The Null Hypothesis in Health Insurance

is that, in the United States, better health insurance produces no difference in health outcomes. Recently, for example, Katharine Baicker, et al, found

This randomized, controlled study [in Oregon] showed that Medicaid coverage generated no significant improvements in measured physical health outcomes in the first 2 years, but it did increase use of health care services, raise rates of diabetes detection and management, lower rates of depression, and reduce financial strain.

Pointer from, well, everyone. All I can say is that this is really separating what David Brooks calls the “detached” from the “engaged.” The latter are making an all-out effort at what I call trying to close minds on your own side.

Somewhat detached commentary includes

Tyler Cowen, Ray Fisman, and Reihan Salam.

Robin Hanson has an even stronger version of the null hypothesis. His version says that differences in health care spending produce no difference in health care outcomes. He and I disagree about how to characterize this result. Let me try to explain how we differ. Let us stipulate that:

1. Some medical procedures improve health, but not in a way that shows up in statistics. For example, if you get your broken arm fixed, you are much better off than not getting it fixed, but this will probably not show up in measured statistics of health outcomes, including longevity.

2. Some medical procedures are a waste (futile care, unwanted care, treatments of non-existent ailments, treatments that do not work, and so on).

3. Some medical procedures have an adverse effect on health.

4. Some medical procedures improve health outcomes, but only with a low probability (e.g., precautionary screening).

5. Some medical procedures definitely improve health outcomes in a measurable way.

Note also, that most studies of medical spending are not controlled experiments. In observational studies, including cross-country comparisons, the results tend to be dominated by a 6th factor, namely that health outcomes are determined much more by individual genes and behavior than by medical intervention.

Robin and I agree that (5) is true. The question becomes, how does (5) wash out in the statistics on differences in spending? His view is that there has to be enough (3) to offset the (5). My view is that it is mostly that (1), (2), and (4) serve to dilute (5). If I am correct, then researchers should find some quantitative differences in health outcomes, but these differences will not be statistically significant. Out of (bad) habit, they will report this as “no difference in outcomes.” This makes it sound as if they have proven the null hypothesis, when they have merely failed to reject it.

Of course, in a large study (as this was), there may not be much difference between failing to reject the null and proving it. The confidence interval around zero could be small (if someone has access to the paper, you can let me know).

The Home Borrowership Crisis

Christopher L. Foote, Kristopher S. Gerardi, and Paul S. Willen of the Boston Fed write,

the facts refute the popular story that the crisis resulted from financial industry insiders deceiving uninformed mortgage borrowers and investors. Instead, they argue that borrowers and investors made decisions that were rational and logical given their ex post overly optimistic beliefs about house prices

This paper from last year was cited the other day by Scott Sumner.

One quibble I have is that the paper makes it sound as if the only variable that shifted during the run-up to the crisis was house price expectations. In fact, the proportion of loans with down payments less than 10 percent shot up (even the authors have a figure showing that the market share of loans with down payments under 5 percent nearly doubled, to almost 30 percent of loans, in just four years–from 2002 to 2006), the proportion of loans backed by non-owner-occupied properties (i.e., speculative investments) went from roughly 5 percent to roughly 15 percent, and the proportion of loans that went to borrowers with lower credit scores also rose.

Of course, the expectations of rising home prices helped fuel the decline in lending standards, because you cannot be punished for making a bad loan in a rising market. And the deterioration in lending standards helped fuel rising home prices, because it broadened the market to buy homes. Hence the bubble.

Facts About Austerity in the U.S.

From CBO head Doug Elmendorf. I focused on the 7th slide, comparing 2012 with 40-year averages. The figures are as a percent of GDP.

Category 40-year average 2012
Net Interest 2.2 1.4
All other spending 7.9 9.1
Defense 4.7 4.3
Social Security and Medicare 6.2 7.9
Revenue 17.9 15.8

Pointer from James Hamilton. I hope Mark Thoma will link to me here, because he is forever linking to posts that spin the fiscal data in a way that is very different from how I see it. What stands out to me is this:

Where is the austerity in the budget, i.e., the biggest shortfall in spending from the 40-year average? It is in “net interest.” It is definitely not in domestic discretionary spending (the “all other spending” category).

The “austerity” comes from low interest rates, which cause interest payments to be low. Think about that.

I note that yesterday’s employment report showed that the first four months of 2013, under “austerity,” were much better than 2009, under “stimulus.” I know that other things were not equal. They never are. Any macroeconomist can argue that he is always right, because the interpretation of data has so many degrees of freedom.

What I’m Reading

1. The New Digital Age, by Eric Schmidt and Jared Cohen. Before I read it, I had modest expectations. Afterward, I regretted buying it.

2. The End of Power, by Moses Naim. So far, this is a candidate for my favorite non-fiction book of the year. Maybe you have to discount some of my enthusiasm as confirmation bias, but I cannot imagine readers of this blog experiencing disappointment with the book. Expect a longer review from me at some point.

Education and Stratification

Megan McArdle writes,

according to Sean Reardon, there is also a gap between the middle class and the elite. American society is increasingly stratified, he says, because elite parents are investing so much in the cognitive enrichment of their kids.

But is that really the right explanation? The rich pulling away from the middle class is also exactly what we would see if test-taking ability has a substantial inherited component, and the American economy is increasingly selecting for people who are very, very good at taking tests.

Toss in changes in marriage patterns, too.