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Business Research

, Volume 1, Issue 1, pp 26–53 | Cite as

Analysts’ Forecast Accuracy in Germany: The Effect of Different Accounting Principles and Changes of Accounting Principles

  • Jürgen ErnstbergerEmail author
  • Simon Krotter
  • Christian Stadler
Open Access
Article

Abstract

This paper assesses the influence of an adoption of IAS/IFRS or US GAAP on the financial analysts’ forecast accuracy in a homogenous institutional framework. Our findings suggest that the forecast accuracy is higher for estimates based on IFRS or US GAAP data than for forecasts based on German GAAP data. Moreover, in the year of switching from German GAAP to US GAAP the forecast accuracy is lower than in other years. The paper contributes to prior research by providing evidence about the usefulness of international accounting data and about the adoption effects of a change to such accounting principles.

Keywords

accounting adoption effect analysts analysts’ forecast accuracy financial analysts German GAAP Germany HGB IAS IFRS IFRS adoption learning effect US GAAP 

References

  1. Abarbanell, Jeffery and Reuven Lehavy (2003): Biased Forecasts or Biased Earnings? The Role of Reported Earnings in Explaining Apparent Bias and Over-/Underreaction in Analysts’ Earnings Forecasts, Journal of Accounting and Economics, 36(1–3): 105–146.Google Scholar
  2. Acker, Daniella, Jo Horton, and Ian Tonks (2002): Accounting Standards and Analysts’ Forecasts: The Impact of FRS3 on Analysts’ Ability to Forecast EPS, Journal of Accounting & Public Policy, 21(3): 193–217.Google Scholar
  3. Alford, Andrew W. and Philip G. Berger (1999): A Simultaneous Equations Analysis of Forecast Accuracy, Analyst Following, and Trading Volume, Journal of Accounting, Auditing & Finance, 14(3): 219–240.Google Scholar
  4. Ang, James S. and Stephen J. Ciccone (2001): International Differences in Analyst Forecast Properties, Working paper, Florida State University and University of New Hampshire.Google Scholar
  5. Ashbaugh, Hollis and Morton Pincus (2001): Domestic Accounting Standards, International Accounting Standards, and the Predictability of Earnings, Journal of Accounting Research, 39(3): 417–434.Google Scholar
  6. Ashbaugh-Skaife, Hollis and Joachim Gassen (2006): Can Audit Reforms Change the Monitoring Role of Audits? Evidence from the German Audit Market, Working paper, University of Wisconsin and University of Berlin.Google Scholar
  7. Auer, Kurt V. (1996): Capital Market Reactions to Earnings Announcements: Empirical Evidence on the Difference in the Information Content of IAS-based Earnings and EC-Directives-based Earnings, The European Accounting Review, 5(4): 587–623.Google Scholar
  8. Baldwin, Bruce A. (1984): Segment Earnings Disclosure and the Ability of Security Analysts to Forecast Earnings per Share, The Accounting Review, 59(3): 376–389.Google Scholar
  9. Bamber, Linda S. and Younsoon S. Cheon (1998): Discretionary Management Earnings Forecast Disclosures: Antecedents and Outcomes Associated with Forecast Venue and Forecast Specificity Choices, Journal of Accounting Research, 36(2): 167–190.Google Scholar
  10. Bannister, James W. and Harry A. Newman (1996): Accrual Usage to Manage Earnings toward Financial Analysts’ Forecasts, Review of Quantitative Finance and Accounting, 7(3): 259–278.Google Scholar
  11. Barniv, Ran, Mark J. Myring, and Wayne B. Thomas (2005): The Association between the Legal and Financial Reporting Environments and Forecast Performance of Individual Analysts, Contemporary Accounting Research, 22(4): 727–758.Google Scholar
  12. Barra (2005): United States equity risk model handbook, Berkeley.Google Scholar
  13. Barra (2006): German equity risk model handbook, Berkeley.Google Scholar
  14. Barron, Orie E., Charles O. Kile, and Terrence B. O’Keefe (1999): MD&A Quality as Measured by the SEC and Analysts’ Earnings Forecasts, Contemporary Accounting Research, 16(1): 75–109.Google Scholar
  15. Barron, Orie E., Oliver Kim, Steve C. Lim, and Douglas E. Stevens (1998): Using Analysts’ Forecasts to Measure Properties of Analysts’ Information Environment, The Accounting Review, 73(4): 421–433.Google Scholar
  16. Barth, Mary E., Wayne R. Landsman, and Mark Lang (2008): International Accounting Standards and Accounting Quality, Working paper, Stanford University, Journal of Accounting Research, 46(3): 467–498.Google Scholar
  17. Bartov, Eli and Gordon M. Bodnar (1996): Alternative Accounting Methods, Information Asymmetry and Liquidity: Theory and Evidence, The Accounting Review, 71(3): 397–418.Google Scholar
  18. Bartov, Eli, Dan Givoly, and Carla Hayn (2002): The Rewards to Meeting or Beating Earnings Expectations, Journal of Accounting and Economics, 33(2): 173–204.Google Scholar
  19. Bartov, Eli, Stephen R. Goldberg, and Myungsun Kim (2005): Comparative Value Relevance among German, U.S., and International Accounting Standards: A German Stock Market Perspective, Journal of Accounting, Auditing & Finance, 20(2): 95–119.Google Scholar
  20. Basu, Sudipta, LeeSeok Hwang, and Ching-Lih Jan (1998): International Variation in Accounting Measurement Rules and Analysts’ Earnings Forecast Errors, Journal of Business Finance & Accounting, 25(9/10): 1207–1247.Google Scholar
  21. Bartov, Eli, Dan Givoly, and Carla Hayn (2002): The Rewards of Meeting or Beating Earnings Expectations, Journal of Accounting and Economics, 33(2): 173–204.Google Scholar
  22. Bartov, Eli, Stephen R. Goldberg, and Myungsun Kim (2005): Comparative Value Relevance among German, U.S., and International Accounting Standards: A German Stock Market Perspective, Journal of Accounting, Auditing & Finance, 20(2): 95–119.Google Scholar
  23. Basu, Sudipta, LeeSeok Hwang, and Ching-Lih Jan (1998): International Variation in Accounting Measurement Rules and Analysts’ Earnings Forecast Errors, Journal of Business Finance & Accounting, 25(9/10): 1207–1247.Google Scholar
  24. Beckman, Judy, Christina Brandes, and Brigitte Eierle (2007): German Reporting Practices: An Analysis of Reconciliations from German Commercial Code to IFRS or US GAAP, Advances in International Accounting, 20: 253–294.Google Scholar
  25. Behn, Bruce K., Nancy B. Nichols, and Donna L. Street (2002): The Predictive Ability of Geographic Segment Disclosures by U.S. Companies: SFAS No. 131 vs. SFAS No. 14, Journal of International Accounting Research, 1(1): 31–44.Google Scholar
  26. Bessler, Wolfgang and Matthias Stanzel (2007): Qualität und Effizienz der Gewinnprognosen von Analysten — Eine em-pirische Untersuchung für den deutschen Kapitalmarkt, Kredit und Kapital, 40(1): 89–129.Google Scholar
  27. Brown, Lawrence D. (1983): Accounting Changes and the Accuracy of Analysts` Earnings Forecasts, Journal of Accounting Research, 21(2): 432–443.Google Scholar
  28. Brown, Lawrence D., Gordon D. Richardson, and Steven J. Schwager (1987): An Information Interpretation of Financial Analyst Superiority, Journal of Accounting Research, 25(1): 49–67.Google Scholar
  29. Burgstahler, David and Michael Eames (2006): Management of Earnings and Analysts’ Forecasts to Achieve Zero and Small Positive Earnings Surprises, Journal of Business Finance and Accounting, 33(5–6): 633–652.Google Scholar
  30. Cairns, David (2006): The Use of Fair Value in IFRS, Accounting in Europe, 3(1): 5–22.Google Scholar
  31. Capstaff, John, Krishna Paudyal, and William Rees (1998): Analysts’ Forecasts of German Firms’ Earnings: A Comparative Analysis, Journal of International Financial Management & Accounting, 9(2): 83–116.Google Scholar
  32. Chang, James J., Tarun Khanna, and Krishna Palepu (2000): Analyst Activity around the World, Working paper, University of Pennsylvania and Harvard Business School.Google Scholar
  33. Clement, Michael B. (1999): Analyst Forecast Accuracy: Do Ability, Resources and Portfolio Complexity Matter?, Journal of Accounting & Economics, 27(3): 285–303.Google Scholar
  34. Clement, Michael B., Lynn Rees, and Edward B. Swanson (2003): The Influence of Culture and Corporate Governance on the Characteristics that Distinguish Superior Analysts, Journal of Accounting, Auditing, and Finance, 18(4): 593–618.Google Scholar
  35. Cuijpers, Rick and Willem Buijink (2005): Voluntary Adoption of Non-local GAAP in the European Union: A Study of Determinants and Consequences, European Accounting Review, 14 (3): 487–524.Google Scholar
  36. Das, Somnath (1998): Financial Analysts’ Earnings Forecasts for Loss Firms, Managerial Finance, 24(6): 39–50.Google Scholar
  37. Das, Somnath and Shahrokh M. Saudagaran (1998): Accuracy, Bias, and Dispersion in Analysts’ Earnings Forecasts: the Case of Cross-listed Foreign Firms, Journal of International Financial Management and Accounting, 9(1): 16–33.Google Scholar
  38. Das, Somnath, Carolyn B. Levine, and Kartik K. Sivaramakrishnan (1998): Earnings Predictability and Bias in Analysts’ Earnings Forecasts, The Accounting Review, 73(2): 277–294.Google Scholar
  39. Daske, Holger (2005): Adopting International Financial Reporting standards in the European Union: Empirical Essays on Causes, Effects and Economic Consequences, Frankfurt/Main.Google Scholar
  40. Daske, Holger (2006): Economic Benefits of Adopting IFRS or US-GAAP — Have the Expected Cost of Equity Capital Really Decreased?, Journal of Business Finance & Accounting, 33(3/4): 329–373.Google Scholar
  41. Daske, Holger and Günther Gebhardt (2006): International Financial Reporting Standards and Experts’ Perceptions of Disclosure Quality, Abacus, 42(3/4): 461–498.Google Scholar
  42. Dechow, Patricia M., Richard G. Sloan, and Amy P. Hutton (1996): Causes and Consequences of Earnings Manipulation: An Analysis of Firms Subject to Enforcement Actions by the SEC, Contemporary Accounting Research, 13(1): 1–36.Google Scholar
  43. Degeorge, Francois, Jayendu Patel, and Richard Zeckhauser (1999): Earnings Management to Exceed Thresholds, The Journal of Business, 72(1): 1–34.Google Scholar
  44. Ding, Yuan, Ole K. Hope, Thomas Jeanjean, and Hervé Stolowy (2007): Differences between Domestic Accounting Standards and IAS: Measurement, Determinants and Implications, Journal of Accounting and Public Policy, 26(1): 1–38.Google Scholar
  45. Duru, Augustine and David M. Reeb (2002): International Diversification and Analysts’ Forecast Accuracy and Bias, The Accounting Review, 77(2): 415–434.Google Scholar
  46. Easterwood, John C. and Stacey R. Nutt (1999): Inefficiency in Analysts’ Earnings Forecasts: Systematic Misreaction or Systematic Optimism?, Journal of Finance, 54(5): 1777–1797.Google Scholar
  47. El Shamy, Mostafa A. and Rashid Al-Qenae (2005): The Change in the Value-relevance of Earnings and Book Values in Equity Valuation over the past 20 Years and the Impact of the Adoption of IASs: The Case of Kuwait, International Journal of Accounting, Auditing and Performance Evaluation, 2 (1–2): 153–167.Google Scholar
  48. Elliott, John A. and Donna R. Philbrick (1990): Accounting changes and earnings predictability, The Accounting Review, 65(1): 157–174.Google Scholar
  49. Gassen, Joachim and Thorsten Sellhorn (2006): Applying IFRS in Germany: Determinants and Consequences, Betrieb-swirtschaftliche Forschung und Praxis, 58(4): 365–386.Google Scholar
  50. Gebhardt, William R., Charles M. C. Lee, and Bhaskaran Swaminathan (2001): Toward an Implied Cost of Capital, Journal of Accounting Research, 39(1): 135–176.Google Scholar
  51. Goncharov, Igor (2005): Earnings Management and its Determinants: Closing Gaps in Empirical Accounting Research, Peter Lang: Frankfurt/Main et al.Google Scholar
  52. Gu, Feng and Weimin Wang (2005): Intangible Assets, Information Complexity, and Analysts’ Earnings Forecasts, Journal of Business Finance & Accounting, 32(9–10): 1673–1702.Google Scholar
  53. Haller, Axel (2002): Financial Accounting Developments in the European Union: Past Events and Future Prospects, The European Accounting Review, 11(1): 153–190.Google Scholar
  54. Haller, Axel and Brigitte Eierle (2004): The Adaptation of German Accounting Rules to IFRS: A Legislative Balancing Act, Accounting in Europe, 1(1): 27–50.Google Scholar
  55. Hand, John R. M. (1990): A Test of the Extended Functional Fixation Hypothesis, The Accounting Review, 65(4): 740–763.Google Scholar
  56. Harris, Marry S. and Karl A. Muller (1999): The Market Valuation of IAS versus US-GAAP Accounting Measures Using Form 20-F Reconciliations, Journal of Accounting and Economics, 26(1–3): 285–312.Google Scholar
  57. Hayn, Carla (1995): The Information Content of Losses, Journal of Accounting and Economics, 20(2): 125–153.Google Scholar
  58. Heckman, James J. (1979): Sample Selection Bias as a Specification Error, Econometrica, 47(1): 153–161.Google Scholar
  59. Higgins, Huong N. (1998): Analyst Forecasting Performance in Seven Countries, Financial Analysts Journal, 54(3): 58–62.Google Scholar
  60. Higgins, Huong N. (2002): Analysts’ Forecasts of Japanese Firms’ Earnings: Additional Evidence, The International Journal of Accounting, 37(4): 371–394.Google Scholar
  61. Holthausen, Robert W., David F. Larcker, and Richard G. Sloan (1995): Annual Bonus Schemes and the Manipulation of Earnings, Journal of Accounting and Economics, 19(1): 29–74.Google Scholar
  62. Hope, Ole K. (2003a): Disclosure Practices, Enforcement of Accounting Standards, and Analysts’ Forecast Accuracy: An International Study, Journal of Accounting Research, 41 (2): 235–272.Google Scholar
  63. Hope, Ole K. (2003b): Accounting Policy Disclosures and Analysts’ Forecasts, Contemporary Accounting Research, 20(2): 295–321.Google Scholar
  64. Hope, Ole K. (2004): Variations in the Financial Reporting Environment and Earnings Forecasting, Journal of International Financial Management and Accounting, 15(1): 21–43.Google Scholar
  65. Hüfner, Hans P. Möller (1997): Erfolge börsen-notierter Unternehmen aus der Sicht von Finanzanalysten: Zur Verlässlichkeit von DVFA-Ergebnissen und deren Prog-nose, Zeitschrift für Bankrecht und Bankwirtschaft, 9(1): 1–14.Google Scholar
  66. Hung, Mingyi and Ram K. Subramanyam (2007): Financial statement effects of adopting International Accounting Standards: the case of Germany, Review of Accounting Studies, 12(4): 623–657.Google Scholar
  67. Hussain, Simon (1998): Lead Indicator Models and UK Analysts Earnings Forecasts, Accounting and Business Research, 28(4): 271–280.Google Scholar
  68. Hutton, Amy P. (2005): Determinants of Managerial Earnings Guidance Prior to Regulation Fair Disclosure and Bias in Analysts’ Earnings Forecasts, Contemporary Accounting Research, 22(4): 867–914.Google Scholar
  69. Hwang, LeeSeok, Ching-Lih Jan, and Sudipta Basu (1996): Loss Firms and Analysts’ Earnings Forecast Errors, Journal of Financial Statement Analysis, 1(2): 18–30.Google Scholar
  70. Ijiri, Yuji and James Noel (1984): A Reliability Comparison of the Measurement of Wealth, Income, and Force, The Accounting Review, 59(1): 52–63.Google Scholar
  71. Irvine, Paul J. (2004): Analysts’ Forecasts and Brokerage-firm Trading, The Accounting Review, 79(1): 125–150.Google Scholar
  72. Jacob, John, Thomas Z. Lys, and Margaret A. Neale (1999): Expertise in Forecasting Performance of Security Analysts, Journal of Accounting and Economics, 28(1): 51–82.Google Scholar
  73. Jaggi, Bikki and Rohit Jain (1998): An Evaluation of Financial Analysts’ Earnings Forecasts for Hong Kong Firms, Journal of International Financial Management and Accounting, 9(3): 177–200.Google Scholar
  74. Kinnunen, Juha, Jyrki Niskanen, and Eero Kasanen (2000): To whom are IAS Earnings Informative? Domestic versus Foreign Shareholders’ Perspectives, The European Accounting Review, 9(4): 499–517.Google Scholar
  75. Knutson, Peter H. (1992): Financial Reporting in the 1990s and beyond, Association for Investment Management and Research (AIMR), New York.Google Scholar
  76. Lang, Mark H. and Russel J. Lundholm (1996): Corporate Disclosure Policy and Analyst Behavior, The Accounting Review, 71(4): 467–492.Google Scholar
  77. Lang, Mark H., Karl V. Lins, and Darius P. Miller (2003): ADRs, Analysts, and Accuracy: Does Cross Listing in the United States Improve a Firm’s Information Environment and Increase Market Value?, Journal of Accounting Research, 41(2): 317–345.Google Scholar
  78. Lennox, Clive S. and Chul W. Park (2006): The informativeness of earnings and management’s issuance of earnings forecasts, Journal of Accounting and Economics, 42(3): 439–458.Google Scholar
  79. Leuz, Christian (2003): IAS versus US GAAP: Information Asymmetry-based Evidence from Germany’s New Market, Journal of Accounting Research, 41(3): 445–472.Google Scholar
  80. Leuz, Christian and Robert E. Verrecchia (2000): The Economic Consequences of Increased Disclosure, Journal of Accounting Research, 38(3): 91–124.Google Scholar
  81. Lin, Beixin and Rong Yang (2006): The Effect of Repeat Restructuring Charges on Analysts’ Forecast Revisions and Accuracy, Review of Quantitative Finance & Accounting, 27(3): 267–283.Google Scholar
  82. Lobo, Gerald J., Sung S. Kwon, and Gordian A. Ndubizu (1998): The Impact of SFAS No. 14 Segment Information on the Price Variability and Earnings Forecast Accuracy, Journal of Business Finance & Accounting, 25(7/8): 969–985.Google Scholar
  83. Lys, Thomas and Lisa G. Soo (1995): Analysts’ Forecast Precision as a Response to Competition, Journal of Accounting, Auditing & Finance, 10(4): 751–765.Google Scholar
  84. Maddala, Gangadharrao S. (1983): Limited-Dependent and Qualitative Variables in Econometrics, Cambridge University Press: New York.Google Scholar
  85. Markov, Stanimir and Ane Tamayo (2006): Predictability in Financial Analyst Forecast Errors: Learning or Irrationality?, Journal of Accounting Research, 44(4): 725–761.Google Scholar
  86. Matsumoto, Dawn A. (2002): Management’s Incentives to Avoid Negative Earnings Surprises, The Accounting Review, 77(3): 483–514.Google Scholar
  87. Mensah, Yaw M., Xiaofei Song, and Simon S.M. Ho (2004): The Effect of Conservatism on Analysts’ Annual Earnings Forecast Accuracy and Dispersion, Journal of Accounting, Auditing & Finance, 19(2): 159–183.Google Scholar
  88. Mikhail, Michael B., Beverly R. Walther, and Richard H. Willis (1997): Do Security Analysts Improve their Performance with Experience?, Journal of Accounting Research, 35 (3): 131–157.Google Scholar
  89. Niskanen, Jyrki, Juha Kinnunen, and Eero Kasanen (2000): The Value Relevance of IAS Reconciliation Components: Empirical Evidence from Finland, Journal of Accounting & Public Policy, 19(2): 119–137.Google Scholar
  90. Nobes, Christopher and Robert Parker (1998): Comparative International Accounting, 5th ed., Prentice Hall Europe: London.Google Scholar
  91. O’Brien, Patricia C. (1990): Forecast Accuracy of Individual Analysts in Nine Industries, Journal of Accounting Research, 28(2): 286–304.Google Scholar
  92. Peek, Erik (2005): The Influence of Accounting Changes on Financial Analysts’ Forecast Accuracy and Forecasting Superiority: Evidence from the Netherlands, European Accounting Review, 14(2): 261–295.Google Scholar
  93. Petersen, Mitchell A. (2007): Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches, Working paper, Northwestern University, forthcoming Review of Financial Studies.Google Scholar
  94. Plumlee, Marlene A. (2003): The Effect of Information Complexity on Analysts’ Use of that Information, The Accounting Review, 78(1): 275–296.Google Scholar
  95. Revsine, Lawrence, Daniel Collins, and Bruce W. Johnson (2001): Financial Reporting & Analysis, 2nd ed., Prentice Hall: Upper Saddle River, NJ.Google Scholar
  96. Richardson, Scott, Siew H. Teoh, and Peter D. Wysocki (2004): The Walkdown to Beatable Analyst Forecasts: The Roles of Equity Issuance and Insider Trading Incentives, Contemporary Accounting Research, 21(4): 885–924.Google Scholar
  97. Swaminathan, Siva (1991): The Impact of SEC Mandated Segment Data on Price Variability and Divergence of Beliefs, The Accounting Review, 66(1): 23–41.Google Scholar
  98. Teoh, Siew H., Welch Ivo, and T.J. Wong (1998): Earnings Management and the Long-Run Market Performance of Initial Public Offerings, Journal of Finance, 53(6): 1935–1974.Google Scholar
  99. Van Tendeloo, Brenda and Ann Vanstraelen (2005): Earnings Management under German GAAP versus IFRS, European Accounting Review, 14(1): 155–180.Google Scholar
  100. Vanstraelen, Ann, Marilyn T. Zarzeski, and Sean W.G. Robb (2003): Corporate Nonfinancial Disclosure Practices and Financial Analyst Forecast Ability across Three European Countries, Journal of International Financial Management and Accounting, 14(3): 249–278.Google Scholar
  101. Wallmeier, Martin (2005): Analysts’ Earnings Forecasts for DAX100 Firms during the Stock Market Boom of the 1990s, Financial Markets and Portfolio Management, 19(2): 131–151.Google Scholar
  102. Williams, Patricia A. (1996): The Relation between a Prior Earnings Forecast by Management and Analyst Response to a Current Management Forecast, The Accounting Review, 71(1): 103–115.Google Scholar
  103. Wooldridge, Jeffrey M. (2002): Econometric Analysis of Cross Section and Panel Data, MIT Press: Cambridge et al.Google Scholar

Copyright information

© The Author(s) 2008

Authors and Affiliations

  • Jürgen Ernstberger
    • 1
    Email author
  • Simon Krotter
    • 2
  • Christian Stadler
    • 3
  1. 1.Faculty of Business, Economics and Information SystemsUniversity of RegensburgGermany
  2. 2.Corporate Finance DepartmentSiemens AGMünchenGermany
  3. 3.School of Management, Royal HollowayUniversity of LondonGermany

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