On Inference When Using State Corporate Laws for Identification

Harvard Law School John M. Olin Center Discussion Paper No. 1024 (2019)

European Corporate Governance Institute – Finance Working Paper No. 644/2019

33 Pages Posted: 17 Dec 2019 Last revised: 2 Jan 2020

Date Written: December 6, 2019

Abstract

A popular research design identifies the effects of corporate governance by (changes in) state laws, clustering standard errors by state of incorporation. Using Monte-Carlo simulations, this paper shows that conventional statistical tests based on these standard errors dramatically overreject: in a typical design, randomly generated “placebo laws” are “significant” at the 1/5/10% level 9/21/30% of the time. This poor coverage is due to the extremely unequal cluster sizes, especially Delaware's concentration of half of all incorporations. Fixes recommended in the literature fail, including degrees-of-freedom corrections and the cluster wild bootstrap. The paper proposes a permutation test for valid inference.

Keywords: Anti-Takeover Laws, Corporate Governance, Cluster-Robust Inference, Monte Carlo, Placebo Laws, Permutation Test

JEL Classification: C12, G34, G38, K22

Suggested Citation

Spamann, Holger, On Inference When Using State Corporate Laws for Identification (December 6, 2019). Harvard Law School John M. Olin Center Discussion Paper No. 1024 (2019), European Corporate Governance Institute – Finance Working Paper No. 644/2019, Available at SSRN: https://ssrn.com/abstract=3499101 or http://dx.doi.org/10.2139/ssrn.3499101

Holger Spamann (Contact Author)

Harvard Law School ( email )

Cambridge, MA 02138
United States

ECGI ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels
Belgium

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