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A Search and Learning Model of Export Dynamics

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August 2021

Written by: C.J. Krizan, James Tybout, Jonathan Eaton, Marcela Eslava, David Jinkins

Working Paper Number:

CES-21-17

Abstract

Exporting abroad is much harder than selling at home, and overcoming hurdles to exporting takes time. Our goal is to identify specific barriers to exporting and to measure their importance. We develop a model of firm-level export dynamics that features costly customer search, network effects in finding buyers, and learning about product appeal. Fitting the model to customs records of U.S. imports of manufactures from Colombia we replicate patterns of exporter maturation. A potentially valuable intangible asset of a firm is its customer base and knowledge of a market. Our model delivers some striking estimates of what such assets are worth. Averaging across active exporters, the loss from total market amnesia (losing its current U.S. customer base along with its accumulated knowledge of product appeal) is US$ 3.4 million, about 34 percent of the value of exporting overall. About half is the loss of future sales to existing customers while the rest is the cost of relearning its appeal in the market and reestablishing visibility as an exporter. Given the importance of search, learning, and visibility, the 5-year response of total export sales to an exchange rate shock exceeds the 1-year response by about 40 percent.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords. :
market, macroeconomic, sale, import, export, shipment, exporting, exporter, importing, consumer, gdp, firms exporting, buyer, exported, trading, importer, custom, export market

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations. :
Bureau of Labor Statistics, National Science Foundation, Center for Economic Studies, County Business Patterns, Organization for Economic Cooperation and Development, Employer Identification Numbers, Longitudinal Firm Trade Transactions Database, Disclosure Review Board, Federal Statistical Research Data Center

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