Knowledge that Transforms

This article studies the transmission of the Global Financial Cycle (GFC) to domestic credit market conditions in a large emerging market, Turkey, over 2003–13. We use administrative data covering the universe of corporate credit transactions matched to bank balance sheets to document four facts: (1) an easing in global financial conditions leads to lower borrowing costs and an increase in local lending; (2) domestic banks more exposed to international capital markets transmit the GFC locally; (3) the fall in local currency borrowing costs is larger than foreign currency borrowing costs due to the co-movement of the uncovered interest rate parity (UIP) premium with the GFC over time; (4) data on posted collateral for new loan issuances show that collateral constraints do not relax during the boom phase of the GFC.

We develop a concept of weak identification in linear instrumental variable models in which the number of instruments can grow at the same rate or slower than the sample size. We propose a jackknifed version of the classical weak identification-robust Anderson–Rubin (AR) test statistic. Large-sample inference based on the jackknifed AR is valid under heteroscedasticity and weak identification. The feasible version of this statistic uses a novel variance estimator. The test has uniformly correct size and good power properties. We also develop a pre-test for weak identification that is related to the size property of a Wald test based on the Jackknife Instrumental Variable Estimator. This new pre-test is valid under heteroscedasticity and with many instruments.

Critics claim that patent screening is ineffective, granting low-quality patents that impose unnecessary social costs. We develop an integrated framework, involving patent office examination, fees, and endogenous validity challenges in the courts, to study patent screening both theoretically and quantitatively. In our model, some inventions require the patent incentive while others do not, and asymmetric information creates a need for screening. We show that the endogeneity of challenges implies that courts, even if perfect, cannot solve the screening problem. Simulations of the model, calibrated on U.S. data, indicate that screening is highly imperfect, with almost half of all patents issued on inventions that do not require the patent incentive. While we find that the current patent system generates positive social value, intensifying examination would yield large welfare gains. The social value of the patent system would also be larger if complemented by antitrust limits on licensing.

We study how strategic interaction and cooperation are affected by the heterogeneity of cognitive skills of groups of players, over consecutive plays of repeated games with randomly matched opponents using Prisoner’s Dilemma as stage game. We observe overall higher cooperation rates and average final payoffs in integrated treatment groups—where subjects of different IQ levels interact together—than in separated treatment groups. Lower IQ subjects are better off and higher IQ subjects are worse off in integrated groups than in separated groups. Higher IQ subjects adopt harsher strategies when they are pooled with lower IQ subjects than when they play separately. We demonstrate that this outcome should be expected in learning and evolutionary models where higher intelligence subjects exhibit lower frequency of errors in the implementation of strategies. Estimations of errors and strategies in our experimental data are consistent with the model’s assumptions and predictions.

We exploit a volcanic “experiment” to study the costs and benefits of geographic mobility. In our experiment, a third of the houses in a town were covered by lava. People living in these houses were much more likely to move away permanently. For the dependents in a household (children), our estimates suggest that being induced to move by the “lava shock” dramatically raised lifetime earnings and education. While large, these estimates come with a substantial amount of statistical uncertainty. The benefits of moving were very unequally distributed across generations: the household heads (parents) were made slightly worse off by the shock. These results suggest large barriers to moving for the children, which imply that labour does not flow to locations where it earns the highest returns. The large gains from moving for the young are surprising in light of the fact that the town affected by our volcanic experiment was (and is) a relatively high income town. We interpret our findings as evidence of the importance of comparative advantage: the gains to moving may be very large for those badly matched to the location they happened to be born in, even if differences in average income are small.

Allocating resources without monetary payments is expected to yield inefficient allocations. Theory suggests that introducing rationing when resources are allocated repeatedly over time can mitigate this issue, while the magnitude of the resulting efficiency gains is an empirical question in most settings. We study a dynamic assignment mechanism used by the Michigan Department of Natural Resources to allocate bear hunting licenses and find that it yields a more efficient allocation than static mechanisms, allocating participants to types of resources for which they have a higher value without crowding out participants with a high overall value for hunting. Our empirical analysis also highlights the importance of heterogeneity across participants and across allocated resources for determining the efficiency of a dynamic allocation mechanism.

This article proposes a test for the conditional superior predictive ability (CSPA) of a family of forecasting methods with respect to a benchmark. The test is functional in nature: under the null hypothesis, the benchmark’s conditional expected loss is no more than those of the competitors, uniformly across all conditioning states. By inverting the CSPA tests for a set of benchmarks, we obtain confidence sets for the uniformly most superior method. The econometric inference pertains to testing conditional moment inequalities for time series data with general serial dependence, and we justify its asymptotic validity using a uniform non-parametric inference method based on a new strong approximation theory for mixingales. The usefulness of the method is demonstrated in empirical applications on volatility and inflation forecasting.

We study the co-evolution of religion, science, and politics. We first uncover, in international and U.S. data, a robust negative relationship between religiosity and patents per capita. The model then combines: (1) scientific discoveries that raise productivity but sometimes erode religious beliefs; (2) a government that allows innovations to diffuse, or blocks them; (3) religious institutions that can invest in doctrinal reform. Three long-term outcomes emerge. The “Western-European Secularization” regime has declining religiosity, unimpeded science, and high taxes and transfers. The “Theocratic” regime involves knowledge stagnation, unquestioned dogma, and high religious-public-goods spending. The “American” regime combines scientific progress and stable religiosity through doctrinal adaptations, with low taxes and some fiscal-legal advantages for religious activities. Rising income inequality can, however, empower a Religious-Right alliance that starts blocking belief-eroding ideas.

This article develops and estimates a dynamic model where individuals differ in ability and location preference to evaluate the mechanisms that affect the evolution of immigrants’ careers in conjunction with their re-migration plans. Our analysis highlights a novel form of selective return migration where those who plan to stay longer invest more into skill acquisition, with important implications for the assessment of immigrants’ career paths and the estimation of their earnings profiles. Our study also explains the willingness of immigrants to accept jobs at wages that seem unacceptable to natives. Finally, our model provides important insight for the design of migration policies, showing that policies that initially restrict residence or condition residence on achievement shape not only immigrants’ career profiles through their impact on human capital investment but also determine the selection of arrivals and leavers.

To assign teachers to schools, a modified version of the well-known deferred acceptance mechanism has been proposed in the literature and is used in practice. We show that this mechanism fails to be fair and efficient for both teachers and schools. We identify a class of strategy-proof mechanisms that cannot be improved upon in terms of both efficiency and fairness. Using a rich dataset on teachers’ applications in France, we estimate teachers preferences and perform a counterfactual analysis. The results show that these mechanisms perform much better than the modified version of deferred acceptance. For instance, the number of teachers moving from their positions more than triples under our mechanism.