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 ECARES ULB CP 114
B-1050 Brussels
Belgium

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