Professor Matthias Parey

We estimate the effects of in-utero exposure to a trade embargo on survival and human capital in an import-dependent developing country. Using a regression discontinuity design, we find that a nearly comprehensive embargo imposed by India on Nepal in 1989 led to a large decline in reported live births, and increased early life mortality. The decline in births is concentrated in poorer, more remote districts, and is sharper for female births than male births, consistent with documented gender discrimination. Women survivors of exposure are more educated in adulthood than unexposed cohorts.

This entry discusses programs that support, encourage or administer International Student Mobility (ISM). According to the definition from the Higher Education Funding Council for England (HEFCE, 2004), ISM is “any form of international mobility which takes place within a student’s programme of study in higher education”. ISM programs can refer to supporting outbound students (outward mobility) as well as incoming students from abroad (inward mobility). Students planning a spell abroad can either plan and organize their stay independently (as what are called free movers) or via a student exchange program. This entry begins by providing an overview of patterns of student mobility, and then describes the role of student mobility programs. ISM includes both short-term study abroad visits as well as long-term study abroad stays for entire degree programs. This entry emphasizes study abroad as a part of a student’s higher education studies (often referred to as credit mobility), rather than completing an entire degree program abroad (degree mobility). In the following, the challenges of evaluating the effect of study abroad programs on subsequent outcomes are discussed. The introduction of the ERASMUS program is considered in light of research that has been undertaken using the launch and growth of the program as opportunities to examine and understand the effects of study abroad participation. The entry discusses the role of student exchanges on subsequent international mobility choices, as well as on subsequent labor market outcomes. It concludes by addressing some key open questions in this area.

Berkson errors are commonplace in empirical microeconomics. In consumer demand this form of measurement error occurs when the price an individual pays is measured by the (weighted) average price paid by individuals in a specified group (e.g., a county), rather than the true transaction price. We show the importance of such measurement errors for the estimation of demand in a setting with nonsep-arable unobserved heterogeneity. We develop a consistent estimator using external information on the true distribution of prices. Examining the demand for gasoline in the U.S., we document substantial within-market price variability, and show that there are significant spatial differences in the magnitude of Berkson errors across regions of the U.S. Accounting for Berkson errors is found to be quantitatively important for estimating price effects and for welfare calculations. Imposing the Slutsky shape constraint greatly reduces the sensitivity to Berkson errors.

This paper presents a test for exogeneity of explanatory variables in a nonparametric instrumental variables (IV) model whose structural function is identified through a conditional quantile restriction. Quantile regression models are increasingly important in applied econometrics. As with mean-regression models, an erroneous assumption that the explanatory variables in a quantile regression model are exogenous can lead to highly misleading results. In addition, a test of exogeneity based on an incorrectly specified parametric model can produce misleading results. This paper presents a test of exogeneity that does not assume the structural function belongs to a known finite-dimensional parametric family and does not require estimation of this function. The latter property is important because nonparametric estimates of the structural function are unavoidably imprecise. The test presented here is consistent whenever the structural function differs from the conditional quantile function on a set of non-zero probability. The test has non-trivial power uniformly over a large class of structural functions that differ from the conditional quantile function by O(n−1/2)⁠. The results of Monte Carlo experiments and an empirical application illustrate the performance of the test.