International Trade Finance and Learning Dynamics

David Kohn, Emiliano Luttini, Michal Szkup and Shengxing Zhang
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Michal Szkup: University of British Columbia
Shengxing Zhang: Carnegie Mellon University

No 346, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)

Abstract: We study how trade finance and long-term relationships between exporters and importers facilitate international trade by allowing exporters to learn about demand uncertainty and counterparty risk. Using detailed micro-level Chilean data, we document that new exporters are more likely to use cash-in-advance (CIA) arrangements andgradually switch to providing trade credit as they continue to export. These dynamics affect export growth and are more salient for firms with less exporting experience andselling to riskier destinations. We set up an international trade model in which firms make exporting and trade financing decisions subject to demand and counterparty risksand estimate it using microdata. We then use the model to quantify the relative importance of demand and counterparty risks and investigate how trade finance choicesand learning affect the dynamics of exports. Our model implies that the response of aggregate exports and the number of exporters to shocks to aggregate interest rates canovershoot in the short run if long-term relationships and relationship-specific knowledge are destroyed. Building relationships takes time, making the response to theseshocks sluggish and persistent. Crucially, these responses depend on the riskiness of trade destinations.

Keywords: export dynamics; trade finance; learning; demand risk; counterparty risk (search for similar items in EconPapers)
Pages: 52 pages
Date: 2024-12
New Economics Papers: this item is included in nep-fdg and nep-int
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Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:346

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