We propose a simple method to identify the effects of unilateral and non-discriminatory trade policies on bilateral trade within a theoretically-consistent empirical gravity model. Specifically, we argue that structural gravity estimations should be performed with data that include not only...

We propose and apply methods to quantify the impact of national institutions on international trade and development. We are able to identify the direct impact of country-specific institutions on international trade within the structural gravity framework. Our approach naturally addresses the...

This paper argues that skill formation is a life-cycle process and develops the implications of this insight for Scottish social policy. Families are major producers of skills, and a successful policy needs to promote effective families and to supplement failing ones. Targeted early...

This paper analyses the effect of international borders and of trade agreements at international borders on subnational (i.e. regional) growth. We construct an extensive panel dataset covering 1,350 regions in 86 countries worldwide between 1950 and 2017. Our results show that international...

Starting with Tinbergen (1962), quantifying the effects of regional trade agreements (RTAs) on international trade flows has always been among the most popular topics in the trade literature. Also not surprisingly, to estimate the effects of RTAs, most researchers and policy analysts have relied...

Making use of restrictions imposed by equilibrium, theoretical progress has been made on the nonparametric and semiparametric estimation and identification of scalar additive hedonic models (Ekeland, Heckman, and Nesheim, 2002) and scalar nonadditive hedonic models (Heckman, Matzkin, and...

This paper considers the identification and estimation of hedonic models. We establish that in an additive version of the hedonic model, technology and preferences are generically identified up to affine transformations from data on demand and supply in a single hedonic market. For a very...