Religiosity and risky behavior

Teenagers tend to engage in risky behavior, and many reasons have been identified for this. Still, there are large differences across teenagers, and some literature seems to have identified religiosity as a powerful explanatory variable for less risk taking. But as so often, correlation is not causation. "Nice" kids who follow their parents' advice and behave may also be more likely to follow their parents to church, for example. Perhaps more importantly, individual religiosity may be influence by religious fervor in the social circle beyond the family.

Jennifer Mellor and Beth Freeborn try to disentangle this by using data from the National Longitudinal
Study of Adolescent Health and consider binge drinking, smoking and marijuana use. One may discuss whether the latter is truly risky, but this is not the topic here. Mellor and Freeborn use county-level religious density, a measure that takes into account the proportion of people of a same religious group in the same area, as an instrument to control for the social environment. For religiosity, they use the frequency of church attendance.

Measuring religiosity is tricky business. Density measures depend on the size of the area and how one fragments religious groups (split protestants apart or not, for example). And church attendance may be more a social event than anything else in some areas. I prefer measures like "Do you believe in hell?" to measure this. But let us assume the authors do the right thing (I wished they would supply some robustness exercises).

The results? Marijuana use is robust to taking into account the endogeneity in religiosity. So religious teenager indeed smoke less pot. But smoking cigarettes and binge drinking is a frequent as for less religious teenagers.

Placement officers can lower unemployment

From my casual observation, it appears that in countries where the unemployment rate is rather high, unemployed workers tend to rely more on government run employment offices to find jobs. I do not think there is causation in this correlation though. But this makes it more important to understand whether employment office are good at anything.

Jens Hainmueller, Barbara Hoffmann, Gerhard Krug and Katja Wolf discuss an experiment in Germany where the case load of some employment officers was halved, which would be equivalent to doubling the number of employment officers. Does this help in increasing the placement of the unemployed? The above four claim that yes: the unemployment rate is reduced and so is the number of people registered in employment offices. But these results are obvious, except maybe that they are statistically very significant. What matters more is that they are economically significant.

Is a 0.5%-point reduction in the unemployment rate economically significant? Probably yes. Is it worth the cost? Remember, you double the number of case workers and you increase taxes to pay them. In fact, some of the unemployed may have been hired as case workers. It is much less obvious that the experiment is positive look at it this way.

This is what should have been studied. I am too often frustrated by studied that just look at the statistical significance of an effect, ignoring the economic significance and especially how this fits in the rest of the economy. And this happens too often with labor economics papers. If there is one thing that distinguishes economists from other social scientists is that we tend to think more in a general equilibrium way, and this papers for sure does not do justice to economics.

Optimal deposit insurance

With the current financial crisis, the question of the optimality of bank deposit insurance has flared up again. Figuring out how much deposit insurance should cover is not an obvious exercise. Indeed, one has to think this as a game between bank managers, who want to take advantage of moral hazard through excessive risk taking, bank owners, looking maximize bank value, depositors, who decide whether to run and withdraw funds, and regulators, who want to prevents crises, but also want to liquidate banks that should be liquidated.

Michael Manz develops a nice and rich model that attack the problem from the perspective of global games. This has the advantage of resolving the issue of multiple equilibria in the standard bank run models. Among the many results, several stand out. If the bank risk is exogenous, coverage should not be high as it prevents necessary and efficient runs. Also, liquidity requirements are a good substitute to deposit insurance. Finally, coverage should not increase in the event a financial crisis hits. The reason is that the financial risk increases with the scope of deposit insurance because, if I understand right, while higher coverage protects better deposits in banks of systemic importance, it leads to more moral hazard in others and then increases the likelihood of a run on all banks. The only way out is to discriminate coverage by bank, which is a completely different regulatory game.

Rational procrastination

So you have a deadline to submit a project. Your cost, in terms of utility for example, for working on the project is stochastic with a known distribution. When should you start working on it? The solution to this problem is a stopping rule, which will of course depend on the way you discount future disutility.

Alberto Bisin and Kyle Hyndman look at this with three different types of discounters and come up with interesting solutions. Agents with a standard exponentially discounted utility will choose to work on their project when it is most convenient, which may be before the deadline. Agents with hyperbolic discounting will delay until the last moment. But hyperbolic discounter may not be that naïve. Sophisticated ones realize they have a procrastination problem and will end up completing their project before the deadline.

This last result is important because sophisticated hyperbolic discounters and exponential discounter end up being, potentially, observationally identical. However, looking at me and around me, there are many hyperbolic discounters who are aware of their problem, but still cannot do anything about it except complaining. I am thus not quite convinced of the empirical relevance of this result. Of course, my empirics are anecdotal, but I saw no empirical evidence at all in the paper.

People are nasty

We all know that doing better then others is an integral part of our satisfactions. Thus when we think about utility functions, at least in some contexts, it is important to consider not just absolute outcomes but also relative ones. Indeed, there is for example evidence that people are willing to lose something only to hurt (more) others. Presumable this raises their utility.

Klaus Abbink and Benedikt Herrmann push this further with an interesting experiment. They let people chose to pay in order to probabilistically hurt someone else in a game where Nature may hurt the other anyway. And when Nature is in play, people hurt much more each other, and also expect this to happen more. The moral cost is clearly lower, as one can always defend oneself by pretending Nature did it. Strangely, this is even prevalent when there is complete anonymity.

Optimal irrationality

One can safely say that the assumption of rationality is central to economics. One idea behind it that economic agents must be trying there best. But what if it were optimal to behave in an irrational way? Surely, one could build some twisted example where irrationality would be preferable, same some game theoretic environment where being unpredictable is superior. But this is still a rational choice, called mixing strategy. Would there be some truly irrational behavior that could at least weakly improve outcomes?

James Feigenbaum, Frank Caliendo and Emin Gahramanov come up with such an example. They use an overlapping generation economy where one can improve on the permanent income rule. Now, we know OLG models can quirky and lead to strange results, but this is still an interesting example. They key here is that there is a publicly shared rule of thumb, say, "save more now" that can alter aggregate outcome, in this example increase labor income and thus wealth. Households are not just price takers, but they consider that if everybody deviates, it will have consequences. All you need it to have some trigger that lets everyone converge on this new focal point. In short, animal spirits at work.

Why all the fuss about business cycles?

There is a surprising amount of research on business cycles, and also public concern about recessions, if your consider the most influential work on the topic. In his 1987 book, Robert Lucas claimed that the welfare cost of business cycle was minimal. The model he used was utterly simple, in particular with a represntative household and has been attacked many times since. But in his 2003 AEA presidential address, Lucas claims that all modifications to his model from the literature taken together are not able to give a significant welfare improvement from the elimination of business cycles.

In recent years, there has been much progress in working with heterogeneous agent models with business cycles. And these models can highlight costs from business cycle fluctuations in the order of 1% of consumption. Their more important result is that this cost is very unequally distributed, which makes it very significant to some. Take two examples. Tom Krebs argues that the real cost of business cycles is in the long-term job displacement of workers. The reason is that short-term fluctuations can have long-term consequences. Or Per Krusell, Toshihiko Mukoyama, Ayşegül Şahin and Anthony Smith show that the elimination of business cycles not only smooths variables, but also changes their average level. The latter happens because of changes in precautionary savings and through the resulting changes in prices. Both papers also show that there are strong redistribute forces at work, and the welfare impact of aggregate fluctuations is worth several percents of consumption in some worker categories, something worth caring about.