Econometrica最新文献

Econometric analysis typically focuses on the statistical properties of fixed estimators and ignores researcher choices. In this article, I instead approach the analysis of experimental data as a mechanism-design problem that acknowledges that researchers choose between estimators, sometimes based on the data and often according to their own preferences. Specifically, I focus on covariate adjustments, which can increase the precision of a treatment-effect estimate, but open the door to bias when researchers engage in specification searches. First, I establish that unbiasedness as a requirement on the estimation of the average treatment effect can align researchers' preferences with the minimization of the mean-squared error relative to the truth, and that fixing the bias can yield an optimal restriction in a minimax sense. Second, I provide a constructive characterization of treatment-effect estimators with fixed bias as sample-splitting procedures. Third, I discuss the implementation of second-best estimators that leave room for beneficial specification searches.

We thank Man Chon Iao—a Ph.D. student at NYU—for bringing to our attention that we had a mistake in our code that generated the results in the published version of our paper. In this erratum, we: (1) discuss the mistake, (2) highlight the changes we made to our code in response to the mistake, and (3) reproduce all the relevant tables and figures of the paper after correcting the mistake. In particular, Section 2 of this erratum discusses the mistake, Section 3 updates the paper's core tables and figures, and Section 4 updates all remaining motivating and robustness tables and figures. Any table or figure we did not reproduce means the table/figure was unchanged compared to the original.

In summary, the magnitudes of the reported estimates change, although the qualitative results remain.

At the heart of the empirical component of our paper is the creation of state level wage measures during the period surrounding the Great Recession. When we initially made our composition adjusted state level wage measures, we summed over the wages for those working in each of our detailed demographic groups within each state for each year using repeated cross-sectional data from the American Community Survey. We then divided the total wages paid in each state-demographic group-year cell by the total number of individuals within each state-demographic group-year cell. This step produced a measure of the average wage for each demographic group in each state in each year. We then aggregated the state level demographic groups in each year—holding the group weights fixed at some initial time period level—to make our measure of demographically adjusted state wages in each year. Our mistake stems from the fact that we should have divided by the total number of “working” individuals within each group instead of the total number of individuals (unconditional on work status) within each group.

The main empirical result in the paper is the estimation of a state level New Keynesian Wage Phillips Curve (Table V, Section 5). The main quantitative results are the implications for aggregate business cycles of incorporating regional data when estimating a DSGE model (Figures 4 and 5, Section 7). We update these results below.

Below, we present the updated results for Figure 1, Figures 3, 3, 4, 5, Appendix A5–A6, and Tables I, II, and IV, V, VI, VII, VIII of the main paper. All other tables and figures are unaffected by our changes.

Policymakers often test expensive new programs on relatively small samples. Formally incorporating informative Bayesian priors into impact evaluation offers the promise to learn more from these experiments. We evaluate a Colombian program for 200 firms which aimed to increase exporting. Priors were elicited from academics, policymakers, and firms. Contrary to these priors, frequentist estimation cannot reject null effects in 2019, and finds some negative impacts in 2020. For binary outcomes like whether firms export, frequentist estimates are relatively precise, and Bayesian posterior intervals update to overlap almost completely with standard confidence intervals. For outcomes like increasing export variety, where the priors align with the data, the value of these priors is seen in posterior intervals that are considerably narrower than the confidence intervals. Finally, for noisy outcomes like export value, posterior intervals show almost no updating from priors, highlighting how uninformative the data are about such outcomes. Future policy experiments could use these posteriors as priors in a Bayesian or empirical Bayesian analysis.

Government debt can be rolled over forever without primary surpluses in some stochastic economies, including some economies that are dynamically efficient. In an overlapping-generations model with constant growth rate, g, of labor-augmenting productivity, and with shocks to the durability of capital, we show that along a balanced growth path, the maximum sustainable ratio of bonds to capital is attained when the risk-free interest rate, r_f, equals g. Furthermore, this maximal ratio maximizes utility per capita along a balanced growth path and ensures that the economy is dynamically efficient.

Landmines affect the lives of millions in many conflict-ridden communities long after the end of hostilities. However, there is little research on the role of demining. We examine the economic consequences of landmine removal in Mozambique, the only country to transition from heavily contaminated in 1992 to mine-free in 2015. First, we present the self-assembled georeferenced catalog of areas suspected of contamination, along with a detailed record of demining operations. Second, the event-study analysis reveals a robust association between demining activities and subsequent local economic performance, reflected in luminosity. Economic activity does not pick up in the years leading up to clearance, nor does it increase when operators investigate areas mistakenly marked as contaminated in prior surveys. Third, recognizing that landmine removal reshapes transportation access, we use a market-access approach to explore direct and indirect effects. To advance on identification, we isolate changes in market access caused by removing landmines in previously considered safe areas, far from earlier nationwide surveys. Fourth, policy simulations reveal the substantial economywide dividends of clearance, but only when factoring in market-access effects, which dwarf direct productivity links. Additionally, policy counterfactuals uncover significant aggregate costs when demining does not prioritize the unblocking of transportation routes. These results offer insights into the design of demining programs in Ukraine and elsewhere, highlighting the need for centralized coordination and prioritization of areas facilitating commerce.

We develop and estimate a model of consumer search with spatial learning. Consumers make inferences from previously searched objects to unsearched objects that are nearby in attribute space, generating path dependence in search sequences. The estimated model rationalizes patterns in data on online consumer search paths: search tends to converge to the chosen product in attribute space, and consumers take larger steps away from rarely purchased products. Eliminating spatial learning reduces consumer welfare by 12%: cross-product inferences allow consumers to locate better products in a shorter time. Spatial learning has important implications for product recommendations on retail platforms. We show that consumer welfare can be reduced by unrepresentative product recommendations and that consumer-optimal product recommendations depend on both consumer learning and competition between platforms.

We use the martingale construction of Luedtke and van der Laan (2016) to develop tests for the presence of treatment heterogeneity. The resulting sequential validation approach can be instantiated using various validation metrics, such as BLPs, GATES, QINI curves, etc., and provides an alternative to cross-validation-like cross-fold application of these metrics. This note was prepared as a comment on the Fisher–Schultz paper by Chernozhukov, Demirer, Duflo, and Fernández-Val, forthcoming in Econometrica.