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Firm characteristics of two-way traders: Evidence from Probit vs. Kernel-Regularized Least Squares regressions

Author

Listed:
  • Joachim Wagner

    (Leuphana Universität Lüneburg, Institut für Volkswirtschaftslehre)

Abstract

Firm characteristics in empirical models for margins of international trade usually enter these models in linear form. If non-linearities do matter and are ignored this leads to biased results. Researchers, however, can never be sure that all possible non-linear relationships are taken care of. A solution is provided by Kernel Regularized Least Squares (KRLS) that uses a machine learning approach to learn the functional form from the data. While in earlier applications the big picture revealed by standard empirical models and KRLS was identical this note presents a case where results from a standard approach and KRLS do differ considerably.

Suggested Citation

  • Joachim Wagner, 2025. "Firm characteristics of two-way traders: Evidence from Probit vs. Kernel-Regularized Least Squares regressions," Working Paper Series in Economics 433, University of Lüneburg, Institute of Economics.
    • Handle: RePEc:lue:wpaper:433
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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