, and the World Bank for very helpful comments. We also thank Jenny Nuñez, Luis Cerpa, the Chilean Customs Authority, and the Instituto Nacional de Estadísticas for assistance with building the dataset. All errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. Andres Zahler acknowledges the Nucleo Milenio Initiative NS100017 "Intelis Centre" for partial funding. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
Exporting firms often enter foreign markets that are similar to their previous export destinations. We develop a dynamic model in which a firm’s exports in a market may depend on how similar the market is to the firm’s home country (gravity) and to its previous export destinations (extended gravity). Given the large number of export paths from which forward-looking firms may choose, we use a moment inequality approach to estimate our model. Our estimates indicate that sharing similarities with a prior export destination in terms of geographic location, language, and income per capita jointly reduces the cost of foreign market entry by 69–90%. Reductions due to geographic location (25–38%) and language (29–36%) have the largest effect. Extended gravity thus has a large impact on export entry costs.
We use Monte Carlo experiments to evaluate whether "upward pricing pressure" (UPP) accurately predicts the price effects of mergers, motivated by the observation that UPP is a restricted form of the first order approximation derived in Jaffe and Weyl (2013). Results indicate that UPP is quite accurate with standard log-concave demand systems, but understates price effects if demand exhibits greater convexity. Prediction error does not systematically exceed that of misspecified simulation models, nor is it much greater than that of correctly-specified models simulated with imprecise demand elasticities. The results also support that both UPP and the HHI change provide accurate screens for anticompetitive mergers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.