Reputation and learning: Japanese car exports to the United States

This paper incorporates learning and reputation building into a simple dynamic stochastic model with asymmetric information. We use the model to study a bilateral trade flow influenced significantly by learning and reputation, namely U.S. imports of Japanese cars over the period 1961–2004. Numerical simulations replicate the trade flow in a robust fashion. Including the Voluntary Export Restraint in our simulations predicts U.S. imports decreased by 2.46 million cars over the years 1981–1984. Since learning and reputation building require time, predicted short run trade patterns can be quite different than those predicted in the long run. We apply this idea to understand the change in Japanese market share in the U.S. automobile market. We also explore the importance of sectorial differences in the speed of learning and reputation building on predicted trade patterns. Lastly, we examine how the extent of asymmetric information existing between importers and exporters changes under different trade policies.