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Review of Accounting Studies

, Volume 23, Issue 3, pp 1071–1095 | Cite as

Decomposing the market, industry, and firm components of profitability: implications for forecasts of profitability

  • Andrew B. Jackson
  • Marlene A. Plumlee
  • Brian R. Rountree
Article

Abstract

Academics and practitioners frequently highlight that overall market and industry performance is an important aspect of a firm’s profitability. However, few studies allow for the decomposition of a firm’s profitability into market, industry, and idiosyncratic components, and those that do often assume that the market and industry components are cross-sectional constants. In this study, we allow for variation in firm-specific sensitivities to market, industry, and idiosyncratic economic shocks, and then assess whether and when this decomposition results in improved forecasts of profitability. For the overall sample, we find significant improvements in terms of the magnitude of forecast errors and the frequency with which forecasts based on the decomposed values are superior versus forecasts using only total profitability. Across the sample as a whole, decomposing profitability in the forecasting process results in more accurate forecasts greater than two-thirds of the time (increasing to almost 80% within certain subsamples). Our results provide strong support for the role that firm-specific measures of market and industry profitability play in predicting a firm’s future performance, as well as highlighting settings where the decomposition provides the greatest benefit in terms of predicting future changes in profitability.

Keywords

Macroeconomy Market Industry Profitability Forecasting Firm-specific estimates 

JEL classification

M41 

Notes

Acknowledgements

We appreciate comments from two anonymous reviewers, Steve Penman (editor), Philip Brown, Peter Clarkson, Ilia Dichev, Doug Foster, Steve Hillegeist, Stijn Masschelein, Jim Ohlson, Cathy Shakespeare, Cameron Truong, Marvin Wee, and seminar participants at the 2016 AAA Annual Meeting, 2016 AFAANZ Annual Conference, 2017 MEAFA Research Meeting, Monash University, UNSW Sydney, University of Otago, University of Technology Sydney, and University of Western Australia. All errors remain our own responsibility.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Accounting, UNSW Business SchoolUNSW SydneySydneyAustralia
  2. 2.University of UtahSalt Lake CityUSA
  3. 3.Rice UniversityHoustonUSA

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