This paper develops a methodology for predicting the impact of trade liberalization on exports by industry (3-digit ISIC) based on the pre-liberalization distribution of exports by product (5-digit SITC). Using the results of Kehoe and Ruhl (2013) that much of the growth in trade after trade liberalization is in products that are traded very little or not at all, we predict that industries with a higher share of exports generated by least traded products will experience more growth. Using our methodology, we develop predictions for industry-level changes in trade for the United States and Korea following the U.S.-Korea Free Trade Agreement (KORUS). As a test for our methodology, we show that it performs significantly better than the applied general equilibrium models originally used for the policy evaluation of the North American Free Trade Agreement (NAFTA).

Applied general equilibrium (AGE) models, which feature multiple countries, multiple industries, and input-output linkages across industries, have been the dominant tool for evaluating the impact of trade reforms since the 1980s. We review how these models are used to perform policy analysis and document their shortcomings in predicting the industry-level effects of past trade reforms.We argue that, to improve their performance, AGE models need to incorporate product-level data on bilateral trade relations by industry and better model how trade reforms lower bilateral trade costs. We use the least traded products methodology of Kehoe et al. (2015) to provide guidance on how improvements can be made. We provide further suggestions on how AGE models can incorporate recent advances in quantitative trade theory to improve their predictive ability and better quantify the gains from trade liberalization.

Applied general equilibrium (AGE) models, which feature multiple countries, multiple industries, and input–output linkages across industries, have been the dominant tool for evaluating the impact of trade reforms since the 1980s. We review how these models are used to perform policy analysis and document their shortcomings in predicting the industry-level effects of past trade reforms. We argue that, to improve their performance, AGE models need to incorporate product-level data on bilateral trade relations by industry and better model how trade reforms lower bilateral trade costs. We use the least-traded-products methodology of Kehoe et al. (2015) to provide guidance on how improvements can be made. We provide further suggestions on how AGE models can incorporate recent advances in quantitative trade theory to improve their predictive ability and better quantify the gains from trade liberalization.

a b s t r a c tThis paper develops a methodology for predicting the impact of trade liberalization on exports by industry (3-digit ISIC) based on the pre-liberalization distribution of exports by product (5-digit SITC). We evaluate the ability of our methodology to account for the industry-level variation in export growth by using our model to "predict" the growth in industry trade from the North American Free Trade Agreement (NAFTA). We show that our method performs significantly better than the applied general equilibrium models originally used for the policy evaluation of NAFTA. We find that the most important products in our analysis are not the ones with zero pre-liberalization trade, but those with positive, yet small amounts of pre-liberalization trade.