Education, natural resources and corruption

Poor countries are cursed by corruption, low human capital and an economy mostly based on natural resources. These three factors have often been treated as exogenous to GDP and in particular to each other. But could they be linked? The correlation is certainly there, what about causation?

Iván Aldave and Cecilia García-Peñalosa make the argument that the "blessing" of natural resources gives the wrong incentives: why get educated when the soil is rich without effort? This is something we already knew, see for example how rich countries without natural resources are (see: Alps, Scandinavia, Great Britain). But the link from natural resources to corruption is more intriguing. Natural resources are generally state owned, thus more prone to rent seeking than, say, manufacturing. The more natural resources, the more you want to invest in political capital to the detriment of other forms of capital.

How to discount time for climate change policies

If you ever tried to argue with a biologist about the pros and cons of conservation, of climate change or habitat encroachment, for example, the debate will pretty fast narrow down to whether the future should be discounted or not. For an economist, this is a nonsensical debate, as the present value of anything is infinity if there is no discount rate and a possibly infinite lifetime. But among economists as well, there is a debate about what discount rate to use, in particular after the release of the Stern Review (previous post about this).

David Anthoff, Richard Tol and Gary Yohe now provide a much more rational discussion about how to treat discounting for climate change. Take a standard Ramsey model, and in the Euler equation one needs to take into account time preference, risk aversion and the growth rate of marginal utility. Under fairly standard assumptions, this amounts to figuring out the (pure) discount rate, the curvature of utility and the growth rate of consumption. Obviously, the (pure) discount rate will have a large impact on the discount rate to use, but so will have risk aversion considering the large uncertainties about climate change. The uncertainties are not so much about whether it is happening, but rather how far and fast this change will happen.

Interestingly, Anthoff, Tol and Yohe find that the present value of the social cost of carbon is $61 a metric ton, which is a lot more than the $0 the US Congress seems to be ready to price it for the initial carbon permits...

Can migration be Pareto optimal?

Immigration policy is a continuous hot potato, probably because there are winners and losers from any change. Could we then not devise some compensation scheme so as to obtain a Pareto improvement? Clearly, migrants benefits from moving, as they chose to move. In the receiving country, some gain, some lose, but on can assume that on aggregate the country wins, as it lets people in, but not too many, to avoid hurting too much those that lose. The latter could be compensated, though.

Gabriel Felbermayr and Wilhelm Kohler argue that this cannot work for immigration. It works for international trade, because one can discriminate more easily against those who benefit the most from open borders, and they are willing to pay for the greater benefits from gains from trade. In the case of immigration, other considerations come into play, such as that one should not discriminate people by their origin. Thus it becomes impossible to tax some of their welfare gain from migration to compensate local losers. That is a problem of political feasibility, but that should not hinder us from advocating what is politically not feasible, because it is better than the politically feasible.

Forecasting with DSGE models

Dynamic Stochastic General Equilibrium (DSGE) models are designed to do policy analysis. They are based on microfoundations and calibrated or estimated to provide quantitative answers to policy scenarios and in particular study environments for which there is no historical precedent. These model are not designed for forecasting, traditional statistical tools, where ad-hoc models with minimal theory are fitted to the data, are optimized for this. But one may still ask whether DSGE models are any good for forecasting.

Rochelle Edge, Michael Kiley and Jean-Philippe Laforte take the the DSGE model used by the Federal Reserve Board to check on its forecasting performance and are surprised by its success. If fact, the specific DSGE model they use, dubbed "Edo", outperforms both the time-series model of the Fed and the staff predictions. Now, "Edo" is not a simple and small real business cycle model, it is a heavy beast with lots of details. Adding complexity allows a model to provide richer results, but contrarily to statistical models, it may lower the performance of a DSGE model. Indeed, adding new features may undo well-performing components of the model, as everything is interlinked ("general equilibrium"). It is all the more remarkable that this large model works so well.

Interestingly, this exercise is performed with real-time data, i.e., data that was available at the time the forecast would have been made, neglecting subsequent revisions. This is important from a policy point of view, as real-time forecasts are those that really matter for policy decisions.

To all naysayers, DSGE models are good for forecasting, and better than traditional models. The fact that they may not have predicted the current crisis does not mean that they need to be rejected en bloc. Did traditional, statistical models do any better? Of course not, as they are notoriously bad at predicting turning points. Also, the fact that DSGE models (among others) failed this time does not mean that suddenly all lessons learned from these models are not valid anymore and that Keynesian policies are suddenly effective again.

Credit markets and the persistence of unemployment

Some literature has established that the presence of credit constraints can have an impact on the unemployment rate. It can reduce by making it impossible to find credit when unemployed and thus urging unemployed workers to find a job as fast as possible. But it can also increase it, either because structural change in the economy needs investment (and credit) or because search frictions on the labor market are mirrored by search frictions on the credit market. These have been among some explanations offered for why unemployment rate are usually higher in Europe than in America. But his does not explain why the unemployment rate is more persistent in Europe.

Nicolas Dromel, Elie Kolakez and Etienne Lehmann believe credit constraints also have a role to play here. And they do. The key is that during the transition from trough to peek of the business cycle, firms take a while to get financing as their net worth is still low. Net worth is important because it is needed as collateral in this credit constraint world. As credit is slowed, firms cannot hire as fast as they could, and this again hurts their net worth. In the US, credit is available much more broadly than in Europe, and in particular there is more willingness to take a gamble early in the recovery in a recession. This speeds it up and leads to less persistent unemployment. We'll see in the coming months whether this is still true.

A large US current account deficit is normal

The recent decades have seen a steady decline of the net financial asset position of the United States. As of 2006, the current account deficit of the US amounts to 1.6% of world GDP, US net foreign asset correspond to -5% of world GDP. Mostly everyone sees that as a huge problem and a sign the US is on the decline.

Enrique G. Mendoza, Vincenzo Quadrini and José-Víctor Ríos-Rull argue that this is completely normal and a consequence of globalization and the fact that the US has much better developed financial markets. In some way, this allows the United States to do more with less. There experiment is the following: suppose a world where firms are subject to various idiosyncratic shocks. There are two countries, one where the firms can better insure against those shocks than in the other. The "better" country will see less capital formation in autarky, as firms require less own funds for insurances, and thus better returns on capital. But upon international liberalization, interest rates are equalized worldwide, and the dispersion of capital across countries becomes wider.

Mendoza, Quadrini and Ríos-Rull formalize this with a full-blown model they calibrate and then use to compare to actual outcomes. They not only confirm the intuition above, they also find that the magnitudes of the effects correspond roughly to those seen in the data. The also manage to replicate how the portfolio of US assets has changed: more net equity and FDI and more net debt obligations. In other words, there nothing abnormal with the evolution of the US current account.

Unemployment insurance and work ethic

Why is the average unemployment rate so high in Europe? This question has kept economists busy for some time and various explanations has been proposed: the type of shocks Europe faces combined with the type of education, the generosity of unemployment insurance, tax rates, "culture", measurement. All these explanations have some merit, but I like to see the bigger picture, especially as these factors are not necessarily exogenous.

In this respect, Jean-Baptiste Michau, provides an interesting exercise, where the work ethic culture parents teach their children depends on what they expect unemployment insurance generosity will be, and the latter depends on the work ethic of the population. Such a model can provide a story on how work ethic and unemployment insurance evolve over time. There is now a large literature on policy formation, and I think this paper makes a good point that policy can have a feed back of preference formation.

When to bribe with sex

There are these times where you need to bribe and you do not know what kind of bribe to use: cash or sex? Luckily, José Rodrigues-Neto has just produces a handy and rigorous guide for your decision making.

Clearly, sex as a bribe is less efficient than money, for reasons related to the deadweight loss of Christmas. However, sex may be less detectable. Also, and the author does not take this into account, less expensive to provide for some. In short, the optimal bribe is money when there is a large efficiency loss with sex, but it is sex when the receiver likes that a lot. It could be both in between those extremes.

Of course, there are other favors than sex that could be offered. Meals and tickets to events, however, have well defined monetary values unless there is some rationing (think, Bayreuth tickets or meals with politicians). In that respect, a Wagner opera is like sex. There, I said it.

Risk aversion is learned behavior

We often consider preferences to be given and unchanging. I reported earlier about risk aversion to be found to be changing according to external circumstances. But this can still be rationalized as invariant preferences if one increases the state space over which preferences are formed to include these circumstances. But could preferences be learned? There is no doubt about this. Look around you and see for example how gastronomic taste runs in families. There is also evidence that intertemporal substitution and savings behavior more generally is inherited (a reference escapes me now).

Pushing the envelope further, Bruno Moreira, Raul Matsushita and Sergio Da Silva find an intriguing result: toddlers are risk lovers, yet older children and adults are risk averse, so it must be that risk aversion is learned. I cannot reject this conclusion, but so is an alternative explanation, that there are hormonal changes or changes in the brain as toddlers age that would alter their preferences. I guess we need to wait for neuroeconomics to study children as well to convince me of the authors' conclusion.

Automatic fiscal discipline

Would people who do not care about future generations vote to increase government debt indefinitely? Zheng Song, Kjetil Storesletten and Fabrizio Zilibotti argue that no, even in an environment where there is no possible commitment to future fiscal policy.

How is this possible? Take a simple 2-period overlapping generations model where people work when young and save for retirement when old. They are taxed for the provision of a public good that they care about. Each agent votes twice, as young and as old, for fiscal policy: the tax and the provision of the public good (and thus the deficit).

Because the young ones worry about the provision of public goods in the future, they want to impose some fiscal discipline. This is exacerbated as taxes (which are increasing over time) become more distortionary. Also, when debt is already high, the young ones realize that their future public goods will be low, thus they make sure debt is reduced so that a proper quantity of public goods will be provided. In some sense, this is the inverse of the "starving the governement" argument that the second Bush administration seems to have advocated. But then, it may not have cared about public goods.

PS: I was off the Internet for two weeks. I appreciate all the concern about my absence and should have warned my readers. However, I can only recommend getting completely off the Internet for some time. It shows how dependent (or addicted) we have become.

Are the sick or the rich retiring early?

A major challenge of the necessary reform of social security is to keep people from retiring early and in particular getting them to retire later. The big question here is what incentive will get them to voluntarily lengthen their working years. To do anything sensible here, one needs first to understand the retirement decision.

Jennifer Roberts, Nigel Rice and Andrew Jones notice that in Britain, early retirees are rich and in poor health. In Germany, early retirees are poor and also in poor health. This would mean that health is a major determinant in retirement decisions, not wealth or income. To establish this more firmly, the build a hazard model and confirm the result. This means: financial incentives to keep people from taking early retirements, and by extension to stay on longer, will not work if health outcomes do not improve.

Optimal doping testing

Doping appears to be pervasive in sports. If one wants to fight it, it opens the question about what the optimal strategy is, where the strategy space is comprised of the test frequency and the penalty. It is quite obvious that test should not be predictable.

Dmitry Ryvkin approaches this question using winner-take-all contests. With low participant numbers, the larger the tournament, the more frequently players need to be tested. But starting from some threshold, the frequency can decease. The reason is that as more players join, the expected payoffs of dopers and non-dopers decrease, but the payoff of doping first increases and then decreases. This is based on the assumption that the expected payoff of winning decreases in the number of players (thus prestige of winning does not increase faster than the number of players).

In terms of penalty, players that are caught doping are excluded from the contest, no surprise, but are also subject to a small penalty. This is required because it enhances the effectiveness of testing by making the testing probability non-monotonic in the number of players. This seems a rather technical argument. But I surmise that making players risk averse instead of risk neutral would not make this additional penalty necessary.

Measuring unemployment with Google

Unexpected statistics sometimes work surprisingly well in measuring in a more timely manner than official numbers some important economics aggregates. The prime example is the recession index of The Economist, which is based on the frequency of the word "recession" in the Wall Street Journal and the New York Times. This measure agrees well with the NBER business cycle dates, and does so much earlier than official data is released or the NBER ruled. Of course, one could argue that there is an endogeneity issue with this index, and journalists may talk up a recession, and then it really happens.

Nikos Askitas and Klaus Zimmermann offer another indicator that does not suffer from such endogeneity problem. They claim that the German unemployment rate is appropriately measured by Google searches using some keywords, like (translating) "unemployment office or agency", "unemployment rate", "personnel consultant" or the most popular job sites. What can Google not do?