• Medientyp: E-Book
  • Titel: How Fama-MacBeth Can Go Wrong – And an Informative Solution
  • Beteiligte: Khalaf, Lynda [Verfasser:in]; Schaller, Huntley [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2011]
  • Umfang: 1 Online-Ressource (56 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.1785858
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 14, 2011 erstellt
  • Beschreibung: We find that weak identification can lead to econometric problems with Fama-MacBeth regressions, including serious size distortions and biased point estimates. Two sources of weak identification are particularly important and have been little studied in the finance literature – small betas and collinearity in the beta matrix. We introduce a technique (RTP) to deal with weak identification and compare the new technique with Fama-MacBeth and other alternatives. RTP has correct size and very good power to reject misspecified models. RTP has two further useful properties: 1) it provides a warning of weak identification; 2) model rejections can be informative
  • Zugangsstatus: Freier Zugang