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Learning by exporting with a dose-response function

2025-05-06 · Francesca Micocci, Armando Rungi, Giovanni Cerulli

This paper investigates the causal effect of export intensity on productivity and other firm-level outcomes with a dose-response function. After positing that export intensity acts as a continuous treatment, we investigate counterfactual productivity levels in a quasi-experimental setting. For our purpose, we exploit a control group of non-temporary exporters that have already sustained the fixed costs of reaching foreign markets, thus controlling for self-selection into exporting. Our findings reveal a non-linear relationship between export intensity and productivity, with small albeit statistically significant benefits ranging from 0.1% to 0.6% per year only after exports reach 60% of total revenues. After we look at sales, variable costs, capital intensity, and the propensity to filing patents, we show that, before the 60% threshold, economies of scale and capital adjustment offset each other and induce, on average, a minimal albeit statistically significant loss in productivity of about 0.01% per year. Crucially, we find that heterogeneous export intensity is associated with the firm's position on the technological frontier, as the propensity to file a patent increases when export intensity ranges in 8%-60% with a peak at 40%. The latest finding further highlights that learning-by-exporting is linked to the building of absorptive capacity.

📄 PDF Abstract BibTeX arXiv:2505.03328

Code (1)

francescam94/Predicting-Exporters-with-ML

Tasks

counterfactual

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