A study of the institutional and economic determinants of

IFRS adoption in emerging economies

Anas Kossentini*

Hakim Ben Othman**

** Corresponding author: * Dr. Anas Kossentini, PhD. Lecturer in Accounting at Tunis Business School (T.B.S), University of Tunis Assistant Professor of Accounting at ISIG, University of Kairouan Researcher at LIGUE-ISCAE, University of Manouba, Tunisia Street Address: Institut Suprieur dInformatique et de Gestion, Office N9, 3100, Kairouan Mail Drop : PO. Box n19, Av Khmaiess Alouini 3100, Kairouan Tel : (00216) 77. 236.571, Fax: (00216) 77.236.632 E-mail: anas.kossentini@topnet.tn

Pr. Dr. Hakim Ben. Othman, PhD. Full Professor of Accounting and Finance at Tunis Business School (T.B.S.), University of Tunis & Senior researcher at LIGUE-ISCAE, University of Manouba Street Address: Tunis Business School, Office N1-12, El Mourouj 2074, Tunisia Mail Drop: PO.Box n65, Bir El Kassaa 2059, Tunisia Tel: (216) 79.409.333 (Extension: 272), Fax: (216) 79.409.119 E-mail: hakim.bo@planet.tn

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mailto:anas.kossentini@topnet.tnmailto:hakim.bo@planet.tn

A study of the institutional and economic determinants of

IFRS adoption in emerging economies

Abstract

The purpose of this study is to explore the underlying assumptions of institutional and economic network theories that may support or constrain emerging economies decisions to adopt IFRS. We investigate the country-level effects of institutional pressures of isomorphic changes as well as economic network pressures on the extent of IFRS adoption in emerging economies. The empirical analysis is based on a variety of regressions techniques for 50 emerging economies over a period spanning from 2001 to 2011. Particularly, we consider several specifications of random effects, pooled OLS and ordered logistic regressions. We find that both coercive and mimetic isomorphism show a strong and consistent positive effect on the level of IFRS adoption. However, we report that normative isomorphism affects negatively and significantly the extent of IFRS adoption in emerging economies. Furthermore, economic pressures, as measured by the economic network benefits of IFRS standards, is a strong predictive factor for emerging economies to adopt IFRS. Overall, these results support our general theoretical framework in that the institutional and economic environment affects emerging economies decisions to adopt IFRS or not to adopt IFRS. This paper has accounting standard-setting policy implications for emerging economies. In order to gain international legitimization and attract foreign investment, it is important to improve financial information quality through IFRS adoption. In a global economic system, it is essential to standard-setters as well as market regulators in non-adopter emerging economies to meet trade-partner pressures by providing relevant financial information recognized worldwide. This study touches on a new perspective on the adoption of IFRS by emerging economies. We rely, jointly, on the institutional theory and the economic network theory in order to predict emerging economies decisions to adopt or not to adopt IFRS. Furthermore, we investigate empirically the effects of institutional and economic pressures on the level of IFRS adoption by introducing GLLAMM (Generalized Linear Latent and Mixed Model) estimation for ordered logit regression.

Keywords: IFRS adoption, institutional theory, economic network theory, emerging economies, GLLAMM ordered logit techniques.

JEL: G38, K20, M41, M48, O57.

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1. Introduction In 1968, the pioneering paper of Mueller put forth a theory that accounting reflects economic, social, political, cultural and other local environmental conditions. Since then, research in international accounting has been exploring factors that may explain de jure and de facto differences between accounting systems in several countries (Gray and Morris, 2007; Choi and Meek, 2005; Nobes and Parker, 2004; Mueller et al., 1991; Cooke and Wallace, 1990; AlHashim and Apran, 1988; Apran and Radebaugh, 1985; Choi and Mueller, 1984).

The adoption of International Financial Reporting Standards (hereafter, IFRS) is considered one of the standard-setting strategies used in many emerging economies (e.g. Perera and Baydoun, 2007; Belkaoui, 2002, 1988). It is noteworthy that a number of studies advocate the adoption of IFRS as national standards or as published by the IASB for emerging economies (e.g. Assenso-Okofo et al., 2011, in Ghana; Al-Akra et al., 2009, in Jordan; Tyrrall et al., 2007 in Kazakhstan; Chamisa, 2000 in Zimbabwe). Prior work reported a number of potential benefits that emerging economies stand to gain from IFRS adoption including a reduction in the cost of accounting standards elaboration (e.g. Madawaki, 2012, in Nigeria; Joshi et al., 2008, in Bahrain), international legitimacy (e.g. Irvine, 2008, in the United Arab Emirates; Larson and Street, 2004, in Eastern European countries), access to international markets (e.g. Perumpral et al., (2009,) in India; Whittington, 2005, in Eastern European countries), and a growth of foreign direct investment (e.g. Madawaki, (2012), in Nigeria; Ritsumeikan, (2012), in 46 developing countries).

In recent literature, evidence has been provided that the extent of IFRS adoption changes from one emerging economy to another (Shima and Yang, 2012; Ramanna and Sletten, 2010; Judge et al., 2010; Clements et al., 2010). Indeed, the decision to adopt IFRS by a country does not necessarily mean a full adoption or a partial adoption. With this respect, we do find countries that harmonize their accounting standards with IFRS (e.g. Iran and Tunisia). Other countries allow voluntary use of IFRS (e.g. Morocco and Turkey), or require IFRS adoption for only some categories of listed companies (Saudi Arabia). It is noteworthy that the nature of IFRS adoption by a country varies across jurisdictions and across time.

Given that several factors can affect the status of IFRS adoption, a number of studies focused on the special relationship between the extent of IFRS adoption and its country-level determinant. Some of these studies investigated the economic determinants of IFRS adoption (e.g. Shima and Yang, 2012; Ramanna and Sletten, 2010; Zeghal and Mhedhbi, 2006). Other studies focused on the institutional antecedents of IFRS adoption (e.g. Ritsumeikan, 2011; Bogdan et al., 2010; Judge et al., 2010). Although previous investigations provide some insight into the country-factor determinants of IFRS usage around the world, there is a lack of studies in the particular context of emerging economies. To our knowledge, Ritsumeikan (2011) is the unique empirical study that focused on the country-level effects of institutional pressures on IFRS adoption using a sample of 46 developing countries. Furthermore, Zeghal and Mhedhbi (2006) considered the role of economic pressures in the decision of adopting IFRS for 60 developing countries.

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We use a comprehensive theoretical framework and detailed IFRS adoption levels in order to provide a broader understanding of the international accounting harmonization process in emerging economies. Our study responds to the lack of research in this field. Particularly, we draw upon institutional theory and economic network theory to understand the determinants of 50 emerging economies decisions to adopt or not to adopt IFRS for a period ranging from 2001 to 2011. Estimators are obtained through a variety of regressions techniques. Specifically, several specifications of random effects, pooled OLS and ordered logistic regressions were considered.

Results indicate that both coercive and mimetic isomorphism, measured respectively by foreign aid, according to the issuance of a Report on the Observance of Standards and Codes (hereafter, ROSC), and trade freedom, according to the density of Big 4 offices, show a strong and consistent positive effect on the level of IFRS adoption. On the contrary, the strength of the accounting profession, according to International Federation of Accountants (hereafter, IFAC) membership, which represents the proxy of normative isomorphism, affects negatively and significantly the level of IFRS adoption in emerging economies. Furthermore, economic pressure, as measured by the economic network benefits of IFRS standards, represent a strong predictive factor for emerging economies to adopt IFRS. Overall, we can state that our findings support our general theoretical framework in that the institutional and economic environment affects emerging economies decisions to adopt IFRS (in case of coercive isomorphism, mimetic isomorphism and IFRS economic network benefits) or not to adopt IFRS (in case of normative isomorphism).

Our study touches on a new perspective on the adoption of IFRS by emerging economies. The contributions of this study are twofold. Firstly, besides the fact that studies on the antecedents of IFRS adoption are relatively rare, we rely, jointly, on the institutional theory and the economic network theory in order to predict emerging economies decisions to adopt or not to adopt IFRS. Secondly, we investigate empirically the effects of institutional and economic pressures on the level of IFRS adoption using Generalized Linear Latent and Mixed model (hereafter, GLLAMM) estimation routine for ordered logit regression.

This paper is organized as follows. Section 2 outlines the empirical literature review regarding the country-level determinants of IFRS adoption. Section 3 identifies the relationship between institutional theory and IFRS adoption strategy. Section 4 describes the relationship between economic network theory and IFRS adoption strategy. Section 5 develops our research design. The findings are reported in section 6 and the paper concludes with a summary and policy implications.

2. Country-level determinants of IFRS adoption: empirical literature review It is noteworthy that some emerging economies adopt IFRS while others do not. Although particular reasons may depend on the time period and the country specificities, there is a general agreement that countries environmental conditions affect the decision of emerging economies to adopt IFRS (Shima and Yang, 2012; Ritsumeikan, 2011; Judge et al., 2010; Bogdan et al., 2010; Clements et al., 2010; Ramanna and Sletten, 2010; Archambault and Archambault, 2009; Ramanna and Sletten, 2009; Zeghal and Mhedhbi, 2006; Hope et al., 2006). Given that several factors can affect the status of IFRS adoption in emerging economies, a number of studies focused on the special relationship between the extent of IFRS adoption and

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its country-level determinants. In this regard, most prior work investigated the country-level determinants of full IFRS adoption.

Ritsumeikan (2011) addressed the relationship between the decisions of 46 developing countries to adopt IFRS and those countries institutional contexts. Drawing upon the institutional isomorphism theory of DiMaggio and Powell (1983), he revealed that IFRS adoption by developing countries is significantly related to institutional pressures. Particularly, his findings show that coercive isomorphism (as measured by the weight of foreign aid in the economy), normative isomorphism (as measured by the secondary education level) and mimetic isomorphism (as measured by the size of capital market) are strong predictive factors of developing countries decision to adopt IFRS. Furthermore, the results supported that the countrys IFRS adoption decision is motivated more by institutional and social pressures, than it is by economic factors (as measured by economic growth and foreign direct investment inflows).

Clements et al., (2010) examined the influence of cultural diversity and country size on the IFRS adoption decision of 61 developed and emerging economies. The results reveal that there are no significant cultural differences between the adopters and non-adopters. Indeed, Hofstedes (1980) cultural dimensions (as operationalized by power distance, individualism, masculinity and uncertainty avoidance) do not influence countries decision to adopt or not to adopt IFRS. Furthermore, it was found that larger and more powerful countries are more reluctant to adopt IFRS than smaller and less powerful countries.

In one of the earliest attempts to identify country-level determinants of IFRS adoption around the world, Hope et al., (2006) relied on Coffees (2002) bonding theory and cost/benefit analysis to predict the association between the countries decisions to adopt IFRS and a number of institutional factors. Particularly, they focused on the role of investor protection and stock market access in the IFRS adoption decision. The sample included 38 developed and emerging economies. As hypothesized, it was documented that countries with weak shareholder protection are more likely to adopt IFRS than are countries with strong shareholder protection. Furthermore, the empirical analysis supported the view that countries providing better access to their stock markets for international investors are more likely to adopt IFRS.

Zeghal and Mhedhbi (2006) investigated factors that may affect 64 developing countries decisions to adopt or not to adopt IFRS. The authors considered the factors of economic growth, education level, the degree of external economic openness, cultural membership in a group of countries, and the existence of a capital market. The results exhibited that developing countries that enjoy the highest literacy rate, that have a capital market, and that belong to an Anglo-American culture are the most motivated to adopt IFRS.

Using a large number of environmental factors, Archambault and Archambault (2009) examined the decision of 120 developed and developing countries to permit or not to permit the use of IFRS for their listed companies. Their empirical model included factors related to culture, political systems and economic systems. The results showed that countries are more likely to permit IFRS as the level of education and import activities increase. Furthermore, permitting the use of IFRS for listed companies appeared to be significantly influenced by the level of economic development. Indeed, developing and underdeveloped nations are more likely to permit IFRS than developed countries. On the countrary, it was found that political systems, inflation rate, and foreign stock exchange listings are not found to influence countries decisions to permit or not to permit IFRS usage.

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Another body of research showed that the extent of IFRS adoption changes from one developing country to another (e.g. Ramanna and Sletten, 2010; Judge et al., 2010). With this respect, we do find countries that harmonize their accounting standards with IFRS (e.g. Iran and Tunisia). Other countries allow voluntary use of IFRS (e.g. Morocco and Turkey), or require IFRS adoption for only some categories of listed companies (Saudi Arabia). Consequently, the use of IFRS can take several levels. This has led many authors to improve the operationalization of IFRS adoption, through using multinomial categorization (e.g. Bogdan et al., 2010; Judge et al., 2010; Ramanna and Sletten, 2009) or ordered classification (e.g. Shima and Yang, 2012; Ramanna and Sletten 2010).

Bogdan et al., (2010) focused on the possible linkages between the adoption of IFRS and the national legislative taxonomy. The authors considered a sample of 162 jurisdictions for the year 2009. As expected, it was found that countries which are characterized by principles and practices-based legislative systems are more likely to adopt IFRS. Particularly, full IFRS adoption is more likely to occur for countries with a mono-system of common law. Furthermore, the authors found that strong rule of law, with an effective mechanism of property rights enforcement, can contribute to faster IFRS adoption.

Drawing upon institutional theory to predict the antecedents of IFRS adoption, Judge et al., (2010) attempted to understand why some economies have quickly embraced IFRS standards while others partially adopted IFRS and still others continue to resist. The sample included 132 developing, transitional and developed economies for a period ranging from 2003 to 2007. The authors found empirical support for the three hypothesized institutional isomorphic pressures: coercive (as measured by foreign aid as a percentage of GDP), mimetic (as measured by import penetration as a percentage of GDP) and normative (as measured by secondary education attainment).

Ramanna and Sletten (2009) provided insights into the benefits and costs of IFRS adoption by investigating heterogeneity in countries decisions to adopt IFRS. They focused their analysis on a sample of 102 non-European Union countries for a period ranging from 2002 to 2007. It was found that a country is more likely to endorse IFRS if other countries in its geographical region are IFRS adopters. In the same vein, the authors found that the likelihood of a country to adopt IFRS is significantly influenced by the IFRS adoption status of its trade partners. Additionally, it was demonstrated that more powerful countries are less likely to surrender standard-setting authority to the IASB. In line with their previous work of 2009, Ramanna and Sletten (2010) performed an in-depth empirical analysis on the potential effects of economic network in explaining the time-series growth of IFRS harmonization across countries. They measured the extent of IFRS adoption through a five-level ordinal response variable that captures the degree of closeness between countries local GAAPs and IFRS. The results suggested that the level of IFRS adoption in a country is an increasing function of the value of its network, showing that IFRS adoption is self-perpetuating. Furthermore, it was demonstrated that more political powerful countries are less likely to endorse IFRS in their legislations.

Shima and Yang (2012) examined the effects of Choi and Meeks (2008) environmental characteristics on the countrys decision to adopt IFRS. The sample consisted of 73 developed and emerging economies. The results highlighted that equity sourced financing, importance of taxation, and inflation affect negatively the likelihood of adopting IFRS in a given country. In terms of political and social ties, it was found that colonization by the UK, the importance of economic activities with IFRS-adopter partners and economic growth positively influenced the

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decision to adopt IFRS. Finally, Shima and Yang (2012) highlighted the positive and significant effects of a common law legal system, education level and uncertainty avoidance on a countrys decision to allow or mandate IFRS.

3. Relationship between IFRS adoption strategy and institutional theory: research hypotheses

3.1. Institutional environment and the diffusion of IFRS Previous literature has consistently provided evidence that the environmental factors at a country-level have an important influence on accounting development and have led to accounting diversity (e.g. Gray and Morris, 2007; Choi and Meek, 2005; Nobes and Parker, 2004; Mueller et al., 1991; Cooke and Wallace, 1990). A number of institutional factors (e.g. political, legal, educational and religious) were considered. Ritsumeikan (2011) posited that such institutional factors were nationally limited. Indeed, their impact on accounting system development was seen only within certain jurisdictions and did not go beyond that. Touron (2005) argued that various institutonal factors may affect domestic standard-setters and play a role in the standards adoption process. Recently, local accounting standard-setters have been involved in a process of globalization, as world-wide, emerging economies and developing countries have succumbed to a process of economic homogenization, including international accounting harmonization (Cooper et al., 2003). Currently, there is an unstoppable movement toward international comparability and harmonization of national accounting standards through the adoption of IFRS (Judge et al., 2010).

The diffusion of IFRS has been accomplished through the contributions of many international organizations such as the World Bank (hereafter, WB), the International Monetary Fund (hereafter, IMF), the IFAC, the International Organization of Securities Commission (hereafter, IOSCO) and the World Trade Organization (hereafter, WTO) (Phuong and Nguyen, 2012; Boolaky, 2012; Albu et al., 2011; Assenso-Okofo et al., 2011; Al-Akra et al., 2009; Irvine, 2008; Hassan, 2008; Mir and Rahman, 2005), through multinational corporations and their related business strategies (Phuong and Nguyen, 2012; Ritsumeikan, 2011; Albu et al., 2011; Judge et al., 2010, Irvine, 2008; Belkaoui, 1994), and through professional bodies and professional accounting firms (Muniandy and Ali, 2012; Albu et al., 2011; Joshi et al., 2008; Irvine, 2008; Hassan, 2008; Chand, 2005; Mir and Rahman, 2005; Belkaoui, 1994). Irvine (2008) pointed out that the adoption of a globalized set of accounting standards, including IFRS, provides emerging economies with legitimacy.

A growing number of studies draw upon institutional perspective to gain a better understanding of phenomena in many disciplines: international alliances (Parkhe, 1998), penetration of e-commerce (Gibbs and Kraemer, 2004), foreign entry mode (Meyer and Nguyen, 2001) and the international spread of ISO 9000 quality certificates (Guler et al., 2002). In an institutional environment, accounting can be viewed as a social process through which individuals accept that national accounting standards are usurped in the interests of international accounting harmonization (Rodrigues and Craig, 2007, p. 743). The use of an institutional approach to explain and interpret the move of emerging economies toward IFRS acceptance has been acknowledged through a number of country-case studies (e.g. Aboagye-Otchere and Agbeibor,

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2012 in Ghana; Albu et al., 2011 in Romania; Irvine, 2008 in the United Arab Emirates; Hassan, 2008 in Egypt; and Mir and Rahman, 2005 in Bangladesh). Accordingly, there is lack of empirical studies in this field. To our knowledge, Ritsumeikan (2011) is the unique study that explored empirically the institutional determinants of IFRS adoption in 46 developing countries. Since then, no further empirical research has addressed such institutional country-level determinants.

3.2. Institutional isomorphism and IFRS adoption: research hypotheses We relied on the institutional theory as a theoretical lens to explore the process of IFRS adoption in emerging economies. As mentioned in the previous subsection, there has been an increasing interest in the institutional theory in many areas. Institutional theory has been adopted in accounting literature as a valuable framework to explain the country-specific factors affecting emerging economies decisions to permit the use of IFRS (Mir and Rahman, 2005). Indeed, Guler et al., (2002) explicitly stated that institutional pressures occur at the country-level as well as the firm-level or the organizational-level. Irvine (2008) indicated that organizational practices, legislated at nation-state level, are then transmitted through to more specific organizational fields, and then to individual organizations.

In a globalized environment, the interactions between nation-states have greatly increased. The diffusion of best accounting practices, including IFRS, has been accomplished through the contribution of international organizations such as the WB and IMF (e.g. Boolaky, 2012; Albu et al., 2011), multinational corporations (e.g. Phuong and Nguyen, 2012; Ritsumeikan, 2011) and professional accounting firms such as the BIG 4 (e.g. Muniandy and Ali, 2012; Joshi et al., 2008). Irvine (2008, p. 129) stated that the nation states become increasingly aware, in the global arena, of the need to adopt internationally appropriate behavior in the form of IFRS. This is then drilled down through organizational fields, to individual organizations. Empirical literature on IFRS has largely addressed the determinants and consequences of IFRS adoption at the a firm-level. Ramanna and Sletten (2009) argued that the firm-level studies are conditional on countries decisions to allow or mandate IFRS, suggesting that studies of IFRS adoption at a country-level can only stand to enrich researchers understanding of the main determinants of IFRS adoption in emerging economies . The following figure aims at illustrating how institutional pressures, operate at a global country-level field, then down, successively, to the organizational field, and finally, to the level of firms.

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Figure 1. Global institutional framework for IFRS implementation

Source: adapted from Irvine (2008)

Institutional isomorphism of DiMaggio and Powell (1983) was derived from the organizational conformity with social values and beliefs that shape organizational life. Irvine (2008, p. 127) argued that such values and beliefs are more important than technical benefits, bestowing powerful legitimizing attributes, thereby granting organizations access to resources and ensuring their survival in an increasingly organized and inter-connected society. DiMaggio and Powell (1983, p. 150) stated that organizations compete not just for resources and customers, but for political power and institutional legitimacy, for social as well as economic fitness. Furthermore, DiMaggio and Powell (1983) pointed out that the concept of institutional isomorphism is a useful tool for understanding the politics and ceremony that pervade much modern organizational life.

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They supported that institutional isomorphism occurs through three mechanisms: (1) coercive isomorphism; (2) mimetic isomorphism; and (3) normative isomorphism. Guler et al., (2002) argued that coercive pressures are represented by rules enshrined in regulatory systems, and can also include pressures from international organizations (e.g WB and IMF). Normative pressures stem mainly from professional organizational behavior (DiMaggio and Powell, 1983). Mimetic pressures refer to the copying of successful organizational behavior by other organizations, especially in situations of uncertainty (Irvine, 2008). We use these three institutional mechanisms to understand the determinants of emerging economies decisions to adopt or not to adopt IFRS.

3.2.1. Coercive isomorphism and adoption of IFRS DiMaggio and Powell (1983, p. 150) defined coercive isomorphism as resulting from both formal and informal pressures exerted on organizations by other organizations upon which they are dependent and by cultural expectations in the society within which organizations function. Such pressures may be felt as force, as persuasion, or as invitations to join in collusion. The coercive institutional pressure comes primarily from financial dependence (Mir and Rahman, 2005; DiMaggio and Powell, 1991). DiMaggio and Powell (1983, p. 154) further noted that in cases where alternative sources are either not readily available or require effort to locate, the stronger party to the transaction can coerce the weaker party to adopt its practices in order to accommodate the stronger partys needs. Emerging economies can be forced to endorse IFRS in their legislations due to coercive institutions outside of the economy. Judge et al., (2010) pointed out that the IMF routinely provides aid to developing countries in financial trouble with the demand that IFRS accounting standards to be adopted. Albu et al., (2011) indicated that the WB exerted pressure in granting its financial assistance to Romania by imposing many conditions, including IFRS usage by listed companies. Boolaky (2012) argued the international economic activities undertaken by Mauritius prompted international organizations, such as the WB and WTO, to require IFRS financial statements. Al-Akra et al., (2009) explicitly stated that Jordan has been under pressure exerted by several international institutions, including IASB, IFAC, IOSCO, IMF and WB to permit the use of IFRS. Hassan (2008) showed that the relationship between domestic agencies (e.g. the accounting profession, the Ministry of Economic Affairs, the state) as well as international funding agencies (WB, IMF, United Nations) produced institutional pressures to push the Egyptian accounting standard-setting body to develop financial regulations in accordance with IFRS. Ashraf and Ghani (2005) outlined that regional and international financial institutions such as the Asian Development Bank, WB, and IMF played a key role in shaping accounting and reporting practices of Pakistan on the basis of IFRS. Mir and Rahman (2005) stressed the significant pressures exerted by key international donor/lending institutions on the Bangladeshi Government and professional accounting bodies to adopt IFRS. Therefore, we formulate our first research hypothesis:

H.1. The greater the level of external pressures exerted by international donor/lending institutions on an emerging economy, the higher will be the level of IFRS adoption due to coercive isomorphism. 3.2.2. Mimetic isomorphism and adoption of IFRS In explaining mimetic isomorphism, DiMaggio and Powell (1983, p. 152) stated that organizations tend to model themselves after similar organizations in their field that they perceive to be more legitimate or successful. They further proposed that organizations that are

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struggling to establish well defined practices will most likely import institutionalized technologies and rules (DiMaggio and Powell, 1983, p. 155). Scott (1995) argued that in situations where there are high uncertainties about the best approach to be applied, it is recommended to seek a successful reference group and mimic their course.

The mimetic mechanism is central to understand the mode of diffusion of IFRS accounting standards across emerging economies (Mir and Rahman, 2005). Many developing and emerging economies have sought to copy IFRS standards without a careful appreciation of their specific national accounting needs (Belkaoui, 2002). From the mimetic perspective, emerging economies imitate the successful IFRS adoption experience of other developed or emerging economies. Phuong and Nguyen (2012) listed a number of factors that prompted the government of Vietnam to endorse IFRS, especially the increasing number of foreign investors that demand IFRS financial statements. Judge et al., (2010) provided evidence that mimetic pressure, as measured by import penetration as a percentage of GDP, prompted countries around the world, especially developing ones, to adopt IFRS. In the same vein, Ritsumeikan (2011) found that the openness of the economy, that represents mimetic isomorphism, is an important determinant of emerging economies decisions to allow or mandate IFRS. Albu et al., (2011) as well as Chand (2005) showed that the increased number of multinational companies exerted important mimetic pressures in favor of IFRS adoption, respectively in Romania and Fiji. On this basis, we set forth our second hypothesis:

H.2. The greater the level of economic globalization and integration that an emerging economy experiences, the higher will be the level of IFRS adoption due to mimetic isomorphism. 3.2.3. Normative isomorphism and adoption of IFRS DiMaggio and Powell (1983, p. 152) interpreted normative pressures as the collective struggle of members of an occupation to define the conditions and methods of their work, to control the production of producers (Larson, 1977: 49-52), and to establish a cognitive base and legitimation for their occupational autonomy. Accordingly, normative isomorphism stems primarily from professionalization. Hassan (2008) indicated that education level as well as professional training programs exert institutional pressures to normalize social practices (including accounting) among different organizations operating in the same field. Particularly, Hassan (2008) stressed the important role played by universities, professional associations and professional regulators in reinforcing and normalizing such social practices.

There is ample evidence within the accounting profession to support the normative perspective. Muniandy and Ali (2012) pointed out the great efforts made by the Malaysian Accounting Standard Board1 to endorse IFRS. Albu et al., (2011) argued that the Big 4 played a profound role in the globalization of accounting and represent the normative pressure that affected the decision of Romania to implement IFRS. In Egypt, Hassan (2008) indicated that the Egyptian accounting profession entered into various activities that promote the use of best international accounting practices. The author reported the particular case of the Egyptian public auditing organization that has legally enforced the adoption of IFRS on public organizations. Joshi et al., (2008) stressed the influential role played by the BIG 4 in disseminating international accounting (IFRS) and auditing (ISA) practices in emerging economies generally and in Bahrain

1 The Malaysian accounting standard-setting body.

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particularly. Chand (2005) supported that a higher level of professional expertise and training facilitates the implementation of IFRS in emerging economies generally and in Fiji particularly. Accordingly, we formulate the following hypothesis.

H.3. The greater the strength of the accounting profession that an emerging economy experiences, the higher will be the level of IFRS adoption due to normative isomorphism. 4. Relationship between IFRS adoption strategy and economic network theory: research

hypotheses 4.1.The economic theory of networks Katz and Shapiro (1985, p. 424) supported that there are many products for which the utility that user derives from consumption of the good increases with the number of other agents consuming the good. They argued that the key idea in network theory is that a network-dependent products benefits depend upon the number of the other users who are in the same network. Katz and Shapiro (1985) draw a distinction between direct value of the product and network-related value. The authors pointed out that the direct value is generated through a direct physical effect of the number of purchasers on the quality of the product. Regarding the network-related value, Katz and Shapiro (1985) considered that a product can be adopted or used even if its direct value is inferior than that of a substitute product. The economic literature sometimes calls the direct value autarky value, while the network-related value is referred to as synchronization value (Liebowitz and Margolis, 1994).

Several examples of network-dependent products were considered by a number of studies (e.g. Katz and Shapiro, 1985; Liebowitz and Margolis, 1998, 1994; and Ramanna and Sletten, 2010, 2009), including: computer software, automobile repair, video games, and Facebook network-dependent product. Liebowitz and Margolis (1998) supported that the decision of a consumer to buy a Mac computer depends on: (1) the features of the computer, including: the graphics card and the speed of the computer processor, etc. (the direct value or autarky value); and (2) the easiness by which users can share files, obtain technical services, etc (the network-related value or synchronization value). Additionally, Ramanna and Sletten (2010) considered the example of Facebook as a popular network-dependent product. They argued that the utility that an Internet user derives from the adoption of Facebook, supposedly being the best communication portal, depends on: (1) the direct value of Facebook (the demand for a good communication portal, the features, the applications, etc.); and (2) the value from other people using Facebook or the value from Facebooks network (the ease by which information is shared, the perceived lower transaction costs due to the increasing number of Facebook adopters, etc.).

4.2. IFRS adoption strategy and economic theory of networks support It is noteworthy that a single set of high quality accounting standards would provide considerable support for international investors to evaluate the performance of companies across national boundaries (Chua and Taylor, 2008). That is, IFRS standards are likely to lower transaction costs for foreign users of financial statements (Ramanna and Sletten, 2010). From the perspective of economic theory of networks, the benefits that a given country derives from IFRS adoption can be explained by the magnitude of its economic relations with other partner-countries that have already adopted IFRS. In this sense, IFRS standards are considered a network-dependent product.

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Ramanna and Sletten (2009) asserted that the time-series growth in the extent of IFRS adoption across countries could be due to the network related value of IFRS standards. They further added that a countrys decision to adopt IFRS can be viewed through the lens of direct/autarky and network-related/synchronization values. As mentioned earlier, the direct value is related to the quality of IFRS standards. Assessing the quality of IFRS standards in emerging economies is viewed at a firm-level (e.g. value relevant financial information under IFRS for the United Arab Emirates (Alali and Foote, 2012); reduced earnings management under IFRS for India (Rudra, 2012)). Because we are investigating the country-level determinants of IFRS adoption, we consider only the network-related value of IFRS (the key idea in the economic theory of networks) and we ignore the direct value of IFRS due to its firm-level dimension.

Phuong and Nguyen (2012) stressed the heavy pressure exerted by the main commercial partners of Vietnam to align its national accounting standards with IFRS. Irvine (2008) indicated that trade -partners have been the key players behind the move of the United Arab Emirates to adopt IFRS. Relying on the economic theory of networks, Ramanna and Sletten (2010, 2010) found that a country is more likely to endorse IFRS if other countries in its geographical region are IFRS adopters. In the same vein, the authors found that the likelihood of a country to adopt IFRS is significantly influenced by the IFRS adoption status of its trade partners.

From the perspective of economic theory of networks, it is expected that the extent of IFRS adoption in an emerging economy will increase due to the magnitude of trade relations with IFRS adopter partner-countries. Therefore, we formulate our fourth research hypothesis:

H.4. Emerging economies with a high magnitude of trade relations with IFRS adopter partner-countries will experience high levels of IFRS adoption.

5. Research design 5.1.Sample We consider a relatively large number of countries based on the list provided by the S&P (2010) website in order to obtain a fair representation of emerging economies. Accordingly, we relied on two main S&P indices for emerging economies classification, namely: S&P Emerging Frontier BMI and S&P/IFCI for emerging markets. However, we excluded emerging economies members of the European Union because of their joint decision to adopt IFRS regardless of local environmental factors (e.g. Romania, Latvia, and Czech Republic). In addition, Ramanna and Sletten (2009) demonstrated that the IFRS adoption decision by the European Union member states was closely tied to the establishment of the IASB. The aforementioned arguments make the analysis of the effects of institutional and economic factors on the individual IFRS adoption decision in European Union member states unfeasible. Moreover, we excluded emerging economies with missing data. Our final sample consists of a complete data set for 50 emerging economies over a period spanning from 2001 to 2011 (see Table 1).

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Table 1. Distribution of 50 emerging economies by region2

Middle East and North Africa (13 countries)

Africa (9 countries)

Asia (13 countries)

Latin America (15 countries)

Bahrain (7)

Botswana (3)&(7)

Armenia (5) &(2)&(4)&(7)

Argentina (1)&(3)

Iran (2)

Cote DIvoire (1)

Bangladesh (6)

Bolivia (3)

Israel (5)

Ghana (2) & (7)

India (5)&(7)

Brazil (2)&(7)

Jordan (7)

Kenya (7)

Indonesia (5)

Chile (2)&(4)&(7)

Kuwait (7)

Mauritius (2) & (7)

Kazakhstan (2) & (4)& (7)

Colombia (2)

Lebanon (7)

Namibia (5) & (7)

South Korea (5)&(7)

Costa Rica (7)

Morocco (1) & (3)& (4)

Nigeria (2)

Malaysia (2) & (3) & (5)

Ecuador (2)

Oman (7)

South Africa (5) & (7)

Mongolia (5) & (7)

El Salvador (2)&(3)&(4)

Qatar (4) & (7)

Zambia (5) & (7)

Pakistan (2)

Guyana (7)

Saudi Arabia (4)

Philippines (2)& (6)

Jamaica (2) & (7)

Tunisia (2)

Singapore (5)

Mexico (5)

Turkey (1)&(3)&(7)

Sri Lanka (2) & (3)

Paraguay (1)

United Arabs Emirates (4) & (7)

Thailand (5)

Peru (6)&(7)

Trinidad and Tobago (7)

Uruguay (2)& (5)&(7)

Legend:

Values from 1 to 7 are defined for a period ranging from 2001 to 2011 as follows: 1 No IFRS adoption for listed companies and local GAAPs reject IFRS. 2 No IFRS adoption for listed companies and local GAAPs were based on IFRS with major changes 3 Permitted IFRS adoption for listed companies 4 Mandatory IFRS adoption for some listed companies 5 IFRS adopted as local GAAPs for all listed companies with minor changes 6 IFRS adopted as local GAAPs for all listed companies 7 IFRS adopted as published by IASB for all listed companies

2We present in Table 2 italicized countries in order to highlight the emerging economies shifting toward higher levels of IFRS adoption over a seven-year period (from 2001 to 2011). We rank seven categories of IFRS harmonization from the weakest to the strongest form.

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5.2. Measurement of variables and data sources

5.2.1. Measuring level of IFRS adoption The decision of a country to adopt IFRS has been often operationalized, in previous empirical literature, either through a binary variable, that takes the value of 1 if the country adopts IFRS and 0 otherwise (Ritsumeikan, 2011; Clements et al., 2010; Archambault and Archambault, 2009; Zeghal and Mhedhbi, 2006; Hope et al., 2006), or through a variable that, in addition to IFRS adoption or rejection, takes into account countries that adopt IFRS with modifications (countries adapting international accounting standards with their local environmental conditions) (Bogdan et al., 2010); Chen and Sami, 2009). Both measures suffer from several weaknesses. Indeed, the decision to adopt IFRS by a country does not necessarily mean a full adoption or a partial adoption. With this respect, we do find countries that harmonize their accounting standards with IFRS (e.g. Iran and Tunisia). Other countries allow voluntary use of IFRS (e.g. Morocco, Turkey), or require IFRS adoption for only some categories of listed companies (Saudi Arabia). It is noteworthy that the nature of IFRS adoption by a country varies across jurisdictions and across time.

This has led many authors like Ramanna and Sletten (2010) and Judge et al., (2010) to improve the operationalization of IFRS adoption. Judge et al., (2010) relied on the Deloitte website categorization to measure the extent of IFRS adoption. Their variable, labeled IFRS adoption, took one of four stages in order to consider the degree of adoption of IFRS by a national economy. When a country is coded as 1, that signifies that the IFRS standards are not permitted and local accounting standards are utilized exclusively. In contrast, a country coded as 4 signifies that IFRS standards are mandatory for all listed firms. However, Judge et al., (2010) consider that some economies are in a state of transition from local standards to international standards and have partially adopted IFRS. As such, Judge et al., (2010) have chosen to code as 2 countries that indicate optional IFRS adoption; and 3 countries that indicate mandatory IFRS adoption for some listed firms. Ramanna and Sletten (2010) categorized IFRS adoption using an ordinal variable reflecting the variety of possible IFRS adoption stages. Their variable takes five values: 1 for country-year with no IFRS related activities; 2 for country-year with convergence projects; 3 for country-year in which voluntary IFRS adoption is permitted; 4 for country-year in which IFRS is required for some listed firms; and 5 for country-year with full IFRS adoption for listed firms.

We believe that all the attempts for categorizations mentioned above are not mutually exclusive. Most of these coding systems classify as non-adopters some countries that have essentially been adopting IFRS as their national standards but with some minor or major changes. Therefore, we cannot categorize them as countries rejecting IFRS. For example, IFRS are prohibited for listed companies in Tunisia, but the Tunisian accounting system was developed on the basis of IFRS but with significant changes (ROSC, 2006). Likewise, IFRS are not permitted for listed companies in Singapore, but local GAAPs were developed on the basis of IFRS with some minor changes (Deloitte, 2011). Additionally, in the Philippines, IFRS are not permitted for listed companies; however, starting from 2006 the Philippines adopted IFRS as their national accounting standards without changes (ROSC, 2006). Unfortunately, coding Tunisia, Singapore,

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and the Philippines as non-adopter countries leads to an imperfect operationalization of IFRS adoption.

In this study, we introduce a more complete IFRS adoption categorization in order to provide a broader understanding of the international accounting harmonization process in emerging economies. Accordingly, we ranked seven categories of IFRS harmonization from the weakest to the strongest form (see table 1 and appendix):

(1) for country-year in which there is no IFRS adoption for listed companies and local GAAPs reject IFRS;

(2) for country-year (e.g. Tunisia from 2001 to 20113) in which there is no IFRS adoption for listed companies and local GAAPs were based on IFRS with major changes;

(3) for country-year in which IFRS are permitted for listed companies; (4) for country-year in which IFRS are mandatory only for some listed companies; (5) for county-year (e.g. Singapore from 2001 to 2011) in which IFRS are adopted as local

GAAPs for all listed companies with minor changes;

(6) for country-year (e.g. the Philippines from 2006 to 2011) in which IFRS are adopted as local GAAPs for all listed companies; and

(7) for country-year in which IFRS are adopted as published by IASB for all listed companies. Our extended coding system aims to improve the categorization of IFRS adoption employed in previous literature.

We focus on IFRS adoption status for a period spanning from 2001 to 2011. We evaluated the reliability and the validity of our seven-level coding system in order to assess our measurement accuracy. Indeed, we performed test-retest reliability where we checked our IFRS adoption categorization at two different points in time. We found that correlation between the two tests was very high (0.97). Accordingly, this finding highlights a comfortable consistency and reliability of IFRS adoption data. Second, we used inter-rater reliability procedure. Relying on the same data sources4, observers5 reported very few differences when categorizing, independently, IFRS adoption status. Differences in IFRS adoption classification came mainly from discrepancies existing among data sources. For example, Egypt is classified in Deloitte website as requiring IFRS for all listed companies. Conversely, Pricewaterhouse Coopers website indicates that IFRS are prohibited for all Egyptian listed companies. Nevertheless, ROSC (2004) pointed out that Egyptian accounting standards are mandatory for all listed firms and were based on IFRS with minor changes6. In our study, we exclude countries with discrepancies among data sources in order to increase the reliability of our IFRS adoption data.

Validity of IFRS adoption measurement was assessed using content validity approach. Brewer and Hunter (1989) stated that content validity establishes that the measure covers the full range of the concepts meaning. This approach includes exhaustiveness and mutually exclusiveness.

3 For all analysis, we focus on a study period that spans from 2001 to 2011. 4 Please refer to Appendix as well as subsection 5.2.4. Data sources. 5 Observers are the author and co-author(s). 6 For more information about discrepancies among data sources, please refer to subsection 5.2.4. Data sources.

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First, we were able to classify every country-year observation, with respect to IFRS adoption, in terms of the seven-level categories scale composing the IFRS adoption variable. Consequently, the exhaustiveness ingredient is validated. Second, we were able to classify every country-year observation, regarding IFRS adoption, in terms of one and only one category composing the seven-level categories scale of IFRS adoption variable. Subsequently, the mutually exclusiveness ingredient is confirmed.

5.2.2. Test variables proxies Coercive isomorphism (COERCit)

Emerging economies can be forced to endorse IFRS in their legislation due to coercive institutions outside of the economy (e.g. WB, IMF). Previous empirical literature selected foreign aid as a percentage of GDP (FAIDSit) as a general proxy for coercive pressures (Ritsumeikan, 2011; Judge et al., 2010). We expect that such a proxy referred to external pressures exerted by international organizations to adopt international best practices. It is not exclusively related to IFRS implementation. For a better assessment of the coercive pressures exerted by international financial institutions, we include the indicator proxy of ROSC reports (accounting and auditing section). These reports are issued through a program jointly sponsored by the WB and the IMF. As stated by Ramanna and Sletten (2010) ROSC reports make policy recommendations that encourage emerging economies to adopt IFRS. We attribute the value of 1 if a ROSC report was issued for a given emerging economy in a given year and 0 otherwise (ROSCit). In our study, coercive isomorphism (COERCit) acts as an interactive variable to test for the impact of foreign aid on the level of IFRS adoption according to the issuance of a ROSC report (COERCit = FAIDSit*ROSCit)

Mimetic isomorphism (MIMETit) It is noteworthy that mimetic isomorphic pressures arise from the desire to imitate successful experiences. As stated earlier, mimetic pressures are central to understand the mode of diffusion of IFRS accounting standards across emerging economies. A number of possible measures were selected in previous empirical literature including: trade freedom (TRAFREEit), foreign direct investment inflows and import penetration (Ritsumeikan, 2011; Judge et al., 2010; and Guler et al., 2002). We believe that these proxies referred to the openness degree of a given emerging economy to mimetic pressures. They are not exclusively related to a countrys decision to adopt IFRS. For a better assessment of the mimetic pressures in the IFRS era, we include the indicator proxy of the number of BIG 4 offices over population in millions (BIG4OFit). Joshi et al., (2008) stressed the influential role played by the international accounting and auditing firms (Big 4) in disseminating international accounting (IFRS) and auditing (ISA) practices in emerging economies generally and in Bahrain particularly. Albu et al., (2011) pointed out that the increasing demand for Big 4 services exerted important mimetic pressures in favor of the adoption of IFRS. In our study, mimetic isomorphism (MIMETit) acts as an interactive variable to test for the impact of economic openness on the level of IFRS adoption according to the density of BIG 4 offices (MIMETit = TRAFREEit*BIG4OFit)

Normative isomorphism (NORMit) Normative isomorphism reflects how professional norms and standards influence the adoption of an organizational practice. Ritsumeikan (2011) as well as Judge et al., (2010) asserted that a high

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degree of professionalism occurs in well -educated societies. Accordingly, the enrollment in secondary schools as a percentage of the total population in the age group of secondary education has been used as a proxy for normative pressures for IFRS adoption (Ritsumeikan, 2011; Judge et al., 2010). Judge et al., (2010) explained their use for this proxy by the fact that accounting professionalism is virtually non-existent. We expect that the secondary school enrollment proxy refers to the education level of a nation. It does not necessarily reflect the advancement of accounting professionalization. In line with Nobes and Parker (2004) and HassabElnaby et al., (2003), we consider the proxy of the number of CPAs over population in millions as an indicator of accounting development (NCPAit). Indeed, highly qualified accountants are more and more required to cope with and to achieve greater professionalization (HassabElnaby et al., 2003). We expect that a high degree of professionalism does not lead directly to IFRS adoption. For a better assessment of the normative pressures in the IFRS field, we include the indicator proxy of IFAC membership (IFACit). In previous literature, it was shown that the IFAC urged its member countries to incorporate IFRS into their national jurisdictions (Ali, 2005). We attribute the value of 1 if a given emerging economy is represented by a professional accounting body in the IFAC and 0 otherwise. In our study, normative isomorphism (NORMit) acts as an interactive variable to test for the impact of accounting profession strength on the level of IFRS adoption according to IFAC membership (NORMit = NCPAit*IFACit).

Network benefits of IFRS adoption (NETWORKit) IFRS standards are considered to be a network-dependent product. Indeed, the benefits that a given emerging economy derives from IFRS adoption can be explained by the magnitude of its economic relations with other partner-countries that have already adopted IFRS. Consistent with Ramanna and Sletten (2010, 2009), we measure the network benefits to an emerging economy from adopting IFRS in a given year by the status of its top five trade-partner countries with respect to IFRS standards. We rely on the WTO website (http://www.wto.org) to identify the top five trading partners of each emerging economy considered in our study. Subsequently, we calculate the percentage of IFRS adopters among the top five trading partners as of the prior year. We define IFRS adopters to mean either: permitted IFRS adoption for listed companies; Mandatory IFRS adoption for some listed companies; IFRS adopted as local GAAPs for all listed companies with minor changes; IFRS adopted as local GAAPs for all listed companies; and IFRS adopted as published by IASB for all listed companies. Accordingly, network benefits from IFRS adoption for a country i in year t are given by: NETWORKi,t = (Percentage of IFRS adopters in top five trade-partner countries)i,t-1 5.2.3. Control variable identification To control for the effect of institutional and economic factors on the level of IFRS adoption in emerging economies, we introduce a set of control variables considered by previous literature.

Economic growth rate (ECOGit) Prior work in the field of accounting harmonization argued that economic factors are important determinants of the development of accounting systems in emerging economies (e.g. Gordon et al., 2012; Ritsumeikan, 2012; Phuong and Nguyen, 2012; Assenso-Okofo et al., 2011; Zeghal and Mhedhbi, 2006; Apran and Radebaugh, 1985).

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http://www.wto.org/

Zeghal and Mhedhbi reported that the average of economic growth is higher in developing countries that decided to adopt IFRS. Shima and Yang (2012) found that high rates of economic growth influenced positively and significantly countries decisions to adopt IFRS. In addition, Ritsumeikan (2011) as well as Judge et al., (2010) highlighted the importance of the stage of economic growth in IFRS implementation. Archambault and Archambault (2009) indicated that permitting the use of IFRS for listed companies appeared to be significantly influenced by the level of economic growth. This variable is represented by annual GDP growth.

Legal system (LEGSYSit) Doupnik and Salter (1995) noted that the legal system of a given country is of great relevance to the accounting regulatory system. David and Brierley (1985) asserted that it is possible to split countries neatly into codified legal systems and common law legal systems. It was demonstrated that a country with stricter enforcement regimes experiences higher quality financial information (Armstrong et al., 2010). In this regard, La Porta et al., (1998, 2006) as well as Burgstahler et al., (2006) documented that law enforcement and reporting incentives are sharply higher in common law countries than in civil law ones.

Shima and Yang (2012) highlighted the positive and significant effects of a common law legal system on a countrys decision to allow or mandate IFRS. Bogdan et al., (2010) found that countries which are characterized by principles and practices-based legislative systems are more likely to adopt IFRS. Particularly, full IFRS adoption is more likely to occur in countries with a mono-system of common law. Our proxy for the legal system is a dummy variable that takes the value of one if the country has a common law legal system and zero if the country has a civil law legal system.

Stock market size (SMSit) The development of stock markets influences substantially the accounting environment of any country, especially emerging economies. In general, capital market participants demand a higher quality of financial and non-financial disclosure (HassabElnaby et al., 2003). Judge et al., (2010) highlighted a positive and significant effect of market capitalization, used as a proxy for stock market size, on countries decisions to allow or mandate IFRS for their listed companies. Hope et al., (2006) reported that access to equity capital is positively associated with the decision to adopt IFRS. In a sample of 64 developing countries, Zeghal and Mhedhbi (2006) showed that the existence of a well-established stock market is a positive and significant factor tied to the adoption of IFRS. To assess the effects of stock market size on the level of IFRS adoption we use the proxy of stock market capitalization as a percentage of GDP.

Accounting and taxation connection (ACTACit) International accounting literature largely addressed the relationship between accounting and taxation, especially in emerging economies (e.g. Al-Akra et al., 2009; Larson and Street, 2004; Belkaoui, 1994).

Phuong and Nguyen (2012) indicated that the strict link between tax regulations and accounting in Vietnam may generate difficulties in making IFRS successful. Rodrigues et al., (2012) considered the decrease of tax influence on accounting practices as a major driver of IFRS adoption in Brazil. Albu et al., (2011) reported the strong link between accounting and taxation

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as one of the main challenges experienced by Romania in its process of IFRS implementation. Trabelsi (2010) argued that the close link between accounting and taxation is one of the main obstacles for IFRS adoption in Tunisia. Shima and Yang (2012) provided empirical evidence that the importance of taxation negatively affects the likelihood of adopting IFRS in a given country. Accordingly, it is expected that a strong link between accounting and taxation in a given emerging economy negatively affects the decision to adopt IFRS.

We relied on the PwC website (http://pwc.com) in order to assess the link between accounting and taxation. If the tax regime was indicated as dependent, this means that taxable profit is entirely based on the legal entity statutory accounts. As a consequence, there is a very close link between accounting and taxation. The variable ACTAC acts as a dummy variable that takes the value of 1 if there is a strong link between accounting and taxation and 0 otherwise.

Education level (EDUCit) Choi and Meek (2008) posited that a high education level is a major prerequisite to apply and interpret accounting standards and practices. Archambault and Archambault (2009) indicated that the level of education affects the ability to read and understand IFRS. Zeghal and Mhedhbi (2006) pointed out that the adoption of IFRS by developing countries requires a high level of education to be able to understand, interpret, and then make use of such standards.

Shima and Yang (2012) highlighted the positive and significant effect of education level on a countrys decision to allow or mandate IFRS. Archambault and Archambault (2009) provided empirical evidence that countries are more likely to permit IFRS as the level of education increases. We represent this variable by the enrollment in tertiary education as a percentage of total population in the age group of tertiary education.

Law enforcement (LENFit) There is evidence that emerging economies with more strict enforcement regimes derive s more benefits from IFRS usage in comparison with emerging economies with weak enforcement mechanisms (Ben Othman and Zeghal, 2008). Chand (2005) argued that enforcement mechanisms are important to ensure an appropriate compliance with IFRS. Indeed, Papua New Guinea showed a lack of legal backing. Conversely, Fiji experienced well-established mechanisms of law enforcement. Consequently, the benefits derived from IFRS adoption are more likely to arise in Fiji than in Papua New Guinea (Chand, 2005). Trabelsi (2010) considered the weak enforcement mechanisms as one of the main challenges for IFRS implementation in Tunisia.

La Porta et al., (2006, 1998) show that law enforcement contains three main components: efficiency of the judicial system, rule of law and corruption index. Also, Kauffmann et al., (2007) provide other measures of law enforcement, including regulatory quality, rule of law and control of corruption. We measure law enforcement as the mean of the three measures introduced by Kauffmann et al., (2007) (Ben Othman and Zeghal, 2008).

5.2.4. Data sources We identify the main sources of data collection for the different variables selected for this research. As for independent variables, we used a variety of websites including: (1) WB and more specifically the World Development Indicators (http://data.worldbank.org) and the World Governance indicators (http://info.worldbank.org); (2) UNESCO (http://stats.uis.unesco.org); (3)

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http://pwc.com/http://data.worldbank.org/http://info.worldbank.org/http://stats.uis.unesco.org/

Economic Freedom (http://.heritage.org); (4) BIG4 accounting firms (PwC: http://pwc.com; Deloitte: http://deloitte.com; Ernst & Young: http://ey.com; KPMG: http://kpmg.com); (5) WTO (http://wto.org); (6) Ottawa University: (http://droitcivil.uottawa.ca); (7) IFAC (http://ifac.org). Table 2 presents the list, definition, and source of data for both dependent and independent variables.

Table 2. Variable definitions and data sources Variables Definitions Source

LIFRSit Level of harmonization with IFRS measured by an ordinal variable from non-adoption to full adoption.

The authors, based on many sources (please refer to appendix).

COERCit Coercive isomorphism measured by an Interactive variable: FAIDSit*ROSCit.

The authors.

FAIDSit Foreign aids as a percentage of GDP. WDI.

ROSCit Binary variable that takes the value of 1 if a ROSC report was issued for a given emerging economy in a given year and 0 otherwise.

WB website.

MIMETit Mimetic isomorphism measured by an Interactive variable: TRAFREEit*BIG4OFit.

The authors.

TRAFREEit Trade freedom index. Economic Freedom Index website.

BIG4OFit Number of BIG 4 offices over population in millions.

By the Authors, based on BIG4 international accounting firms websites.

NORMit Normative isomorphism measured by an Interactive variable: NCPAit*IFACit.

The authors.

NCPAit Number of CPAs over population in millions.

The authors, based on: IFAC website, ROSC reports, and CPAs professional organization website of each emerging economy.

IFACit Binary variable that takes the value of 1 if a given emerging economy is represented by an accounting CPAs professional body in the IFAC and 0 otherwise.

IFAC website.

NETWORKit Percentage of IFRS adopters among the top 5 trading partners.

The authors, based on WTO website.

ECOGit Annual GDP growth. WDI.

LEGSYSit Binary variable that takes the value of one if the country has a common law legal system and zero if the country has a civil law legal system.

Ottawa University website, the Faculty of law, Civil law section.

SMSit Stock market capitalization as a percentage of GDP. WDI.

ACTACit Binary variable that takes the value of 1 if there is a strong link between accounting and taxation and 0 otherwise.

PwC website.

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http://.heritage.org/http://pwc.com/http://deloitte.com/http://ey.com/http://kpmg.com/http://wto.org/http://droitcivil.uottawa.ca/http://ifac.org/

EDUCit Enrollment in tertiary education as a percentage of total population in the age group of tertiary education. UNESCO website.

LENFit Mean of regulatory quality, rule of law and control of corruption. WGI

In order to classify developing countries by referring to their level of harmonization with IFRS, our interest variable is built on five data sources. Our primary source for IFRS categorization is ROSC reports (accounting and auditing section) produced by a program jointly sponsored by the WB and the IMF (http://www.worldbank.org/ifa/rosc_aa.html). We analyzed 36 ROSC reports available for 36 emerging economies included in our study (see appendix). We focused on the setting accounting and auditing standards section as well as the accounting standards as designed and practiced section. This analysis was conducted to compare local standards and IFRS in order to decide about the real status of a county vis--vis IFRS (see column A in the appendix). The second main source of data is Deloitte's website (http://www.iasplus.com) which provides, in its jurisdiction section, a table summarizing the global use of IFRS in 174 countries. In most cases, the Deloitte website provides a timeframe and/or a history of IFRS adoption country by country and a somewhat brief comparison between national GAAPs and IFRS (see column B in the appendix). The third main source of IFRS categorization is the PwC website (http://www.pwc.com) that provides information about the adoption of IFRS in 109 countries. Additionally, each section for a given country provides, in some cases, key useful dates for the effective usage of IFRS (see column C in the appendix).

GAAP (2001) was used by Ding et al., (2009) to calculate a conformity score between local GAAPs and IFRS for 62 countries. We used this conformity score, as a secondary data source to check IFRS categorization during the earlier years (especially 2001 and 2002) even though data provided by GAAP (2001) is relatively old (see column D in the appendix). Occasionally, we used additional data sources when the history of IFRS adoption in a given country is not available in the three main data sources (e.g. Bolivia, Costa Rica, Iran, etc.) (see column E in the appendix).

These data sources enabled us to determine in which year a country shifted from one category to another. In some cases, the effective date of IFRS adoption occurred mid-year. For example, the Deloitte website indicated that Uruguay required IFRS effective July 2007. In such a case, we consider the effective date of IFRS usage as the next year. Therefore, Uruguay is categorized as a non-adopter country in 2007 because we believe that it is difficult for a developing country, at a first time adoption, to adequately use IFRS. In other cases, the effective date of IFRS adoption is not clearly specified. Therefore, it is not clear if the country started using IFRS on January 1 or not. For example, the PwC website pointed out that IFRS have been required for all listed companies in Qatar since 2002. In that case, we classified Qatar as an adopter-country starting from January 1, 2003.

Each main data source covers a different set of countries and/or time periods. The estimation of the main data sources of the extent of IFRS adoption occasionally differs from one source to another. For example, in the Venezuelan case, the Deloitte website reports that IFRS are not permitted for listed companies while the PwC website indicates that IFRS are permitted for listed companies. For such conflicting situations, some authors like Ramanna and Sletten (2010)

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http://www.worldbank.org/ifa/rosc_aa.htmlhttp://www.iasplus.com/http://www.pwc.com/

decided on the adoption status by referring to the majority of data sources. We believe that Ramanna and Slettens approach is not appropriate in all cases. These authors relied on only one source of data (for example Deloitte) and ignored a another reliable data source (for example PwC). In our study, we exclude countries with discrepancies among data sources. Our objective is to operationalize our variable of interest as cleanly as possible.

5.3. Econometric modeling Our objective is to investigate institutional and economic determinants of the ever-increasing push toward international harmonization of accounting standards across emerging economies. Thus, emerging economies decisions to adopt IFRS vary across jurisdictions and across time. To take advantage of both individual and time dimensions of our sample, we use panel estimation techniques. Indeed, during a period that spans from 2001 to 2011, data are available for 50 emerging economies.

Our general empirical model is as follows:

iittitiiit TtniFZY ,...,;,...,1 ,'' 1,1, =+++= (1)

itY indicates the dependent variable: LIFRSit

1, tiF includes interest variable proxies COERCi, t-1: is the coercive isomorphism variable MIMETi, t-1: is the mimetic isomorphism variable NORMi, t-1: is the normative isomorphism variable NETWORKi, t-1: is the network benefit of IFRS adoption variable

1, tiZ represents the vector of k control variables including: ECOGi, t-1: is the economic growth variable LEGSYSi, t-1: is the legal system variable SMSi, t-1: is the stock market size variable ACTACi, t-1: is the accounting and taxation connection variable EDUCi, t-1: is the education level variable LENFi, t-1: is the law enforcement variable

,,...,1, nii = are constant coefficients specific to each country. Their presence assumes that differences across the considered countries appear by means of differences in the constant term. These individual coefficients are estimated together with both vectors of coefficients '' & .

it is the error term. We used a variety of panel estimation techniques to assess the effects of institutional and economic pressures on IFRS adoption in emerging economies, while controlling for other

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important environmental factors. Our empirical strategy is to conduct the most comprehensive and appropriate statistical analysis.

5.3.1. Linear regression framework Our outcome of IFRS adoption is treated as an ordinal variable with seven categories ranging from non -adoption to full adoption. In our first empirical testing strategy, we considered OLS regression techniques. Although the IFRS adoption dependent variable is represented by ordinal categorical response, we have chosen to opt for OLS a regression for two main reasons. Firstly, previous empirical literature with respect to the country-level determinants of IFRS implementation used OLS regression techniques for their ordered categorical measurements of IFRS adoption (e.g. three ordinal scale levels of IFRS adoption (Shima and Yang, 2012), five ordinal scale levels of IFRS adoption (Ramanna and Sletten, 2010), and four ordinal scale levels of IFRS adoption (Judge et al., 2010)). Secondly, using parametric tests in the case of ordered Likert scale is valid (Lubke and Muthen, 2004; Glass et al., 1972). Lubke and Muthen (2004) supported that OLS regression is generally possible for at least five point scale and it is much better for a seven point scale (which represent our ranking for seven categories of IFRS harmonization).

In a linear regression framework, there are three ways to estimate equation (1): random effects, fixed effects, and pooled OLS estimation. In general, the Hausman test is conducted to decide whether to use fixed or random effects. This comes down to test for the specification in order to determine if the coefficients of the two estimates (fixed and random) are statistically different (Cameron and Trivedi, 2009). Additionally, pooled OLS estimators are consistent if the random effects model is appropriate (Cameron and Trivedi, 2009) and are inconsistent if the fixed effects model is appropriate (Afonso et al., 2011).

5.3.2. Ordered response framework Jamieson (2004) asserted that, in ordered categories, the intervals between the scale values are not equal. He further argued that non-parametric statistics are appropriate when using Likert scale data. Because the dependent variable, level of IFRS adoption, is categorical and therefore has discrete values, maximum likelihood estimation is the most appropriate method to use in estimating the model. In addition to the OLS regression presented in the previous subsection, we also estimate the economic and institutional determinants of IFRS adoption in emerging economies under a limited dependent variable framework. Because the IFRS adoption level is a discrete variable and reflects an order in terms of probability of default (Ramanna and Sletten, 2010), the ordered logit is a natural approach for this type of problem (Afonso et al., 2011). We consider seven levels of a countrys position vis--vis IFRS standards, embodied in an unobserved latent variable Yit*. This latent variable depends on the same set of variables presented in equation (1):

iittitiiit TtniFZY ,...,;,...,1 ,'' 1,1,* =+++= (2)

Our IFRS adoption levels have seven cut-off points. The final categorization is given by:

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ti,*

11

11 ti,*

12

12 ti,*

13

13 ti,*

14

14 ti,*

15

15 ti,*

16

16 ti,*

ti,

Yc if rejection IFRS:L1

cYc if IFRS and GAAPsbetween sdifferencemajor :L2

cYc if firms listedfor permitted IFRS:L3

cYc if firms listed somefor mondatory IFRS:L4

cYc if changesminor th locally wi adopted IFRS:L5

cYc if locally adopted IFRS:L6

cY if IASBby published as adopted IFRS:L7

Y (3)

The parameters of equations (2) and (3), precisely '' , , and the cut-off points 1611 cc are estimated using maximum likelihood. According to Afonso et al., (2011) as well as Wooldridge (2002) we used random effects ordered logit estimation which considers the error term it to be normally distributed, and maximizes its log-likelihood.

As we have panel data, the model is estimated using STATA software running the routine gllamm. GLLAMM stands for generalized linear latent and mixed models. This type of estimation is becoming more commonly used in social sciences (Michael, 2008).

6. Results and interpretations 6.1. Descriptive statistics and correlation tests

Table 3 (Panel B) shows descriptive statistics of all categories of IFRS adoption. It seems that emerging economies are influenced by IFRS in shaping their local accounting standards. Indeed, 22% represent country-year observations with no IFRS adoption for listed companies and local GAAPs based on IFRS with major changes (L2). Moreover, 21% represent country-year observations where IFRS are adopted as local GAAPs for all listed companies with minor changes (L5). However, 39% represent country-year observations where IFRS are fully adopted either as local standards or as published by IASB (L6 and L7). There are only 7% of country-year observations that show a total rejection of IFRS (L1). Most emerging economies included in our study do not reject IASBs standards and experience a move toward high levels of IFRS adoption. Indeed, 55% of country-year observations show a partial adoption of IFRS (L2, L3, L4 and L5 combined) and 39% represent country-year observations where there is a full IFRS adoption (L6 and L7 combined).

Figure 2. Coercive pressures for the sample of 50 emerging economies by IFRS categories

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Table 3 (panel A) and Table 4 report that coercive pressures (COERC) experience a very large variability across 50 emerging economies and along with the IFRS categories. The averages of the coercive pressures are sharply higher in categories L3 (0.613), L4 (0.805) and L7 (1.669) in comparison with the other categories. This suggests that emerging economies accepting IFRS as published by IASB, whatever the acceptance form, will experience a high degree of coercive pressure. In addition, Figure 2 exhibits that these coercive pressures exerted by international donor/lending organizations increase over time, especially for the aforementioned categories (L3, L4, and L5).

Figure 3. Mimetic pressures for the sample of 50 emerging economies by IFRS categories

0

0.5

1

1.5

2

2.5

3

3.5

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

L1

L2

L3

L4

L5

L6

L7

0

50

100

150

200

250

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

L1

L2

L3

L4

L5

L6

L7

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Regarding mimetic pressures (MIMET), it was reported that economic openness according to the density of Big 4 offices is substantially high in country-year observations where IFRS standards are fully adopted as published by IASB (138.74) (See Table 3, Panel A as well as Table 4). Figure 3 outlines a relatively stable situation over a period ranging from 2001 to 2010.

Table3. Descriptive statistics on dependent and independent variables for the total sample of emerging economies

Panel A: Descriptive statistics for environmental variables Variable IFRS category Country-years Mean Standard

deviation Nb. % COERC L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 0.299 0.660 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 0.374 1.186 L3: IFRS permitted 43 7.82 0.613 1.013 L4: IFRS required for some 26 4.73 0.805 1.491 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 0.180 0.565 L6: IFRS adopted as local GAAPs 16 2.91 0.376 0.309 L7: IFRS adopted as published by IASB 196 35.64 1.669 4.044 MIMET L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 21.780 11.11 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 43.754 58.274 L3: IFRS permitted 43 7.82 54.094 43.652 L4: IFRS required for some 26 4.73 88.780 126.52 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 79.589 89.096 L6: IFRS adopted as local GAAPs 16 2.91 10.289 1.084 L7: IFRS adopted as published by IASB 196 35.64 138.74 125.17 NORM L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 361.01 597.622 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 661.89 994.486 L3: IFRS permitted 43 7.82 1117.6 1609.83 L4: IFRS required for some 26 4.73 104.23 488.88 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 826.39 1416.79 L6: IFRS adopted as local GAAPs 16 2.91 85.051 113.404 L7: IFRS adopted as published by IASB 196 35.64 293.78 457.740 NETWORK L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 20 21.809 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 31.932 24.745 L3: IFRS permitted 43 7.82 37.674 22.343 L4: IFRS required for some 26 4.73 47.692 24.707 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 41.25 26.205 L6: IFRS adopted as local GAAPs 16 2.91 30 24.221 L7: IFRS adopted as published by IASB 196 35.64 60 22.280 ECOG L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 2.657 5.056 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 4.712 3.141 L3: IFRS permitted 43 7.82 4.748 2.501 L4: IFRS required for some 26 4.73 3.551 4.593 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 4.887 3.140 L6: IFRS adopted as local GAAPs 16 2.91 5.054 2.825 L7: IFRS adopted as published by IASB 196 35.64 5.210 4.368 LEGSYS L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 0 0 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 0.403 0.492 L3: IFRS permitted 43 7.82 0.186 0.393 L4: IFRS required for some 26 4.73 0.192 0.401 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 0.437 0.498 L6: IFRS adopted as local GAAPs 16 2.91 0.375 0.5 L7: IFRS adopted as published by IASB 196 35.64 0.586 0.493 SMS L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 22.056 20.873

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L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 31.911 34.964 L3: IFRS permitted 43 7.82 26.835 19.825 L4: IFRS required for some 26 4.73 57.439 48.570 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 61.653 61.359 L6: IFRS adopted as local GAAPs 16 2.91 46.692 22.733 L7: IFRS adopted as published by IASB 196 35.64 60.898 61.824 ACTAC L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 0.289 0.459 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 0.142 0.351 L3: IFRS permitted 43 7.82 0 0 L4: IFRS required for some 26 4.73 0 0 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 0 0 L6: IFRS adopted as local GAAPs 16 2.91 0 0 L7: IFRS adopted as published by IASB 196 35.64 0.025 0.158 EDUC L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 29.093 23.014 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 24.114 12.805 L3: IFRS permitted 43 7.82 24.265 14.087 L4: IFRS required for some 26 4.73 27.942 11.690 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 30.454 25.894 L6: IFRS adopted as local GAAPs 16 2.91 31.502 2.851 L7: IFRS adopted as published by IASB 196 35.64 25.073 16.909 LENF L1: No IFRS adoption and local GAAPs reject IFRS 38 6.90 -0.757 0.461 L2: No IFRS adoption and local GAAPs were based on IFRS with major changes 119 21.64 -0.228 0.645 L3: IFRS permitted 43 7.82 -0.148 0.458 L4: IFRS required for some 26 4.73 -0.013 0.508 L5: IFRS adopted as local GAAPs with minor changes 112 20.36 0.211 0.839 L6: IFRS adopted as local GAAPs 16 2.91 -0.440 0.056 L7: IFRS adopted as published by IASB 196 35.64 0.088 0.537 Panel B: Descriptive statistics of all categories of IFRS adoption Variables Number of country-years Percentage of country-years NOIFRS 38 6.90%

L1 38 6.90 % PIFRS 300 54.55%

L2 119 21.64 % L3 43 7.82 % L4 26 4.73 % L5 112 20.36 %

FIFRS 212 38.55 % L6 16 2.91 % L7 196 35.64 %

Total 550 100% Notes: LIFRS is the level of harmonization with IFRS that takes the value of 1 (L1) for country-year in which there is no IFRS adoption for listed companies and local GAAPs reject IFRS, the value of 2 (L2) for country-year in which there is no IFRS adoption for listed companies and local GAAPs were based on IFRS with major changes, the value of 3 (L3) for country-year in which IFRS are permitted for listed companies, the value of 4 (L4) for country-year in which IFRS are mandatory only for some listed companies, the value of 5 (L5) for county-years in which IFRS are adopted as local GAAPs for all listed companies with minor changes, the value of 6 (L6) for country-year in which IFRS are adopted as local GAAPs for all listed companies, and the value of 7 (L7) for country-year in which IFRS are adopted as published by the IASB for all listed companies; NOIFRS is the non-adoption of IFRS measured by a dummy variable that takes the value of 1 for the country-year which was ranked first in the variable LIFRS and 0 otherwise; PIFRS is the partial adoption of IFRS measured by a dummy variable that takes the value of 1 for the country-year which was ranked either second and/or third and/or fourth and/or fifth in the variable LIFRS and 0 otherwise; FIFRS is the Full IFRS adoption measured by a dummy variable that takes the value of 1 for the country-year which was ranked sixth and seventh in the variable LIFRS and 0 otherwise; COERC represents the coercive pressures measured by an interactive variable: foreign aid according to the

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issuance of a ROSC report; MIMET represents the mimetic pressures measured by an interactive variable: trade freedom according to the density of BIG 4 offices; NORM represents the normative pressures measured by an interactive variable: the strength of the accounting profession according to the IFAC membership; NETWORK is the network benefits of IFRS adoption measured by the percentage of IFRS adopters among the top five trading partners; ECOG is the economic growth measured by the annual variation of the GDP; LEGSYS is the legal system measured by a binary variable that takes the value of one if the country has a common law legal system and zero if the country has a civil law legal system; SMS is the stock market size measured by the stock market capitalization as a percentage of GDP; ACTAC is the accounting and taxation connection measured by a binary variable that takes the value of 1 if there is a strong link between accounting and taxation and 0 otherwise; EDUC is the level of education measured by the enrollment in tertiary education as a percentage of total population in the age group of tertiary education; LENF is the law enforcement measured by the mean of regulatory quality, rule of law and control of corruption.

In terms of professionalization, we notice that the strength of the accounting profession according to IFAC membership is more important for country-year observations with partial IFRS adoption, respectively for L3 (1117.69), L5 (826.391) and L2 (661.89), than in full IFRS adoption and IFRS rejection country-year observations. Figure 4 sums up this finding and highlights the sharply higher normative pressures among the partial-adopter emerging economies.

Figure 4. Normative pressures for the sample of 50 emerging economies by IFRS categories

Table 3 (Panel A) shows that the network benefits of IFRS, as measured by the percentage of IFRS adopters among the top five trading partners, are extremely high for emerging economies that have adopted IFRS standards as published by the IASB. It is noteworthy that emerging economies accepting IFRS as published by the IASB, whatever the acceptance form (IFRS permitted or mandatory for some listed firms), will experience great network benefits from adopting IFRS. Fig