US local lenders knew about the housing bubble

Among the main culprits of the recent boom and bust in the US housing market that have been identified, the lenders and their excessive pushing of mortgages have been prominently featured. As pushing mortgages to people who cannot afford it seems to be a losing proposition, some pretty weird incentives must be in place for this to work. In other words, their must be some pretty sophisticated scheme in the lending business for some to make a gain from this. Local lenders, though, are not that sophisticated, as they handle most of the steps in the lending process themselves. As it turns out, they saw the debacle coming and pretty much got out of lending mortgages as soon as they felt things were getting excessive.

This is what you can conclude from the the analysis of Kristle Romero Cortés. She finds that where home prices where rising the fastest, the share of local lenders on the mortgage market was declining the fastest. In the subsequent bust, home prices were declining less in areas where local lenders were more present during loan origination. And looking at California only, foreclosures rates were lower where local lending was more prevalent. And all these results are even stronger where local lenders did not securitize the mortgages. What this shows is that there is still good value in homegrown lending, where the lender knows the markets intimately and knows to back off where things are getting dicey. Or, this can also be an indictment of the national mortgage chains like Countrywide Financial that were lending without thinking or had twisted incentives in place.

Department size and research productivity

This is a bit late for the current job market for Economics PhDs, but say you have to choose among several job offers (lucky you). The departments are are all of equal prestige and working conditions, salary, and geographic environment are all comparable. The only difference is the size of the faculty. What offer should you take if you care about your future research output?

Clément Bosquet and Pierre-Philippe Combes say you should go for the uniformly good, more field diverse, and larger department. At least this applies to French academic economists. Even more interesting, they observe that department characteristics are as important as researcher characteristics. The initial placement of a researcher thus matters a lot for her future, and this may explain why there are so few success stories after an initially poor placement, at least in Economics. Of course, the academic market in France is very different from any other country, so I am not sure the results can generalize, but this is a start.

How to contain housing bubbles

One cannot deny that housing bubbles can lead to nasty consequences, as shown in Japan, the US and Spain, for example. What can a policy maker do? Foremost, it is difficult to identify bubbles on the spot, and even in hindsight. Also, imagine the backlash when the government intervenes to rein in a booming industry. One thus needs a policy rule that kicks in automatically, or some policy that just reduces the volatility of prices. Natural candidates are transaction taxes and capital gains taxes for houses, and such taxes have been proposed not only for real estate markets, but also for financial markets in general (for instance, the Tobin tax).

Nicole Aregger, Martin Brown and Enzo Rossi exploits differences in such taxes across Swiss administrative divisions, as well as corresponding house price indices, to identify whether such taxes work. They do not. The capital gain taxes, especially those that apply to short-term gains, amplify prices movements. Why? Likely because house owners are reluctant to put their house on the market if such penalties apply, which drives prices even higher. As for transaction taxes, they have no impact whatsoever on price fluctuations. Thus such tax policies do not work, unlike you are willing to subsidize capital gains...

Why Americans spend so much on health: they work themselves sick

If you compare Americans to Europeans, you can come up with a few differences: they are richer, work more, pay less in taxes, spend a lot more on health, but are less healthy. Could all these facts somehow be related?

Yes, according to Hui He and Kevin Huang, who use a dynamic general equilibrium model to study the impact of labor income taxes on the labor supply and health outcomes. The resulting story they can tell follows essentially these lines: First, to be more likely to be healthy, you need a good amount of leisure, or not be overworked (which may explain why I have been sick the last few days). But if labor income tax is low, you tend to want to work more. This diminishes your health, which you compensate by buying more health services, which you can afford thanks to higher income. Due to high demand for these services, they also become more expensive. In the end, Americans end up with an outcome where they have more stuff to consume which they trade off with paying more for health services, enjoying lower health and less leisure. All this because of the labor income taxes. Whether they are better off is a matter of individual taste. I could certainly need a bit more leisure about now.

Protestantism and economic growth

Among Christians, Protestants have a reputation of hard workers. This is motivated by the preachings of the early reformers who have emphasized literacy and hard work, to the disadvantage of wasteful fun and decorum. This was quite a break from Catholicism, where decorum and the arts are very important. I am likely not alone in thinking that this explains why the South of Europe, predominantly Catholic, is poorer than the North.

Davide Cantoni makes me doubt that now but using a dataset that has fewer confounding factors than European national data: the Holy German Empire. Indeed, it was fractures in many fiefdoms of various religious orientations. Of course, economic data is rather limited for the sample periods of 1300 to 1900, so Cantoni does what economic historians typically do in such a situation: use population data, a presumably good proxy for economic development in a Malthusian world. There is rather good data for cities, and we know how they switched their religious denomination over time. And Cantoni finds nothings. No matter how he turns the data, Protestantism has no impact. Why? Maybe because we think of the teachings of Calvin when thinking about Protestantism, while Calvin was of limited impact? But what about the emphasis on literacy?

What is an ordinary saver?

The banking crisis in Cyprus has been handled very poorly, few would disagree. There was foremost a deplorable approach to naming things, for example "deposit tax," and also the fact that it took so long to come to a solution, which allowed privileged people to escape losses imposed on others. However, one idea that I found rather strange was the concept that the "ordinary saver" should not be penalized.

Justina Fischer, in a paper whose length rivals this blog post, argues that ordinary savers need extra protection because they have fewer choices in savings vehicles and they may be suffering from information asymmetries. But who are the ordinary savers? Are these people with little savings? Those with undiversified savings? If household finance data taught us something, it is that there is extraordinary diversity in savings and wealth, and that the life cycle matters a lot. So it impossible to easily categorize people as ordinary by simply looking at their savings account.

That said, a deposit account bears risk and it is not a sacred cow that the government or someone else should insure at any cost. During the liquidation of a bank, depositors may be defined to be the first to be served (which is not even true in some countries, for example in the US holders of derivatives are first), but that does not mean that there is necessarily enough for them. That said, a country may decide to insure deposits up to an amount, and many do. But this is part of a financial contract that a country may not even be able to hold, as the Cypriot example shows us. And if we think a bit harder about it, this insurance should not apply to the account but to the person, like guaranteeing everyone that the first X euros in bank deposits anywhere cannot be taken in a bank bankruptcy. But anything above that is subject to usual bankruptcy proceedings.

Misallocation of human capital in developing countries

It is now well established and documented that capital and labor are very poorly distributed across and within sectors in developing economies. The impact of this misallocation is large enough to explain a non-negligible part of the gap between rich and poor countries. This analysis has, however, only pertained to worker counts and physical capital. What about human capital?

Dietrich Vollrath looks at the sectoral allocation of human capital in 14 developing economies, analyzing the marginal return by using wage data. He comes to the conclusion that the misallocation has an impact on GDP of at most 5%, more than in the US but clearly negligible to explain cross-country differences. I find this hard to believe from my casual observation. For example, in many developing economies, the brightest minds go into government administration because this is where they can extract the most rents (some call this corruption). They expand a bureaucratic machine at the expense of the productive sector. That cannot be good for GDP. Using wage data here can be misleading, as the marginal product of corrupt bureaucrats, at least in social terms, is certainly not reflected in their wage. Add to this important informal sectors where wages may be substantially mismeasured, even in household surveys, and I am not quite as confident in the data as Vollrath seems to be.

Are illegal drugs price elastic?

Without a doubt, the US has a huge illegal drug problem. Incarceration rates are astronomical, highlighting that prison is neither a good deterrent nor a good strategy against repeat offenses. And one can question whether prison is appropriate in the first place. In this context, it is surprising how little we know about illegal drug demand. How does it respond to enforcement, risk, penalties or prices? Good data is hard to come by and clean experiments are rare and not necessarily generalizable.

Scott Cunningham and Keith Finlay offer one case where we may have a clean case of exogeneity in that sudden scarcity for two components of methamphetamine occurred through a country-wide ban in 1995 (which quadrupled meth prices for a few months) and 1997. Using this as an instrument, they try to explain demand as measured by admissions to drug treatment facilities. The latter is the best proxy one can find for actual consumption, but is it good enough? Only if the proxy stays proportional to consumption despite severe disruptions on the markets, which I think is a heroic assumption. In any case, they find that the price elasticity of meth is very low, maxing at -0.25 after six months. Keep in mind that this is a relatively short-run elasticity, thus hardly surprising for an addictive good. Still, cross-price elasticities reveal that meth has in alcohol a pretty good substitute. Is then an intervention in meth markets really worth it, especially if it means making cough medicine difficult to buy for the rest of us?

Cannibalism in Ireland

Cannibalism within most animal species arises only in extreme circumstances. It is not clear to me why this is less prevalent than intra-species killing, as the latter has a clear negative impact on the survival of the species, whereas eating already dead fellows has no impact. In any case, there is a huge taboo on cannibalism, and humans are no different. But it happens in extreme situations, and famine may be one.

Cormac Ó Gráda studies the incidence of cannibalism during famines and focuses on Ireland. Unlike for other great famines elsewhere or before, conclusive evidence for cannibalism and especially murder-cannibalism seems difficult to find for 19th century Ireland. The famine was certainly severe enough for some hearsay about it to emerge, perhaps figuratively. Does the lack of a record imply that the Irish are more humane and principled? Or that the taboo is so strong that cannibalism is unmentionable? While the paper provides an interesting analysis of the historical record, answers to these questions would also be interesting.

Something happening in reaction to nothing

Prices reflect information. We tend to test this by looking at how the revelation of new information has an impact on prices, in particular on the stock market. But the fact that no information is being revealed may also be informative, and this could lead to price changes. The question is then whether market participants are attentive enough to notice no information is coming.

Stefano Giglio and Kelly Shue study this by checking on price changes after a merger or acquisition proposal has been revealed. Sometimes they are not getting finalized, and the longer nothing happens, the longer it should become clear the fusion is off. Thus, prices should, all else equal, revert to pre-announcement levels. Looking at 5000 mergers, they find that prices underreact to the absence of news. Either there is a behavioral issues, such as Bayesian updating not working properly when there is no event to update, or there could be a rational explanation in that risk exposure, frictions or asymmetric information issues could be changing as the merger proceeds (or not). Giglio and Shue cannot exclude any of these explanations but show that the behavioral one is certainly consistent with the data. That would mean that there are opportunities to make money lying out there...

Why is it so difficult to find a job in France?

For anybody thinking about labor market policy, France is a basket case of how you should not give in to the pressure from the street and rigidify the labor market to almost everyone's disadvantage. With such extreme job protections, do then labor market status transitions look markedly different from other countries?

Jean-Olivier Hairault, Thomas Le Barbanchon and Thepthida Sopraseuth use administrative and labor market survey data to build time series for job separation and job finding rates. While their analysis is somewhat limited by the fact that they cannot capture a third state, "not in the labor force," the results are strong enough to conclude that contrarily to, say, the US the job finding rate is the major driver in changes to the unemployment rate. In other words, employment protection is effective and the job separation rate fluctuates little with economic activity. However, hiring fluctuates a lot, and given the high average unemployment rate, it is a clear indication that employers are scared to hire workers they could not get rid of if necessary. This is a clear indictment of excessive employment protection.

Test statistics and the publication game

It is well known that journals do not like replications or confirmations of hypotheses. They are looking for the empirical results that contradict popular wisdom, and this must be influencing the way researchers look for test results. To increase your chances of success, you want to only mention highly significant results and ignore the so-so ones.

Abel Brodeur, Mathias Lé, Marc Sangnier and Yanos Zylberberg look at the distribution of p-values in articles published in the top three economics journals. I am not quite sure what the distribution of p-values would be if the publication process were unbiased, but it would probably look like a Poisson distribution and it would be monotonic on each side of the mode. What the authors find does not look at all like this. There is a distinct lack of test results that just miss the 5% or 10% significance, and distinctively more that just pass those thresholds, making the distribution bimodal. Interestingly, this problem is less present when stars are not used to highlight significance or when the authors are tenured.

These results indicate that there is more than a selection bias. This is an inflation bias by the researcher when he only presents the most significant results, which were obtained by finding the specification that allows to pass the magic significance thresholds. I do not think this is ethical, but the publishing game makes it unavoidable, so the profession is apparently fine with it. I guess we have to tolerate this and take it into account when reading papers much like we know there is grade inflation when looking at transcripts or there is similar inflation when reading recommendation letters.

PS: This paper is a strong candidate for the best paper title of the year. Bravo!

PS2: What is really unethical is claiming results are significant when they are not. The case of Ulrich Lichtenthaler comes to mind, who added "significance stars" to his results when they were not warranted. The fact that he still managed to publish widely is an indictment of the quality of research in business journals, too.

Fathers are drinking away their time with their children

It is no secret that growing up with an alcoholic parent is no fun. It is even worse for single parents. How bad this is is difficult to evaluate, as one would need data on alcohol consumption by parents and a measure of outcomes for children. Maybe some proxies can help here.

Gianna Claudia Giannelli, Lucia Mangiavacchi and Luca Piccoli take time spent with the children as a proxy for child wellbeing. They use a Russian survey and look at how much time each parent spends with the children, along with their alcohol consumption. They find that fathers care less about their children when they drink more, but there is no effect for mothers. In some ways, this reminds me of the paper by Siwan Anderson and Jean-Marie Baland that shows that mothers in Kenya use ROSCAs to keep money away from their (drinking) husbands, despite the fact that ROSCAs are a very inefficient savings technology.

But let us get back on topic. Is time spent with your children the best measure of child wellbeing? Certainly not, but it is supposed to be a proxy. But on theoretical grounds, I need a lot of convincing here. Indeed, if my parents had been alcoholic, I would have preferred, all else being equal, that they spent the least possible time with me. This would reverse the conclusion of the paper ("negative impact of fathers' alcohol consumption on child welfare," implying no impact of the mothers' alcohol consumption).

The construction sector is key to the business cycle

It is well known that the construction sector is a very important indicator of the business cycle. In fact, residential construction has been a reliable early indicator of economic activity for many decades and this characteristic is occasionally rediscovered. What is there still to learn about the construction sector?

Michele Boldrin, Carlos Garriga, Adrian Peralta-Alva and Juan Sánchez build a business cycle model including an input-output table. Looking at the last business cycle and putting in the model only variations in housing demand, they find that the construction sector contributed to 30-60% of the increase of employment before the recession, and 8-15% for GDP. But during the recession, the importance of this sector was even more massive: 30-40% respectively 45-60%. Part of it comes from the size of the shock, and part for the inter-linkages with other sectors.

Now think about the consequences for policy: if a major part of the recession of the recession is driven by a single and relatively small sector, it makes no sense to rely solely on monetary policy as it is currently the case. Monetary policy cannot distinguish by sector (and if it does, it loses independence). One would need active fiscal policy, like what was initially intended with the stimulus program. The current austerity mood, however, goes exactly in the other direction, as public investment programs are of course the first ones to suffer from cuts. Or you can just declare that this is all a structural shift, and keep any policy out of this.

Competitive behavior by gender: jumping to conclusions

Men are more competitive than women. Whether this is genetic or nurtured is much studied and occasionally discussed here (I, II, III). I do not think there are definitive answers because it is very difficult to find an environment where one can pursue a truly controlled experiment. If we keep adding varied studies, however, we could get to a clearer picture and finally understand whether girls are at a disadvantage in a competitive environment and need to be helped.

An interesting recent study is by René Böheim and Mario Lackner who study jumping competitions. In high jump and pole vault competitions, athletes fail out after three successive misses and need to choose heights strategically as the competition evolves. They do not want to jump too much, especially as they need to keep their best jumps for last. But it is also risky to skip many heights, as one may start with three misses on a bad day. Interestingly, the strategic choices of men and women differ. Men take more risky decisions despite the fact that the return to risk is lower. What is particularly interesting here is that men and women differ in a context where they do not interact. Were they to compete against each other (applying the appropriate handicap), women would appear to be less competitive.

So is this study compelling evidence of innate differences? No. First, the women competing in jumping competitions were still raised in an uncontrolled environment. Second, we are only looking at elite athletes here, and analyzing the extreme tail of an unknown distribution does not help in making conclusions about the general population. And third, I think even the membership in this distribution tail is not equivalent. It is well-known that much fewer women participate in competitive sports, and they likely face less competition. In a winner-takes-all context, as a consequence you do not need to be that risk-taking.

Who cares about the median voter? Not the politicians, maybe

Most implementations of political economy in economic modeling assume that the median voter is the determinant voter. Some studies may take into account that the likelihood of voting is not the same for everyone, but the basic principle is that politicians adjust their proposals according to some sort of median in a universe where every man and woman has roughly equal weight.

Pablo Torija tests this by looking at which parties were in power in OECD countries. Assuming that voter preferences are quadratic in income and depend on the distance of the individual's policy preference to the one of the party in power, one can then determine for which household this policy would be optimal, and then see where this household is in the empirical income distribution. The actual implementation is a bit more involved than that, as parties' ideology is coded on a linear scale, and this is interacted with income. All this is then regressed on happiness indicators from surveys to proxy for utility.

The results are striking. Right-wing parties' median voter is at the 99th percentile. For left-wing parties, it is at the 95th percentile. That is for 2009. Extrapolating the empirical model, it is much closer to the median in the 1970s. But are these results believable? For one, the policy preferences of the individual somehow vanish between the simple theoretical model and the empirical implementation. And more generally, static preferences that only depend on income and ideology seem rather crude. Is this income before or after taxes? That can have a tremendous impact. And people may care about other things, see for example the recent debate about the importance of leisure and working conditions in US and French tire plants. I suspect that results are biased upwards by all this.

Is kidnap insurance a good thing?

In some countries, kidnapping for ransom has become a common and profitable business. It does not strike as an added-value generating activity, but one has to live with it. One way in which markets have responded to this is that it is now possible to by kidnap insurance that pays ransoms. Is this a good thing? Indeed, kidnapping frequency may increase if there is a higher likelihood that a ransom is going to be paid. That is not unlike US colleges that charge higher tuitions because they can, as public funds for students grants and loans have been ramped up. But let us keep talking about criminal kidnapping.

Alexander Fink and Mark Pingle look into this issued. The first question one may ask is whether this kind on insurance is sustainable in the first place. Indeed, many insurance markets fail due to adverse selection or moral hazard issues. In this case, risk aversion on the insureds is high enough that they are willing to pay premiums sufficiently above what would be actuarially fair. Indeed, there is a risk of getting somebody killed, and optimal kidnappers would want to randomize over this just to make sure that they can extract the most. The presence of insurance will increase the number of kidnapings, but if it does not do this too much, one should see a reduction in killings. We can thus not unambiguously say that kidnap insurance should be allowed.

Are economists really uneasy about studying inequality?

Economists are often misunderstood. People do not understand what we do. They think we spend all our time forecasting the stock market. And the whole profession has been accused of not foreseeing the recent recession. Some economists have redirected this criticism and made a name for themselves by complaining that economic models do not take this or that into account. That is true, but this is often irrelevant, as models are abstractions and they cannot take everything into account. You want to build the right model for the particular question at hand. I have mentioned a few of those essays on this blog, in part because they frustrate me as they are ignoring the very literature they are calling for. There is a lot more to Economics than the principles with perfect markets we tend to teach as an introduction to the field.

The latest paper to frustrate me is by Brendan Markey‐Towler and John Foster. They claim the Economics profession is uncomfortable with issues about inequality to the point of ignoring them. To support this, they quote extensively from the introduction of the Handbook of Economic Inequality, which of course is going to try to make the case that inequality is underrepresented in the literature. Why so? Markey-Towler and Foster claim this has to do with the profession's adherence to Arrow-Debreu markets, welfare theorems, the Hicks-Kaldor efficiency-equity trade-off, and Arrow's impossibility theorem. Because the profession is so enamored in these theorems, it views the impact of inequality to be political only, but of no economic consequence. Never mind that you can still have inequality in such economies. Never mind that every issue of the top journals has papers with such properties and inequality. Never mind that many papers go through great lengths in trying to model observed inequality while studying many issues. I agree not every paper does this, far from this, but then not every answer hinges on inequality. Again, models are an abstraction, and one cannot include everything. One keeps what is most likely to matter. Occam's razor is still valid today.

Markey-Towler and Foster have this distorted and unfortunately common view that economists believe markets are always complete and perfect, and thus inequality cannot happen. This sounds a lot like those who criticize Economics after taking one class, where they learned that free markets and free trade are good. But economists have long realized that things are much more complicated than that, and the study of the departures from this perfect world dominates current research in Economics. In fact, read this blog and you should see that I hardly mention such perfect markets. The authors' solution? Complex systems theory, which I liken to modeling the actors of an economy being linked by a giant plumbing system with leaks, plugs and bottlenecks. That sounds much like the frictions, information asymmetries and imperfect competition we put in our models, except that complex systems theory is much more detailed, requires gigantic amounts of data to calibrate or estimate, and has gone nowhere so far. So researchers had to resort to heroic assumptions to show something could happen, without any ability to validate it empirically.

I do not think this is the way to go, and we can agree to disagree on that. But I take offense at the idea that economists are somehow uncomfortable, even scared of dealing with inequality. That is just not true.

Efficient raffling of public goods

How to provide for a public good is a classic problem, because of the free-rider problem. If you cannot compel users, say, by forced taxation, it is very difficult to recoup the cost of a public good, unless the cost is very low and the benefit to each user very large. That rarely happens. So how can you solve this conundrum when philanthropy is not available?

Jörg Franke and Wolfgang Leininger propose an algorithm based on raffling the cost of the public good. This ideas is due to John Morgan: you create a lottery for the benefit of a socially beneficial public good. Then, people are willing to pay more for the public good. But this is not yet sufficient for the efficient amount of public good. To get there, Franke and Leininger propose an unfair raffle. The raffle tickets are sold at prices that look like Lindahl pricing, but unlike in the Lindahl model, there is no coercion. While there are already many charity raffles that would fit the Morgan model, I cannot think of an unfair public-good raffle in practice, though.

Overconfident NBA players are lead to a financial demise

Some professional athletes manage to amass amazing fortunes only to file for bankruptcy a few years after their retirement from sports. How can such large wealth go to waste so quickly? The typical explanation is that poor investments were made. Why does it happen so frequently to them? My take has been that either their wealth attracts swindlers, or the comparative advantage of these athletes is not human capital, or both.

Ruby Henry thinks this has to do with over-confidence. He builds a database of NBA players drafted in the 1990's and collects from various Internet source information about their personalities and their professional characteristics. The first sign of trouble is that most of those venturing into entrepreneurial undertakings do it in food services or real estate, two sectors were bankruptcies are particularly common. The second sign is that they do not seem to diversify much. One can interpret this as the consequence of over-confidence in one's ability and luck. Ruby measures the level of confidence of a player with the number of 3-point shots attempted per playing minute. And it appears that shooting for more 3-pointers later leads to more business ventures, and more bankruptcies. That would explain the variation across NBA players. But does that explain why NBA on average have more bankruptcies, and especially more spectacular ones?