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Firms’ Relative Operational Efficiency and Analysts’ Earnings Forecasts

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  • Fatma Cebenoyan

    ()
    (Department of Economics, Hunter College)

  • Donal Byard

Abstract

Relatively more efficient firms tend to maintain more stable levels of output and operating performance compared to their industry peers (Mills and Schumann 1985). Such firms also tend to have more sustainable performance (Berger et al. 1993). Given their more stable and sustainable levels of operating performance, we test the related prediction that financial analysts find the earnings of relatively more efficient firms to be more predictable. Using a stochastic frontier approach to measure firms’ relative operational efficiency, we find that analysts face less earnings uncertainty for relatively more efficient firms, compared to other firms in the same industry. We find that this broader more encompassing measure of firms’ relative operational efficiency yields stronger results than comparable accounting ratios (ROA and ROE). These results indicate that analysts behave as if they factor into their forecasts an understanding of the underlying economics of a business of an industry. Furthermore, the users of these forecasts can also benefit from this information in terms of assessing the level of reliability of forecasts.

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Bibliographic Info

Paper provided by Hunter College Department of Economics in its series Economics Working Paper Archive at Hunter College with number 302.

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Date of creation: 2003
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Handle: RePEc:htr:hcecon:302

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Keywords: Relative Operational Efficiency; Return on Assets; Return on Equity; Analysts’ Earnings Forecasts; Earnings Uncertainty.;

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  1. Joseph P. Hughes & William W. Lang & Loretta J. Mester & Choon-Geol Moon & Michael S. Pagano, 2002. "Do Bankers Sacrifice Value to Build Empires? Managerial Incentives, Industry Consolidation and Financial Performance," Center for Financial Institutions Working Papers 02-18, Wharton School Center for Financial Institutions, University of Pennsylvania.
  2. Jacobson, Robert, 1987. "The Validity of ROI as a Measure of Business Performance," American Economic Review, American Economic Association, vol. 77(3), pages 470-78, June.
  3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  4. DeYoung, Robert, 1997. "A diagnostic test for the distribution-free efficiency estimator: An example using U.S. commercial bank data," European Journal of Operational Research, Elsevier, vol. 98(2), pages 243-249, April.
  5. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-93, May.
  6. Kwan, Simon H. & Eisenbeis, Robert A., 1995. "An analysis of inefficiencies in banking," Journal of Banking & Finance, Elsevier, vol. 19(3-4), pages 733-734, June.
  7. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
  8. Allen N. Berger & Loretta J. Mester, 1997. "Inside the black box: what explains differences in the efficiencies of financial institutions?," Finance and Economics Discussion Series 1997-10, Board of Governors of the Federal Reserve System (U.S.).
  9. Mills, David E & Schumann, Laurence, 1985. "Industry Structure with Fluctuating Demand," American Economic Review, American Economic Association, vol. 75(4), pages 758-67, September.
  10. Dechow, Patricia M., 1994. "Accounting earnings and cash flows as measures of firm performance : The role of accounting accruals," Journal of Accounting and Economics, Elsevier, vol. 18(1), pages 3-42, July.
  11. Allen, Linda & Rai, Anoop, 1996. "Operational efficiency in banking: An international comparison," Journal of Banking & Finance, Elsevier, vol. 20(4), pages 655-672, May.
  12. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
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