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Why Do EPS Forecast Error and Dispersion Not Vary with Scale? Implications for Analyst and Managerial Behavior

Authors


  • We received helpful comments from an anonymous referee, Jeff Abarbanell, Mark Bagnoli, Ray Ball, Ryan Ball, Sudipta Basu, Larry Brown, Brian Burnett, Christian Leuz, Jim Ohlson, Cathy Schrand, Phil Shane, Rene Stulz, Frank Zhang, Marc Zimmerman, and seminar participants at AAA Annual meetings, Arizona, Colorado, FARS midyear meetings, 2009 FEA Conference, Georgetown, HKUST, the 2010 JAR Conference, London Business School, Miami, Purdue, Nanyang Business School, Rutgers, and Yale.

ABSTRACT

We document a counter-intuitive finding regarding analyst forecasts of quarterly earnings per share (EPS): magnitudes of deviations from benchmarks—individual forecasts versus consensus (dispersion) and consensus versus actual (forecast error)—do not vary with scale. Seasonally differenced EPS, or time-series forecast error, also exhibits substantial lack of variation with scale, but only for firms followed by analysts. This lack of variation with scale is not observed for analyst and time-series forecasts for (a) EPS for some countries, (b) sales and cash flows for all countries, and (c) stock splits. We propose and investigate different explanations for these puzzling regularities that have important implications for practice and research. We believe the cause is managerial smoothing of EPS designed to reduce across-firm variation in EPS volatility.

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