Defending the One Percent (Again)

Click here to read my column in Sunday's NY Times.  I expect this one will generate more than its share of irate letters.

Obamacare versus Romneycare

One of the themes that we have all heard over the past few years is that President Obama's healthcare reform is merely bringing the kind of changes Massachusetts had under Governor Romney to the nation. If that were really true, you would think that these national reforms would have minimal impact on the state of Massachusetts. Well, here is a story from today's Boston Globe:

About 50,000 health insurance applications, many filed by low-income Massachusetts residents, have yet to be processed by the state’s troubled insurance marketplace, officials disclosed Thursday, and it may take months to get all these people enrolled in subsidized plans. 

For several months, residents have been encouraged to file old-fashioned paper applications because the state’s insurance website has been hobbled by error messages and has crashed frequently since it was revamped in October to comply with the more complex requirements of the federal health care law. 

Frustration with the broken Massachusetts Health Connector website and the paperwork backlog was evident Thursday, when Jean Yang, the agency’s executive director, wept as she told the Connector board how demoralized her staff is.

Happy Valentine's Day

Source.

If Obamacare reduces labor supply, will it raise wages?

In a couple of recent articles written by smart economists, I have read the following claim: CBO says the incentives in the Affordable Care Act will reduce labor supply. If it does, then real wages will increase.

That sounds like reasonable, textbook economics. But I don't think it is true. The problem is that the logic is entirely partial equilibrium. It is holding everything else constant. But that is surely not right in the long run. Lower labor supply means lower income, which means lower saving, which means lower investment, which means a lower capital stock, which means lower productivity, which means lower labor demand.

Perhaps the easiest way to think about this issue is in the context of a Solow growth model. In the Solow model, the steady-state real wage is a function of technology, the saving rate, and the population growth rate. If labor supply per person suddenly falls by, say, 2 percent and stays there, the real wage will rise initally, but it will eventually return to its former level. Steady-state income per person falls by the full 2 percent.

One effect that might occur is a change in the composition of labor income. If the Act reduces labor supply primarily among the low-skilled, while not having that effect among the highly-skilled, then we might get a change in the relative wages of skilled and unskilled. But an overall increase in real wages seems unlikely.

The Economics of Downton Abbey

From The Washington Post.

Solow vs Mankiw on the One Percent

Readers of this blog will be familiar with my recent article Defending the One Percent.  In the new released issue of JEP, you can read a letter by Bob Solow commenting on the article as well as my response.

Sentence of the Day

From the Congressional Budget Office:

CBO estimates that the ACA [Affordable Care Act] will reduce the total number of hours worked, on net, by about 1.5 percent to 2.0 percent during the period from 2017 to 2024, almost entirely because workers will choose to supply less labor—given the new taxes and other incentives they will face and the financial benefits some will receive.

Implicit in this estimate are elasticities that measure how much people respond to incentives.  My sense is that CBO is typically conservative when it come to gauging these incentives effects.  So I would take their estimate of the impact on hours worked as a lower bound. The actual figure may be higher.


Addendum: Here is a column I wrote about these incentive effects five years ago.

Econ Summer Camp

Grad students with an interest in the history of economic thought should click here.

Humility-based Libertarianism

On the suggestion of Bryan Caplan, I just read In Praise of Passivity by philosopher Michael Huemer. A lot in the article makes sense to me.  As a social scientist, I think there is much we don't know about how the world works, and that intellectual humility goes a long way to explaining my skepticism about many governmental interventions into private behavior.  In any event, I also recommend the article.

An Econ Conference for Undergrads

In April in Washington, DC.

My Proposed (but not accepted) Bet with Paul Krugman on the Obama Forecast

Scott Sumner declares that I would have been the winner.

What worries Americans?

When Gallup recently asked Americans what the biggest problem facing the United States is, the four most common answers were dissatisfaction with government, the economy in general, unemployment, and healthcare.  Each was mentioned by more than 15 percent of those polled.  The gap between rich and poor was mentioned by only 4 percent.


If President Obama wants to make the 2014 electoral debate about income inequality, as he seems to, he has an uphill climb ahead of him.

How an Economist Helped Inspire the Movie Dr. Strangelove

Thomas Schelling, of course.

Does income inequality increase mortality?

In his recent Times column, Paul Krugman writes:

Rising inequality has obvious economic costs: stagnant wages despite rising productivity, rising debt that makes us more vulnerable to financial crisis. It also has big social and human costs. There is, for example, strong evidence that high inequality leads to worse health and higher mortality.

The links are from the online version of Paul's column.  I followed the second link to an interesting article by Angus Deaton.  Angus writes the following (emphasis added):

Darren Lubotsky and I ⁷ have investigated the relationship between income inequality, race, and mortality at both the state and metropolitan statistical area level. In both the state and the city data, mortality is positively and significantly correlated with almost any measure of income inequality. Because whites have higher incomes and lower mortality rates than blacks, places where the population has a large fraction of blacks are also places where both mortality and income inequality are relatively high. However, the relationship is robust to controlling for average income (or poverty rates) and also holds, albeit less strongly, for black and white mortality separately. Nevertheless, it turns out that race is indeed the crucial omitted variable. In states, cities, and counties with a higher fraction of African-Americans, white incomes are higher and black incomes are lower, so that income inequality (through its interracial component) is higher in places with a high fraction black. It is also true that both white and black mortality rates are higher in places with a higher fraction black and that, once we control for the fraction black, income inequality has no effect on mortality rates, a result that has been replicated by Victor Fuchs, Mark McClellan, and Jonathan Skinner⁹ using the Medicare records data. This result is consistent with the lack of any relationship between income inequality and mortality across Canadian or Australian provinces, where race does not have the same salience. Our finding is robust; it holds for a wide range of inequality measures; it holds for men and women separately; it holds when we control for average education; and it holds once we abandon age-adjusted mortality and look at mortality at specific ages. None of this tells us why the correlation exists, and what it is about cities with substantial black populations that causes both whites and blacks to die sooner.

In a review of the literature on inequality and health, I note that Wilkinson's original evidence, which was (and in many quarters is still) widely accepted showed a negative cross-country relationship between life expectancy and income inequality, not only in levels but also, and more impressively, in changes. But subsequent work has shown that these findings were the result of the use of unreliable and outdated information on income inequality, and that they do not appear if recent, high quality data are used. There are now also a large number of individual level studies exploring the health consequences of ambient income inequality and none of these provide any convincing evidence that inequality is a health hazard. Indeed, the only robust correlations appear to be those among U.S. cities and states (discussed above) which, as we have seen, vanish once we control for racial composition. I suggest that inequality may indeed be important for health, but that income inequality is less important than other dimensions, such as political or gender inequality.¹⁰

Is Angus's article really support for Paul's claim?  It seems to me that it is more the opposite.

On Assortative Mating

A new working paper concludes:

"Data from the United States Census Bureau suggests there has been a rise in assortative mating....[I]f matching in 2005 between husbands and wives had been random, instead of the pattern observed in the data, then the Gini coefficient would have fallen from the observed 0.43 to 0.34, so that income inequality would be smaller"

How much income inequality is explained by varying parental resources?

When people think about inequality of incomes, a key issue is inequality of opportunity. Some people are born to rich parents who can afford private schools, summer camp, SAT tutors, etc., while others have poorer parents who cannot easily afford such things. One might wonder how much of the income inequality we observe can be explained by differences in the resources that people get because of varying parental incomes.

Let me suggest a rough calculation that gives an approximate answer.

The recent paper by Chetty et al. finds that the regression of kids’ income rank on parents’ income rank has a coefficient of 0.3. (See Figure 1.) That implies an R2 for the regression of 0.09. In other words, 91 percent of the variance is unexplained by parents’ income.

I would be willing venture a guess, based on adoption studies, that a lot of that 9 percent is genetics rather than environment. That is, talented parents have talented kids partly because of good genes. Conservatively, let’s say half is genetics. That leaves only 4.5 percent of the variance attributed directly to parents’ income.

Now, if you let me play a bit fast and loose with the difference between income and income rank, these numbers suggest the following: If we had some perfect policy invention (such as universal super-duper pre-school) that completely neutralized the effect of parent’s income, we would reduce the variance of kids' income to .955 of what it now is. This implies that the standard deviation of income would fall to 0.977 of what it now is.

The bottom line: Even a highly successful policy intervention that neutralized the effects of differing parental incomes would reduce the gap between rich and poor by only about 2 percent.

This conclusion does not mean such a policy intervention is not worth doing. Evaluating the policy would require a cost-benefit analysis. But the calculations above do suggest that all the money the affluent spend on private schools, etc., explains only a tiny fraction of the income inequality that we observe.
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Addendum: A few readers seem confused about how to infer an R2 from a coefficient.  The key is that the left and right hand side variables in the regression have the same variance.  In this case, the R2 is the square of the coefficient.  This conclusion is a standard result for AR(1) models, which is what we have here, as applied to generational data.  (Also, a few readers are confused when they look at the paper's Figure 1. The points plotted are not the raw data but binned averages, so you cannot see the R2 in the plot.)

Has economic mobility declined?

No, says a new paper by Raj Chetty et al.:

"We present new evidence on trends in intergenerational mobility in the U.S. using administrative earnings records. We find that percentile rank-based measures of intergenerational mobility have remained extremely stable for the 1971-1993 birth cohorts....[C]hildren entering the labor market today have the same chances of moving up in the income distribution (relative to their parents) as children born in the 1970s."

Do department chairs have real effects?

Apparently we do:

"There is one robust predictor of a department’s future research output. After adjustment for a range of personal and institutional characteristics, departmental research productivity improves when the incoming department Chair’s publications are highly cited."

A Summer Opportunity...

...for graduate students with an interest in matching theory, especially as applied to market design. Click here to learn more.

How much is a Lars Hansen autographed reprint worth?

A student is trying to find out.  He emails me:

I'm a 1st year MBA student at Chicago Booth -- where even the Marketing Professors have a PhD in Economics. 

I'm taking a class this quarter called Entrepreneurial Selling (more info here). One of the coolest assignments is a bartering challenge: Prof. Wortmann gives everybody a simple Chicago Booth pen and we need to barter it for something with larger monetary value, and then keep bartering once a week until the end of the quarter. 

I did my first trade with Prof. Lars Peter Hansen (Economics Nobel Prize 2013). In exchange for my pen, he gave me an autographed copy (he wrote a cool anecdote as well) of his most famous article. I'm now running an auction at eBay (it's OK to trade things for cash): see here.