• Medientyp: E-Book
  • Titel: On Inference When Using State Corporate Laws for Identification
  • Beteiligte: Spamann, Holger [Verfasser:in]
  • Erschienen: [S.l.]: SSRN, [2020]
  • Erschienen in: Harvard Law School John M. Olin Center Discussion Paper ; No. 1024 (2019)
  • Umfang: 1 Online-Ressource (33 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.3499101
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 6, 2019 erstellt
  • Beschreibung: 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
  • Zugangsstatus: Freier Zugang