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.