Constant elasticity of substitution (CES) demand for monopolistically competitive firm-varieties is a standard tool for models in international trade and macroeconomics. Inter-variety substitution in this model follows a simple share proportionality rule. In contrast, the standard toolkit in industrial organization (IO) estimates a demand system in which cross-elasticities depend on similarity in observable attributes. The gain in realism from the IO approach comes at the expense of requiring richer data and greater computational challenges. This paper uses the data generating process of Berry, Levinsohn and Pakes (1995), BLP, who established the modern IO method, to simulate counterfactual trade policy experiments. We use the CES model as an approximation of the more complex underlying demand system and market structure. Although the CES model omits key elements of the data generating process, the errors are offsetting, allowing it to fit BLP-based predictions closely. For aggregate outcomes, it turns out that incorporating non-unitary pass-through matters more than fixing over-simplified substitution patterns.

Combining data on locations with career and educational histories of mathematicians, we study how distance and ties affect citation patterns. The ties considered include coauthorship, past colocation, and relationships mediated by advisers and the alma mater. With fixed effects capturing subject similarity and article quality, we find linkages are strongly associated with citation. Controlling for ties generally halves the negative impact of geographic barriers on citations. Ties matter more for less prominent and more recent papers and have retained their quantitative importance in recent years. The impact of distance, controlling for ties, has fallen and is statistically insignificant after 2004.

We model the decision to travel across an international border as a trade-off between benefits derived from buying a range of products at lower prices and the costs of travel. We estimate the model using microdata on Canada–United States travel. Price differences motivate cross-border travel; a 10% home appreciation raises the propensity to cross by 8% to 26%. The larger elasticity arises when the home currency is strong, a result predicted by the model. Distance to the border strongly inhibits crossings, with an implied cost of 87 cents per mile. Geographic differences can partially explain why American travel is less exchange rate responsive.

One of the best-established empirical results in international economics is that bilateral trade decreases with distance. Although well known, this result has not been systematically analyzed before. We examine 1,467 distance effects estimated in 103 papers. Information collected on each estimate allows us to test hypotheses about the causes of variation in the estimates. Our most interesting finding is that the estimated negative impact of distance on trade rose around the middle of the century and has remained persistently high since then. This result holds even after controlling for many important differences in samples and methods.

This paper develops a theoretical model of location choice under imperfect competition to formalize the notion that firms prefer to locate “where the markets are.” The profitability of a location depends on a term that weights demand in all locations by accessibility. Using a sample of Japanese firms' choices of regions within European countries, we compare the theoretically derived measure of market potential with the standard form used by geographers. Our results show that market potential matters for location choice but cannot account entirely for the tendency of firms in the same industry to agglomerate.