Do remittances create credit?

Remittances from foreign workers to their families at home are an important source of income in some countries. Whether this is a good solution for the long term is debatable, though, as it may create a dependency. Thus it is important to understand whether these remittances end up not just fueling consumption but build the basis for investment in various forms of capital and future domestic income.

Christian Ambrosius looks at Mexico and finds that receiving remittances is strongly associated with the ownership of a savings account, especially in rural areas. So at least all of the remittances are going into consumption. More interesting is that there is also evidence that it also builds up some borrowing capacity, especially in microfinance banks. Once more, it is not the big financial institutions that seem to be the key to the development of the poorest, but the small institutions that rely on the local social network. And remittances are perfect to finance that.

Why does Angola invest in Portugal?

Standard theory tells us that a country with a low capital endowment, relative to its labor endowment, should have high capital returns and thus should be attracting foreign capital until capital returns are equal at home and abroad. While there is foreign direct investment from the North to the South, it is by far as high as it should be, and capital returns are far from being equalized. There are proposed answers to this puzzle, from mismeasurement to country-specific risk, but that does not explain why there would be foreign direct investment from the South to the North.

Carlos Pestana Barros, Bruno Damásio and João Ricardo Faria look at the case of Angola investing substantially in its former colonial master, Portugal. They build a model of a open economy subject to corruption practices. It is not quite clear to me how this model maps into the linear equation that is estimated (partly because not all equations display in the paper). But at this points, the interesting results is that this FDI is driven by exports and mostly by corruption. One has to understand that corruption in Angola is among the world's highest. For example, there is an unexplained residual in the country's fiscal account that corresponds to about a quarter of its GDP, which is absolutely mind boggling. This corruption is so big that not only does it dry out the FDI flow from Portugal, it reverses it.

Foreclosure crisis: it is not about irrationality and sneaky bankers

Why has there been a foreclosure crisis in the United States? Two popular explanations are that 1) evil mortgage brokers forced people to take mortgages they could not possibly honor, and 2) those taking the mortgages did not understand what they were doing. As an economist who insists on logic and rationality, it is difficult to adopt these points of view, except that a point could be made about perverse incentives in the mortgage industry where the risk is masked and pushed unto unsuspecting people. But were mortgage holders really that stupid to think they would be able to make it? After all, I know several PhD economists who are still underwater, and they do not look stupid to me.

Christopher Foote, Kristopher Gerardi and Paul Willen come to the rescue. They argue that market participants made perfectly rational decisions given the information they had a the time, and in particular given the beliefs they had. The latter turned out to be too optimistic in retrospect though. Foote, Gerardi and Willen come to this conclusion with an interesting data analysis. They draw 12 "facts" that together contradict the popular explanations. Foremost, it does not appear that there is any correlation between exploding mortgage rates and mounting foreclosures. Also, even borrowers with spotty credit have had a remarkably good repayment history. One should thus not conclude that mortgages were designed to fail. Furthermore, all the instruments and innovations in the mortgage industry were introduced well before the past decade, and there was no significant regulatory change. Market participants knew what they were doing, had plenty of information and understood the risks. They were too optimistic though. Finally, no top-rated mortgage-backed security turned out to be toxic. The same cannot be said about similar bond-based securities.

All in all, there was nothing really wrong with the mortgage market apart from being too optimistic. In other words, there was a bubble, which can be a perfectly rational outcome. So there. But we still need to better cope with the eventuality of a bubble.

Put some economics back into spatial econometrics

One of the hot areas for econometric research in recent years has been spatial econometrics. Think of it, at least initially as time series econometrics in a different dimension. One interesting aspect of it is that instead of being single-dimensional like time series, it can be two-dimensional, or even more I guess. This field brings interesting new challenges, and it must be exciting working in this field. However, as too often in econometric theory, research becomes quickly detached from reality, and more specifically from the needs of empiricists. N never goes to infinity, for example.

Luisa Corrado and Bernard Fingleton bring forward another important point. These techniques are used to test economic theories, so one should be able to embed some restrictions from economic theory. It is all nice and sweet when one can find an optimal weighting matrix with the right properties, but it is useless if the found weights cannot be matched with anything one wants to test. The causality goes the wrong way: first determine restrictions from the theory, then use the constraints to find the optimal weighting matrix.

This is not just a theoretical consideration. Spatial lags are crucial in spatial econometrics and are suppose to capture some network effects. But they can also soak up the impact of latent or unobserved variables, as in "regular" econometrics. This can lead to severe miss-specification and biased inference, somethings one is all to familiar with using lags in time series. In fact, one should be downright suspicious of any time-series results that only holds when lagged dependent variables are used. The same must apply to spatial econometrics.

How integrated are Eastern and Western Europe now?

25 years ago, it was very rare to see a car with Eastern European plates in Western Europe. Now, they are all over the place, including trucks (why are there so many from Romania?). This is a clear indication, even if you ignore history, that the East-West integration is stronger than it has been for a long time. But there are more aspects to integration than the movement of cars.

Catherine and Klaus Prettner basically look whether the two regions are cointegrated. They build two national aggregates, one with 12 European Community countries (unfortunately no UK) and 5 Central European countries. Using a vector error-correction model with restrictions from a standard open-economy business-cycle model with cash-in-advance. Output shocks to one area spill over to the other, surprisingly in similar magnitudes in both directions. Interest rate shocks are expectedly asymmetric though: West impacts East, but East does not impact West. But given that all this has been in transition mode over the 1995-2009 sample, I really wonder how these impacts have changed over time. A framework with time varying coefficients would have been helpful here.

Air conditioners on the rebound

The various cash for clunkers programs during the last recession had two objectives in mind: create aggregate demand (or shift it from good to bad times) and improve the stock of capital. In the case of cars, it was expected that this would lower pollution. Other programs outside of recessions have had the same goal, for example subsidies to replace light bulbs or appliances for more energy efficient ones. But it does not always work out as expected.

Lucas Davis, Alan Fuchs and Paul Gertler look at a recent and large appliance renewal initiative in Mexico. A staggering 1.5 million households changed their refrigerator or air condition units for better ones, with again the goal of reducing electricity consumption. But it seems to have backfired for the AC units. Indeed, they seem to have been so much more efficient that people feel less guilty of running them, increasing the total energy consumption in the process. This is called the rebound effect, which has already been discussed here. And once again, nothing beats taxing energy use instead of subsidizing alternative energy, or alternative energy uses.

The impact of recessions on economist productivity

In recessions, those who have the hardest time finding jobs are those who try for the first time. Facing these difficulties, many decide to pursue their studies in graduate school. From this, one should expect future productivity to be higher in the future, because of the higher level of human capital. But for a given level of human capital, labor productivity should be lower post-recession, because the marginal new graduate is of lower quality.

Michael Boehm and Martin Watzinger look at the performance of PhD economists and find that those who studied or graduated during a recession over-perform the others as measured by publication records. That would not surprise me for those who graduated during tough times, as only the best get jobs. Indeed, the study matches those who graduated with those who are still members of the American Economic Association. Thus, there is some selection bias. But for those who start in a recession, and thus would graduate in "normal" times, given the average length of a recession, this is more surprising. Boehm and Watzinger can justify this with the good old Roy model of reallocation of talent: in a recession, people switch to recession proof sectors, and those who can do this the most easily are those who are about to choose in which sector to work: students. As the number of graduate students slots does not change much, at least in Economics, the quality of those admitted is higher, if the admission officers do their work well. As the publication record many years later shows, they do.

Predation, labor share and empirical evidence

When you look at national accounts, one striking fact is that the labor income share is remarkably stable in each country. And the average level of this labor income share varies quite dramatically across countries. These differences vanish to a large extend once you allocate proprietor's income (these are business owners) to labor income and capital income, but some differences remain.

Carlos Bethencourt and Fernando Perera-Tallo try to explain these differences. They build a model where workers can choose to produce or predate. If the labor income share is high, they rather produce, if it is low, predating is more interesting. With an increase in productivity, the labor income share increases, and this amplifies the impact on output as fewer people predate. This mechanism can thus make it easier to explain GDP/capita differences across countries from total factor productivity differences.

But for all this to happen, you need an elasticity of substitution between capital and labor in the production function below one, or the labor income share would not change. Empirical evidence for that is not that compelling though (hence the attractiveness of the Cobb-Douglas production function). And if the elasticity is above one, all results are reversed. But assume it is lower than one for a moment. Then it means that any attempt to improve institutions to make predation less rewarding should improve output. That would be anti-corruption campaigns, for example. Yet, I am not convinced that corruption actually lowers output. As I posted before, the empirical literature is not conclusive on this. And that empirical result would be consistent with the elasticity of substitution being close to one, if this model were not to be rejected.

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.