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Effects of IFRS mandatory adoption and country-specific factors on
accounting quality: evidence from Italy
Paola Paglietti
Department of Economics and Business Studies, University of Cagliari
Viale S. Ignazio 17, I-09123, Cagliari, Italy
Tel.: +39 0706753352
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Effects of IFRS mandatory adoption and country-specific factors on accounting quality:
evidence from Italy
ABSTRACT
This paper studies the impact of the IFRS mandatory adoption in a typical code-law European
country such as Italy. It aims at investigating how and whether the accounting information
quality changes following IFRS implementation. The focus is on value relevance which is
considered as one of the basic attributes of accounting quality. An empirical analysis is
performed on a representative sample of 522 firm-year observations concerning Italian listed
companies observed from 2001 to 2006. Data are analyzed by contrasting the pre-adoption
period (2001-2004) with the post-adoption one (2005-2006) to test for a systematic change in
value relevance induced by IFRS. Likewise, a sectoral analysis is performed to investigate if
accounting quality differs with respect to the macro-sector of activity. Results confirm the
expected overall increase in the value relevance under IFRS, particularly for firms operating in
the Finance and Services sectors. The research also documents changes in Italy’s countryspecific factors in the period surrounding IFRS adoption that may contribute to an improvement
in accounting quality. Such a concern is consistent with previous literature supporting the idea
that accounting quality does not depend only on the high quality of accounting standards, but it is
also a function of the country’s complex institutional setting.
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INTRODUCTION
In 2002, the European Union (EU) Parliament required all companies listed in the EU to adopt
the International Financial Reporting Standards (IFRS) issued by the International Accounting
Standards Board (IASB) for the preparation of their consolidated financial statements, from 1
January 2005 onwards1. The application of IFRS in individual company accounts and in the
consolidated accounts of non-listed companies was left as an option to member states. One of
IASB’s main goals is to develop a single set of accounting standards that, if followed, require
companies to report “high quality, transparent and comparable information in financial
statements”2. Evidence of higher accounting quality has been interpreted by Barth et al. (2008)
for the IFRS-adopting firms which exhibit less earnings management, more timely loss
recognition and more value relevance of earnings, based on a worldwide sample. Such concerns
lead to the expectation that the IFRS mandatory adoption in Europe should determine important
economic consequences for financial reporting. However, as Ball (2006) points out, in Europe
most political and economic influences on financial reporting practice remain local despite the
IFRS adoption. Thus, an exogenously imposed set of accounting standards, such as IFRS with
their common-law view of financial statement, does not necessarily influence per se financial
reporting quality, particularly in countries with a code-law institutional setting. Along the same
line, Soderstrom and Sun (2007) claim that cross-country differences in accounting quality are
likely to remain after the IFRS implementation because accounting quality is affected by the
country’s legal and political system, as well as by the incentives to financial reporting.
Taking all these considerations into account the present study focuses on Italy, a European
country that has been experiencing the IFRS mandatory adoption. It aims at investigating the
effect of the IFRS adoption and the country-specific factors on the accounting information
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quality. Since accounting quality is a broad concept with multiple dimensions (Burgstahler et al.,
2006), this study focuses on the value relevance which is considered one of the basic attributes of
accounting quality (Francis et al., 2004). Value relevance expresses the ability of financial
statement information to capture or summarize information that affects share values and it is
indicated by the statistical association between accounting information and market prices or
returns (Francis and Schipper, 1999, pp. 326-327).
By using consolidated financial statement data from a sample of 87 Italian listed companies
observed from 2001 to 2006, the value relevance in Italy is investigated to answer the first
research question: Does the value relevance of earnings and book value of equity systematically
change in Italy with the mandatory adoption of IFRS? For this purpose, the combined, relative
and incremental value relevance of book value of equity and earnings with respect to share prices
are examined. In addition, the value relevance of earnings levels and earnings changes is
investigated for the period 2002-05 using the return regression model.
Data are also analyzed on a sectoral basis to answer the second research question: 2) How does
the IFRS adoption impact the value relevance in the different sectors? To respond to this the
same set of association studies are performed separately for firms operating in the Finance,
Industry and Services macro-sectors to study cross-sectional differences in the value relevance.
This analysis documents that such a sectoral classification is an important discriminating factor
that influences the overall level of accounting information quality. The same conclusion can not
be drawn for other factors, like the sign of reported earnings and market capitalization, as
documented in a sensitivity test (see section 5.2). Results of the empirical analysis suggest that,
in most cases, value relevance increases following the IFRS adoption.
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The research focuses on Italy because its domestic accounting standards, which have been
influenced by a code-law institutional setting, present a large deviation from IFRS. They have
been driven by emphasis on the financial statement conformity with tax regulations,
conservatism, and broad-stakeholders orientation. Accordingly, it is expected that the adoption of
IFRS should be relatively more beneficial for investors. Moreover, differently from most
Continental European countries, the Italian legislator required the use of IFRS also in individual
accounts of listed companies. Such an extension should strengthen IFRS enforcement by making
accounting numbers of consolidated financial statements more reliable for empirical analysis.
The country has also been experiencing important changes in its country-specific factors that
could contribute in strengthening the IFRS implementation therefore positively influencing the
accounting information quality. In particular, it is documented that domestic events that
happened just before and along the IFRS implementation are likely to contribute to increase
value relevance in Italy in these years (see section 3.2).
Prior research reports positive impact of the voluntary IFRS adoption on accounting quality
(Soderstrom and Sun, 2007); whereas, little evidence is reported when the adoption is
compulsory. This study tries to contribute to the international accounting research focusing on a
country experiencing the mandatory adoption of IFRS. Research results may provide insights
about properties of IFRS versus national standards in the current EU setting. They may also
contribute to the literature examining the quality of IFRS-based accounting amounts.
The rest of the paper is organized as follows. Section 2 describes the prior research. Section 3
documents the transition to IFRS in Italy and discusses the changes in the country-specific
factors. Section 4 deals with the research design, the sampling information and the hypothesis
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development. Section 5 illustrates the results of both the empirical analysis and of the sensitivity
test. The final section presents some concluding remarks.
PRIOR RESEARCH
A part of the value relevance studies compare the explanatory power of earnings and book value
across countries (Ali and Hwang (2000) & Arce and Mora (2002) & Harris et al. (1994) & Joos
and Lang (1994) & King and Langli (1998)). They also document the value relevance of
accounting numbers in developing countries (Al-Sehali and Spear (2004) & Chen and Wang
(2004) & Davies-Friday et al. (2006) & Eccher and Healy (2003) & Prather-Kinsey (2006)) and
in transition economies (Gornik-Tomaszewski and Jermakovicz (2001) & Hellström (2006)).
This paper takes origin from that stream of research aimed at comparing the value relevance of
earnings and book value generated by different sets of accounting standards. Some of the
research efforts in this field concern non-US firms listing on New York Stock Exchange (Amir et
al. (1993) & Harris and Muller (1999) & Rees and Elgers (1997)). Other more recent studies aim
to provide findings which have implications for policymakers on recent moves towards replacing
local GAAP with IFRS for non-European countries (Bao and Chow (1999) & El Shami and Al
Qenae (2005) & El Shami and Kayed (2005) & Sami and Zhou (2004)).
The present study tries to contribute to the international debate about replacing local GAAP with
IFRS in Continental Europe. Most of the related literature is concentrated on Germany. Bartov et
al. (2005) observe from 1998 to 2000 a sample of 417 firms traded on the German Stock
Exchange. They compare the value relevance of earnings produced under three accounting
regimes: German GAAP, US-GAAP and IFRS, since firms traded on the German Neuer Markt
were required to choose only between US-GAAP and IFRS. Their primary finding is a higher
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value relevance for earnings prepared under either IFRS or US-GAAP in comparison to those
prepared under German GAAP. These results hold for profit observations only. A comparison
between value relevance of earnings produced under US-GAAP and IFRS results in no
significant difference. Later on, Hung and Subramanyam (2007) compare the financial statement
effects of using IFRS to those using German GAAP for a sample of German companies that
elected to adopt IFRS. They also examine these companies’ restatements of prior years
accounting numbers in the adoption year. Results show that the adjustments for book value
between the two reporting systems are value relevant, but not that for earnings. No difference in
value relevance of book value and earnings under IFRS and German GAAP emerges. In
addition, total assets and book value are significantly higher under IFRS and there is a higher
variability in book value and earnings under IFRS. Finally, they find that IFRS adopters exhibit
larger loss provisions.
It is not easy to draw reliable conclusions about the effects of IFRS adoption in Germany
comparing the results of these two studies, since they reach somewhat conflicting findings. The
main reasons are probably attributable to the bias deriving from the analysis of self-selected
firms due to the IFRS voluntary adoption phase as well as to a possible sample heterogeneity.
Some distinguishing elements of the present study should enforce its results with respect to other
similar research. It is well known that by limiting the analysis to a single country it correctly
presumes that the pricing process is the same for all the observed firms. From a methodological
point of view, this concern would strengthen findings deriving from a single-country analysis (as
for example Bartov et al., 2005) over cross-country comparisons (as, for example, Arce and
Mora, 2002). Nonetheless, Eccher and Healy (2003) provide evidence that prices may reflect
investor clienteles and can differ across firms. Controlling for macro-sectors allows the
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investigation of value relevance for firms with similar characteristics and should reduce such a
bias. In addition, a representative sample of companies is observed longitudinally in time, so that
the analysis is carried out on a sample drawn according to two stratification factors, market
capitalization and sector classification, to properly accomplish statistical representation. Only a
small proportion of firms originally sampled have been replaced due to particular events
(mergers, acquisitions, de-listings, etc.), so that the survivorship bias problem is minimized.
Finally, results do not suffer from possible self-selection bias as the study concerns a mandatory
adoption of IFRS instead of a voluntary one.
THE ITALIAN FRAMEWORK
The transition to IFRS in Italy
Italy did not take any clear position towards international accounting standards before the
Regulation (EC) No. 1606/2002. During the mid-1990s several EU Member States allowed listed
companies to prepare their consolidated accounts in accordance with IFRS or US-GAAP instead
of national rules to respond to the “demand pull” for international accounting (Van Hulle, 2004,
p. 361). The number of companies taking advantage of the new financial reporting rules varied
among the countries. Aisbitt (2003) reports 58 companies using IFRS in Germany in 2000, 12 in
Austria, 2 in Belgium and Finland, but zero in Italy, France and Luxemburg. Actually, Italy
passed a law3 in 1998 allowing listed companies to use “internationally recognized” accounting
standards for consolidation, but the implementation decree has never been issued.
The main motivation for the lack of interest in international accounting standards is that the
Italian economic environment was characterized by extensive corporate ownership
concentration, minor importance of the equity market, great importance of long term debts
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provided by banks. In this context, accounting practices were mainly aimed to safeguard capital
maintenance in the interest of corporate stakeholders, particularly creditors, justifying
conservative accounting practices. Also, financial statements served as the base for the
computation of income taxes. In contrast, international standards like IFRS are intended to assure
fair presentation of the company’s financial position and performance in order to provide
decision-useful information to a wide range of users, with particular reference to investors
(IASC, 1989, para. 10-12).
Only with the EU commitment adoption Italian listed companies started experiencing the use of
IFRS. In accordance with the recommendation of the Committee of European Securities
Regulation (CESR) dated December 30, 2003, they presented the information required by IFRS
1 in the 2005 quarterly reports to facilitate the transition to the new accounting standards4.
In 2005, the government enforced the IFRS implementation options established by the
Regulation (EC) No. 1606/2002 by issuing the Legislative Decree No. 38/2005. It prescribes that
all listed companies and companies operating in the financial sector such as banks, supervised
financial companies and companies issuing financial instruments widely distributed among the
public, have to apply IFRS in their consolidated accounts from 2005 onwards and in their
individual accounts from 2006 or, optionally, from 2005. In addition, the application of the new
standards is also allowed to other non-listed companies; they are free to adopt IFRS for both
individual and groups accounts5. Only companies presenting abbreviated accounts are excluded.
As for the individual account, IFRS have been authorized to give homogeneity to the financial
statements (OIC, 2005). As Haller and Eierle (2004, p. 35) argue, the application of uniform
accounting principles and rules for individual and group accounts ease the preparation of group
accounts and improve the consistency of the internal management and control system. Indeed,
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the decision of making full implementation of IFRS is particularly interesting and unexpected
since Italy is characterized by regulatory rigidity and a legalistic outlook. It could be arguable
that after a series of company scandals (e.g. Parmalat) some governments may want to distance
themselves from accounting standard setting (Sellhorn and Gornik-Tomaszewski, 2006, p. 199).
Finally, to guarantee the same treatment to IFRS adoption and non-adoption firms, the
Legislative Decree No. 38/2005 modified both the civil and fiscal law. It is worth mentioning
that the legislator inserted in the Civil Code a provision prohibiting the distribution of most of
the gains derived by fair value measurements. Also, fiscal neutrality of IFRS revaluations that
generate net equity increase were established.
Country-specific factors affecting the value relevance of accounting information
This study supports the idea that ongoing changes in some of Italy’s country-specific factors
could affect the degree to which firms comply with IFRS therefore positively influencing the
value relevance of accounting information. While cross-country studies quantify the relation
between country-specific factors and the value relevance of accounting numbers (e.g. Alford et
al. (1993) & Ali and Hwang (2000) & Ball et al. (2000)), studies investigating individual
countries describe these factors in a qualitative manner; that is, by indicating whether they
increase or decrease the value relevance and under which conditions (Hellström, 2006). This is
the case of the present study focusing on six country-specific factors, interacting with each other,
suggested by prior research on international differences in financial reporting practice, namely:
legal system, financial system, equity market, ownership concentration, auditing and tax system.
La Porta et al. (1997) repot that countries with poorer legal protection have smaller and narrower
capital markets. In particular, French-civil-law countries have both the weakest investor
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protections and the least developed capital markets in comparison to common law countries.
These are the characteristics of Italy which is classified by La Porta et al. (1998) as a Frenchcivil-law country with some German influence. Previous studies show that accounting quality is
higher in countries with a common law origin and high protection of shareholders rights (e.g. Ali
and Hwang (2000) & Ball et al. (2000) & Leuz et al. (2003)). In this respect, the legal system in
Italy is expected to negatively affect value relevance.
As to the main sources for corporate funding, Italy has been classified as a bank-oriented country
(Demirguc-Kunt and Levine, 2001). The literature (Berglof, 1990) defines the bank-oriented
financial system as characterized by close links between firms and banks, which supply most of
their capital needs. Banks are the principal financing agent and also play an important role as
shareholders. Actually, Italian banks do not have a large share in companies ownership but,
being the companies main capital suppliers they have easy access to firms’ financial
information6. Thus, the demand for published financial information reduces. This feature of the
Italian financial system can negatively affect value relevance. Ali and Hwang (2000) find that
value relevance is lower for countries with bank-oriented financial systems as opposed to
market-oriented ones.
Despite probable limitations on value relevance related to the legal and financial systems,
benefits could derive from some events which are starting to change the Italian economic
scenario. The recent and ongoing development of the Italian equity market is expected to
positively affect value relevance. The demand for accounting information from market
participants provides incentives for firm managers to increase the quality of financial reporting
so to facilitate current and potential shareholders’ investment decisions. This effect is supported
by Nobes’s (1998) suggestion that, unless a country is culturally dominated by another, its
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financial system is the main driver of its financial reporting practices. Table 1 documents the
growth of the Italian Stock Exchange during the last six years in terms of number of traded
shares (deriving also from IPOs and takeover bids), market capitalization, trading activity, and so
on. This sizable enlargement is also attributable to the broad privatization process. The country
experienced public offerings for about 125 million Euro, that was the second one among OCSE
countries and the first one in Europe. Aganin and Volpin (2003) reported that the stock market
capitalization grew to 70 percent of the gross national product in 2000 (in the 1980s it was lower
than 8%) and that this increase was largely due to the listing of large corporations. Strikingly,
this development of the stock market is not supported by foreign investment. Tyrral et al. (2007,
p. 92) argue that IFRS are supposed to provide greater transparency in financial statements,
which should attract increased Foreign Direct Investment (FDI). This presumption is not
supported by evidence in Italy, where there is no consistent increase in inward FDI during the
recent years whereas outward FDI increases, as documented in Table 1.
The reduced-size of the Italian equity market is historically associated with a lowly diffused
ownership structure (La Porta et al., 1998) which has probably generated a weak demand for
financial reporting. The ownership and control structure of Italian listed companies presents a
high level of concentration and a limited number of shareholders, linked by either family ties or
agreements of a contractual nature (i.e. shareholders’ agreements), who are willing and able to
wield power over the corporation (Melis, 2005, p. 479). Nevertheless, recent figures (Table 1)
highlight that the concentration of shares owned by the largest shareholder decreases from 2001
(42.2%) to 2006 (27.5%) and, consequently, the same percentages concerning the other majority
shareholders and the market increase from 9.2% to 15.2% and from 48.6% to 57.3%
respectively. This change is supposed to positively influence value relevance since it implies that
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a growing number of investors are likely to increase the demand for high quality accounting
information, forcing companies in this way to appropriately apply IFRS. Such an increase in the
percentage of shares owned by the market has probably also been favoured by the Italian
government’s efforts towards the improvement of the minority shareholders’ protection. It led to
the introduction in 1998 of the “Draghi reform” and the reform of the governing saving in 2005
(Law No 262/2005). Along the same line, the Italian Stock Exchange introduced in 1999 the
“Preda code”, a code of ethics aimed at promoting better corporate governance practices for
listening firms.
The auditing service is an important enforcement mechanism affecting the quality of accounting
information. Francis and Wang (2006) document that earnings quality increases for firms with
Big 4 auditors7, based on an international broad sample. They also report the market share of the
Big 4 auditors in Italy is 93%. This is the highest percentage in Europe and would positively
affect the statistical association between stock prices and accounting numbers. Nevertheless,
Italy is the only European country to have made auditor rotation compulsory. The “Draghi
reform” requires that the auditing firm in Italy is appointed for three years by the shareholders’
meeting following the favourable opinion of the board of statutory auditors. After three
appointments (i.e. nine years) the law requires the company to rotate its lead audit firm. It is not
clear how this mandatory rotation could affect the value relevance of accounting information: a
Bocconi University report (SDA Bocconi, 2002) highlights that audit firm rotation is detrimental
to audit quality but has a positive effect on improving public confidence in the corporate sector.
It concludes that auditor rotation produces a negative net effect on the shareholder’s value.
Finally, the divergence between financial and tax accounting in Italy is supposed to positively
influence value relevance. The literature supports this conjecture with some empirical evidence
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(Ali and Hwang (2000) & Joos and Lang (1994)). The strong relationships between accounting
and taxation in Italy were reduced introducing the Legislative Decree No. 6/2003. It eliminated
the commercial rule allowing fiscal items in the accounts with related disclosure in the notes.
Also, the Legislative Decree No. 344/2003 eliminated the compulsory inclusion of some
expenses in the income statement in order to obtain their deduction from tax accounts. These
expenses can now be directly deducted from the annual tax return.
Summarizing, Italy has been experiencing several structural changes affecting its countryspecific factors that can influence the IFRS adoption effectiveness with respect to the value
relevance of accounting information. In particular, the recent growth of the equity market
generated by internal factors (privatizations, IPOs, etc.), the recent decrease in the ownership
concentration, the Big 4 auditing concentration and the divergence between financial and tax
accounting are all factors that should favour an increase in the statistical association between
IFRS accounting information and stock prices.
RESEARCH DESIGN
Sample selection
The empirical analysis is carried out on a sample of 522 firm-year observations concerning a
cohort of 87 Italian companies trading their common shares on the Milan Stock Exchange (MSE)
from 2001-2006. Data of published consolidated financial statements as well as market share
prices for the period 2001-2006 were collected from the MSE website (www.borsaitalia.it).
All the accounting data expressed in Euro were submitted in accordance with I-GAAP8 up to
2004 and in accordance with IFRS from 2005 onwards. Among the 522 firm-year observations,
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348 derive from I-GAAP financial statements and 174 from IFRS ones. Market share prices are
referred to the end of the first four-month period.
A stratified sampling scheme is used to accomplish statistical representation with respect to the
macro sectors of activity (Finance, Industry and Services)9 and the market capitalization. A
company is selected if, following its inclusion in the sample: a) the sampling weight of its
macro-sector does not exceed that of the corresponding macro-sector of the population for more
than  1.50% (see Table 2); b) the null hypothesis of the Kolmogorov-Smirnov (KS) test
comparing the empirical distribution of the macro-sector market capitalization within the sample
with that characterizing the population is not rejected10 (see Figure 1).
In order to preserve homogeneity of the sample along time, accounting data concerning the set of
selected firms were collected for the years from 2001 to 2006. Since sampling was performed
during the first half of 2005, a small number of replacements have been made in the sample since
accounting data for some companies were no longer available because of mergers and
acquisitions. Companies of the same magnitude (in terms of net equity) and operating in the
same macro-sector of the replaced ones were selected11.
Table 3 presents descriptive statistics and correlations for the sampling observations. Results
reveal that earnings and book value are positively correlated with price and with each other over
the entire period and that the correlation among the three variables increases after the adoption of
IFRS. It is worth noticing that this increase is particularly large for the correlations between
earnings and the other two variables.
Hypothesis development
This study investigates the value relevance of I-GAAP and IFRS book value and earnings
assuming that IFRS produce higher quality accounting information for investors in comparison
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to I-GAAP. This assumption derives from the different approach to the financial statement used
by these two accounting regimes. Particularly, IFRS interpret the financial statement in a
perspective way: the use of fair value measurements should reveal better the present company
economic state and its future performances. As Barth et al. (2008, p. 5) argue, accounting
amounts that reflect better a firm’s underlying economics provide investors with information to
aid them in making decisions. In this respect, IFRS can be considered more investor-oriented. On
the contrary, I-GAAP are primarily oriented towards stakeholders, with special attention to
creditors. Thus, they tend to prefer conservative accounting practices in order to preserve capital
maintenance during the time. These considerations introduce the first research question: Does the
value relevance of earnings and book value systematically change in Italy with the mandatory
adoption of IFRS? To answer this question the combined, relative and incremental value
relevance analysis are carried out using price and return regression models.
The first expected result is that the combined value relevance of book value and earnings is
higher under IFRS. To assess this result, the Ohlson (1995) model assuming a linear relationship
between price, book value per share and earnings per share is used (see Easton et al., 1993). The
resulting price-levels regression is as follows:
Pit   0  1BVit   2 Eit   it
where:
Pit is the price of a share for firm i four months after the fiscal year-end t;
BVit is the book value per share of firm i at the end of the year t12;
Eit is the earnings per share for firm i for time period t-1 to t;
εit is the other value-relevant information of firm i for year t orthogonal to Eit and BVit.
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The second expected result is that the increase in the relative value relevance of earnings
following the transition to IFRS is higher than the increase in the relative value relevance of
book value. This is because under IFRS earnings should be more informative (Ball, 2006) and
thus should be able to describe better firms underlying economics. To determine the explanatory
power that Eit and BVit have for prices individually, equation (1) can be split into two models in
order to consider the relative value relevance of BVit and Eit respectively13:
Pit  0  1BVit   it
(2)
Pit   0  1Eit   it
(3)
The relative value relevance of Eit and BVit is measured by the adjusted R2’s of the corresponding
models (2) and (3). Comparing the value of adjusted R2 deriving from model (2) with that of
model (3), it is possible to understand if BVit is more value relevant than Eit, or vice versa.
Following similar approaches (see, for example, Arce and Mora, 2002), this study applies the
Vuong test14 to evaluate the magnitude of the differences between these adjusted R2s.
The empirical analysis also investigates if book value and earnings provide different additional
information to investors by measuring their incremental explanatory power. Denoting the
adjusted R2s coefficients from equations (1) to (3) as R21 , R22  and R23 respectively, the total
explanatory power of the model (1) is decomposed into three parts: i) the incremental
2
explanatory power of book value: RBV
 R21  R23 ; ii) the incremental explanatory power of
earnings: RE2  R21  R22 ; iii) the explanatory power common to both earnings and book value:
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2
RC2  R21   RBV
 RE2  15. The third expected result is that, under IFRS, the incremental value
relevance of earnings increases whereas that of book value decreases.
Furthermore, the research considers the strength of the relationship between earnings and stock
returns as a proxy for value relevance. To evaluate whether the ability of earnings levels and
earnings changes in explaining stock returns improves under IFRS (fourth expected result), the
return regression model proposed by Easton and Harris (1991) is considered:
Rit   0   1  Eit Pit 1    2  Eit Pit 1    it
(4)
where:
Rit is the dividend adjusted stock market return of firm i four months after the fiscal yearend t;
Eit / Pit-1 is the earnings per share of year t deflated by the stock price in year t-1 observed
for firm i four months after the fiscal-year end t-1;
∆Eit / Pit-1 is the change in the earnings per share from years t-1 to t deflated by the stock
price in year t-1 observed for firm i four months after the fiscal-year end t-1.
The value relevance of both earnings and the deflated change in the earnings are measured by the
adjusted R2 of model (4). Again, following the R 2 decomposition introduced for model (1),
incremental value relevance of Eit / Pit-1 and ∆Eit / Pit-1 can be measured in the same way
decomposing the R 2 of model (4). Generally, model (4) is considered to be less sensitive to scale
effects compared to model (1) 16.
When estimating price and return regression models, pooled data of the pre-adoption period
(2001-2004) are contrasted with those of the post-adoption one (2005-2006). In this respect, the
Chow (1960) test17 is used to examine for differences in the value relevance in the two periods.
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This test is applied to compare regression results obtained from models (1) to (4). In addition, to
enforce the idea that changes in value relevance are systematic and do not depend on a particular
year, the association between accounting numbers and stock market data is preliminarily
measured on a yearly basis.
Finally, this study assumes that the magnitude of the increase in the value relevance of
accounting information following the IFRS adoption could vary with respect to the activity
sector. Thus, the second research question is: How does the IFRS adoption impact the value
relevance in the different sectors? A sectoral analysis is carried out to investigate how value
relevance changes in the three different macro-sectors (Finance, Industry and Services) from the
pre-adoption period to the post-adoption one. Models (1) to (4) are applied separately for each
macro-sector and for the two different periods. Previous studies (Barth, 1994 & Barth et al.
(1996) & Eccher et al. (1996)) document that fair value disclosure made by banks are value
relevant and that banks’ shareholders value this information. In view of that, the fifth expected
result is that value relevance increases particularly in the Finance sector.
EMPIRICAL RESULTS AND INFERENCES
Value relevance of earnings and book value under IFRS and I-GAAP
This section summarizes the results obtained when applying models (1) to (4) to the observed
sample of Italian firms in order to evaluate the value relevance of earnings and book value during
the period 2001-06. When estimating each model, data have been winsorized to the 5% level to
mitigate the effect of outliers. Despite the outlier elimination, the number of observations used to
estimate each model does not violate any of the criteria proposed in the literature for determining
the minimum sample size required to conduct a multiple regression analysis (see, among others,
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Algina et al. (2002) & Cohen and Cohen (1983) & Green (1991) & Nunnally and Bernstein
(1994)). In addition, consistent with prior research (such as Collins et al.,1997), firms with
negative book value (under either I-GAAP or IFRS) are deleted.
Yearly regressions
Table 4 reports the results of the models applied on annual data, distinguishing those deriving
from price regressions (i.e., models (1) to (3), Panel A) from those deriving from return
regressions (i.e., model (4), Panel B).
Model (1) provides a measurement of the combined value relevance. Its estimated coefficients
and adjusted R2s are reported in the first block of Table 4. Results provide evidence of the
expected changes in the relevance of accounting information for the Italian listed companies. The
R21 coefficient reaches its maximum value (0.70) in 2006 and the estimated coefficients
obtained in 2005 and 2006 under IFRS differ from the corresponding ones obtained in previous
years under I-GAAP. Overall, these models seem to provide evidence about the occurrence of
the first expected result: the combined value relevance of book value and earnings is higher
under IFRS.
The second block of Table 4 shows the results of the relative value relevance measured by
models (2) and (3). BVit explains 44% of the market price changes in 2005. This value is not so
different compared to previous years. The predictive ability of BVit increases to 66% in 2006.
Thus, it seems that the IFRS adoption leaves the relative value relevance of BVit unchanged in
2005 and causes an increase starting from 2006. Instead, Eit alone explains 62% of market price
changes in 2005 and 58% in 2006. These figures highlight a consistent increase in the relative
value relevance of Eit compared to the I-GAAP period. These findings lead to the second
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expected result: the increase in the relative value relevance of earnings following the transition
to IFRS is higher than that of book value. In each year, a comparison of the relative value
relevance of Eit and BVit is made by means of the R2s as well as of the Vuong test. In 2005, the
Vuong-Z statistic is significantly negative, indicating that Eit is relatively more relevant than BVit.
In previous years the evidence is exactly the opposite: the Z-statistic is always positive,
confirming the superiority of BVit in terms of relative value relevance under I-GAAP, even if
only in 2003 this value is significant at conventional levels (0 ≤ p ≤ 1%). These results show that
BVit is relatively more relevant than Eit under I-GAAP but not under IFRS, whereas a clear
superiority of Eit over BVit can not be found under IFRS.
2
As for the incremental value relevance, values of RBV
and RE2 reported in the last two columns
of Table 4 seem to partially confirm the third expected result. The incremental value relevance of
2
book value reduces when moving from I-GAAP to IFRS: values of RBV
in 2005 and 2006 are
considerably low if compared to those of the period 2001-2004. Whereas, the incremental value
relevance of earnings increases to 0.18 in 2005, but in 2006 it does not differ so much compared
2
to previous years. This issue would require further investigation, although the decrease of RBV
under IFRS suggests a reduction of the incremental information provided to investors by the
balance sheet.
Panel B of Table 4 reports the results of the return regression. Available data allows I-GAAP
accounting numbers to be used to estimate models from 2002 to 2004 and IFRS ones for the
period 2005-200618. Results show that the adjusted R2 of model (4) reaches its maximum value
in 2006 (0.13). This analysis is in line with the expectation that value relevance of both earnings
levels and earnings changes increases under IFRS (fourth expected result) and suggests that
earnings levels play a prominent role in explaining stock returns. Under I-GAAP, the regression
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coefficients are often not significant. Despite the fact that the goodness of fit of return regression
models is considerably lower than the one provided by price regression ones, these results can be
considered as consistent with previous literature19.
Pooled regressions
Table 5 shows a comparison among the results of the models (1) to (4) for the I-GAAP data
(2001-2004) and for the IFRS data (2005-2006).
Price regression results in Panel A suggest that IFRS adoption increases the combined and the
relative value relevance of accounting information, since R21 , R22  and R23 under IFRS are
higher than those under I-GAAP. These findings enforces the conclusions drawn from yearly
regressions and confirms the prediction that the IFRS adoption causes an increase in the
combined value relevance and that the increase in the relative value relevance is more
pronounced for earnings (from 11% to 63%) than for book value (from 39% to 49%).
Nevertheless, comparing the results of models (2) and (3) in each period, adjusted R2s and the
Vuong test definitively indicate that Eit (BVit) is relatively more relevant that BVit (Eit) under
IFRS (I-GAAP). The increase in the incremental value relevance of earnings that partially
emerged from yearly regressions is definitively confirmed in the pooled ones: results show that
the incremental contribution to equity valuation of Eit (measured by RE2 ) increases from 2% to
2
16%, whereas that of BVit (measured by RBV
) even decreases to 3% from 31%. This would mean
that income statement information is starting to gain importance for investors’ valuation
mechanisms and that firms profitability is influencing investment decisions. The Chow tests
always reject the null hypothesis of no difference in value relevance between the pre-adoption
and the post-adoption periods. Overall, these findings suggest that the IFRS adoption induces
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systematic differences in the value relevance of accounting information in the post-adoption
period compared to the pre-adoption one.
Return regression outcomes on pooled data are reported in Panel B. They confirm the increase of
the statistical association between earnings and stock returns in the post-adoption period with
respect to the pre-adoption one, although such an increase is moderate (from 4% to 7%). Under
IFRS, earnings changes seem to be more relevant than under I-GAAP. Their incremental value
relevance equals 3% in the post-adoption period, being very close to that of earnings levels (4%).
Sectoral analysis
Table 6 reports the results of the pooled (price and return) regressions for the Finance, Industry
and Services sectors respectively.
The Finance sector includes insurance and banking companies as well as financial holdings, real
estate agencies and other financial services firms. For this set of companies, price regression
results (Panel A) highlight that the combined value relevance increases consistently ( R21
increases to .88 from .56) as well as the relative value relevance of Eit ( R23 increases to .88
from .53); the increase in the relative value relevance of BVit is less marked ( R22  increases to
.49 from .39). It is worth noticing that this sector is always characterized by a higher relative
value relevance of Eit in comparison to that of BVit. Under IFRS, the significance of the Vuong’s
Z-statistics provides strong evidence of this superiority. The latter is also confirmed by the
incremental value relevance: the contribution provided to equity valuation by Eit increases
2
consistently under IFRS ( RE2 increases to .39 from .17) whereas it reduces to zero for BVit ( RBV
decreases to zero from .04). Thus, financial companies clearly show that income statement
accounting information is more relevant for investors than that of the balance sheet. The IFRS
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adoption further intensifies this superiority, probably because financial companies make
extensive use of fair value measurements.
Different conclusions can be drawn for the Industry sector. It includes companies operating in
several homogeneous domains20. In this sector, the combined value relevance does not differ too
much when moving to IFRS from I-GAAP but changes are detectable in the relative value
relevance. Under I-GAAP, BVit is relatively more value relevant than Eit, as showed by the value
of the Vuong’s Z-statistic. This result probably depends on conservative practices and income
smoothing. Rather, under IFRS the superiority of BVit over Eit is not so marked, as the relative
value relevance of Eit increases considerably with the transition to IFRS ( R23 increases to .49
from .06) whereas that of BVit is unchanged. Incremental value relevance results coherently show
that BVit provides consistent additional information to equity valuation under I-GAAP, but not
2
under IFRS ( RBV
decreases to .09 from .48).
The Services sector is the less homogeneous one. It includes companies operating in the retailing
and publishing activities, utilities, transport and tourism as well as diversified services. As the
Finance sector, services companies experience a consistent increase in the combined value
relevance in the post-adoption period, together with an increase in the relative and incremental
value relevance of Eit. Somewhat surprisingly, the relative value relevance of BVit decreases.
Finally, the empirical analysis investigates if the value relevance of earnings levels and earnings
changes is sensitive to the activity sector (Panel B). The results are in line with the conclusions
drawn from the price regression models. IFRS adoption increases the value relevance of
earnings, particularly for the Finance and Services sectors, whose companies are probably the
major fair value users. Most of the total variation of returns in the Services sector is explained by
earnings levels. Whereas, earnings changes seem to play a role in the Finance sector, probably
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because in this sector earnings are most sensitive to the changes induced by the first use of IFRS
fair value accounting.
Overall, the results of the sectoral analysis indicate that IFRS adoption differently impact value
relevance in the three sectors, justifying the second research question. Moreover, the higher
increase in value relevance for financial companies confirms the fifth expected result: accounting
information provided by these companies is particularly relevant and informative for investors.
Instead, the lower increase of value relevance in the Industry sector probably depends on the
survival of conservative practices that reduce the effectiveness of the IFRS implementation
towards the disclosure of more useful information for investors.
Sensitivity analysis
This section presents a sensitivity test carried out to check for the presence of omitted important
variables. In particular, the proposed regression models do not consider the effect of the market
capitalization and the sign of reported earnings on the value relevance of accounting information.
Instead, the macro sector of activity is explicitly considered by partitioning the sample into three
disjoint sub-samples and by running separate regressions. In this respect, the aim of the
sensitivity test is twofold: it checks for the presence of other (omitted) influential variables and it
controls for the appropriateness of the sectoral analysis and of its reported findings.
The sensitivity test considers the residuals of model (1) and tests whether there are other
excluded variables that have some predictive ability as well as verifying whether the macrosector effectively has a different influence on the value relevance in the pre-adoption period and
in the post-adoption one. With this aim, the following regression model is considered:
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log  uit   1Mcapit  2 Finit  3 Indit  4 Servit  5 Sign.Eit   it
(5)
where log(|uit|) is the natural logarithm of the absolute value of the residuals21 of model (1) for
the firm i at time t; Mcapit is the market capitalization of firm i at the end of the year t; Finit, Indit
and Servit are dummy variables indicating if the firm i at time t belongs to the Finance, the
Industry or the Services sector, respectively. Sign.Eit is another dummy variable indicating if the
firm i at time t reported a positive earnings or not.
This model assumes that, the larger (and more significant) the regression coefficient associated
to a specific predictor is, the larger the explanatory power of the predictor itself in model (1) is.
Estimated regression coefficients are reported in Table 7, distinguishing also in this case the
results of the pre-adoption period from those of the post-adoption one. For both periods the
coefficients associated to Mcapit ( ˆ1 ) are close to zero and not significant. The same result holds
for Sign.Eit observing the value of the coefficient ˆ5 . This would mean these two factors have no
influence on the degree of value relevance of the Italian listed firms. Instead, values of the
coefficients associated to the macro-sectors ( ˆ2 to ˆ4 ) enforce the results presented in the
previous section, where it is demonstrated that IFRS adoption particularly increases the value
relevance of accounting information in the Finance and Services sectors.
CONCLUDING REMARKS
Following the recent IFRS mandatory adoption in Europe, this paper studies the consequences of
the IFRS-based financial statement presentation on the value relevance of accounting
information in Italy. Understanding the implication of IFRS adoption is an urgent need for
managers, investors and regulators, particularly in European countries with a predominant code-
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law institutional structures, since IFRS derive from a common-law view of financial reporting.
The aim of this research is to investigate how the mandatory adoption of IFRS has impacted the
value relevance of book value of equity and earnings, and to assess whether it increases the
quality of accounting information for investors. At the same time, since political and economic
forces profoundly affect reporting practice (Ball et al., 2003, p. 236), changes in the countryspecific factors that may favour the effectiveness of the IFRS implementation are also
considered.
Research results are coherent with the expectations. Price regression outcomes show that book
value of equity and earnings under IFRS are jointly and systematically more value relevant than
the corresponding I-GAAP amounts. In addition, it emerges that earnings increase their relative
value relevance more than book value of equity when moving to IFRS, despite higher relative
value relevance of book value of equity under I-GAAP. Return regression results also point out
that earnings levels and earnings changes increase their explanatory power during the IFRS
adoption period. Finally, the sectoral analysis highlights that IFRS adoption particularly
increases the value relevance for financial companies, and that firms operating in the Services
sector also experience a consistent increase in the quality of accounting information. On the
contrary, value relevance seems to remain almost unchanged for the Industry sector firms. The
sectoral analysis results suggest that, in each macro-sector, companies have probably been
experiencing a different degree of implementation of IFRS. Perhaps, financial reporting practice
in Industrial companies still remains rather conservative.
Nevertheless, as reported in literature, accounting quality does not solely depend on the high
quality of accounting standards. It is also a function of firms’ reporting incentives created by
market and political factors. In view of that, it was straightforward to consider that some recent
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changes in Italy’s country-specific factors could have favoured the effectiveness of the IFRS
adoption, therefore positively influencing accounting quality. Particularly, this study has
documented that the recent growth of the equity market, the ongoing company privatization
process, the decrease in ownership concentration as well as the divergence between accounting
and taxation are all factors that might have contributed to the increase in the value relevance of
accounting information in Italy.
This paper has tried to continue the research in the area of adopting IFRS. Of course, it is not
possible to draw definitive inferences from the results of this study since IFRS are observable
only for two years. However, the empirical analysis shows solid concerns in favour of the future
consolidation of these results that, as previously discussed, will also depend on the full
coordination between financial reporting practice and regulatory environment.
Notes
1
Regulation (EC) No. 1606/2002. Hereinafter, the term “IFRS” is used to refer to both the
accounting standards issued by the IASB and the International Accounting Standards (IAS),
issued by the International Accounting Standards Committee (IASC), which was the IASB’s
predecessor.
2
IASC Foundation Constitution, Part A, para. 2. Available at:
www.iasb.org/About+Us/About+the+Foundation/Constitution.htm.
3
Legislative Decree No. 58/1998, also known as “Draghi reform”.
4
In particular, they re-presented in one of the 2005 quarterly reports the balance sheet dated
January 1, 2004 as well as both the balance sheet and the income statement dated December 31,
2004 according to IFRS.
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IFRS are voluntary from 2005 onwards for the companies belonging to IFRS compliant groups
and for those that prepare consolidated accounts. For the individual accounts of the other
companies the government will communicate the term for using the new standards.
6
Bianchi and Bianco (2007, p. 19) document that the weighted average share of banks in Italian
listed companies is 4.7% in 2006, whereas it is 6.1% in Germany and 9.6% in Spain.
7
Deloitte & Touche, Ernst & Young, KPMG and Price Waterhouse Coopers.
8
The term “Generally Accepted Accounting Principles” (GAAP) is not formally defined in Italy.
Nevertheless, the term “Italian GAAP” is used throughout the paper and abbreviated with the
acronym I-GAAP to simplify terminology.
9
Italian listed firms are classified by the company managing the MSE trading activity (Borsa
Italiana S.p.a.) into three macro sectors: Industry, Services and Finance; each of them is further
classified into some activity sectors.
10
For details about the “two sample” Kolmogorov-Smirnov (KS) test see, among others, Kendall
and Stuart (1979).
11
The percentage of replaced firm-year observations is 3.64% (19 replacements over the 522
firm-year observations).
12
The book value per share has been adjusted by subtracting the earnings per share, in order to
avoid possible multicollinearity problems since the year-end book value contains the same
period’s earnings.
13
This decomposition has been derived theoretically by Theil (1971) and has been used in many
papers. See, among others, Arce and Mora (2002) & Collins et al. (1997).
14
This test is described in Vuong (1989), and is based on a likelihood ratio testing whether the
residual variances of both models are equal. The test statistic is standard normally distributed. Its
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positive value indicates the performance of model (2) is superior to that of model (3) (i.e., BVit is
relatively more value relevant than Eit ), and vice versa.
15
The same approach to incremental value relevance analysis has been used by Arce and Mora
(2002), Collins et al. (1997), Francis and Schipper (1999) and King and Langli (1998).
16
Basically, the use of the return regression model within the empirical analysis is made to take
into account the so called “scale effect” problem typically affecting price-levels regression. See
Easton (1998, p. 238) for details.
17
The Chow test is an econometric test of whether the coefficients in two linear regressions on
different data are equal.
18
To evaluate the earnings change from 2004 to 2005, the restatements of the 2004 income
statements presented in the 2005 quarterly reports are considered.
19
Harris et al. (1994), Joos and Lang (1994), Ball et al. (2000), among others, show that the
explanatory power of the return regression is substantially lower than that of the price levels.
20
These are Food, Automobile, Papers, Chemicals, Housing, Household and Electronic
Appliance, Plant & Machinery, Diversified Industrials, Mining, Metallurgic, Oils, Textiles,
Clothing and Accessories.
21
This logarithmic transformation of the residuals of model (1) is performed in order to make
their distribution more symmetrical and closer to the Gaussian one.
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Hung, M., & Subramanyam, K. R. (2007). Financial statement effects of adopting International
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Table 1: The evolution of equity market, ownership concentration and foreign direct investment
in Italy during the period 2001-2006.
Year
Equity market1
N. Listed companies
N. IPO
N. Takeover bids
Market Capitalization (% GDP)
Market Capitalization (€ mil.)
Overall trading activity (€ mil.)
Average daily trading activity (€
mil.)
Turnover velocity
Foreign Direct Investment2
FDI flows inward (€ mil.)
FDI flows outward (€ mil.)
Ownership Concentration3
% shares owned by the largest
shareholder
% shares owned by other
majority shareholders
% shares owned by market
2001
2002
2003
2004
2005
2006
294
295
279
278
282
311
18
14
10
10
19
46
20
22
32
19
23
15
47.4
35.4
36.5
41.8
47.7
52.8
592,319 457,992 487,446 580,881 676,606 778,501
658,042 633,659 679,017 732,592 954,796 1,145,650
2,611
93.3
2,515
120.7
2,695
143.6
2,851
137.1
3,730
151.9
4,510
157.5
11,037
15,926
10,854
12,778
12,250
6,769
12,549
14,375
14,904
29,605
12,996
31,185
42.2
40.7
33.5
32.7
28.6
27.5
9.2
48.6
8.0
51.2
11.6
54.9
13.0
54.3
15.5
55.9
15.2
57.3
Source: Italian Stock Exchange – Borsa Italiana (2007)
Source: United Nations Conference on Trade and Development – UNCTAD (2006). The data cover all types of
financial flows affecting equity capital, namely, listed voting stocks (shares), unlisted voting stocks, other nonvoting stocks (including preferred shares), and non-cash acquisitions of equity, such as through the provision of
capital equipment. They also include bonds and money market instruments, loans, financial leases and trade credits
as well as the purchase and sale of land and buildings in Italy /abroad by non-resident/resident enterprises and
individuals.
3
Source: Italian Stock Exchange Security and Exchange Commission – CONSOB: Commissione Nazionale per le
Società e la Borsa (2006).
1
2
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Table 2: Distribution of the firms included in the sample and in the entire set of Italian listed
companies, with respect to the main sectors and activity sectors.
N. of
N. of
Population
Sampling Weights
Activity Sector
listed
sample
weights
weights difference
firms
firms
Food
9
4.02%
3
3.45%
-0.57%
Automobile
7
3.13%
3
3.45%
0.32%
Papers
1
0.45%
0
0.00%
-0.45%
Chemicals
15
6.70%
6
6.90%
0.20%
Housing
10
4.46%
4
4.60%
0.13%
Household/Electronic Appliance
25
11.16%
9
10.34%
-0.82%
Plant/Machinery
9
4.02%
3
3.45%
-0.57%
Diversified Industrials
3
1.34%
1
1.15%
-0.19%
Mining/Metallurgic/Oils
4
1.79%
2
2.30%
0.51%
Textiles/Clothing/Accessories
18
8.04%
7
8.05%
0.01%
Industry
101
45.09%
38 43.68%
-1.41%
Insurance
11
4.91%
4
4.60%
-0.31%
Banks
30
13.39%
12
13.79%
0.40%
Financial Holdings
17
7.59%
7
8.05%
0.46%
Diversified financials
1
0.45%
0
0.00%
-0.45%
Real Estate
12
5.36%
5
5.75%
0.39%
Financial Services
3
1.34%
1
1.15%
-0.19%
Finance
74
33.04%
29 33.33%
0.30%
Retailing
2
0.89%
1
1.15%
0.26%
Publishing
15
6.70%
6
6.90%
0.20%
Diversified Services
2
0.89%
1
1.15%
0.26%
Utilities
17
7.59%
7
8.05%
0.46%
Transport/Tourism
13
5.80%
5
5.75%
-0.06%
Services
49
21.88%
20 22.99%
1.11%
Main
Sector
Total
224
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100%
87
100%
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0.20
0.15
0.05
0.05
4
6
8
10
12
0.00
0.00
0.00
2
0.10
Density
0.15
Density
0.10
0.10
0.05
Density
0.15
0.20
0.25
0.20
POPULATION
0
2
4
N = 71 Bandw idth = 0.6658
FINANCE
6
8
10
12
2
4
N = 91 Bandw idth = 0.5043
INDUSTRY
6
8
10
12
N = 49 Bandw idth = 0.7193
SERVICES
4
6
8
10
N = 29 Bandw idth = 0.779
FINANCE
12
0.20
0.05
0.00
0.00
0.00
2
0.10
Density
0.15
0.15
0.05
0.10
Density
0.10
0.05
Density
0.15
0.20
0.20
SAMPLE
0
2
4
6
8
10
N = 38 Bandw idth = 0.8068
INDUSTRY
12
14
2
4
6
8
10
12
N = 20 Bandw idth = 0.8308
SERVICES
Figure 1: Empirical distribution functions of logarithms of the 2004 market capitalization in the
three main sectors for the entire set of Italian listed companies (Population, top panel) and for the
companies included in the sample (bottom panel).
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Table 3: Descriptive statistics and correlation among variables1.
Panel A: descriptive statistics and correlation matrix for the period (2001-2006)
Descriptive Statistics
Median
Standard deviation
4.98
10.29
2.52
4.48
0.22
0.74
Variable
Price (P)
Book Value (BV)
Earnings (E)
Mean
8.64
4.26
0.39
Price (P)
Book Value (BV)
Earnings (E)
Correlation matrix
Price (P)
Book Value (BV)
1.000
0.646
1.000
0.550
0.445
Min.
0.08
0.01
-2.43
Max.
69.07
23.40
3.74
Earnings (E)
1.000
Panel B: descriptive statistics and correlation matrix for the period (2001-2004)
Descriptive Statistics
Median
Standard deviation
4.30
7.22
4.24
3.91
0.18
0.69
Variable
Price (P)
Book Value (BV)
Earnings (E)
Mean
7.47
2.44
0.29
Price (P)
Book Value (BV)
Earnings (E)
Correlation matrix
Price (P)
Book Value (BV)
1.000
0.630
1.000
0.334
0.284
Min.
0.11
0.29
-2.43
Max.
55.00
22.38
3.03
Earnings (E)
1.000
Panel C: descriptive statistics and correlation matrix for the period (2005-2006)
Descriptive Statistics
Median
Standard deviation
6.68
11.62
4.28
4.81
0.32
0.75
Variable
Price (P)
Book Value (BV)
Earnings (E)
Mean
11.05
2.58
0.59
Price (P)
Book Value (BV)
Earnings (E)
Correlation matrix
Price (P)
Book Value (BV)
1.000
0.704
1.000
0.794
0.743
1
Min.
0.08
0.01
-0.90
Max.
69.07
23.40
3.74
Earnings (E)
1.000
The number of firm-year observations with necessary data is 522. The period of study covers the years 2001–2006.
P is the price per share of firm i at the end of year t, E is the earnings per share of firm i for year t, and BV is the
book value per share of firm i at year end t.
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Table 4: Yearly regression results1
Panel A: Price regression models2
Models: (1) Pit  0  1BVit   2 Eit   it ; (2) Pit  0  1BVit   it ; (3) Pit   0  1Eit   it
Vuong’s
R21
R22 
R23
̂ 2
̂1
Z
̂1
ˆ1
Year
N
statistic
2001
1.04
4.34
1.22
6.76
77 5.70
.36
.20
.85
***
3.22*** .43
6.74***
4.45***
I-GAAP
2002
1.04
4.37
1.30
7.08
76 5.08
.35
.24
.98
***
3.23*** .42
6.51***
4.93***
I-GAAP
2003
I-GAAP
2004
I-GAAP
2005
IFRS
2006
IFRS
77
77
77
73
1.09
8.98***
1.18
5.15***
.28
1.10
1.86
5.62***
3.07
4.28***
2.64
1.47
11.52
6.03***
5.16
3.27***
.58
.41
.62
.70
1.14
8.57***
1.37
7.13***
1.47
7.81***
2.70
11.99***
.48
.40
.44
.66
3.76
3.68***
7.77
4.51***
13.16
11.15***
12.00
9.99***
2
RBV
RE2
.24
.07
.19
.07
.14
2.32***
.44
.10
.20
1.32*
.20
.01
.62
-1.88**
.00
.18
.58
1.01
.13
.04
Panel B: Return regression models3
Model: (4)
Rit   0   1  Eit Pit 1    2  Eit Pit 1    it
Year
N
2002 I-GAAP
75
2003 I-GAAP
75
2004I-GAAP
81
2005 IFRS
82
2006 IFRS
76
ˆ1
ˆ2
.372
3.37***
.014
1.17
-.001
-2.46**
.224
2.79***
-.133
-3.13***
.006
.72
-.000
-.59
.002
1.30
.007
2.22**
-.006
-.94
R2
R 2 due to ˆ1
R 2 due to ˆ2
.11
.12
-.01
.00
.01
-.01
.06
.05
.01
.11
.07
.04
.13
.10
.00
1
N is the number of observations used to estimate each model. The first number in each cell reports the regression
coefficient, whereas the second is the value of the t-statistic to test whether the regression coefficient is equal to
zero. The symbols *, **, *** indicate the statistical significance of the test at 0.10, 0.05, and 0.01, respectively.
2
Pit is the price of a share for firm i four months after the fiscal year-end t; BVit is the book value per share of firm i
at the end of the year t; Eit denotes the earnings per share for firm i for time period t-1 to t. ̂1 , ̂ 2 , ̂1 and ˆ1 are the
2
estimated regression coefficients. R21 , R21 and R21 are the adjusted R2’s. RBV
 R21  R23 and RE2  R21  R22 measure
the incremental value relevance of BV and E respectively.
3
Rit is the dividend adjusted stock market return of firm i four months after the fiscal year-end t; Eit / Pit-1 is the
earnings per share of year t deflated by the stock price in year t-1 observed for firm i four months after the fiscalyear end t-1; ΔEit / Pit-1 is the change in the earnings per share from years t-1 to t deflated by the stock price in year
t-1 observed for firm i four months after the fiscal-year end t-1. ˆ1 and ˆ2 are the estimated regression coefficients.
R 2 is the adjusted R2 of model (4).
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9th Global Conference on Business & Economics
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Table 5: Pooled regression results1
Panel A: Price regression models2
Models: (1) Pit  0  1BVit   2 Eit   it ; (2) Pit  0  1BVit   it ; (3) Pit   0  1Eit   it
Vuong’s
R21
R22 
R23
̂ 2
̂1
Year
N
Z
̂1
ˆ1
statistic
2
RBV
RE2
320
1.16
13.10***
2.14
3.79***
.42
1.25
14.49***
.39
4.24
6.33***
.11
3.05***
.31
.02
IFRS
155
.69
3.62***
9.67
8.57***
.66
1.92
12.31***
.49
12.70
16.20***
.63
-1.41*
.03
.16
Pooled
478
1.13
13.65***
4.55
8.77***
.50
1.48
18.82***
.42
7.92
14.72***
.31
1.51*
.19
.08
01-04
I-GAAP
05-06
Chow’s F
statistic
12.72***
6.41***
27.98***
Panel B: Return regression models3
Model: (4)
Rit   0   1  Eit Pit 1    2  Eit Pit 1    it
Year
N
ˆ1
ˆ2
R2
R 2 due to ˆ1
R 2 due to ˆ2
02-04 I-GAAP
245
-.001
-3.11***
-.000
-.02
.03
.03
.00
05-06 IFRS
159
-.133
-2.76***
.006
2.48**
.07
.04
.03
Pooled
374
-.001
3.42***
-.000
-.30
.03
.03
.00
Chow’s F statistic
16.58***
1
N is the number of observations used to estimate each model. The first number in each cell reports the regression
coefficient, whereas the second is the value of the t-statistic to test whether the regression coefficient is equal to
zero. The symbols *, **, *** indicate the statistical significance of the test at 0.10, 0.05, and 0.01, respectively.
2
Pit is the price of a share for firm i four months after the fiscal year-end t; BVit is the book value per share of firm i
at the end of the year t; Eit denotes the earnings per share for firm i for time period t-1 to t. ̂1 , ̂ 2 , ̂1 and ˆ1 are the
2
estimated regression coefficients. R21 , R21 and R21 are the adjusted R2’s. RBV
 R21  R23 and RE2  R21  R22 measure
the incremental value relevance of BV and E respectively.
3
Rit is the dividend adjusted stock market return of firm i four months after the fiscal year-end t; Eit / Pit-1 is the
earnings per share of year t deflated by the stock price in year t-1 observed for firm i four months after the fiscalyear end t-1; ΔEit / Pit-1 is the change in the earnings per share from years t-1 to t deflated by the stock price in year
t-1 observed for firm i four months after the fiscal-year end t-1. ˆ1 and ˆ2 are the estimated regression coefficients.
R 2 is the adjusted R2 of model (4).
October 16-17, 2009
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ISBN : 978-0-9742114-2-7
Table 6: Pooled regression results comparing the pre-adoption period with the post-adoption one
in the three macro-sectors1
Panel A: Price regression models2
Models: (1) Pit  0  1BVit   2 Eit   it ; (2) Pit  0  1BVit   it ; (3) Pit   0  1Eit   it .
Finance Sector
Vuong’s
2
R21
R22 
R23
RBV
̂ 2
̂1
̂1
ˆ1
RE2
Year
N
Z
statistic
.60
7.47
1.40
9.87
01-04 106
.56
.39
.53
-.98
.04 .17
I-GAAP
3.17*** 6.48***
8.34***
10.88***
05-06
IFRS
48
-.05
-.24
.28
1.72*
Chow’s F statistic
Pooled 155
13.08
.88
12.38***
1.83
6.84***
.49
12.89
.88
18.95***
10.20
1.55
11.33
.66
.40
.66
11.11***
10.30***
17.50***
3.68**
2.69*
3.07**
-3.39***
.00
.39
-2.09**
.00
.26
Industry Sector
Year
01-04
I-GAAP
05-06
IFRS
N
̂1
̂ 2
R21
̂1
R22 
ˆ
R23
Vuong’s
Z
statistic
2
RBV
RE2
1
137
1.56
2.67
12.09*** 3.45***
.55
1.60
.51
12.01***
3.57
3.22***
.06
3.50***
.48
.04
69
1.27
3.91***
.58
2.05
8.74***
11.23
8.24***
.49
.33
.09
.06
3.34***
.39
.03
5.95
3.24**
.52
1.67
2.92
1.82
6.13
.55
.52
.16
13.54*** 3.92***
15.08***
6.33***
Chow’s F statistic
3.68**
8.36***
11.87***
Pooled 207
Services Sector
̂ 2
R21
̂1
R22 
ˆ1
R23
Vuong’s
Z
statistic
2
RBV
RE2
Year
N
̂1
01-04
72
1.25
6.86***
3.42
2.60**
.41
1.23
6.51***
.36
3.04
1.81*
.03
1.63*
.38
.05
35
1.88
6.56***
13.69
7.43***
.70
1.46
3.23***
.21
11.29
4.18***
.32
-.36
.38
.48
.91
.33
.15
I-GAAP
05-06
IFRS
1.32
8.39***
Chow’s F statistic
Pooled 109
October 16-17, 2009
Cambridge University, UK
6.02
1.33
6.10
.48
.33
.15
5.65***
7.45***
4.47***
9.77***
2.61*
2.76*
45
9th Global Conference on Business & Economics
Model:
Year
Panel B: Return regression models3
(4) Rit   0   1  Eit Pit 1    2 Eit Pit 1    it
N
02-04 I-GAAP
84
05-06 IFRS
53
Pooled
137
ˆ1
.037
.37
1.047
1.84*
.059
.72
Chow’s F statistic
Year
N
02-04 I-GAAP
103
05-06 IFRS
74
Pooled
183
ˆ1
-.001
-3.39***
-.098
-1.17
-.001
-2.23**
Chow’s F statistic
Year
N
02-04 I-GAAP
55
05-06 IFRS
34
Pooled
90
Chow’s F statistic
ISBN : 978-0-9742114-2-7
ˆ1
-.065
-.17
.292
4.09**
.081
.58
Finance Sector
ˆ2
R2
-.003
-.01
-.90
.011
.13
2.69**
.002
-.01
.65
7.41***
Industry Sector
ˆ2
R2
.000
.08
.06
.003
.00
.56
.000
.02
-.25
14.75***
Services Sector
ˆ2
R2
.001
-.03
-.58
.089
.30
1.93*
-.007
-.01
-.69
1.06
R 2 due to ˆ1
R 2 due to ˆ2
-.01
.00
.04
.10
.00
.00
R 2 due to ˆ1
R 2 due to ˆ2
.09
-.01
.00
.00
.02
-.01
R 2 due to ˆ1
R 2 due to ˆ2
-.02
-.01
.23
.06
-.01
-.01
1
N is the number of observations used to estimate each model. The first number in each cell reports the regression
coefficient, whereas the second is the value of the t-statistic to test whether the regression coefficient is equal to
zero. The symbols *, **, *** indicate the statistical significance of the test at 0.10, 0.05, and 0.01, respectively.
2
Pit is the price of a share for firm i four months after the fiscal year-end t; BVit is the book value per share of firm i
at the end of the year t; Eit denotes the earnings per share for firm i for time period t-1 to t. ̂1 , ̂ 2 , ̂1 and ˆ1 are the
estimated regression coefficients. R21 , R21 and R21 are the adjusted R2’s. Vuong’s test Z statistic measures the
2
significance of the relative value relevance of model (2) over model (3). RBV
 R21  R23 and RE2  R21  R22 measure
the incremental value relevance of BV and E respectively.
3
Rit is the dividend adjusted stock market return of firm i four months after the fiscal year-end t; Eit / Pit-1 is the
earnings per share of year t deflated by the stock price in year t-1 observed for firm i four months after the fiscalyear end t-1; ΔEit / Pit-1 is the change in the earnings per share from years t-1 to t deflated by the stock price in year
t-1 observed for firm i four months after the fiscal-year end t-1. ˆ1 and ˆ2 are the estimated regression coefficients.
R 2 is the adjusted R2 of model (4).
October 16-17, 2009
Cambridge University, UK
46
9th Global Conference on Business & Economics
ISBN : 978-0-9742114-2-7
Table 7: Sensitivity analysis results1
Model2: (5)
log  uit   1Mcapit  2 Finit  3 Indit  4 Servit  5 Sign.Eit   it
Data
N
01-04I-GAAP
321
05-06IFRS
158
ˆ1
ˆ2
ˆ3
ˆ4
ˆ5
-.000
.987
1.057
1.139
-.224
.45
5.78*** 7.22*** 6.26*** -1.48
.000
.022
.096
.084
.003
1.32
.71
3.61***
2.56**
.10
R2
.38
.41
1
N is the number of the observation. The first number in each cell reports the regression coefficient, whereas the
second is the value of the t-statistic to test whether the regression coefficient is equal to zero. The symbols *, **, ***
indicate the statistical significance of the test at 0.10, 0.05, and 0.01, respectively.
2
log  uit  t is the natural logarithm of the absolute value of residuals of model (1) for firm i at time t; Mcapt is the
market capitalization of firm i at the end of the year t; Fin, Ind and Serv are dummy variable indicating if the firm i
at time t belongs to the Finance, Industry or Services sector, respectively. Sign.E is another dummy variable
indicating if the firm i at time t reported positive earnings or not.
October 16-17, 2009
Cambridge University, UK
47