Causality in Empirical Analyses With Emphasis on Asymmetric Information and Risk Management

70 Pages Posted: 14 Nov 2023

See all articles by Georges Dionne

Georges Dionne

HEC Montreal - Department of Finance

Date Written: October 31, 2023

Abstract

We discuss the difficult question of measuring causality effects in empirical analyses, with applications to asymmetric information and risk management. It is now well documented in the economic literature that policy analysis must be causal. Hence, the measurement of its effects must also be causal. After having presented the main frameworks for causality analysis, including instrumental variable, difference-in-differences, and generalized method of moments, we analyze the following questions: Does risk management affect firm value and risk? Do we face a moral hazard problem in the insurance data? How can we separate moral hazard from adverse selection and asymmetric learning? Is liquidity creation a causal factor for reinsurance demand? We show that residual information problems are often present in different markets, while risk management may increase firm value when appropriate methodologies are applied.

Keywords: Asymmetric information, moral hazard, adverse selection, risk learning, risk management, causality test, dynamic data, essential heterogeneity, difference-in-differences, instrumental variable, propensity scor, generalized method of moments

JEL Classification: C12, C18, C23, C25, C26, D80, G11, G22

Suggested Citation

Dionne, Georges, Causality in Empirical Analyses With Emphasis on Asymmetric Information and Risk Management (October 31, 2023). Available at SSRN: https://ssrn.com/abstract=4619113 or http://dx.doi.org/10.2139/ssrn.4619113

Georges Dionne (Contact Author)

HEC Montreal - Department of Finance ( email )

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Montreal, Quebec H3T 2A7
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514-340-6596 (Phone)
514-340-5019 (Fax)

HOME PAGE: http://www.hec.ca/gestiondesrisques/

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