Bayesian learning in an infant industry model

• 成果类型: Article
• 署名作者: Hoff, K
• 刊物名称: JOURNAL OF INTERNATIONAL ECONOMICS
• ISSN/ISSBN: 0022-1996
• DOI: 10.1016/S0022-1996(97)00007-X
• 发表日期: 1997
• 页码: 409-436
• 关键词: Bayesian learning; information externality; infant industry; Industrial policy

摘要

Most analyses of the infant industry argument assume that production early on benefits subsequent production in deterministic fashion. This paper presents an alternative framework for evaluating the infant industry argument that focuses on imperfect information as a barrier to entry. Initial entrants provide information of social value by reducing uncertainty for potential followers about the suitability of local conditions. In contrast to earlier work, I show that factors that increase the informational barrier to entry may lower the optimal subsidy to the infant industry, and that the standard test of the success of infant industry policy is not always valid. (C) 1997 Elsevier Science B.V.