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Learning to export from neighbors

Ana Fernandes and Heiwai Tang

No 185, Globalization Institute Working Papers from Federal Reserve Bank of Dallas

Abstract: 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 from 2000 to 2006. Our findings are robust to controlling for firms? supply shocks, countries? demand shocks, and city-country fixed effects.

JEL-codes: F1 F2 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2014-06-01
New Economics Papers: this item is included in nep-bec, nep-int and nep-tra
Note: Published as: Fernandes, Ana and Heiwai Tang (2014), "Learning to Export from Neighbors," Journal of International Economics 94 (1): 67-84.
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Citations: View citations in EconPapers (47) Track citations by RSS feed

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Working Paper: Learning to Export from Neighbors (2014) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:fip:feddgw:185

DOI: 10.24149/gwp185

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