Mandatory IFRS Adoption and Accounting Conservatism
Bin Ke,1 Danqing Young2 and Zili Zhuang3
June 28, 2013
We wish to thank Charles Hsu, and workshop participants at xxx for helpful comments. 1 Division of Accounting, Nanyang Business School, Nanyang Technological University, S3-01b-39, 50 Nanyang Avenue, Singapore 639798.Tel: +65 6790 4832. Fax: +65 6791 3697. Email: [email protected]. 2 School of Accountancy, Chinese University of Hong Kong, Shatin, Hong Kong. Tel: +852 3943 7892. Fax: +852 2603 5114. Email:[email protected]. 3 School of Accountancy, Chinese University of Hong Kong, Shatin, Hong Kong. Tel: +852 3943 7776. Fax: +852 2603 5114. Email:[email protected].
ABSTRACT Using a large sample of listed firms from 17 European countries that mandatorily adopted IFRS over the period 2005-2008, we examine the effect of mandatory IFRS adoption on accounting conservatism defined using Basu’s (1997) differential timeliness (DT) measure. An important distinction of our study is that we avoid the common criticisms of the DT measure by comparing the difference in the DT measure under local accounting standards and IFRS for the same firm in the same IFRS reconciliation year. We find no evidence that the mandatory IFRS adoption changes the degree of accounting conservatism for non-financial firms, independent of the firms’ countries of domicile. For financial firms domiciled in strong legal enforcement countries, we find some weak evidence that the mandatory IFRS adoption increases the degree of accounting conservatism. In contrast, for financial firms domiciled in weak legal enforcement countries, we find that the mandatory IFRS adoption results in a decrease in accounting conservatism. Key words: IFRS; conservatism JEL: M41, M48, G14, N20 Data Availability: Data used in this study are publicly available from the sources identified in the paper.
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1. Introduction
The objective of this study is to examine how the mandatory adoption of
International Financial Reporting Standards (IFRS) affects accounting conservatism
defined using Basu’s (1997) differential timeliness (DT) measure. We test our research
question using the unique IFRS reconciliation data for a comprehensive sample of 2,591
unique firms from 17 European countries that mandatorily adopted IFRS over the
period 2005-2008.
Watts (2003a) defines accounting conservatism as the differential verifiability
required for recognition of profits versus losses. Watts (2003a) indicates that
conservatism has survived in accounting for many centuries and appears to have
increased in the last 30 years. Up to recently, the IASB’s and FASB’s conceptual
frameworks had regarded conservatism as one of the four principal qualitative
characteristics of financial statements. To the surprise of many, the new joint conceptual
framework of the IASB and FASB adopted in September 2010 does not include
conservatism as a desirable quality of financial reporting information (IASB 2010) and
instead considers “faithful representation” as a fundamental quality characteristic of
financial information, which implies a focus on completeness, neutrality, and freedom
from errors.
The shift in the stand of the IASB and FASB has generated a lot of discussions
and controversies due to the widespread mandatory adoption of IFRS around the world
and the fact that many requirements in IFRS differ from those in local standards for
many IFRS adopting countries. Critics argue that the mandatory adoption of IFRS
2
reduces accounting conservatism and ultimately accounting quality for several reasons.
First, Watts (2003a, 2003b) argues that the observed accounting conservatism in many
countries’ local accounting standards is a result of important economic forces such as
contracting and shareholder litigation. It is believed that IFRS’ extensive use of fair
value accounting reduces accounting conservatism and thus the usefulness of
accounting information to investors.
However, it is far from clear whether all the fair value accounting rules under
IFRS will result in less conservative financial reporting relative to local accounting
standards. For example, IFRS2 requires the expensing of employee stock options when
they are granted. This rule could result in more conservative earnings because, except
for UK and Ireland, all the other European countries in our sample did not require the
expensing of stock options prior to the IFRS adoption. Likewise, IAS39 requires firms to
recognize the fair value of derivatives on the balance sheet and the change in the fair
value of derivatives in earnings. For firms operating in countries whose local
accounting standards didn’t require the fair value of derivatives to be recognized on the
balance sheet, the mandatory IFRS adoption could lead to more conservative financial
reporting.
Second, critics claim that as principles-based standards, IFRS inherently lack
detailed implementation guidance and thus afford managers greater flexibility
(Langmead and Soroosh 2009). Nelson et al. (2002) show in a survey of Big 5 U.S. audit
firms that audit partners and managers are less likely to require adjustments to clients’
earnings management attempts when dealing with less precise or relatively looser
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standards. Hence, there is a risk that the mandatory adoption of IFRS could lead to
more aggressive financial reporting.
However, EU regulators were aware of such risks and passed some new
regulations to facilitate the mandatory adoption of IFRS. For example, the Transparency
Directive was passed in December 2004 which focuses on enforcement mechanisms to
ensure public companies to have appropriate level of transparency to investors. Such
new regulations may reduce managers’ incentives to use principles-based IFRS to
manipulate reported earnings. Therefore, it is an empirical question how mandatory
IFRS adoption affects accounting conservatism.
Three studies (Piot et al. 2011; Andre et al. 2012; Ahmed et al. 2012) have
examined the effect of mandatory IFRS adoption on accounting conservatism. All three
studies use Basu’s (1997) DT measure as one of the proxies for accounting conservatism.
The sample of mandatory IFRS adopters used by both Piot et al. and Andre et al. are all
European firms while close to 90 percent of the mandatory IFRS adopters used by
Ahmed et al. are European firms. A common feature of the three studies’ research
design is that they examine the change in accounting conservatism in the period before
versus the period after the mandatory IFRS adoption (i.e., an inter-temporal approach).
All three studies find evidence of a decline in accounting conservatism after the
mandatory IFRS adoption.
However, as noted by Barth et al. (2011), a limitation of the inter-temporal
approach is that any observed changes in conservatism after the mandatory IFRS
adoption could be due to competing explanations such as concurrent changes in a
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firm’s economic environment. For example, Christensen et al. (2012) find that
concurrent enforcement changes around the IFRS mandate partially explain the capital
market effects of mandatory IFRS adoption.
The inter-temporal approach’s limitation is especially relevant to the DT measure
because Givoly et al. (2007) show that certain time-variant characteristics of a firm’s
information environment unrelated to conservatism, including the degree of uniformity
in the content of the news during the examined period, the types of events occurring in
the period, and the firm’s disclosure policy, can affect the DT measure. Dietrich et al.
(2007) show more generally that the DT measure suffers from significant biases such
that empirical results could falsely indicate evidence of conservatism even in the
absence of asymmetric timeliness in reported earnings.1
In this study we assess the effect of mandatory IFRS adoption on accounting
conservatism using an alternative approach that does not suffer from the same
limitation as the inter-temporal approach. Specifically, we compare the degree of
accounting conservatism measured using the DT measure under two different sets of
accounting standards, local accounting standards versus IFRS, for the same firm years.
This is made possible because IFRS 1 First-time Adoption of International Financial
Reporting Standards (IASB 2003) requires that when a firm adopts IFRS, it must provide
1 Patatoukas and Thomas (2011) further show that two time-variant empirical regularities, related to scale, combine to cause a bias in the DT measure. Patatoukas and Thomas (2011) advise researchers to avoid using the DT measure. However, Ball et al. (2013) argue that the DT measure is a valid measure of accounting conservatism. Ball et al. show that the scale effects identified by Patatoukas and Thomas (2011) are merely a correlated omitted variable problem and can be easily dealt in a straightforward fashion such as using fixed effects regression. Our research design can also mitigate the bias noted by Pataoukas and Thomas because we compare the DT measure under local standards versus under IFRS for the same firm year.
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a reconciliation of net income based on local standards to that based on IFRS for the last
year the firm applied local standards (denoted as the reconciliation year). Because our
research design holds constant all the other aspects of a firm’s institutional environment,
any difference in the DT measure across the two sets of accounting standards is likely
attributed to the mandatory IFRS adoption.
Following Barth et al. (2011), we analyze non-financial firms and financial firms
separately because firms in these two major industry groups differ in asset and income
composition, and therefore are affected differently by differences between IFRS and
local accounting standards. For example, IFRS’ extensive use of fair value accounting is
expected to have a greater impact on financial firms than on non-financial firms. Prior
research indicates that legal enforcement matters in the credible implementation of IFRS
(Daske et al. 2008; Li 2010). Hence, we further decompose our sample firms into those
domiciled in strong legal enforcement countries and those domiciled in weak legal
enforcement countries.
For non-financial firms, we find no evidence of a significance difference (increase
or decrease) in the DT measure under local standards and IFRS for either strong legal
enforcement countries or weak legal enforcement countries. For financial firms
domiciled in strong legal enforcement countries, we find no evidence of a significant
decrease in the DT measure after the mandatory IFRS adoption as reported in the prior
literature. Instead, there is some evidence of a significant increase in the DT measure
after the mandatory IFRS adoption. In contrast, for financial firms domiciled in weak
legal enforcement countries, we find evidence that the mandatory IFRS adoption
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reduces accounting conservatism. However, this latter result should be interpreted with
caution due to the small sample size.
We also examine how the mandatory IFRS adoption affects the timeliness in the
recognition of good news and bad news separately. We find little evidence that the
mandatory IFRS adoption results in significant changes in the recognition of good news
and bad news for non-financial firms. For financial firms domiciled in strong legal
enforcement countries, we find that the recognition of both good news and bad news
becomes more timely under IFRS than under local standards. In contrast, for financial
firms domiciled in weak legal enforcement countries, we find that the recognition of
bad news becomes less timely under IFRS than under local standards; but there is no
evidence of a significant change in the recognition of good news under IFRS versus
under local standards.
Overall, the difference in the results (both the DT measure and the timeliness in
the recognition of good news and bad news separately) between non-financial firms
and financial firms may not be too surprising because IFRS’ extensive use of fair value
accounting is expected to have a greater impact on financial firms. The difference in the
results for financial firms domiciled in strong versus weak legal enforcement countries
suggests that the mandatory IFRS adoption can improve financial firms’ timeliness in
the recognition of both good news and bad news without sacrificing accounting
conservatism, provided that the implementation of the mandatory IFRS adoption is
subject to strong legal enforcement.
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Our findings on accounting conservatism based on the DT measure are
inconsistent with those from Piot et al. (2011), Andre et al. (2012), and Ahmed et al.
(2012) and provide timely information to the ongoing debate on the economic
consequences of mandatory IFRS adoption.
The rest of the paper is organized as follows. Section 2 discusses the institutional
background and sample selection procedures. Section 3 presents the research design.
Section 4 reports the regression results. Section 5 concludes.
2. Institutional Background and Sample Selection Procedures
Mandatory IFRS adopters are required to follow the procedures described in
IFRS 1 when adopting IFRS for the first time. For firms adopting IFRS in 2005, IFRS 1
requires presentation of statements of financial position for fiscal years ending 2003,
2004, and 2005, and statements of comprehensive income for 2004 and 2005. In making
the transition from local standards to IFRS, firms must (1) derecognize assets and
liabilities recognized in accordance with local standards but not IFRS, (2) recognize
assets and liabilities that are recognized in accordance with IFRS but not local standards,
(3) reclassify amounts following the requirements of IFRS, e.g., reclassifying a financial
instrument as a liability that had previously been recognized as equity in accordance
with local standards, and (4) use measurement principles embodied in IFRS. In addition
and more relevant to our study, all mandatory IFRS adopting firms are required to
provide a reconciliation of the 2003 and 2004 statements of financial position and 2004
net income based on local standards to net income based on IFRS. In this study we take
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advantage of the two net income figures provided by the mandatory reconciliation to
address our research question.
Table 1 shows the sample selection procedures. We started with the population
of 3,757 firms in Worldscope for the 17 European countries that mandatorily adopted
IFRS over the period 2005-2008. We were able to locate the annual reports and hand
collect from the annual reports the reported earnings under both local standards and
IFRS in the reconciliation year for 2,749 firms. After eliminating firms with missing
stock prices and the number of common shares outstanding, we obtain a final sample of
2,591 unique firms.
Table 2 shows the descriptive statistics for the final sample. Panel A reports the
distribution of the sample firms by the year of reconciliation. Most prior research
focuses on firms that mandatorily adopted IFRS in 2005 (reconciliation year is 2004).
However, as seen in Panel A, these firms represent only 60.67% of our sample. Panel B
shows the distribution of our sample firms by country for strong and weak legal
enforcement countries separately. DeFond and Hung (2004) show that it is the law
enforcement institutions rather than investor protection laws that matter to investor
protection. Hence, we classify the foreign countries in our sample into the weak and
strong investor protection groups by the median score of law enforcement ratings (7.72)
reported in La Porta et al. (1998).2
2 Luxembourg was not rated by La Porta et al. (1998) and thus is automatically assumed to belong to the weak investor protection country group. However, inferences are robust to treating Luxembourg as a strong investor protection country.
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3. Research Design
We use the following standard cross-sectional regression model (Basu 1997) to
estimate the DT measure:
EPSit = β0 + β1Dit + β2Rit + β3Dit×Rit (1)
See the appendix for all the variable definitions. The dependent variable EPS refers to
either the EPS measured using local accounting standards (denoted as EPS_LOCAL) or
the EPS measured using IFRS (denoted as EPS_IFRS) in the reconciliation year. The
coefficient on R (β2) measures the degree of timeliness in good news recognition. The
sum of the coefficient on R and D×R measures the degree of timeliness in bad news
recognition. The coefficient on D×R (β3) represents the DT measure, i.e., the differential
timeliness in the recognition of bad news vs. good news. A positive coefficient on D×R
is often interpreted as evidence of accounting conservatism in the prior literature.
However, due to the ongoing debate on the interpretation of the coefficient on D×R
(Givoly et al. 2007; Dietrich et al. 2007; Patatoukas and Thomas 2011; Ball et al. 2013), we
refrain from interpreting the coefficient on D×R in its absolute term. Instead, we focus
on the difference in the coefficients on D×R under local accounting standards and IFRS.
If mandatory IFRS adoption results in reduced (increased) accounting conservatism, we
should expect the coefficient on D×R to be smaller (larger) when the dependent variable
is EPS_IFRS rather than EPS_LOCAL.
As noted in the Introduction, the impact of IFRS adoption could be different for
non-financial firms and financial firms and depend on the strength of a country’s legal
10
enforcement. Hence, we report all the regression results for non-financial firms and
financial firms across different legal enforcement regimes separately.
4. Regression Results
4.1. Regression Results for Non-Financial Firms and Financial Firms
To increase the test power, we first estimate model (1) for non-financial firms and
financial firms separately, without distinguishing the listed firms’ legal enforcement
regimes. Table 3 reports the regression results of model (1). Panel A shows the
descriptive statistics of the key regression variables EPS and R for non-financial firms
and financial firms separately. The mean (median) EPS in the reconciliation year is
significantly higher under IFRS than under local accounting standards for both non-
financial firms and financial firms (p<0.001).
Panel B shows the regression results of model (1) for non-financial firms. We find
that the coefficient on D×R is not significantly different under local accounting
standards versus under IFRS. Hence, there is no evidence that the mandatory IFRS
adoption results in any significant change in accounting conservatism for non-financial
firms. In addition, neither the coefficient on R nor the sum of the coefficients on R and
D×R is significantly different under local accounting standards versus under IFRS,
suggesting there is no difference in the timeliness of both good news and bad news
recognition across the two types of accounting standards.
Turning to financial firms in Panel C, we find that the coefficient on D×R is not
significantly different under local accounting standards versus IFRS, suggesting no
11
evidence that the mandatory IFRS adoption results in any significant change in
accounting conservatism for financial firms. However, we do notice that the coefficient
on R is significantly more positive under IFRS (p=0.042). In addition, the sum of the
coefficients on R and D×R is more positive under IFRS than under local accounting
standards though the two-tailed p value is only 0.179. Thus, there is weak evidence that
the mandatory IFRS adoption makes financial firms’ recognition of both good news and
bad news more timely without adversely affecting the degree of accounting
conservatism.
4.2. Change in Accounting Conservatism by Country’s Legal Enforcement Strength
Prior research suggests the impact of mandatory IFRS adoption on financial
reporting quality depends on the strength of a country’s legal enforcement. Therefore,
we further decompose the sample firms in Table 3 by the legal enforcement quality of
the firms’ countries of domicile. The results are shown in Table 4.
For non-financial firms (see Panel A of Table 4), the decomposition does not
significantly alter our inferences of Table 3. Specifically, for both strong and weak legal
enforcement firms, the coefficient on D×R continues to be insignificantly different under
local accounting standards versus under IFRS.
For financial firms, however, our inferences in Panel B of Table 4 change relative
to those in Table 3. For financial firms domiciled in strong legal enforcement countries,
we continue to find no evidence of a significant difference in accounting conservatism
under local accounting standards versus under IFRS. In addition, the coefficient on R
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continues to be significantly larger under IFRS than under local accounting standards
(p=0.004) while the difference between the sums of the coefficients on R and D×R
remains insignificant, suggesting that the timeliness of the bad news recognition does
not change significantly under IFRS.
Turning to financial firms domiciled in weak legal enforcement countries, we
find that the coefficient on D×R is significantly smaller under IFRS than under local
accounting standards, suggesting that the degree of accounting conservatism declines
after the mandatory IFRS adoption for financial firms domiciled in weak legal
enforcement countries. This latter evidence is consistent with the concern of IFRS critics
that weak legal enforcement reduces the implementation credibility of mandatory IFRS
adoption, which in turn reduces the degree of accounting conservatism in reported
earnings. However, this result should be interpreted with caution due to the small
sample size (N=122). With regard to the timeliness of good news and bad news
recognition, we find that the coefficient on R is insignificantly different between local
accounting standards and IFRS, but the sum of the coefficients on R and D×R is
significantly smaller under IFRS than under local accounting standards. This latter
evidence suggests that the mandatory IFRS adoption in weak legal enforcement
countries reduces financial firms’ timeliness of bad news recognition.
4.3. The Differences between Local Accounting Standards and IFRS
The regression results reported in Tables 3 and 4 are based on the implicit
assumption that the mandatory IFRS adoption is an economically significant event for
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the affected firms. However, this is unlikely to be true for the countries whose local
accounting standards were already fairly close to the IFRS prior to the mandatory
adoption. Accordingly, we follow Bae et al. (2008) by eliminating the countries whose
local standards don’t differ significantly from the IFRS. Specifically, Bae et al. (2008,
Table 1) manually code the differences between local standards and IFRS for 21 major
IAS items. We eliminate the following countries whose differences between local
standards and IFRS are no greater than 7 (i.e., one third of the 21 IAS items): UK,
Ireland, Netherlands, and Norway. With the exception of Ireland, all the deleted firms
belong to high legal enforcement countries.
Table 5 shows the replication of the regression models in Table 4 using this
smaller sample. Focusing on the results for non-financial firms in Panel A, we continue
to find no evidence that the coefficient on D×R differs significantly under local
standards versus under IFRS for both strong legal enforcement countries and weak
legal enforcement countries. The only noticeable change relative to Table 4 is that the
sum of the coefficients on R and D×R is now smaller (i.e., less timely) under IFRS than
under local standards, but the difference is only marginally significant (p=0.074).
Turning to the results for financial firms in Panel B, we find that the coefficient
on D×R becomes marginally more positive under IFRS than under local standards for
financial firms domiciled in strong legal enforcement countries (p value=0.066). This
evidence suggests that the mandatory IFRS adoption results in an increase rather than a
decrease in conservatism for financial firms domiciled in strong legal enforcement
countries. This finding is contrary to the conventional wisdom. The reason for this
14
result lies in the fact that after the mandatory IFRS adoption the timeliness of bad news
recognition increases to a greater extent than the timeliness of good news recognition.
Specifically, the coefficient on R (good news) increases from 0.049 to 0.080 (p
value=0.121) while the sum of the coefficients on R and D×R (bad news) increases from
0.543 to 0.767 (p value=0.014). The increase in the timeliness of the bad news recognition
is significant (p value=0.014) while the increase in the timeliness of the good news
recognition is not (p value=0.121).
For financial firms domiciled in weak legal enforcement countries, the coefficient
on D×R continues to be smaller under IFRS than under local standards, and the
difference is statistically significant (p=0.000). In addition, we continue to observe a
significant difference in the sum of the coefficients on R and D×R (p =0.000). Similar to
Table 4, the decline of accounting conservatism under IFRS for firms domiciled in weak
legal enforcement countries is mainly driven by the decrease in the timeliness of
recognizing bad news under IFRS. Again, readers should exercise caution when
interpreting the results in Table 5 due to the small sample sizes.
5. Conclusion
The objective of this study is to examine the effect of mandatory IFRS adoption
on accounting conservatism defined using Basu’s (1997) differential timeliness (DT)
measure. We test our research question using a large sample of listed firms from 17
European countries that mandatorily adopted IFRS over the period 2005-2008. An
important distinction of our study is that there are two sets of net income figures
15
measured using local standards and IFRS for the same firm in the IFRS reconciliation
year. Hence, we able to avoid the common criticisms of Basu’s DT measure by holding
constant a firm’s institutional environment. For non-financial firms, we find little
evidence that the mandatory IFRS adoption results in significant changes in the degree
of accounting conservatism for firms domiciled either in strong legal enforcement
countries or weak legal enforcement countries. For financial firms, we find some weak
evidence that the mandatory IFRS adoption results in an increase in accounting
conservatism for firms domiciled in strong legal enforcement countries but we find a
significant decrease in accounting conservatism for firms domiciled in weak legal
enforcement countries.
Overall, our findings are contrary to the conventional wisdom that the
mandatory IFRS adoption would lead to a reduction in accounting conservatism. The
reason for this surprising finding is that the adoption of IFRS results in the increased
timeliness in both good news recognition and bad news recognition without affecting
the differential timeliness of bad news recognition versus good news recognition, which
is captured by Basu’s DT measure. Our results are inconsistent with several existing
studies that rely on an inter-temporal approach to assess the impact of mandatory IFRS
adoption on accounting conservatism using Basu’s DT measure. As our approach
doesn’t suffer from the common criticisms of the inter-temporal approach, the evidence
from our study suggests caution for future researchers who wish to use inter-temporal
approach to study the economic consequences of mandatory IFRS adoption.
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Appendix. Variable Definition
EPS_LOCAL = the basic earnings per share in the reconciliation year, deflated by the year-beginning stock price; EPS_IFRS = the restated IFRS earnings per share in the reconciliation year, deflated by the year-beginning stock price; R = the 12-month raw return from 8 months before the fiscal year end of the reconciliation year to 4 months after the fiscal year end of the reconciliation year; D = a dummy variable that equals one if R<0, and zero otherwise. Legal enforcement: we classify the foreign countries in our sample into the weak and strong investor protection groups by the median score of law enforcement ratings (7.72) reported in La Porta et al. (1998).
19
Table 1 Sample Selection Procedure
Number of unique firms
All firms in Worldscope for the 17 European countries that mandatorily adopted IFRS in 2005-2008
3,757
minus firms whose annual reports for the reconciliation year could not be found
-1,008
minus firms with missing common shares outstanding -96 minus firms with missing stock prices at the end of the 4th month after the fiscal year end -17 minus firms with missing stock returns -45 Final sample
2,591
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Table 2. Descriptive Statistics
Panel A. Sample distribution by year of reconciliation Year of Reconciliation Frequency Percent
Cumulative Percent
2004 1,572 60.67 60.67 2005 534 20.61 81.28 2006 220 8.49 89.77 2007 265 10.23 100.00
Panel B. Sample distribution by country of domicile
Non-Financial Firms Financial Firms Strong legal enforcement countries Austria 13 4 Belgium 43 23 Switzerland 41 6 Germany 188 32
Denmark 58 23 UK 836 207 Finland 85 11 Netherlands 81 14 Norway 74 13 Sweden 119 25 Subtotal 1,538 358
Weak legal enforcement countries France 315 53 Greece 40 12 Ireland 33 5 Italy 118 33 Luxembourg 4 4 Spain 35 10 Portugal 28 5 Subtotal 573 122 Total 2,111 480
See the Appendix for the definitions of strong and weak legal enforcement.
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Table 3. Regression Results for Non-Financial Firms and Financial Firms Separately
Panel A. Descriptive statistics
Non-Financial Firms
Mean Std. Dev.
10th Percentile
25th Percentile Median
75th Percentile
90th Percentile
EPS_LOCAL 0.028 0.204 -0.133 -0.008 0.048 0.086 0.150 EPS_IFRS 0.040 0.211 -0.126 -0.001 0.056 0.097 0.162 R 0.199 0.472 -0.317 -0.075 0.133 0.416 0.742 Financial Firms
Mean Std. Dev.
10th Percentile
25th Percentile Median
75th Percentile
90th Percentile
EPS_LOCAL 0.089 0.195 -0.027 0.036 0.077 0.128 0.245 EPS_IFRS 0.116 0.206 -0.027 0.050 0.096 0.162 0.281 R 0.276 0.393 -0.115 0.065 0.232 0.440 0.634
Panel B. Regression results for non-financial firms (N=2,111)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.039 0.004 D -0.039 0.006 R 0.040 0.008 R 0.040 0.002 D×R 0.211 0.000 D×R 0.204 0.000 Cons. 0.050 0.000 Cons. 0.061 0.000 The sum of the coefficients on R and D×R 0.251 0.001
0.244 0.000
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.803
p value for the Ho: the coefficient on R is equal for the two regressions 0.925
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.767
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Panel C. Regression results for financial firms (N=480)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.073 0.026 D -0.052 0.287 R 0.021 0.399 R 0.046 0.186 D×R 0.331 0.000 D×R 0.405 0.001 Cons. 0.107 0.000 Cons. 0.127 0.000 The sum of the coefficients on R and D×R 0.352 0.000
0.451 0.001
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.371
p value for the Ho: the coefficient on R is equal for the two regressions 0.042
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.179
See the Appendix for all variable definitions. The reported p values are clustered by country.
23
Table 4 Regression Results by Country Legal Enforcement for Non-Financial Firms and Financial Firms Separately
Panel A. Regression results for non-financial firms
Strong legal enforcement countries (N=1,538)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.046 0.007 D -0.047 0.008 R 0.027 0.046 R 0.028 0.014 D×R 0.199 0.000 D×R 0.200 0.001 Cons. 0.056 0.000 Cons. 0.068 0.000 The sum of the coefficients on R and D×R 0.225 0.001
0.228 0.000
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.944
p value for the Ho: the coefficient on R is equal for the two regressions 0.673
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.887
24
Table 4 Panel A. (cont.)
Weak legal enforcement countries (N=573)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.011 0.554 D -0.012 0.577 R 0.074 0.000 R 0.069 0.000 D×R 0.351 0.008 D×R 0.278 0.211 Cons. 0.037 0.000 Cons. 0.045 0.004 The sum of the coefficients on R and D×R 0.425 0.019
0.347 0.146
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.614
p value for the Ho: the coefficient on R is equal for the two regressions 0.762
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.547
25
Panel B. Regression results for financial firms
Strong legal enforcement countries (N=358)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.047 0.204 D -0.044 0.419 R 0.048 0.000 R 0.084 0.000 D×R 0.352 0.000 D×R 0.390 0.016 Cons. 0.105 0.000 Cons. 0.119 0.000 The sum of the coefficients on R and D×R 0.401 0.000
0.474 0.000
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.658
p value for the Ho: the coefficient on R is equal for the two regressions 0.004
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.328
26
Table 4 Panel B. (cont.)
Weak legal enforcement countries (N=122)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.125 0.041 D -0.263 0.000 R -0.073 0.143 R -0.082 0.118 D×R 0.579 0.507 D×R -2.031 0.142 Cons. 0.118 0.001 Cons. 0.154 0.000 The sum of the coefficients on R and D×R 0.506 0.577
-2.114 0.176
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.000
p value for the Ho: the coefficient on R is equal for the two regressions 0.264
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.000 Following DeFond and Hung (2004), a country is classified as a strong (weak) legal enforcement country if the country’s score of law enforcement ratings reported in La Porta et al. (1998) is above (below) the median. See the Appendix for all variable definitions. The reported p values are clustered by country.
27
Table 5 Regression Results by Country Legal Enforcement for Non-Financial Firms and Financial Firms Separately: The sample is limited to countries whose local accounting standards and IFRS differ
significantly Panel A. Regression results for non-financial firms
Strong legal enforcement countries (N=547)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.054 0.243 D -0.062 0.185 R 0.057 0.102 R 0.053 0.092 D×R 0.260 0.000 D×R 0.215 0.001 Cons. 0.074 0.001 Cons. 0.083 0.000 The sum of the coefficients on R and D×R 0.318 0.001
0.267 0.003
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.139
p value for the Ho: the coefficient on R is equal for the two regressions 0.414
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.074
28
Table 5 Panel A. (cont.)
Weak legal enforcement countries (N=540)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.007 0.718 D -0.009 0.699 R 0.073 0.000 R 0.068 0.000 D×R 0.415 0.000 D×R 0.323 0.172 Cons. 0.039 0.000 Cons. 0.046 0.004 The sum of the coefficients on R and D×R 0.488 0.009
0.391 0.139
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.592
p value for the Ho: the coefficient on R is equal for the two regressions 0.774
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.533
29
Panel B. Regression results for financial firms
Strong legal enforcement countries (N=124)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D 0.057 0.212 D 0.097 0.188 R 0.049 0.010 R 0.080 0.033 D×R 0.494 0.002 D×R 0.687 0.008 Cons. 0.104 0.000 Cons. 0.111 0.000 The sum of the coefficients on R and D×R 0.543 0.009
0.767 0.016
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.066
p value for the Ho: the coefficient on R is equal for the two regressions 0.121
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.014
30
Table 5 Panel B. (cont.)
Weak legal enforcement countries (N=117)
Dep. Var. = EPS_LOCAL
Dep. Var. = EPS_IFRS
Coeff. p value Coeff. p value D -0.125 0.045 D -0.258 0.000 R -0.074 0.140 R -0.084 0.115 D×R 0.583 0.518 D×R -2.046 0.136 Cons. 0.117 0.002 Cons. 0.154 0.000 The sum of the coefficients on R and D×R 0.510 0.591
-2.130 0.180
p value for the Ho: the coefficient on D×R is equal for the two regressions 0.000
p value for the Ho: the coefficient on R is equal for the two regressions 0.256
p value for the Ho: the sum of the coefficients on R and D×R is equal for the two regressions 0.000 Following Bae et al. (2008), we delete the following countries whose local accounting standards don't differ significantly from IFRS: UK, Ireland, Netherlands, and Norway. See the Appendix for all variable definitions. The reported p values are clustered by country.
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