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Dr. George Kontopoulos Pr. Georges Selim Mr. David Tyrrall

Value relevance of investor oriented vs. creditor oriented accounting systems through the IFRS transition Evidence from the UK, the Netherlands, Germany and France. Dr. George Kontopoulos Pr. Georges Selim Mr. David Tyrrall. Key issues. Basic question:

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Dr. George Kontopoulos Pr. Georges Selim Mr. David Tyrrall

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  1. Value relevance of investor oriented vs. creditor oriented accounting systems through the IFRS transitionEvidence from the UK, the Netherlands, Germany and France Dr. George Kontopoulos Pr. Georges Selim Mr. David Tyrrall

  2. Key issues • Basic question: Are IFRS more value relevant than European National GAAPs? • Aims of this research: - make “within country” comparison, testing the value relevance through the IFRS transition - make “across-country” comparisons, investigating the difference in value relevance between investor oriented (UK, Netherlands) and creditor oriented (Germany, France) accounting systems

  3. Literature review • Prior literature on value relevance and IFRS • Test the difference between earnings and book value • Examine the difference between code and common law accounting systems • Use annual accounts of early IFRS adopters or reconciliation reports pre-adoption to assess the effects of the IFRS transition • Main finding: early adopters benefit from the shift to IFRS in terms of value relevance • What is different to this research? • Looks at mandatory adopters – using annual financial statements under national GAAP (pre-IFRS period) and financial statements under IFRS (post-IFRS period) • It follows the “Investor” vs. “Creditor” oriented accounting systems categorization

  4. Methodology • The theoretical framework of this study is based on Ohlson (1995) • Basic concept: use of financial reporting for equity valuation • We use the following model: Where, = share price of a firm i three months after the end of fiscal year t, = earnings per share of firm i at the end of the year t, = book value per share of firm i at the end of year t, = indicator variable that is one if earnings are negative and zero otherwise, = error term, i.e. other value relevant information that cannot be captured by earnings and book value figures. • Then the model is decomposed to test the incremental explanatory power of earnings and book value (Collins et al. 1997)

  5. Data collection • 50 firms from four countries: UK, Netherlands, Germany, France • Used annual published financial reporting data between 2003 and 2006 (inclusive i.e. four years data) • Financial statements year ending 2003 & 2004: pre-IFRS period • Financial statements year ending 2005 & 2006: post-IFRS period • For pre-IFRS period include only firms using national GAAP and full consolidation

  6. Findings - UK • Upward trend in explanatory power of book value, earnings, total model • Explanatory power of earnings constantly outperforming that of book value • Increase in the value relevance greater for book value than for earnings

  7. Findings - Netherlands • Like the UK, upward trend in explanatory power of book value, earnings, and total model • Explanatory power of earnings consistently outperforming that of book value • Netherlands has the highest increase between the pre and post-IFRS value relevance but also the most variability

  8. Findings - Germany • The explanatory power of book values is increasing while the value relevance of earnings is decreasing • The overall value relevance is slightly rising • Germany is the country with the highest level of value relevance through time

  9. Findings - France • The explanatory power of earnings is decreasing and that of book value is increasing through time • Value relevance peaks in 2004 and 2005 but is slightly decreasing for the post-IFRS period • Overall through the period value relevance is higher from that in the UK and the Netherlands and lower from that in Germany

  10. Findings - Investor vs. creditor oriented Investor / UK Investor / Netherlands Creditor / Germany Creditor / France • Overall level and change in value relevance not the same for all countries, but the overall value relevance is increasing for the observed countries for the post-IFRS period • The creditor oriented group has different characteristics (higher level, lower increase) from the investor oriented group (lower level, higher increase)

  11. Conclusions • Although there are differences, value relevance is increasing during the post-IFRS period • Balance sheet is gaining in importance for value relevance over the income statement through time in all countries • The overall value relevance spiked up between 2004 and 2005 possibly due to dual reporting (reconciliation statements) • Investor oriented countries (the UK and the Netherlands) indicated higher positive change but lower overall level of value relevance of accounting information compared with creditor oriented countries (Germany and France) • Putting it differently there are differences in level and differences in slope • Why these results?

  12. Possible explanations Differences in slope: • The UK and the Netherlands have more cross-listed firms than France and Germany, therefore more companies to gain the main benefits of the IFRS transition • France and Germany had more early adopters than the UK and the Netherlands so the main beneficiaries of IFRS adoption were deliberately excluded from our sample Differences in level are more problematic: • France and Germany had more early adopters than the UK and the Netherlands so they were more prepared for the IFRS transition, therefore the level was higher than that of the investor oriented countries • Is creditor oriented accounting more value relevant?

  13. Thank you Questions/comments please

  14. Appendix I – TablesUK Descriptive Statistics

  15. Appendix I – TablesUK (excluding outliers/extremes) • Model Summary Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  16. Appendix I – TablesUK (excluding outliers/extremes) • Coefficients Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  17. Appendix I – TablesNetherlands Descriptive statistics Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  18. Appendix I – TablesNetherlands • Model summary Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  19. Appendix I – TablesNetherlands • Coefficients Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  20. Appendix I – TablesGermany Descriptive statistics Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  21. Appendix I – TablesGermany (excluding outliers/extremes) • Model summary Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  22. Appendix I – TablesGermany (excluding outliers/extremes) • Coefficients Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  23. Appendix I – TablesFrance Descriptive Statistics Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  24. Appendix I – TablesFrance (excluding outliers/extremes) • Model summary Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  25. Appendix I – TablesFrance (excluding outliers/extremes) • Coefficients Source: Developed by the authors *Notes: The estimated regression models are based on ordinary least squares. Adjusted R-square and Standardised beta coefficients were used in order to make valid comparisons. BV stands for Book Values Per Share while EAR stands for Earnings Per Share. The regression model used is (4).

  26. Appendix II – Creditor vs. investor oriented accounting systems (Nobes, 1998)

  27. Appendix III - Hypotheses testing • H1: “The adoption of IFRS will change the value relevance of accounting information in the EU” • H2: “The investor oriented accounting systems (UK, Netherlands) will have different value relevance from the creditor oriented ones (Germany, France) after the adoption of IFRS”

  28. Appendix IV - Data collection process • Sampling process: Step 1: Selection of countries and listed firms Step 2: Exclusion of ADR’s, financial & utility firms (using GICS) Step 3: Prior to 2005 include only firms using domestic GAAP and full consolidation (first-time adopters IFRS1). Companies voluntarily following IAS (early adopters) or US GAAP were also excluded. This will be the final population of firms out of which random sampling will follow. Step 4: Scale proxies: market capitalisation, P/E, growth/sales (eliminate top & bottom 1.5 %, control for effects of extreme values) Step 5: Randomly select 50 firms from each country for each year • Observation period: Financial statement 2003-2004 (national GAAP) and 2005-2006 (mandatory IFRS) • Grouping: - Investor oriented (UK, Netherlands), creditor oriented (Germany, France)

  29. Appendix V – GraphsFindings individual countries congregate • Value relevance in individual countries excluding outliers/extremes: UK Netherlands Germany France

  30. Appendix V – GraphsDecomposing the model (value relevance/black, book value/grey, earnings/white, disclosure effect/blue) • Value relevance of book values vs. earnings : UK Netherlands Germany France

  31. Appendix V – GraphsRegression models used (UK)

  32. Appendix V – GraphsRegression models used (Netherlands)

  33. Appendix V – GraphsRegression models used (Germany)

  34. Appendix V – GraphsRegression models used (France)

  35. Appendix VI - Areas for future research • Extend this research to cover more years (backwards and forwards) • Include more countries, or group of countries (like Eastern Europe) • Focus more on scale effects, difference between small, medium, large capitalization firms • Examine sectors within and across countries under the same methodology • Contradict German “early IFRS adopters” with “German enforced IFRS users” • Apply and justify different methodologies like Hellstroms’ (2006) log regression model • Do a qualitative study to juxtapose these findings to preparers’ and users’ views on the effect of IFRS transition

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