: you get what you, or your employer, can afford to insure you for. But our current system of employer-financed health insurance exists only because the federal government encouraged it by making the premiums tax deductible. That is, in effect, a more than $200 billion government subsidy for health care. In the public sector, primarily Medicare, Medicaid and hospital emergency rooms, health care is rationed by long waits, high patient copayment requirements, low payments to doctors that discourage some from serving public patients and limits on payments to hospitals.”

As I’ve said many times before, health care is a scarce good an must be rationed.  Unlike most goods, healthy people generally do not demand zero medical care, so some people are under the assumption that medical care is only for the sick and thus should not be rationed.  However, since medical care is costly, it must be rationed, either by price, by wait lists, or by other means.

The article also mentions Richard Kronick, a UCSD professor and member of my dissertation committee, and his research suggests that “there is little evidence to suggest that extending health insurance to all Americans would have a large effect on the number of deaths in the United States.”

The authors advocates using a QALYs to evaluate the cost effectiveness of treatments, just as the UK’s NICE does now.

This week I’ll be in Vancouver for the Western Economic Association International Conference.  

I’ll be presenting my paper on “Why Does Getting Married Make You Fat? Incentives and Appearance Maintenance.”

Southern California is in the midst of a drought.  What is the city doing to conserve water?  They are resorting to new rules and ‘water cops‘.

• Apartments, Condos and Businesses can water: Monday, Wednesday & Friday
• Homes with odd-numbered addresses can water: Sunday, Tuesday & Thursday
• Homes with even-numbered addresses can water: Saturday, Monday & Wednesday
• Apartments, Condos and Businesses can water: Monday, Wednesday & Friday
• On your watering day, you may only water before 10 a.m. or after 6 p.m.
• Landscape irrigation using sprinklers is limited to no more than ten minutes maximum per watering station per assigned day.

Isn’t there an easier way?  Of course.  The answer is to raise the price of using water.  I’ve broached this idea in two previous posts.   Charging more for water (especially during a drought) will accomplish the same goal as these arcane rules set out to do: reduce water demand.

Watering at night or early in the morning saves water because less water evaporates at this time of day. If water is more expensive, people will voluntarily water early or late in the day to save water.  Further, a higher price of water compel people to 1) water less and 2) plant vegetation that requires less water such as succulents.  This way people will water when they please, but will water less often and with less water.

Economists believe that getting prices right will lead to efficient market allocation; in the case of water conservation, economists are almost certainly correct.

The Economist paraphrasing Nobel laureate Paul Krugman:

• Most work in macroeconomics in the past 30 years has been useless at best and harmful at worst, said Mr Krugman.

Let us say you are a person trying to choose between buying bananas and oranges. What you are trying to do is maximize a utility function u(x,y) where x represents bananas and y represents oranges.  You can not buy an infinite amount of each however.  This is subject to a budget constraint.  Thus, we have the following maximization problem.

• max u(x,y) s.t. p₁x + p₂y ≤ I

If we add functional form assumptions on the utility function we can form the following Lagrangian:

• L= ln(x) + αln(y) – λ[p₁x + p₂y - I]

Our first order conditions are:

• L_x:  1/x – λp₁ =0
• L_y:  α/y – λp₂ =0
• L_λ:  p₁x + p₂y – I =0

Our optimal level of bananas and oranges is:

• x* = I/[(1+α)p₁]
• y* = Iα/[(1+α)p₂]
• λ* = (1+α)/I

We solved for x* (bananas), y* (oranges), and λ*, but what the heck is λ? The term λ is the shadow price. The shadow price represents the following: assume that instead of I dollars of income, we had I+ε dollars. If we had the extra ε of income, the shadow price λ tells us by how much the objective function (utility function) would increase since we could buy a few more apples and bananas.

The N.Y. Times recently reported that the recession has threatened many loan forgiveness programs.  Loan forgiveness programs are common for nurses and teachers.  This made me think, why would a firm offer loan forgiveness instead of higher wages?

1. Cost of capital. Businesses may take advantage of lower borrowing costs.  ”After-loan” wages would be higher for workers if businesses offered loan forgiveness for a given labor cost to the firm.
2. Self-control.  Workers may prefer lower wages with loan forgiveness to higher wages without loan forgiveness.  The loan forgiveness is in essence forced savings; compelling workers to take a lower wage in order to pay off their loan.
3. Employee selection.  Loan forgiveness is often used to attract workers to rural and/or low-income areas.  Loan forgiveness is most attractive to workers who are most liquidity constrained.  By attracting liquidity constrained workers initially, these workers will also be the least likely to move–since moving also involves large fixed costs.  It could also be the case that employers are searching for workers who are more motivated by the work they do then the wage they make; these workers would be willing to start a career in a low wage sector in exchange for debt forgiveness.  Thus, short term costs may accrue to the firm, but they may be able to reap long-term savings.

Any other reasons you can think of?

Yesterday, May 27, Clive Granger passed away at the age of 74.  Dr. Granger was one of the most-respected faculty members at UC-San Diego.  I frequently saw him around the Economics department even when he was in his 70s.

Dr. Granger won the Nobel prize in 2003 for is work on the econometrics of time-series data.  In 2005, Dr. Granger was knighted.  Over his entire career, Dr. Granger published 12 books and over 250 articles.

He will be missed.

• Econbrowser on Granger.
• Clive Granger’s Wikipedia profile.
• UCSD Clive Granger Obituary.

When beginning your research, here are the questions you need to ask yourself [from Mostly Harmless Econometrics]:

1. What is the causal relationship of interest?  What specific mechanism will cause a change in the dependent variable of interest?  Often one uses economic theory to predict these causal relationships.
2. What experiment could be used to capture the causal effect of interest?  Before you can decide on an identification technique, one must figure out what the ideal experiment would be.  If you want to estimate the effect of physician payment on surgery rates, would you randomize patients to different physicians?  Different physicians may select into different payment schemes.  Would you randomize physician payment?  In this case, different types of patients may select different doctors.  What would be the ideal?
3. What is your identification strategy?  Many medical studies use randomized control trials, but there are very few RCTs investigating economic phenomenon.  A researcher must decide how to eliminate problems of selection and endogeneity.  Common strategies include OLS, difference-in-difference, instrumental variables, and others.
4. What is your mode of statistical inference?  This is the nitty-gritty stuff.  How will you estimate your standard errors?  What variables do you include in your regression?   Is the sample representative?  What is the correct group to study.  In my paper on Marriage and Weight Gain, I limit the sample to individuals aged 18-55 since these are individuals most likely to be in the dating market.  

Yesterday, I attended a lecture by Peter Wagner about grant-writing.  The talk focused on grants in the sciences, and I will pass on Dr. Wagner’s advice to my loyal readers.

Three Golden Rules

• After writing each section of the grant, re-read it as if you were a reviewer.
• Finish the grant application at least 2 weeks before the due date.
• Put the grant away for at least 1 week. Then go back and re-read it.

Other helpful tips

• You proposal will be valuable if it is: 1) novel and can contributes significant knowledge to the field, 2) is technically feasibly and uses sound methodology, 3) can test your hypothesis as definitely as the state of the art permits.
• The abstract is the most important part of your grant application. Make sure it is concise and generates interest in your project even among those who are not specialists in your field. Be sure reviewers can easily answer the question “Who cares?” when reading over the grant application. Also, do not put any references in the abstract.
• For the sciences, the objective of your grant application should be the additional knowledge you wish to be gained from the study. The specific aims are the broad steps that need to be accomplished in order to accomplish your objective. For instance, if going to Seattle for a conferences is your goal, then the specific aims would be: book a flight, reserve a hotel room, register for the conference, etc.
• Dr. Wagner recommends that in the Methods section, the subheadings should relate to each specific aim.  For instance, “Experimental Design for Specific Aim 1.”
• Your literature review should be concise but also display that you have an understanding of the field.  Be sure to include all major papers in the field.  Also, include papers whose methodology you will use or will expand in your methodology.  If possible, check who will be on the reviewing committee.  If a reviewer has published papers that are relevant to your area of study, be sure to cite them in your grant application.
• Be sure to justify your budget.  Do not say “15% of Joe Blogg’s time is required therefore 15% of salary is requested.”  Instead, spell out in detail the time requirements including set-up, execution, data analysis and writing up the finished product.  Also, justify expenses for equipment, supplies and travel.  If you can’t answer the question “Why couldn’t you have done this for 80% of the budget you are proposing,” then you have not sufficiently justified your budget.

See also: Wagner (1991) “On writing a grant application. A personal view.” Physiologist. 1991 Apr;34(2):29-31.

An excerpt from a National Geographic article by Simon Worrall:

The world economy in the ninth century had two powerful engines. One was Tang dynasty China, an empire stretching from the South China Sea to the borders of Persia, with ports open to foreign traders from far and wide. The Tang welcomed diverse people to its capital, Changan, the site of modern-day Xian, and multiethnic groups lived side by side in a city of a million—a population unmatched by a Western city until London in the early 19th century. Then, as today, China was an economic powerhouse—and much of that power was built on trade.

The other economic engine was Baghdad, capital of the Abbasid dynasty from 762 onward. That dynasty inherited the Muslim world in the Middle East; by 750 it had spread as far as the Indus River to the east and Spain to the west, bringing with it trade, commerce, and the religion of Islam (the Prophet Muhammad himself had been a merchant).

Tang China was hungry for fine textiles, pearls, coral, and aromatic woods from Persia, East Africa, and India. In return, China traded paper, ink, and above all, silk. Silk, light and easily rolled up, could travel overland. But by the ninth century, ceramics from China had grown popular as well, and camels were not well suited for transporting crockery (think of those humps). So increasing quantities of the dishes and plates that held the meals of wealthy Persian Gulf merchants arrived by sea in Arab, Persian, and Indian ships.

Recently, I have seen a number of commercials promoting tourism to Jamaica.  Why are these commercials running?

Let us assume that these commercials convince 2% of vacationers to go to Jamaica.  If this is the case, it would make more sense to advertise during boom times; 2% of a large number of vacationers is a bigger number than 2% of the current small stock of vacationers.  On the other hand, it is possible that advertising is more effective now since the advertising budgets from other countries have been cut.  

A final possibility is that the Jamaica Tourism Board is not profit maximizing.  It may have a target tourism level.  Achieving the status quo tourism level may be more valuable to Jamaica in order to maintain a more stable level of tourism-related employment. Does this mean that the Jamaica Tourism Board is not a fiscally sound organization or that–like many government organizations–it is simply acting to smooth the booms and busts that results from normal swings in the world economy?

Marketplace discusses whether or not NIH funded studies should be make available for free.

• Duke University law professor James Boyle: “The Web works great for porn or for shoes, or for flirting on social networks. But it doesn’t work really well for science. We haven’t done for science what we did on the rest of the Web, which is basically to have this open Web with everything linked together.”
• Laura Jannek is a med student at Case Western: “I mean this is how capitalism works, right? The strong companies are the ones who can adapt to the changing environment, and you can’t prevent information technology from progressing as it is.”

Information is a public good. When research is funded by the government, the socially optimal solution is to make this information available for free to the public. Open access is the way to go.

How do you create a Markov Model for the effectiveness of pharmaceuticals?   Below is an example from Briggs, Claxton and Sculpher’s book titled “Decision Modelling for Health Economic Evaluation.”

Example

The main characteristic of a Markov Model is that it defines different states and then defines transition probabilties between each state.  Let us examine the case of someone with an HIV infection.  There are 4 possible states in this simplified model:

• State A: cd4 levels are between 200 and 400
• State B: cd4 levels are less than 200
• State C: The individual has AIDS
• State D: Death

Transition Probabilities

Now we must find a baseline transition probability matrix.  In this case, the baseline will be no treatment, but the baseline could also be one form of treatment to be compared to another.  This table gives the transition probabilities.  You can read the table as follows: A person in state A has a 72.1% chance of being in state A next period, a 20.2% chance of being in State B next period, a 6.7% chance of being in state C next period and a 1.0% chance of being in state D next period.

Now there is a drug treatment on the market which has a relative risk of 0.509.  This means that the chance of moving to a worse state has decreased by about half.  The book’s authors note that “Often it is assumed that baseline event probabilities should be as specific as possible to the location(s) and subgroup(s) of interest, but that the relative treatment effect is fixed.”

To get the new transition probabilties after treatment, we multiply the transition probabilities by 0.509 if the represent a worsening of the state.  The remaining ‘extra’ probability is moved to the probability of transitioning to the current state.  In this model, no one can transition to a better state (i.e., remission) so we do not have to worry about the relative risk of getting better.

Look at the first row of the transition probabilities matrix with the therapy.  State A transition probabilities to states B, C, and D are multiplied by 0.509 to get the new transition probabilities (i.e., .202*.509 = .103; .067*.509=.034;  0.010*.509 = .005).  The probability of staying in state A after treatment is just one minus the other probabilities (i.e., 1 – .103 – .034 – .004 = .858).

Survival

Now we want to find out how many people will survive.  We can do this with a simple simulation.  The baseline simulation is shown here and the simulation with the treatment is shown here.  To get the future probabilities, simply multiply the transition probabilities by the people in each state.  For instance, to find out how many people will be in state C in year 5, we need to look at year 4.  We know that of the people in state A, 0.067 will go to state C; Of the people in state B, .407 will go to state C; of the people in state C, 0.750 will state in state C, and of the people in state D, 0.000 move into state C.  Thus we calculate the number of people in state C in year 5 as: .27*.067+.23*.407+.34*.75+17*0 = 0.36.

We could also accomplish this with matrix algebra.  The vector of people in each state is equal to [1 0 0 0]*Tⁿ.  This means that in year 0, we have 100% of people in state A.  The transition matrix is represented by T and n is the number of years in the future we want to view.

In our analysis, we see that the baseline 20-year survival rate is only 3.2%, but with the treatment, this increases to 33.2%.

Cost

We can also determine the costs of the treatment and baseline.  The treatment has the added expense of purchasing the drug for $2278.  However, with the treatment fewer people are moving into the more expensive stages B and C.  Thus there is a tradeoff.

We can see from the simulation, that the treatment is more expensive than the baseline.  To calculate this, you simply multiply the proportion of people in each state by the cost in each state to get the cost per year.  It is also important to discount the costs to get the expenses in terms of net present value.  In this example, I used a 6% discount rate.

Markov with Memory

In general, Markov models are memoryless, meaning they do not care how long an individual has been in each state.  It is possible to create ‘memory’ using tunnel stages.  Let us examine the following example for disease X.  In this model there are 5 stages, 1 having the disease, 3 remission stages, and death.  An individual with disease X has a 60% chance of keeping the disease, a 20% chance of remission less than 1 year and a 20% chance of death.  Of course, they have a 0% chance of being in remission for 1-2 years or >2 years after only 1 period.  If a person does go into remission, we see that they have a 40% chance that the disease reoccurs, a 50% chance of getting to the remission for 1-2 years stage, and a 10% chance of death.  By making these stage related to time, we have created a Markov model that simulates memory.

Summary

With Markov modelling, we can estimate the effect a drug has, both in terms of its health implications–such as survival rates and the number of people in each stage–as well as its cost implications.  The key assumption is that the treatment effect is constant across all stages.

• Bank of America shareholders approved the purchase of Merrill Lynch on December 5, 2008.  
• Last year in the fourth quarter,  Merrill Lynch lost $15.84 billion.  
• Bank of America President Ken Lewis knew that Merrill was at risk of huge 4th quarter losses.
• Ken Lewis did not tell shareholders about Merrill’s impending large losses.  Why?

Under oath, Ken Lewis testified that “he believed Messrs. Paulson and Bernanke were instructing him to keep silent about deepening financial difficulties at Merrill, the struggling brokerage giant.”   

According to Lynn Turner, former chief accountant at the SEC, “If these allegations are proven true, both Bernanke and Paulson should be prosecuted by the SEC to the fullest extent of the law.”

Economists coercing business leaders to hide vital economic information…Say it ain’t so, Ben!

Clinical trials often examine the effectiveness of a treatment outside of real world contexts.  For instance, if a medicine is very effective, but has severe side effects, this likely will reduce adherence and can make the medicine less effective in the real world.  The Economics 2.0 book looks at when individuals are most satisfied with a colonoscopy:

“[An] experimental was conducted with colonoscopies at a time when sedation was not yet customary.  With half of the patients, the doctor left the instrument inside the colon at the end of the examination for one extra minute, without moving it.  This was unpleasant, but much less painful than the colonoscopy itself.  It turned out that patients who had this done to them later recalled the overall examination as less unpleasant than other test subjects who had the instrument removed earlier.  Also, they were more likely to show up for follow-up examinations.“

Here’s another excerpt from the Economics 2.0 book.

“Scientists Sara Solnick and David Hemenway…questioned students in what kind of world they would rather live–one where they earned $50,000 and everyone else half as much, or alternatively, $100,000 while everybody else would make twice as much.  The majority chose the first option, even though they would have cleared improved their lot by picking the second.”

• Norbert Häring and Olaf Storebeck (2009).  Economics 2.0: What the best minds in economics can teach you about business and life.  Palgrave MacMillan, New York, NY.
• Solnick, Sara and David Hemenway (1998). “Is More Always Better?: A Survey on Positional Concerns,” Journal of Economic Behavior and Organization, vol. 37, pp. 373-383.

Biofuels may not be all they are cracked up to be.  The Economist reports (“Biofools“) that biofuels may actually hurt the environment more than traditional energy sources.   

The International Council for Science (ICSU)…report concludes that, so far, the production of biofuels has aggravated rather than ameliorated global warming. In particular, it supports some controversial findings published in 2007 by Paul Crutzen of the Max Planck Institute for Chemistry in Mainz, Germany. Dr Crutzen concluded that most analyses had underestimated the importance to global warming of a gas called nitrous oxide (N2O) by a factor of between three and five. The amount of this gas released by farming biofuel crops such as maize and rape probably negates by itself any advantage offered by reduced emissions of CO2.

Although N2O is not common in the Earth’s atmosphere, it is a more potent greenhouse gas than CO2 and it hangs around longer. The upshot is that, over the course of a century, its ability to warm the planet is almost 300 times that of an equivalent mass of CO2. 

On my commute to campus this morning, I used the UCSD shuttle.  This shuttle service now uses buses fueled by biodiesel.  One drawback of using biodiesel, however, is that the engines are prone to overheat.  When today’s temperature hit 95 degrees in San Diego, sure enough the bus broke down and was not able to make the 25 minute journey to campus.  

Biofuels may not be the fuel of the future after all.

What is a convex set?  An object is convex if for every pair of points within the object, every point on the straight line segment that joins them is also within the object.  Mathematically, we can define a convex set as follows.

• C is a convex set if: αx+(1-α)y ∈ C, ∀ α ∈ [0,1], ∀ x,y ∈ C.

In other words, this means that if we connect any two elements in the set C with a straight line, all the points on the strait line must also be contained within the set.

Let us use an example of U.S. states.  We can consider a state a ‘convex state’ if we can drive in a strait line between any two places in the state and never leave the state.  Let us look at this map of Colorado.  Let us look at the two lines connecting Denver with Grand Junction and the other connecting Fort Collins with Colorado Springs.  We see that when we drive in a straight line between any two cities in Colorado, we will never leave the state.

On the other hand look at the following maps of Texas.  You can see that if we drive in a straight line from El Paso to Amarillo, we will pass through New Mexico.  Similarly, if we drive from New Orleans to Monroe, Louisiana, we will pass through Mississippi.  Thus, neither Texas nor Louisiana can be considered convex states.

According to Rasmussen Reports:

• 53% of American adults believe capitalism is better than socialism,
• 20% believe socialism is better, and
• 27% are undecided.

An NBER working paper by  Jonathan Guryan, Melissa Schettini Kearney (2009) gives strong evidence that gambling is addictive using a creative identification technique:

“We use the sale of a winning ticket in the zip code, the location of which is random conditional on sales, as an instrument for present consumption and test for a causal relationship between present and future consumption…Our data from the Texas State Lottery suggests that after 6 months, roughly half of the initial increase in lottery consumption is maintained. After 18 months, roughly 40 percent of the initial shock persists, though estimates become less precise. These estimates provide an upper bound on the degree of addictiveness in lottery gambling. They also highlight the potential effectiveness of innovations and advertising campaigns designed to increase lottery gambling.”

The authors wisely note that the welfare implications of their findings are ambiguous.  Is the increase in lottery sales due to increased addiction or learning-by-doing (i.e., it’s fun to play the lottery and I do it in moderation)?  If individuals become “…rational addicts in a Becker-Murphy sense, optimal provision and pricing would depend only on the external harm imposed, for example, on family members from the displaced consumption of other household goods.”

Further, government sponsored gambling is a way to raise money for public expenditures.  One must compare the deadweight loss from standard revenue raising measures (e.g., sales and income taxes) compared to lotteries.  I presume that the deadweight loss from raising revenue via the lottery is smaller than sales and income taxes in the absence of addictive gambling, but may be larger in the case where compulsive gambling becomes a widespread problem.

• Jonathan Guryan, Melissa Schettini Kearney (2009) “Is Lottery Gambling Addictive?” NBER WP # 14742.

Businessweek reports that the members of the G20 “…will pledge funds ‘more than doubling’ the amount the IMF initially sought to $750 billion.”  Bloomberg reports that “In the past six months, the fund has approved $16.4 billion for Ukraine, $15.7 billion for Hungary, $10.4 billion for Latvia, $2.5 billion for Belarus, $2.1 billion for Iceland, $7.6 billion for Pakistan and $516 million for Serbia.” 

One question is, what is the nature of a loan from the IMF?  It is not a contract between individuals or firms.  It is not a contract between governments and banks.  It is a contract between one government and another.  The politicians of developing countries are agreeing to pay back the loan in the future.  Unfortunately, while the promise of current politicians to pay back the loan may be made in good faith, this does not imply that future politicians will uphold their end of this bargain.  Future politicians in the developing world will claim that the West is imposing an undue burden upon them with these large loans.  Bono has been arguing for debt relief for developing countries for many years now. 

The book The Bubble that Broke the World chronicles the history of World War I reparations.  Germany could not afford to pay for reparations.  Germany then took out loans from the U.S. to pay for these reparations.  Germany then claimed that the reparations (and the loan) imposed too much of a burden and wanted to default.

We see that throughout history, loans between countries do not work out as intended.   There are better options than offering loans to these developing countries.  One option is that the developing countries could get loans directly from banks or issue bonds.  Although the foreign countries would pay higher rates then would be the case than if the loan was backed by the IMF, it would be free of the political taint of the burdonsome IMF loans.  With loans made from bankers, developed countries would have a responsibility to pay back the loan to creditors or else stigmatize their country to investors and thus face increased interest rates for many yeas to come.  

If the developed countries really want to help developing countries, they could just give them the money.  One should not think of loan as aid.  Bankers certainly do not.  

If the G20 wants to help developed nations, they should give them money.  If they would rather spend money on domestic issues, that is fine as well.  However, offering loans is a disingenuous way of ‘helping’ the developed world.

If you get sick and have a non-group health insurance plan, your premiums will increase.  When you think about it, this really doesn’t make much sense.  The concept of ‘health insurance’ is that it is supposed to protect your assets in the case where your health deteriorates.

John Cochrane proposes one solution: the creation of health status insurance.  ”If a health shock causes your medical-insurance premiums to rise, it pays a lump-sum payment sufficient to pay the higher medical-insurance premiums. (To deter fraud, the payment goes into a special account that can only be used for medical insurance premiums.)”

The N.Y. Times has an interesting profile of Freeman Dyson, a man who claims that global warning may not pose a grave risk to civilization.  Dyson agrees with the scientific consensus that:

• Rapidly rising carbon-dioxide levels in the atmosphere are caused by human activity,
• The world is getting warmer, also due to human activity
• Using coal to generate energy creates “real pollutants” like soot, sulphur and nitrogen oxides, “really nasty stuff that makes people sick and looks ugly.”

So why does Dyson believe that global warming is not a big deal?  First, there has been no overwhelming evidence that warming trends will adversely affect humans or the environment.  Al Gore’s film “An Inconvenient Truth” claims that polar bears will drown if the ice caps melt, but it is more likely that polar bears will be able to adapt to changing conditions over time.  A change in temperature will affect some species adversely, but it may be favorable to other species (such as humans).  Dyson claims that many Greenlanders enjoy a warming of the globe since they can grow cabbage in their own yards.   

Dyson also support energy produced by coal.  Although coal energy is dirty, is it cheap.  Cheap energy can help bring India, China and other countries in the developing world from poor nations to ones securely in the middle-class.  Dyson says, “By restricting CO2 you make life more expensive and hurt the poor. I’m concerned about the Chinese.  [The Chinese are] changing their standard of living the most, going from poor to middle class. To me that’s very precious.”

As an economist, I know that models that predict large scale effects using non-linear modeling can be highly unreliable. Dyson claims that standard climate models take into account atmospheric motion and water levels but have no feeling for the chemistry and biology of sky, soil and trees. This likely exaggerates the danger of global warming.  Thus, large scale anti-global warming interventions involve very large, up front costs in exchange for extremely uncertain benefits far into the future.  

This is not to say that we should ignore the environment.  Clean air and water very important and clearly affect a population’s health.  Further, as a resident of the smog-filled Southern California, I would certainly appreciate efforts to clean up the air.  I believe a carbon tax would be the best way to reduce pollution, but setting a goal of zero carbon emissions is not only unfeasible, it is counterproductive.  

Climate-change specialists often speak of global warming as a matter of moral conscience.  Don’t hurt “the environment.”   We need more science and less ideology when evaluating the effects (good and bad) of global warming.  

• “The key to change…is to let go of fear” – Roseanne Cash

In the run-up of real estate and stock market prices, demand for labor in the construction, real estate, finance industry was high.  With the drastic drop in real estate and stock market prices, the demand for loan officers, construction workers and investment bankers has dropped.  Individuals who have been laid must find a new job.  Those who are currently in dead-end jobs need to find positions in growing industries and cities.  For instance, a construction worker who used to build McMansions in the suburbs should be looking to move to new area where jobs are available working on government infrastructure projects.

Nevertheless, many employees in dead-end jobs may decide to try to keep these jobs.  Why?  One reason workers keep jobs they do not like is that they do not want to lose health insurance coverage for their family.  Moving to a new city can mean a temporary lapse of health insurance.  Further, new employers often do provide health insurance for a few months.  

The phenomenon that workers remain at sub-optimal jobs to maintain their health insurance is known as “job lock.”  I wrote a brief literature review about job lock 3 years ago.

A recent Economist article has revisited the problem of job lock as well:  

“…most Americans still get their health insurance from their jobs.  This makes it hard for anyone with a sick child to quit and start a new firm. It also makes it harder to switch jobs, despite a law helping employees to stay in company plans for 18 months after they leave. Scott Adams of the University of Wisconsin-Milwaukee found that married men with no alternative source of insurance were 22% less likely to switch jobs than those who, for example, could get covered by their wife’s employer.

Tying health care to a job can tie people to jobs they hate. Gerry Stover, who now runs a doctors’ group in West Virginia, recalls a time when his wife was pregnant and he couldn’t get health insurance at a private firm. He became a prison guard. As a public employee, his family was covered. But the job was neither pleasant nor a good use of his talents.”

While employer-provided health insurance is a good place to pool individuals of different health risks, tying health insurance to your employer may impede labor mobility and slow economic growth.

No matter the price, John Keesecker of Food and Water Watch argues that selling water for profit is a bad idea.

Keesecker: ”I think when folks see water being privatized, they see a price being put on something that’s essential.” - Marketplace.

Should water be free?  Water is a necessity.  Without it, you cannot live.  In an egalitarian society, is giving away water for free the best way to ensure that poor people receive the water they need to survive?

No.  Free water is a horrible idea.  Water is a scarce resource.  When water is free, individuals will not have an incentive to invest in water saving technologies.  For instance, if fixing a leaky pipe in your house costs $1000, you’re much more likely to pay to fix the leak if you also have to pay for the wasted water.  When water is free, you may put off fixing the pipe perhaps indefinitely.

If price of water rises and becomes unaffordable for some poor people, do we just leave them ‘out to dry’?  

If we want to redistribute money to the poor, giving cash transfers would be preferable to selling water at a 0 price.  With cash transfers, the poor could choose whether they wanted to spend their money on water or other necessities such as food and shelter.  If cash transfers are not feasible, a voucher program could be instituted.  Poor individuals already receive vouchers for food and a “water stamps” program could be similarly successful.  

A significant, positive price on water combined with some form of redistribution system should please most parties.  Environmentalists will be happy that a positive price on water will compel individuals and businesses to conserve water; social liberals will be happy that the poor will be able to purchase the water they need; and fiscal conservatives will be happy that the “water stamps” program will have a fixed budget as opposed to an open-ended program of handing out water for free.

The Wilson Quarterly looks at whether or not putting academic journals online is a good idea.  Although getting access to academic articles is easier than ever, scholars are concentrating their reading on a less diverse range of articles.

“As journals go online, researchers actually see less of their contents.  For every additional year of archives a journal makes electronically available at no charge, the number of distinct articles cited in other journals falls by 14 percent on average.”  On the other hand, “articles that are available for free are read much more frequently than those requiring a subscription.”

• “Virtually Invisible” Wilson Quarterly, Autumn 2008, pp. 76.

Penelope Trunk doesn’t believe in grad school.

• HT: Marginal Revolution.

The economic stimulus plan is looking to spend money on “shovel ready” infrastructure projects.  Even though stimulus bill funds have not yet been spent, fiscal policy has already generated increased economic activity in one sector: lobbying.

NPR’s Marketplace reports that Washington lobbyists earned a record-breaking $3.2 billion last year. Sheila Krumholz, Executive Director for the Center for Responsive Politics, states:

“There was this unique opportunity that government was handing out money and anytime that happens, companies will spend what they must to get in line to get a piece of the pie.“

Many politicians are proposing that a “Buy American” clause be included in the stimulus package.  This is bad idea.  Protecting American jobs from foreign may seem like a good idea to save jobs.  However, if  ”Buy American” bill is passed other countries will institute their own protectionist provisions.  In fact, Brazil may challenge the “Buy America” provision at the WTO.

The Washington Post reports, “Nations including China and many in Europe are preparing to spend billions of dollars of taxpayer money on stimulus projects. American companies are angling for a piece of those pies, and retaliatory measures against U.S. companies, executives argue, could significantly complicate those efforts.”

The Wilson Quarterly reviews a paper  by Erik Lindberg (2008) which seeks to answer the following question: why today is Hamburg an economic powerhouse of over 2 million whereas the smaller city of Lübeck only plays a much less significant role in the German economy .  In the 15th century, Hamburg and Lübeck were both prosperous German port cities of a similar size.  ”Lübeck connected to the Baltic Sea via the Trave River and Hamburg to the North Sea via the Elbe.  Their divergent fates illustrate the perils of extreme protectionism…In the face of increasing Baltic Sea competition from upstart traders from London and Amsterdam, Lübeck chose to protect its powerful landowners and leading merchant guild …Hamburg, by contrast, encourage trade with Dutch, Flemish, and English merchanges, and even a score of Portuguese Jews were invited to movie in.”

History reveals the perils of protectionism.  Further, even if the “Buy American” clause is intended to be temporary, political interest groups will have an incentive to lobby to make this protectionist philosophy stick in the long term.

Let us call on our politicians to reject the “Buy American” clause in order turn American cities and towns into Hamburgs, and not Lübecks.

Due to the poor economy and state budget deficit , the University of California will face a $450 million shortfall.

From Nobel Prize winner Friedrich A. Hayek’s “Pretence of Knowledge” Speech.

“Unlike the position that exists in the physical sciences, in economics and other disciplines that deal with essentially complex phenomena, the aspects of the events to be accounted for about which we can get quantitative data are necessarily limited and may not include the important ones. While in the physical sciences it is generally assumed, probably with good reason, that any important factor which determines the observed events will itself be directly observable and measurable, in the study of such complex phenomena as the market, which depend on the actions of many individuals, all the circumstances which will determine the outcome of a process, for reasons which I shall explain later, will hardly ever be fully known or measurable. And while in the physical sciences the investigator will be able to measure what, on the basis of a prima facie theory, he thinks important, in the social sciences often that is treated as important which happens to be accessible to measurement.“

I have been traveling a lot lately doing flyouts for job interviews.  I was at an airport recently and forgot to flush the toilet.  Usually this is not a problem, since most urinals at airports are automatic flush toilets.  However, in this case the toilet was not an automatic flush toilet.  This got me thinking about the economics of automatic toilet flushers.

On average, individuals will flush the toilet with some probability, p.  If a toilet has an automatic flush mechanism, then the toilet will flush with probability 1.  Of course, not all toilets are automatic flush toilets.  Thus, if f percent of toilets are automatic flush, the increase in the probability of flushing a toilet is f*(1-p).

Chart

In a partial equilibrium setting, marginal effect of adding an automatic flush toilet increases flushing rates by 1-p. 

• ∂[f+p(1-f)]/∂f = 1-p

So automatic flush toilets are a good thing right?  Probably, but maybe not as much as expected.  People may get used to having automatic flush toilets (as I did).  As the proportion of automatic flush toilets increases, this may decrease the probability that anyone flushes the toilet in the non-automatic setting since have become so  accustomed to having an toilet that flushes itself.

The probability of flushing a non-automatic toilet may depend on the proportion of toilets that are automatic flush.  In the general equilibrum, we can replace p, with p(f) where ∂p(f)/∂f<0). Now the impact of installing an automatic flush toilet is not as large. 

• ∂[f+p(f)(1-f)]/∂f = (1-p)+(1-f)p’ 

What this equation says is that installing an automatic flush toilet increases the chance that a specific toilet flushes, but decreases the probability an individual flushes a toilet in a non-automatic setting.

Who would have thought that airport toilets could be so interesting!

My paper titled “Why Does Getting Married Make You Fat? Incentives and Appearance Maintenance” was just accepted for presenatation at the Western Economic Association International (WEAI) conference.  This paper is co-authored with Uri Gneezy.  The conference will take place June 29-July 3, 2009 in Vancouver, Canada.

Be it rent or mortgage payments, paying for shelter is the largest after-tax expense for most people.  Differences in housing prices can greatly affect your purchasing power.  If you earn $50,000 in Wausau, Wisconsin, you will be able to afford a much larger house than if you lived in San Francisco.   Of course, living in San Francisco offers more job opportunities and amenitities than does Wausau.  

What is the price of a typical house in your metro area?  This chart reveals the median home price for 158 metro areas.  The prices are divided up between single family homes (SFH) and condominiums.  

Which cities have the most expensive median home prices?  Below are my rankings:

• Ranking: Median Single Family Home Prices.
• Ranking: Median Condominium Prices.

The most expensive metro areas to buy a home or condo are: San Francisco; Los Angeles; San Diego; New York; Washington, D.C.; Boston; Seattle; Boulder, CO; Miami.

The New York Times also has a nice graphic that better incorporates the recent downturn in housing prices, but is only available for select markets.  The data is derived from the Case-Shiller home price index.

Data Source:

• National Associations of Realtors.

The Wall Street Journal reports that the tough economic times has lead to a decline in demand for new Economics Ph.D. students.  As someone who is ‘on the job market’ this year, I certainly agree that it has been a tough year.  Many universities who placed job advertisements to hire new Ph.D. Economists have since withdrawn the post due to budgetary considerations.  Just as the WSJ states, the experience of my peers at UCSD has been that “…even qualified candidates went through just a fraction of the usual number of interviews this year, and some schools have canceled flyouts.”

The Economist magazine has a listing of the eight up-and-coming economists.  Below is a list of their names and some commentary if applicable.

• Amy Finkelstein.  Dr. Finkelstein researches in the public and health economics fields.  I have featured here work multiple times on this blog (see here, here, here, here and here).
• Jesse Shapiro.  I met Dr. Shapiro at an IHS conference last spring and have been very impressed with his work.  Some of Dr. Shapiro’s research findings include: harsher jail conditions do nothing to deter prisoners from reoffending and that preschoolers who watch television do better academically than children who don’t.
• Esther Duflo.  Dr. Duflo is a well known development economist whose work involves randomized interventions. For instance, she found that giving away 1 kg of daal (lentils) when parents take their kids to be immunized greatly improved immunization rates compared to the control group not given the daal.
• Roland Fryer – Social Economics, the Economics of Affirmative Action/Racism.
• Raj Chetty – Public Economics, Taxation.
• Iván Werning – Macroeconomics.
• Xavier Gabaix – Behavioral Economics, Asset pricing.
• Marc Melitz – Trade Economics.

” A substantial short-term rise in spending on defense and intelligence would both stimulate our economy and strengthen our nation’s security.” – Martin Feldstein in WSJ.

Robert Higgs disagrees.

“…be fearful when others are greedy and greedy only when others are fearful.”

• Warren Buffet

Economists have generally found that rich people are happier.  People who are wealthy are likely to be happier than those who have trouble affording food, clothes, or shelter.  What is driving this happiness differential?  Is the additional happiness from additional wealth due to the fact that you can more easily fulfill basic needs, or is it because people with fancier cars and more iPhones are actually happier?

A paper by  Di Tella and MacCulloch (2008) examines what happens to individuals in developed countries when they become wealthier.  They find that increased wealth does increase happiness, but only temporarily.

“We find evidence that for wealthy Germans, and for the rich half of European nations, higher levels of per capita income don’t buy greater happiness. The reason appears to be adaptation. However even for the rich half of European nations such habituation may take over 5 years so the happiness gains that they experience, whilst not permanent, can still be relatively long-lasting. Finally we study a cross section of nations in 2005 from the World Gallup Poll and find that the past 45 years of economic growth (from 1960-2005) in the rich half of nations has not brought happiness gains above those that were already in place once the 1960s standard of living had been achieved. However in the poorest half of nations we cannot reject the null hypothesis that the happiness gains they have experienced from the past 45 years of growth have been the same as the gains that they experienced from growth prior to the 1960s. ”

As Thomas Jefferson once said: “It is neither wealth nor splendor, but tranquillity and occupation, which give happiness.”

• Rafael Di Tella, Robert MacCulloch (2008) “Happiness Adaptation to Income beyond ‘Basic Needs,’” NBER Working Paper No. 14539.

Many pundits are calling for Barack Obama to fund massive infrastructure projects.  UC-San Diego economist Jim Hamilton of  believes that increased block grants to states will not only stimulate the economy, but also permit states the flexibility they need to spend these fund efficiently.

To stimulate the economy, expand government health insurance.

To stimulate the economy, defeat government health insurance expansions.

“When goods do not cross borders, soldiers will.”

• Frédéric Bastiat

Bernard Madoff operated one of the biggest Ponzi schemes in history.  He has not only defrauded rich investors, but charities and university endowments as well.  If smart, Wall-street types were fooled by Madoff, can you realistic expect to avoid these Ponzi schemes?  It may surprise you but the answer is YES.

If you are a loyal reader of this blog, you know that I am a huge advocate of index fund investing (see these posts).  I have tauted the low expense ratios and diversification benefits of index funds.  Now, there is one additional benefit: transparency.

If you invest in an S&P 500 Index Fund at Vanguard, you are fairly certain that the fund’s performance will track very closely (within 1-2 percentage points) of the underlying index.  If you see the S&P 500 drop 30% in a year, and your stock broker claims that you have made a 10% positive return, you know to be suspect.  Similarly, if you buy a small cap index fund and small caps rose by 20%, but your fund only went up by 5%, you should be suspect of the returns as well.

Thus, by investing in index funds, you can validate whether or not your returns seem reasonable by comparing them to the underlying benchmark indices.

“Adequate credit is to trade what altitude is to aircraft; without it, the odds of coming to grief over preilous commercial terrain are great.  All merchant enterprises sooner or later lose cargoes or encounter soft markets.  Without ample capital reserves and the ability to borrow at low rates of interest, bankruptcy is inevitable.”

~ William Bernstein (2008) on the importance of credit to the East India Company, in A Splendid Exchange.

Does better screening lead to improvements in health outcomes?  Conventional wisdom holds that this is always true.  For instance, catching breast cancer at an early stage greatly improves survival probabilities.  However, early screening can lead to a statistical anomaly where better screening appears to improve mortality rates even when treatments are entirely ineffective.

Here is an example using the dreaded disease economicitis.  Let us divide people into 3 groups.

• Healthy: You live forever.
• 1st stage economicitis is asymptomatic. Life expectancy when 1st stage economicitis begins is 10 years.  One half of economicisits cases are 1st stage.
• 2nd stage economicitis appears when individuals mysteriously grow a third or possibly fourth hand.  Life expectancy with second stage economicitis is 2 years.  One half of economicitis cases are 2nd stage.

Before any screening was developed, individuals would learn they had  economicitis  when they started growing extra hands.  Thus, documented life expectancy for those with  economicitis was 2 years, since all individuals who were recorded as having  economicitis were in the 2nd stage.

Let us assume that a screening technique is now available.  If the screening device is able to detect 100% of stage 1 and stage 2 economicitis cases, then we will see that life expectancy will increased to 6 years (10/2+2/2=6). Statisticians looking at the data may claim the following: “The economicitis screening test has increased life expectancy after diagnosis from 2 to 6 years!”

This claim, however, is false since there is no effective treatment for  economicitis.  The increase in average life expectancy is not due to any improvement in health care, but only because the relatively healthier individuals with 1st stage economicitis are now being detected by the test.

Merrill Goozer reports that “While the rest of the economy was shedding nearly 600,000 jobs and the nation’s once-proud automobile industry went begging for a bailout,” the health care sector actually added 52,100 jobs last month.

The S&P 500 is down 41% compared to last year.  The unemployment rate in the U.S. is now at 6.7%.  Large financial institutions are failing and droves of homeowners are defaulting on their mortgages.  Is it time to give up on capitalism?

Before we hand over the keys to the economy to President-elect Barack Obama, we should first heed this sage advice from Milton Friedman (video).

As Health Access California reminds us, tough economic times are often when sweeping government policies are enacted.    President-elect Obama has some tough choices to make.  Should he expand existing government programs to help those who are hurt by the economic crisis?  Or should he scale back these government programs to show some fiscal responsibility?  Or is starting a universal health insurance plan a good idea?

A NEJM editorial states that “The expansion of health care to large populations is expensive, and presidents may need to quiet their inner economists.”  If policymakers quiet their inner economist, not only will I be out of a job, but health care will get a lot more expensive.  Joe Paduda agrees that a focus on cost-effective medical care is paramount.  Paduda claims that not focusing on cost has made Medicare Part D ‘a disaster.’

“On a national scale, the program is a disaster. The ultimate liability for Part D is $8 trillion, a liability that is unfunded. This is what we can expect if Congress passes and President Obama signs into law national health reform that does not aggressively, and forcefully, address cost – a deficit explosion that will make the cost of the current bailouts look like lunch money.”

What does the Healthcare Economist recommend?  Listen to your inner economist!

The Chronicle of Higher Education has data on 2007-2008 salaries for professors at various ranks (Assistant, Associate, Full Professor) in various departments.  

• AVERAGE FACULTY SALARIES BY FIELD AND RANK AT 4-YEAR COLLEGES AND UNIVERSITIES, 2007-8.

Professors teaching Law, Business or Engineer were among the highest paid.”Among new assistant professors, those in business had the highest average salary, at $86,640. The three disciplines with the lowest average salaries for full professors were English, visual and performing arts, and parks, recreation, leisure, and fitness studies, the survey found.”

Salaries also varied by the type of institution.  Professors at Doctoral Institutions made the most, followed by Master’s Institutions.  Professor teaching at two-year colleges had the lowest salaries.

• What Professors Earn.

Randall Parker of East Carolina University has a detailed overview of how the Great Depression unfolded.

• HT: Marginal Revolution.

I am currently on the “Job Market.”  I will receive my Ph.D from UC-San Diego this spring and hope to have a job for next fall.  There are lots of advice papers on what graduate students should do to maximize their chances of getting a job.  Yet few graduate students ever learn what the labor demanders want.  What are universities thinking during the hiring process?

A paper by Jessica Holmes and David Colander examines this question.  They review their experience trying to hire a faculty member at Middlebury College in Vermont.  The complete article is available here.

In “Too Small to Fail, ” The Washington Monthly writes on the success of conservatively-managed small banks in the midst of the financial market collapse. 

Why are small banks succeeding?  First, they are running their business more conservatively; in the tradition of, well, traditional bankers.  Secondly, they develop personal relationships with customers giving them superior information about their customers credit worthiness.   Ben Bernanke terms this being rich in “informational capital.”  Of special note is the following quotation:

“According to FDIC data, the failure rate among big banks (those with assets of $1 billion or more) is seven times greater than among small banks.”

It’s time to raise the gas tax.  An economist proposing a tax increase?  Yes.

Increasing taxes overall is rarely beneficial for the economy, but raising the gas tax will increase the welfare of the country.  In earlier posts, I wrote that a higher gas tax makes a lot of sense.  An increased gas tax will reduce driving which will have two beneficial effects: less traffic and less pollution. One could use the added funds from the gas tax to improve public transportation, improve infrastructure, or reduce taxes on income or other goods.

Why is now the time to raise the gas tax?  

1. When gas prices were over $4 per gallon, raising the gas tax was politically infeasible.  Now, however, with the price of gas under $2.50 in San Diego, a gas tax increase of 50 cents per gallon would still keep gas prices under $3 (which doesn’t sound too bad anymore). 
2. Furthermore, the government is looking for new revenue sources to plug its huge deficit and the gas tax is one solution.  
3. Finally, since the elections have just taken place, politicians have some measure of job security at least for a few years.  With this added job security, Congressmen and Congresswomen can increase the gas tax without having to worry about pandering to voters. 

Wayne State University’s Economics Department has a nice webpage with links to helpful economic information.  This includes:

• List of Economics Journals
• Government Economic Information websites
• A list of think tanks
• Information on Financial Markets.

Narrow-mindedness is one of the flaws of human cognition.  Often times, perceived conflicts of interests or bias may just be due to narrow-minded thought.

For instance, George Bush decided to invade Iraq.  While I do not want to argue the merits or demerits of the invasion, likely one of the reasons Bush decided to invade the country was because he wanted the U.S. to have a steady supply of oil.  Is oil that important?  From Bush’s point of view, it likely is.  He formed Arbusto Energy, an oil company and much of his family was involved in the oil industry.

What about Henry Paulson?  He decided a Wall Street bailout (e.g., Bear Sterns, AIG) was the best way revive the economy.  Is this because he is corrupt and a Wall Street crony?  Likely no.  However, he did work at Goldman Sachs for many years.  Thus, he likely overestimates the importance of Wall Street in the economy because that is where he built his career.  Paulson has many friends in Wall Street who informed him of their problems.  Paulson, likely has less friends in the trucking industry–who is also suffering from a stagnating economy and high gas prices–so he knows less about the trucking industry’s problems.

How do we solve the health care crisis?  The Healthcare Economist received his training in economics and you may notice that he often uses an economic framework to analyze issues.  Is economics always the right framework?  Likely no.

These three examples are derivatives of the problem of availability bias.  Individuals base their decisions on the information available to them.  However, the information available to any one person does not give the whole picture.  This leads to the quotation in the title of this blog post.  How do we fix the problem of availability bias?  Salon.com gives some instruction:

“You know the joke that economists like to tell each other about the drunk looking for his keys under the streetlight, not because that’s where he lost them, but because that’s where the light is? That’s just the way life is — you use the tools that you’ve got to examine the problems that you’ve got, whether they are big problems or small ones. What really makes economics move forward is when somebody learns how to build a new streetlight, or a portable streetlight, or an infrared streetlight…”

Learn to use your own infrared streetlight.

The UC San Diego Department of Economics has posted this year’s list of Job Market Candidates.  Included in the list is your favorite healthcare economist, Jason Shafrin.

The New York Times has an revealing article on Henry Cisneros.  Mr. Cisneros was the U.S. Secretary of Housing and Urban Development (HUD) under President Clinton.  In an attempt to expand home ownership rates, especially among low-income households, Mr. Cisneros loosened mortgage restrictions.  ” Families no longer had to prove they had five years of stable income; three years sufficed…lenders were allowed to hire their own appraisers rather than rely on a government-selected panel.”

The article portrays the fallout from HUD reforms under Cisneros.  Lago Vista is a Cisneros development in San Antonio and was supposed to be a beacon of hope for low income households.  Now, “scores of homes have been foreclosed, including one in five over the last six years on the community’s longest street, Sunbend Falls, according to property records.”

Conflicts of Interest

Mr. Cisneros later capitalized on his experience at HUD. “[H]e joined the boards of a major builder, KB Home, and the largest mortgage lender in the nation, Countrywide Financial — two companies that rode the housing boom, drawing criticism along the way for abusive business practices.”  Later, Mr. Cisneros became a developer himself and built up the now impoverished Lago Vista development.

Government intervention towards the noble goal of increased home-ownership rates for the poor, has had the unintended consequence of exacerbating the housing crisis.

In recent years, economists have examined the phenomenon of offshoring.  Offshorable service jobs are characterized by a number of factors.   Jensen and Kletzer note that offshorable jobs have little face-to-face customer contact and work processes that can be monitored via the internet.  Thus, data entry is easily offshorable whereas barbershop services are not.

A paper by Alan Blinder reveals a troubling observation: economists are easily offshorable!  The occupation of “Economist” had an offshoreablitily index of 89%.  This ranks economists as the 37th most offshorable profession of the 291 occupations studied.  A presentation by Lori Kletzer at the UC Labor Economics workshop claimed that economists are the 15th most offshorable profession of the 457.

Why are economists so offshorable?  Economists write frequently, conduct data analysis and think a lot.  All of these tasks can be done anywhere in the world (assuming you have a laptop and an internet connection).  Looks like American economists aren’t indispensible after all.

Today I attended a seminar by Eli Berman on his paper, “Can Hearts and Minds Be Bought? The Economics of Counterinsurgency in Iraq.“  He noted that the U. S. Military often employs pediatricians to collect information.  When, the military pays for a pediatrician to serve an Iraqi community., not only does this engender good will from the local Iraqi population, but soldiers mill around the pediatrician’s waiting room.  After conversing with some of the parents, many Iraqis share intelligence about the identity or location of rebel insurgents. In rural areas, a similar technique works with veterinarians.

While your wallet may be a little lighter and your 401(k) may have taken a beating, the economic downturn may actually improve your health.

The N.Y. Times reports that “people tend not to take care of themselves in boom times — drinking too much (especially before driving), dining on fat-laden restaurant meals and skipping exercise and doctors’ appointments because of work-related time commitments.”

When the economy slows, individuals don’t work as hard which reduces stress.  Also, people have more time to spend with their family.  Economic slowdowns often mean less driving, which will significantly reduce the number of motor vehicle accidents.  I have also read some paper where economic slowdowns reduce pollution and thus decrease mortality rates.

“In May 2000, the Quarterly Journal of Economics published a surprising paper called “Are Recessions Good for Your Health?” by Christopher J. Ruhm…Dr. Ruhm found that death rates declined sharply in the 1974 and 1982 recessions, and increased in the economic recovery of the 1980s. An increase of one percentage point in state unemployment rates correlated with a 0.5 percentage point decline in the death rate — or about 5 fewer deaths per 100,000 people.”

One clear caveat must be noted however.  While cyclical downturns may be good for an individual’s health, “It’s clear that long-term economic gains lead to improvements in a population’s overall health.”

The Economist magazine took a poll of academic economists working at NBER to see who they would vote for.  Barack Obama came out as the favorite.  Even though 46% of academic economists list themselves as Democrats compared to only 10% who claim to be Republican, Obama came out overwhelmingly ahead.

Seventy percent of economists would rather work for Obama than McCain (compared to 10% for McCain).  Eighty percent of economists believe Obama has a better economic team.

“John McCain has professed disdain for ‘so-called economists’, and for some the feeling has become mutual,” says Erik Brynjolfsson, a professor at the Massachusetts Institute of Technology Sloan School of Management.

• Note: The Healthcare Economist website has not endoresed either candidate

President Bush’s speech tonight urged Americans to side with the Bush-Bernanke-Paulson worldview that a bailout is the only option.  Is it the only option?

Luigi Zingales believes Henry Paulson’s decision to bail out Wall Street is a mistake.  Most economists agree that the government won’t get a “deal” when negotiating the price of risky assets.

“In a negotiation between a government official and banker with a bonus at risk, who will have more clout in determining the price?  The Paulson RTC will buy toxic assets at inflated prices thereby creating a charitable institution that provides welfare to the rich–at the taxpayers expense.”  

Zingales continues: “Do we want to live in a system where profits are private, but losses are socialized?”

On Monday and Tuesday I will be attending the All-UC Labor Economics Workshop at UCLA.  I will be presenting a poster from my job market paper: “Operating on Commission: How physician financial incentives affect surgery rates.”

In an attempt to stabilize the economy, the U.S. government has taken some significant actions.  Let’s recount.  The government has taken over Fannie Mae and Freddie Mac.  Combined assets: $5 trillion.  The government has “rescued” Bear Stearns by backstopping questionable assets valued at $29 billion.  The government has given a loan to AIG for $85 billion.  Further, Lehman Brothers–a firm with $600 billion of assets–is bankrupt.  The SEC has banned short selling on 800 financial stocks.

Are these government actions warranted?  Looking just at the stock market, we see that despite the doom and gloom, the S&P 500 is down less than 1% over the past month and the Dow is actually up 0.4%. [Although year to date, both are down around 15%].  Conservatives claim that the stock market’s resiliency is a sign that the government does not need to bail out these firms.  Liberals believe that bailouts caused the market recovery.  Was the bail-out needed?

The Economist writes that “Officials worried that the collapse of AIG, with its $1 trillion balance sheet and operations in 130 countries, could send the financial system into a tailspin.”  On the other hand, Joseph Stiglitz claims that the bail-outs amount to corporate welfare: “It’s one thing for, to have some safety net for very poor people. It’s a different thing to have safety net for some of the biggest corporations in America.”  Menzie Chinn notes that these bailouts certainly will do nothing to help the U.S. government pay off their debt.  

Who is to blame for this mess?  Maybe Alan Greenspan:

Edward M. Gramlich, a Federal Reserve governor who died in September, warned nearly seven years ago that a fast-growing new breed of lenders was luring many people into risky mortgages they could not afford.

But when Mr. Gramlich privately urged Fed examiners to investigate mortgage lenders affiliated with national banks, he was rebuffed by Alan Greenspan, the Fed chairman.

A more important question is what should be done now.  If we wish to have a more deregulated financial sector, this will likely lead to higher average economic growth accompanied by a higher probability of financial crisis.  If we wish to live in a less regulated world, investors must face the consequences of their asset allocation decisions.  More regulation may slow economic growth over the long run, but–if the regulation is effective and wisely implemented–will reduce the probability of financial crisis.  If the federal government is liable to bail out failing financial institutions, regulations must be tighter; otherwise financial institutions will suffer from moral hazard and invest in overly risky asset.  

Now we are in the worst of both worlds.  Government regulation was lax, but instead of letting investors eat their losses, the government is bailing them out.  

What would happen if we did not bail out Fannie, Freddie, Bear Sterns and AIG?  The truth is, no one knows.  Financial markets could have stabilized; or financial markets could have gone into a tailspin.  The one thing we do know:  Joe Taxpayer has a large bill coming in the mail.

John Cochrane gives writing tips for Ph.D. students.  One of the key insights it the following:

“Many economists falsely think of themselves as scientists who just “write up” research. We are not; we are primarily writers. Economics and finance papers are essays. Most good economists spend at least 50% of the time they put into any project on writing. For me, it’s more like 80%.”

Below are some other highlights from this paper.

• “Figure out the one central and novel contribution of your paper.  Write this down in one paragraph.”
• “A good paper is not a travelogue of your search process.”
• “The main point of the literature review should be to set your paper off against the 2 or 3 closest current papers, and to give proper credit to people who deserve priority for things that might otherwise seem new in your paper.”
• In the body of the paper, your task is to get to the central result as fast as possible.
• “There should be nothing before the main result that a reader does not need to know in order to understand the main result.”
• “…the theory must be the minimum required for the reader to understand the empirical results.”
• “As you edit the paper ask yourself constantly, ‘can I make the same point in less space?’ and ‘Do I really have to say this?’”
• “Follow the rule ‘first describe what you do, then explain it, compare it to alternatives, and compare it to others’ procedures’ at the micro level as well as the macro level. For example, in describing a data transformation, just start with, say, ‘I adjust income by the square root of household size’. Then tell us why adjusting is important, and then talk about different adjustment functions. Most writers do all this in the reverse order.”
• “Simple is better.”
• “Don’t use footnotes for parenthetical comments.”
• “The caption of a regression table should have the regression equation and the name of the variables, especially the left hand variable.”
• “Good figures really make a paper come alive, and they communicate patterns in the data
  much better than big tables of numbers.”
• “Much bad writing comes down to trying to avoid responsibility for what you’re saying.”
• “Clothe the naked ‘this.’ ‘This shows that markets really are irrational…’ This what?”

What are the three most important things for empirical work?  Identification, Identification, Identification. Cochrane also has a list of tips for explaining your empirical work.

1. What economic mechanism causes dispersion in the right hand variables?
2. What economic mechanism constitutes the error term?
3. Explain why you think the error term is uncorrelated with the right hand variables in economic terms.
4. Describe the source of variation in the data that drives your estimates, for every single number you present. For example, the underlying facts will be quite different as you add fixed effects. With firm fixed effects, the regression coefficient is driven by how the variation over time within each firm. Without firm fixed effects, the coefficient is (mostly) driven by variation across firms at a moment in time.
5. Think of reverse causality stories.
6. Consider carefully what controls should and should not be in the regression. Most papers have far too many right hand variables. You do not want to include all the “determinants” of y on the right hand side.

• High R² is usually bad — it means you ran left shoes = α+β right shoes +γprice.  Right shoes should not be a control!
• Don’t run a regression like wage = a + b education + c industry + error. Of course, adding industry helps raise the R², and industry is an important other determinant of wage (it was in the error term if you did #2). But the whole point of getting an education is to help people move to better industries, not to move from assistant burger-flipper to chief burger-flipper.

Cochrane, John H. “Writing Tips for Ph.D. Students.”

Soldiers have their gun, musicians their instrument and economists their pen.  Deft writing can elucidate the most esoteric economic ideas; poor writing is boring and impenetrable. Although few realize it, writing is the economist’s trade.

Deirdre McClosky’s Economical Writing is an entertaining, practical guide for any social scientist.  Below is a list of some the book’s quotable insights.

• “The big secret in economics is that good writing pays well and bad writing pays poorly.”
• “Poincaré’s good French and Einstein’s good German early in the twentieth century were no small contributors to their influence on mathematics and physics.”
• “The reader like the consumer is sovereign.”
• “The teachable trick is getting a first draft. Don’t wait until the research is done to begin writing because writing, to repeat, is a way of thinking.”
• “If you change the typeface of your draft, you will see it in a new light.”
• Read your work out loud.
• “At the end of a session, or at any substantial break, always write down your thoughts, however vague, on what will come next.”
• “A writer must entertain if she is to be read.”
• “Use titles for diagrams that state their theme, such as ‘All conferences should happen in the Midwest’ instead of ‘A Model of Transport Costs.’”
• “Footnotes should guide a reader to sources.  That’s all.”
• “English achieves coherence by repetition, not by signal.  Repeat and your paragraphs will cohere.”
• “What is written without effort is generally read without pleasure” – Dr. Samuel Johnson
• “…the object is not to write so the reader can understand but so that she cannot possibly misunderstand.”
• “Weak writers these days use too many commas.”
• “In revision the trick is to delete most commas before ‘the’…”
• “The most important rule of rearrangement is that the end of the sentence is the place of emphasis.”
• “The imperative is a good substitute for the passive, especially for taking a reader through mathematical arguments: ‘then divide both sides by x’ instead of ‘both sides are then divided by x.’”
• “…Be concrete.  A singular word is more concrete than a plural (compare ‘Singular words are more concrete than plurals.”
• “The rule is to query every ‘this’ or ‘these.’  Take most of these out.”
• “Be clear.”

I highly recommend this book to any social scientist.

• McCloskey, Deirdre N, 2nd ed. (2000) Economical Writing, Waveland Press Inc., Long Grove, IL, 98 pages.

The Healthcare Economist, Jason Shafrin, has a new homepage available at jasonshafrin.com.  The homepage has links to my recent drafts of my research and a brief bio.  Blog posting will continue on this site.

Should the Treasury bail out Fannie and Freddie?  A recent Economist article gives a level-headed solution: nationalize and then dismantle them.

Most libertarians would say that Fannie and Freddie should fail.  Having these two giant players collapse, however, add dynamite to an already explosive mortgage finance market.  Thus, the short term solution must be to bail out these two entities and nationalize the assets.  Sending Fannie and Freddie a financial lifeline to benefit private shareholders, however, does not make sense and is not fair to taxpayers.  In the words to the Economist, “That is capitalism at its worst: it means shareholders and executives reap the profits, but the taxpayer bears the losses.”

In the long term, a housing market without Fannie or Freddie is likely in the U.S.’s best interest.  Taxpayers won’t be on the hook to bail out private shareholders and the mortgage finance market will likely be more competitive.

“The two Leviathans have squeezed private firms into the riskiest ends of the mortgage market, such as subprime lending. They have not brought sharply lower mortgage rates to America.  Europe, where mortgage markets are fully private, is no worse-off.”

Thus, I whole-heartedly agree with the Economist’s prescription: nationalization and dismantlement is the the best route.

Justin Wolfers writes in the Freakonomics blog that economists should limit their objections during academic seminars to a list of comments to make discussions of research papers more efficient. Here are some of my favorite:

• Adam Smith said that.
• Unfortunately, there is an identification problem which is not dealt with adequately in the paper.
• The residuals are clearly non-normal, and the specification of the model is incorrect.
• Have you tried two-stage least squares?
• The conclusions change if you introduce uncertainty.
• I proved the main results in a paper published years ago.
• The market cannot, of course, deal satisfactorily with that externality.
• But what if transaction costs are not zero?
• What empirical finding would contradict your theory?
• What happens when you extend the analysis to the later (or earlier) period?
• That is alright in theory, but it doesn’t work out in practice.
• The problem cannot be dealt with by partial equilibrium methods; it requires a general equilibrium formulation.
• Is there a weak instruments problem?
• The conclusion rests on the assumption of fixed tastes, but (of course) tastes have surely changed.
• The trouble with the present situation is that the property rights have not been fully assigned.
• How did you handle endogeneity problem?

This list is likely only entertaining for academic economics. Wolfers wonders if the economics fields ability to characterize objections to research paper with such a list may suggest “…a methodological narrowness to neoclassical economics. But equally, it is the clarity of the framework that gives economic analysis its power.”

The U.S. is in a huge amount of debt. This will only worsen in the short- to medium-term as the the baby boomers retire and Medicare and Social Security budgets balloon. Here’s a movie about it.

• “This country has started consuming more than it produces.” – Warren Buffet

Income inequality has generally increased since the 1970s. Even for researchers who find that income inequality has Does this mean that happiness inequality has also increased? An NBER working paper by Betsey Stevenson and Justin Wolfers claims that this is not the case. Below is the a portion of the abstract.

While there has been no increase in aggregate happiness, inequality in happiness has fallen substantially since the 1970s. There have been large changes in the level of happiness across groups: Two-thirds of the black-white happiness gap has been eroded, and the gender happiness gap has disappeared entirely. Paralleling changes in the income distribution, differences in happiness by education have widened substantially…Juxtaposing these changes with large rises in income inequality suggests an important role for non-pecuniary factors in shaping the well-being distribution.

• Betsey Stevenson, Justin Wolfers (2008) “Happiness Inequality in the United States” NBER Working Paper No. 14220.
• Richard V. Burkhauser, Shuaizhang Feng, Stephen P. Jenkins, Jeff Larrimore (2008) “Estimating Trends in US Income Inequality Using the Current Population Survey: The Importance of Controlling for Censoring” NBER WP #14247.

Economists often state that uninsured individuals do not “want” health insurance. Joe Paduda claims that this is not the case; most uninsured do want health insurance. Mr. Paduda cites a Washington Post, Kaiser Family Foundation and Harvard University survey which shows that “when asked why they don’t participate in their employer’s program, 1% of survey respondents said it was because didn’t think they needed insurance.” Most people decide to not to purchase health insurance–not because they do not want it–because they can not afford it.

This is where economic terminology can create confusion and also clarify the situation. Let me give you an example of what “want” means to an economist.

I want an Audi R8. However, the cost of this car starts at $112,500. Thus, I prefer to drive a 2003 Toyota Matrix and have some money left over to buy food, pay for rent, etc. Although I do “want” the sports car, I want more to not owe a huge amount of debt and instead be able to afford for other goods that I desire.

Similarly, for economists, if an individual is uninsured, it must be the case that this is because they prefer this situation. This may seem like a tautology, but what it means is that an individual who is uninsured would rather be uninsured than pay $12,100 and be insured. The $12,100 that would have gone to health insurance, can be used for food, rent, etc. Further, if you are young and healthy, the probability that you will become sick is probably fairly small compared to the average insured individual and thus you will be paying more for insurance than the expected value of your medical costs.

Those who argue that all individuals should have health insurance can argue this based on equity goals. However, in order to make health insurance more attractive, one must either 1) lower the price of health insurance, or 2) increase the after-tax incomes of low income workers. The first can be done with more flexible insurance arrangements, offering more basic health insurance coverage, improving the efficiency of the health care sector and by man other means. The second means to increasing insurance can be accomplished by either increased economic growth or a more redistributive tax policy.

Nevertheless, nothing in this world is free (especially health care). Everyone would want health insurance if it were free; but because it is so expensive, other wants come to be more important than health insurance and thus individuals become uninsured.

A recent study found that the average professor is subsidized $10,554 at University of New Mexico’s Gallup campus.  The “subsidy” is the average professor salary less the amount of revenue he/she generates from grants and teaching classes.  The full article is available here.

• HT: Marginal Revolution

EconBrowser discusses a paper by Claessens, Kose and Terrones, entitled “What Happens During Recessions, Crunches and Busts?“  The authors look at what happens historically to important macroeconomic variables when there is either a recessions, a credit contraction, an episode of house price declines, and/or an episode of equity price declines.  The authors find the following:

“Our results indicate that interactions between macroeconomic and financial variables can play major roles in determining the severity and duration of a recession.  In particular, we show that recessions associated with credit crunches and house price busts are deeper and last longer than other recessions are….If these statistics, based on a large number of episodes, provide any guidance, they suggest that the adjustments of credit and housing markets in the United States are only in the early stages relative to historical norms and might still take a long time”

The authors found that episodes of credit contractions and housing price declines lasted lasted 6 and 8 quarters respectively during a typical downturn; for a credit “crunch” or a housing “bust” these downturns in the economy lasted 10 and 18 quarters respectively.

The U.S. Economy may not be out of the water yet.

California has been one of the states that have been hardest hit by the “housing crisis.” According to the May 2008 Case/Shiller Index, home prices in San Diego and Los Angeles Counties have fallen 23% and 25% respectively over the past year. Foreclosures are rising and many houses are now left empty.

The Economist reports (“Meet the new neighbors“) that the housing crisis is spawning a rise in the West Nile virus in California. When homes with pools are left unattended, this creates a breeding ground for West Nile mosquitoes. Public health officials have reported that the West Nile virus has reached record levels in southern California.

Looks like the housing crisis may create a public health crisis as well.

Are marginal utilities higher when you are sick or when you are healthy? What this question basically asks is whether or not you enjoy having more income when you are healthy or when you are sick. On the one hand, when you are healthy, you may value expensive items (e.g., travel, flat screen tv, sports car) more than when you are sick. On the other hand, when you are sick, you may value income more in order to pay for prepared meals, or home health care.

A paper by Finkelstein, Luttmer and Notowidigdo (2008) explore how the utility function changes with illness. They derive an interesting model based on earlier work of De Nardi, French and Jones 2006 and Palumbo 1999.

Model

• U(C,S) = γ₀S + (1 + γ₁S)u(C)

The utility function above is based on the amount of consumption, C, and whether or not the person is sick, S. S is equal to unity if the individual is sick and zero if they are in good health. The γ₀ term is negative represents the absolute change in utility which occurs when someone is sick and the γ₁ parameter gives the effect of sickness on marginal utility. If γ₁ is positive, then being sick increases marginal utility (the benefit from one additional dollar of income) and if γ₁ is negative then being sick decreases marginal utility.

The authors use a CRRA utility function as follows:

• u(C)=c^1-α/(1-α)

Individuals can purchase a health insurance benefit, b, to protect them against income risk from becoming sick. The authors find that the optimal health insurance level depends not only on risk aversion, but also on how marginal utility changes between healthy and sick states (i.e., the parameter γ₁).

Similarly, risk aversion and state-dependent marginal utilities will also affect an individual’s optimal savings rate.

We see that the optimal levels of health insurance and saving depend significantly on whether or not marginal utility increases or decreases when one becomes sick.  If marginal utility increases when one is sick, more health insurance is optimal.  If marginal utility decreases when one is sick, less health insurance is optimal. Similarly, increased marginal utility when a person is sick, increases optimal savings rates but the effect is smaller than the effect on optimal health insurance. The question remains: when a person gets sick, does marginal utility increase or decrease empirically?

Empirical Results

The authors utilize data from the Health and Retirement Survey.  The study uses a self-assessment of subjective well being as a proxy for utility, and estimates how changes in permanent income affect the marginal utility of non-medical consumption when an individual is sick and when they are healthy.  The authors results are summarized as follows:

The results suggest that, relative to the standard practice of assuming a state-independent utility function, accounting for our estimate of state dependence lowers the optimal share of medical expenditures reimbursed by health insurance by about 20 to 45 percentage points, and lowers the optimal fraction of earnings saved for retirement by about 1 percentage point.

In summary, people adjust to their new, sick state and adjust their marginal utilities accordingly to cope with the change in their life situation.

• Finkelstein, Luttmer and Notowidigdo (2008) “What Good Is Wealth Without Health? The Effect of Health on the Marginal Utility of Consumption“, NBER WP #14089.

What have my fellow brethren of social scientists discovered lately? The Boston Globe summaries some interesting findings such as:

• Women find men with stubble more attractive than those who are clean shaven or have significant amounts of facial hair. I guess women must think Brett Favre is a sexy dude…whether or not he is retired.
• Evidence of the winner’s curse is found in major league baseball free agency.
• Award-winning CEOs earn more money, but their companies preform worse. Is regression to the mean at work?

Hat tip: The Sports Economist.

What is the typical salary of an Economist just after they finish graduate school? This question is of particular interest to me personally, since I am going on the job market this year.

Below are some of the results from the Survey of the Labor Market for New Ph.D. Hires in Economics, from the University of Arkansas School of Business. The data are from new hires in 2006.

The AEA Paper and Proceeding from also has data on new assistant professors salaries for economists as well.

Additional compensation includes guaranteed summer compensation and signing bonus. It does not include fringe benefits.

As an academic researcher, using the web has made my life significantly easier.  I can access millions of articles from academic journals in the click of a button.  Sites such as JStor and ScienceDirect have hundreds of journals located in the same place for easy use.  With so much more information online, I am able to access information in the “long tail” of the academic knowledge spectrum.

In an article titled “Digital Libraries,” The Economist magazine, however, reports that “as more journals become available online, fewer articles are being cited in the reference lists of the research papers published within them.”  The findings are from a study by James Evans, a sociologist at the University of Chicago.

“…for every additional year of back-issues of a journal available online, the average age of the articles cited from that journal fell by a month. He also found a fall, once a journal was online, in the number of papers in it that got any citations at all.”

This phenomenon is likely due to the advent of search engines.  Search engines often rank academic article by either the date published or the number of citations the article has received.  Whereas a manual library search in the old days treated each article as near equals regardless of its publication date and number of citations, electronic searchers are more likely to come across the best most popular work.

Last year, I wrote a blog post about how Los Angeles could fix its traffic problems.  Today, the San Diego Union Tribune reported that traffic has decreased between 3.3% and 9.1% during the week and between 5.2% and 11.9% on the weekends.  How has San Diego accomplished this?

Higher gas prices are the reason.  A pleasant byproduct of higher gas prices are that less people will drive.  Of course, when less people drive, traffic decreases.

As mentioned in the earlier post, instead of building more and more freeways, southern California should have implemented a gas tax or implement more toll on freeways.  Higher gas prices are in essence doing the same thing that a gas tax would.  Higher gas prices, however, end up in the pockets of oil companies whereas a gas tax could be used to create better public transportation infrastructure, thus making it easier not to use one’s car and thus further decreasing traffic.

At least this is what David Williams of the Health Business Blog has experienced in paying for his firm’s Blue Cross/Blue Shield plan.  “This year’s increase is 13.3 percent, on top of last year’s 26.3 percent increase and an 11 percent increase the year before. Thanks to the magic of compounding it means the premium has gone up about 60 percent in three years. Health insurance has become a serious burden for us.”

With these large increases, Williams sympathizes with Wal-mart’s aversion to providing health care for their workers.

“A worker making the US minimum wage of $6.55 per hour, working 40 hours per week, 50 weeks per year would make $13,100. By contrast our company’s premium is more than $15,000 per family. And of course that doesn’t count the out-of-pocket payments if someone actually wants to use their insurance.”

With rising gas and food prices, in addition to the near constant pace of insurance price increases, consumers buying power is definitely getting squeezed.

I recently read an article in Consumer Reports about online budgeting tools.  I decided to try out Buxfer.com myself and was really impressed with the site.

You are easily able to upload statements from your bank, paypal, credit card and other accounts.  The site automatically applies tags to certain transactions so you can easily chart your expenses for groceries, gas, rent etc.

Also, Buxfer complies with Consumer Reports WebWatch guidelines on privacy, service, and other factors.

Generally, economists believe that individuals are rational and make choices to maximize utility. How do you reconcile the fact that most people would prefer to own a Ferrari, but actually own a car like a Toyota Matrix? Once you take into account all aspects of this choice (including price) then the Toyota Matrix doesn’t look so bad.

However, an NBER working paper by Beshears Choi, Laibson and Madrian (2008) claims that sometimes, people’s revealed preferences may not coincide with their true preferences:

1. Passive choice. If individuals do not actively make a choice, such as would be the case for a default 401(k) enrollment at work, people may not be choosing optimally (at least initially).
2. Complexity. It is often difficult for individuals to act rationally in complex situations. For instance, when one is faced with a large number of choices or faced significant uncertainty regarding future prospects, individuals may act suboptimally.
3. Limited Personal Experience. “Human learning is often generated by feedback.” Thus, the more experience an individual has, the more rational they will act. You probably get a better deal buying groceries than buying a used car, because you have much more experience with the former.
4. Third Party Marketing. “Tom Sawyer tricked his friends into paying him for the privilege of painting his family’s fence. A great deal of real behavior is also influenced by marketing.”
5. Intertemporal Choice. How should people discount future utility? The authors claim that “Only discounting due to mortality risk is easily defended philosophically.”

How can we correct for these “incorrect” revealed preferences? Beshears and co-authors give some suggestions:

Structural estimation specifies a positive model with a precise set of economic and psychological motives (perhaps including non-Bayesian thinking and other decision-making errors). This model is then estimated using data, and the resulting positive preferences are mapped into normative preferences using normative axioms.

Active decisions …[require individuals] to explicitly state their preference without beinginfluenced by (or being able to rely on) a default option.

In most stationary economic environments, initial choices are likely to be further from normative optimality than choices made after many periods of experience. One should therefore give more weight to asymptotic choices [preferences revealed after having experience with the choices] when attempting to infer normative preferences.

When homogeneous individuals make noisy, error-prone decisions, their individualdecisions do not reflect normative preferences, but their aggregate behavior can …

Self-reported preferences reveal something about an agent’s goals and values. Normative economics should allow self-reports to have some standing.

• Beshears J, Choi JJ, Laibson D, Madrian BC (2008) “How are preferences revealed” NBER WP #13976.

Jonathan Rowe’s essay (“Our Phony Economy“) in the June edition of Harper’s Magazine criticizes the blind use of GDP as the only measure of the economy. GDP by definition looks at the total quantity of good produced in a given year. Rowe wisely notes that solely relying on GDP can omit some important aspects which effect the economy. For instance, using more gas and oil increases economic activity, but polluting the air does not count as reduced economic activity. If we our society becomes more unsafe and businesses must hire security guards and electronic security systems, this shows up as an increase in GDP whereas most people would believe that have a more unsafe society constitutes a reduction in welfare.

Activities such as parental child care are not counted in the economy while private day care does count as economic activity. When measuring gasoline production, GDP should take into account that gasoline production increases economic activity on the one hand, but also reduces fossil fuel levels as well. Rowe notes that some economic activity may include economic ‘bads’ such as drug abuse or fraud.

Finally, a disease outbreak where a city would have to hire more doctors, nurses, and medical staff would be considered an increases in economic activity. However, no economist would advocate that a “disease-led recovery” would be the best way to improve welfare. What matters to individuals is their health level, not how much they spend on medical care.

What Rowe does not do is offer better alternatives. The reason that pollution, safety, and fossil fuel extraction are not counted in GDP now is that they are very difficult to measure. What is the cost of releasing x amount of pollution into the air? How much do people value safety? In order to figure out how much the extraction of fossil fuels costs, we need to have some idea of how much fossil fuels are currently in the ground (which we don’t really know).

Doctors have a very difficult time determining health levels so how would statisticians be able to come up with some health-related economic indicator. With respect to economic “bads” like drug abuse, who should be the one determining what is an economic “good” and what is an economic “bad.” Drunk driving is certainly not a productive activity, but having a glass of beer or wine with your dinner certainly adds to the welfare of many people.

Thus, Rowe’s wisely notes that GDP does not provide an exact measure of social welfare. Nevertheless, until someone comes up with a better statistical tool, GDP will be the rough instrument with which most analysts, media, researchers and the public will use to measure economic activity.

This blog has repeatedly reported on the success of microfinance organizations such as Nobel-prize-winner Muhammad Yunus’ Grameen Bank and ACCIÓN (see 26 Mar 07 and 26 May 06 posts). Up to this point, the organizations who have worked to make loans to the world’s poor have been nonprofit organizations. Now, however, The Economist reports (“Doing good…“) that CompartamosBanco is a private for-profit business who is aiming to make money making loans to the poor.

Having for-profit businesses service loans shows that microfinance is expanding. The profits from these loans can be used to offer more and more loans to the the world’s poor. However, for-profit firms do charge high interest rates. Interest rates at CompartamosBanco are currently 79%. These figures are so high because it costs $152 to service the average $450 loan.

While Muhammad Yunus is somewhat troubled by the advent of for-profit microfinance, ACCIÓN has partnered with CompartamosBanco on some projects.

Should microfinance be a for profit business? What is your opinion?

The Austrian Economists blog has a great post (“Hard Work Pays Off“) giving a bunch of advice for grad students. Below are some of my favorite quotations:

• Don Lavoie — “Why are you doing this? Don’t ever forget your answer to that question.”
• James Buchanan — “All work is work in progress. Don’t get it right, get it written.”
• James Buchanan — “It takes varied reiterations to force alien concepts upon reluctant minds.”
• Bob Tollison — “Never consider a criticism as lethal, but instead as an opportunity for another line on your CV.”
• Kenneth Boulding — “At some point in your career you will be confronted with the following dilemma — should you read or should you write. I chose to write.”
• Peter Boettke — “Look out the window rather than on the black board for your questions. Strive to find puzzles where it appears that history defies what logic dictates and then solve the puzzle by demonstrating with the tools of rational choice theory and institutional analysis the the defiance was only an illusion.”
• Andrei Shleifer — “Why be boring?”

And most importantly…

• James Buchanan — “The best dissertation is a done dissertation.”

The American Society of Health Economists (ASHE) has honored Michael Grossman as the winner of the Victor Fuchs Lifetime Contribution Award.  Much of Dr. Grossman’s research deals with child and adolescent health, as well as drug and alcohol use.  An interview with Dr. Grossman is available in the ASHE spring newsletter.

The Berkeley Electronic Press’ Studies in Nonlinear Dynamics & Econometrics journal has a video interview with James Hamilton, a UCSD economist and one of the best instructors I have had.

NPR’s This American Life has a great episode (“The Giant Pool of Money“) explaining in a non-technical, entertaining manner how the “credit crunch” came upon us. The episode looks at all the parts of the mortgage-backed securities chain: home owners and borrowers, brokers, banks, rating agencies, Wall Street, and foreign and domestic investors.

A special program about the housing crisis produced in a special collaboration with NPR news. We explain it all to you. What does the housing crisis have to do with the turmoil on Wall street? Why did banks make half-million dollar loans to people without jobs or income? And why is everyone talking so much about the 1930s? It all comes back to the Giant Pool of Money.

Economist Greg Mankiw reveals the answer in the “Trade: why not?” post on The Free Exchange blog.

Many doctors claim that the medical malpractice system is broken and needs to be fixed. Doctors have high malpractice insurance premiums and often practice defensive medicine to protect themselves against lawsuits. To help alleviate this problem, many politicians have asked for some sort of tort reform. Tort reform can be generally categorized into 4 types of legal changes:

1. Caps on noneconomic damages. Noneconomic damages cover items other than monetary losses, such as pain and suffering.
2. Caps on punitive damages. Punitive damages are awarded in addition to compensatory (economic and noneconomic) damages in order to punish defendants for willful and wanton conduct.
3. Modifications of collateral-source rule. Under the common-law collateral source rule (CSR), amounts that a plaintiff receives from sources other than the defendant (e.g., from his or her own insurance) may not be admitted as evidence in a trial.
4. Modifications of the joint-and-several liability (JSL) rule. In a trial with more than one defendant, the first step is to apportion blame for the harm. Under JSL, the plaintiff can then ask the “deep pockets” defendant to pay all of the damages, even if that defendant was responsible for only a small fraction of the harm. Modifications to the JSL rule often hold that the “Deep pockets” defendant must be at least 50% liable for the harm in order to be held 100% responsible for the damages.

Which of these reforms are helpful? A paper by Currie and MacLeod (QJE 2008) aims to answer this question. The authors look at variation in tort laws across states between 1989 and 2001. They claim that malpractice laws put doctors more at risk for a lawsuit is a good thing because it will cause them to behave more carefully. When doctors fear expensive lawsuits or a blow to their reputation, they may behave with more caution. Thus, capping punitive and non-economic damages should decrease caution. On the other hand the JSL rule puts doctors more at risk. They will not be protected from a suit simply be associating with a deep pockets hospital.

Empirical Results

To test this, the authors look at the number of Caesarean sections performed and the rate of induction or stimulation of labor. C-sections are popular with doctors because they receive additional compensation compared to a “regular” birth. However, performing a C-section on a mother who does not need it exposes them to additional risks. The authors find that “JSL reform reduces C-sections and complications of labor and delivery…In contrast, caps on damages are found to increase procedure use, and hence costs. They also increase complications of labor and delivery in some specifications.”

For a robustness check, the authors look at C-section rates for high- and low-risk babies separately. The authors assume that doctors have less treatment discretion for high risk cases, and the results demonstrate that tort reform had less of an effect on procedure rates or outcomes for high risk cases.

• Currie, Janet; MacLeod, W Bentley (2008). “First do no harm? Tort reform and birth outcomes” Quarterly Journal of Economics, v 123(2): 795-830.

For many years price increases in the medical sector has outpaced overall inflation by a significant amount. According to the Bureau of Labor Statistics, here is the increase in consumer prices over the last few years.

Medical inflation is outpacing general inflation by an average of 1.5% per year. But is this measure of medical inflation accurately measured? Not according to paper by Joseph Newhouse (1992). Here are 4 reasons why not.

1. Medical CPI measures input, not final goods. The CPI for medical services focuses on inputs such as physician visits or hospital days. However, the service the patient consumers is treatment for a specific disease. An increase or decrease in the requisite number of doctors visits is a change in the input towards treatment. A true measure of medical CPI would measure how the price to treat a disease changes over time.
2. Actual Prices not observed. Generally, statisticians use the list price as the price of medical services. However, very few people pay this list price. Most individuals have insurance and these insurance companies negotiate bulk discounts. Thus, the list price is not the relevant price for most individuals.
3. Quality changes. Even if one uses the same amount of inputs in treating a disease, the quality of medical care has likely increased over time. Of course, observing quality changes in medical care is extremely difficult.
4. Medical CPI weight out-of-pocket expenses. Medical CPI weighs the cost to consumers of medical spending. However, since most people have health insurance, items which are paid more frequently out of pocket receive a higher weight. For instance, dental care is more frequently paid out of pocket and thus receives a higher weight in the CPI. [I am not sure if this weighting has changed in more recent versions of the medical CPI].

• Joseph P. Newhouse (1992) “Medical Care Costs: How Much Welfare Loss?” The Journal of Economic Perspectives, Vol. 6, No. 3 (Summer, 1992), pp. 3-21

John Tierney writes in The New York Times (“Appeasing the Gods…“) that “”We buy insurance not just for peace of mind or to protect ourselves financially, but because…we think buying health insurance will keep us from getting sick.”

A rational person would believe that buying insurance against an event will not alter the probability that it will occur–ignoring issues of moral hazard.  For instance, the act of buying health insurance should not make us less likely to be sick.  Using more preventive care which is cheaper due to insurance can prevent illness, but the act of buying health insurance should not effect the probability one gets sick holding constant the medical care levels.

A better example may be travel insurance.  “Last year, tens of millions of people bought life insurance for scheduled flights of airlines in the United States. Not one of those insured passengers died in a crash.”  Is this a waste of money?  Not if you are superstitious and believe that the act of buying life insurance affects the probability your plane will crash.

“So when we think about passing up flight insurance, we conjure up disaster just as easily as ancient Greeks imagined a thunderbolt from Olympus, and we too figure we can avert it through the equivalent of a bull sacrifice. Intuitively, we haven’t made great strides since Homer’s day. But at least our gods take credit cards.”

• Hat tip to Arnold Kling at EconLog.

The average person believes that they are above average in almost all respects. This phenomenon is often called the Lake Wobegon effect after Garrison Keillor’s fictitious town in which all people are above average.

A paper by Dunning, Heath and Suls (2004) gives some great examples of Lake Wobegon in action.

“Motorcyclists believe they are less likely to cause an accident than is the typical biker (Rutter, Quine, & Albery, 1998). Business leaders believe their company is more likely to succeed than is the average firm in their industry (Cooper, Woo, & Dunkelberg, 1988; Larwood & Whittaker, 1977). People think they are less susceptible to the flu than their contemporaries, and as a result avoid getting flu shots (Larwood, 1978). Of college professors, 94% say they do above-average work (Cross, 1977). People signing up to bungee jump believe they are more likely to avoid injury than the average bungee jumper, although their friends and family do not share this impression (Middleton, Harris, & Surman, 1996). Ironically, people even state that they are more likely than their peers to provide accurate self-assessments that are uncontaminated by bias (Friedrich, 1996; Pronin, Lin, & Ross, 2002).”

…Surgical trainees place too much confidence in their diagnoses after looking at X-ray evidence (Oksam, Kingma, & Klasen, 2000). After looking over a client’s case materials, clinical psychologists overestimate the chance that their predictions will prove accurate (Oskamp, 1965).

Despite the prevalence of overconfident self-assessment, I suffer from no such problem. That is of course because I am an above-average blogger.

For all my economist peers who are sick and tired of monetary policy, financial option valuations, and esoteric econometric specifications, it may be time for a change. The American Association of Wine Economists (AAWE) is holding their second annual conference August 14-16 in Portland, Oregon. The AAWE also publishes the Journal of Wine Economics.

I am sure the members of the AAWE do not mind conducting “research” as to which wines are the highest quality.

Who says economics is the dismal science?

Eric Crampton argues against the paternalistic view some economists have taken in a recent editorial in Health Economics. Here’s an excerpt:

“Of course, most economists would disagree vehemently [that taxing unhealthy behaviors is a good thing]. Raising taxes does tend to reduce consumption and, where consumption generates large negative externalities (costs borne by uninvolved parties) can even be efficient: Pigovean taxes (taxes proportionate to those external costs) can push us closer to socially-optimal outcomes. But, there is no inefficiency caused by people choosing to live lifestyles they view as preferable despite the health costs.

If I decide to enjoy a shorter life rather than eek out a miserable existence without wonderfully-marbled steaks, a beer or several, or even the occasional cigar, zero inefficiency is induced thereby.

…what evidence there is suggests that to the extent smoking induces a “fiscal externality,” the sign of the effect is wrong: smokers pay more in cigarette taxes than they ever cost the public purse. They die earlier of cheaper diseases and collect less in superannuation than do non-smokers. And, as a 10% increase in cigarette taxes correlates with a 2% increase in obesity, one wonders whether increased cigarette taxes consequently require further increases in taxes on fatty foods.

Crampton supports the idea of “De gustibus non est disputandum,” we should not criticize individuals’ preferences.

“‘Libertarian paternalism’, ‘optimal paternalism’ and ‘cautious paternalism’ have been promulgated by prominent economists.” A recent Health Economics editorial by Jody L. Sindelar contradicts the economist conventional wisdom that correcting externalities, providing information and protecting youths are the only role for the government in the health policy arena.

I agree with Sindelar that making general economic theory more flexible to the practicalities of the real world is important. For instance, she cites the effectiveness of the PROGRESA program in Mexico. The program has been so sucessful that it has been adopted in New York City. The authors also cite the fact that small conditional cash payments conditional on drug abstinence have also been effective in help those addicted to drugs quit their habit.

Nevertheless, we must be careful how much believe the government should manipulate our lives. Sindelar claims that smoking, alcohol and drug abuse, and overeating all are examples of irrational behavior. While these activities are harmful, many people do enjoy having a cigarette, getting intoxicated, or eating copious amounts of desserts and the decision to smoke, drink, overeat or use drugs is likely not irrational. I do not believe that these activities should be taxed or prohibited just because they are harmful to the individual. Only if they lead to harm in other individuals (i.e.: externalties, such as second hand smoke, drunk driving, etc.) would specific tax be merited.

In my view, I do not believe that all government action is bad. Yet, I believe that the burden of proof should be that government action is truly beneficial. In the criminal court, people are “innocent until proven guilty.” In the public policy arena, there should be no government action, unless the government action has been proven beyond a reasonable doubt to be effective.

• JL Sindelar (2008) “Paying for performance: the power of incentives over habits.” Health Economics, 17(4): 449-451.

According to the U.S. News and World Report UC San Diego was ranked as the tenth best economics department in the U.S.

Most economics simplify markets and assume that there is one market price. In reality, however, we observe significant price dispersion. Because of this, we see that that searching for the lowest price–while costly–can buyers to superior outcomes. George Stigler (1961) is a seminal paper on the Economics of Information which I will review here.

When should a person search? This occurs when the marginal benefit to search is equal to the marginal cost. Let us assume that the marginal cost of searching is proportional to the individuals cost of time. The marginal benefit of searching is:

• q*|∂P_min/∂n|

The number of searches is denoted as n. We see that people who buy a higher quantity, q, of goods will search longer. One implication of this is that business professional will search more than casual shoppers since they will likely buy higher quantities. Since tourist have little information and purchase low quantities, Stigler accurately predicts that tourist will pay higher prices than experienced buyers.

Also, “the expected savings from search will be greater, the greater the price dispersion of prices.” However, when goods are one-of-a-kind or unique, then the efficiency of searching is extremely low since it is difficult to identify potential sellers.

Brokers can be brought into the market to make it more efficient. These brokers “will eliminate the profitability of quoting very high selling and very low buying prices and will render impossible some of the extreme price bids.” Price dispersion will not disappear entirely when there are brokers since these brokers must make at least some profit to compensate them for their time. As price dispersion nears zero, brokers will leave the market.

What other conclusions does Stigler derive?

1. The larger the fraction of the buyer’s expenditures on the commodity, the greater the savings from search and hence the greater the amount of search.
2. The larger the fraction of repetitive (experienced) buyers in the market, the greater the effective amount of search (with positive correlation of successive prices).
3. The larger the fraction of repetitive sellers, the higher the correlation between successive prices, and…the larger the amount of accumulated search.
4. The cost of search will be larger, the larger the geographical size of the market.

• George J. Stigler (1961) “The Economics of Information” Journal of Political Economy, 69(3): 213-225.

Most people do not understand what a health economist is. Where do they work? What do they do? How do they spend their time?  How are they trained?

A paper by Morrisey and Cawley (Health Econ 2008) attempts to answer this question. The authors conducted an online survey to achieve a better understanding of what health economists do.

Training

Ninety-three percent of health economists have a Ph.D. A few health economists have an MD (2.6%), an RN (1%) or a JD (<1%) in addition to their PhD. Of those with a Ph.D., 72% have a Ph.D. in Economics. Below are a list of the economics departments that have trained the most health economists in the sample:

Seventy-six percent of health economists wrote a health related dissertation, even though 2/3 of graduate programs lacked a formal health economics field. For instance, at UCSD I am writing my dissertation on health economics even though there is not established program.

Employment

Where do health economists work? Most work in academia (64%), but a large percentage also work for the government (12%), NGOs (15%) or the private sector (9%). Of those who are academically employed, below is a chart detailing where their principal appointment is located.

For those who work in public health or medical school about 50% of their salary is made up from funding from external grants and contracts.

Research Interest

Below is a chart detailing the subspecialty of the health economists in the survey.  Respondents could choose multiple options.

After reading this post, hopefully you now have some idea of who health economists are and what they do.

• Morrisey MA, Cawley J. 2008. “US Health Economists: Who we are and what we do” Health Economics, 17(4): 535-543.

Many economists espouse utilitarianism as a superior ethical framework to proposed alternatives. A paper in Nature magazine finds that “Damage to the prefrontal cortex increases utilitarian moral judgements.”

Maybe there is some merit to the paper…economists have always been a strange breed.

Freakonomics by Steven Levitt and Stephen J. Dubner is an extremely popular book that has made economics a (somewhat) sexy topic of discussion. Levitt’s research makes economics exciting and his quirky, controversial studies make interesting reading.

John DiNardo, however, thinks that even Freakonomics is “interesting” and “entertaining,” it may not be revealing truths. Dr. DiNardo has written three critical reviews of the book. DiNardo’s criticisms call into doubt the meaning of some of the conclusions derived from Levitt’s research. For instance, DiNardo discusses the logical meaning the causal effect of obesity on health.

Nonetheless, I would argue that it is unlikely that anyone will devise a severe test of the proposition that obesity causes an increase in all-cause mortality. Simply put, the effect of obesity (or of ideal weight) is inextricably implementation specific. That is, it is not helpful to think about the “effect” of obesity for the same reason it is not helpful to debate the “causal effect of race on income”(Granger 1986). Many of us suspect, for example, that encouraging obese individuals to “starve themselves” for short periods of time might help one lose weight, but wouldn’t necessarily promote longevity (although it might, who knows? ).

Similarly, we might expect weight loss that results from increased physical activity to be more protective than
weight loss that results from increased life stress. The experience in the U.S. with the drugs fenfluramine and dexfenfluramine (Redux) is a case in point. Despite good evidence that the causal effect of taking Redux was weight loss, the drugs were pulled from the market because a “side effect” of the medication was an increase in potentially serious heart problems (Food and [Drug] Administration 1997) . Indeed, it would appear that the presumption that obesity is a cause of ill health made it virtually impossible to debate whether non–obesity was the cause of the increased heart problems. Rather, the consensus seems to be that the heart problems were not caused by non–obesity, but rather by Redux’s “side effects.”

My point is simple: when each way of “assigning” obesity that we can imagine would be expected to produce a different effect on all–cause mortality or other outcome, it is not at all clear that it is helpful to debate the “effect of obesity.” It seems more intelligible (and more policy relevant) to discuss the effect of Redux or exercise than it is to talk about the “effect” of obesity.

One study that DiNardo does hold up as an example of fine research is Cullen, Jacob and Levitt (Econometrica 2006). This paper was written by Levitt as well as my dissertation advisor Julie Cullen.

• John Dinardo (2007). “Interesting Questions in Freakonomics .” Journal of Economic Literature, Volume 45, Number 4, pp. 973-1000(28)
• Julie Berry Cullen, Brian A Jacob, Steven Levitt (2006) “The Effect of School Choice on Participants: Evidence from Randomized Lotteries.” Econometrica 74 (5) , 1191–1230 doi:10.1111/j.1468-0262.2006.00702.x

The American Economic Association (AEA) has some great resources for economists.  For instance,  it has links to:

• Rankings of the Top Economics Graduate programs
• Articles on Economists’ salaries and the Economist Job Market
• Articles on Economics Graduate Schools
• General information on Graduate study in Economics

Darkness at Noon by Arthur Koestler is a unique novel which describes the imprisonment of Communist revolutionary Nicholas Rubashov. Rubashov was a loyal supporter of the Communist cause in Russia, but his subsequent imprisonment on bogus charges causes him to reflect on whether his fight to bring Communism to Russia was truly beneficial to Russian society. The book demonstrates how Communist idealist notions became perversions as Stalin took power and instituted a cruel dictatorship.

One of the main themes of the book is that philosophical generalizations and abstract ideals often lead to disastrous results when they are applied without regard to individual circumstance. As Ferdinand Lassalle once said:

‘Show us not the aim without the way./ For ends and means on earth are so entangled/ That changing one, you change the other too;/ Each different path brings other ends in view.’

One passage from the book may be particular applicable to economists whose solutions to mathematical problems may not prove to be fruitful in the ‘real-world’.

‘A mathematician once said that algebra was the science for lazy people–one does not work out x, but operates with it as if one knew it. In our case, x stands for the anonymous mases, the people. Politics mean operating with the x without worrying about its actual natures. Making history is to recognize x for what it stands for in the equation.’

William Easterly is a famous development economist at NYU. Yet in a 2007 paper in the American Economic Review, Easterly asks “Was Development Assistance a Mistake?”

Easterly first recounts how development economics conventional wisdom on how to end poverty has changed over time.

• 1950-1970s: Raising investment is the key to reducing poverty. “…[d]evelopment (i.e. economic growth) was a simple matter of raising the rate of investment to GDP, including public investments like roads, dams, irrigation canals, schools, electricity and private investment. However, private investment was usually not trusted to do enough or do the right things, and so there was a strong role for the state to facilitate and direct investment, guided in turn by the development experts.”
• 1980s: Washington Consensus. This policy “…called for removing price distortions, opening to trade, and correcting macroeconomic imbalances (mainly budget deficits). The slogan of the new wave was ‘adjustment with growth.’”
• 1990s: New Growth Literature. Here economists would would use hundreds of right hand side variables and regress them on growth in order to find the determinants of economic growth. “Durlauf, Johnson, and Temple (2005) pointed out that 145 different right hand side variables were significant as determinants of growth in various studies with around 100 degrees of freedom.”
• 2000s: We don’t know. In 2005, the World Bank states that “different policies can yield the same result, and the same policy can yield different results, depending on country institutional contexts and underlying growth strategies.” The Barcelona Development Agenda proclaimed that “there is no single set of policies that can be guaranteed to ignite sustained growth.”

So how does Easterly sum up the contribution of development economists to the world?

“In sum, we don’t know what actions achieve development, our advice and aid doesn’t make those actions happen even if we knew what they were, and we are not even sure who “we” are that is supposed to achieve development. I take away from this that development assistance was a mistake.”

In fact, Easterly likens development economists advice to that of a communist central planner.

“The 20th century’s first development economist may have been Lenin, who wrote a famous pamphlet in 1902 called ‘What is to be done?,’ and said that the revolutionary intelligentsia had the answer. A long line of such diverse thinkers as Edmund Burke, Karl Popper, Friedrich Hayek, Isaiah Berlin, and James C. Scott have criticized the idea that experts can re-design society, all the way back to the French Revolution, and the catastrophic outcomes of the more extreme attempts to do so supported these criticisms. Yet the unquenchable demand for experts who can call tell “us” the right answers shows no sign of ending soon.”

Are smart people risk averse? Are dumb people impatient?

This is what Thomas Dohmen, Armin Falk, David Huffman, Uwe Sunde explore in their 2007 Discussion paper. Using data from a choice experiment of 1000 German adults, the authors tested for risk aversion using a Holt & Laury framework, and for impatience by varying the annual rate of return for a €100 investment. It is necessary to test the risk aversion and impatience parameter separately because in expected utility theory (EUT), a more concave utility function will cause more impatient choices, holding constant the discount rate. Cognitive ability was measured using questions similar to those on the Wechsler Adult Intelligence Scale (WAIS).

The authors found that individuals with higher cognitive abilities are less likely to be risk averse. Further, those who scored higher on the WAIS are significantly less impatient. This finding is true even after controlling for income, education, and credit constraint co-variates.

According to the authors:

“The paper also points to a different interpretation of reduced form models that have been estimated in the literature on cognitive ability and labor market outcomes. These models have typically included a measure of cognitive abilities, but not risk aversion or impatience, as explanatory variables (e.g., Cawley et al., 2001). Outcomes such as educational attainment or wages may by affected by risk aversion and impatience, and thus part of the impact of cognitive ability may reflect the correlation with these traits. In other words, our findings point to a potentially important source of omitted variable bias in this type of estimation.

Given that cognitive ability is known to be transmitted from parents to children, our findings could also be relevant for the literature on intergenerational transmission of preferences and socio-economic status.”

• Thomas Dohmen, Armin Falk, David Huffman, Uwe Sunde, 2007. “Are Risk Aversion and Impatience Related to Cognitive Ability?” IZA Discussion Paper No. 2735.

Sometimes, a coefficient isn’t what it seems to be. When using an ordinary least squares (OLS) regression, the regression coefficients indicate the proportion by which the dependent variable changes when the independent variables increases by one unit. Regression coefficients are more difficult to interpret, however, for more complicated regression specifications such as probit, mutlinomial logit, negative binomial, etc.

Let us assume that a regression coefficients are fitted to the following equation:

• y=f(Xβ)=f(β₀+β₁x₁+…+β_kx_k)

For instance, in the probit model, f(·)=Φ(·), where Φ(·) is the normal cdf. In the OLS setting,∂y/∂x_k=β_k. Thus, there are no interaction terms–unless explicitly states as one of the variables in X–in the OLS. However, in the probit case, ∂y/∂x_k=φ(xβ)β_k., where φ(·) is the pdf of the normal distribution. Thus, the marginal effects differ depending on the value of x.

The standard solution to this problem is to calculate the marginal effects when x is set equal to its mean value. When x_k is a dummy variable (i.e.: x_k∈{0,1}), the marginal effects are calculated by setting x_-k equal to their mean and then finding the difference in y when x_k increases from 0 to 1. This difference is the marginal effect for the discrete variable.

Sometimes this method will lead to results that are difficult to interpret. For instance, one could calculate the marginal effect on health from taking a new drug for someone with a gender=.051, and minority status=0.24. Since someone can either be male or female, they can be a minority or not, finding the marginal effect for this hypothetical person may not be the very revealing.

Another method would set continuous variables equal to their mean (e.g.: age, income) and then we could calculate the marginal effects for a the typical white female, a typical black male, etc.

A final methodology is given in Boonen, Schut and Koolman (2008). The authors investigate whether or not health insurance company financial incentives are effective in directing enrollees towards preferred provider pharmacies. In the results section of their paper, they state:

“The marginal effects for discrete variables are computed by calculating the change resulting from a change in the discrete variable from 0 to 1 holding all other variables fixed at their mean (see, for example, McGuirk and Porell, 1984; Madden et al., 2005). An average individual does not exist, however, and in our research we are interested in the probability that a certain consumer does or does not visit the preferred supplier. The marginal effects are thus not computed over the average individual but represent the mean of the marginal effects over each individual. This is done by computing the effect of, for example, a one-year increase in age on the probability of visiting the preferred provider for each individual and then averaging these probabilities across all individuals in the sample (Strombom et al., [JHE] 2002; Greene, 2003). The standard errors for the marginal effects are computed through bootstrapping. ”

This post should give researchers some idea of how to calculate marginal effects for complex regression models. It should be noted that there is no one optimal method, but one should determine how best to analyze the data and then use the marginal effects method most appropriate for your data analysis.

“In 1988, the first year for which data are available, there were fewer than 14,000 patients waiting for a kidney transplant and about 7,000 deceased-donor kidneys. Today, the waiting list has grown more than fivefold — an increase fueled partly by higher rates of diabetes — but the number of deceased-donor kidneys has only inched up. ”

There is a serious kidney shortage in the U.S.  Any economist can tell you that shortages generally occur from either a natural disaster or when the government imposes a below market price on a commodity.  In this case, the government has said that one can not sell organs; thus the market price for a kidney is set to zero.   Could a market for kidneys solve this problem?

The Wall Street Journal has a pair of interesting articles (“Kidney Shortage…” and “A Market for Kidneys?“) on whether or not we should have a kidney market.  Julio Elias of the University of Buffalo comes out in favor while Alvin Roth of Harvard University is against.  Dr. Elias makes a case based on economic theory:

“The current system of live organ transplants resembles an autarkic economy in which patients in need of an organ transplant are constrained to the organs available in the pool of friends and relatives. The kidney exchange system developed by Al and others is a barter system, and clearly will provide an improvement over the current system.

But a general conclusion of economics is that barter is an inferior system when compared to a money system, since barter requires the coincidence of wants. With the use of computers, and a national registry, multilateral barter is a good possibility, but still less efficient than using general purchasing power; i.e., a market. The main disadvantages of the kidney exchange system are the limitations that only kidneys from relatives and friends can be used and that the exchange must happen at the same time. A market-based exchange does not have such serious limitations.”

Dr. Roth believes that creating a market is politically infeasible and socially repugnant.  Although he does not reject the merits of an organ market, he does say that more practical steps–such as an organ exchange or making all individuals organ donors upon death unless they explicitly opt out–will currently be more politically feasible.

“There would be more live-donor transplants if everyone who wanted to donate a kidney to someone could do so, but a healthy person’s kidney is often incompatible with his or her intended donor. So, one way economists have helped is in helping organize kidney exchanges, which allow incompatible patient-donor pairs to exchange with other such pairs. “

 What do you think?

Many health economists wonder how much individuals would be willing to pay for a treatment. Since most medical care is paid by third parties (i.e. private insurance companies or the government) we can not use revealed preference econometrics which has been used in other areas of economics. Instead, many economists ask individuals directly these valuation questions. Yet simply asking the question is not enough. Do you ask the person how much they should pay for a treatment for an illness they do not yet have? Or should we only ask patients who have the disease how much they would be willing to pay for their own treatment? In healthcare systems that are run by the government, one may also want to know how much a person would pay for treatment for other people’s diseases.

In order to understand, what perspective should be taken, a paper by Dolan et al. (Health Economics 2003) uses a simple chart to illustrate six different perspectives:

The term p_p gives of the probability of one’s own need for treatment, and p_o is the probability that others in society will need treatment.

Why is it important for researchers to keep track of all these different perspectives when measuring willingness to pay (WTP)? Dolan notes that empirically, “real patients often give higher valuations than hypothetical patients.” Yet this need not be the case. If patients, ex-post, have adapted to the disease to a significant degree, than hypothetical patients may have higher valuations that real patients.

Whenever a researcher is investigating WTP measures, they must very cautious as to the perspective under which the question is asked.

• Dolan P, Olsen JA, Menzel P, Richardson J. An inquiry into the different perspectives that can be used when eliciting preferences in health. Health Economics. 2003 Jul;12(7):545-51.

According to optimal tax theory, taxes should be highest on relatively inelastic activities.  For instance, most men work full-time and and the tax rate does not affect this.  On the other hand, it has been should that the labor supply of women is much more sensitive to wages and income tax rates.  If we follow the conclusions from the optimal taxation literature we should tax men more than women.

This is what Harvard economists Alberto Alesina and Andrea Ichino propose (see Vox EU).  The Free exchange blog as well as Gilles Saint-Paul of the Toulouse School of Economics, however, are more sensible and reject this proposition.  Free exchange concludes on a particularly interesting point:

“…The economist’s idealised utilitarian social planner does not take seriously the costs incurred by the conflicts that will flare up when some are made ‘more equal than others’.  Perhaps liberal constitutions prominently feature equality before the law for a good reason: official non-discrimination works as a truce, a way of keeping the social peace.“

Health economists, policy makers, physicians and public health officials all want to maximize the well-being of society. These groups evaluate different medical treatments or public health interventions and then determine if the benefit is worth the cost.

In an opinion piece by Dorte Gyrd-Hansen in Pharmacoeconomics (2005), two schools of thought are examined. Those who are ‘welfarists’ believe that “the output of healthcare should be judge according to the extent to which it contributes to overall welfare (i.e. the [weighted] sum of individual utilities….’extra-welfarists’ do not define the output of healthcare in terms of preferences for health vis-a-vis other goods, but according to its contribution to health itself, i.e. they wish to maximize health as against overall welfare.”

What does this mean in reality?

“From a welfarist theoretic framework, treating a person who copes well with her disease and thus generates a high level of personal utility despite a poor health state will not be as efficient as treating a person who copes poorly. Extra-welfarists would aim at constructing an outcome measure that would produce equal values for the two strategies thus overriding individual preferences.”

Let’s use a chart to compare these two philosophies:

From the chart we see that welfarists try to maximize [the sum of] individual utilities subject to a budget constraint. Extra-welfarist, try to maximize health which is done by choosing all medical procedures which are more cost-effective than a certain threshold. This threshold, C, is must be chosen by policymakers. Welfarists wisely see that some individuals value health more than others in comparison to other goods. The extra-welfarist assumes all individuals with the same disease are homogeneous. This may seem naive, but in practice, it is very difficult to find each individuals willingness to pay for an increased level of health.

Extra-welfarists often try to elicit willingness-to-pay (WTP) measures for an additional QALY (i.e. quality-adjusted life year). If one applies a single WTP for each QALY, this “will entail overriding individual preferences such as diminishing marginal utility of health and potential differences in the value of increment health across population groups.” If we could rank health on a scale from 0 to 100 where 0 is equivalent to death and 100 is perfect health, economists would argue that under diminishing marginal utility of health that and individual would value an increase in health from 50 to 60 more than they would an increase from 90 to 100.

So is using the extra-welfarist QALY acceptable? While the welfarist camp offers no practical, easily estimable alternative, the do bring out some short comings of using QALYs (e.g., diminishing marginal utility of health, individual heterogeneity in terms of valuation of health against other good). Thus, I think the QALY method is helpful to analyze the benefit of a particular medical treatment, but the cost per QALY should not be the only factor taken into account when analyzing whether or not to adopt a new medical procedure.

• Gyrd-Hansen D., 2005. Willingness to pay for a QALY: theoretical and methodological issues. Pharmacoeconomics, 23(5):423-32.

Hybrid cars are supposed to save the environment, but they will also increase traffic. How can this be?

Example 1

Let us suppose that Hybrid Harry has a hybrid car which gets 50 mpg. Gas-guzzler Gary has a truck which gets 20 mpg. Both Harry and Gary live in San Diego and have relatives in Los Angeles that they visit over the holidays. Gary is much more likely to take the train to LA than Harry. Let’s see why:

It is about 240 miles to go from San Diego to LA and back. This means that Harry will use 4.8 gallons of gas. If a gallon of gas costs $3.50, than Harry will spend $16.80 on his trip.

Gary will need to use 12 gallons of gas to get from San Diego to Los Angeles. At $3.50 per gallon, Gary’s trip will cost $42.

If a train ticket costs $30 round trip, then Hybrid Harry will decide to drive while Gas-guzzler Gary will make the environmentally friendly choice of taking the train.

Example 2

Using a similar logic, Hybrid Harry will be more willing to live in the suburbs or exurbs and have a longer commute to work. Since commuting is cheaper for Hybrid Harry than Gas-guzzler Gary, Gary is more likely to live closer to his work.

Thus, we see that Hybrid Harry will be driving more miles than Gary and creating more traffic.

Typically, economists when economists look at the health insurance market, they focus on the insurance side of it. By this I mean to define insurance as the purchase of a product which will reimburse the buyer in the case of an adverse event. However, one must also look at the concept of protection. Protection is defined as expending a costly effort to reduce the probability of an adverse event. This costly effort, however, will not effect the amount of the loss, only the probability that it occurs.

A seminal paper by Ehrlich and Becker (JPE 1972) finds the optimal levels of self-protection and how optimal self-protection change when insurance markets are introduced. Let us assume that the probability of a loss is p(e) where e is the effort expended and p’<0. An expected utility maximizer optimizes the following function:

• max_e [1-p(e)]*U(I -e) + p(e)*U(I – L – e)

The first order condition is:

• -p’*[U(I -e)-U(I - L - e)]=(1-p)*U’(I -e) + p*U’(I – L – e)

Ehrlich and Becker note that “[t]he term on the left is the marginal gain from the reduction in p; that on the right, the decline in utility due to the decline in both incomes, is the marginal cost.”

When we introduce an insurance market, the expected utility maximizer faces a new objective function.

• max_e,s ,s [1-p(e)]*U(I-e-s*π(e)) + p(e)*U(I – L – e + s)

Here s is the insurance benefit and π(e) is price of the insurance; s*π(e) is the insurance premium. Let U(0)=U(I-L-e+s) and U(1)=U(I-e-s*π(e)). The first order conditions now become:

• -(1-p)U’(1) + p*U’(0)=0
• -p’*[U(1)-U(0)] – (1-p)*U’(1)*[1+s*π'] – p*U’(0)=1

How does self protection change when insurance markets are introduced? According to Ehrlich and Becker “On the one hand, self protection is discouraged because its marginal gain is reduced by the reduction of the difference between the incomes and thus the utilities in different states, on the other hand, it is encouraged if the price of market insurance is negatively related to the amount spent on protection through the effect of these expenditures on the probabilities.”

If insurance companies are actually able to measure self-protection and can price insurance accordingly, then individuals will have some incentive to increase prevention in order to lower their premiums. If insurance is priced in an actuarially fair manner (i.e., π=p(e)/[1-p(e)]) we can show that premiums will drop when self-protection increases:

• ∂π/∂e=p’/(1-p)²<0

However, if insurance companies are not able to observe self-protection efforts, than it is likely that moral hazard will occur–self protection will decrease. In the words of the authors, “Self-protection would then usually be discouraged by market insurance–moral hazard would exist–because the main effect of introducing market insurance would be to narrow the differences between incomes in different states.”

• Ehrlich I, Becker G. 1972. “Market Insurance, Self-Insurance, and Self-Protection.” The Journal of Political Economy, 80(4), pp. 623-648.

What happens when your the government is run by those tax-and-spend, dovish, universal health care loving, welfare promoting big government Democrats? Is there a difference when the low tax, hawkish, drug company pawns, anti-equality, small government Republicans take over? Few would question that there are significant ideological differences between the two parties and that federal and state elections have a large impact on the direction this country will take. But do parties matter for local elections?

This is the question analyzed by Ferreira and Gyourko in their 2007 NBER working paper. The authors use a regression discontinuity frame work (à la Lee 2001, Lee 2007) to analyze the outcome of 4,543 elections in 413 cities between 1950 and 2005. The authors find that on the local level, party labels do not affect 1) the size of government, 2) the allocation of spending, or 3) crime rates. This is true despite the fact that the incumbent has a large political advantage.

Why would this be the case. The authors argue that Tiebout sorting can lead to fairly homogeneous preferences among residents. Thus, when mayors run for office, there is less room for idealism. Further, ‘big ticket’ questions such as abortion, national defense spending, and foreign policy are not decided on the local level and these ideological issues–which often dominate federal elections–are not important in national elections. For instance, the Republicans in general may be against allowing illegal immigrants to obtain citizenship, but New York elected two Republican mayors (Guiliani and Bloomberg) who were necessarily ‘pro-immigrant’ due to a constituency made up of many first and second generation immigrants.

• Fernando Ferreira, Joseph Gyourko (2007) “Do political parties matter? Evidence from U.S. Cities.” NBER Working Paper #13535.

Who has the best Economics blog of 2008? The Bayesian Heresy makes their selections. Topping the list is the UCSD professor Jim Hamilton’s Econbrowser blog. In 2006, the Bayesian Heresy named the Healthcare Economist as the #2 Specialized Economics blog.

Barack Obama wins Iowa and is predicted to win New Hampshire according to Gallup polls.  Then Hillary Clinton wins New Hampshire.  Why were Gallup poll predictions wrong?

The Statistical Modeling blog tries to make sense of this in their post “What was going on with the New Hampshire polls?“  The post gives three reasons why the Gallup polls could have been wrong:

1. The likely voter screen and its potential deficiencies.   The Gallup polls only count the opinions of people they deem to be “likely voters” and thus the polls may have incorrectly included or excluded people.
2. Problems in survey weighting, especially when Iowa turnout was so strange.  Surveys weight their responses in order that the poll results are more representative of the voting public.  The survey designers may have incorrectly weighted the observations.
3. Obama being black.  “Some people have a theory that people will lie in a poll and say they support the black candidate because they don’t want to seem racist, but then they actually vote for the white person.”

Development economists have long sought the answers as to why new innovations do or do not get implemented in developing countries. Giliches (1957) found that hybrid corn adoption has an S-shaped function over time. Other studies have found that an individual’s social network is the primary determinant of technology adoption. If your friends try out a new technology and it works, you will be more likely to hear about this advance if you have a large social network. Other economists blame credit constraints for the slow adoption of many farming technologies. A large up-front cost of some fertilizer or new seeds may be prohibitive, even if there is a high payback rate in terms of crop yield. Finally, it is possible that the “new and improved” technology may not be better. A pesticide developed in the West may work on American or European pests but may prove impotent against different other farm threats in other countries.

A paper by Elaine Liu, however, argues that there is another driving force which may explain technology adoption: risk preferences. To test this, Liu surveys Bt cotton adoption of farmers in the Henan, Shandong, Hebei and Anhui provinces in China. Bt cotton is slightly more expensive that regular cotton seeds, but farmers who use these new seeds spray 82% less pesticides than with the original seeds.

To test for risk aversion, Liu employs a Holt and Laury (2002) methodology but uses prospect theory to fit parameters of the individual’s utility functions. This allows individuals to be loss averse and also to use nonlinear probability weighting.

After controlling for various covariates, Liu finds the following results.

• Individuals with higher levels of risk aversion adopt Bt cotton later.
• Individuals with higher levels of risk aversion continue using higher levels of pesticide even though less pesticide is needed when Bt cotton is used compared to traditional cotton seeds.
• Farmers with more education were not found to adopt Bt cotton earlier, but once they did begin using the Bt seeds, they wisely used less pesticide.

Although Liu does not mention this, prudence may play a factor in these technology adoption decisions. Taking a sure loss from the higher price of Bt cotton may not outweigh the gain from decreasing the probability of crop loss.

By 2006, the adoption of Bt cotton was nearly 100% and it seems that Chinese farmers are reaping the rewards of this new technology. Once the farmers understood better the benefits of the new seed, risk decreased and farmers were more likely to adopt the new Bt cotton technology.

One of the biggest news stories this year is the collapse of the subprime mortgage lending market. Why did this happen? How much do we really know about subprime lending?

A working paper by William Adams, Liran Einav and Jonathan Levin examines the subprime market for automobile loans. The authors find that liquidity constraints are a major force in shaping the subprime loan market. They find that car loans spike in January through March. Why is this? Poor individuals often take out a loan against their tax rebates. These rebates can be very high–up to $4500–and these individuals will use these rebates to help finance a car purchase.

Finance charges for these loans are very high. Interest rates usually surpass 20% and often at the state-mandated 30% interest cap. A $11,000 loan paid off over 42 months would incur $6000 of finance charges.

Yet it seems that loan demand within the subprime market is not very responsive to interest rates. It is, however, much more responsive to the amount of the down payment.

We estimate that a 100 dollar increase in the minimum down payment reduces the probability that an applicant will purchase by 0.0301, while a 100 dollar increase in the car price reduces the purchase probability by only 0.0034. That is, a 100 dollar increase in the minimum down payment has the same e¤ect as a 900 dollar increase in car price. This can still be explained in the absence of liquidity constraints, but it requires a much higher annual discount rate of 427 percent.

The authors found evidence of both moral hazard and adverse selection in the subprime market. Moral Hazard means that individuals are more likely to default on large loans. Adverse selection occurs when high risk borrowers desire large loans. The authors find that when a loan amount increases $1000, the default rate increases 24%. Sixteen percentage points is due to moral hazard and the rest is due to adverse selection.

Are there any ways to mitigate these market failure problems? The authors find that “risk-based minimum payments play a substantial role in mitigating adverse selection in financing choices.” These factors lead to the observation that “in practice, observably risky buyers end up with smaller rather than larger loans because they face higher down payment requirements.” Modern credit scores give the lender more information regarding the credit-worthiness of the borrower and help to match high-risk borrowers with smaller loans.

• William Adams, Liran Einav, Jonathan Levin. (2007). “Liquidity Constraints and Imperfect Information in Subprime Lending” NBER Working Paper #13067.

It’s decision time for Medicare Part D purchasers. Seniors have until December 31st to make their Part D choice and this decision is not a painless one.

The Marketplace Money radio program recently reported (‘Deciphering Part D‘) that “the most popular policies have increased their prices substantially, especially Humana and United Healthcare, the ones that most of the people are in. Some of the policies’ prices have even doubled. So even though the average prices have only increased by about 14 percent, if you’re in one of the more popular plans, it’s really important to look at what your costs will be next year because you may want to change to a different policy.”

How can some plans double their prices yet still retain customers? Neo-classical economists would say that if the price of insurance at one company would rise, all seniors would switch to the cheaper plan and there would be a competitive equilibrium at the market price. Yet in the presence of switching costs, the insurance companies may be able to raise prices significantly without losing many customers.

Switching costs for Medicare Part D include the time consuming process of selecting from the hundreds of Medicare Part D plans. Children of seniors may also have to aid their parents in selecting a plan. Thus, if the price of my Part D insurance went up 16% while the rest of the plans went up 14%, I may decide to pay the higher price since I do not want to incur the search costs of finding a new Medicare Part D plan.

Companies such as Humana and UnitedHealth knew this would be the case. In the first year of Part D, these companies likely under-priced their insurance plans to attract customers. Once the customers had settled on their policies, they could more easily raise prices.

Despite the market inefficiencies caused by switching costs, this is not a reason to completely abandon a free market system. If the price increases of an individual company get too high, they will eventually outweigh the switching cost and the senior will move to a new plan. Further, information technology advances can help reduce switching costs. For instance, Medicare has a Prescription Drug Plan Finder that helps to estimate the cost of different plans depending on which prescriptions you are taking.

The N.Y. Times ran an interesting pair of articles Sunday regarding how economists “got it wrong.”

Conflict of Interest

Ben Stein (in “The Long and Short of It at Goldman Sachs“) comments on the economic analysis conducted by economist Jan Hatzius of Goldman Sachs. Dr. Hatzuis concludes that the sub-prime mortgage ‘crisis’ will not only hurt the stock market, but adversely affect overall growth. Is Dr. Hatzius’ doomsday scenario going to happen?

Mr. Stein believes Dr. Hatzius’ assertion “…is a conclusion that is an estimation based upon a guess.” Economists, especially macro-economists, have had a very poor track record predicting the future. This is likely because the entire U.S. economy is extremely complex and even if it were to be modelled, it would be non-linear in nature and subject to the consequences of chaos theory.

More troubling, is Mr. Stein’s hypothesis of why Dr. Hatzius’ analysis is gaining prominence:

Perhaps as a token of Dr. Hatzius’s genuine intelligence, which is fine. But to me, his paper seemed like a selling document in the real Wall Street sense of selling — namely, selling short. (Dr. Hatzius notes that he has long been bearish on housing, since faraway 2006, but I respectfully note that that is a lot different from predicting a credit catastrophe. The spokesman for Goldman also noted the company’s bearishness on housing since 2006. He also noted that in the recent past, Goldman Sachs has moved to a considerably larger short posture and that the firm is net short.)

…But what leaps out at me from this story is that Goldman Sachs was injecting dangerous financial products into the world’s commercial bloodstream for years.

My pal, colleague and alter ego, the financial manager Phil DeMuth, culled data from a financial Web site, ABAlert.com (for “asset-backed alertâ€?), that Goldman Sachs was one of the top 10 sellers of C.M.O.’s for the last two and a half years. From the evidence I see, Goldman was doing this for years. It might have sold very roughly $100 billion of the stuff in that period, according to ABAlert…

…The point to bear in mind, as Mr. Sloan brilliantly makes clear, is that as Goldman was peddling C.M.O.’s [Collateralized Mortgage Obligations], it was also shorting the junk on a titanic scale through index sales — showing, at least to me, how horrible a product it believed it was selling.

Dr. Hatzius likely honestly believes in his analysis, but one can not doubt that there is a serious conflict of interest being that Goldman Sachs pays his–likely very large–salary.

Do-gooders gone wrong

In an article on famine in Malawi (“Ending Famine, Simply by Ignoring the Experts“), economists once again got it wrong.

• World Bank Economists advised Malawi “…to adhere to free market policies and cut back or eliminate fertilizer subsidies, even as the United States and Europe extensively subsidized their own farmers.”  The result was Malawi has been dependent on food aid from rich nations and international organizations.
• Malwai’s solution was to begin subsidizing fertilizer to increase crop yield.  The result is that “… this year, a nation that has perennially extended a begging bowl to the world is instead feeding its hungry neighbors. It is selling more corn to the World Food Program of the United Nations than any other country in southern Africa and is exporting hundreds of thousands of tons of corn to Zimbabwe.”

Some claim that that the recent positive result was due to good rains over the last 2 years.  Nevertheless, the results are indisputable.  While I am generally in favor of more freer markets, here is one example of where economists got it wrong again.  Most World Bank economists are idealistic and want to improve the world for the poorest of the poor.  However, it seems that an international bureaucracy–despite having some of the smartest minds in the world on its payroll–is not doing a great job.

Conclusion

What should we take from these stories?  First, is that one must always be on the lookout for conflicts of interest that may bias a given piece of economic analysis.  Any one piece of economic analysis should not be sufficient to persuade you of the veracity of a theory; multiple analyses who reach the same conclusion are needed in order to have an adequate degree of reliability.  Secondly, top-down governing does not work, even if the people enacting policy are extremely bright economists.

This leads us to a new motto: Don’t always believe your local economist…except the Healthcare Economist, of course.

Where does an aspiring health economist look for journals relevant to the interdisciplinary field of health economics?  Which data sets are relevant for the empirical word a health economist would conduct?

If you’re looking for answers to these questions, check out the Resources page of my personal website.  The Resources page has a list of journals and data sets that health economists will find useful.

Can a state run petroleum company be as efficient as a private sector company? The answer is a resounding, “yes but…” It is possible that state-run petroleum companies can be efficient as long as they stick to the business of producing oil. Yet Tina Rosenberg’s “The Perils of Petrocracy” article in the N.Y. Times Sunday Magazine examines what has happened in the case of Hugo Chávez and Venezuela.

Chávez has siphoned off millions of dollars from Venezuela’s oil company, Petróleos de Venezuela S.A. (Pdvsa), for his own political uses. Much of the money has gone towards funding schools, medical clinics, and misiones for Venezuela’s poor. While this providing health and educational infrastructure for Venezuela’s poor is a laudable goal, it is unclear that conditions in Venezuela have improved.

“…the percentage of those living without running water and living in inadequate housing, as well as the number of young children not attending school, has scarcely budged in the last 10 years.”

Chávez heavy handed tactics have led to Pdvsa hirings based on political affiliation, not merit. Investment in oil rigs, maintenance, and other operational necessities has diminished during the Chávez era and it is likely that long-run oil production will steadily decrease. Pdvsa not longer published clear, S.E.C.-style financial reports regarding where funds are spent. Also, other governmental policies have lead to high inflation rates, leading to decreased investment in Venezuela. The cult of personality surrounding Chávez is growing and even spawning Chávez-emulating governors in Carabobo (see “An Imitator of Chávez“).

How is health care in Venezuela? While the Cuban physician-staffed misiones are providing more primary care to poor citizens, disinvestment in other forms of medical care has meant that Venezuela’s hospitals are “falling apart.”

What is the solution? While not as politically attractive as nationalization and spouting slogans such as “El Petróleo Es Nuestro,” privatizing the oil sector and extracting heavy taxes or royalties seems to be a much better solution. The tax revenue can be used to pay for social programs and the long run viability of oil production will remain high. One complication with privatization is that firms may bribe politicians in order to pay low taxes or reduce payments for mining rights below their fair-market value. Nevertheless, privatization is better than Chávez’s corrupt cronyism.

The winners of the 2007 Nobel Prize in Economics are: Leonid Hurwicz, Eric S. Maskin, and Roger B. Myerson.  The trio won the prize for their work on Mechanism Design.  See the Nobel Prize press release as well as the Scientific Background paper detailing exactly what is mechanism design.

The Economist’s View website provides a number of links to newspaper articles and blog posts regarding the 2007 Economics Nobel prize.  “Mechanism Design for Grandma” on the Marginal Revolution site gives a simple explanation of Mechanism Design Theory.

As an Applied Microeconomist who is generally skeptically of the practical importance of much of economic theory, I find Tyler Cowen’s post on the Marginal Revolution website particularly interesting:

No doubt mechanism design, and the general problem of inducing truth-telling, will be with us forever.  But how practical are these general results?  Or have the theorists simply provided us with cautionary notes and left the real applications to the context-specific world of practice?  Did these guys get at the real reasons why we don’t organize the entire economy as a second-price auction?

Part of me thinks: “Hey, let’s say Natasha wants Yana to tell her the truth about when she will clean her room.  This stuff isn’t useful!”

Another part of me thinks: “It is most important to get theory right.  These guys are brilliant.  Only the philistines demand that all scientific contributions have immediate applications.”

Some of you might argue: “These guys have already had a big impact on real world auctions and incentive schemes.”  In terms of the induced improvement in human welfare, I find that a difficult case to make.  The important progress has come from recognizing much simpler truths about incentives.

An explanation for the recent General Motors-United Auto Workers deal is pretty simple: it is a transfer of risk.  GM will set up a Voluntary Employee Beneficiary Association (VEBA) which will be controlled by the union.  According to the Detroit Free Press (” UAW ratifies”) GM will place about $30 billion dollars in the account which will pay for the health care benefits of GM retirees.  The benefit to GM is that it can now focus on cutting costs and improving quality in car production, rather than worrying about the risk of increasing health care premiums.  The health care inflation risk is now being transfered to GM retiree beneficiaries.  If health care costs in the future exceed the $30 billion in the VEBA, then GM retirees will have to pay for these costs out of their own pocket.

Why wold the UAW accept this agreement?  Although the UAW accepted increasing risk due to inflationary medical costs, it eliminated another type of risk: bankruptcy risk.  Because the VEBA is controlled by the UAW, GM retirees will still have funded health care even if GM goes bankrupt.  Thus, UAW retirees have eliminated the catastrophic risk (GM bankruptcy) in exchange for accepting increased risk of increasing health care costs.

I believe the VEBA will work out well for both sides.  The deal also may be the death knell for defined benefit programs.

• See also Joe Pauda’s analysis of the GM-UAW deal on Managed Care Matters.

The N.Y. Times has an interested article titled “Exploring Ways to Shorten the Ascent to a Ph.D.” The piece speaks of the difficulty of completing a Ph.D. and wonders whether a PhD should be considered more of a training exercise or a mandate for revolutionary research. An excerpt:

For those who attempt it, the doctoral dissertation can loom on the horizon like Everest, gleaming invitingly as a challenge but often turning into a masochistic exercise once the ascent is begun. The average student takes 8.2 years to get a Ph.D.; in education, that figure surpasses 13 years. Fifty percent of students drop out along the way, with dissertations the major stumbling block. At commencement, the typical doctoral holder is 33, an age when peers are well along in their professions, and 12 percent of graduates are saddled with more than $50,000 in debt.

Do students who attend better schools preform better academically? This is tautologically correct, but not very informative. What would happen if we randomly moved students from low quality schools to high quality schools? Would they do better?

Using the results from Chicago Public Schools randomized lotteries of elementary studies, Julie Cullen–my dissertation adviser–attempts to answer this question in her latest NBER working paper. It is a follow-up to a similar Econometrica paper written with Brian Jacob and Steven Levitt (of Freakanomics fame) which studied a similar subject but used data on high school students. Below is the abstract.

In this paper, we examine whether expanded access to sought-after schools can improve academic achievement. The setting we study is the “open enrollment” system in the Chicago Public Schools (CPS). We use lottery data to avoid the critical issue of non-random selection of students into schools. Our analysis sample includes nearly 450 lotteries for kindergarten and first grade slots at 32 popular schools in 2000 and 2001. We track students for up to five years and examine outcomes such as standardized test scores, grade retention and special education placement. Comparing lottery winners and losers, we find that lottery winners attend higher quality schools as measured by both the average achievement level of peers in the school as well as by value-added indicators of the school’s contribution to student learning. Yet, we do not find that winning a lottery systematically confers any evident academic benefits. We explore several possible explanations for our findings, including the possibility that the typical student may be choosing schools for non-academic reasons (e.g., safety, proximity) and/or may experience benefits along dimensions we are unable to measure, but find little evidence in favor of such explanations. Moreover, we separately examine effects for a variety of demographic subgroups, and for students whose application behavior suggests a strong preference for academics, but again find no significant effects.

• Cullen JB, Jacob, BA (2007) “The Effect of School Choice on Participants: Evidence from Randomized Lotteries” NBER Working Paper #13443
• Cullen JB, Jacob BA, Levitt S (2006) “The Effect of School Choice on Participants: Evidence from Randomized Lotteries” Econometrica, 74(5) p. 1191-1230.

In classical economics models, supply and demand curves create a unique market price. Anyone who has shopped around for a good deal, however, knows that there is often significant price dispersion, even for homogeneous goods. For instance, gas prices can often vary greatly within a single neighborhood.

On Monday I attended a seminar by Matthew Lewis regarding his paper titled “When do Consumers Search?” He claimed that most search models are able to create an equilibrium which includes price dispersion by balancing two opposing forces:

1. Increased price dispersion causes consumers to search more for better deals.
2. Increased consumer search leads to reduced price dispersion.

One research problem encounter by those who model consumer search behavior is that it is very difficult to measure search empirically. Mr. Lewis solves this problem by using internet traffic data for GasBuddy.com, a website dedicated to providing information on local gas prices throughout the U.S. and Canada.

Methods

Lewis uses the following econometric specification.

• ln(Reach)_t = α₁ + α₁date + α₂*Σ_{{k=0 to 4}} Δp_t-k ξ_t-k + α₃*Σ{_{k=0 to 4}} Δp_t-k (1-ξ_t-k) + …

The equation measures the impact of retail gasoline price changes (i.e.: Δp_t-k) on the GasBuddy traffic (i.e.: ln(Reach)). The term ξ_t-k is equal to unity if the price change is positive and equal to zero if the price change is negative. Using this method, Lewis can separately analyze the impact of positive and negative price impacts. Lags of 5-19 and 20-49 days are also included in the full specification.

Results

Lewis found that increased gas prices lead to increased consumer search. Decreasing prices, however, had no effect on consumer search. Lewis explains this by citing his observation that when prices increase, price dispersion increases, but when prices decrease, there is no change or a decrease in price dispersion. Thus, the asymmetrical pricing strategies by the retail gasoline firms may explain these search results.

On the other hand, a prospect theory may explain these results more intuitively. If individuals are loss averse, an increase in gas prices will be more painful to consumers and thus search will increase. A decrease in gas prices means and increase in utility relative to the reference point and thus consumers may not be as motivated to search. An income effect could also explain this finding. This micro-theoretic explanation could help to explain why retail gas station price dispersion occurs asymmetrically with respect to price increases compared to decreases.

• Lewis, Matthew S.; Marvel, Howard P. “When Do Consumers Search?” Sept 2007 Working Paper.

There is an interesting article from the Techdirt blog about “How patents skew medical research.” The blog post states “The monopoly power granted by patents pushes all research money into only things that can be patented, ignoring other possible cures, even if they can be both profitable and quite helpful.”

The post includes an example from the WSJ (“One Doctor’s Lonely Quest…“). Dr. Donald G. Stein found some evidence in the 1960s that the hormone progesterone help to heal brain injuries. Getting funding for more research to prove this finding was difficult. The WSJ writes:

Dr. Stein thought he had a big part of the answer to the question that had been vexing him for years. The medical establishment, however, largely shrugged off the results.

A naturally occurring hormone like progesterone, some forms of which have been available generically for infertility, is of little interest to drug makers. That’s because the substance probably can’t gain secure patent protection. That shut off a major avenue of potential funding for his research. “Big pharma likes more of an airtight protection,” says Todd Scherer, director of the Office of Technology Transfer at Emory, Dr. Stein’s current academic home.

For more information about patent protection, you can also read my review of Boldrin and Levine’s Against Intellectual Property book.

I just finished reading Burton Malkiel’s influential book A Random Walk Down Wall Street. Originally published in 1973, the book was one of the first to advocate for the creation of a “no-load, minimum-management-fee mutual fund that simply buys the hundreds of stocks making up the broad stock-market averages and does no trading from security to security in an attempt to catch the winners.” In other words, the book called for the creation of the index funds, which have become extremely popular.

The book talks about how difficult it is to pick winners, since by definition half of investors will do worse than the market and half will do better. As John Maynard Keynes stated:

Playing the stock market is analogous to entering a newspaper beauty-judging contest in which one must select the six prettiest faces out of a hundred photographs, with the prize going to the person whose selections most nearly conform to those of the group as a whole.

The book recommends a buy-and-hold strategy using dollar cost averaging. Some critics of this passive investment style claim that some individuals (e.g.: Peter Lynch and Warren Buffet) have been able to beat the market consistently. A reply would be that Mr. Lynch and Mr. Buffet have access to information which is not possessed by the typical investor. Also, mathematical probability states that when many people are betting on the market, their are bound to be a few people who have a string of winning years.

The book also talks about some historical investment crazes; or as Dr. Malkiel calls them, creating “castles in the air.” For instance:

• Tulip Bulb craze: Tulips imported into Holland from Turkey during the 17th century gained instant popularity. According to Investopedia: “The true bulb buyers (the garden centers of the past) began to fill up inventories for the growing season, depleting the supply further and increasing scarcity and demand. Soon, prices were rising so fast and high that people were trading their land, life savings, and anything else they could liquidate to get more tulip bulbs. Many Dutch persisted in believing they would sell their hoard to hapless and unenlightened foreigners, thereby reaping enormous profits. Somehow, the originally overpriced tulips enjoyed a twenty-fold increase in value – in one month!” Eventually the market crashed and individuals who had traded the value of their home for a single tulip realized the error of their ways.
• South Seas bubble: This financial institution was granted a monopoly over trade in the South Seas by the British government. The company was supposed to grow due to trade in slaves, as well as mineral wealth (i.e.: gold and jewels). The company even agreed to finance a large debt Britain incurred after a war. “Investors quickly saw what they perceived as value in the monopoly of the South Seas. Shares were quickly snatched up from the start… The management team of this company started hyping the stock, spouting illusions of grandeur to the investors.” After the stock price reached astronomical levels, the crash began. “Eventually word broke out that the management team had sold out completely. Investors were left holding the bag. Panic selling of the worthless shares immediately ensued. Fortunes were lost in a heartbeat.”

This book is a great read for any investor and I highly recommend it.

The Laffer curve is a compelling economic concept.  It claims that government revenue as a function of tax rates is shaped as an inverted-U.  This means that, at first, raising the tax rate from zero will increase tax rates.  However, there is some tax rate which maximizes government revenue (but not necessarily social welfare).  When tax rates are increased beyond this point, however, tax revenues decrease because as income taxes rise, the disincentive to work becomes sufficiently great that the higher per hour amount of tax receipts will be more than offset by the workers incentive to work less hours.

The theory is theoretically sound and elegant, but do economists actually know what the tax rate which maximizes government revenue will be?

The mathematician Martin Gardner claims not.  His satirical construct called the neo-Laffer curve (see image).  According to Wikipedia, “The neo-Laffer curve matches the original curve near the two extremes of 0% and 100%, but rapidly collapses into an incomprehensible snarl of chaos at the middle. Gardner based his curve on actual US economic data collected in a fifty year period by statistician Persi Diaconis.”

Gardner makes the sound point that the Laffer curves is very appropriate for theoretical analysis and as a pedagogical tool, but it does not sufficiently reflect reality in order for politicians to make tax policy based on the construct.

Why do the Orthodox Jews have so much political power in Israel? Why are third parties in the U.S. so weak? These phenomenon can be explained by the Banzhof power index. The index is calculated as follows. Let us look at the Israeli election in 2003 for the Knesset. Here are the voting results of the top 3 parties:

In the Knesset, the parties must form a coalitions which has at least a majority of the seats. In the case above, a majority would consist of a coalition with at least 30 seats. The Banzhof power index tells us the Shas (religious) party is equally powerful as the Likud (conservative) and Labour (liberal) parties even though the Shah party has less than half the number of seats as the Likud. Let us look at all the winning coalitions:

Likud-Labor; Likud-Shas; Labor-Shas; Likud-Labor-Shas

There are 4 possible coalitions. The groups which are pivotal are underlined in each coalition. We see that each group is pivotal 2 times, and thus each has a Banzhof power index of 2/6=1/3. This is why the religious parties in Israel are so powerful even though they receive a much lower percentage of the vote.

Why is this not a problem in the U.S? In the U.S. no coalitions need to be formed. A candidate must win a majority of electoral college votes and if they do not then there is a run off. The benefit of this system is that small third parties do not become more powerful than they deserve. On the other hand, however, the concerns of third party voters are often ignored due to the American election rules.

Sean Carroll, a physicist at California Institute of Technology, has some interesting comments regarding how economists use the utility function in a post titled “So what have you been maximizing lately?“  For instance, here are his musings on ‘rational choice’:

If the job of science is to describe what happens in the world, then there is an empirical question about what function people go around maximizing, and figuring out that function is the beginning and end of our job. Slipping words like “rationalâ€? in there creates an impression, intentional or not, that maximizing utility is what we should be doing — a prescriptive claim rather than a descriptive one.

Why do people, like myself, go through the grueling, boring, masochistic process of obtaining an Economics PhD. Well, according to Paul Kedrosky (“Self help“) getting a PhD can help you discover what you really like to do.

…what I found out when doing my thesis — and something I noticed in pretty much everyone I knew who at least started one — was that you mostly discovered what else you were interested in. Why? Because pretty much anything else is more absorbing than writing a 400-page Ph.D. thesis…

It turns out, it seems, that doing a Ph.D. (even if you drop out, which I generally recommend) is a great way to discover what you want in life, albeit it will likely have little to do with the Ph.D. itself.

There have been some interesting economics blog postings in recent weeks about the theory of the second best. Dani Rodrik of Harvard argues (“Why do economists disagree“) that economists can generally be viewed as first-best economists and second best economists. For instance, first-best economists would claim that all healthcare should be privately financed, with a private insurance system. Second-best economists will argue that the medical insurance market is far from perfect (e.g.: adverse selection and moral hazard issues, informational uncertainties). The second best economists may argue for government intervention. In the second best world, however, a narrowly guided policy may make things worse and not better.

Healthcare example

For instance, to correct the problem of adverse selection, economists may wish to create a single payer, government-run healthcare system. This government-run healthcare system will eliminate the problem of adverse selection and increase equality (good) but may create deadweight loss due to increased progressive taxation or inefficient procurement of medical services due to the influence of lobbyists (bad). Does the good outweigh the bad? The answer is-of course-it depends.

What about an employer mandate?  Again, this issue likely will eliminate problems of adverse selection and increase equality.  The mandate, however, will likely increase costs significantly for small business–small business have much higher load factors than large businesses–which could stymie economic growth and reduce GDP for the entire society.  Again, whether or not the good outweighs the bad in this situation is unclear.

Second-best Examples from the Economics Literature

The Economist’s Free Exchange blog (“Making the second best of it“) cites a paper by Lipsey and Lancaster (Rev Econ Studies 1956).  In the introduction, the Lipsey-Lancaster paper states:

It is well known that the attainment of a Paretian optimum requires the simultaneous fulfillment of all the optimum conditions. The general theorem for the second best optimum states that if there is introduced into a general equilibrium system a constraint which prevents the attainment of one of the Paretian conditions, the other Paretian conditions, although still attainable, are, in general, no longer desirable. In other words, given that one of the Paretian optimum conditions cannot be fulfilled, then an optimum situation can be achieved only by departing from all the other Paretian conditions. The optimum situation finally attained may be termed a second best optimum because it is achieved subject to a constraint which, by definition, prevents the attainment of a Paretian optimum.

The paper also gives an example from the trade literature.  What happens when a country decides to join a customs union (i.e.: free trade zone), such as NAFTA or the European Union?

…under these circumstances, a customs union will tend to raise welfare by encouraging trade between the member countries but that, at the same time, it will tend to lower welfare by discouraging the already hampered trade between the union area and the rest of the world. In the final analysis a customs union will raise welfare, lower it, or leave it unchanged, depending on the relative strength of these two opposing tendencies.

Another example of the problems of the second best is derived from the optimal taxation literature.

Consider a community of two individuals having different taste patterns [for goods X, Y and leisure]. The “government” of the community desires to raise a certain sum which it will give away to a foreign country. The community has made its value judgement about the distribution of income by deciding that each individual must contribute half of the required revenue. It has also been decided that the funds are to be raised by means of indirect taxes. It follows from the Corlett and Hague analysis that the best way to raise the revenue is by a system of unequal indirect taxes in which commodities “most complementary” to leisure are -taxed at the highest rates while commodities “most substitutable” for leisure are taxed at the lowest rates. But the two individuals have different tastes so that commodity X is substitutable for leisure for individual 1 and complementary to leisure for individual 2, while commodity Y and leisure are complements for individual 1 and substitutes for 2. The optimum way to raise the revenue, therefore, is to tax commodity X at a low rate when it is sold to individual 1 and at a high rate when it is sold to individual 2, while Y is taxed at a high rate when sold to I but a low rate when sold to 11. A second best optimum thus requires that the two individuals be faced with different sets of relative prices.”

But this ‘optimal’ solution violates the principal of anonymity.  If one was to invoke anonymity, this would impose another constraint and thus lead us to another ‘optimal’ solution.

As you can see, in a world filled with uncertainty, it is very difficult to make policies which are unequivocally welfare enhancing (especially in the health care setting).

Here are two interesting articles from the blog-o-sphere:

Cat Bonds

The NY Times has an interesting article about catastrophic risk (“In Nature’s Casino“). The article talks about how individuals such as John Seo and Karen Clark have helped to create a market for cat bonds.

The problem with catastrophes is that insurance companies have not been able to adequately diversify in the event of a natural disaster.

“But by their very nature, the big catastrophic risks of the early 21st century couldn’t be diversified away. Wealth had become far too concentrated in a handful of extraordinarily treacherous places. The only way to handle them was to spread them widely, and the only way to do that was to get them out of the insurance industry and onto Wall Street.”

Cat bonds are a solution to this problem. These bonds are basically insurance policies which are sold as bonds to investors. If a catastrophe does not occur, the investors earn returns generally far above market returns. If the catastrophe does occur, than usually most of the investor’s principal is wiped out.

Just another example of markets in action.

Political Dogs

Merrill Goozner of GoozNews has a very compelling report on The Most Costly Earmark in S-CHIP.

“Last week, I learned that the bill contains another unheralded earmark, also unrelated to children’s health. This one, too, funnels hundreds of millions of dollars to special interests. And unlike the hospital earmarks, which were a mere raid on the treasury, this earmark, given the Orwellian name “Quality Incentive Payments in the End Stage Renal Disease Program,â€? will subject hundreds of thousands of Americans on dialysis to unnecessary risk, and will in all likelihood lead to premature deaths.”

It looks like both Democrats and Republicans are equally adept at inserting their favorite earmarks into a bill. Goozner reports that the legislation earmarks $300m over the next 3 years towards rewards for clinics which reach quality benchmarks for treating Medicare’s End Stage Renal Disease (ESRD) patients.  Those clinics who have 92% of their ESRD patients with red blood cell counts over 11 g/dl will receive the bonus.

“The measure gives clinics a powerful incentive to continue using large quantities of one company’s drug – Amgen’s Epogen, which stimulates red blood cell production…Recent studies have shown that raising red blood cell counts over 12.5 grams per deciliter in dialysis and cancer patients increases the risk of heart attacks and premature death. Any clinic that raises 92 percent of its patients above 11 will probably have half its patients above 12 – the maximum allowable level on the FDA black box warning – and a sizable fraction above the 12.5 danger line.”

Goozner writes than Amgen hired a team of lobbyists who likely influenced the insertion of this earmark into the SCHIP bill.  Goozner’s thorough reporting has more details on the Epogen saga, which gives more evidence that one should be very weary of medical decisions dictated by politicians.

While almost all economists will argue that a single payer health care system is inefficient, many economists support the idea on redistributive ground. Taxing the young and healthy–either directly through taxes or by forcing them to buy non-actuarially fair insurance–and giving the money to pay for the medical care for the old and sick seems like the morally correct path upon which to proceed.

Megan McArdle of Asymetrical Information (now on The Atlantic Monthly website) has a series of posts (original post, “The morality of health care finance,” “Another bad argument…“) which questions this line of reasoning. She ponders whether or not the class of old and sick people, as a whole, are a more deserving class than the young and healthy. Ms. McArdle claims that the old and sick are a less deserving class. Here’s why:

• The old and sick are less needy than the young and healthy. “They have more assets and less poverty than any other group.”
• The old and sick are more fortunate than the young and healthy. Some of the young and healthy will not live to old age, whereas the old and sick have had the blessing of living a long time.

McArdle indirectly mentions the moral hazard of having a single payer insurance system; if you know someone else will foot the bill for your medical costs, you may decide to live a less healthy life style.

Some of Ms. McArdle’s critics argue that the young and healthy will someday be old and sick, and thus under a veil of ignorance argument, a single payer system is morally correct. This is similar to the PAYGO system that we have now for the social security system. Young workers pay for old sick people. One problem is demographic risk; if there are many old, sick people and few young healthy workers, the tax rates on the young will be extremely high. Further, one could avoid all these inter-generational transfers if each individual saved while they were young in order to finance their health care expenditures/insurance premiums when they are old.

The final blog concludes by wondering why “…Warren Buffet is entitled to have his prescriptions paid for by my dry cleaner simply because Warren Buffet happens to be in worse health”

The true benefits of a single payer system is that it provides a form of premium insurance. When individuals become sick, their health insurance company will pay for their care…for 1 year. Then, when the individual has to renew their policy, unless they have a group insurance plan, their insurance premiums will rise to reflect the greater expected medical expenditure level. This problem could be solved by having consumers choose long-term insurance contracts. Long-term insurance contracts, however, limit competition, since patients can not switch insurance plans if they received poor service.

There are many problems with the market for health insurance. I am not sure whether a single payer system is the answer or not, but Ms. McArdle’s arguments against the morality of a single payer system definitely add some doubt to claims that a single payer system is needed on moral grounds.

The Aaron Schiff’s 26Econ website has a ranking of the top economics blogs based on Technorati data. The Healthcare Economist comes in at number 38.

The Undergraduate Economist has three interesting maps to consider. The first draws each country with its size proportional to its PPP-adjusted public sector health spending; the second shows territory size proportional to the number of people 15-49 with HIV. The final map shows each country with its territory size proportional to the percent of worldwide private spending on health services spent there.  Sadly, health care spending is lowest in the countries with the highest incidence of HIV infection.

Many economists claim that Americans are spendthrifts and for good reason. The average American has over $9000 of credit card debt. Why don’t we act more like the Japanese and save?

A NBER working paper by Charles Yuji Horioka, Wataru Suzuki, Tatsuo Hatta claim that Japan’s high saving rates in the 70s and 80s were mainly due to demographics and not to the fact that the Japanese are inherently a culture of savers.

The Facts

In the 70s, 80s, and even 90s, Japan has ranked as one of the top OECD countries in terms of savings rates. In 1975 Japan ranked #1 in the OECD in terms of net household savings; in 1980 and 1985, Japan ranked #2, just behind Italy. Today, their saving rate has declined from 23% in 1975 to 4% in 2005.

Claim

The authors claim that the reason why the national savings rate was so high was due to demographics. In the 1970s and 1980s, a large share of Japan’s population was made up of working adults. The dependency ratio was exceeding low. Since working adults are savers, having a low dependency ratio will lead to high national savings rates.

In the near-term and intermediate-term future, Japan will age rapidly. Currently, 20.6% of Japan’s population is over 65, but this figure will rise to 35.7% by 2050. Since working adults are savers, while the elderly and young spend more than they earn, the authors predict the savings rate to fall precipitously in the near future. In 1975, the net household savings rate was about 23%. The net savings rate stayed above 15% until the late 1980s. By 2005, as the population has aged, the savings rate has fallen below 5%.

Conclusion

It seems that the Japanese are not such a frugal culture as Americans once though. It also turns out that most Americans (55%) have $0 credit card debt and that the median person with credit card debt only owes $2200 (according to the Bean Counter Blog). As usual, those who we hold up as idols are never really as good as we first think; those we demonize are typically not as bad as we first think.

Note

The authors wisely note that “Japan’s saving rate can be expected to decline sharply as its population ages. However, aging will also raise the saving rate of individuals due to the existence of a pay-as-you-go public pension system.”

• Charles Yuji Horioka, Wataru Suzuki, Tatsuo Hatta (2007) “Aging, Saving, and Public Pensions in Japan,” NBER WP #13273.

Greg Mankiw has a great post on Advice for Grad Students, with links to advice given by David Romer, Hal Varian, David Laibson and more.  Cochrane’s “Writing Tips for PhD students” is especially helpful for graduate students who are attempting to write scholarly articles.

In 2006, the National Assessment of Educational Progress (NAEP) conducted its periodic assessment of the quality of American high school students. What is unique about the 2006 “Nation’s Report Card” was that it was the first time that high school students were tested regarding the subject of economics. How did they do? Well, it depends on who you ask.

• The Wall Street Journal laments that”High Schoolers Aren’t Good at Economics.”
• On the other hand, the New York Times proclaims “12th Graders Show Better Grasp of Market Forces Than Expected on U.S. Economics Test.”

Since this is the first year the test has been conducted, no one is really sure how the students did. One can not compare the results to previous years’ totals.

What questions were the students asked? You can try out a few of the sample questions yourself.

• What happens to most of the money deposited in checking accounts at a commercial bank?
  1. It is used to pay the bank’s expenses.
  2. It is loaned to other bank customers.
  3. It is kept in the bank’s vault until depositors withdraw the funds
  4. It is paid to the owners of the bank as return on their investment.
• Suppose that the federal government initially has a balanced budget. Which of the following changes in government tax revenues and expenditures over time will definitely lead to an increase in the national debt?
  1. Tax increase, no change in Expenditures
  2. Tax increase, decrease Expenditures
  3. Tax decrease, increase Expenditures
  4. No change in Taxes, decrease Expenditures
• In the United States, which of the following forms of taxation currently represents the largest source of tax revenue for the federal government?
  1. Property Tax
  2. Sales Tax
  3. Corporate Income Tax
  4. Personal Income Tax
• Two countries are currently trading with each other. The countries agree to remove all trade restrictions on products traded between them. Which of the following is most likely to decrease?
  1. The variety of goods available
  2. The price of imported goods
  3. The quality of goods available
  4. The amount of imported goods

Answers:

b, c, d, b.

Sound too good to be true? Well, according to the Motley Fool website (“Best market“), Zimbabwe’s stock exchange returned 912% in 2006. The Mises Institute states that between January and the beginning of April 2007, the Zimbabwe stock exchange returned 595%, and looks to continue to be the top stock index in 2007 as well.

You of course have to invest in this market, right?

Not so fast. Zimbabwe’s economy is actually collapsing. According to the Mises Institute:

“Zimbabwe is in the middle of an economic disintegration, with GDP declining for the seventh consecutive year, half what it was in 2000. Ever since President Mugabe’s disastrous land-reform campaign (an entire article in itself), the country’s farming, tourism, and gold sectors have collapsed. Unemployment is said to be near 80%.”

So why is the stock market rising so fast? The answer is hyperinflation. The CIA World Factbook states:

“The official annual inflation rate rose from 32% in 1998, to 133% in 2004, 585% in 2005, and approached 1000% in 2006, although private sector estimates put the figure much higher.”

Thus, if the rate of return in a stock market is 912%, but the rate of inflation is 1000%, when you convert the investment made in Zimbabwean dollars (ZWD) into U.S. Dollars, you will actually be losing 8.8 cents on every dollar invested (assuming currency rates adjust perfectly for inflation and no other factors).

Economic Policy

Economist have often given countries advise as to how to manage their economy. Cut spending. Invest in infrastructure. Balance the budget. Borrow from the IMF. Borrow from the World Bank. Raise taxes. Lower taxes. Increase user fees. Privatize state-run companies. And so on. Some policy recommendations work in some situations and some work in others.

One of the few policy recommendations which always works is the following: don’t print money to finance government projects! Printing large amounts of money devalues a country’s currency, leads to hyperinflation, and greatly distorts investment and saving decisions. Yet Zimbabwe’s president Robert Mugabe is not heeding these warnings. In a recent Washington Post article (“…Print more Cash“), however, Mr. Mugabe vowed to print more money to finance his projects, despite the hyperinflation it is creating.

If I were you, investing in Zimbabwe is not my idea of a good bet.

“We want the protection the government provides, and we want freedom. Put those together, and what we really want is for our government, and the whole public sector, from firefighters to voluntary organizations, to be both responsible and responsive.”

I recently finished reading the book The Fox in the Henhouse: How Privatization Threatens Democracy by Si Kahn and Elizabeth Minnich. The book rails against the evils of privatization. As an economist, my default response is to believe that privatization is generally good. While the book does make some compelling arguments against privatization in certain industries, I am not compelled to call for a dismantling of the capitalist system.

I believe that the production of most goods and services should be done by the private sector. Competition between firms ensures that companies will not cheat or injure their customers; if they do, they will not be in business for long. Customer choice between firms acts as a disciplining mechanism to ensure that quality goods are produced at a reasonable price. In some sectors, monopolies form and consumers who wish to purchase a good or service have no choice other than to buy for the monopolist. While this of course is a sub-optimal scenario, it does not necessarily mean that a government takeover would improve the situation. When the government takes over an industry, it itself becomes a monopolists, and production decisions may be made for political rather than economic reasons.

Below, I look at a few different sectors, recounting some of the book’s arguments and adding my own comments.

Prisons

When prisons are privatized, the government outsources care of the prisoners to a private company. Between 1984 and 2005, private companies such as the GEO Group built 120,000 new private prisons. The book argues that private prison companies have lobbied politicians for stricter laws in order to increase the prison population and thus increase their profit. While it is true that private prison companies have an incentive to increase the number of people incarcerated, it seems that this fact could also be used to argue for smaller government which would be less influenced by lobbyists tactics.

I do agree with Kahn and Minnich that prisons should not be privatized. The government is the ones sending individuals to jail and is the ones who should care for them. Prisoners, of course, have no choice of the facility to which they are sent. Thus, if prisoners are abused, they can not switch prisons to one with better conditions. Prisons also have to enforce the prisoners constitutional rights, which is likely done more effectively by a public entity. Despite my agreement with the authors on this issue, I should point out the government run prisons do not have a stellar track record (e.g.: Abu Gharib, Guantánamo Bay, prisons in North Korea, the Gulag of Stalinist Russia).

Schools

The authors argue that education is a public good and thus should be provided by the government. They claim that charter schools preform worse than public schools (there is much debate about this subject).

I believe that everyone should be entitled to a good education. However, people should be able to choose which school they go to and that school can be either public or private. I am a big fan of voucher programs (e.g.: in Milwaukee). If the school you are attending is poor, you can switch schools and attend a better one. The competition for students should raise the quality of schools in the long run.

At the university level, private colleges have been a big success. Many of the most reputable universities are private (Harvard, Yale, Princeton, Penn). The University of Phoenix’s innovative distance learning program has been a rousing success as well. Thus, I conclude that there is a significant need for public financing of K-12 education, but having the government provide education services itself is highly inefficient.

[Disclaimer: I myself attended a public school through high school, but attended a private university (Penn). I am now a grad student at a public university (UC-San Diego)]
Natural Resources

Kahn and Minnich favor nationalizing natural resources, the approach Evo Morales of Bolivia is taking. They argue that these resources could fund many social services for the country. However, any profitable sector could provide significant funds for social services if its profits were expropriated. Why target only national resources? This is one reason why we have taxes, to help decrease income inequality. Taxation creates inefficiencies, but not as much as expropriation.

Using oil or gas for social services profits may be well-intentioned idea, but many leaders who are choking off democracy (see: Saudi Kings, Vladimir Putin, Hugo Chavez) have been using natural resource revenue as a political slush fund.

Healthcare

Healthcare is one area where some government oversight is needed. Governments need to help fund the treatment of diseases with significant externalities. For instance, the book cites a statement from Paul Farmer who claims that after public funding for TB specialist was cut, “TB incidence in Moscow was 27 per 100,000 population; by 1993 it had almost doubled to 50 per 100,000.”

The book also notes that fee-for-service physicians have an incentive to preform unnecessary medical procedures to maximize profits. The book does not mention that salaried government physicians may not have the same incentive to work hard that the FFS system provides.

Kahn and Minnich want health care to be free for everyone, but as anyone with common sense will tell you, “There’s no such thing as a free lunch.” Citizens pay for medical care, whether through insurance premiums, taxes or direct payment. Having free health care will induce individuals to over-use medical services which will then increase the cost to society.

Nevertheless, if redistribution from healthy to sick is as necessary a moral obligation as transferring resources from rich to poor, than some type of government intervention should be necessary. Exactly what form this government intervention should take, I do not know at this time.

Conclusion

Thus, whenever there is competition in a market, I believe private sector production of good and services is optimal. When the private sector has a monopoly in a sector, the evaluation is more opaque and should be treated on a case-by-case basis.

This week we have been looking at Expected Utility Theory (EUT) and its alternatives. Many people have challenged the empirical and theoretical basis for EUT. For instance, Matthew Rabin (Econometrica 2000) claims that EUT has implausible implications. For instance, if an individual would prefer $0 to playing a lottery with a 50% chance of losing $100 and 50% chance of winning $110, this implies that this same person would refuse a play lottery that had a 50% chance of losing $800 and a 50% chance of winning $2090. The person also would refuse to play a lottery with a 50% of losing $1000 and a 50% chance of winning an infinite amount of money.

What are the alternatives to EUT?

An article by Chris Starmer (JEL 2000) outlines some of the alternative theories to EUT. Earlier this week we discussed Prospect Theory so I will not review that theory now. Here are some other alternatives.

UCSD professor Mark Machina is well known for his work on generalized expected utility analysis. In Machina (Econometrica 1982), he extends creates the following expected utility framework:

• V(q)= Σ U(x_i)p_i
• where U(x_i)=∂[V(q)]/∂p_i;
  
• q is the vector of probabilities (p₁, p₂,…,p_n) corresponding to outcomes (x₁, x₂,…,x_n)

Machina showed that “…standard expected utility results (e.g.: risk aversion iff concavity of U(.)) also hold for the probability derivatives U(x_i;q)= ∂V(q)/∂p_i of smooth non-expected utility preference functions V(.), so that U(.;q) can be thought of as the ‘local utility function’ of V(.) about q. For example, the property ‘concavity of U(.;q) at every q‘ is equivalent to global risk aversion of V(.).” Hypothesis II of the Machina paper has indifference curves which “fan out” in the Machina triangle and imply that individuals “become more risk averse as the prospects they face get better.”

Regret Theory was developed by David Bell (1985) and Loomes and Sugden (1986). Loomes and Sugden create the following utility function:

• V(q)=Σ_i p_i[u(x_i)+D(u(x_i)-U)]

The function D(.) is a measure of disappointment. U is the prior expectation of the utility from the prospect. This theory takes into account that an agent may prefer to take $100 for sure rather than a lottery where 50% of the time one wins $200 and 50% of the time one wins $50, because the agent will fell much disappointment from receiving $50 if U=$100.

Rank-Dependent Expected Utility uses decision weighting–like those used in Prospect Theory–to give weights to different probabilities π(p). This model was first proposed by Quiggin (1982). Weights are attached “to any consequence of a prospect depends not only on the true probability of that consequence but also on its ranking relative to the other outcomes of the prospect…With consequences indexed…such that x₁ is worst and x_n best, we can state rank-dependent expected utility theory as the hypothesis that agents maximize the decision weighted form with weights for i = 1,…, n – 1 given by

• w_i=π(p_i+…+p_n) – π(p_i+1+…+p_n)
• w_n=π(p_n)

Thus, individuals are using decision weights to compare the probabilities of doing better than an outcomes x_i and x_i+1. This procedure allows for extreme outcomes to have either very high or very low weights. However, “a small change in the value of some outcome of a prospect can have a dramatic effect on its decision weight if the change affects the rank order of the consequence; but a change in the value of an outcome, no
matter how large the change, can have no affect on the decision weight if it does not alter its rank.”

Empirical Testing

Which of these theories is best? Hey and Orme (Econometrica 1994) try to test these various theories empirically to see which best fits the data. Numerous theories are tested and there is no clear cut winner, but the paper is a very interesting read.

• Chris Starmer (2000) “Developments in Non-Expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk” Journal of Economic Literature, Vol. 38, No. 2., pp. 332-382.
• Hey and Orme (1994) “Investigating Generalizations of Expected Utility Theory Using Experimental Data” Econometrica, Vol. 62, No. 6., pp. 1291-1326.

Yesterday, I talked about expected utility theory (EUT). Today I will write about one on the major departures from EUT: Prospect Theory. This theory was developed by Nobel laureate Daniel Kahneman and Amos Tversky (Econometrica 1979). The four key characteristics of prospect theory are:

1. Individuals use decision weights, π(p), rather than probabilities, p, when making decisions.
2. The value function is defined as deviations from a reference point. Thus, earning $100,000 this year is perceived differently for an individual earning $50,000 last year compared to one making $1 million last year.
3. Individuals are risk averse with respect to gains but risk loving with respect to losses. This implies that the value function is concave for gains, but convex for losses.
4. The value function is steeper for losses than for gains . This means that losses of $1000, hurt more than gains of $1000.

Why is there a need for prospect theory?

Much experimental evidence has shown that EUT does not only hold. Consider the Allais paradox. Which of the following lotteries would you choose:

• A: ($1m, 1) vs. B: ($1m, .89; 0, .01; $5m .10)
• C: (0, .89; $1m, .11) vs. D: (0,.90; $5m, .10)

Most people choose A and D. Yet it can be shown that under the EUT, these lotteries are mathematically equivalent and this leads to a preference reversal.

Another example is the following:

• A: (6000, .45; 0, .55) vs. B: (3000, .90; 0, .10)
• C: (6000, .001; 0, .999) vs. D: (3000,.02; 0, .998)

The majority of people surveyed here chose B and C. Again these A and C are two are equivalent lotteries as are B and D. The probability of winning in the latter pair is simply dived by 450. Thus, we see a preference reversal according to traditional EUT theory.

Also we see that people treat losses and gains differently.

• A: (6000, .25; 0, .75) vs. B: (4000, .25; 2000, .25; 0, .5)
• C: (-6000, .25; 0, .75) vs. D: (-4000, .25; -2000, .25; 0, .5)

Kahneman and Tversky find that 82% of people choose B over A, but 70% of people choose C over D. This implies that individuals are risk averse with respect to gains and risk loving with respect to losses.

Editing

Before utility functions are evaluated, Kahneman and Tversky say that choices are “edited.” The reason for this is 1) it helps to prevent obvious contradictions in which would occur if editing was not included, and 2) the editing process may more accurately reflect the process by which individuals make choices. Here are some of the ways which individuals edit:

• Coding: Outcomes are perceived as gains and losses with respect to a reference point. The reference point may be the status quo or it may be an expectation. For instance, if my monthly before-tax earnings are $2000 but my after-tax earnings are $1500, I may perceive this as a $500 loss from my expected income rather than a simple $1500 gain.
• Combination: Identical outcomes are simplified so that (100, .25; 100, .25; 0 .50) = (100, .50; 0 .50).
• Segregation: Risky components are separated from non-risky components. For instance, (500, .7; 100, .3) is decomposed into a sure gain of $100 and a lottery of (400, .7; 0, .3).
• Cancellation. This implies that when lotteries are compared, common outcomes are eliminated. “For example, the choice between (200, .20; 100, .50; -50, .30) and (200, .20; 150, .50; -100, .30) can be reduced by cancellation to a choice between (100, .50;-50, .30) and (150, .50; -100, .30).”

Evaluation

After editing, individuals make decisions according to the following utility function:

• Σ π(p)v(x)

Tversky and Kahneman (J Risk Uncert 1992) show that empirically, the function gives an inverted-S shape (see graph). “…for both positive and negative prospects, people overweight low probabilities and underweight moderate and high probabilities. As a consequence, people are relatively insensitive to probability difference in the middle of the range.” As mentioned earlier, the value x is evaluated with respect to a reference point. It is either a gain or a loss. For gains, v”<0 but for losses v”>0. Also, because the utility function is steeper for losses than gains, v(x)<-v(-x). For a graphical display of a prospect theory value function, see a picture from the U of RI economics website.

Another lottery experiment to support prospect theory is the following:

• A: (5000, .001; 0, .999) vs. B: 5
• C: (-5000, .001; 0, .999) vs. D: -5

Of those surveyed, 72% of people choose A over B, but 83% of people chose C over D. This would seem to imply that individuals are risk loving for gains and risk averse to losses. However, the bulk of the evidence has shown that this is not the case. As mentioned above, it seems more likely that people tend to overweight low probability events and underweight high probability events.

While Prospect Theory still is not as popular in mainstream economics as Expected Utility Theory. This is likely due to the added data needed regarding how an individual is editing, and what the individual’s reference point would be. Further, one wonders whether or not individuals become more ‘rational’ in the expected utility sense if they receive feedback from repeated games. Nevertheless, Prospect Theory seems to very accurately explain many of the findings in experimental economics and more work in this area is needed.

• Daniel Kahneman; Amos Tversky (1979) “Prospect Theory: An Analysis of Decision under Risk” Econometrica, Vol. 47, No. 2. Mar., pp. 263-292.
• Amos Tversky; Daniel Kahneman; (1992) ” Advances in prospect theory: Cumulative representation of uncertainty” Journal of Risk and Uncertainty, Volume 5, Number 4 / October, 1992, pp. 297-323.

How do economists understand individuals preferences when there is risk? Without risk, economists generally believe that individuals have a utility function which can convert ordinal preferences into a real-valued function. This real valued function is the utility function.

When risk enters into the picture, the expected utility theory (EUT) is used. This theory was developed by Daniel Bernoulli (1738) and expanded by John von Neumann and Oskar Morgenstern (1947). The EUT implies that utility functions have the following functional form:

• U=Σ_i p_iu(x_i)

Here there are i states of the world. In each state of the world, i, the individual receives x_i dollars. The probability of receiving x_i is p_i. An individual will prefer one risky lottery over another if their utility is higher in the first lottery compared to the second.

For example, let us assume that there are two lotteries. In lottery A you receive $100 for sure. In lottery B you have a 60% chance of receiving $200 and a 40% chance of receiving $0. Thus your utility in each case would be:

• U_A= 1*u(100)
• U_B= .6*u(200)+.4*u(0)

The lottery you choose will be based on your expected utility. Risk neutral individuals have linear utility functions, risk averse individuals have concave utility functions (u”<0) and risk loving individuals have convex utility functions (u”>0).
Do people actually make decisions according to these rules?

4 axioms

In order for people to make decisions according to the EUT framework, 4 axioms must hold. Let q, r, and s, be defined as the following lotteries: q=(x₁,p₁; x₂,p₂;…x_n,p_n), r=(y₁,q₁; y₂,q₂;…y_n,q_n) and s=(z₁,w₁; _z2,w₂;…z_n,w_n). Also, define aWb to mean that ‘a’ is weakly preferred to ‘b’.

1. Completeness. This entails that for all q, r: either qWr or rWq or both. If the answer is both, then I am indifferent between q and r.
2. Transitivity. If qWr, rWs then qWs.
3. Continuity. If qWr, rWs then there exists some p such that (q,p; s,1-p)~r.
4. Independence. This requires that if qWr, then (q,p; s,1-p)W(r,p; s,1-p) This means that I prefer tacos to hamburgers for lunch, I will not change my preferences between tacos and hamburgers if I am offered a salad as well. This is the axiom most commonly relaxed when alternatives to EUT are examined.

Are these axioms realistic? In the next post, I will review an article which describes “Developments in Non-Expected Utility Theory” where some of these axioms are violated.

There is a very interesting article by James Fallows in The Atlantic Monthly regarding the manufacturing sector in China, with a particular focus on Shenzhen. The article requires a subscription but the Finance Famulus and The Huffington Post websites offer an excerpts.  There is slide show on the Atlantic website for free, however, which also summarizes the article.

Although a little out of date, I came across a recent rankings of U.S. Economics departments. The paper (“Rankings of U.S. Economics Departments“) is written by Richard Dusansky and Clayton J. Vernon and was published in The Journal of Economic Perspectives in 1998. The rankings are as follows:

As you can see from the scores, my school (UC-San Diego) ranks 9th. Rankings from EconPhD.net have UCSD at number 21 (worldwide), but the most recent U.S. News and World Report Economics Department rankings have UCSD at #10 in the nation. Also a study in Science Watch put UCSD as the 5 th highest impact research institution in the nation from 1995-2005 for business and economics and the 2005 rankings from The Chronicle of Higher Education rank UCSD as #9 in Economics.

On The Library of Economics and Liberty website, there is an interesting article from a Friedrich Hayek’s 1945 AER paper (“The Use of Knowledge in Society“). The paper begins with a discussion of scientific compared to practical knowledge (i.e.: the knowledge of the particular circumstances of time and place).

“…scientific knowledge, occupies now so prominent a place in public imagination that we tend to forget that it is not the only kind that is relevant. It may be admitted that, as far as scientific knowledge is concerned, a body of suitably chosen experts may be in the best position to command all the best knowledge available—though this is of course merely shifting the difficulty to the problem of selecting the experts”

When academics create economic models, they often assume that practical knowledge is a given. ‘Perfect information’ is a common economic assumption. When finding an equilibrium, economists can calculate the exact quantity of good for a given demand and supply curve. This equilibrium, of course, assumes that there will be no change in supply or demand in the future. Hayek explains:

“One reason why economists are increasingly apt to forget about the constant small changes which make up the whole economic picture is probably their growing preoccupation with statistical aggregates, which show a very much greater stability than the movements of the detail. The comparative stability of the aggregates cannot, however, be accounted for—as the statisticians occasionally seem to be inclined to do—by the “law of large numbers” or the mutual compensation of random changes.”

I am particularly skeptical of macro-economists who claim to have found the steady state equilibrium. While this finding may be true mathematically, a steady state theoretical solution within a world empirically found to be in a constant state of flux is of limited use. Hayek continues:

“If we can agree that the economic problem of society is mainly one of rapid adaptation to changes in the particular circumstances of time and place, it would seem to follow that the ultimate decisions must be left to the people who are familiar with these circumstances, who know directly of the relevant changes and of the resources immediately available to meet them.”

In reality, knowledge, especially practical knowledge is broadly diffused throughout society. Hayek continues on in the essay to rail against the evils of centralized planning and “marvels” and the information imparted through the capitalistic price mechanism. This article is very interesting and certainly deserves a thorough read through the entire article.

• Hayek, Friedrich; (1945) “The Use of Knowledge in Society” American Economic Review, XXXV, No. 4, Sept., pp. 519-530.

In the forthcoming days, I will be summarizing some of the lectures given at the European Science Days summer school in Steyr, Austria. On the first day, there was an interesting lecture by Louis Eeckhoudt about risk and pain disaggregation.

Most individuals are familiar with the concept of risk aversion. However, the lecture spoke extensively regarding the issue of prudence, presented in a paper by Kimball (1990).

Example

Which lottery would you prefer?

• In lottery A you have a 1/4 chance of getting 0 € and a 3/4 chance of getting 2000 €.
• In lottery B you have a 3/4 chance of getting 1000 € and a 1/4 chance of getting 3000 €.

What did you choose? Be honest…

Most people prefer lottery B. Why? The expected value and variance of the two lotteries are identical. However, the skewness of lottery B is positive, but is negative for lottery A. If people are prudent, they choose lottery B. Mathematically, prudence occurs if the third derivative of the utility function is positive (U”’) is positive. Intuitively, people would rather have an upside risk with small probability than a downside risk with small probability even if the mean and variance of the two lotteries are equal.

Dr. Eeckhoudt also introduced the concept of temperance. An individual is temperate if an an exogenous increase in one risk leads them to reduce risk in other areas. Applying this to alcohol, a temparate person would reduce their wine consumption as their beer consumption increase in order to moderate their aggregate risk of getting drunk. Mathematically, temperate individuals have a utility funciton where the fourth derivative (U””) is negative.

Applications to Health

Dr. Eeckhoudt spoke about the well known phenomenon that risk averse people would like to purchase some sort of insurance. If possible, they will self insure. This differs from self-prevention. Let us look at two examples:

• Self insurance: With probability p, you will become sick and have a utility of x-L(e)-e. With probability 1-p, you will be healthy utility x-e. In this example, by exerting effort, e, you can decrease your health loss L. Thus, the more effort you put forth, the closer will be the two utility levels in each state and thus risk will be dimished.
• Self-prevention: With probability p(e), you will become sick and have a utility of x-L-e. With probability 1-p(e), you will be healthy and have utility x-e. In this example, by exerting effort, e, you can decrease your the probability of becoming sick, p(e). The key insight from Dr. Eeckhoudt was that more prudent people have a lower level of self prevention!

This is certainly an important societal issue since prudence may decrease healthy behaviors such as self-prevention measures against sickness (e.g.: excercising, quitting smoking, immunizations).

Multi-dimensional prudence
Dr. Eeckhoudt underlying message was that if people prefer to disagregate their pain/risk level, rather than combining losses or risk into a single time period or payoff, this has interesting implications. Let us look at prudence in the mutli-dimensional case.

Each individual recieves utility from income, x, and health, h. The variable s represents sickness and e is a zero mean stochastic term which one could interperet as income risk. Which of the following lotteries should people prefer?

• In lottery A you have a 1/2 chance of being healthy and having a risky job (x+e,h) and 1/2 chance of having having a safe job but getting sick (x,h-s).
• In lottery B you have a 1/2 chance being sick and having a risky job (x+e,h-s) and a 1/2 chance of being healthy and having a safe job (x,h).

A prudent person will prefer lottery A to lottery B. In lottery B, sickness and risk are concentrated into one state, where as the risk/losses are disaggregated or spread between the two states.

What is more important: economic theory or testing these theories empirically? In her paper in the Economists’ Voice, Barbara Bergmann calls for “A New Empiricism” in the field of economics.

For instance, the assumption that individuals are rational decision makers may be hard to substantiate empirically.

The researchers [Daniel Kahneman and Amos Tversky] found that in many cases people making choices depart from the behavior that economists had posited as rational. However as Vernon Smith, who developed the field of experimental economics, recently pointed out, it may be that the economists’ notions of what is rational in various contexts needs a reality check.

Gary Becker claims that markets should eliminate racial discrimination. If a company decides not to hire individuals of one race, it will be put at a competitive disadvantage compared to non-racist firms. While markets may work to reduce discrimination somewhat, they definitely do not eliminate it.

Economists have studied the extent of racial discrimination in the labor market by sending out carefully matched black and white “testersâ€? to answer ads for job vacancies, so as to tally differences in treatment. In another study, testers who differed by race and sex but were coached to use similar bargaining tactics were sent out to dealerships to bargain for new cars. In these studies, highly significant differences in treatment by race and sex were found—-non-whites and women were disadvantaged compared to white males.

Dr. Bergmann’s article calls for a logical change in economists’ thinking to focus more on empirical truths of their theories rather than their theoretical elegance.

If you’re an economist and in need of a laugh, check out the Stand-up Economist’s Principles of Economics, Translated on YouTube.

Is their a difference between micro-economists and macro economists?

• “The difference of course being that micro economists are people who are wrong about specific things, and macro economists are wrong about things in general.”

As my colleague Mike Ewens wrote to me: “Monopolists hate competitors and have to use the government to keep them away.”

An example that takes center stage can be found in a recent Chicago Tribune article (“AMA takes on Retail Clinics“) . Some doctors have asked the AMA to ban on in-store clinics currently being opened by companies such as Wal-Mart and Walgreens.

Why would doctors want to do this? Likely this is to protect their ability to charge high prices to their patients. How can they justify their demands to the public? They claim in-store clinics put patient’s health at risk.

The article concludes:

“We would be disappointed if the AMA adopted a policy that is counter to what patients are demanding, which is more accessible and affordable health care that reduces overall costs,” Walgreens spokesman Michael Polzin said in a statement. “It would be hard to argue against those principles. The bottom line is, retail clinics are improving health-care access and health outcomes while keeping the patient’s doctor informed as the patient desires.”

I see no reason to outlaw in-store clinics. Giving consumers more choice is always a good thing.

What’s does a DDD mean for a PBM? What is a QALY? What is the difference between ‘face validity’ and ‘construct validity’?

The Pharmacoeconomics journal has a Glossary of Terms used in Health Economics which are very useful for anyone who wishes to disentangle to the jargon used in this field.

Giving corporate executives bonuses based on the performance metrics of the company they manage is one way to incentivize managers to increase profits, sales, company stock price or any other financial measure. But is this the best way to run a company?

In 1985, Paul Healy wrote prescient paper of how corporate executives can alter accounting practices to maximize their bonus payments. Unlike prior articles, Healy claimed that executives will have incentives to both increase and decrease stated earnings by choosing the timing of discretionary accruals.

Let us look at a bonus compensation scheme where executives receive a bonus based on the pre-tax earnings of the company, whenever they exceed a specified lower bound L. Further, bonus payments are also assumed to be capped at an upper limit of earnings U. Thus we have that bonus payments are equal to:

• B=p{min[U, max(E-L,0)]}

Thus when earnings, E, are below L, the executive receives no bonus. When earnings are between L and U, the executive receives a payment of p(E-L). If earnings are greater than or equal to U, the bonus is capped at pU.

Healy found that one easy way to change earnings between different time periods is to alter the timing of discretionary accruals. For instance, if accountants believe there is a non-preforming asset that they will need to write off in the six-month period, managers can instruct accountants whether to write off the asset in the current quarter or the subsequent quarter. When I worked at GE, managers would alter sales and inventory accruals in order to meet their quarterly goals. While these changes were not illegal (when to charge an accrual is a subjective decision), the timing was heavily influenced by middle manager incentives.

In the Healy paper, the author showed that when earnings, E, are below the lower limit L, managers have an incentive “to take a bath” by charging income-decreasing accruals in the current period. This way, income in the subsequent period will be higher and they will not be losing any bonus income in the current period since they are already below the lower bound, L. Managers with earnings well above the upper limit U, also have an incentive to shift earnings from the current period to subsequent periods. Those with earnings between the upper and lower limits do have an incentive to use income-increasing accruals in the current period in order to maximize their bonus.

• Healy, Paul M. “The effect of bonus schemes on accounting decisions,” Journal of Accounting and Economics, vol 7, pp. 85-107.

Monetary incentives improve performance. This statement is almost gospel in the economics field. For instance, if I pay all my blog readers $1 for each time they visit this website, it is likely that the traffic on Healthcare Economist will increase dramatically. Sales staff compensated on a 100% commission basis often sell more items than sales individuals paid on a salaried basis.

Uri Gneezy (currently at UCSD’s Rady School of Management) and Aldo Rustichini conducted 2 experiments to show that paying more does not always improve outcomes. Below are a description of the two experiments and their results.

Experiment 1: University of Haifa Test

Undergraduates at the University of Haifa were asked to answer 50 questions from an IQ test. The students were separated into 4 groups, each of whom was paid 60 shekels (about $15) to participate .

• Group 1: This group was asked to answer as many questions as they could.
• Group 2: This group was paid 0.10 shekels (about 0.025 USD) for each question answered correctly
• Group 3: This group was paid 1 shekel (about 0.25 USD) for each question answered correctly
• Group 4: This group was paid 10 shekels (about $2.50 USD) for each question answered correctly.

Unsurprisingly, groups 3 and 4 preformed the best. It was found, however, that group 1 scored better than did group 2. This finding holds even when the 4 groups were compared based on the top and bottom quintiles.

Experiment 2: Charity Work

One hundred eighty high school students were divided into 3 groups during their annual charity drive. Students went door to door to solicit contributions for various chartitable organizations.

• Group 1: This group was was given a motivational speech about the importance of the activity.
• Group 2: This group received the speech as well as a payment of 1% of donations collected.
• Group 3: This group received the speech as well as a payment of 10% of donations collected.

Surprisingly, group 1 preformed the best, while group 2 preformed the worst.

Authors’ explanation

The authors believe that their are two types of motivation: intrinsic and financial. Offering small financial rewards will reduce intrinsic motivation and only offer mild financial motivation. Offering large financial rewards will also decrease intrinsic motivation, but will strongly stimulate financial motivation. The authors state:

“The main conclusions of these studies were that positive rewards, in particular monetary rewards, have a negative effect on intrinsic motivation. If a person is rewarded for performing an interesting activity, his intrinsic motivation decreases. The negative effect is significant only if the reward is contingent on the performance; subjects who are paid a fixed positive amount, independent of their performance, do not display reduction in intrinsic motivation.”

• Gneezy and Rustichini (2000) “Pay enough or don’t pay at all” QJE, 115:3, pp. 791-810.

What is the optimal asset allocation?  Of course the answer to this question depends on where you are in life and your tolerance for risk.  A retired person who is 70 years old likely should have a higher percentage of their assets invested in money market funds and bonds than a 35 year old with most of their career ahead of them.

For those with a relatively long time horizon, I recommend investing heavily in equity and bond index funds.  Why index funds?  Eugene Fama, one of the intellectual father’s  of the efficient market hypothesis, said “I take the market efficiency hypothesis to be the simple statement that security prices fully reflect all available information.”  From Wikipedia:

The [efficient market] hypothesis implies that fund managers and stock analysts are constantly looking for securities that may out-perform the market; and that this competition is so effective that any new information about the fortune of a company will rapidly be incorporated into stock prices. It is postulated therefore that it is very difficult to tell ahead of time which stocks will out-perform the market. By creating an index fund that mirrors the whole market the inefficiencies of stock selection are avoided.

Paul Merriman’s Fund Advice website is an excellent resource for those who are interested in investing in index funds (that’s a tongue twister).  His article on the “Ultimate Buy and Hold Strategy” is particularly enlightening.  Mr. Merriman also gives some model portfolios for various fund groups.  I prefer the Vanguard funds due to their relative low expense ratios.  While the Fund Advice website recommends 40% bonds, I believe that this is pretty conservative for young investors (disclaimer, I am 27 years old).  Thus, a 20% bond allocation should be sufficient.  As I noted before, you should put some cash put into a money market fund for emergencies and to plan for large expenditures which you expect to occur in the next year or two.  The amount of money to put in the money market depends on your own personal situation.  Also, I abstract from any mention of home purchasing as an investment, even though for many people a large portion of their savings is tied up in the equity of their house.

My model portfolio is show below.  All funds are from the Vanguard group, but you can create a similar portfolio with funds from other mutual fund groups.