Learning to export from neighbors
Fernandes, Ana P.
Journal of International Economics
© 2014 Elsevier B.V. All rights reserved.
Reason for embargo
Embargo of 18 months due to publisher policy.
This paper studies how learning from neighboring firms affects new exporters' performance. We develop a statistical decision model in which a firm updates its prior belief about demand in a foreign market based on several factors, including the number of neighbors currently selling there, the level and heterogeneity of their export sales, and the firm's own prior knowledge about the market. A positive signal about demand inferred from neighbors' export performance raises the firm's probability of entry and initial sales in the market but, conditional on survival, lowers its post-entry growth. These learning effects are stronger when there are more neighbors to learn from or when the firm is less familiar with the market. We find supporting evidence for the main predictions of the model from transaction-level data for all Chinese exporters over the 2000-2006 period. Our findings are robust to controlling for firms' supply shocks, countries' demand shocks, and city-country fixed effects.
“NOTICE: this is the author’s version of a work that was accepted for publication in the Journal of International Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of International Economics, [Vol. 94, Issue 1, (September 2014)] DOI: 10.1016/j.jinteco.2014.06.003 ¨
Vol. 94, Issue 1, pp. 67-84