We provide a general theoretical characterization of how firms' technology choice on a technology frontier determines the long-run elasticity of substitution between capital and labour. We show that the shape of the frontier determines factor shares and the elasticity of substitution between capital and labour. If there are adjustment costs to technology choice, the short-and long-run elasticities differ, with the long-run always higher. If the technology frontier is log-linear, the production function becomes Cobb-Douglas in the long run but, consistent with empirical evidence, short-run dynamics are characterized by gross complementarity. The approach is easily implementable and yields a powerful way to introduce CES-type production functions in macroeconomic models. We provide an illustration within an estimated dynamic general equilibrium model and show that the use of our production technology provides a good match for the short-and medium-run behaviour of the U.S. labour share.

We propose a dynamic theory of financial intermediaries that are better able to collateralize claims than households, that is, have a collateralization advantage. Intermediaries require capital as they have to finance the additional amount that they can lend out of their own net worth. The net worth of financial intermediaries and the corporate sector are both state variables affecting the spread between intermediated and direct finance and the dynamics of real economic activity, such as investment, and financing. The accumulation of net worth of intermediaries is slow relative to that of the corporate sector. The model is consistent with key stylized facts about macroeconomic downturns associated with a credit crunch, namely, their severity, their protractedness, and the fact that the severity of the credit crunch itself affects the severity and persistence of downturns. The model captures the tentative and halting nature of recoveries from crises.

This article studies how credit markets respond to policy constraints on household leverage. Exploiting a sharp policy-induced discontinuity in the cost of originating certain high-leverage mortgages, we study how the Dodd–Frank “Ability-to-Repay” rule affected the price and availability of credit in the U.S. mortgage market. Our estimates show that the policy had only moderate effects on prices, increasing interest rates on affected loans by 10–15 basis points. The effect on quantities, however, was significantly larger; we estimate that the policy eliminated 15% of the affected market completely and reduced leverage for another 20% of remaining borrowers. This reduction in quantities is much greater than would be implied by plausible demand elasticities and indicates that lenders responded to the policy not only by raising prices but also by exiting the regulated portion of the market. Heterogeneity in the quantity response across lenders suggests that agency costs may have been one particularly important market friction contributing to the large overall effect as the fall in lending was substantially larger among lenders relying on third-parties to originate loans. Finally, while the policy succeeded in reducing leverage, our estimates suggest this effect would have only slightly reduced aggregate default rates during the housing crisis.

© The Author(s) 2018. Low adoption of agricultural technologies holds large productivity consequences for developing countries. Many countries hire agricultural extension agents to communicate with farmers about new technologies, even though a large academic literature has established that information from social networks is a key determinant of product adoption. We incorporate social learning in extension policy using a large-scale field experiment in which we communicate to farmers using different members of social networks. We show that communicator own adoption and effort are susceptible to small performance incentives, and the social identity of the communicator influences others' learning and adoption. Farmers appear most convinced by communicators who share a group identity with them, or who face comparable agricultural conditions. Exploring the incentives for injection points in social networks to experiment with and communicate about new technologies can take the influential social learning literature in a more policy-relevant direction.

We use 130 years of data on historical migrations to the U.S. to show a causal effect of the ancestry composition of U.S. counties on foreign direct investment (FDI) sent and received by local firms. To isolate the causal effect of ancestry on FDI, we build a simple reduced-form model of migrations: Migrations from a foreign country to a U.S. county at a given time depend on (1) a push factor, causing emigration from that foreign country to the entire U.S., and (2) a pull factor, causing immigration from all origins into that U.S. county. The interaction between time-series variation in origin-specific push factors and destination-specific pull factors generates quasi-random variation in the allocation of migrants across U.S. counties. We find that doubling the number of residents with ancestry from a given foreign country relative to the mean increases the probability that at least one local firm engages in FDI with that country by 4 percentage points. We present evidence that this effect is primarily driven by a reduction in information frictions, and not by better contract enforcement, taste similarities, or a convergence in factor endowments.

Individuals are constantly processing external information and translating it into actions. This draws on limited resources of attention and requires economizing on attention devoted to signals related to economic behaviour. A natural measure of such costs is based on Shannon’s “channel capacity”. Modelling economic agents as constrained by Shannon capacity as they process freely available information turns out to imply that discretely distributed actions, and thus actions that persist across repetitions of the same decision problem, are very likely to emerge in settings that without information costs would imply continuously distributed behaviour. We show how these results apply to the behaviour of an investor choosing portfolio allocations, as well as to some mathematically simpler “tracking” problems that illustrate the mechanism. Trying to use costs of adjustment to explain “stickiness” of actions when interpreting the behaviour in our economic examples would lead to mistaken conclusions.