August 2006

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The Easy ‘A’

August 17, 2006 in Uncategorized | Permalink

As a teacher’s assistant at UCSD, I often see undergraduate students selecting courses based on how easy the professor grades rather than on the amount of knowledge they will be able to glean from the course.  Why is this?  Arnold Kling gives a four main reasons in his “College Customers v. Suppliers” post on the Econlog website:

  1. The consumers are basically right. Most courses are not really worth taking for most students, so the easy A is the best choice. 
  2. The course that offers the easy A still gives the student the option to learn something, but the course that requires learning does not give the student the option to earn an easy A. So the option value is always with the coures that offers the easy A.
  3. Consumers are myopic, and their preference for an easy A is irrational. (This is the view that many professors hold implicitly.)
  4. Grades are measurable, and real learning is not. Consumers think grades are more important than they really are, because what is measured and reported is more salient than what is unmeasured.

Is there a solution?  Kling suggests external examinations:

“I should note that one potential solution to a competitive race-to-the-bottom in terms of rigor would be to have external examinations. When I was a student at Swarthmore in the Honors program, our exams were written and graded by professors from outside the college…With the exam exogenous, my grade-motivated students would want my course to be rigorous rather than easy.”

PacAdvantage: Adverse Selection Death Spiral

August 17, 2006 in Current Events, Health Insurance | Permalink

The adverse selection death spiral has reared its ugly head again.  PacAdvantage, an insurance pooling company for 6000 small and medium sized businesses in California has closed its doors.  The Sacramento Business Journal reports (“Backer pulls plug on PacAdvantage health purchasing pool“) that the three remaining insurers underwriting the plan have pulled out.   Michael Holt of The Health Care Blog analyzes has some perceptive analysis of the situation:

“What happens to voluntary purchasing pools? Simple economics—they only get customers who can’t get a better deal in the underwritten insurance market and so they go into a death spiral where the people in them are too sick to be supported by the premiums they charge. Today PacAdvantage announced that it was closing down, throwing 110,000 people into the small group and individual market, where by definition, no insurer wants them (unless they’re like me—very lucky).

PacAdvantage is the type of organization that our friends in the ‘voluntary universal insurance’ world (Cato, Galen et al) think is going to solve all of our problems, with no need for pesky mandates to buy insurance, or for community rating, or standardized benefits packages.”

In my June 15th post, I mentioned Cutler and Zeckhauser’s 1997 paper which discussed this concept of an adverse selection death spiral in the context of Harvard’s employee health insurance plans. 

Looking at healthcare…health care…health-care????

August 17, 2006 in Miscellaneous | Permalink

Healthcare Economist.  Why not Health Care Economist?  Or Health-care Economist?  Which one is correct?

The Chicago Manual of Style webpage offers a discussion of the issue.  The site claims that ‘health care’ is the correct spelling according to Webster’s Collegiate Dictionary, eleventh edition.  One individual, however, writes to the website saying:

“I find in my American Heritage Dictionary of the English Language (my favorite) that healthcare, without the hyphen, is the second spelling for the noun form of the word. Health care and health-care are listed as the spellings for the adjectival form of the word.”

Although it seems that ‘Health Care Economist’ may be more grammatically correct since I use the word as an adjective, I am going to rebel from the status quo and stick with Healthcare Economist.  My apologies to grammar experts everywhere.

How profitable is risk selection?

August 16, 2006 in Academic Articles, Health Insurance | Permalink

Many papers on health insurance worry about the problem of adverse selection.  Critics of HMOs claim that the fact that HMOs have lower costs is not due to more efficient provision of services nor the limitation of the provision of services, but instead largely caused by the fact that the people who choose to enroll in HMOs are healthier on average.  Shen and Ellis (2002) aim to test whether or not costs incurred from modeling an individual’s risk lead to higher profits.  A patient’s risk is measured in 4 different ways:

  1. using age-sex categorization
  2. using prior medical service utilization
  3. using Adjusted Clinical Groups (ACG) [example]
  4. using Diagnostic Cost Groups (DCG)

The data used in the paper come from the Mercer privately insured dataset for the years 1992 and 1993.  The authors use OLS estimation and justify this econometric methodology by claiming that when data sets are large, OLS is nearly as good an approximation as cell-based or non-linear models.  The authors find that categories 2, 3, and 4 provide significant information regarding the probability that an individual will incur future medical costs (R-squared between 0.079 and .106).  Category 1 also improves cost prediction over the pricing with no categorization, but the age-sex category is less accurate (R-squared of 0.019).  The authors find ACG generally has the highest gross profit rates for insurance companies regardless of the information which the payer has.  Gross profit ranges between 24% and 60%.  Overall profit increase ranges from $68 to $260 million depending on the risk selection system used and the information the payer has about their own propensity to use medical services.

In order to obtain these results, the authors used a simulation methodology and assumed that it was costless to drop any unprofitable payer.  The authors also looked only at one-year profit maximization schemes and did not look at any reputation effects.  Shen and Ellis conclude that this additional information does help increase an insurance company’s bottom line.  The major contribution of this paper is that they quantify how much additional profit can be gained from these risk selection mechanisms, even if this quantification is done in a static environment in which customers can be costlessly dropped from coverage.  The authors do not mention whether or not risk selection is good or bad for society since the utilty loss of those dropped form coverage is not modeled.  The only area of study is insurance company profits. 

Shen and Ellis (2002) “How profitable is risk selection? A comparison of four risk adjustment models,” Health Economics, Vol 11, pp. 165-174.

Crisis of Abundance Conference

August 15, 2006 in Miscellaneous, Public Policy | Permalink

On August 29th, 2006 there will be a book forum discussing The Crisis of Abundance by Arnold Kling.  While I have not yet read this book, I do respect Mr. Kling’s work and am anxious to see him discuss his views in this type of setting.  The book made the top 10 list of the National Chamber Foundation (the educational arm of the U.S. Chamber of Commerce).  Also attending the forum will be Michael Cannon, director of Health Policy Studies at the Cato Institute; Jason Furman, a Visiting Scholar at NYU; and Sebastian Mallaby, Editorial Writer and Columnist for the Washington Post.  For those not in Washington, D.C. area, the conference will be available online as well. 

The conference takes place on August 29th at noon ET.  For more specifics, click here.

Below is an excerpt from chapter one of Crisis of Abundance:

My guess is that 30 years ago, a patient with similar symptoms would have been treated “empirically,â€? a term doctors use to describe a situation for which they do not have a precise diagnosis and treatment, so that instead they must use guesswork. A layman’s synonym for treated empirically would be “trial and error.â€? In this case, the patient might have been sent home with an antibiotic and perhaps a prescription for Prednisone, a steroid used to reduce inflammation. There would have been nothing else to do. In 1975, computerized medical imaging technology was new and exotic, with limited applications.

In contrast, in 2005, over the course of a few days Quixote was given a computed tomography (CT) scan, referred to a specialist, sent to a different hospital, referred to a specialty clinic, seen by a battery of specialists there, and given yet another CT scan. Ultimately, however, she was sent home, as she might have been 30 years ago, with an antibiotic, Prednisone, and no firm diagnosis.

Compared with 30 years ago, Quixote received more services, in the form of specialist consultations and high-tech diagnostics. However, the ultimate treatment and outcome were no different. This does not mean that medicine is no better today than it was a generation ago. The CT scans and specialist consultations could have turned out differently. They might have been critically important, depending on her actual condition. Under some circumstances, treating Quixote empirically with an antibiotic and Prednisone could have been a mistake, perhaps costing some or all of her sight in one eye.

Such is modern medicine in the United States. Doctors are able to take extra precautions. They can use more specialized knowledge and better technology to try to pin down the diagnosis. They can perform tests to rule out improbable but dangerous conditions. But only in a minority of cases does the outcome deviate from what would have been the case 30 years ago.

An interview with Arnold Kling is also available at TCS Daily (“To much of a good thing?“).

The Effect of Health Shocks and Aging on Asset Allocation

August 14, 2006 in Academic Articles, Economics - General | Permalink

If one does not include Social Security and defined benefit assets, households with heads aged 65-74 have net assets of $190,100.  Households with heads aged 75 and above have net assets of $163,100.  How do the elderly allocate their assets?  Does their portfolio choice change over time?  Does it change in response to health shocks?  

These are the questions which Coile and Milligan (2006) seek to answer.  In their research, they found that their was little evidence that the elderly draw down their assets substantially during retirement [Guiso, Haliassos, Jappelli (2002); Borsch-Spuppan (2003)].  Milligan (2005) also found that in Canada, most households do not sell their houses or vehicles until late in life.  One reason for the paucity of home sales may be due to transaction costs.  For the elderly, the largest transaction cost may be the psychic cost of having to uproot themselves from their familiar abode. 

Econometrics

Coile and Milligan use data from the Health and Retirement Survey between 1992 and 2002.  Their econometric specifications are very simple:

  • Asset holdingsit = b0 +b1ageit +b 2Xit +g t +e it
       

     

The asset holdings (i) include five categories: stocks/bonds, a house, a vehicle, bank accounts/CDs, and business/real estate.  Here the aim is to examining trends as individuals age.  The authors later include dummies for 3 shocks: 1) having a spouse die, 2) being diagnosed with a chronic illness, and 3) experiencing an acute event (such as a heart attack, stroke, etc.).  Lags and leads of these shocks are also included.  Finally, cohort based fixed effects by birth year are used as well as household fixed effects.  As authors are wise to explain the following:

“In comparing the linear age, cohort fixed effect, and household fixed effect specifications, the usual trade-offs apply – the specifications with cohort and household fixed effects likely do a better job of controlling for unobservable heterogeneity, but there is a risk of being left with too little variation to estimate statistically significant relationships.“

Results

The authors find that home ownership is fairly steady at 80% until age 80.  After that home ownership drops off to 54% at age 90.  Similar results are found for vehicle ownership.  The authors found that becoming a widow is a strong predictor of selling one’s principal residence.  This results has been found in other economics studies, but what is new is that the widow shock also decreases ownership of vehicles, businesses and real estate, while increasing the share of assets held in bank accounts and CDs.  The authors also find similar results for the health shocks, but the findings are not as robust.  Negative health shocks vary in magnitude, and measuring the precise date of ‘poor health’ may be difficult if one’s health was already deteriorating before the ‘shock.’  We see a pattern of movement from more to less risky investments as one nears the end of one’s life.  The pattern is magnified when a negative health shock or death of a spouse occurs.  Both shocks may lead to increased spending (on health products or substitutes for household labor), and thus the need to maintain a minimum level of non-volatile income through CDs.  One issue I believe the authors missed is that a family’s wealth may greatly affect its asset allocation.  Using an instrument of initial wealth, and creating dummies for different wealth percentiles may have lead to more accurate analysis of what is causing behavioral changes. 

Coile, Milligan (2006) “How Housing Portfolios Evolve after Retirement: The Effect of Aging and Health Shocks,” NBER Working Paper #12391.

The invisible hand on the keyboard

August 11, 2006 in Economics - General | Permalink

In this week’s Economist magazine, one article (“The invisible hand on the keyboard“) asks why economists spend valuable time blogging.  Some of the more popular blogs receive thousands of visitors daily, yet why would an economist supply their output (knowledge) for free when they can receive payment from a university, the government, or private business for their work?  The article gives a few reasons:

  1. Self promotion – Economists with popular blogs may become more prestigious.  Further, the authors can plug any of the books or journal articles which they have published. 
  2. Refining one’s ideas and engaging in stimulating activity - Greg Mankiw at Harvard muses over his blogging participation and states, “It’s a natural extension of my day job-to engage in intellectual discourse about economics.”  Nobel-prize winner Gary Becker believed his blog would permit “instantaneous pooling (and hence correction, refinement , and amplification) of the ideas and opinions, facts and images, reportage and scholarship generated by the bloggers.”
  3. Fun – most economist enjoy intellectual discussion and blogging is one of the bests ways for a wide variety of individuals to participate in the discussion.

The Economist article also suggests that blogging, and the internet more generally, has reduced the competitive advantage of top universities.  Since anyone can access experts through their blogs and the web, academia has become more egalitarian.  Their point is supported by a 2006 NBER working paper by Kim, Morese and Zingales (“Are elite universities losing their competitive edge“).

HWR posted

August 10, 2006 in Miscellaneous | Permalink

The latest edition of the Health Wonk Review has been posted at Matthew Holt’s The Health Care Blog.

The Long Tail of Healthcare: Why 25 million Americans have a “rare” disease

August 10, 2006 in Economics - General, Healthcare IT | Permalink

The Health Care Blog has a very interesting post (“Healthcare and the Long Tail“) by Jim Walker.  Mr. Walker is a lifelong Philadelphia resident who is the Director of Business Development for the social networking site called MyMedwork.  He uses concepts developed in Chris Anderson’s book The Long Tail and applies them to the healthcare field.  Here is an excerpt:

“For those not familiar with the Long Tail, Anderson describes how Amazon, Netflix, and other online retailers sell lots of the usual blockbusters, but actually derive more total volume from 100s of thousands of niche products.  In healthcare, it is the left side of this distribution curve which inspires (for better or worse) Wal-Mart, Target, and others to offer “Doc In A Boxâ€? services -  Allergies, Bladder Infections, Bronchitis, Ear Infections, Pink Eye, Sinus Infections, and a full battery of vaccines – all served up for a fixed price while you wait.

On the right hand end of the curve though, the NIH Office of Rare Disease classifies over 6,000 conditions, each afflicting fewer than 200,000 Americans.  Along this part of the curve, things do indeed get very ambiguous in a hurry – both for patients and physicians. Specialization is a response to this range of ailments (“nicheficationâ€? in Anderson’s terms), and brings physicians repeated cases of a particular nature – giving them the confidence that they can routinely diagnose and treat a high percentage of these patients. However, even within a particular specialty area, cases will naturally follow a distribution curve from typical to atypical. Unto themselves – atypical cases are just that – one of a kind aberrations that force physicians to go outside their typical “comfort zoneâ€? of diagnosis and treatment.  For each individual physician, these atypical cases feel like the exception rather than the rule. What the Long Tail suggests though, is that taken in their entirety, these rare cases actually compromise a large percentage of all medical cases. In fact, over 25 million Americans suffer from a “rareâ€? condition.

This is problematic, because in general, physicians – and the healthcare system as a whole – are not well prepared for dealing with the many and inevitable rare cases. In fact, statistics show that the median time to diagnosis of a rare condition is six months, and the average is almost three years!”

The Incidence of Adverse Medical Outcomes under Prospective Payment

August 10, 2006 in Medicaid/Medicare, Supply of Medical Services | Permalink

Yesterday, I reviewed one paper claiming PPS along with competition reduced cost, but these cost reductions occurred mostly for the most expensive (read most sick) patients. Continuing the PPS theme, today we will look at a 1995 article in Econometrica in which David Cutler attempts to measure “The Incidence of Adverse Medical Outcomes under Prospective Payment.” Under PPS, hospitals no longer received any revenue from preforming the marginal service, or equivalently hospitals bear the full cost of marginal treatments. Also, average cost figures for each procedure changed depending on how the DRG was valued. The price a hospital received for a procedure is:

  • P_h,d=WGT_d*P_h*(1+IME_h)*(1+DSH_h)

The DRG value of a certain diagnosis ‘d‘ is given by variable ‘WGT‘ which is adjusted by a hospital specific factor ‘P_h‘ which reflects the local wage conditions. Other adjustment factors are the indirect medical education costs (‘IME‘) and a federal subsidy to hospitals which provide a disproportionate share of their services to the poor (‘DSH’ – see Baicker and Staigler post). Cutler hypothesizes that the effect hospitals bearing the cost of marginal treatment will be increased mortality. Also, any decrease in average price for a treatment should result in increased mortality. Cutler also investigates re-admission rates as well.

Using 1981-1988 data from Medicare and Social Security records, first preforms a difference in difference estimate using Massachusetts (which adopted a PPS in 1986) as a control for the federal PPS (which was adopted in 1984). He finds that mortality increased after the PPS was passed and readmission probability also increased. To refine the analysis, Cutler then uses a maximum likelihood estimation on a logistic hazard function to estimate the impact of PPS into 2 components: 1) the effect of eliminating revenue for the marginal treatment and 2) the impact of any changes in average cost for the procedure.

The impact of the elimination of marginal reimbursement led to a 25% decline in mortality, and a mild increase in the readmission probability. On the other hand, a one standard deviation decrease in average payment for a procedure led to an increase in mortality of 0.5%. The average price decrease also led to a lower re-admission rate.

How can we explain these findings? The elimination of marginal reimbursement may have decreased the use of unnecessary procedures. A more likely explanation is that of DRG creep where doctors code mildly sick patients as having severe diseases in order to increase their compensation. The result of DRG creep is that the patient pool in each DRG group is healthier after PPS than before it simply due to these classification changes and not due to any improvements in the medical care received. Since hospitals do not get paid for marginal services, they may wish to readmit their patients in order to double-bill Medicare.

The finding that an increase in average cost of a procedure reduced mortality is intuitive since paying hospitals more money to take care of certain illness will likely lead to better care for those illnesses. Readmissions are less likely as well, since increasing the profitability of a procedure would reduce the probability of a hospital needing to use double billing.

The true value of this paper is performing clever econometric specifications using MLE estimators. A discrete set of mass points [as suggested by Heckman and Singer (1984)] is used to account for unobserved heterogeneity for each individual. As Cutler admits, it is difficult to judge if many of the health impacts of PPS are due to true changes in the level of medical care or simply due to accounting changes such as DRG creep, so one should interpret these findings with caution.

Cutler (1995), “The Incidence of Adverse Medical Outcomes under Prospective Payment,” Econometrica, Vol. 63, No. 1. (Jan., 1995), pp. 29-50.

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