Does Mandatory Adoption of International Financial Reporting ...

Does Mandatory Adoption of International Financial ReportingStandardsIncrease Investment Efficiency?ByGary C. Biddle, The University of Hong Kong, China,Carolyn M. Callahan, Fogleman College of Business, University of Memphis,Hyun A Hong, Fogleman College of Business, University of Memphis, andRobin L. Knowles, McCoy College of Business, Texas State UniversityUpdated October 2011

studies have further drawn a distinction between voluntary and mandatory adoptions of IFRS(Ashbaugh 2001 finding lower cost of capital (Daske et al. 2008; Li 2010), increased marketliquidity (Daske et al. 2008) and positive stock market reactions to be associated with (anincreased likelihood of) IFRS mandatory adoptions in the EU (Armstrong et al. 2010; Christensenet al. 2007). Kim et al. (2010) find voluntary adopters enjoy lower bank loan rates and lessrestrictive debt covenants than non adopters. Ahmed et al. (2011) find mandatory adoptions ofIFRS to be associated with improved accounting quality with Cascino and Gassen (2010)providing evidence of greater balance sheet comparability.This study extends this literature by examining the effects of mandatory IFRS adoptions onthe economic fundamental of firms’ capital investment decisions.Specifically, we examineassociations between IFRS adoptions and two measures of firm-level capital investmentefficiency: investment-cash flow sensitivity and value-enhancing risk taking. Investment-cashflow sensitivity is a classic measure of investment efficiency in the corporate finance literature(e.g., Fazzari et al. 2000, Love 2003, Malmendier and Tate 2005). However, Kaplan and Zingales(2000) caution that investment cash-flow sensitivity may reflect financial constraints in addition toinvestment policy efficiency. Thus, we also examine a second proxy for capital investmentefficiency – the value-enhancing risk-taking activities undertaken by firms using a measure fromJohn et al. (2008). Drawing on the intuition that riskier investments have more volatile cash flows,they show that investment decisions made by firms with stronger investor protections are lessrisky and more value-enhancing.We employ a difference-in-differences research design to best isolate relations between IFRSadoptions and changes in firm-level investment efficiency for both voluntary and mandatoryadopters. We utilize same-country voluntary adopters to control for the effects of country-specificand macro-economic factors. In sensitivity analysis, we further (e.g., Daske et al. 2008) employas controls a random sample of firms from non-adopting countries.2

Our primary sample consists of 31,476 firm-year observations for 10,340 firms that adoptedIFRS for the first-time during the period 2001 to 2008. We find mandatory adoptions of IFRS tobe significantly associated with enhanced capital investment efficiency measured by bothinvestment cash-flow sensitivity proxies, whereas voluntary IFRS adopters show no significantchange. Mandatory IFRS adopters likewise exhibit shifts to more optimal, risk-adjusted levels ofcapital investment. These results are robust to alternative measures and controls.Whereas several studies have found enhanced capital market efficiencies followingmandatory IFRS adoptions in countries with strong legal and institutional characteristics (Daske etal. 2008, Li 2010, Lee et al. 2008, Wang and Welker 2010), Schleicher et al. (2010) find enhancedcapital investment efficiencies in countries with small equity markets, highly concentratedownership, poor disclosure levels and weak enforcement environments. This study finds greatergains in capital investment efficiencies for IFRS adopters in countries whose prior accountingstandards diverged more from international standards. This finding lends support to an emergingcontrast between the effects of IFRS on capital market and capital investment efficiencies.Our research design differs from prior studies in several respects. First, our sample spans 18countries from the EU and eight from outside the EU. 1Second, our research design includesvoluntary IFRS adopters to control for the effects of country-specific factors and macroeconomicshocks.Third, we examine value-enhancing risk taking as a second proxy for investmentefficiency in addition to investment-cash flow sensitivity following Kaplan and Zingales (2000).Finally and importantly, our research design tests legal, institutional and accounting factorsindependently to isolate their separate effects on firm-level capital investment efficiency. By sodoing, we are able to document that the use of IFRS is associated with increased firm-level capitalinvestment efficiency due to the effects of enhanced disclosures and enhanced comparability of1 In comparison, Schleicher et al. (2010) examine 5,655 firms from six EU countries, an 82%smaller sample size. Daske et al. (2008) use firms in non-adopting countries as a control sample,with inferences based on mandatory adopters that comprise less than 11% of their sample.3

accounting information). 2We further find that manufacturing firms exhibit the largest increases incapital investment efficiency after adopting IFRS.Collectively, our findings suggest thatmandatory IFRS adoptions benefit capital providers via enhanced disclosures and enhancedcomparability that allow and motivate managers to invest capital more efficiently.Our study contributes to the accounting literature in several ways. Importantly it is the first toprovide direct empirical evidence regarding whether firm-level capital investment efficiencyincreased with mandatory IFRS adoptions as proponent predicted. Second, we employ a secondcapital investment efficiency measure from John et al. (2008) reflecting firms’ value-enhancingrisk-taking behavior to complement and confirm findings obtained from examining investmentcash-flow sensitivity following the advice of Kaplan and Zingales (2000). Finally, our designexploits controls provided by firms from 18 EU and eight non-EU countries and voluntary IFRSadopters.This paper proceeds as follows: section 2 provides a review of literature and developshypotheses to be tested; section 3 discusses data, sample selection criteria and research design;section 4 presents findings; section 5 provides additional analysis; and section 6 concludes.2. Background and Hypothesis DevelopmentFinancial economics theories argue that firms’ suboptimal capital investment processes arelargely driven by the information asymmetry between firms and outside capital providers. Somefinance theories demonstrate how the ex ante information asymmetry between managers andoutside capital suppliers influences how a firm allocates its capital to investment opportunities.Other theories highlight how the ex post information asymmetry between shareholders andbondholders renders firms’ investment policy suboptimal (Jensen and Meckling 1976; Myers2 This contrasts with Schleicher et al. (2010) who compare “insider” and “outsider” economiesdefined by stock market sizes, ownership concentration, investor rights, disclosure levels and legalenforcement.4

1977). For example, Jensen and Meckling (1976) show that managers of a levered firm, who aregenerally better informed than bondholders, expropriate bondholders’ fixed claims by undertakingrisky projects, often with negative NPV. Myers (1977) show that the information asymmetrybetween shareholders and bondholders in a highly levered firm leads shareholders to rejectpositive NPV projects when the yields of the projects are likely transferred to bondholders. Thesestudies indicate that information asymmetries can cause capital investment processes to besuboptimal.If information asymmetries between managers and outside capital suppliers contribute tosuboptimal investment policies, then a reduction in this asymmetry could ameliorate the problem.The adoption of better accounting policies and a subsequent increase in reporting quality couldreduce this asymmetry; Biddle and Hilary (2006) find that reporting quality is negativelyassociated with the sensitivity of firms’ investment to cash flow. These results are upheld in aconcurrent study using private company data by Chen et al. (2011), who find that privatecompanies’ investment cash flow is negatively associated with accounting quality (proxied bydiscretionary accruals, discretionary revenues and total current accruals).The adoption of a single set of global standards could reduce information asymmetry byimproving the level of comparability of financial statements, therefore improving investors’ abilityto identify good (and bad) investment opportunities. Comparability across companies and acrosscountries could improve after the adoption of IFRS if investors, financial analysts, auditors,regulators and other stakeholders no longer need to understand financial statements that areprepared using different accounting standards from many jurisdictions, reducing informationprocessing costs (Cox 2007). Aharony et al. (2010) study the value relevance of severalaccounting information items before and after the mandatory adoption of IFRS in the EU. Theyfind that the value relevance of goodwill, research and development expenditures, and property,plant and equipment revaluations is positively associated with the level of deviation between local5

accounting standards and IFRS, suggesting that the informativeness of these accounting items toinvestors increases after the mandatory adoption of IFRS.In addition, the adoption of accounting standards that require a higher degree of disclosurecan enable outside capital providers to more effectively compare value-creating investmentprojects with value-destroying investment projects. Leuz and Verrecchia (2000) find that Germanfirms that commit to increased levels of disclosure by voluntarily adopting InternationalAccounting Standards (IAS) or US Generally Accepted Accounting Principles (GAAP)demonstrate improved metrics that are associated with reduced information asymmetry. Similarly,Li (2010) shows that the mandatory introduction of IFRS in the EU increases disclosure levels,resulting in lower cost of equity capital by an average of 47 basis points. If the disclosure levelincreases from compliance with the reporting requirements of IFRS, managers’ investmentpolicies could become more visible to investors, increasing the transparency of firms’ investmentpolicies and reducing information asymmetry.As the level of disclosure and the comparability of financial information increases, agencyproblems stemming from information asymmetry with outside capital providers should decrease.Increased financial reporting quality, for example, facilitates the identification of positive NPVprojects by outside capital providers, therefore it should be associated with reduced adverseselection problems (e.g., capital rationing by shareholders) that firms might encounter whenissuing securities to finance positive NPV projects. Additionally, increased accountingtransparency enhances external monitoring to reduce insiders’ dysfunctional behavior such asmoral hazard (Antle and Eppen 1985), empire building (Jensen and Meckling 1976; Hope andThomas 2008), free cash flow problems (Jensen 1986) and escalation of commitment (Staw 1981;Kanodia et al. 1989), among others. Therefore, our first hypothesis stated in alternative form is:Hypothesis 1: Firm-level capital investment efficiency increases after the mandatory adoptionof IFRS.6

Legal and political institutionsIFRS requires a higher level of disclosure in financial reporting relative to most nationalaccounting standards (Ashbaugh and Pincus 2001; Ding et al. 2007); an increased level ofdisclosure is linked to increased accounting quality and decreased information asymmetry betweencontrolling shareholders and outside capital suppliers (Biddle and Hilary 2006). The improvedfinancial reporting environment could increase the effectiveness of oversight and discipline thatinternational financial intermediaries provide to markets, reducing the opportunity for controllingshareholders to expropriate returns from outside capital suppliers by undertaking value-destroyinginvestment projects. Therefore, minority investors should be able to use the enhanced disclosuresrequired under IFRS to identify dysfunctional investment processes of controlling shareholders.On the other hand, a large body of the IFRS literature finds improved corporate governanceconsequences only for firms domiciled in countries with strong legal environments. For example,Bae et al. (2008) and Byard et al. (2010) find that the number of financial analysts following thefirm increases after the adoption of IFRS only in countries with strong legal and politicalinstitutions, suggesting that the effects of the mandatory switch may be significant only in thesecountries. Wang and Welker (2010) examine the association between equity issuance and buy andhold returns with the unexpected change in prior year net income after the mandatory adoption ofIFRS for firms in Australia and 14 EU countries. They find a stronger relationship between thechange in reported accounting performance and market value for firms in countries with strongerlegal institutions.Prior to the date to mandatorily adopt IFRS, regulation and enforcement in EU countriesvaried widely, with The Netherlands at one extreme of the spectrum having no independentregulatory oversight and a reporting environment viewed as “permissive.” Brown and Tarca(2005) describe a regulatory environment where compliance with accounting standards, evenwithin the public auditing profession, was recommended instead of required. The introduction of7

IFRS in many jurisdictions is accompanied by concomitant institutional developments to increaseregulatory oversight and enforcement, most notably in the EU (Brown and Tarca 2005). The EUnow requires countries to take appropriate measures to ensure compliance with IFRS (EC 2002),therefore we can expect a more uniform and on average greater focus on enforcement andcompliance with accounting standards. Additionally, regulatory reform and increased enforcementin the EU can serve as a model to non-EU countries who also introduce the mandatory use ofIFRS.An improvement in the oversight function of regulatory institutions and in the enforcement ofcompliance with accounting standards mandated by IFRS should have a varied effect acrosscountries depending on the previous level of investor protections. These benefits could be moresignificant in countries where investor protection mechanisms are relatively weaker before themandatory introduction of IFRS. In contrast, the benefits could be marginal for countries whichalready have strong investor protection mechanisms in place. This is consistent with research bySchleicher et al. (2010), who find that the effects of the mandatory adoption of IFRS upon firms’investment-cash flow sensitivity in selected EU countries are significant only in “insider”economies where investors have poor legal protections from insiders’ self-serving investmentpolicies, while the investment efficiency effects are insignificant in “outsider” economies whereinvestors enjoy strong legal protections.Given the above competing arguments, we do not predict whether the investment efficiencyeffects of the IFRS mandate are more significant in weaker or stronger legal/politicalenvironments. Our second hypothesis stated in alternative form is:Hypothesis 2: after the mandatory adoption of IFRS, the increase in investment efficiency forfirms domiciled in countries with relatively weak legal/political institutions is different thanfor firms domiciled in countries with relatively strong legal/political institutions.8

Concentration of corporate ownershipShleifer and Vishny (1997) identify costs associated with concentrated corporate ownership,i.e., large shareholders who exert control over the management and assets of the firm. These largeshareholders can expropriate assets from the firm, in effect redistributing its wealth away fromsmaller shareholders through the pursuit of personal objectives. This behavior is more severeamong firms that have concentrated ownership structures (La Porta et al. 1998). In their study onthe ownership structure of large firms in 27 countries they demonstrate that, except in countrieswith strong shareholder protection mechanisms, the ownership of large firms is typicallyconcentrated among families or the state. The concentration of ownership is achieved through theuse of various mechanisms such as pyramids and dual class share structures, among others. Thesemechanisms enable controlling shareholders to have disproportionately greater controlling powerover the firm and its assets relative to their cash flow rights. Several finance and accountingstudies show that concentrated ownership and the separation of control rights and cash flow rightsare significantly associated with value destruction (Claessens et al. 2002; Faccio and Lang 2001).Wurgler (2000) further emphasizes that the informational asymmetry between insiders and outsidecapital suppliers associated with ownership concentration decreases the efficiency of firms’ capitalallocation processes.Under IFRS, companies are required to disclose more comprehensive information relative tolocal accounting standards (Ding et al. 2007); this higher degree of disclosure requirements isexpected to reduce information asymmetry between controlling shareholders and outside capitalsuppliers. Reduced information asymmetry after the adoption of IFRS should allow current andpotential outside capital suppliers to more easily identify controlling shareholders’ dysfunctionalinvestment processes (e.g., under- and over-investment). Thus after the adoption of IFRS, outsidecapital suppliers monitor and discipline controlling shareholders’ self-serving investment policies(Cuijpers and Buijink 2005). If the disclosure of more comprehensive financial information9

facilitates more effective monitoring mechanisms, controlling shareholders should not be able toexpropriate wealth from outside capital suppliers as easily by undertaking value-destroyinginvestment projects. A reduction in expropriation risk can decrease shareholder concentration byimproving outside capital suppliers’ ability to identify firms that are attractive investment targets.If this is the case, firms with valuable growth opportunities that report their financial statements incompliance with IFRS should be able to attract sufficient external capital to finance profitablegrowth opportunities, increasing the efficiency of firms’ investment policies.On the other hand, prior studies caution that unless firms’ reporting incentives provide asufficient basis to encourage transparency, the adoption of IFRS could be in name only. Daske etal. (2009) note that reporting incentives and actual reporting behavior play a major role in theeffects associated with the voluntary adoption of IFRS. While they find that the voluntaryadoption of IFRS is associated with positive market effects (e.g., increased market liquidity,reduced cost of capital) on average, this effect is driven by firms that are serious about increasingfinancial transparency. They conclude that the greater effect is from a change in reportingincentives and actual reporting behavior rather than by the adoption of IFRS per se.Large shareholders exert control over the management and assets of the firm withconcentrated corporate ownership, and thus, likely have lower incentives to increase transparencyfollowing the IFRS mandate. If the reporting environment for firms with concentrated ownershipdoes not facilitate transparency after the date of mandatory adoption, it will bias against ourfinding results. Based upon these arguments our third hypothesis, stated in alternate form, is:Hypothesis 3: after the mandatory adoption of IFRS, the increase in investment efficiency forfirms domiciled in countries where corporate ownership is relatively more concentrated isgreater than for firms domiciled in countries where corporate ownership is relatively lessconcentrated.10

Financial disclosures and the comparability of financial informationWe identify two mechanisms through which the adoption of IFRS could be associated withincreased investment efficiency: increased financial disclosures and comparability (Tweedie 2006;Li 2010). Our argument assumes that variability in enforcement across countries decreases withthe mandatory introduction of IFRS, which is consistent with the increased focus on concomitantimprovements in regulatory oversight, as illustrated in the EU (Brown and Tarca 2005). IFRStypically requires a higher level of disclosure and more comprehensive financial information thanlocal accounting standards (Ashbaugh and Pincus 2001; Ding et al. 2007), resulting in increaseddisclosure of financial information and better accounting quality under IFRS compared to localGAAP when compliance is enforced.A higher degree of financial disclosure should facilitate investors’ ability to extract financialinformation needed in the investment process (Hunton et al. 2006). Consistent with this argument,Hope et al. (2006) and Burt and Harnischfeger (2000) show that one of the major reasons for thevoluntary adoption of IFRS is to satisfy investors’ demand for a higher quality of financialinformation. The benefit from increased financial disclosures should be greater for firms incountries which have relatively more opaque local accounting standards compared to IFRS, whilethe mandatory adoption of IFRS is less likely to affect firms in countries that already enjoy highreporting quality.The second mechanism through which compliance with IFRS could increase investmentefficiency is by improving cross-border comparability between firms’ financial reporting. Thispositive informational externality from the enforcement of a single set of uniform accountingstandards results when investors no longer have to translate firms’ financial reporting from localaccounting standards to another using different accounting standards. And, the adoption of IFRSacross multiple jurisdictions should reduce the costs of preparing and comprehending disparatesets of financial reporting (Hope et al. 2006), decreasing estimation risk and home-bias risk related11

to investments across borders. DeFond et al. (2009) provide evidence that the enhancedcomparability resulting from the adoption of IFRS reduces the home-bias of U.S. mutual fundinvestors, increasing their cross-border investment in firms that are mandatory adopters incountries with more transparent informational environments. And research by Cascino andGassen (2010) find that accounting comparability for some financial items has increased after themandatory adoption of IFRS. They find that, except for goodwill, the variance in balance sheetline items reported after the adoption of IFRS decreases relative to the pre-adoption period andrelative to their control group. These results are consistent with the mandatory adoption of IFRShaving a positive impact on the comparability of balance sheet items. The benefits associated withincreased comparability of accounting information after the mandatory introduction of IFRS couldbe more significant in countries whose domestic standard is more disparate to IFRS whenenforcement is effective.Our fourth hypothesis stated in alternate form summarizes the previous discussion:Hypothesis 4: after the mandatory adoption of IFRS, firm-level investment efficiencyincreases for firms domiciled in countries with more opaque accounting standards, and forfirms domiciled in countries whose local standards are the least comparable to IFRS.3. Sample and research designOur sample period begins in 2001, extends to 2008 and is comprised of observations withavailable financial data in Compustat Global Vantage Industrial/Commercial and market data inCompustat Global Vantage Issue from 26 countries which adopt IFRS between 2003 and 2005(see Table 1, Panel A for a list of countries and their adoption dates). Our main analysis oninvestment-cash flow sensitivity includes all industries, but in additional analysis on firms’ risktakingbehaviors, to be consistent with the methodology by John et al. (2008), we focus only onmanufacturing firms. In these additional tests we include only firms with Standard Industrial12

Classification codes (SIC) between 2000 – 3999. All continuous variables are winsorized at theextreme two percentiles.Our research design is motivated by finance theory, which posits that in a perfect capitalmarket, the costs of external capital are identical to those of internal capital (Tobin 1969; Tobin1982; Hubbard 1998). Theoretically, firms’ capital allocation policy is driven by Tobin’s Q-ratio,which is an ex ante proxy for firms’ growth opportunities (Tobin 1969; Hubbard 1998). However,numerous finance and accounting studies show that because of capital market imperfections suchas information asymmetry, the costs of external capital can be higher than internal capital, andfirms often deviate from an optimal capital allocation policy (Jensen and Meckling 1976; Myers1977; Myer and Majluf 1984; Stiglitz and Weiss 1981). For example, firms might forgo growthopportunities because they cannot finance these opportunities with more expensive external capital.As a result, their investment policies are determined by their internally generated cash flows. Priorfinance studies measure the deviation from a firm’s theoretical optimum investment policy as thesensitivity of their capital investments to the level of internally generated cash flows.One potential problem in employing the investment-cash flow sensitivity measure in ourresearch design is that firms’ market-to-book ratio, which is a proxy for Tobin’s Q ratio, isendogenously determined. Therefore, firms’ cash flows may represent firms’ growth opportunitiesthat are not completely captured by the market-to-book ratio. To address this problem, as anadditional robustness test, we also use a heterogeneous two-stage linear regression to estimatefirms’ market-to-book ratio where the first stage regresses market-to-book ratio onto two-yearslagged market-to-book ratio and three-years lagged capital intensity variables, and then use theestimated firm-level market-to-book ratio in the investment cash-flow sensitivity regressionmodels in the second stage (Biddle and Hilary 2006). 33 As an alternative test, we use an average industry-level Q-ratio rather than a firm-level Q-ratio asa proxy for growth opportunities to obtain a more accurate measurement of firms’ growth13

We estimate our models using panel data methodologies with country- and industryspecificfixed effects. We include country and industry fixed-effects using the Fama and French(1997) 48-industry classification in the panel regressions and report coefficients estimated usingstandard errors adjusted with two-dimensional clusters at the industry and country level. Thisshould control for industry-specific and country-specific shocks to firms’ investment processes. 4Invest j,t = β 0,t + β 1,t * OCF j,t-1 + β 2,t * MTB j,t-1 + ε j,t (1)Where:Subscripts i and t identify the firm and year.Invest = capital expenditures, scaled by net property, plant and equipment at the beginning of theyear.OCF = operating cash flows, scaled by net property, plant and equipment at the beginning of theyear.MTB = market to book ratio, measured as the ratio of the market value of equity plus the bookvalue of total assets minus the book value of equity, which are divided by the book valueof total assets.The tests of our hypotheses are based on an extension of the investment-cash flow sensitivitymodel and difference-in-differences analysis methodology, constructed from the estimatedcoefficients from the extended investment-cash flow sensitivity model in equation (1). Theapplication of a difference-in-differences design to the exogenous accounting shock (i.e., theopportunities. Walker (2005) argues that an industry-level Q-ratio is less affected by measurementerror than a firm-level Q-ratio. If the market is informationally efficient, the market value of a firmis determined by any market perceived inefficiency in a firms’ anticipated investment policy aswell as by firms’ growth opportunities (Walker 2005). Hence, we estimate the average investmentand Tobin’s Q for each industry in a given year and country on the basis of the Fama and French(1997) 48-industry classification. For the brevity of exposition in the tables, we do not reportresults based on the investment-cash flow sensitivity regression with industry-level Q ratio, but theresults are qualitatively the same as reported in the current tables, which is based on theheterogeneous two-stage linear regression with firm-level Q ratio.4 In versions of our model that contain time-invariant country-level institutional variables (e.g.,legal and capital market-related indices), country-specific fixed effects would be correlated withthese country-level institutional variables to a complete extent, as suggested by Doidge (2004). Weaddress this concern in sensitivity testing by using a random effects model with country-specificrandom effects in conjunction with the country-specific fixed effects. In this case, coefficientestimates are made using both fixed effects and random effects methodologies.14

mandate to adopt IFRS) enables us to mitigate possible endogeneity issues, omitted variable biasesand other threats to statistical validity (Meyer 1995; Li 2010).To test our first hypothesis, we modify equation (1) by including indicator variables toidentify the type of IFRS adopter (voluntary versus mandatory adopters) and the time period (preversuspost-IFRS implementation). We identify voluntary and mandatory adopters by the dataitem “astd” in Compustat Global. If the data item equals “DI” before (on or after) the date tomandatorily implement IFRS, the firm is classified as a voluntary (mandatory) adopter.Observations with fiscal years before (on or after) the mandatory implementation date areclassified as pre- (post-) IFRS. The inclusion of these two binary indicator variables allows us toclassify firm-year observations into four subgroups, depending on the type of IFRS adopters andthe IFRS adoption time period, and to conduct difference-in-differences analyses to test ourhypotheses.To test our first hypothesis that the mandatory adoption of IFRS is associated with an increasein firm-level capital investment efficiency, we implement the following model:Investment i,t = α + β 1 Mandatory i,t + β 2 Post i,t + β 3 Mandatory i,t * Post i,t + β 4 OCF i,t+ β 5 Mandatory i,t *OCF i,t + β 6 Post i,t *OCF i,t + β 7 Mandatory i,t * Post i,t * OCF i,t+ β 8 MTB i,t + β 9 Mandatory i,t * MTB i,t + β 10 Post i,t * MTB i,t+ β 11 Mandatory i,t * Post i,t * MTB i,t + ∑ Controls + ε i (2)Where:Subscripts i and t identify the firm and year.Mandatory = A binary indicator variable, which takes on a value of one for firm-years if the firmdid not adopt IFRS before the mandatory adoption date for that country.Post = A binary indicator variable, which takes on a value of one for firm-years ending onor after the mandatory adoption date for that country.Controls = US GAAP =A binary indicator variable, which takes on a value of one for firmyearsif the firm also reports in US GAAPUS Listing=A binary indicator variable, which takes on a value of one for firmyearsif the firm also reports on a US exchange.In equation (2) our main interest is the sign and significance of the coefficient β 7 and the sumof the coefficients β 6 and β 7 . The coefficient β 7 represents the incremental effect of the mandatory15

adoption of IFRS on the investment cash-flow sensitivity of mandatory adopters relative tovoluntary adopters. The sum of coefficients β 6 and β 7 estimates the average effect of the adoptionof IFRS upon firms’ investment for mandatory adopters. We expect a negative sign on thecoefficient β 7 as well as on the sum of coefficients β 6 and β 7 , given our expectation that the IFRSmandate mitigates capital market frictions associated with information asymmetry.The conditional effects of various factors upon investment after the adoption of IFRSWe expand our model in equation (2) by adding conditional indicator variables toestimate the relationship between IFRS and investment cash-flow sensitivity conditioned upon: (i)the strength of legal and political institutions; (ii) ownership structure concentration; (iii) thenumber of additional disclosures that are required by IFRS compared to domestic GAAP; and (iv)the number of inconsistencies between local GAAP and IFRS. Each conditional variable is addedto the model one at a time to isolate its effect on the efficiency of firms’ investment policies.Investment i,t = α + β 1 Mandatory i,t + β 2 Post i,t + β 3 Mandatory i,t * Post i,t + β 4 OCF i,t+ β 5 Mandatory i,t * OCF i,t + β 6 Post i,t * OCF i,t + β 7 Mandatory i,t * Post i,t *OCF i,t+ β 8 MTB i,t + β 9 Mandatory i,t * MTB i,t + β 10 Post i,t * MTB i,t+ β 11 Mandatory i,t * Post i,t * MTB i,t + Conditional Variables * { γ 1 Mandatory i,t+ γ 2 Post i,t + γ 3 Mandatory i,t * Post i,t + γ 4 OCF i,t + γ 5 Mandatory i,t * OCF i,t+ γ 6 Post i,t * OCF i,t + γ 7 Mandatory i,t * Post i,t * OCF i,t + γ 8 MTB i,t+ γ 9 Mandatory i,t * MTB i,t + γ 10 Post i,t * MTB i,t + γ 11 Mandatory i,t *Post i,t *MTB i,t } + ε i (3)Where:Conditioning variables are alternatively:Inconsistency between local GAAP and IFRS = an indicator variable that takes the value 1(0) if thenumber of national accounting rules that require different accounting treatmentsfrom those required by IAS is greater (less) than the sample median. Highervalues indicate that local accounting standards diverge from the qualitativelysimilar IFRS to a greater extent. Data is from Nobes (2001).Additional disclosures = an indicator variable that takes the value 1(0) if the number of additionaldisclosures that IAS requires over local GAAP is greater (less) than the samplemedian. Higher values indicate that local GAAP requires a smaller number offinancial disclosures compared to the qualitatively similar IFRS. Data is fromNobes (2001).Rule of law = an indicator variable that takes the value 1(0) if the value of an index representingthe strength of legal enforcement is greater (less) than the sample median. The16

index is from Kaufmann et al. (2007) for the year 2005. Higher values representcountries with higher quality legal enforcement.Control of Corruption = an indicator variable that takes the value 1(0) if the index valuerepresenting the strictness of the control of corruption in the private sector isgreater (less) than the sample median. The index is from Kaufmann et al. (2007)for the year 2005. Higher values represent countries with stronger systems tocontrol corruption in the private sector.Ownership Concentration = an indicator variable that takes the value 1(0) if the averagepercentage of common shares owned by the three largest shareholders in the tenlargest non-financial, privately owned domestic firms in a given country isgreater (less) than the sample median. Data is constructed by La Porta et al.(1998).High Q = an indicator variable that takes the value 1(0) if firms’ market-to-book ratio is greaterthan the median value of market-to-book ratio of the sample.Other variables as defined above.Our main focus in equation (3) is the sign and significance of the sum of coefficients β 6 + β 7 ,and β 6 + β 7 + γ 6 + γ 7 . The sum of coefficients β 6 + β 7 (β 6 + β 7 + γ 6 + γ 7 ) represents the averageeffects from the mandatory adoption of IFRS on the investment cash-flow sensitivity of mandatoryadopters in countries with index values lower (higher) than the sample median for eachconditioning variable (see below). Additionally, the sum of coefficients γ 6 + γ 7 captures theincremental effect of the mandatory switch for mandatory adopters in countries with index valueshigher than median.To test our second hypothesis that after the mandatory adoption of IFRS the change ininvestment efficiency is conditional on the relative strength of legal & political institutions, we usetwo proxies for the strength of investor protection mechanisms as conditioning variables. Thesetwo proxies measure the strength of a country’s legal and political institutional mechanisms; thefirst is from an index by Kaufmann et al. (2007) on the rule of law in the year 2005. The indexindicates the degree of confidence that a country’s citizens have in respect to the quality of its lawenforcement systems. The indicator variable LAW = 1 (0) if a country’s index value is greater(less) than the sample country median, meaning that the country is characterized as having stricterlaw enforcement systems. The second variable is CONTROL, which is drawn from Kaufmann etal. (2007) on the control of corruption in the year 2005. The indicator variable CONTROL = 1 (0)17

if a country’s index value is greater (less) than the sample country median, meaning that a countryis characterized as having stronger systems to control corruption in the private sector. The sum ofcoefficients β 6 + β 7 (β 6 + β 7 + γ 6 + γ 7 ) represents the average effects from the mandatory adoptionof IFRS on the investment cash-flow sensitivity of mandatory adopters in countries where legalinstitutions are weaker (stronger). Additionally, the sum of coefficients γ 6 + γ 7 captures theincremental effect of the mandatory switch for mandatory adopters in countries where legalinstitutions are stronger.To test our third hypothesis, that after the mandatory adoption of IFRS the increase ininvestment efficiency is conditional on the concentration of corporate ownership, we use data fromLa Porta et al. (1998) on average industry concentration in the ten largest non-financial, privatelyowned domestic firms in each country. We use this data to construct an indicator variable,Ownership Concentration, that takes the value 1 (0) if a country’s average ownershipconcentration is greater (less) than the sample country median, where higher values represent alarger percentage of common shares owned by the three largest shareholders. The sum ofcoefficients β 6 + β 7 (β 6 + β 7 + γ 6 + γ 7 ) represents the average effects of the adoption of IFRS onthe investment cash-flow sensitivity of mandatory adopters in countries where the concentration ofownership is lower (higher). Additionally, the sum of coefficients γ 6 + γ 7 captures the incrementaleffect of the mandatory switch for mandatory adopters in countries where ownership is highlyconcentrated among the three largest shareholders.To test our fourth hypothesis, that after the mandatory adoption of IFRS the increase ininvestment efficiency is conditional on the opaqueness of local standards and the degree ofdivergence from international standards, we identify two mechanisms that should proxy for thechange in information asymmetry after the adoption of IFRS. The first mechanism we examine isthe additional number of disclosures required to place national standards on a comparable basiswith IFRS (Nobes 2001). Higher values indicate that national standards provide fewer disclosures18

to financial statement users and are therefore considered less transparent. The indicator variableAdditional Disclosures = 1 (0) if a country’s index value is greater (less) than the median indexvalue, meaning that the national standards are of lower (higher) quality than the median samplevalue. Note that to orthogonalize these accounting indices to the countries’ legal/politicalinstitution characteristics, we regress these two variables, Inconsistency and Disclosures, ontocountries’ legal origin and the log values of GDP in their 1990s, and then take the residuals as aproxy for the size of Inconsistency and Disclosures.The second mechanism is Inconsistency, which represents the divergence between nationalstandards and the more comprehensive, higher quality standards required by IFRS (Nobes 2001).Higher values represent a greater difference between the two standards, which is expected to resultin greater information asymmetry between insiders and investors. The indicator variableInconsistency = 1 (0) if a country’s index value is greater (less) than the median index value,meaning that the national standards are of lower (higher) quality than the median sample value.The sum of coefficients β 6 and β 7 (β 6 , β 7 , γ 6 , and γ 7 ) measures an average effect of the IFRSmandate on firms’ investment cash-flow sensitivity in countries where accounting informationalquality is relatively higher (lower).[Insert Table 1 about here]4. Descriptive Statistics and Empirical ResultsIn univariate analysis, we identify the 26 countries included in our study (see Table 1, PanelA). Our sample includes countries that have more than 30 firms with sufficient accounting andfinance data. Our sample begins in 2001 and ends in 2008 and it consists of 7,200 unique firmsand 31,476 total firm-year observations. Of these, 2,494 firm-year observations also are crosslistedin the United States. The countries that contribute the most unique firms and firm-year19

observations to our study are the United Kingdom, Australia, Germany, France and Singapore. Allcountries in our study require that firms mandatorily adopt IFRS for fiscal years ending on or afterDecember 31, 2005 except Singapore who require adoption on or before December 31, 2003. 5About 41% of our sample is in the post mandatory adoption period, generating a well-balanceddata set between the pre and post mandatory periods. Our sample includes both voluntary 6 andmandatory adopters, with mandatory adopters constituting the majority of firm-year observations,81.3%. The percentage of firms that voluntarily adopt IFRS prior to the mandatory deadline varieswidely by country; Hungary, Austria and Czech Republic (Venezuela, Singapore and Australia)are the countries with the highest (lowest) frequency of firms adopting IFRS voluntarily. Acomparison of our sample voluntary adopters by country with the sample used in Daske et al.(2008) finds a broadly similar pattern; we follow their study in that we do not drop countries withfew observations.Table 1, Panel B presents institutional variables we use in our analysis to study the effect ofmandatory IFRS adoption on investment-cash flow sensitivity. The Rule of Law and the Controlof Corruption indices are from Kaufman et al. (2007); high values indicate stronger legal andpolitical institutions. The Rule of Law and the Control of Corruption indices show a wide range ofvariation in the strength of legal enforcement mechanisms across countries. For example, the Ruleof Law index of Switzerland is 2.00, while that of Venezuela is -1.30. The country with thehighest (lowest) ranking on the Control of Corruption index is Finland (Venezuela) with an indexvalue of 2.59 (-1.04). Also, there is a significant variation in the degree of ownership5 Firms listed in the EU have the option use a “carve-out” that diverges from IFRS as issued by theIASB. However, at a speech given at the Plenary session of the 2009 American AccountingAssociation Annual Meeting in New York City on 4 August 4 2009, Sir David Tweedie states that“….the European carve-out, which is optional, is only used by 29 companies out of 8,000….”6 See footnote 1 for information about our use of firms in non adopting countries as an alternatecontrol group, following Daske et al. (2008).20

concentration across countries (La Porta et al. 1998); Greece, Belgium, Italy and Portugal (UnitedKingdom, France and Sweden) have the greatest (lowest) concentration of ownership.[Insert Table 2 about here]In Table 2 we report descriptive statistics on the raw data for our dependent and continuousindependent variables. A comparison of mean and median values for two of our variables, INVESTand OCF indicate that there is skewness in our sample data, with the mean value of the INVESTvariable being influenced by large positive values, and the mean value of the OCF variable beinginfluenced by negative values. The possible influence of outliers is mitigated by winsorizing thetwo extreme percentiles. The possibility of nonlinear relationships is addressed by transformingthe data following Biddle and Hilary (2006); our main variables (MTB, INVEST, OCF) aretransformed using a log transformation if their values are positive and an arctangenttransformation if their values are negative.[Insert Table 3 about here]In Table 3 we report country-level multivariate regression analysis for investment-cash flowsensitivity separately for voluntary and mandatory adopters. Coefficients are estimated usingstandard errors that are adjusted using a two-dimensional cluster at the industry and country level.We identify a significant decrease to the cash-flow sensitivity of mandatory adopters in severalcountries, most notably Italy, Spain and Portugal while the cash-flow sensitivity of voluntaryadopters in these same countries either increases or does not change. As the voluntary adopterslikely face the same macroeconomic factors as the mandatory adopters, we are able to mitigatethese possibly confounding factors. These three countries score below the median value for the21

Rule of Law and Control of Corruption indices, and both Italy and Portugal are among the top fourcountries in terms of ownership concentration. Only mandatory adopters in Finland andSwitzerland experience a significant increase in their cash flow sensitivities. Both countries scorehigh in terms of the Rule of Law and Control of Corruption indices, with Finland (Switzerland)scoring third place and first place (first place and fourth place) in the respective indices. Ourcountry-level analysis is thus far consistent with our hypotheses.[Insert Table 4 about here]We start our study of the changes of investment-cash flow sensitivity subsequent to themandatory switch, based on the univariate difference-in-differences analysis of our main variables.Table 4 reports mean values of the dependent variable, INVEST, and both continuous independentvariables, OCF and MTB. The difference-in-differences design allows us to compare the changesof investment-cash flow sensitivity between the two groups of firms, voluntary and mandatoryadopters, before and after the date of mandatory adoption. This comparison allows us to controlfor the effects of macroeconomic factors and exogenous shocks, to the extent they have the sameeffect on both groups, by differencing out the changes in the investment-cash flow sensitivity forvoluntary adopters from the changes in the investment-cash flow sensitivity for mandatoryadopters.We report that investment by mandatory adopters increases after the date of mandatoryadoption, while operating cash flow decreases; thus mandatory adopters’ cash flow sensitivitydecreases significantly after the mandatory adoption of IFRS. As the MTB ratio of mandatoryadopters also increases, the increase in investment observed is more likely due to mandatoryadopters’ growth opportunities than due to their internally generated cash-flows. In contrast, overthis same time period, the investments of voluntary adopters increase as do their cash flows,22

suggesting that voluntary adopters’ investment-cash flow sensitivity likely remains the same orbecomes higher in the post-IFRS adoption period. Additionally, a comparison of our sample MTBratio for the pre-adoption and post-adoption periods with figures from Daske et al. (2008) aresimilar in spite of the different time periods.[Insert Table 5 about here]Table 5 reports empirical results from equation (2) to test our first hypothesis, that firm-levelcapital investment efficiency increases after the mandatory adoption of IFRS. Panel A reportsestimated coefficients and one-tailed p-values for the full sample period and with the transitionyear 2005 deleted to eliminate possible confounding effects of the transition to new accountingstandards. Results with and without 2005 data are similar. As the results are unchanged whenexcluding the transition year, our analysis focuses on the full sample.Our results are consistent overall with our univariate results. The coefficient onOCF*Mandatory*PostIFRS is significantly negative, consistent with the cash-flow sensitivity ofmandatory adopters decreasing more significantly after the adoption date relative to the cash-flowsensitivity of voluntary adopters. Note that multiple-interaction variables take on the value zero orthe value of the continuous variable, (OCF or MTB), facilitating the interpretation of multipleinteractionvariables.For ease of exposition, we implement difference-in-differences analysis in Panel B, which isconstructed based on combined coefficients from the multivariate regression model in Panel A ofTable 5 and estimated statistics from the aggregated coefficients. Panel B segments our results intofour groups with voluntary and mandatory adopters reported along the rows and the pre- and postadoptionperiods reported in columns. The upper half of Table 5, Panel B reports the full sampleand the lower half excludes the transition year 2005. We find that after the mandatory adoption23

date, only firms that mandatorily adopt IFRS experience a significant decrease in their investmentcashflow sensitivity; the investment-cash flow sensitivity of voluntary adopters does not changesignificantly.[Insert Table 6 about here]Table 6 reports empirical results from equation (3) to test hypotheses two and three, that theincrease in firm-level investment efficiency after the mandatory adoption of IFRS differsdepending on the strength of legal and political institutions, or on ownership concentration. PanelA reports estimated coefficients and one- or two-tailed p-values when the Rule of Law, Control ofCorruption and Ownership concentration institutional indicator variables are included one at atime in equation (3). The respective indicator variable is set to 1 (0) when the country of domicileis higher (lower) than the sample country median value, where a higher value of the Rule of Law(Control of Corruption) index indicates stricter enforcement (i.e., stronger controls on privatefirms); and a higher value for Ownership concentration represents a higher average ownershippercentage controlled by a few dominant shareholders. To make a fair comparison of the changesof investment-cash flow sensitivity between mandatory adopters and voluntary adopters, wecombine coefficients and re-estimate the statistical significance of the aggregated coefficientsfrom the analysis in Table 6.Hence, for ease of exposition, we report the reconstructed coefficients for each institutionalfactor from Panel A of Table 6, depending on the value of its respective binary indicator variable.When we compare the differences between our treatment and control groups using this design, wecan identify that the investment-cash flow sensitivity decreases significantly after the mandatoryadoption date only for mandatory adopters and voluntary adopters domiciled in countries with aweaker Rule of Law. However, as indicated by Panel B, the decrease in investment cash-flow24

sensitivity for mandatory adopters is much more dramatic than that of voluntary adopters (0.272versus 0.159, p-value=0.083 for voluntary adopters, and 0.519 versus 0.210, p-value < .001 formandatory adopters). Alternatively, in countries with stronger Rule of Law, the cash-flowsensitivity of mandatory adopters remains the same after the mandatory adoption date (0.082versus 0.112, p-value = 0.224 for mandatory adopters). A similar pattern is seen in the middle setof two-by-two results reporting on the Control of Corruption institutional factor. Collectively,these results provide evidence that the mandatory introduction of IFRS is correlated withimproved investor protection mechanisms in countries with weak investor protection mechanisms.In the bottom set of difference-in-differences analyses reporting on the relationship betweenmandatory IFRS adoption and ownership concentration, we report that after the mandatoryadoption date, the decrease of investment-cash flow sensitivity for mandatory adopters issignificant only in countries with a high concentration of ownership (0.167 versus -0.119, p-value< .001 for mandatory adopters). Viewed together, these results provide evidence that themandatory adoption of IFRS appears to mitigate information asymmetry between minority andmajority shareholders in countries where a few investors exert significant control over firms’resources and assets.[Insert Table 7 about here]Results from hypothesis four, that the mandatory adoption of IFRS is correlated with firmlevelinvestment efficiency to a greater extent in countries whose national accounting standardsdiverge from IFRS to a larger degree is reported in Table 7. Panel A reports estimated coefficientsand one-tailed p-values when the institutional indicator variables that proxy for the discrepancy ofdisclosure requirements between national standards and IFRS (Additional Disclosures) and thedegree that national standards are inconsistent with IFRS (Inconsistency) are included one at a25

time in equation 3. The Additional Disclosure indicator variable is set to 1 (0) when the nationalaccounting standards of the country of domicile requires more (fewer) disclosures to equate toIFRS disclosure requirements than sample median value, and the Inconsistency indicator variableis set to 1 (0) when the national accounting standards of the country of domicile has more (less)inconsistencies with IFRS. We report that investment cash-flow sensitivity decreases formandatory adopters (OCF* Mandatory*Institutional factor) after the mandatory switch incountries where the national accounting standards of the country of domicile requires moredisclosures to equate to IFRS disclosure requirements, or has more inconsistencies with IFRS.Panel B reports combined coefficients and re-estimated statistics for the aggregatedcoefficients for each institutional factor when its respective indicator variable first takes the valuezero and then takes the value one. When we compare the differences between our treatment andcontrol groups using this design, we can identify that after the mandatory adoption date mandatoryadopters are associated with a decrease in investment-cash flow sensitivity only in countries wherethe national standards are less comparable to IFRS (0.531 versus 0.291, p-value < .001 in Panel B,and 0.463 versus 0.304, p-value < .001 in Panel C). The national accounting standards of thesecountries have fewer disclosures and more discrepancies between their standards and IFRS beforethe mandatory adoption of IFRS than other countries where national standards more closelyresemble the reporting and disclosure requirements of IFRS before the mandatory adoption date.Over the same time period, voluntary adopters are associated with an increase in cash-flowsensitivity in countries where the national standards provide disclosures that are more comparablewith IFRS.We conclude that these results are consistent with the mandatory adoption of IFRS decreasinginformation asymmetry between outside investors and insiders only when national accountingstandards are not effective in providing investors with sufficient information to be able to identifysub-optimal decision processes by current and potential investment targets. When national26

standards already provide relatively higher quality financial information to investors, themandatory adoption of IFRS does little to change firms’ reporting incentives, and hence does littleto change the effectiveness of communications between insiders and current and potentialinvestors.[Insert Table 8 about here]5. Additional AnalysisIndustry effectsIn additional analysis, we investigate whether industry membership plays a role in influencingthe association between the mandatory adoption of IFRS and the increase in investment-cash flowefficiency. Table 8 reports results from industry-level regressions of investment expenditures ontooperating cash flows and our indicator variables (Mandatory and Post*Mandatory), along with theinteractions between them. Based on this research design, we study cross-sectional variation of thechange of investment-cash flow sensitivity across industries. Firms are sorted into 48 industriesbased on Fama and French’s (1997) industry groups. We include only 26 of 48 industry groupswhich have at least 100 firm-year observations. Of the 26 industries included in our study, onlyseven exhibit a significant relationship between the mandatory adoption of IFRS and investmentcashflow sensitivity, suggesting that the effect of the IFRS mandate is concentrated among certainindustries. The association we find always represents a reduction in the cash-flow sensitivity offirms’ investment policies; six of the seven industries that exhibit a significant relationship aremanufacturing industries. This result is not surprising, given that our dependent variable is capitalexpenditures scaled by property, plant and equipment; these amounts are naturally moreeconomically significant for manufacturing firms. The singular exception is the “restaurants,hotel, motel” industry which is classified in a combination of Services and Trade industries.27

Alternative measure of investment efficiency: risk-takingNext we investigate whether the mandatory adoption of IFRS is associated with a change infirms’ risk-taking behaviors. Our analysis is motivated by John et al. (2008), who find thatcountries with weak investor protections are associated with sub-optimally conservativeinvestment behaviors. They model firm investment and perquisite consumption decisions made byself-interested managers and find that managers avoid value-enhancing risk-taking to secure theirconsumption of perquisites. Their model suggests and their empirical analysis confirms that anincrease in investor protections can mitigate these sub-optimal behaviors. We test whether themandatory adoption of IFRS plays a role in investor protection mechanisms and whether it isassociated with increased value-enhancing risky investments for mandatory adopters.We follow John et al. (2008) to develop three measures to estimate the riskiness of corporateprojects undertaken by managers: RISK1 is the average cross-sectional cash-flow volatility foreach of our four subgroups (mandatory and voluntary adopters, each divided into pre- and post-IFRS time periods), calculated as the average standard deviation of cash flows scaled by totalassets. RISK2 is the average of RISK1 by country. This eliminates the overweighting of firms incountries with more observations or more value-weighted observations. RISK3 calculates anaverage imputed risk score by 2-digit SIC code industry groups in each country over our sampletime period, where each industry is adjusted by the volatility of respective US single businesssegment firms’ cash flows in that industry. More specifically, we calculate the cash flow volatilityin each U.S. 2-digit SIC industry. We then use the calculated cash flow volatility as a benchmarkagainst which we study whether investments in the sample countries after the mandatoryintroduction of IFRS reporting are shifted toward industries with higher cash flow volatility.[Insert Table 9 about here]28

We report our results in Table 9; analyzing the average of each risk-taking proxy in a two-bytwoanalysis allows us to eliminate concurrent macroeconomic factors that affect both mandatoryand voluntary adopters to the same extent. Panel A reports results using RISK1, which is theaverage volatility of each subgroups’ cash flows; Panel B uses a country average of RISK1; andRISK3 used in Panel C is the imputed risk score where the risk-taking behaviors of firms in theIFRS adoption countries are benchmarked against those of U.S. firms. Detailed variabledefinitions are provided in Table 9.Across all three risk measures, we report that value-enhancing risk-taking by mandatoryadopters increases after the mandatory adoption date of IFRS. While similar behavior is noted forvoluntary adopters when RISK1 or RISK2 is the proxy for risk-taking, the increased risk-taking bymandatory adopters is more significant than for voluntary adopters. The increased risk-taking byboth mandatory and voluntary adopter groups may be explained by concurrent macroeconomicchanges in the sample countries’ capital markets, such as the improvement of underlying corporategovernance structures. However, the larger increase in risk-taking by mandatory adopters relativeto voluntary adopters suggests that the IFRS mandate may be the cause of the increase. WhenRISK3 is the proxy used, we still see that risk-taking increases for mandatory adopters, while wedo not see similar results for voluntary adopters. This is further evidence supporting ourconclusion that the IFRS mandate causes the increase of the mandatory adopters’ risk-takingbehavior. While some critics may claim that the increase of RISK 1 and RISK2 might be driven bythe inevitable mechanical changes in the accounting recognition and measurements associatedwith mandatory IFRS adoption (e.g., fair-value and principal-oriented accounting standards), theincrease in the imputed risk measure RISK3, suggests that the increase of RISK1 and RISK2 isdriven by firms’ value enhancing risk-taking rather than the changes of accounting mechanicsassociated with the IFRS. Furthermore, given that mandatory adopters are likely to have higher29

informational asymmetry relative to the voluntary adopters, we interpret these results to mean thatvalue-enhancing risk-taking behaviors by managers is greater for firms which potentially sufferfrom informational asymmetry prior to the mandatory adoption of IFRS.Financial constraintKaplan and Zingales (2000) argue that one of our proxies for investment efficiency, theinvestment-cash flow sensitivity, represents a firm’s degree of financial constraint rather than theirsuboptimal investment policy. To address this possibility, we add Altman’s Z-score (1968) andleverage to equation (1); these variables should proxy firms’ degree of financial constraint. Ourresults are qualitatively unchanged, indicating that our analysis is not contaminated by the level offirms’ financial constraint.6. ConclusionWe investigate whether the mandatory introduction of International Financial ReportingStandards (IFRS) in 26 countries is associated with an improvement in firm-level capitalinvestment efficiency. We also examine the differential effect of investment efficiency associatedwith the countries’ legal and political environment as well as financial transparency and ownershipconcentration after the mandatory adoption of IFRS. Our research design leverages informationfrom voluntary adopters to absorb the effects of macroeconomic shocks and reduces concernsfrom omitted variables, and our use of a randomly-selected control group following the literature(e.g., Daske et al. 2008) confirms our findings.Our research question exploits information in balance sheet items by examining the realeffects of the IFRS mandate (e.g., the effect of the IFRS mandate upon managers’ investmentpolicies). We extend the IFRS literature beyond the previously researched capital market effects;research by Cascino and Gassen (2010) find an increase in the comparability of balance sheet30

items after the mandatory adoption of IFRS, while they find conflicting results for earningsattributes.We find that the mandatory adoption of IFRS is associated with enhanced firm-levelinvestment efficiency. In addition, we utilize methodologies in John et al. (2008) to document thatafter the mandatory adoption of IFRS, firms’ investment policy is associated with a shift towards arisk-adjusted optimal level while their investment-cash flow sensitivity decreases. Further, we findthat this association is more pronounced in countries with weak law enforcement institutions andhigher ownership concentration. Considering these results collectively, we conclude that theadoption of IFRS benefits outside capital providers through the increased financial disclosure andcomparability of accounting information, and thus, enhanced investment efficiency. This suggeststhat the use of IFRS is associated with enhanced investment efficiency at the firm-level, a matterof great importance to firm managers and regulators world-wide.31

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TABLE 1Sample distribution by country and yearPanel A: Accounting standards and listing status by IFRS adoption countryPre IFRSPost IFRSVoluntary Mandatory Voluntary Mandatory US GAAP US ListingCountryUnique Firm- Firm-Firm-Firm-Firm-Firm-Firm-Firms Years Years % Years % Years % Years % Years % Years %Australia 1,272 4,899 38 0.008 2,844 0.581 22 0.004 1,995 0.407 397 0.081Austria 75 320 149 0.466 46 0.144 81 0.253 44 0.138 18 0.056 60 0.188Belgium 90 380 87 0.229 129 0.339 54 0.142 110 0.289 2 0.005 21 0.055Czech Republic 10 30 11 0.367 7 0.233 8 0.267 4 0.133 3 0.1Denmark 124 596 107 0.180 288 0.483 61 0.102 140 0.235 26 0.044Finland 113 602 45 0.075 319 0.530 30 0.05 208 0.346 16 0.027France 623 3,106 311 0.100 1,681 0.541 153 0.049 961 0.309 5 0.002 246 0.079Germany 662 3,127 1,067 0.341 881 0.282 637 0.204 542 0.173 367 0.117 173 0.055Greece 109 404 16 0.040 169 0.418 17 0.042 202 0.500 11 0.027 32 0.079Hong Kong 182 752 11 0.015 421 0.560 9 0.012 311 0.414 164 0.218Hungary 18 75 38 0.507 5 0.067 27 0.360 5 0.067 34 0.453Ireland 56 209 13 0.062 111 0.531 9 0.043 76 0.364 1 0.005 45 0.215Italy 240 1,029 36 0.035 536 0.521 13 0.013 444 0.431 2 0.002 76 0.074Luxembourg 20 95 21 0.221 38 0.400 15 0.158 21 0.221 21 0.221 40 0.421The Netherlands 159 825 51 0.062 484 0.587 23 0.028 267 0.324 61 0.074 135 0.164Norway 172 682 12 0.018 372 0.545 6 0.009 292 0.428 6 0.009 26 0.038Philippines 106 486 174 0.358 94 0.193 127 0.261 91 0.187 33 0.068Poland 58 197 39 0.198 72 0.365 24 0.122 62 0.315 38 0.193Portugal 42 214 14 0.065 117 0.547 9 0.042 74 0.346 21 0.098Singapore 549 2,443 4 0.002 651 0.266 14 0.006 1,774 0.726 4 0.002 79 0.032South Africa 204 1,004 270 0.269 421 0.419 121 0.121 192 0.191 1 0.001 155 0.154Spain 118 429 9 0.021 182 0.424 5 0.012 233 0.543 31 0.072Sweden 264 1,324 43 0.032 752 0.568 21 0.016 508 0.384 20 0.015Switzerland 189 938 337 0.359 208 0.222 222 0.237 171 0.182 24 0.026 85 0.091United Kingdom 1,757 7,280 904 0.124 3,756 0.516 364 0.050 2,256 0.310 4 0.001 524 0.072Venezuela 8 30 19 0.633 11 0.367 14 0.467Total 7,220 31,476 3,807 0.121 14,603 0.464 2,072 0.066 10,994 0.349 527 0.017 2,494 0.07936

TABLE 1 (continued)Panel B: institutional variables by countryIFRS AdoptionCountriesAnnouncementof MandatoryIFRS ReportingRule of LawIndexControlof CorruptionIndex37Number ofInconsistenciesbetween LocalGAAP and IFRSNumber ofAdditionalDisclosures overLocal GAAPOwnershipConcentrationIndexAustralia 07/04/2002 1.70 2.02 20 8 0.51Austria 06/04/2002 1.80 2.05 13 3 0.28Belgium 06/04/2002 1.40 1.45 15 7 0.62Czech Republic 06/04/2002 0.70 0.26 14 6 NADenmark 06/04/2002 1.90 2.42 13 5 0.40Finland 06/04/2002 1.90 2.59 19 8 0.34France 06/04/2002 1.30 1.32 19 6 0.24Germany 06/04/2002 1.70 1.80 20 7 0.50Greece 06/04/2002 0.70 0.28 20 9 0.68Hong Kong 09/10/2004 1.50 1.61 8 2 0.54Hungary 06/04/2002 0.70 0.44 17 8 NAIreland 06/04/2002 1.60 1.75 15 0 0.36Italy 06/04/2002 0.50 0.45 19 6 0.60Luxembourg 06/04/2002 1.90 2.27 16 8 NAThe Netherlands 06/04/2002 1.70 2.25 5 2 0.31Norway 06/04/2002 1.90 2.09 5 3 0.31Philippines 10/02/2003 -0.40 -0.79 10 2 0.51Poland 06/04/2002 0.30 0.14 18 5 NAPortugal 06/04/2002 1.10 1.13 12 7 0.59Singapore 12/07/2000 1.80 2.20 10 1 0.53South Africa 05/20/2003 0.20 0.32 2 1 0.52Spain 06/04/2002 1.10 1.16 22 9 0.50Sweden 06/04/2002 1.80 2.37 11 4 0.28Switzerland 11/11/2002 2.00 2.32 17 7 0.48United Kingdom 06/04/2002 1.60 1.89 15 0 0.15Venezuela 04/21/2004 -1.30 -1.04 8 4 0.49Sample is composed of firms in countries that mandated the adoption of IFRS between 2001 and 2008. The sample is divided into two timeperiods: Pre-IFRS (post-IFRS) is composed of firm-year observations with fiscal years ending before (on or after) the date to mandatorilyadopt IFRS; the sample is also divided by type of adoption: voluntary (mandatory) adopters are firms that adopt IFRS before (on or after) thedate to adopt IFRS. The full sample comprises 31,476 firm-year observations from 26 counties. Countries are included in the sample if theyhave at least 30 firm-year observations of accounting data from Global Vantage Industrial/Commercial (IC) files and stock price data fromGlobal Vantage Issues file. Observations with missing values for any variable are excluded. Panel A reports the number of firms, the numberand percentage of firm-year observations by type of adoption and by period for IFRS adoption countries . Panel B presents the date mandatory

adoption of IFRS was announced together with raw values of the institutional proxies used in the multivariate analyses across the 26 IFRSadoptioncountries.Variable Definitions:Rule of law = an indicator variable that takes the value 1(0) if the value of an index representing the strength of legal enforcement is greater (less) thanthe sample median. The index is from Kaufmann et al. (2007) for the year 2005. Higher values represent countries with higher quality legalenforcement.Control of corruption = an indicator variable that takes the value 1(0) if the index value representing the strictness of the control of corruption in theprivate sector is greater (less) than the sample median. The index is from Kaufmann et al. (2007) for the year 2005. Higher values representcountries with stronger systems to control corruption in the private sector.Number of inconsistencies between local GAAP and IFRS = an indicator variable that takes the value 1(0) if the number of national accounting rulesthat require different accounting treatments from those required by International Accounting Standards is greater (less) than the sample median.Higher values indicate that local accounting standards diverge from the IFRS to a greater extent. Data is from Nobes (2001).Number of additional disclosures over local GAAP = an indicator variable that takes the value 1(0) if the number of additional disclosures that IASrequires over local GAAP is greater (less) than the sample median. Higher values indicate that local GAAP requires a smaller number offinancial disclosure compared to the qualitatively similar IFRS, from Nobes (2001).Ownership concentration index= an indicator variable that takes the value 1(0) if the average percentage of common shares owned by the 3 largestshareholders in the ten largest non-financial, privately owned domestic firms in a given country is greater (less) than the sample median. Datais constructed by La Porta et al. (1998).US GAAP = indicator variable that takes the value 1 (0) if the firm also reports using US GAAP.US listing = indicator variable that takes the value 1 (0) if the firm is cross-listed on a US exchange.38

TABLE 2Descriptive statistics for firm-level variablesVariable N Mean Std. dev. P25 Median P75Invest 31,476 0.713 5.562 0.100 0.203 0.404OCF 31,476 -0.752 12.531 0.001 0.269 0.713MTB 31,476 1.713 1.535 0.973 1.271 1.830Sample is composed of firms in countries that mandated the adoption of IFRS between 2001 and 2008. The full sample comprises 31,476 firm-yearobservations from 26 counties. Countries are included in the sample if they have at least 30 firm-year observations of accounting data from GlobalVantage Industrial/Commercial (IC) files and stock price data from Global Vantage Issues file. Observations with missing values for any variable areexcluded. This table presents presents descriptive statistics for firm-level variables before transformation.Variable definitions (Global Vantage variable names in parentheses):Invest= Firm’s capital expenditure (CAPEX) scaled by its net value of property, plant and equipment (PPENT) at the beginning of the fiscal year.OCF = Firm’s cash flow (its Net Income before extraordinary items (IB) + Depreciation (DP)) scaled by its net value of property, plant and equipment(PPENT) at the beginning of the fiscal year.MTB = market to book ratio, measured as the ratio of the market value of equity plus the book value of total assets minus the book value of equity,which are divided by the book value of total assets.39

TABLE 3Country-level multivariate regression analysisInvestment i,t = α + β 1 Post i,t + β 2 OCF i,t + β 3 OCF i,t * Post i,t + β 4 MTB i,t + β 5 MTB i,t * Post i,t+ ∑ Controls + ε iInvestment cash-flow sensitivity by type of adopter and countryVoluntary AdoptersOCF*MTBPost*PostOCF IFRS MTB IFRSAdj.R2 N OCFOCF*PostIFRSMandatory AdoptersMTB*PostMTB IFRSAdj.R2NAustralia coeff. -0.369 0.536 0.638 -0.487 0.14 60 0.190 -0.076 0.453 0.159 0.10 4,839p-value 0.351 0.259 0.318 0.437 0.000 0.050 0.000 0.006Austria coeff. 0.449 -0.280 0.351 -0.129 0.55 230 0.499 -0.332 -1.258 1.409 0.41 90p-value 0.000 0.000 0.079 0.602 0.004 0.096 0.077 0.059Belgium coeff. 0.539 -0.117 0.006 0.244 0.46 141 0.586 -0.200 -0.308 0.159 0.44 239p-value 0.000 0.267 0.982 0.449 0.000 0.034 0.250 0.560Czech Rep. coeff. -0.350 -0.967 0.551 -1.801 0.51 19 -0.316 -0.721 -0.838 3.413 0.99 11p-value 0.579 0.438 0.492 0.161 0.442 0.389 0.346 0.181Denmark coeff. 0.415 -0.090 0.002 -0.324 0.41 168 0.370 -0.023 -0.019 0.079 0.26 428p-value 0.000 0.244 0.993 0.069 0.000 0.773 0.873 0.583Finland coeff. 0.542 -0.105 -0.995 0.651 0.61 75 0.342 0.117 0.270 -0.037 0.39 527p-value 0.000 0.446 0.001 0.079 0.000 0.089 0.053 0.823France coeff. 0.482 -0.007 -0.103 0.482 0.39 464 0.506 -0.070 -0.065 0.148 0.39 2,642p-value 0.000 0.914 0.467 0.008 0.000 0.015 0.267 0.060Germany coeff. 0.294 0.076 0.249 -0.043 0.23 1,704 0.312 0.035 -0.068 0.683 0.22 1,423p-value 0.000 0.039 0.001 0.682 0.000 0.446 0.455 0.000Greece coeff. 0.469 -0.277 -1.139 0.179 0.82 33 0.844 -0.166 -0.450 0.199 0.65 371p-value 0.001 0.161 0.055 0.693 0.000 0.019 0.043 0.493Hong Kong coeff. 0.404 0.988 1.850 -2.040 0.69 20 0.338 -0.080 0.370 0.136 0.23 732p-value 0.383 0.248 0.256 0.313 0.000 0.320 0.001 0.377Hungary coeff. 0.223 0.130 0.016 0.481 0.37 65 -0.620 0.693 0.520 1.758 0.97 10p-value 0.169 0.266 0.957 0.394 0.339 0.381 0.205 0.280Ireland coeff. 0.664 -0.105 0.969 0.063 0.89 22 0.140 0.132 -0.366 0.981 0.21 187p-value 0.002 0.498 0.152 0.911 0.270 0.413 0.068 0.002Italy coeff. 0.810 -0.484 -0.529 0.712 0.73 49 0.810 -0.468 -0.441 0.892 0.62 980p-value 0.000 0.421 0.637 0.784 0.000 0.000 0.027 0.001Luxembourg coeff. -0.013 -1.432 0.827 -0.302 0.45 36 0.319 -0.035 0.446 -0.213 0.67 59p-value 0.978 0.031 0.156 0.347 0.001 0.844 0.045 0.470Netherlands coeff. 0.381 0.078 -0.796 0.851 0.72 74 0.316 -0.014 0.007 -0.033 0.27 751p-value 0.001 0.637 0.002 0.002 0.000 0.780 0.938 0.801Norway coeff. -0.140 -0.082 -0.372 0.687 0.50 18 0.374 -0.046 -0.120 0.550 0.29 664p-value 0.754 0.845 0.297 0.121 0.000 0.495 0.220 0.000Philippines coeff. 0.243 -0.044 0.008 -0.207 0.28 301 0.280 -0.092 0.486 -0.889 0.33 185p-value 0.014 0.708 0.971 0.446 0.061 0.615 0.114 0.020Poland coeff. 0.109 0.204 0.767 -0.264 0.57 63 0.318 -0.151 0.287 -0.249 0.48 134p-value 0.514 0.250 0.037 0.557 0.000 0.204 0.212 0.357Portugal coeff. 0.774 0.978 -4.091 8.627 0.89 23 0.756 -0.422 0.044 0.212 0.65 191p-value 0.000 0.002 0.003 0.001 0.000 0.001 0.932 0.716Singapore coeff. 0.487 0.090 1.415 -2.399 0.84 18 0.442 -0.066 -0.107 0.158 0.19 2,425p-value 0.090 0.756 0.256 0.083 0.000 0.084 0.369 0.223South Africa coeff. 0.343 -0.028 -0.109 0.146 0.34 391 0.431 -0.091 -0.364 0.471 0.41 613p-value 0.000 0.688 0.287 0.294 0.000 0.118 0.000 0.000Spain coeff. 0.908 1.129 -0.050 0.313 0.99 14 0.854 -0.432 -0.211 -0.157 0.76 415p-value 0.000 0.049 0.859 0.190 0.000 0.000 0.206 0.406Sweden coeff. 0.553 0.198 -0.280 0.128 0.55 64 0.299 -0.076 0.322 0.045 0.24 1,260p-value 0.012 0.529 0.432 0.733 0.000 0.082 0.000 0.600Switzerland coeff. 0.296 0.079 0.135 -0.152 0.32 559 0.390 0.095 0.278 0.040 0.39 379p-value 0.000 0.134 0.136 0.151 0.000 0.068 0.028 0.779United Kingdom coeff. 0.270 0.072 0.212 0.073 0.33 1,268 0.283 -0.037 0.284 0.179 0.17 6,012p-value 0.000 0.055 0.000 0.406 0.000 0.106 0.000 0.000Venezuela coeff. 0 0.976 0.017 0.932 -1.598 0.70 30p-value 0.001 0.976 0.330 0.184Sample is composed of firms domiciling in countries that mandated the adoption of IFRS between 2001 and 2008.The full sample comprises 31,476 firm-year observations from 26 countries. Country-level regressions by adoptiontype are run and coefficients are estimated using generalized least squares with robust standard errors adjusted forindustry membership. P-values are two-tailed. Control variables are included but not reported.40

TABLE 4Difference-in-differences univariate analysis of mandatory versus voluntary adopters, by adoption period (mean)InvestmentOCFVoluntaryadoptersPre-mandatoryperiod(i) 0.47N=3,807Post-mandatoryperiod(ii ) 1.20N=2,072Row Diff-0.73**VoluntaryadoptersPre-mandatoryperiod(i) 0.20N=3,807Post-mandatoryperiod(ii ) 1.09N=2,072Row Diff-0.89***Mandatoryadopters(iii) 0.39N=14,603(iv) 0.47N=10,994-0.08***Mandatoryadopters(iii) -0.83N=14,603(iv) -1.32N=10,9940.49***Column Diff 0.08 *** 0.73*** -0.65***Column Diff 1.03*** 2.41*** -1.38***MTBPre-mandatoryperiodPost-mandatoryperiodRow DiffVoluntaryadopters(i) 1.46N=3,807(ii ) 1.81N=2,072-0.35***Mandatoryadopters(iii) 1.59N=14,603(iv) 1.95N=10,994-0.36***Column Diff -0.13*** -0.14*** 0.01***Sample composed of firms in countries that mandated the adoption of IFRS between 2001 and 2008. The full sample comprises 31,476 firm-year observationsfrom 26 countries. This table reports the results of the univariate difference-in-differences analysis on our main variables. *, **, and *** denote statisticalsignificance at the 10%, 5% and 1% levels (two-tailed), respectively.Variable definitions: See Table 1 and 2.41

TABLE 5Investment-cash flow-sensitivity after the mandatory introduction of IFRSInvestment i,t = α + β 1 Post i,t + β 2 OCF i,t + β 3 OCF i,t * Post i,t + β 4 MTB i,t + β 5 MTB i,t * Post i,t + ∑ Controls + ε iPanel A: Pooled regressionModel 1:Full periodModel 2:Omits transition period(2005)Predictedsign coeff. p-value coeff. p-valueIFRS Adopter Types &Investment-Cash Flow-Sensitivity:OCF 0.359

TABLE 5 (Continued)Panel B:Two-by-two analysis of mandatory versus voluntary adopters, by periodInvestment-Cash Flow-SensitivityModel 1 (N=31,476)Pre-mandatoryperiod (i)Post-mandatoryperiod (ii)(ii)-(i)Voluntary adopters (iii) 0.359*** 0.350*** -0.009Mandatory adopters (iv) 0.471*** 0.293*** -0.178***(iv)-(iii) 0.112*** -0.057** -0.169***Panel C:Two-by-two analysis of mandatory versus voluntary adopters, by period, transition period (2005) deleted.Investment-Cash Flow-SensitivityModel 2 (N=26,856)Pre-mandatoryperiod (i)Post-mandatoryperiod (ii)(ii)-(i)Voluntary adopters (iii) 0.371*** 0.362*** -0.009Mandatory adopters (iv) 0.489*** 0.283*** -0.206***(iv)-(iii) 0.118*** -0.079*** -0.197***Sample is composed of firms in countries that mandated the adoption of IFRS between 2001 and 2008. Model 1 includes the full sample of 31,476 firm-yearobservations from 26 countries and Model 2 excludes the transition year, 2005. This table reports the results of testing the change of the investment-cash flow44

sensitivity for voluntary adopters and mandatory adopters subsequent to the IFRS mandate. Panel A reports the pooled regression results for the full periodsample of firm-year observations from 2001 through 2008, as well as for the sample after omitting transition period (2005) including 26,856 firm-yearobservations from 2001-2004 and 2006-2008. Panel B reports the two-by-two analysis of mandatory adopters versus voluntary adopters by period for the fullsample, constructed using the coefficients in Panel A. Panel C reports the two-by-two analysis of mandatory adopters versus voluntary adopters by period for thesample after deleting the transition period, constructed using the coefficients in Panel A. Coefficients are estimated using generalized least squares with countryand industry fixed effects and robust standard errors adjusted for two dimensional clusters, based on country and industry membership. Control variables areincluded but not reported. *, **, and *** denote statistical significance at the 10%, 5% and 1% levels (two-tailed), respectively.Variable definitions: See Table 1 and 2.45

TABLE 6Investment-cash flow-sensitivity after the mandatory introduction of IFRS, conditional on the legal/political factorsInvestment i,t = α + β 1 Mandatory i,t + β 2 Post i,t + β 3 Mandatory i,t * Post i,t + β 4 OCF i,t + β 5 Mandatory i,t * OCF i,t + β 6 Post i,t * OCF i,t+ β 7 Mandatory i,t * Post i,t *OCF i,t + β 8 MTB i,t + β 9 Mandatory i,t * MTB i,t + β 10 Post i,t * MTB i,t + β 11 Mandatory i,t * Post i,t * MTB i,t+ γ 1 Mandatory i,t * Institutional factor + γ 2 Post i,t * Institutional factor + γ 3 Mandatory i,t * Post i,t * Institutional factor+ γ 4 OCF i,t * Institutional factor + γ 5 Mandatory i,t * OCF i,t * Institutional factor + γ 6 Post i,t * OCF i,t * Institutional factor +γ 7 Mandatory i,t * Post i,t * OCF i,t * Institutional factor + γ 8 MTB i,t * Institutional factor+ γ 9 Mandatory i,t * MTB i,t * Institutional factor + γ 10 Post i,t * MTB i,t * Institutional factor+ γ 11 Mandatory i,t * Post i,t *MTB i,t * Institutional factor + ε iPanel A: Pooled regressionIFRS Adopter Types &Investment-Cash Flow-Sensitivity,conditional on institutional factors:Model 3a:Rule of Law1(0) = Stricter (Weaker)EnforcementModel 3b:Control of Corruption1(0)=Stronger(Weaker)controlsModel 3c:Ownership Concentration1(0)=Higher (Lower)concentrationPredicted sign coeff. t-value coeff. t-value coeff. t-valueOCF 0.272 0.034 -0.150 0.013 -0.191 0.130OCF*Institutional factor -0.150 0.013 -0.343 0.001 0.076 0.281OCF* Mandatory + 0.247

TABLE 6 (continued)Panel B:Two-by-two analysis of mandatory versus voluntary adopters by period, conditional on legal/politicalfactorsVoluntaryadopters(iii)Mandatoryadopters(iv)(iv) – (iii)Investment-Cash Flow-Sensitivity(Weak rule of law)Premandatoryperiod (i)Postmandatoryperiod (ii)(ii) – (i)0.272** 0.159*** -0.113*0.519*** 0.210*** -0.309***0.247*** 0.051 -0.196***Voluntaryadopters(iii)Mandatoryadopters(iv)(iv) – (iii)Investment-Cash Flow-Sensitivity(Strong rule of law)Premandatoryperiod (i)Postmandatoryperiod (ii)0.122*** 0.209***0.082*** 0.112***(ii) – (i)0.087**0.030- 0.040 -0.097*** -0.057*Voluntaryadopters(iii)Mandatoryadopters(iv)Investment-Cash Flow-Sensitivity(Weak constraint of corruption)PremandatormandatoryPost-period (i) period (ii) (ii) – (i)-0.150** -0.260*** -0.110*0.076*** -0.227*** -0.303***Voluntaryadopters(iii)Mandatoryadopters(iv)Investment-Cash Flow-Sensitivity(Strong constraint of corruption)PremandatormandatoryPost-period (i) period (ii) (ii) – (i)-0.493*** -0.407*** 0.086**-0.533*** -0.504*** 0.029(iv) – (iii) 0.226*** 0.033 -0.193*** (iv) – (iii) -0.040 -0.097*** -0.057Voluntaryadopters(iii)Mandatoryadopters(iv)Investment-Cash Flow-Sensitivity(Low ownership concentration)PremandatormandatoryPost-period (i) period (ii) (ii) – (i)-0.191 -0.098 0.093**-0.210 -0.223 -0.013Voluntaryadopters(iii)Mandatoryadopters(iv)Investment-Cash Flow-Sensitivity(High ownership concentration)PremandatormandatoryPost-period (i) period (ii) (ii) – (i)-0.115 -0.146 -0.0310.167 -0.119 -0.286***(iv) – (iii) -0.019 -0.125*** -0.106** (iv) – (iii) 0.282*** 0.027 -0.255***Sample is composed of firms in countries that mandated the adoption of IFRS between 2001 and 2008. The fullsample comprises 31,476 firm-year observations from 26 countries. Panel A reports coefficients estimated usinggeneralized least squares with country and industry fixed effects and robust standard errors adjusted for twodimensional clusters, based on country and industry membership. Model 3a includes the indicator variable Rule of47

Law as the institutional factor; model 3b includes the indicator variable Control of Corruption as the institutionalfactor; and model 3c includes the indicator variable Ownership Concentration as the institutional factor. Panel Breports two-by-two analysis. Control variables are included but not reported. *, **, and *** denote statisticalsignificance at the 10%, 5% and 1% levels (two-tailed), respectively.Variable definitions: See Table 1 and 2.48

TABLE 7Investment-cash flow-sensitivity after the mandatory introduction of IFRS and two mechanismsPanel A: Pooled regressionIFRS Adopter Types &Investment-Cash Flow-Sensitivity, conditional on institutional factors:Model 3d:Additional disclosures1(0) = More (Less) additionaldisclosuresInstitutional FactorsModel 3e:Inconsistency1(0) = Higher(Lower)InconsistencyPredicted sign coeff. t-value coeff. t-valueOCF +0.280

TABLE 7 (continued)Panel B: Two-by-two analysis of mandatory versus voluntary adopters by period, and increased comparability as the mechanism.Investment-Cash Flow-Sensitivity(Less additional disclosure)Pre-mandatoryperiod (i)Post-mandatoryperiod (ii)(ii)-(i)Investment-Cash Flow-Sensitivity(More additional disclosure)Pre-mandatoryperiod (i)Post-mandatoryperiod (ii)(ii)-(i)Voluntaryadopters (iii)0.280*** 0.357*** 0.077*Voluntaryadopters (iii)0.393*** 0.386*** -0.007Mandatoryadopters (iv)0.278*** 0.324*** 0.046*Mandatoryadopters (iv)0.531*** 0.291*** -0.240***(iv)-(iii) -0.002 -0.033 -0.031(iv)-(iii) 0.138** -0.095** -0.233***Panel C:Two-by-two analysis of mandatory versus voluntary adopters by period, and increased disclosure as the mechanismInvestment-Cash Flow-Sensitivity(Lower Inconsistency)Pre-mandatoryperiod (i)Post-mandatoryperiod (ii)(ii)-(i)Investment-Cash Flow-Sensitivity(Higher Inconsistency)Pre-mandatoryperiod (i)Post-mandatoryperiod (ii)(ii)-(i)Voluntaryadopters (iii)0.393***0.327***-0.066Voluntaryadopters (iii)0.343*** 0.379*** 0.036Mandatoryadopters (iv)0.358*** 0.340*** -0.018Mandatoryadopters (iv)0.463*** 0.304*** -0.159***(iv)-(iii) -0.035 0.013 0.048(iv)-(iii)0.120*** -0.075*** -0.195***Sample is composed of firms in countries that mandated the adoption of IFRSbetween 2001 and 2008. The full sample comprises 31,476 firm-year observations from 26 countries. Panel A reports coefficients estimated using generalizedleast squares with country and industry fixed effects and robust standard errors adjusted for two dimensional clusters, based on country and industry membership.Model 3d includes the indicator variable Inconsistency as the institutional factor and model 3e includes the indicator variable Additional disclosures as theinstitutional factor. Panel B reports two-by-two analysis. Control variables are included but not reported. *, **, and *** denote statistical significance at the10%, 5% and 1% levels (two-tailed), respectively.50

Variable definitions: See Table 1 and 2.51

TABLE 8Additional analysis: Investment-cash flow-sensitivity after the mandatory introduction of IFRS(individual industry estimations)Investment i,t = α + β 1 Post i,t + β 2 OCF i,t + β 3 OCF i,t * Post i,t + β 4 MTB i,t + β 5 MTB i,t * Post i,t + ∑ Controls + ε iIndustries OCF OCF* Mandatory OCF* Post IFRSOCF* Mandatory*Post IFRScoeff. p-value coeff. p-value coeff. p-value coeff. p-value RSQ N (obs)Agriculture 0.423 0.000 0.060 0.698 0.104 0.000 -0.644 0.139 0.39 170Food Products 0.248 0.111 0.450 0.073 -0.346 0.058 0.189 0.482 0.39 675Alcoholic Beverages 0.630 0.001 -0.287 0.090 -0.456 0.164 0.389 0.237 0.37 320Recreational Products 0.451 0.230 0.137 0.736 -0.327 0.394 -0.307 0.490 0.42 182Entertainments 0.451 0.230 0.137 0.736 -0.327 0.394 -0.307 0.490 0.42 182Printing and Publishing 0.305 0.098 0.278 0.215 -0.070 0.810 -0.135 0.651 0.42 454Consumer Goods 0.329 0.000 0.000 0.995 0.056 0.303 -0.088 0.196 0.17 8,001Electrical Equipment 0.447 0.002 -0.001 0.995 0.445 0.129 -1.024 0.005 0.34 324Automobiles and Trucks 0.144 0.449 0.541 0.043 0.135 0.564 -0.831 0.021 0.49 341Precious Metals -0.093 0.869 0.098 0.865 0.381 0.278 -0.832 0.046 0.16 558Nonmetallic Mining -0.579 0.145 0.626 0.140 0.829 0.043 -1.070 0.027 0.14 695Petroleum and Natural Gas 0.213 0.393 0.043 0.901 -1.545 0.136 1.306 0.170 0.25 663Utilities 0.213 0.393 0.043 0.901 -1.545 0.136 1.306 0.170 0.25 663Telecommunications 0.250 0.064 0.234 0.045 -0.080 0.625 -0.190 0.201 0.31 808Business Services 0.317 0.001 0.103 0.307 0.065 0.553 -0.104 0.358 0.26 4,718Computers 0.458 0.000 -0.073 0.546 0.210 0.049 -0.291 0.005 0.26 1,169Electronic Equipment 0.473 0.000 -0.258 0.036 -0.118 0.386 0.164 0.305 0.17 1,020Lab Equipment 0.334 0.000 0.069 0.746 0.098 0.140 -0.424 0.196 0.35 285Business Supplies 0.074 0.429 0.344 0.091 0.503 0.058 -0.705 0.055 0.36 370Shipping Containers 0.514 0.005 0.447 0.007 -0.682 0.001 -0.068 0.855 0.78 127Transportation 0.561 0.002 0.019 0.909 -0.233 0.132 0.134 0.463 0.35 957Wholesale 0.344 0.000 0.139 0.178 0.312 0.355 -0.336 0.299 0.30 1,238Retail 0.490 0.000 0.040 0.566 -0.035 0.824 0.002 0.992 0.43 1,215Restaurants. Hotel, Motel 0.145 0.213 0.349 0.036 0.504 0.011 -0.484 0.028 0.44 518Consumer Goods 0.440 0.000 0.213 0.140 -0.145 0.693 -0.147 0.723 0.43 477Apparel 0.670 0.011 -0.011 0.975 -0.090 0.852 -0.079 0.893 0.45 38352

Sample is composed of firms in countries that mandated the adoption of IFRS between 2001 and 2008. The full sample comprises 31,476 firm-year observationsfrom 26 countries. This table reports the results of testing the change of the investment-cash flow sensitivity for mandatory adopters subsequent to the IFRSmandate in each industry. Industries are included only if they have at least 100 firm-year observations. Table 8 reports coefficients estimated using generalizedleast squares.53

TABLE 9Additional analysis: Impact of IFRS on firms’ risk-taking (from John et al. 2008)Panel A: Difference-in-difference analysis of risk-taking analysis (firm risk-taking proxy)RISK1 (N=12,391)Pre-mandatoryperiodPost-mandatoryperiodRow DiffVoluntary adopters6.604N=1,81313.812N=5157.208***Mandatory adopters8.760N=7,05919.082N=3,00410.322***Column Diff 2.156*** 5.270*** 3.114***Panel B: Difference-in-difference analysis of risk-taking analysis (country risk-taking proxy)RISK2 (N=96)Pre-mandatoryperiodPost-mandatoryperiodRow DiffVoluntary adopters3.957N=258.690N=214.733*Mandatory adopters4.586N=259.485N=254.899**Column Diff 0.629 0.795 0.166*Panel C: Difference-in-difference analysis of risk-taking analysis (imputed risk score)RISK3 (N=243)Pre-mandatoryperiodPost-mandatoryperiodRow DiffVoluntary adopters7.089N=5812.987N=275.898Mandatory adopters3.266N=876.503N=713.237*Column Diff -3.823* -6.484 -2.66154

Variable definitions:RISK1= Cross-sectional cash flow volatility, i Ei,c,t 1TCT 1t1 c1T t11TEi,c,t2(i = voluntary adoptersprior to the IFRS mandate, voluntary adopters subsequent to the IFRS mandate, mandatory adopters prior to theIFRS mandate, and mandatory adopters subsequent to the IFRS mandate, and C=the number of countries), whereEi,c,t OCFi,c,t1NN j, ti,t k 1OCFk,c,t, and N i,t indexes the firms within year t and the four groups (e.g.,voluntary adopters prior to the IFRS mandate, voluntary adopters post the IFRS mandate, mandatory adopters priorto the IFRS mandate, and mandatory adopters post the IFRS mandate, and C=the number of countries). That is, thedeviation of the firm’s OCF is calculated from the country average and then the standard deviation of this measure iscomputed in four subgroups.RISK2=The average of the firm risk-taking proxy (RISK1),c1N cNc i1i, c| Nc 2RISK3=Calculated for four subgroups of firm-year observations (e.g., voluntary adopters prior to the IFRS mandate,voluntary adopters post the IFRS mandate, mandatory adopters prior to the IFRS mandate, and mandatory adopterspost the IFRS mandate) over the sample period 2001-2008. The imputed risk scores are estimated using the182008USAfollowing formula, i i, j,t* 19941997,j / MV MV i,j,t, where i denotes the fourt2001 j{ 20,...,39}j{20,...,39}subgroups of firm-year observations (e.g., voluntary adopters prior to the IFRS mandate, voluntary adopters post theIFRS mandate, mandatory adopters prior to the IFRS mandate, and mandatory adopters subsequent to the IFRSmandate), j is an industry subscript based on 2-digit SIC codes, t is a year subscript,MV ,i j t,is the marketUSAcapitalization in industry j in year t, and 19941997 , j is the industry j risk score computed using only US singleUSA19941997 , jbusiness segment firms for the period 1994-1997. When calculatingwe include only firm-years,where sales are above 10 million US$. Market values (MV) are computed as of the end of the fiscal year. TheUSA 19941997 , j is computed as the within-industry variation ofEUSAijUSA 1USA, j,t ( OCF i,j,t ) (OCF i,j,t ), i.e.,USANjNi12 1997 N j1997 N j 11USA1994 1997, , , ,, , 1997 USA j USAOCF i j t 1997 OCFi j t where j USA t1994 i1USA t1994 i1 N j,t 1 N j,t t19941994t indexes the manufacturing industries defined as 2-digit SIC codes and i indexes the firms within a given industry. 1994 1997 , j, USAUSAE ,Before computingwe winsorize t, i , j at the extreme one percentile to account for missingvalues. The single business segment firms are identified from the Compustat Segment file. The estimation period ofOCF ,USAi j t, is between 1994 and 1997. Following John et al. (2008), the estimation period starts in 1994 to avoidthe potentially confounding effects related to recession years preceding it. The sample period ends in 1997 becausethe segment reporting in the US has changed as of 1997 (FAS 131 modified the rules of reporting segments, makingthe reporting of US segments pre- and post-1997 incomparable).0.555