Master Thesis: The Accounting Quality of IFRS-adopting Private Firms

Master Thesis: The Accounting Quality of
IFRS-adopting Private Firms

Chaolong Guan
Tilburg University
Supervisor: Dr. Marco Da Rin
Tilburg University
October 2013


Abstract
This study examines the changes of the accounting quality of private firms over the years around the
IFRS adoption event. Based on a sample of 7,043 private firms from three European countries who
adopted IFRS during the period 2003 to 2010, the tests give strong evidence for the findings that private firms experience a decrease in accounting quality on the IFRS adoption year and an increase on
the year after. For measuring accounting quality, the model from Dechow & Dichev (2002) was used.
The model regresses the working capital accruals with the adjacent three-year cash flows, and the
standard deviations of the residuals were characterized as estimation errors, which in turn proxy for accounting qualities. In order to observe the changes in the accounting quality over time, I put the firms
with the same IFRS-adoption year into country-year groups. Then I take two approaches to measure
their accounting qualities. The results are consistent with the main findings. I also make tests controlling for firm size and financial leverage. In light of the shortcomings of the Dechow & Dichev (2002)
model in explaining discretionary accruals, the McNichols (2002) model was also used.

1


I.

Introduction

Accounting standards have been a focus of accounting studies in recent years. They play a crucial role in the corporate financing processes. The development of the accounting standards is an interesting topic in its own right. As were summarized in Kothari, Ramanna & Skinner (2011), there are
three streams of economic theories on accounting regulation: public interest, capture, and ideology theories, which together form an evolutionary viewpoint of the development of accounting standards.
They rule out the public interest theory due to the lack of support for a “benevolent and omniscient policy maker”. They conclude that “competition among standard setters is the most effective means of addressing the concerns over a regulated GAAP highlighted by the capture and ideology theories”.

Over the last number of years the adoption of International Financial Reporting Standards
(IFRS) has gained considerable momentum around the world. The International Accounting Standards
Board (IASB) was established in 2001 to develop International Financial Reporting Standards (IFRS).
A year later, European Union (EU) member states committed to requiring IFRS for all listed corporations in their jurisdictions effective year 2005 (EC, 2002). Since then, almost 100 countries require or
permit the use of IFRS for financial reporting purposes, and several more have decided to require IFRS
in the near future. These countries either mandated IFRS for some listed companies or allow listed
companies to voluntarily adopt IFRS.
From the point of view of the financing agents, their incentives in choosing an accounting
standard for their financial reporting is a topic worth studying. Even though the requirements by the
IFRS-adopting countries are only subjected to the public firms, many private firms around the world
have voluntarily adopted or switched to IFRS. While some studies on public firms have shown some
positive effects that the IFRS adoption has on the decrease of firms' cost of capital, and other relevant
studies shown otherwise, the effects that this switch has on private firms is a rarely explored topic. This
study investigates the relationship between private firms' accounting qualities with their changes of reporting standards.
While most of the relevant studies were made in the territory of listed firms, this study is based
on a sample of 7,043 private firms who adopted IFRS during the period 1997 to 2010 from three countries: United Kingdom, Italy, and Germany. The factors that lead to the differences in the financial reporting between public firms and private firms lay in their differences in investor-management relationships. For a public firm, the investors are always ‘at arms' length’, while for a private firm, their investors can deal with the information asymmetry problem via “insider access”, as described in Ball &
Shivakumar (2005): “examples of insider access include the German ‘‘stakeholder’’ system, with both
labor and capital (bank) represented in corporate governance, the Japanese keiretsu and South Korean
chaebol systems of investing and trading largely within internally informed corporate groups, and the
Chinese system of family controlled businesses and guanxi (connections) networks.” These differences
in agency relationships indicate that the insider access and high-quality public financial reporting are
substitutes in reducing information asymmetry, which leads to the lower demands from investors of
private firms for high-quality accounting reports.
The findings of this study show that the accounting quality of the private firms decreases at the
first year after the IFRS adoption and increase on the second year. For measuring accounting quality,
the model from Dechow & Dichev (2002) is used. The model uses the adjacent three-year cash flows to
explain the working capital accruals, and the standard deviations of the residuals were characterized as
estimation errors, which in turn proxy for the accounting qualities. In order to observe the changes in
accounting quality over time, I put the firms with the same adoption years into the same groups for
firms of each country. Then I take two approaches to measure the accounting qualities of each group. I

also make tests controlling for the firm sizes and financial leverages. In light of the shortcomings of the
Dechow & Dichev (2002) model in explaining discretionary accruals, the McNichols (2002) model was
also used. The results are consistent with the main findings.
2


The rest of this paper will continue as follows. Section 2 will describe and summarize the related literature. Section 3 will explain the method I use to measure the accounting qualities of observations from the data. Then I will describe the data and the research design in section 4. In section 5, I
will discuss about the results from the tests. Section 6 concludes.

II.

Related Literature

The topic of this study is related to some of the fundamental questions in accounting studies,
such as the incentives of the agents in financial reporting and earnings management. Moreover, many
recent literatures have studied the effects of the adoptions of new accounting standard. These studies
focus on different areas of economic topics and provide a methodology base for this study. By studying
them, one can get a comparative understanding of existing methodologies and the current progress of
economic studies on these issues.
One fundamental issue in accounting is: what factors influence the various incentives in corporate financial reporting. One of the incentive problems in corporate financial reporting is that the managers face a trade-off between short-term need to “deliver earnings” and the long-term objective of value-maximizing investment decisions. According to the findings of Graham et al. (2005), managers
would rather take economic actions that could have negative long-term consequences than make within-GAAP accounting choices to manage earnings. Their results indicate that CFOs believe that earnings,
not cash flows, are the key metric considered by outsiders. Ball, Robin, & Sadka (2008) raised the
question of whether financial reporting is shaped by equity markets or by debt markets. They hypothesize that debt markets—not equity markets—are the primary influence. Their measures of countries’
financial reporting properties (country-level financial reporting timeliness and country-level conservatism) are regressed on the countries’ debt and equity market sizes, to estimate where the demand for
financial reporting resides. Their hypotheses about debt market are: 1. Timely loss recognition increases in the importance of debt markets; 2. Conditional conservatism (asymmetrically timely loss recognition relative to gain recognition) increases in the importance of debt markets; 3. Unconditional conservatism (low reported earnings and book values, independent of economic gains and losses) does not
increase in the importance of debt markets, controlling for conditional conservatism. Their hypotheses
about equity market are: 1. Timely gain and loss recognition do not increase in the importance of equity
markets; 2. Conditional conservatism (asymmetrically timely loss recognition relative to gain recognition) does not increase in the importance of equity markets; 3. Overall gain and loss timeliness does not
increase in the importance of equity markets. They estimate country-level financial reporting timeliness
from Basu (1997) piecewise-linear regressions of earnings on returns. The regressions control for various non-market determinants of financial reporting practice, including countries’ legal system origins

and three legal-system variables: Rule of Law, Corruption and Creditors’ Rights. They also report regressions that control for the market-to-book ratio. They argue that firstly MTB contains information
about both expected returns and expected earnings. Secondly, MTB proxies for the proportion of the
variation in the market value of equity that is due to factors (such as synergies and rents) that are not
reflected in book value, and hence affect returns but not earnings.
Also on the incentives in corporate financial reporting: Burgstahler, Hail, & Leuz (2006) hypothesizes that capital markets as well as critical aspects of a firm’s institutional environment determine
the role of earnings. This role in turn influences how corporate insiders use reporting discretion, which
crucially determines the properties of reported earnings. They focus on another dimension of accounting quality other than conservatism, namely, the degree of earnings management. They rely on an earnings management index suggested by Leuz et al. (2003), which is based on four different proxies. They
also conduct sensitivity analyses using alternative earnings management metrics similar to that used by
Lang et al. (2003) and Lang et al. (2006) as well as measures of conservatism. They start with an examination of the effect of capital markets on the reporting incentives. Next, they explore the interaction
3


between market forces and other institutional variables that have the potential to differentially affect
private and public firms: The first factor is the quality of legal enforcement. The quality of legal enforcement is measured by the average score across three proxies from La Porta et al. (1998): (1) an index of the judicial system’s efficiency, (2) an index of the rule of law, and (3) the level of corruption.
They also examine the following four factors. First, they expect that the degree of tax alignment of financial accounting has a differential effect on private and public firms. As private firms are less reliant
on earnings to communicate firm performance, it is less of a concern to private firms if they make earnings less informative in the process of minimizing taxes. Second, they expect accounting rules that
make heavier use of accruals to be associated with less earnings management for public firms than private firms. Third, they expect stricter disclosure rules in securities offerings and associated enforcement
which apply only to firms with publicly traded securities make it harder for firms to engage in earnings
management and create incentives to reveal economic performance. Similarly, strong minorityshareholder protection rules are designed to facilitate equity financing at arm’s length in public markets
and hence are expected to reduce earnings management primarily for publicly traded firms. Fourth,
they expect that the two capital market features (the extent to which the financial system is relatively
more equity market- or bank-based and the degree of financial development) are negatively associated
with earnings management primarily for the public firms.
Another incentive problem involved in corporate financial reporting is that the managers as insiders, in order to protect their private control benefits, use earnings management to conceal the firm
performance from outsiders. However, the ability of insiders to divert resources for their own benefits
is limited by the legal systems that protect the rights of outside investors. As outsiders can only take
disciplinary actions against insiders if outsiders detect the private benefits, insiders have an incentive to
manipulate accounting reports in order to conceal their diversion activities. Leuz, Nanda, & Wysocki
(2003) propose that earnings management is more pervasive in countries where the legal protection of
outside investors is weak. To measure the pervasiveness of earnings management in a country, they

create four proxies that capture the extent to which corporate insiders use their accounting discretion to
mask their firm’s economic performance. The first measure is a country’s median ratio of the firm-level
standard deviation of operating earnings divided by the firm-level standard deviation of cash flow from
operations, which was calculated by subtracting accruals from earnings. The second measure is the correlation between changes in accounting accruals and operating cash flows. The third measure uses the
magnitude of accruals as a proxy for the extent to which insiders exercise discretion in reporting earnings. It is computed as a country’s median of the absolute value of firms’ accruals scaled by the absolute value of firms’ cash flow from operations. The fourth measure follows Burgstahler and Dichev
(1997) to calculate the ratio of ‘‘small profits’’ to ‘‘small losses’’. The aggregate earnings management
score is computed by averaging the country rankings for the four individual earnings management
measures. They begin with a descriptive country cluster analysis, which groups countries with similar
legal and institutional characteristics. To examine more explicitly whether differences in earnings management are related to private control benefits and investor protection, first, they undertake a multiple
regression analysis. They measure outside investor protection by both the extent of minority shareholder rights as well as the quality of legal enforcement. The proxy for minority shareholder rights is an anti-director rights index created by La Porta et al. (1998) that captures the voting rights of minority
shareholders. The legal enforcement measure for each country is the average score across three variables: (1) an index of the legal system’s efficiency; (2) an index of the rule of law; and, (3) the level of
corruption. The regressions control for the endogeneity of investor protection using countries’ legal origins and wealth as instruments for the investor protection variables as suggested by Levine (1999).
Then they directly estimate a 2SLS regression on the control benefits proxy using the level of outsider
rights and legal enforcement as instruments, explicitly accounting for the effect of investor protection
on the level of private control benefits. They use a country’s average block premium estimated by Dyck
4


and Zingales (2002) as a proxy for the level of private control benefits.
The premise in the studies of corporate financial reporting and earnings management is to
measure the quality of financial reporting. Dechow, Ge & Schrand (2010) summarized and analyzed
the various measures which were used as indicators of “earnings quality”. They summarized earnings
quality measures including “persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases,” which were
categorized into three groups: properties of earnings, investor responsiveness to earnings, and external
indicators of earnings misstatements. Among them, the properties of earnings were mostly used in accounting research. The measures in properties of earnings could be further classified into five categories: earnings persistence, abnormal accruals and modeling the accrual process, earnings smoothness,
asymmetric timeliness and timely loss recognition, and target beating. There're two streams to the research in earnings persistence. The first stream assumes that “more persistent earnings will yield better
inputs to equity valuation models, and hence a more persistent earnings number is of higher quality
than a less persistent earnings number.” However, this assumption was not very well justified by extant
studies yet. The second stream attempts to address this problem. In this group, the authors distinguished
studies on the relative contributions of fundamental performance (X) versus the measurement rule (f)

on the persistence of reported earnings. They X and f comes from definitive framework of earnings:
Reported Earnings == f(X). The second type of measures for the properties of earnings is to measure
the abnormal accruals. “The normal accruals are meant to capture adjustments that reflect fundamental
performance, while the abnormal accruals are meant to capture distortions induced by application of
the accounting rules or earnings management (i.e., due to an imperfect measurement system).” “The
general interpretation is that if the 'normal' component of accruals is modeled properly, then the abnormal component represents a distortion that is of lower quality.” Among this category, they summarized
five widely used models of accruals: Jones (1991) model, modified Jones model (Dechow et al., 1995),
performance matched (Kothari et al., 2005), Dechow and Dichev (2002) approach, and discretionary
estimation errors (Francis et al., 2005a). The third category of measures for properties of earnings is
based on the tenet that “earnings smooth random fluctuations in the timing of cash payments and receipts, making earnings more informative about performance than cash flows.” The debate on this tenet
is that standard makers don't regard smoothness as a necessary desirable property of earnings. The authors conclude that “the standard setter’s goal is a representation of fundamental performance that improves cash flow predictability. Smoothness is an outcome of an accrual-based system assumed to improve decision usefulness; it is not the ultimate goal of the system.” The fourth category of measures
for properties of earnings is to separately distinguish the timeliness of loss recognition and profit
recognition. The most frequently used measure of timely loss recognition is the reverse earningsreturns regression from Basu (1997). Basu (1997) provides a second measure of timely loss recognition
that is based solely on the reverse regression on the changes in net income. As I also noted above, Ball,
Robin, & Sadka (2008) makes use of the Basu (1997) reverse regression method and shows that timely
loss recognition “has an endogenous component related to firms’ reporting incentives, primarily equity
incentives.” “Thus, assuming that managers are responding to investor demand for decision usefulness,
these studies suggest that equity markets perceive asymmetric timeliness as improving earnings quality.”
The last category of measures for properties of earnings in Dechow, Ge & Schrand (2010) is target
beating. They suggest that “findings on whether small profits and small loss avoidance represent earnings management based on the observed determinants is mixed, which is suggestive that small profits
and small loss avoidance may not be an indication of earnings management. This indirect evidence is
supported by more direct evidence including Dechow et al. (2003), who show that discretionary accruals are no different for small profit versus small loss firms; Beaver et al. (2007), who suggest that the
‘‘kink’’ in earnings around zero can be explained by asymmetric taxes, rather than opportunistic choices; and Durtschi and Easton (2005, 2009), who show that it is explained by statistical and sample bias
5


issues related to scaling by price.” They conclude that: “the totality of the evidence indicates that the
use of small profits as a proxy for earnings management more generally is unsubstantiated.”
The effects of different reporting choices on the firms were studied in Ball & Shivakumar
(2005), which seeks to identify which recognition model (unconditional conservatism or conditional

conservatism) is most prevalently used for economic gains and losses, and how this choice differs between public and private companies. The international evidence is consistent with insider access and
high-quality public financial reporting being substitutes for reducing information asymmetry, so they
expect private and public companies to follow a similar pattern. In other words, the public firms should
have more timely loss recognition than private companies due to lack of insider access from their investors. Their principal timeliness measure exploits the transitory nature of economic income (Samuelson 1965; Fama, 1970). From Basu (1997), they measure timely gain and loss incorporation as the tendency for increases and decreases in accounting income to reverse. Their hypothesis is that there is less
reversal of income decreases in private companies than in public companies. Next, they conduct an accruals-based test of loss recognition. The role of accruals in the Dechow et al. (1998) model is to mitigate noise in operating cash flow. They envision a second role for accruals, timely recognition of economic gains and losses, and hypothesize that it is a source of positive but asymmetric correlation between accruals and contemporaneous cash flows. Thus they estimate a piecewise-linear relation between cash flows and accruals. They found that “average earnings quality is measurably lower in UK
private companies than in public companies, even though their financial statements are audited and certified as complying with the same accounting standards. Accounting standards are not absolute givens,
and their effect on actual financial reporting is subject to market demand.”
As an important part of financial reporting decision, accounting standards were considered an
economically significant factor. One stream of views on accounting standard changes believes that financial statement comparability would increase by switching from local accounting standards to an international accounting standard. As stated in IASCF [2005], one of the objectives of the IFRS is to develop a set of “global accounting standards that require high quality, transparent and comparable information in financial statements and other financial reporting.” DeFranco, Kothari, & Verdi (2011)
constructs a measure of financial statement comparability to estimate its benefits to users. They build
their definition of comparability on the idea that the accounting system is a mapping from economic
events to financial statements. They use stock return as a proxy for the net effect of economic events on
the firm’s financial statements, and use earnings as a proxy for financial statements. The “closeness” of
the functions between two firms represents the comparability between the firms. They invoke one implication of accounting comparability: if two firms have experienced the same set of economic events,
the more comparable the accounting between the firms, the more similar their financial statements.
They use firm i’s and firm j’s estimated accounting functions to predict their earnings, assuming they
had the same return. They define accounting comparability between firms i and j as the negative value
of the average absolute difference between the predicted earnings using firm i’s and j’s functions. Then
they hypothesize that the availability of information about comparable firms lowers the cost of acquiring information, and increases the overall quantity and quality of information available about the firm.
They expect these features to result in more analysts covering the firm. In addition, enhanced information should facilitate analysts’ ability to forecast firm i's earnings. Thus they predict that comparability will be positively associated with forecast accuracy and negatively associated with forecast dispersion. Beuselinck, Joos, & Van Der Meulen (2007) conjectures that earnings comparability is largely
affected by the way the accruals system recognizes losses in a timely fashion or smooths income over
distinct reporting periods. They focus on the accrual accounting system to investigate the association
between accruals and positive, resp. negative cash flows across different countries. In addition, they
compare the way accrual accounting functions equally (or, differently) across countries. They study the
sensitivity of these accruals – cash flow association to firm-specific reporting incentives and business
6


cycles across a set of countries. They choose a sample of all non-financial companies incorporated in
one of the 15 EU member states over a 15 year period prior and up to IFRS introduction (1991-2005)

as the research setting. They extend the piecewise linear regression model developed by Ball and
Shivakumar (2005; 2006) separating positive and negative cash flow observations. The regressions use
accounting accruals as dependent variable and cash flow from operations as independent variable. Then
they deduct accruals from earnings to get an operating cash flow measure. They include reporting incentives related to capital market pressure, debt levels, and labor relation incentives (measured by size,
leverage, and labor intensity), while controlling for business cycles. Next, they investigate how reporting incentives affect accrual measurement and whether the incentive effects differ across the EU over
the period 1991-2005. They check the robustness of their results with respect to controls for sector
specification, growth characteristics as well as for including market returns in the piece-wise regression
model. Finally, they study whether three institutional country features (importance of stock market,
domestic bank debt, and labor union membership) affects the observed effect of firm reporting incentives on (un)timely loss/gains recognition. Taking a different approach, Bae, Tan, & Welker (2008) approach the topic by measuring investors' responsiveness. They hypothesize that the costs of following a
foreign firm increase with the extent of GAAP differences between the analyst’s domicile country and
the home country of the foreign firm. They also hypothesize that the costs of providing accurate forecasts increase with the extent of GAAP differences between the analyst’s home country and the home
country of the foreign firm. For the dependent variables, they measure the foreign analyst following
with the average number of foreign analysts per year from country A who forecast annual earnings for a
firm during the seven-year period of 1998–2004. To measure forecast accuracy they use the pricescaled absolute difference between an earnings forecast and the actual earnings for a firm at time t. For
the independent variable, they adopt two approaches in measuring the differences in accounting standards between two countries. The first approach identify differences in their sample on the 21 accounting rules which was based on a review of the past literature and relying on a survey of GAAP differences between each of the country-pairs. The second approach uses the survey data to identify commonly occurring differences in accounting across countries. Their comprehensive list of country-pair
control variables is drawn primarily from Sarkissian and Schill (2004), who construct a comprehensive
set of country-pair level variables in their analysis of firms’ cross-listing decisions. Their main results
show that the extent to which accounting standards differ across countries is negatively related to foreign analyst following. They find a weaker negative relation between GAAP differences and forecast
accuracy.
More specifically related to the topic of this thesis, several researches studies the effects of the
accounting standard changes for public firms. Three studies found positive effects: Leuz & Verrecchia
(2000), Gkougkousi & Mertens (2010), and Tan, Wang, & Welker (2011). However, three studies found
otherwise: Christensen, Hail, & Leuz (2013), Daske, Hail, Leuz, & Verdi (2008), and Daske, Hail, Leuz,
& Verdi (2013).
Leuz & Verrecchia (2000) hypothesizes that a switch to an international reporting regime leads
to lower bid-ask spreads, more trading volume, and less share price volatility of listed firms. By estimating a cross-sectional relation between their proxies of a firm’s cost of capital and the firm’s reporting strategy well after firms have switched the disclosure regime, they should be able to separate the
“information-asymmetry” effect from the “news” effect. In addition, an “event study” design observes
the behavior of their proxies around the reporting change and hence mitigates the possibility that some
other unobserved variable (and not the disclosure policy) is responsible for the cross-sectional differences in the proxies. A key problem in estimating the cross-sectional regression is that firms choose
their reporting strategy considering the costs and benefits of international reporting. Therefore, an OLS

regression of the proxy for cost of capital on firm characteristics and a dummy for the firm’s reporting
strategy would suffer from self-selection bias. They deal with this problem with a two-equation method.
7


Their cross-sectional sample comprises 102 firms included in the DAX 100 index during 1998. They
studied the annual reports to identify the firms’ reporting strategy. They also conducted a survey to confirm their classification. Their evidence in German firms is consistent with the notion that firms committing to increased levels of disclosure garner economically and statistically significant benefits.
Gkougkousi & Mertens (2010) examines the effect of IFRS adoption on banks and insurance companies. Doing so is particularly interesting due to the controversial impact of fair-value accounting on the
cost of equity. They measure the cost of equity averaging over the estimates of four different implied
cost-of-equity models from Hail & Leuz (2006). For their proxy for liquidity they use the Amihud 2002
illiquidity measure. The independent variable is a dummy which takes the value 1 if the company reports under IFRS. Their analysis shows a statistically and economically significant decrease in cost of
equity and a statistically and economically significant increase in liquidity for European banks and insurance companies that report under IFRS after 2005. Their additional analyses indicate an increase in
earnings volatility of financial institutions in the post-2005 period, while their risk-taking behavior decreases. Contrary to the predictions of recent theoretical studies, they find that banks and insurance
companies with higher exposure to fair-value accounting enjoy lower cost of equity. Similar to Bae,
Tan, & Welker (2008) described above, Tan, Wang, & Welker (2011) takes an approach on investors'
responsiveness to accounting standard switch. Their first hypothesis is that IFRS adoption is associated
with increased coverage by foreign analysts and an improvement in foreign analysts’ earnings forecast
accuracy. The second hypothesis is that increases in foreign analyst following and improvements in
foreign analysts’ forecast accuracy following IFRS adoption are more pronounced for analysts located
in countries that adopt IFRS at the same time as the firm’s home country and for analysts with previous
IFRS experience. Their last hypothesis is that increases in foreign analyst following and improvements
in foreign analysts’ forecast accuracy following IFRS adoption are more pronounced for firms from
countries with local GAAP that differed more from IFRS prior to IFRS adoption, and are positively associated with the extent to which GAAP differences between the analyst’s home country and the firm’s
home country are reduced by IFRS adoption. The main dependent variables are foreign analyst following and foreign analysts’ earnings forecast accuracy surrounding each firm’s mandatory IFRS adoption.
In the analysis of foreign analyst following, they control for firm size, cross-listing in the United States,
market value to book value of equity, intangible assets, stock return volatility, security issuance, stock
turnover, and stock return. In the analysis of earnings forecast accuracy, they also control for the number of analysts following the firm, earnings forecast horizon, analysts’ general experience and firmspecific experience, the number of analysts working for the brokerage that an analyst is associated with,
and the number of firms covered by an analyst. For their last hypothesis, they use the Bae, Tan, and
Welker (2008) measures to construct two related but distinct measures of the extent to which IFRS
adoption eliminates accounting standard differences. First, they use the number of differences between

local GAAP and IAS as a measure of the extent to which the mandatory adoption of IFRS produces
more comparable reporting (relative to other IFRS firms internationally) for firms in each country.
Then they use the number of differences between local GAAP and IFRS prior to IFRS adoption as a
measure of the number of accounting differences relative to IFRS that are eliminated by IFRS adoption
in each country. They find that firms located in countries where local GAAP differed more from IFRS
prior to IFRS adoption gain more foreign analysts than do firms located in countries with local GAAP
more similar to IFRS. They also find that foreign analyst following increases more when IFRS adoption causes a greater reduction of GAAP differences between analysts’ home countries and firms’ home
countries.
Christensen, Hail, & Leuz (2013) first examines whether there are differential capital-market
effects in EU and non-EU countries around mandatory IFRS adoption. In the second test, they introduce indicators to distinguish between countries with and without bundled changes in enforcement and
examine whether the liquidity effects around IFRS adoption are stronger for the bundled countries. The
8


third test attempts to separate the effects of IFRS adoption and changes in financial reporting enforcement by exploiting the fact that some firms are not affected by the IFRS mandate because they already
report under IFRS on a voluntary basis. Yet, these firms are affected by enforcement changes supporting the IFRS mandate because their financial statements are subject to the (proactive) review process.
The final test exploits the fact that some EU countries made changes to the enforcement of financial
reporting at a different time and not concurrent with the IFRS mandate. They find that, across all countries, mandatory IFRS reporting had little impact on liquidity. The liquidity effects around IFRS introduction are concentrated in the EU and limited to five EU countries that concurrently made substantive
changes in reporting enforcement. There is little evidence of liquidity benefits in IFRS countries without substantive enforcement changes even when they have strong legal and regulatory systems. Moreover, they find similar liquidity effects for firms that experience enforcement changes but do not concurrently switch to IFRS. Daske, Hail, Leuz, & Verdi (2008) examines the economic consequences of
mandatory IFRS reporting. They employ four proxies for market liquidity, that is, the proportion of zero returns, the price impact of trades, total trading costs, and bid–ask spreads, four methods to compute
the implied cost of equity capital, and use Tobin’s q as a proxy for firms’ equity valuations. “Aside
from its policy relevance, the study provides rare evidence on the economic consequences of forcing
firms to change an entire set of accounting and disclosure standards.” Daske, Hail, Leuz, & Verdi (2013)
examines the economic consequences associated with voluntary and mandatory IAS/IFRS adoptions
around the world. They hypothesize that an increased commitment to transparency is expected to reduce information asymmetry and estimation risk, and hence should be rewarded with higher market
liquidity and a lower cost of capital. They analyze a large panel of voluntary IFRS (and IAS) adoptions
from 1990 to 2005 across 30 countries. To analyze the heterogeneity in the economic consequences
across firms, they use two proxies to create variables indicating major changes in firms’ reporting incentives around IFRS adoptions. The first proxy is input-based and focuses directly on firm characteristics that shape firms’ reporting incentives. They use factor analysis and extract a factor that has consistent loadings for these firm characteristics, and then use the distribution of changes in factor scores
around IFRS adoption to split the sample into ‘serious’ and ‘label’ adopters. The second proxy is output-based and measures changes in reporting behavior around IFRS adoptions. They use changes in
accruals-cash flow metric to capture improvements in reporting behavior. They find little evidence that

voluntary IAS adoptions are, on average, associated with an increase in market liquidity or a decline in
the cost of capital. If anything, the effects go in the opposite direction.

III.

The Measurement of Accounting Quality

To measure the accounting qualities of the firms during the sample period, I use the accrualcash flow relation as a proxy for measuring accounting quality. Specifically, I tested on the financial
data of IFRS adopting firms by the method devised by Dechow & Dichev (2002) to derive the measure
of working capital accrual quality with the following firm-level regression:
𝛥𝑊𝐶𝑡 = 𝑏0 + 𝑏1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝑏2 ∗ 𝐶𝐹𝑂𝑡 + 𝑏3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝜀𝑡 .
𝛥𝑊𝐶 is the change in working capital as the dependent variable while 𝐶𝐹𝑂 is the cash flows from operations of the lagged-, current- and forward- year as the explanatory variables. The residuals from the
regressions reflect the accruals that are unrelated to cash flow realizations, and the standard deviation
of these residuals 𝜎(𝜀𝑡 ) is the firm-level measure of accruals quality, where higher standard deviation
denotes lower quality. This method takes advantage of the linkage between current accruals and cash
flows in the immediately adjacent periods. The basis for this method is that accruals may arise following some cash flows and in anticipation of others. The difference between the amount accrued and the
amount realized is characterized as the estimation error which in this study is measured by 𝜎(𝜀𝑡 ).
A shortcoming of this method is that it doesn't incorporate the management incentives in earnings management. According to the surveys and interviews to corporate executives made by Graham et
9


al. (2005), most executives of large public firms highly value the benchmark of earnings. A large portion of them would sacrifice long-term value to smooth earnings. As was tested in McNichols (2002),
the Dechow & Dichev (2002) model is misspecified in that results with stronger explanatory powers
were produced when adding the discretionary accrual factors into the model. Thus, following the suggestion by the paper, I used the McNichols (2002) model to make further tests:
𝛥𝑊𝐶𝑡 = 𝛽0 + 𝛽1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝛽2 ∗ 𝐶𝐹𝑂𝑡 + 𝛽3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝛽4 𝛥𝑆𝑎𝑙𝑒𝑠𝑡 + 𝛽5 𝑓𝑖𝑥𝑒𝑑𝑎𝑠𝑠𝑒𝑡𝑠 + 𝜈𝑡 .
Similarly, the standard deviation of the residuals 𝜎(𝜈𝑡 ) is the measure of accruals quality. The change
in sales and fixed assets were substitutes for change in revenue and PPE in the Jones (1991) model. The
Jones (1991) model intends to separate discretionary accruals from non-discretionary accruals.
McNichols (2002) linked the Jones (1991) model with the Dechow & Dichev (2002) model “to
strengthen both approaches, and to calibrate the errors associated with Jones' measure of discretionary

accruals and DD's measure of earnings quality.”

IV.

Data and Research Design

The tests in this study are based on the financial data and IFRS adoption information of private
firms in three countries: United Kingdom, Italy, and Germany. The data are from the Amadeus data-set
of Bureau van Dijk, containing the comparable financial information for public and private companies
across Europe. I take advantage of the data in three countries: UK, Italy and Germany. The part of data
that I use is the ones with the IFRS adoption information, consisting of more than 1 million firmobservations in each country. Choosing only the data of private firms which adopted IFRS during the
period 2003 to 2010, the sample includes 5,406 firms in UK, 1,207 in Italy, and 430 in Germany.
The financial data of private firms' financial reports are not always continuous due to the private
firms’ nature of lack of extensive disclosure requirements. Neither the financial data nor the IFRS
adoption information in our data-set is complete, which makes it difficult to make time-series tests
about the changes of accounting quality over time on many firms. In order to grasp the general trend of
the changes of the accounting qualities over time, I first put the firm-observations into country-year
groups and try to measure the accounting quality of the firms in each country-year. The regressions are
made on different firms which happen to have non-empty entry of relevant financial data and adoption
information on that year (and their one-year-lagged-, one-year-forward-cash flow data). To observe the
movements of accounting qualities across the whole observation period, I only pick the firms which
adopted IFRS for the first time at that year and wouldn't switch back to local GAAP in later years till
2010. In other words, the firms I test on are the ones that 'stick to' the new accounting standards after
the adoption. These criteria of selection leave us with 1965 British firms, 455 Italian firms and 420
German firms. As the country-year groups often lacks complete firms observations, therefore I only
take measurements of country-year groups of at least 20 observations. Five country-year groups satisfy
this threshold. The results of the tests were displayed in Table 1a. Next, I try to include other variables
which might have explanatory power on the results other than cash flows from operations. The methods
used by Beuselinck, Joos, & Van Der Meulen (2007) which introduced variables that proxy for reporting incentives related to capital market pressure, debt levels were shown to be likely useful in the context of this study. Besides, Ball & Shivakumar (2005) shows that firm size and financial leverage have
significant power in explaining accruals-based test of loss recognition. Therefore I make the same tests

as before except that I control for the firm sizes and financial leverages. The results were reported in
Table 1b. Then I make tests with the extended model suggested by McNichols (2002). Due to the lack
of information on the sales entry the UK data which means that the UK data are inapplicable for the
McNichols (2002) method, the data allow for four of the five country-year groups: German firms who
adopted IFRS in 2008, Italian firms who adopted in 2005, 2006, and 2007. The results are displayed in
Table 2.
While the tests above give a long track record of the accounting qualities of firms that adopted
10


IFRS at 2009 in UK, adopted at 2008 in Germany, and adopted at 2005, 2006 and 2007 in Italy, I make
a second type of tests on the firms that have complete financial data around the adoption years to get
more assertive results. This type of tests requires firm-year observations with non-empty consecutive
financial data and adoption information for the 3 years around IFRS adoption which eliminates a greater sum of data. The reason for 3 years is that on the one hand, the data of 3 consecutive years would
support the checking of the results of the findings from the first type of tests, while on the other hand,
the data would be eliminated to too few to produce any result if the observations of more consecutive
years were required. The whole data-set are the same as before with the 7,043 firms except that this
type of tests doesn't drop the observations that switched back to local GAAP since the third year after
adoption (T+2), because the three-year period is long enough to check the effects observed above, and
not requiring the firms to 'stick to' the new standard leaves more samples for the tests. Moreover, same
as before, I only take measurements of country-year firm groups of more than 20 firms. These criteria
of selection leave us with 8 country-year groups with 992 firms available for testing: 445 British, 471
Italian, and 76 German firms. There are two caveats about the empirical methods. One is the same as in
the first type of tests in that the UK data lack information on the sales entry which makes the UK data
inapplicable for the McNichols (2002) method. Thus, the observations that could be tested with the
McNichols (2002) method were limited down to 540 firms: 464 Italian and 76 German firms. The second caveat is that due to the lack of their data in the year 2011, the results on British firms which
adopted IFRS in 2009 and Italian firms which adopted IFRS in 2009 are only sufficient for estimates
till the year of adoption. The results were displayed in Table 3.

V.

Discussions on the results

The Dechow & Dichov (2002) model relies on the standard deviations of the residuals, which is
the estimated square root of the variance of the dependent variable conditional on the explanatory variables. The measure therefore reflects absolute variation in the residuals rather than variation relative to
the variation in accruals. Thus the estimates are only comparable when they are from the same firmgroups.
As were shown in Table 1a, 1b, and Table 2, the estimates of the regressions made each year of
the different firms with relevant financial information show a significant decrease of accounting quality
on the first year of IFRS adoption. The results from Germany and Italy show that the accounting qualities increase on the second year after the adoption. The decreasing effect is consistent in all firm-groups
while the increasing effects have two exceptions: the Italy 2007 and Italy 2005 firm-groups in the tests
with the Dechow & Dichev (2002) model. The explanation for the two outliers are that for Italy 2007,
the number of observations is too few with only 12 observations in the sample which undermines the
power of the judgment that there’s a lasting low quality effect. The effect could be due to some outlier
firms. While for Italy 2005, the results may also reflect a lasting effect of low accounting qualities after
the IFRS adoption. However, the tests with the McNichols (2002) model displayed in Table 2 show that
Italy 2005 experience an increase in accounting quality on the second year after IFRS adoption. For
Italy 2005, the R-squared of the measurements with the McNichols (2002) model is 75.49% which is
much higher than the 20.14% of the measurements with the Dechow & Dichev (2002) model. The results of the second type of tests were displayed in Table 3, which reflect the change of the same firms
throughout the three-year period around the IFRS adoptions. These results are in general consistent
with the trends reflected by Table 1 and 2. Some inconsistent effects of tests with the Dechow &
Dichev (2002) model could be overwhelmed by the results with higher explanatory power of tests with
the McNichols (2002) model. The results from the McNichols (2002) model give stronger support for
the main findings than the results with the Dechow & Dichev (2002) model. Only two outlier groups
were not explainable by tests with both models: the Italy 2008 and Italy 2009 firms group. One of the
explanations for this is that the observations in the tests of these two groups are few, thus this result
11


may be caused by some outlier firms which might also have caused the abnormal results in the first
type of tests. To summarize, the tests of this study indicate strongly that firms experience a decrease in

accounting quality on the first year after IFRS adoption and an increase on the second year.
An explanation for the finding that earnings quality of private firms decrease with IFRS adoption is that the new standard have low efficiency in application or the enforcement on the private firms
who chose to report in IFRS is slack. Thus the firms that adopted IFRS make inaccurate predictions in
the accruing process of accounting due to either the unfamiliarity with the new standard or adverse selection. Christensen, Hail, & Leuz (2013) examines the public firms and find that enforcement explain
the firms' decrease in cost of capital better than mandatory IFRS change. Some surveys have shown a
relatively high degree of unclarity in the practical application of certain rules after IFRS adoption1.
Daske, Hail, Leuz, & Verdi (2013) shows that their result “is consistent with the notion that firms have
substantial discretion in how they adopt and apply IFRS.” To be complete, the increase effect on the
second year after IFRS adoption may be caused by competition in satisfying the demand of report-users
for higher-quality reporting.
The finding of this study may seem counter-intuitive since that some studies on public firms
such as Leuz & Verrecchia (2000), Gkougkousi & Mertens (2010) and Tan, Wang, & Welker (2011)
have shown beneficial effects of international accounting standard adoptions in lowering firms' cost of
capital. However, other researches separately studying mandatory and voluntary IFRS adoptions including Christensen, Hail, & Leuz (2013), Daske, Hail, Leuz, & Verdi (2008), and Daske, Hail, Leuz,
& Verdi (2013) have found no such effects or even negative effects. Moreover, for public firms, the
economic benefits of adopting an international accounting standard might be reflected in changes in
their cost of capital. While for private firms, it is still an open question in what form might the effects
reveal themselves.
One notable conflict of findings is the conclusion of Bassemir & Novotny-Farkas (2013) in the
effect of IFRS adoption on the earnings qualities of private firms. Their study compares the adopting
firms’ earnings variability, and earnings management towards targets with that of the comparable German GAAP firms. They find that “IFRS firms have significantly higher variability of earnings than the
control group.” However, “the variability of earnings relative to the variability of cash flows is only
insignificantly higher for IFRS firms. Therefore, the higher variability of net income might simply be
due to higher volatility of cash flows for IFRS firms.” They conclude that “taken together, the results
suggest that IFRS firms exhibit, on average, a higher earnings quality than German GAAP firms. However, these results are likely to be attributable to significant differences in the firm characteristics between the IFRS and the full control sample.” Their study focuses on the difference between IFRS
adopters and non-IFRS adopters. This study differs in the approach by observing the changes of IFRS
adopters' accrual estimation errors over time. The tests are more straightforward in that the accounting
qualities of the adopting firms were directly comparing with their own past and future levels. Besides,
their use of small positive income is not a reliable proxy for earnings quality, as suggested by Dechow,
Ge & Schrand (2010): “the use of small profits as a proxy for earnings management more generally is

unsubstantiated.” In addition, the accrual estimation error which was used by this study is a closer way
in modeling the accrual process than the variability of earnings which together with small positive income were used to produces their strongest proof of IFRS firms' earnings quality improvements in
Bassemir & Novotny-Farkas (2013)2.

See Glaum, M, Street, D, and Vogel, Silvia (2007). Making acquisitions transparent – an evaluation of M&A-related IFRS
disclosures by European companies in 2005. PricewaterhouseCoopers AG WPG.
2
See Table 4 of Bassemir & Novotny-Farkas (2013).
1

12


VI.

Conclusion

Based on the sample of 7,043 private European firms who adopted IFRS during the period 2003 to
2010, this study examines the changes of the accounting qualities of private firms around the IFRS
adoption event. The methodology for measuring accounting quality is from Dechow & Dichev (2002)
by modeling the accrual process as the current accruals arise following some cash flows and in anticipation of others in the immediately adjacent periods. The difference between the amount accrued and
the amount realized is characterized as the estimation error. The empirical method uses the adjacent
three-year cash flows to explain the working capital accruals, and use the standard deviations of residuals as proxies for estimation errors. The higher estimation errors stand for lower accounting qualities.
In order to observe the changes in accounting quality over time, I put the firms with the same adoption
year into country-year groups. Then I take two approaches to measure their accounting qualities. In the
first approach, I measure the accounting qualities of each country-year groups. In the second approach,
I pick the firms with financial data and adoption information of 3 consecutive years, and make tests on
these firms. The results of the two approaches are consistent. The results show a decrease of accounting
quality on the IFRS adoption year and an increase one year after. The results are consistent after controlling for firm sizes and financial leverages. In light of the shortcomings in explaining discretionary
accruals of the Dechow & Dichev (2002) model, the McNichols (2002) model which adds in two variables was used. The tests give even stronger evidence for the findings. This thesis contributes to the

discussion of the effects of standard changes on firms’ financial reporting behaviors. The accounting
standards influence the accrual process which bridges the fundamental performance of a firm with the
reported earnings. The findings of this study are especially interesting due to the sample of private
firms which is a highly under-studied area given that private firms consist a majority part in the market.

13


References
Bae, K., Tan, H., and Welker, M. (2008). International GAAP differences: the impact on foreign analysts. The Accounting Review, 83, 593-628.
Ball, R., Robin, A., and Sadka, G. (2008). Is financial reporting shaped by equity markets or by debt
markets? An international study of timeliness and conservatism. Review of Accounting Studies,
13, 168-205.
Ball, R., and Shivakumar, L. (2005). Earnings quality in UK private firms: comparative loss recognition timeliness. Journal of Accounting and Economics, 39, 83-128.
Bassemir, M., and Novetny-Frankas, Z. (2013). IFRS adoption, reporting incentives, and earnings quality in private firms. Working paper.
Basu, S. (1997). The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics, 24, 3-37.
Beuselinck, C., Joos, P., and Van Der Meulen, S. (2007). International earnings comparability. Working paper, Tilburg University.
Burgstahler, D., Hail, L., and Leuz, C. (2006). The importance of reporting incentives: earnings management in european private and public firms. The Accounting Review, 81, 983-1016.
Christensen, H., Hail, L. and Leuz, C. (2013). Mandatory IFRS reporting and changes in enforcement.
Forthcoming in Journal of Accounting and Economics.
Daske, H., Hail, L., Leuz, C. and Verdi, R. (2008). Mandatory IFRS reporting around the world: early
evidence on the economic consequences. Journal of Accounting Research, 46, 1085-1142.
Daske, H., Hail, L., Leuz, C. and Verdi, R. (2013). Adopting a label: heterogeneity in the economic
consequences around IAS/IFRS adoptions. Journal of Accounting Research, 51, 495-547.
Dechow, P., and Dichev, I. (2002). The quality of accruals and earnings: the role of accrual estimation
errors. The Accounting Review, 77, 35-59.
Dechow, P., Ge, W., and Schrand, C. (2010). Understanding earnings quality: a review of the proxies,
their determinants and their consequences. Journal of Accounting and Economics, 50, 344-401.
De Franco, G., Kothari, S., and Verdi, R.S. (2011), The benefits of financial statement comparability.
Journal of Accounting and Economics, 49, 895-931.

EC (Commission of the European Communities), (2002). Regulation (EC) No. 1606/2002 of the European Parliament and of the Council of 19 July 2002 on the Application of International Accounting Standards.
Gkougkousi, X., and Mertens, G. (2010). Impact of Mandatory IFRS Adoption on the Financial Sector.
Working paper, Rotterdam school of management.
Graham, J., Campbell, H., and Rajgopal, S. (2005). The economic implications of corporate financial
reporting. Journal of Accounting and Economics, 40, 3-73.
La Porta, R., Lopez-de-Silanes, F., Shleifer, A., and Vishny, R. (1998) Law and finance. Journal of Political Economy, 106, 1113-1155.
Leuz, C., Nanda, D., and Wysocki, P. (2003). Earnings management and investor protection: an international comparison. Journal of Accounting and Economics, 69, 505-527.
Leuz, C., and Verrecchia, R. (2000). The economic consequences of increased disclosure. Journal of
Accounting Research, 38, 91-124.
Tan, H., Wang, S., & Welker, M. (2011). Analyst following and forecast accuracy after mandated IFRS
adoptions. Journal of Accounting Research, 49, 1307-1357.
McNichols, M. (2002). Discussion of the quality of accruals and earnings: the role of accrual estimation errors. The Accounting Review, 77, 61-69.

14


Tables
Table 1a
This table shows the accounting qualities of different firms for 5 country-year groups of firms at each
year. The results displayed are the estimates of the standard deviations of the residuals 𝜎(𝜀𝑡 )(the higher
numbers indicate lower accounting quality) using Dechow & Dichev (2002) model which is
𝛥𝑊𝐶𝑡 = 𝑏0 + 𝑏1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝑏2 ∗ 𝐶𝐹𝑂𝑡 + 𝑏3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝜀𝑡 ,
with the variables WC and CFO denoting working capital and the cash flows respectively. 𝛥𝑊𝐶 was
calculated by subtracting the working capital of the previous year from the working capital of the testing year. To report reliable empirical results, I only take measurements of country-year groups of at
least 20 firm observations. The estimates of the accounting qualities after the IFRS adoption were put
in bold fonts. The Obs. rows report the number of firm observations in the tests.
Country
& adoption year

No. of 1999

firms

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

UK 2009

651

1437

1180

2219

758

1267

1311

1098

968

1010

2640

106

263

290

313

336

373

377

410

484

551

445

272

2426

N/A

N/A

187

769

8572

1050

1458

2473

N/A

6

6

3

3

6

11

23

28

19

12

2

4182

N/A

Obs.

1622

Italy 2007
Obs.

36

Italy 2006
Obs.

3671
313

Italy 2005
Obs.

81

Germany
2008
Obs.

3936 59777 10718 7983

5401

3638 34590 2727

24

29

32

34

40

75

91

77

33

11

2

953

2715

3460

2291

4405

4187

5722

5789

978

1317

N/A

12

19

20

22

28

57

50

38

15

5

0

N/A 33731 26392 40991 20556 46001 47625 12670 6866 43655 13153
237

0

12

22

44

59

15

76

83

116

162

174

101

Table 1b
This table shows the accounting qualities of different firms for 5 country-year groups of firms at each
year. The results displayed are from the same tests as table 1a but controlling for firm sizes and financial leverages. The results are the estimates of the standard deviations of the residuals 𝜎(𝜀𝑡 )(the higher
numbers indicate lower accounting quality) using Dechow & Dichev (2002) model which is
𝛥𝑊𝐶𝑡 = 𝑏0 + 𝑏1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝑏2 ∗ 𝐶𝐹𝑂𝑡 + 𝑏3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝑏4 ∗ 𝑆𝐼𝐸𝑍 + 𝑏5 ∗ 𝐿𝐸𝑉𝐸𝑅𝐴𝐺𝐸 + 𝜀𝑡 ,
with the variables WC and CFO denoting working capital and the cash flows respectively. 𝛥𝑊𝐶 was
calculated by subtracting the working capital of the previous year from the working capital of the testing year. The variable SIZE represents the firm sizes, which is measured by total assets of the firms.
LEVERAGE stands for financial leverage and is calculated as long-term debt divided by total assets.
To report reliable empirical results, I only take measurements of country-year groups of at least 20 firm
observations. The estimates of accounting quality of the firms after IFRS adoption were put in bold
fonts. The Obs. rows report the number of firm observations in the tests. The column “No. of firms” are
the number of firms under testing for each group.
Country
& adoption year

No. of 1999
firms

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

UK 2009

960

2014

1520

3053

913

1651

1684

1360

1290

1437

3914

80

194

222

236

262

285

301

327

372

400

309

606

N/A

N/A

N/A

N/A

905

9478

1147

2177

4357

N/A

6

6

3

3

6

11

23

28

19

12

2

6655

5016

3951

N/A

Obs.

1622

Italy 2007
Obs.

36

Italy 2006
Obs.

2331
313

Italy 2005
Obs.

81

Germany
2008
Obs.

1707 28620 3773

2834 38081 1810

24

29

32

34

40

75

91

77

33

11

2

1544

3652

3772

2612

5425

4760

7048

6796

1401

N/A

N/A

12

19

20

22

28

57

50

38

15

5

0

N/A 14714 51837 37450 16359 53925 54155 17203 8300 59707 18329
237

0

12

22

44

59

16

76

83

116

162

174

101


Table 2
This table shows the accounting qualities of different firms for 4 country-year groups of firms at each
year. The results displayed are the estimates of the standard deviations of the residuals 𝜎(𝜈𝑡 )(the higher
numbers indicate lower accounting quality) using model suggested by McNichols (2002) which is
𝛥𝑊𝐶𝑡 = 𝛽0 + 𝛽1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝛽2 ∗ 𝐶𝐹𝑂𝑡 + 𝛽3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝛽4 𝛥𝑆𝑎𝑙𝑒𝑠𝑡 + 𝛽5 𝑓𝑖𝑥𝑒𝑑𝑎𝑠𝑠𝑒𝑡𝑠 + 𝜈𝑡 ,
with the variables WC and CFO denoting working capital and the cash flows respectively. 𝛥𝑊𝐶 was
calculated by subtracting the working capital of the previous year from the working capital of the testing year. 𝛥Sales was calculated by subtracting sales of the previous year from sales of the testing year.
To report reliable empirical results, I only take measurements of country-year groups of at least 20 firm
observations. The estimates of the accounting qualities of the firms after IFRS adoption were put in
bold fonts. The Obs. rows report the number of firm observations in the tests. The column “No. of
firms” are the number of firms under testing for each group.
Country & adoption

year

No. of
firms

Italy 2007
Obs.

36

Italy 2006
Obs.

313

Italy 2005
Obs.

204

Germany 2008
Obs.

237

1999

20002002

2003

2004

2005

2006

2007

2008

2009

606

N/A

N/A

905

9478

1147

2177

4357

N/A

6

12

0

11

23

28

19

12

2

N/A

N/A

7819

6205

4451

N/A

0

0

29

65

76

77

33

11

2

N/A

N/A

807

2137

5578

3499

823

N/A

N/A

0

0

12

41

42

38

15

5

0

N/A

N/A

0

0

3902 35090 1837

10809 33683 48998 12918 6579 42838 11931
59

17

76

82

115

160

173

101


Table 3
This table shows the accounting qualities of the same firms during the 3 years around the IFRS adoptions for 8 country-year groups of firms. The results displayed are the estimates of the standard deviations of the residuals 𝜎(𝜀𝑡 )(the higher numbers indicate lower accounting quality) using Dechow &
Dichev (2002) model which is
𝛥𝑊𝐶𝑡 = 𝑏0 + 𝑏1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝑏2 ∗ 𝐶𝐹𝑂𝑡 + 𝑏3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝜀𝑡 ,
with the variables of WC denoting working capital and CFO denoting the cash flows from the data-set.
𝛥𝑊𝐶 was calculated by subtracting the working capital of the previous year from the working capital
of the testing year. The rows with “McNichols (2002) model” behind the country-year entry are the estimates of the standard deviations of the residuals 𝜎(𝜈𝑡 )(the higher numbers indicate lower accounting

quality) using the model suggested by McNichols (2002) which is
𝛥𝑊𝐶𝑡 = 𝛽0 + 𝛽1 ∗ 𝐶𝐹𝑂𝑡−1 + 𝛽2 ∗ 𝐶𝐹𝑂𝑡 + 𝛽3 ∗ 𝐶𝐹𝑂𝑡+1 + 𝛽4 𝛥𝑆𝑎𝑙𝑒𝑠𝑡 + 𝛽5 𝑓𝑖𝑥𝑒𝑑𝑎𝑠𝑠𝑒𝑡𝑠 + 𝜈𝑡 .
𝛥𝑆𝑎𝑙𝑒𝑠 was calculated by subtracting sales of the previous year from sales of the testing year. To report
reliable empirical results, I only take measurements of country-year groups of at least 20 firm observations. Since the UK data lack information on the sales entry, they are inapplicable for the McNichols
(2002) model. The firms in the UK 2009 and Italian 2009 groups are only sufficient for estimation till
the year of IFRS adoption, due to the lack of data in 2011. The column “No. of firms” are the number
of firms under testing for each group. The 𝑅 2 columns indicate the explanatory level of each regression,
and were displayed for comparing the two testing models.

18


Country & adoption
year

No. of firms

Result one 𝑅 2 (in Result on 𝑅 2 (in
year previous %) the adoption %)
to adoption:
year: T
T-1

Result on
the next
year after
adoption:
T+1

𝑅 2 (in

%)

UK 2005

34

6682.67

9966.34

UK 2009

411

1275.24

2885.89

Italy 2005

118

3619.10

0.13

3640.14

53.08

3686.39

7.23

Italy 2005: McNichols
(2002) model

111

2685.39

56.65

3494.94

36.73

3432.84

39.01

Italy 2006

169

8305.33

14.81

27564.97

2.02

4616.94

12.96

Italy 2006: McNichols
(2002) model

169

7937.65

23.41

23771.31

28.16

3780.16

43.31

Italy 2007

76

10437.62

27.16

38780.09

24.81

17780.20

78.09

Italy 2007: McNichols
(2002) model

76

10176.09

34.72

38097.36

34.33

3821.62

99.12

Italy 2008

57

28607.18

16.50

27639.62

23.37

6123.87

13.79

Italy 2008: McNichols
(2002) model

57

6194.36

96.55

5142.42

97.81

4687.57

57.41

Italy 2009

51

3827.04

35.95

2366.92

79.10

Italy 2009: McNichols
(2002) model

51

3855.91

39.25

2428.76

80.56

Germany 2008

76

13342.22

12.89

15145.70

34.80

14593.76

1.81

Germany 2008:
McNichols (2002)
model

76

12700.65

24.31

14716.99

40.68

12431.14

35.49

19

7793.24