Knowledge that Transforms

Do natural resources benefit producer economies, or is there a “Natural Resource Curse”, perhaps as the crowd-out of manufacturing productivity spillovers reduces long-term growth? We combine new data on oil and gas endowments with Census of Manufactures microdata to estimate how oil and gas booms affect local economies in the U.S. Local wages rise during oil and gas booms, but manufacturing is not crowded out—in fact, the sector grows overall, driven by upstream and locally-traded subsectors. Tradable manufacturing subsectors do contract during resource booms, but their productivity is unaffected, so there is no evidence of foregone local learning-by-doing effects. Over the full 1969–2014 sample, a county with one standard deviation additional oil and gas endowment averaged about 1% higher real wages. Overall, the results provide evidence against a Natural Resource Curse within the U.S.

Kernel-based estimators such as local polynomial estimators in regression discontinuity designs are often evaluated at multiple bandwidths as a form of sensitivity analysis. However, if in the reported results, a researcher selects the bandwidth based on this analysis, the associated confidence intervals may not have correct coverage, even if the estimator is unbiased. This paper proposes a simple adjustment that gives correct coverage in such situations: replace the normal quantile with a critical value that depends only on the kernel and ratio of the maximum and minimum bandwidths the researcher has entertained. We tabulate these critical values and quantify the loss in coverage for conventional confidence intervals. For a range of relevant cases, a conventional 95% confidence interval has coverage between 70% and 90%, and our adjustment amounts to replacing the conventional critical value 1.96 with a number between 2.2 and 2.8. Our results also apply to other settings involving trimmed data, such as trimming to ensure overlap in treatment effect estimation. We illustrate our approach with three empirical applications.

In this article, we use micro data on both trade and production for a sample of large Chinese manufacturing firms in the footwear industry from 2002 to 2006 to estimate an empirical model of export demand, pricing, and market participation by destination market. We use the model to construct indexes of firm-level demand, marginal cost, and fixed cost. The empirical results indicate substantial firm heterogeneity in all three dimension with demand being the most dispersed. The firm-specific demand and marginal cost components account for over 30% of market share variation, 40% of sales variation, and over 50% of price variation among exporters. The fixed cost index is the primary factor explaining differences in the pattern of destination markets across firms. The estimates are used to analyse the supply reallocation following the removal of the quota on Chinese footwear exports to the EU. This led to a rapid restructuring of export supply sources on both the intensive and extensive margins in favour of firms with high demand and low fixed costs indexes, with marginal cost differences not being important.

This paper proposes an asymptotically valid permutation test for a testable implication of the identification assumption in the regression discontinuity design (RDD). Here, by testable implication, we mean the requirement that the distribution of observed baseline covariates should not change discontinuously at the threshold of the so-called running variable. This contrasts to the common practice of testing the weaker implication of continuity of the means of the covariates at the threshold. When testing our null hypothesis using observations that are “close ” to the threshold, the standard requirement for the finite sample validity of a permutation test does not necessarily hold. We therefore propose an asymptotic framework where there is a fixed number of closest observations to the threshold with the sample size going to infinity, and propose a permutation test based on the so-called induced order statistics that controls the limiting rejection probability under the null hypothesis. In a simulation study, we find that the new test controls size remarkably well in most designs. Finally, we use our test to evaluate the validity of the design in Lee (2008), a well-known application of the RDD to study incumbency advantage.

We investigate housing market responses to transaction taxes using administrative data on all property transactions in the U.K. from 2004 to 2012 combined with quasi-experimental variation from tax notches and tax stimulus. We present two main findings. First, transaction taxes are highly distortionary across a range of margins, causing large distortions to the price, volume, and timing of property transactions. Secondly, temporary transaction tax cuts are an enormously effective form of fiscal stimulus. A temporary elimination of a 1% transaction tax increased housing market activity by 20% in the short run (due to both timing and extensive responses) and less than half of the stimulus effect was reversed after the tax was reintroduced (due to re-timing). Because of the complementarities between moving house and consumer spending, these stimulus effects translate into extra spending per dollar of tax cut equal to about 1. We interpret our empirical findings in the context of a housing model with downpayment constraints in which leverage amplifies the effects of transaction taxes.

Distributional comparative statics is the study of how individual decisions and equilibrium outcomes vary with changes in the distribution of economic parameters (income, wealth, productivity, information, etc.). This article develops new tools to address such issues and illustrates their usefulness in applications. The central development is a condition called quasi-concave differences, which implies concavity of the policy function in optimization problems without imposing differentiability or quasi-concavity conditions. The general take-away is that many distributional questions in economics which cannot be solved by direct calculations or the implicit function theorem, can be addressed easily with this article’s methods. Several applications demonstrate this: the article shows how increased uncertainty affects the set of equilibria in Bayesian games; it shows how increased dispersion of productivities affects output in the model of Melitz (2003); and it generalizes Carroll and Kimball (1996)’s result on concave consumption functions to the Aiyagari (1994) setting with borrowing constraints.

This article studies an asymptotic framework for conducting inference on parameters of the form φ( heta_0), where φ is a known directionally differentiable function and heta_0 is estimated by $\hat heta_n$. In these settings, the asymptotic distribution of the plug-in estimator $φ(\hat heta_n)$ can be derived employing existing extensions to the Delta method. We show, however, that (full) differentiability of φ is a necessary and sufficient condition for bootstrap consistency whenever the limiting distribution of $\hat heta_n$ is Gaussian. An alternative resampling scheme is proposed that remains consistent when the bootstrap fails, and is shown to provide local size control under restrictions on the directional derivative of φ. These results enable us to reduce potentially challenging statistical problems to simple analytical calculations—a feature we illustrate by developing a test of whether an identified parameter belongs to a convex set. We highlight the empirical relevance of our results by conducting inference on the qualitative features of trends in (residual) wage inequality in the U.S.

We document contemporaneous differences in the aggregate labour supply of married couples across seventeen European countries and the U.S. Based on a model of joint household decision making, we quantify the contribution of international differences in non-linear labour income taxes and consumption taxes to the international differences in hours worked in the data. Through the lens of the model, taxes, together with wages and the educational composition, account for a significant part of the small differences in married men’s and the large differences in married women’s hours worked in the data. Taking the full non-linearities of labour income tax codes, including the tax treatment of married couples, into account is crucial for generating the low cross-country correlation between married men’s and women’s hours worked in the data, and for explaining the variation of married women’s hours worked across European countries.

I study how relative wages and U.S. border enforcement affect immigration from Mexico to the United States. To do this, I estimate a discrete choice dynamic programming model where a person’s decisions depend on the location of their spouse. I use a new identification strategy to estimate the effect of border enforcement on immigration, accounting for the variation in the allocation of resources along the border. I estimate the model using data on individual immigration decisions from the Mexican Migration Project. Counterfactuals show that a 10% increase in Mexican wages would decrease the number of years spent in the U.S. by about 8%. A 50% increase in enforcement reduces immigration by up to 11.6%.

This article studies the pruned state-space system for higher-order perturbation approximations to dynamic stochastic general equilibrium (DSGE) models. We show the stability of the pruned approximation up to third order and provide closed-form expressions for first and second unconditional moments and impulse response functions. Our results introduce generalized method of moments (GMM) estimation and impulse-response matching for DSGE models approximated up to third order and provide a foundation for indirect inference and simulated method of moments (SMM). As an application,we consider a New Keynesian model with Epstein–Zin preferences and two novel feedback effects from long-term bonds to the real economy, allowing us to match the level and variability of the 10-year term premium in the U.S. with a low relative risk aversion of 5.