Data and Code for: An Empirical Dynamic Model of Trade with Consumer Accumulation

This paper develops a dynamic structural model of trade in which firms slowly accumulate consumers in foreign markets. Estimating the model using export data from individual firms and a particle Markov chain Monte Carlo estimator, the model predicts lower survival rates for new exporters and estimates low entry costs of exporting - less than half of those estimated in the absence of consumer accumulation. Using simulations and out-of-sample predictions, I show that the introduction of such frictions and the reduction in estimated entry costs allow the model to match important facts regarding the aggregate response of international trade to shocks.

本研究构建了一种关于贸易的动态结构模型，其中企业逐步在外国市场上积累消费者。通过使用单个企业的出口数据和粒子马尔可夫链蒙特卡洛估计器来估计该模型，该模型预测新出口商的存活率较低，并估计出口的低门槛成本——低于在没有消费者积累情况下的估计值一半。通过模拟和样本外预测，我展示了引入此类摩擦和降低估计的进入成本，使得模型能够匹配关于国际贸易对冲击的总体响应的重要事实。