A Critique of Recent Quantitative and Deep-Structure Modeling in Capital Structure Research and Beyond

44 Pages Posted: 4 Mar 2010 Last revised: 18 Sep 2013

Ivo Welch

University of California, Los Angeles (UCLA); National Bureau of Economic Research (NBER)

Date Written: September 5, 2012

Abstract

My paper highlights shortcomings of recent quantitative and deep-structure models in corporate finance: (1) These models have omitted too many plausible forces not based on evidence, but based on authors' priors. (2) The link between their unobserved structures and their reduced-form empirical evidence has been too weak. (Even orthogonal forces could have affected their inference.) (3) The existing tests have largely ignored many important econometric issues, such as selection and survivorship biases. (4) The models have never been held to reasonable test standards, such as performance in quasi-experimental settings. Constructively, my paper offers two suggestions: The first is to search for more direct empirical proxies instead of relying on "assumed" first-order conditions. The second is to design quasi-experimental tests of structural models. My paper illustrates these points in the context of Hennessy and Whited (2005) and Strebulaev (2007).

*Earlier version presented at the AFA 2011. Please cite future published paper instead.

Keywords: Quantitative Structural Modeling

JEL Classification: G32

Suggested Citation

Welch, Ivo, A Critique of Recent Quantitative and Deep-Structure Modeling in Capital Structure Research and Beyond (September 5, 2012). AFA 2011 Denver Meetings Paper. Available at SSRN: https://ssrn.com/abstract=1563465 or http://dx.doi.org/10.2139/ssrn.1563465

Ivo Welch (Contact Author)

University of California, Los Angeles (UCLA) ( email )

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HOME PAGE: http://www.ivo-welch.info

National Bureau of Economic Research (NBER)

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