On democracy and tuition hikes

Some students in Quebec have now been on strike for over three months over a law that would increase the tuition in all universities (they are all public) by a total of about US$1500 over five years. This seems a rather trivial amount for a US student, but in countries where tuition is free or almost free, this is not trivial. The apparent violence of the protests, which have gone all the way to sabotaging the subway system, and the daily protest marches show there is some deep issue at play. Let me add my grain of salt on two points.

The first is about democracy. I am all for popular uprisings, demonstrations and marches when there is a failure in the democratic process that leads the government to take decisions that are against the public good. Frankly, I do not see where the failure of democracy is in this case. The law was adopted by a democratically elected government. While Quebec is a province with severe corruption issues (for Western standards), the electoral process seems clean. Polls appear to show wide support for the government's policies. Even the striking students are a minority in the student population. The street should not hold the democratic process and sound policy making hostages.

Which brings me to the second point. Apparent popular support in the polls may be a reaction to the violence and radicalization of the student movement. It may not be about sound policy. But it should. Indeed, the main argument for low tuition is that it makes university access affordable to everyone. That is right, but it is also a gigantic gift to the rich, who send their children much more frequently and much longer to university. If you add the costs and the taxes, giving free tuition is equivalent to a very regressive taxation. I do not think that this is the goal. The goal is to get everyone to pay their fair share in education, for which the future personal benefits in present value are very large. Tuition should be subsidized because of the positive externalities of education, but those that benefit the most from it should also pay the most for it. If students cannot afford studies right now, then grants and loans can overcome that. But the fact that some students cannot afford to study should not lead to a policy where higher education is free, or almost free, for everyone.

The Quebec government is right on this one, and the street is wrong.

Why are seasonal immigrant worker programs so unpopular?

Immigration policy is difficult to optimize, first because some economic rents are at stake, second because people do not want to share the luck of being born in the right place and at the right moment with foreigners who do not have that luck. But even within that context, a policy of seasonal immigration should be easy to adopt, as everybody wins: immigrants are let in only when labor demand is very high and cannot be met by locals, and the immigrants leave when the labor demand is back to normal. And the immigrants are willing to go for it, as it provides good income that is valued as they return home. This is a winning proposition for everyone, yet such policies are rare, and when they exist, they are little used. Why?

Danielle Hay and Stephen Howes take the example of Australia, where such a policy has been adopted for the horticulture industry but little used. It appears growers are reluctant to hire seasonals even when they have trouble finding workers. Either they are unaware, or they are afraid of red tape, or they prefer to hire back-packers (illegals) who show up on their doorstep. So it appears that once more, the fact that illegals can be exploited runs counter to good policy. Again, I appeal that we should give give each worker, legal or not, the same rights. Another win-win proposition.

Why we need small countries: they experiment with policies

Small countries are often considered a nuisance. They are sometimes tax havens that annoy larger countries because it increases tax competition. They have more weight than their size in international organizations (UN, European Commission, ECB) or sports organizations (FIFA), which at least in the latter case encourages corruption. And they increase sample sizes in cross-country regressions without truly adding information, sometimes leading to erroneous results. But small countries are also great because it allows to experiment with policies.

That is the argument of Jeffrey Frankel. He gives plenty of examples of innovative policies adopted in small countries that turned out to be good choices. In many cases, it looks like larger countries would also benefit from adopting them, that is, smallness is not a necessary condition for success. A good read with a boatload of interesting anecdotes to bring up in conversation.

What to do when people expect the government to default on its debt

The situation in Greece is rapidly getting worse, with clear signs that a bank run is in the works, mainly because there is no party majority that would avoid a default on the public debt. In such a situation, what should the fiscal policy be? Clearly, the budgets have to be reduced dramatically as no one would be willing to lend to the government and the government can only pay with cash (which is not the new drachma, as no one will trust that either and we would have immediate hyperinflation and the complete collapse of public services). This is why the government has no choice but to honor its debts if it wants to continue offering public goods, and this is what the Greeks want, I think.

So then, what should happen if the government is committed to pay the debt, but the public does not believe it? For advice, we can turn to the recent paper by Francesco Caprioli, Pietro Rizza and Pietro Tommasino. Suppose economic agents eventually and gradually learn about the good dispositions of the government. They also believe there is a positive correlation between the level of debt and the probability of default. The consequence of these very reasonable assumptions is that government expenses need absolutely to be reduced after a negative tax revenue shock. The first reason is that the interest rate goes up and worsens the situation, the second is that the government needs to keep the debt low to avoid fueling more default expectations, not just today but also in the future due to inertia of beliefs. This is in stark contrast from a situation where the government can credibly commit to repaying the debt: then, debt can effectively be used to smooth out fluctuations in tax revenue.

Greece is so screwed.

Wealth exemptions do not matter in bankruptcy

The major aspect in bankruptcy law variation across states in the US is the wealth exemption. Some states protect substantial wealth from the creditors, the prime example being Texas where housing is exempted without limits, plus $30,000 per spouse. Maryland, however, exempts only $11,000 total personal property plus about $20,000 in owner-occupied housing. This considerable source of variation ought to lead to cross-state variation in bankruptcy rates, as several models would predict, yet the data does not show it.

Jochen Mankart explains why. He uses a life-cycle model where households borrow and save, and they are subject to a variety of shocks, the most relevant being health expense shocks, the most common trigger of bankruptcy in the United States. Varying bankruptcy exemptions, he finds no significant change in bankruptcy rates. The reason is quite simple: those who file for bankruptcy are so poor they have nothing left anyway, thus exemptions do not matter to them. Where it matters though is in the savings rate. Higher exemptions encourages especially the poor to save more. To boot, the model solves the credit card puzzle (see posts 1 and 2).

How group utility differs from individual utility

Expected utility lies at the core of almost all analyses in Economics that feature uncertainty. While one can always come up with exceptions to the rule, expected utility is by and large accepted as a good characterization of the behavior under uncertainty of individuals. The emphasis is here on individuals, and one can wonder whether the behavior could be different when they act as a group. Group dynamics are complex, and there are plenty of examples where individuals behave differently in a group than alone.

Andrea and Piergiuseppe Morone performed an experiment with students where they tried to elicit responses to risky choices, first individually, then in random groups of two. They confirm that in the first case, expected utility seems to be the best representation of the preferences, but in the second case disappointment aversion (commonly also called loss aversion) seems to be dominating. But this is far from being a proof yet, as only 38 students were part of the experiment. The authors also claim that this shows that preference aggregation drives out expected utility, a statement that can be misinterpreted. Indeed, this does not mean that aggregating individual decisions leads to a rejection of expected utility (say, in a representative agent framework). It only says that in situations where people take joint decisions, expected utility may be dominated.

Women and children first? No

The infamous quadruplicate papers of Frey, Savage and Torgler have caused a lot of grief for their multiplicity, yet they yielded a somewhat interesting, yet old result: women and children get priority on maritime disasters, crew are last, and there are some subtle differences among passengers from different nationalities. This result, however, was obtained using a sample of two: the Titanic and the Lusitania. And one also argue that there was some selection bias for the Titanic, as this was a much celebrated inaugural voyage with, let's say, an unusual set of passengers. It could therefore not hurt to increase the sample size.

Mikael Elinder and Oscar Erixson jack up the sample from 2 to 18. And the results are completely reversed. Women are at a distinct disadvantage, crew fare much better than the rest. This is the outcome you would expect from a free-for-all situation where weaker women get pushed aside on the run for the lifeboats. The lesson from this: do not trust a sample of two, even if amplified by four publications.

Looking at the transition from Malthus to industrialization in Germany using real wages

A standard model with a production function concave in labor will tell you that the marginal productivity of labor, and hence the real wage, decreases as labor increases. This the core relationship in the Malthusian model and has been the reason brought forward why some have observed that England enjoyed relative prosperity after the many deaths due to the Great Plague (and why some think the same will happen to Africa due to the AIDS epidemic). Of course, empirical evidence is somewhat thin for such old times.

Ulrich Pfister, Jana Riedel and Martin Uebele add an new data point to this by construction measured of real wages in Germany for the years 1500 to 1850, which they compare to population size. And they confirm the above. The Thirty Year War, which lead to significant population loss, was a period of significantly higher welfare for the survivors than before. This kind of relationship weakened over time though, probably reflecting that new factors became important in production. And it appears this change happened before the typical date we set for the Industrial Revolution in Germany.

Seasonality in house prices

There is a marked seasonal cycle in many housing markets. Sale volumes and house prices are significantly higher in the Summer and lower in the Winter. Evidently there should be some arbitrage, by selling high and buying low and renting in between for those who are genuinely moving or simply holding on to real estate for speculators. Possibly, the transaction costs are too high for this to happen. Or maybe the market for houses is not fluid enough for price not to cycle in a predictable way.

Cemil Selcuk picks up on this second idea and builds a search model where the supply is smaller in the Winter in the sense that the probability of finding an appropriate house is lower. As a result, there are fewer successful matches in the Winter, and they happen with a lower price because of the discount cost of waiting for better opportunities in the Summer and because the matches in the Winter are of lower quality. This is a rather trivial theoretical result, and it would be nice to know whether it approaches quantitatively the seasonal differences that are observed.

Are multipliers larger than we thought?

In the last years, much of the debate on fiscal stimulus vs. austerity was centered on the measurement of government spending multipliers. And to a large extend this was a debate between those how used dynamic stochastic general equilibrium (DSGE) models, finding small multipliers, and those using reduced form models, finding large multipliers. Both strategies have pitfalls, the structural one in that the model may be miss-specified as it is always an abstraction of a complex reality, the reduced-form one because of the Lucas Critique.

Patrick Fève, Julien Matheron and Jean-Guillaume Sahuc make the point that there could be a source of downward bias in the estimation of the elasticity in structural models. It arises from ignoring the endogeneity of government expenses combined with complementarity between public and private consumption. With exogenous expenses, the elasticity is 0.97 for the United States, with endogenous ones, it is 1.31. No small potatoes.

Tax capital *and* inheritances

I probably do not surprise anyone if I claim that how much to tax capital income and bequests is controversial. In the United States, it is due a divergent beliefs about the motivation of entrepreneurs and luck of being born in the right environment. In Europe, arguments center on fairness. The literature does not help much, with results being very sensitive to income processes, market features and preferences. Capital income is generally taxed less than labor income, often not at all, and results on bequests vary wildly, again often with zero tax results.

Thomas Piketty and Emmanuel Saez add to this bewildering literature with a tour-de-force, a very rich, yet tractable model that allows to disentangle quite a few effects and illustrate what influences these taxes, in particular parameters that can be estimated. The richness is necessary to relate the model to real world better than the extant literature which yields this unrealistic and unobserved zero tax result. It is impossible for me to summarize over 100 pages in a few paragraphs, so here is a short overview.

The model features a large degree of heterogeneity, in taste for bequests and wealth accumulation, and in labor ability. Hence labor income and inheritance are not highly correlated, allowing for a trade-off between capital and labor income taxes because, as Piketty and Saez put it, two-dimensional inequality requires two tax tools. The tax on bequests is higher if bequests represent a large fraction of output, if the aggregate elasticity of bequests with respect to their tax is high, and if the taste for bequests is low. Tax rates on bequests can go all the way to 80%, and are for most parametrizations much higher than for labor income. This is because in general labor income should be favored, as it is derived from ability, unless people really like leaving bequests a lot.

If markets are imperfect and there is risk in capital return, then tax rates of capital income and bequests start differing. The lifetime equivalent of the capital income tax is then much higher than the bequest tax rate. because return fluctuations have stronger impact on periodic capital income than bequests, which are mostly accumulated capital and labor income. Important in this is also that in all economies, most people receive very little if any at all in terms of inheritance. This makes results remarkably robust with respect to welfare criteria.

Being tall and risk aversion

Are tall people less risk-averse than others? That seems like an odd question to ask. In particular, what would one want to do with the answer? Well, if the answer is no, this can help in establishing better insurance policies. Also, if some policies influence height, it is good to know what taller people entails (besides the known higher income and confidence).

Olaf Hübler finds that, yes, tall people are less risk averse. What is more interesting is that this result disappears once you factor in other variables, like personality, skills, and information about parental behavior. That is particularly interesting because such information is often not readily available, whereas height can be easier to find and used as a proxy. So, not such an odd question after all. Another question is then why would there be such a relationship.

On the difficulty of targeting financial aid to students

With the cost of education continuing to rise, financial aid to student becomes more important to help those with merit but little means (or borrowing constraints). Identifying whether financial aid actually helps bright students go to university is of course the most important question.

Loris Vergolini and Nadir Zanini study this in the case of Italy, where they surveyed students before and after university entrance, in the context of a generous financial aid initiative targeted towards bright low-income students. The results are sobering. it does not appear to have motivated more students to go to university. Those who were going anyway now are willing to move farther, presumably to potentially better programs. But this program was only recently introduced and could not have an impact on the school effort of those about to graduate. One can hope that its existence will motivate younger cohorts to excel in school to be eligible and make it to university.

Universities as catalysts of the commercial revolution in the Middle Ages

Universities can have a profound impact on the economy of a region, Silicon Valley being a prime recent example. But this is usually difficult to see as they are spread pretty much everywhere now. Hence the interest in looking at older data, where universities were less common and economic activity differed a lot more across regions.

Davide Cantoni and Noam Yuchtman go way back, up to the 14th century in Germany. They compare the establishment of new market places to the founding of universities and find a surprisingly strong correlation when looking at the distance from the nearest university. Of course, you may think this is all endogenous. If a city or region develops, new market places emerge and there is critical mass or wealth for an institution of higher learning. But the authors argue there is causation from universities to markets. Indeed, the Papal Schism of 1386 was an exogenous shock that allowed the creation of universities, and they exploit the trend shift in the granting of markets around this date. The intuition of the causation is that universities provided training in law, which facilitated the creation of legal institutions and ultimately the enforcement of contracts. So, once more, institutions matters, but this is also an interesting counterexample to the intuition that lawyers create demand for there services with no economic or social benefit.

The cost of hiring in Germany

How much does it cost to hire someone? This question is surprisingly difficult to answer. It is not sufficient to keep a log of all the recruitment expenses, the time spent and the training costs. Indeed, there are a lot of implicit costs that may, or may not, appear in the future. Indeed, when you commit to employ someone, you also commit to insuring this person in many ways. In the US, health care insurance is a factor. In many jurisdictions, rules regarding firing may also entail substantial costs, for example if they force you to retain an underperforming employee. And you often also commit to provide some insurance against productivity changes by paying a relatively stable wage. Summing up, figuring out the cost of a hire is damn hard.

Samuel Muehlemann and Harald Pfeifer try to figure out some of these costs for skilled workers in Germany. They find a cost worth on average eight weeks of pay, and that is only taking into account time and expenses during the recruitment process as well as the monetary and time costs of training. Strangely, there are no economies of scale, as the elasticity with respect to the number of hires is 1.3. Even worse, the cost doubles from small to large firms. Labor market institutions do not seem to be blamed for this convexity. I am not sure how to rationalize all this. Large firms can hire several workers simultaneously, and this must save some costs. Same for training programs.