Sample and Descriptive Statistics
VI. Conclusion and Discussion
In this study, we investigate the trend of accounting quality for firms listed in the Taiwan Stock Exchange Corporation during 1990–2011. As mentioned above, before 2000, twGAAP basically followed U.S. GAAP, and in the next thirteen years (2000–2012), twGAAP converged
33
with IFRS. This strategic swift is no doubt seminal. By focusing on the important dimension of accounting quality, value relevance of financial statements, this study try to verify if TFASC has succeeded in improving accounting quality of public firms in Taiwan.
We use two measures to examine the changes in joint value relevance of earnings and book value of equity in the price model during 1990–2011: adjusted R2 comparison of cross-sectional regression and abnormal pricing errors proposed by Gu (2007). We also decompose adjusted R2 to investigate whether the incremental explanatory powers of earnings and book value of equity would respectively change over time. In terms of joint value relevance, the empirical findings show that, although there is a statistically increasing trend during the whole period, it is primarily driven by increases of value relevance in the Developing period. Due to U.S. GAAP has been the infrastructure of twGAAP in the Developing Period, the results are consistent with prior literature showing that financial reporting system is a function not only of accounting standards, hence the marginal benefits of convergence with IFRS are limited. In terms of incremental value relevance, the incremental relevance of earnings exhibits a significant downward trend during the IFRS-Convergence Period, yet the incremental relevance of book value of equity reports a significant upward trend in the meantime. This indicates that the incremental relevance of earnings is slowly being replaced by that of book value of equity. However, consistent evidence cannot be found in the return model. This may be due to the different relations between
34
accounting numbers in explaining stock price in the short term, or increasing volatility of stock returns suggested by Francis and Schipper (1999). Overall, empirical results in this study indicate that, although convergence with IFRS does not lead to a further increase in the joint value relevance of financial statements, the replacement effect in the IFRS-Convergence Period show that at least the efforts of TFASC to stress the relevance of balance sheet have been paid off.
There are some countries still in the stage of limited convergence with IFRS (e.g., the U.S.,
Japan, and India), and one of the possible alternatives is to adopt a “country-specific version of IFRS” (Hail et al. 2010). Taiwan’s unique standard setting history provides an environment to
test the strategy. Specifically, in the context that a country had already followed a set of high quality accounting standards, convergence with IFRS cannot significantly improve the joint value relevance of financial statements for investors. Although convergence with IFRS may bring other qualitative characteristic benefits (for example, increases in comparability between domestic and foreign companies’ financial statements), however, countries with larger economic size continuously using domestic standards still have the ability to attract international investment and trade (Ramanna and Sletten 2013). Thus, comparability of financial statements may be not a decisive concern in determining convergence with or adoption of IFRS. The empirical evidence from Taiwan may provide implications to international standard setters and
35
regulators.
There are some caveats to note here. First, to what extent our conclusions from Taiwan can generalize to firms in other countries is not clear. Every country has its own unique institutional features as well as economic development stage. Findings in emerging markets like Taiwan may not be necessarily applicable to developed markets like the U.S. Second, as prior literature (e.g., Collins et al. 1997; Francis and Schipper 1999; Francis et al. 2002) has suggested, there may be many factors influencing the magnitude of value relevance. Although we try to consider some of them in this study (incidence of negative earnings, stability of economics, and nonrecurring items), some omitted variables may still exist. Therefore, the findings of this study should be interpreted with caution. Finally, we provide evidence with only one dimension of accounting quality (i.e., value relevance), and it cannot substitute for a comprehensive quality analysis.
Naturally, this study cannot prove which one is better between convergence with and adoption of IFRS.
36
APPENDIX
We use the abnormal pricing errors suggested by Gu (2007) to examine the value relevance of earnings and book value of equity. The abnormal pricing errors are estimated as follows:
Step 1: Run the price model (1a) each year and find the residuals for each firm.
Step 2: Classify all absolute fitted values of stock prices/returns ( Pˆ ) across years into 10 classes according to the size.
Step 3: For each class, normal pricing errors (benchmarks) are mean value in that class, calculated as
ii /n, where n is the number of observations of the class.Step 4: Each individual observation’s abnormal pricing error is calculate as the absolute value of difference between i and normal (benchmarks) pricing error.
Step 5: Then, we average the individual abnormal pricing errors of year t to generate the abnormal pricing errorAbPerrt.
37
REFERENCES
Ali, A., and L. Hwang. 2000. Country-specific factors related to financial reporting and the value relevance of accounting data. Journal of Accounting Research 38 (1): 1–21.
Armstrong, C. S., M. E. Barth, A. D. Jagolinzer, and E. J. Riedl. 2010. Market reaction to the adoption of IFRS in Europe. The Accounting Review 85 (1): 31–61.
Ball, R., S. P. Kothari, and A. Robin. 2000. The effect of international institutional factors on properties of accounting earnings. Journal of Accounting and Economics 29 (1): 1–51.
Ball, R., A. Robin, and J. S. Wu. 2003. Incentives versus standards: Properties of accounting income in four East Asian countries. Journal of Accounting and Economics 36 (1-3): 235–270.
Barth, M. E., W. H. Beaver, and W. R. Landsman. 2001. The relevance of the value-relevance literature for financial accounting standard setting: Another view. Journal of Accounting and Economics 31 (1–3): 77–104.
Barth, M. E., W. R. Landsman, and M. H. Lang. 2008. International accounting standards and accounting quality. Journal of Accounting Research 46 (3): 467–498.
Barth, M. E., W. R. Landsman, M. H. Lang, and C. Williams. 2012. Are IFRS-based and US GAAP-based accounting amounts comparable? Journal of Accounting and Economics 54 (1):
68–93.
Basu, S. 1997. The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics 24 (1): 3–37.
Bradshaw, M.T., and G. S. Miller. 2008. Will harmonizing accounting standards really harmonize accounting? Evidence from non-US firms adopting US GAAP. Journal of Accounting, Auditing and Finance 23 (2): 233–263.
Brown, S., K. Lo, and T. Lys. 1999. Use of R2 in accounting research: Measuring changes in value relevance over the last four decades. Journal of Accounting and Economics 28 (2): 83–115.
Chang, J. 1999. The Decline in Value Relevance of Earnings and Book Value. Working paper, University of Pennsylvania.
Chen H., Q. Ting, Y. Jiang, and Z. Lin. 2010. The role of International Financial Reporting Standards in accounting quality: Evidence from the European Union. Journal of International Financial Management and Accounting 21 (3): 220–278.
Chi, S. 2009. Simultaneous presence of different domestic GAAPs and investors’ limited attention bias in U.S. equity Markets: Implications for convergence. Working paper, 2010 AAA Financial Accounting and Reporting Section.
Collins, D. W., E. L. Maydew, and I. S. Weiss. 1997. Changes in the value-relevance of earnings and book values over the past forty years. Journal of Accounting and Economics 24 (1): 39–67.
Core, J.E., W.R. Guay and A.V. Buskirk. 2003. Market valuation in the new economy: An investigation of what has changed. Journal of Accounting and Economics 34 (1–3): 43–67.
38
Daske, H., L. Hail, C. Leuz, and R. Verdi. 2008. Mandatory IFRS reporting around the world: Early evidence on the economic consequences. Journal of Accounting Research 46 (5): 1085–1142.
Daske, H., L. Hail, C. Leuz, and R. Verdi. 2013. Adopting a label: heterogeneity in the economic consequences around IAS/IFRS adoptions. Journal of Accounting Research 51 (3): 495–547.
De George, E. T., C. B. Ferguson, and N. A. Spear. 2013. How much does IFRS cost? IFRS adoption and audit fees. The Accounting Review 88 (2): 429–462.
Drake, M. S., L. A. Myers, and L. Yao. 2010. Are Liquidity Improvements Around the Mandatory Adoption of IFRS Attributable to Comparability Effects or to Quality Effects? Working paper, 2010 AAA Financial Accounting and Reporting Section.
Easton, P. 1985. Accounting earnings and security valuation: Empirical evidence of the fundamental links.
Journal of Accounting Research 23 (Supplement): 54–77.
Ely, K., and G. Waymire. 1999. Accounting standard setting organizations and earnings relevance:
longitudinal evidence from NYSE common stock, 1927-93. Journal of Accounting Research 37 (2):
293–317.
Ewert, R., and A. Wagenhofer. 2009. Earnings quality metrics and what they measure. Working paper, University of Graz.
Feltham, G. A., and J. A. Ohlson, 1995. Valuation and clean surplus accounting for operating and financial activities. Contemporary Accounting Research 11 (2): 689–731.
Francis, J., and K. Schipper. 1999. Have financial statements lost their relevance? Journal of Accounting Research 37 (2): 319–352.
Francis, J., K. Schipper, and L. Vincent. 2002. Earnings announcements and competing information.
Journal of Accounting and Economics 33 (3): 313–342.
Goldberger, A. 1991. A Course in Econometrics. Boston: Harvard University Press.
Gu, Z. 2007. Across-sample incomparability of R2 and additional evidence on value relevance changes over time. Journal of Business Finance and Accounting 34 (7&8): 1073-1098.
Hail, L., C. Leuz, and P. Wysocki. 2010. Global accounting convergence and the potential adoption of IFRS by the U.S. (Part II): Political factors and future scenarios for U.S. accounting standards.
Accounting Horizons 24 (4): 567–588.
International Accounting Standards Board (IASB). 2012. Who We Are and What We Do. Available at:
http://www.ifrs.org/The-organisation/Documents/WhoWeAre2012MarchEnglish.pdf
Joos, P. P. M., and E. Leung. 2013. Investor perceptions of potential IFRS adoption in the United States.
The Accounting Review 88 (2): 577-609.
Kim, J-B., J. Tsui, and C. H. Yi. 2011. The voluntary adoption of International Financial Reporting Standards and loan contracting around the world. Review of Accounting Studies 16 (4): 779–811.
Kim J-B., X. Liu, and L. Zheng. 2012. The impact of mandatory IFRS adoption on audit fees: Theory and evidence. The Accounting Review 87 (6): 2061–2094.
39
Kim, J-B., and H. Shi. 2012. Voluntary IFRS adoption, analyst coverage, and information quality:
International evidence. Journal of International Accounting Research 11 (1): 45–76.
Lang, M. H., J. S. Raedy, and W. Wilson. 2006. Earnings management and cross listing: Are reconciled earnings comparable to US earnings? Journal of Accounting and Economics 42 (1–2): 255–283.
Leuz, C., D. Nanda, and P. Wysocki 2003. Earnings management and investor protection: An international comparison. Journal of Financial Economics 69 (3): 505–527.
Lev, B., and P. Zarowin. 1999. The boundaries of financial reporting and how to extend them. Journal of Accounting Research 37 (2): 353–385.
Li, S. 2010. Does mandatory adoption of International Financial Reporting Standards in the European Union reduce the cost of equity capital? The Accounting Review 85 (2): 607–636.
PricewaterhouseCoopers LLP (PwC). 2012. IFRS Adoption by Country. Available at:
http://www.pwc.com/en_US/us/issues/ifrs-reporting/publications/assets/pwc-ifrs-by-country-apr-2 012.pdf
Ramanna, K., and E. Sletten. 2013. Network Effects in Countries’ Adoption of IFRS. Working paper, Harvard Business School.
Securities and Exchange Commission (SEC). 2010. Commission Statement in Support of Convergence and Global Accounting Standards. Release No. 33-9109. Washington, DC: SEC.
Securities and Exchange Commission (SEC). 2012. Work Plan for the Consideration of Incorporating International Financial Reporting Standards into the Financial Reporting System for U.S. Issuers:
Final Staff Report. Washington, DC: Government Printing Office.
Theil, H. 1971. Principles of Econometrics. New York: John Wiley.
Yip, R. W. Y., and D. Young. 2012. Does mandatory IFRS adoption improve information comparability?
The Accounting Review 87(5): 1767-1789.
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TABLE 1 Descriptive Statistics
Variables Mean Std. Min Q1 Median Q3 Max
Pit 31.42 31.85 0.87 11.75 22.20 39.45 292.00
EPSit 1.58 2.54 -7.11 0.24 1.20 2.60 14.62
BVPSit 16.78 7.60 1.28 12.50 15.12 19.04 65.21
This table presents descriptive statistics for variables used for the following cross-sectional price model of scenario 1 (full sample, N=10,037):
(1a) Sample period: 1990–2011.
Variable Definitions:
Pit = the price of a share of firm i at the end of year t;
EPSit = earnings per share of firm i for year t;
BVPSit = the book value of equity per share of firm i at the end of year t;
it it it
it EPS BVPS
P 01 2
41 TABLE 2
Test on Value Relevance of Earning and Book Value of Equality: Adjust R2 of Cross-sectional Regressions Panel A (Scenario 1, N=10,037)
42
Scenario 3 (N=7,108) a b1 b2 b3 R 2 b1+b3
*, **, *** Indicate significance at 0.10, 0.05, and 0.01 levels, respectively (two-sided, unless direction is predicted).
Panel A of Table 2 presents the estimated coefficients (t-statistics in parentheses) and joint, separate, and incremental adjusted R2 of the price model (equation (1a), (1b), and (1c)) for Scenario 1 (full sample, N=10,037). Panel B of Table 2 presents the results of regressing adjusted R2 on time variables (equation (2a)) for the years included in Scenarios 1, 2 (eliminating firms with negative EPS,N=8,211), and 3 (eliminating firms with negative EPS and in years 2007 and 2008, N=7,108). In Panel C of Table 2, we further divide sample period (1990–2011) into two sub-periods, 1990–1999 (belongs to the Developing Period) and
EPS_IncrR2= incremental explanatory power of earnings per share, calculated as Joint_R2- BVPS_R2;
BVPS_ IncrR2=incremental explanatory power of book value of equity per share, calculated as Joint_R2- EPS_R2;
2
Rt = Joint _R2, EPS_IncrR2or BVPS_ IncrR2;
Yeart=trend variable equal to one for 1990, two for 1991, etc.;
S2=dummy variable representing the IFRS-Convergence Period (if the sample period is 2000–2011, S2=1, and 0 otherwise).
TABLE 3
The Relations between Absolute Fitted Value of Stock Prices and Pricing Errors
Scale Class
price model (Scenario 1, N=10,037)
Mean Pˆ Normal Pricing Errors
(Benchmark)
1 4.608 7.658
2 11.506 6.396
3 16.131 7.115
4 20.429 8.445
5 25.248 9.425
6 30.249 10.204
7 36.128 11.394
8 43.702 12.879
9 54.466 16.186
10 86.644 28.006
This table presents the relations between absolute fitted value of stock prices and pricing errors for the following cross-sectional price model of scenario 1 (full sample, N=10,037):
it it it
it EPS BVPS
P 01 2 (1a) Sample period: 1990–2011.
All observations are pooled across years and divided into ten class base on the absolute fitted value of stock prices (equation (1a)).
For each class, normal pricing error is calculated as the sample mean of the residuals calculated ase n, where n is the number of observations in that class.
TABLE 4
Tests on the Value Relevance of Earnings and Book Value of Equity: Abnormal Pricing Errors
*, **, *** Indicate significance at 0.10, 0.05, and 0.01 levels, respectively (two-sided, unless direction is predicted).
Panel A of Table 4 presents the results (t-statistics in parentheses) of regressing AbPerrt on time variables (equation (3a)) for the years included in Scenarios 1 (full sample, N=10,037), 2 (eliminating firms with negative EPS,N=8,211), and 3 (eliminating firms with negative EPS and in years 2007 and 2008, N=7,108). In Panel B of Table 4, we further divide sample period (1990–2011) into two sub-periods, 1990–1999 (belongs to the Developing Period) and 2000–2011 (belongs to the IFRS-Convergence Period) and run the regression of AbPerrt on time variables again (equation (3b)).
Variable Definitions:
Yeart= trend variable equal to one for 1990, two for 1991, etc.;
S2= dummy variable representing the IFRS-Convergence Period (if the sample period is 2000–2011, S2=1, and 0 otherwise);
AbPerrt= abnormal pricing errors of year t;
For detailed calculation of AbPerrt, see APPENDIX.
t
Table 5
Tests on the Value Relevance of Earnings and Book Value of Equity: AdjustedR2of Cross-sectional Regressions – Stock Prices on April 30
Panel A
Scenario 3 (N=7,108) a b1 b2 b3 R 2 b1+b3
*, **, *** Indicate significance at 0.10, 0.05, and 0.01 levels, respectively (two-sided, unless direction is predicted).
Panel A of Table 5 presents the results (t-statistics in parentheses) of regressing Rt2 on time variables (equation (2a)) for the years included in Scenarios 1 (full sample, N=10,037), 2 (eliminating firms with negative EPS,N=8,211), and 3 (eliminating firms with negative EPS and in years 2007 and 2008, N=7,108). In Panel B of Table 5, we further divide sample period (1990–2011) into two sub-periods, 1990–1999 (belongs to the Developing Period) and 2000–2011 (belongs to the IFRS-Convergence Period) and run the regression of Rt2 on time variables again (equation (2b)).
Variable Definitions:
Joint_R2= the adjusted R2 from equation (1a);
EPS_R2= the adjusted R2 from equation (1b);
BVPS_R2= the adjusted R2 from equation (1c);
EPS_IncrR2= incremental explanatory power of earnings per share, calculated as Joint_R2- BVPS_R2;
BVPS_ IncrR2= incremental explanatory power of book value of equity per share, calculated as Joint_R2- EPS_R2;
2
Rt = Joint _R2, EPS_IncrR2or BVPS_ IncrR2;
Yeart= trend variable equal to one for 1990, two for 1991, etc.;
S2= dummy variable representing the IFRS-Convergence Period (if the sample period is 2000–2011, S2=1, and 0 otherwise).
R2
R2
R2
TABLE 6
Tests on the Value Relevance of Earnings and Book Value of Equity: Abnormal Pricing Errors– Stock Prices on April 30
Panel A
*, **, *** Indicate significance at 0.10, 0.05, and 0.01 levels, respectively (two-sided, unless direction is predicted).
Panel A of Table 6 presents the results (t-statistics in parentheses) of regressing AbPerrt on time variables (equation (3a)) for the years included in Scenarios 1 (full sample, N=10,037), 2 (eliminating firms with negative EPS,N=8,211), and 3 (eliminating firms with negative EPS and in years 2007 and 2008, N=7,108). In Panel B of Table 6, we further divide sample period (1990–2011) into two sub-periods, 1990–1999 (belongs to the Developing Period) and 2000–2011 (belongs to the IFRS-Convergence Period) and run the regression of AbPerrt on time variables again (equation (3b)).
Variable Definitions:
Yeart= trend variable equal to one for 1990, two for 1991, etc.;
S2= dummy variable representing the IFRS-Convergence Period (if the sample period is 2000–2011, S2=1, and 0 otherwise);
AbPerrt= abnormal pricing errors of year t;
For detailed calculation ofAbPerrt, see APPENDIX.
t
Figure 1
Patterns of Adjusted R2 from Regressions of the Price Model (Equation (1a)) for TSEC-listed Firms, 1990-2011 (Scenario 1, N=10,037)
This Figure shows the trend in joint (Panel A) and incremental (Panel B) explanatory power of earnings and book values of equity on stock price across time for scenario 1 (N=10,037).
Sample period=1990-2011 Variable Definitions:
Total R-squ= explanatory power of earnings per share and book value of equity per share on stock price;
Incr_EPS R-squ= incremental explanatory power of earnings per share on stock price;
Incr_BVPS R-squ= incremental explanatory power of book value of equity per share on stock price.
it it it
it EPS BVPS
P 01 2 (1a)
Figure 2
Patterns of Abnormal Pricing Errorsfrom Regressions of the Price Model (Equation (1a)) for TSEC-listed Firms, 1990-2011 (Scenario 1, N=10,037)
This Figure shows the trend in abnormal pricing errors across time for scenario 1 (N=10,037).
Sample period=1990-2011 Variable Definitions:
Total Abq= abnormal pricing errors.
it it it
it EPS BVPS
P 01 2 (1a)
0 2 4 6 8 10 12 14
90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11
Total Abp
Year