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Review of Financial Studies Vol. 34 No. 4 2021

Evaluating Firm-Level Expected-Return Proxies: Implications for Estimating Treatment Effects

Charles M. C. Lee1; Eric C. So2; Charles C. Y. Wang3

1 Graduate School of Business, Stanford University · 2 Sloan School of Management, Massachusetts Institute of Technology. · 3 Harvard Business School, Harvard University

open access

Abstract

We introduce a parsimonious framework for choosing among alternative expected-return proxies (ERPs) when estimating treatment effects. By comparing ERPs’ measurement error variances in the cross-section and in the time series, we provide new evidence on the relative performance of firm-level ERPs nominated by recent studies. Generally, “implied-costs-of-capital” metrics perform best in the time series, whereas “characteristic-based” proxies perform best in the cross-section. Factor-based ERPs, even the latest renditions, perform poorly. We revisit four prior studies that use ex ante ERPs and illustrate how this framework can potentially alter either the sign or the magnitude of prior inferences.

DOI
10.1093/rfs/hhaa066
Volume
34
Issue
4
Pages
1907-1951
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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