Economics – General

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Although executives and managers lead the way, in large part, the answer is doctors.  See the chart below.


Sources:

  • John Bakija, Williams College ”Jobs and Income Growth of Top Earners and the Causes of Changing Income Inequality: Evidence from U.S. Tax Return Data.” November 2010, Working Paper.
  • Hat tip: Mother Jones.

 

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Suppose you look at health care spending in two different regions and observe a significant difference.  You may want to know what the cause of this difference is.  Is it because one region has a mix of people who are sicker; or is because the reason treat patients with a given disease more intensively?

One way to answer this question is to use the Oaxaca decomposition.  This approach was originally formulated by Ronald Oaxaca. This document provides a nice overview of how to use the Oaxaca Decomposition and I apply that framework to the health spending case.

Differences in Health Spending

Assume that there are two regions: Region A and Region B. The spending for the two regions can be modeled using a linear regression framework:

  • YA = βAX + εA
  • YB = βBX + εB

The Y term represents spending and the variable X represents the patient’s health status. Health status could be measured as a vector of factors or as a single indicator (e.g., healthy or sick). The term β describes much an area spending on medical resources to treat a patient with a health status of X. Thus, average difference in spending per person the two regions is:

  • YA – YB = βAXA – βBXB

where XA is the average case mix in the area.

Determinants of Health Spending Differentials

Now the question is whether case mix or spending practices conditional on case mix is the key driver of the differences in spending between regions A and B. One can differentiate these two components using the following Oaxaca Decomposition:

  • YA – YB = ΔXβB + ΔβXA
  • YA – YB = ΔXβA + ΔβXB

In the first equation, the differences in health status (X‘s)are weighted by the coefficients for region B and the differences in the coefficients are weighted by the X’s from region A, whereas in the second, the differences in the X‘s are weighted by the coefficients of from region A and the differences in the coefficients are weighted by the X‘s of from region B.

There are basically three factors that effect health spending in the region: i) differences in health status across regions ii) differences in treatment patterns conditional on health status, and iii) the interaction of health status and conditional treatment effects. One can see this clearly below:

  • YA – YB = ΔXβB + ΔβXB + ΔXΔβ
  • YA – YB = H + T + HT

The equations above show the health status effect (H), the treatment effect (T) and the interaction (HT).

The specification chosen for the Oaxaca decomposition determines whether the interaction effect is placed with the health status effect or the treatment effect.  More precisely:

  • YA – YB = ΔXβB + ΔβXA = H + (HT + T)
  • YA – YB = ΔXβA + ΔβXB = (H+ HT) + T

In effect, the first decomposition specification incorporates the interaction term with the treatment effect whereas the second specification places the interaction term together with the health status effect.

Sources:

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I am currently attending the American Economic Association (AEA) Annual Meeting in Chicago.  The Presidential Address was given by Bengt Holmstrom (Massachusetts Institute of Technology) on “The Nature of Liquidity Provision: When Ignorance is Bliss.”

Although there are numerous presentations on health care, such as the Health Insurance and Health Care Practice seminar lead by Amy Finkelstein. Other sessions of note include:

  • The 2006 Massachusetts Health Care Reform
  • Children’s Health and Education in China
  • Selection and Moral Hazard in Health Insurance
  • Behavioral Economics and Health
  • The Dynamics of Health and Wealth among the Elderly
  • Medicare and Prescription Drugs
  • What Determines the Performance of US and International Healthcare?

The full schedule is available here.

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Although mainly discussing the quality of economics blogs focused on Macroeconomic issues, the Economist endorsed the blog-o-sphere as a productive forum for intellectual debate.  To give it some historical context:

Previous publishing revolutions, such as the advent of printing, prompted similar concerns about trivialisation and extremism. But whatever you think about the impact of blogging on political, scientific or religious debate, it is hard to argue that the internet has cheapened the global conversation about economics. On the contrary, it has improved it.

Sure, writing an economics blog improves the quality of intellectual debates, but why do bloggers do it?  Blogging takes time and resources away from other pursuits (e.g., publishing, other work, leisure).  For only a few blogs does the ad revenue earned make up for the time spent working on the site.

One reasons blogging is attractive is that it helps the reputation of the blogger.

Research (by two blogging economists at the World Bank) suggests that academic papers cited by bloggers are far more likely to be downloaded. Blogging economists are regarded more highly than non-bloggers with the same publishing record. Blogs…have also given voice to once-obscure scholars advancing bold solutions to America’s economic funk and Europe’s self-inflicted crisis.

If blogging can help promote the intellectual debate of a boring topic like macroeconomics, imagine what it is doing for the much more interesting (in my completely unbiased opinion) debates surrounding health economic issues.

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Lions are among the most awe-inspiring animals around.  Their regal manes have inspired many and have been the source of numerous Disney cartoon characters.

The question is, how does one protect the animals?  In Namibia, the answer has been allowing hunters to kill them.  Hunting these animals has the obvious drawback that it decreases the number of these animals alive in the short run.  Further, most hunters prefer hunting adult male lions.

A male lion needs six years to establish himself in a pride and rear a new generation. Overhunting leads to continual turnover in the pride: when a new male takes the throne, he tends to kill the old crop of cubs so he can father his own. But when I asked if he would support a ban on trophy hunting, even Packer demurred.

However, hunting may save the animals.  Hunters pay thousands of dollars to have the chance to hunt these animals.  Villagers can profit from these hunts.  Thus, they have the incentive to allow the hunting of these animals, but not to the degree that this asset is completely used up.  Furthers, villagers themselves may want to hunt the animals themselves if they trample their crops.  If they are valuable assets, however, the villagers will have an incentive to protect them.

Counterintuitively, hunting may be the only path for lions to survive.

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We must have a strategy that regulates the financial system as a whole, in a holistic way, not just its individual components.

  • Ben S. Bernanke, “Financial Reform to Address Systemic Risk” at the Council on Foreign Relations, Washington, D.C., March 10, 2009

 

In a 2010 short paper, Brunnermeier, Hansen, Kashyap, Krishnamurthy and Lo (2010) argue that the field of economics has not adequately examined the topic of systemic risk. One of the reasons for this is that systemic risk is difficult to observe and quantify.  The Office of Financial Research (OFR) is President Obama’s attempt to fill this gap in knowledge.

Even though systemic risk is poorly measured, that does not mean that economists haven’t thought of ideas to combat systemic risk. The Fed Chairman’s quotation citing the need for holistic regulation is one approach. Is a holistic approach to regulation a good thing? Today, I give my 2 cents.

Merits

Financial and economic market are complex entities. Creating multiple government bodies where each one only regulates a piece of a given market can often be suboptimal. An individual agency may be in charge of making a given financial instrument safer or more transparent. Even if they government body succeeds in their mission, their regulations may create unintended consequence. For instance, another, more volatile, less transparent, unregulated financial instrument is created. Or the regulation could have an adverse effect on real markets. Having a single entity regulate all financial markets in an integrated fashion seems like a promising idea.

Problems

However, regulation generally requires more specialized knowledge than any one agency can maintain. For instance, credit default swaps are complicated entities. Regulators must have specific knowledge in order to properly regulate these instruments. Having a single body regulate all financial markets may create an entity with a wide breadth of knowledge but little depth. Further, if the regulatory scheme created by the central planner is poorly constructed, investors may have no other markets from which they can seek more rational regulation. If regulation by some of the government bodies is successful, investors could migrate to investments in more rationally regulated sectors (although this shift from well-regulated to poorly-regulated markets is a distortion in and of itself).

Motivation

In addition, one has to question the Chairman’s motivation for expanded regulation. He may have the best interests of the country at heart; integrated regulation may be the best mechanism through which one can decrease systemic risk. However, Dr. Bernanke is not an unbiased observer. Centralizing regulatory control increases the power of the Fed, the and the prestige of Dr. Bernanke. Thus, the desire to centralize regulation may not be a completely unbiased opinion.

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Two months ago I was standing in Stockholm’s Stadshuset (City Hall).  Soon, Thomas Sargent and Christopher Sims will be there as well.  The pair, however, will be accepting the 2011 Nobel Prize in Economics.

Although I am not a macroeconomist myself, Marginal Revolution has a good description of the pair.

My old professor, Jim Hamilton of UCSD explains macroeconomic impulse response functions which Sims helped develop.

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It is significant that none of the most passionate advocates of aid for Africa are African.  Aid can speed up development that people have already decided to carry out for themselves and have the capacity to do.  It is also essential for vaccination campaigns and for ARVs to combat HIV/AIDS.  Emergency aid is obviously vital to help the victims of war or natural disasters, but that is as true in Surrey as in Somalia.  Small amounts of aid can also work well in local contexts.   But aid from the outside cannot transform whole societies, whole countries.  That can only come about through producing things and trading them or doing something someone else wants to pay for.  Ironically, it is the capitalist West that still sees Africa as a continent that needs aid, while Communist and former Socialist governments like China and India see it as a business opportunity.

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Can health care productivity be increasing even as costs are rising so fast?  This may be the case.   One study by Aizcorbe and Nestoriak (2011) examines this phenomenon.

Using retrospective claims data for a sample of commercially insured patients, we find that, on average, expenditures to treat diseases rose 11% from 2003Q1 to 2005Q4 and would have risen even faster, 18%, had the mix of services remained fixed at the 2003Q1 levels.  This suggests that fixed-basket price indexes, as are used in the official statistics, could overstate true price growth significantly.

Much of the decrease in cost to treat specific conditions come from a shift of patients from inpatient care to outpatient surgical centers.  The question is, was this change a one time productivity gain, or does the health care system have other options for improving productivity (in the sense of reducing cost for the same quality).  It could be the case that Health IT and electronic medical records could produce synergies.  Alternatively, more intensive use of physician assistants and nurse practitioners could reduce the cost of treating many conditions.  We will see what the future holds.

Notes: The authors analysis uses the Symmetry grouping algorithm to define episodes of care.  By using the groupers, the authors are not required to have extensive medical knowledge to perform this analysis.   On the other hand, because the groupers are proprietary, the algorithms can be seen as a ‘black box.’

The formula used to estimate the expenditure and price indices are:

  • Price: {Σcd2xd1/N1}/ {Σcd1xd1/N1}
  • Expenditure: {Σcd2xd2/N2}/ {Σcd1xd1/Nd1}

Where cdt is the cost per episode of type d in year t, xdt is the number of episodes with disease d in time t, and
Nt is the total number of beneficiaries in time t.

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In an egalitarian world, everyone is equal, except perhaps the managers of equality. And certainly in the foreseeable future, there will be endless and not unprofitable work for those whose business it is to spell out in ever greater detail the rules of the game of life, and to adjudicate conflict, and to teach the benighted what thoughts a just society requires. Politics will have died, but everything will be politics.

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