Nonparametric Identification and Estimation of Productivity Distributions and Trade Costs

This paper studies the nonparametric identification and estimation of productivity distributions and trade costs in an Eaton and Kortum (2002) type model. Our identification and estimation strategy gains insights from the empirical auction literature, however, our methodology is novel since we face additional problems resulting from the nature of the trade data. Our methodology does not require data on prices which are usually quite hard to obtain and manages to identify the underlying structure by using disaggregated simple bilateral trade data consisting only of trade values and traded quantities. We recover destination-source-sector specific productivity distributions and trade costs nonparametrically. The fact that these productivity distributions and trade costs are both country and sector specific provides important insights about not only cross country differences but also differences across sectors. Moreover, it has now become a common tradition in models of international trade to use either Fréchet or Pareto distributions to represent the distribution of productivities. They provide great analytical convenience; however, recent studies show gains from trade estimates are very sensitive to these parametrizations. To quantify the welfare gains from trade and answer related policy questions, checking the validity of these parametrizations and analyzing how productivity distributions behave is very important.