A Critique of Recent Quantitative and Deep-Structure Modeling in Capital Structure Research and Beyond
University of California, Los Angeles (UCLA); National Bureau of Economic Research (NBER)
September 5, 2012
AFA 2011 Denver Meetings Paper
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.
Number of Pages in PDF File: 44
Keywords: Quantitative Structural Modeling
JEL Classification: G32
Date posted: March 4, 2010 ; Last revised: September 18, 2013
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