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A conditional independence test for causality in econometrics

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  • Jaime Sevilla
  • Alexandra Mayn

Abstract

The Y-test is a useful tool for detecting missing confounders in the context of a multivariate regression.However, it is rarely used in practice since it requires identifying multiple conditionally independent instruments, which is often impossible. We propose a heuristic test which relaxes the independence requirement. We then show how to apply this heuristic test on a price-demand and a firm loan-productivity problem. We conclude that the test is informative when the variables are linearly related with Gaussian additive noise, but it can be misleading in other contexts. Still, we believe that the test can be a useful concept for falsifying a proposed control set.

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  • Jaime Sevilla & Alexandra Mayn, 2021. "A conditional independence test for causality in econometrics," Papers 2107.09765, arXiv.org.
    • Handle: RePEc:arx:papers:2107.09765
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    References listed on IDEAS

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    1. Abhijit V. Banerjee & Esther Duflo, 2014. "Do Firms Want to Borrow More? Testing Credit Constraints Using a Directed Lending Program," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(2), pages 572-607.
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    Cited by:

    1. Martin Huber & Jannis Kueck, 2022. "Testing the identification of causal effects in observational data," Papers 2203.15890, arXiv.org, revised Jun 2023.

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