Mergers and acquisitions and accounting information quality: An analysis of enforcement in G20 countries

ABSTRACT

The aim of this research was to analyze the impact of enforcement on the relationship between cross-border and domestic mergers and acquisitions (M&As) involving highly indebted targets and the earnings management of acquiring companies in G20 countries from 2010 to 2022. This study fills a gap in the literature by examining how varying levels of enforcement impact earnings management in M&As, particularly when the target companies are highly indebted. Additionally, it compares these influences in domestic and cross-border transactions. The study explores the relationship between enforcement and earnings management, which are critical indicators of accounting information quality. The analysis provides insights into how enforcement can mitigate opportunistic accounting practices in M&As, thereby affecting the transparency and usefulness of information for investors. The findings are valuable for managers, investors, and regulators, as they demonstrate how enforcement can improve the quality of accounting information, particularly in M&As involving indebted targets. This information can guide policies that promote transparency and reduce opportunistic practices. The research employed multiple regression analysis of panel data on acquirers of indebted targets. Earnings management (as measured by the modified Jones and Pae models) was the dependent variable, and the origin of the M&A (domestic or cross-border) was the independent variable, in addition to control variables. The analysis was performed on high- and low-enforcement samples. The results indicate that acquiring companies in M&As of highly indebted targets adopt more conservative accounting practices in high enforcement environments, resulting in less earnings management. In contrast, there is a greater tendency toward earnings management in low enforcement environments. Domestic M&As showed a greater propensity for earnings management than cross-border M&As.

Keywords:
mergers and acquisitions; accounting information quality; enforcement; highly indebted targets

RESUMO

O objetivo desta pesquisa foi analisar a influência do enforcement na relação entre as fusões e aquisições (F&A) transfronteiriças e domésticas com alvos altamente endividados e o gerenciamento de resultados das companhias adquirentes de países que compõem o G20, no período de 2010 a 2022. O estudo aborda uma lacuna na literatura ao investigar como diferentes níveis de enforcement influenciam o gerenciamento de resultados em F&A, especialmente quando as empresas-alvo possuem alto endividamento. Além disso, compara essas influências em operações domésticas e transfronteiriças. O estudo explora a relação entre enforcement e gerenciamento de resultados, indicadores críticos da qualidade da informação contábil. A análise fornece insights sobre como o enforcement pode mitigar práticas contábeis oportunistas em F&A, afetando a transparência e a utilidade das informações para os investidores. As conclusões contribuem para gestores, investidores e reguladores ao demonstrar como o enforcement melhora a qualidade da informação contábil, especialmente em F&A de alvos endividados, orientando políticas que promovam a transparência e a redução de práticas oportunistas. A pesquisa utilizou regressão múltipla de dados em painel para adquirentes de alvos endividados, tendo como variável dependente o gerenciamento de resultados (Jones modificado e Pae) e como variáveis independentes a origem das F&A (domésticas e transfronteiriças), além das variáveis de controle. A análise foi efetuada para amostras de alto e baixo enforcement. Os resultados indicam que, em ambientes de alto enforcement, as empresas adquirentes em F&A de alvos altamente endividados adotam práticas contábeis mais conservadoras, resultando em menor gerenciamento de resultados. Em contrapartida, em ambientes de baixo enforcement, há maior tendência ao gerenciamento de resultados. As F&A domésticas mostraram maior propensão ao gerenciamento de resultados do que as transfronteiriças.

Palavras-chave:
fusões e aquisições; qualidade da informação contábil; enforcement; alvos altamente endividados

1 INTRODUCTION

The surge in mergers and acquisitions (M&As) worldwide has fueled the discussion about the value these transactions generate for the companies involved (Hussain et al., 2022). Since 2010, over 500,000 M&A transactions have been completed, with 2021 being the year with the most announcements, at over 60,000 (Statista, 2022). M&As are defined as the combination of two or more independent companies into a single entity through acquisition of control (Weston et al., 2013). These operations may be emphasized because M&As are considered a short-term corporate growth strategy (Hussain et al., 2022) that creates and distributes value for companies (Malmendier et al., 2018) and facilitates entry into the global market (Cartwright & Cooper, 1990; Deng & Yang, 2015; Khan et al., 2021).

To ensure the success of an M&A, the process must be guided by a clear business strategy aligned with the company's long-term objectives and a careful assessment of the tangible and intangible assets involved in the transaction (Haspeslagh & Jemison, 1991; Hambrick & Crozier, 1985). In this context, the financial structure of target companies can be a decisive factor in the success or failure of the operation. Highly indebted companies can become more attractive targets for M&As, especially if they are undervalued or facing financial difficulties. This creates opportunities for acquirers seeking synergy gains or strategic expansion (Harford et al., 2009).

However, the quality of the debt - including the term, cost, and guarantees - can significantly impact the viability of the acquisition. Short-term debts with high financial costs pose an additional risk to the acquirer and can reduce the potential success of the transaction (Bris & Cabolis, 2008). They can also make it difficult to obtain financing for the acquisition since the added risk can make fundraising more expensive or limited (Chemmanur et al., 2011) and increase the complexity of integrating the companies (Weber et al., 1996). For this reason, Tang et al. (2021) emphasize the need to adopt strategic actions to mitigate these challenges by considering not only the amount of debt, but also its specific characteristics, such as term and financial cost.

Merging with a highly indebted company can create challenges when consolidating and presenting the acquiring company's financial statements. It can be difficult to properly identify, evaluate, and disclose the acquired company's transactions, assets, and liabilities (Dechow et al., 2010). Additionally, acquiring companies may be incentivized to manipulate accounting results to improve their financial position and meet investors' expectations regarding synergies in operations (Healy & Wahlen, 1999).

The quality of accounting information provided by acquiring companies seeking highly indebted targets may be compromised by accounting practices involving adjustments to estimates. Examples include the premature recognition of revenues and the omission of relevant costs and liabilities (Botsari & Meeks, 2008; Erickson & Wang, 1999; Higgins, 2013). These practices compromise the relevance and reliability of accounting figures (Porter & Norton, 2014). These aspects can be measured by the propensity for earnings management (Dechow et al., 2010; Wang, 2006) because incentives for acquiring companies to present positive operational results can encourage managers to engage in opportunistic behavior regarding the accounting information reported by companies, thereby affecting its quality.

A country's institutional and environmental characteristics play a key role in the quality of accounting information reported to external users (Dechow & Schrand, 2004; Dechow et al., 2010). One such factor is the level of enforcement, which refers to the regulatory system's ability to ensure compliance with accounting and financial standards (La Porta et al., 1998). However, enforcement should not be analyzed in isolation because its effectiveness depends on its interaction with other institutional mechanisms, such as corporate governance. Corporate governance can mitigate opportunistic practices in the disclosure of accounting information (Djankov et al., 2008; La Porta et al., 2000). Thus, enforcement can reduce incentives for earnings management regardless of the presence or absence of other governance mechanisms (Ball et al., 2000).

The level of enforcement varies between countries due to several factors, including the effectiveness of regulatory institutions, law enforcement capacity, compliance culture, and the availability of resources for oversight and monitoring (Coffee, 2002; La Porta et al., 1998). In environments with rigorous enforcement, penalties for noncompliance with accounting standards tend to be severe, increasing the transparency and reliability of financial reports. Conversely, in countries with weaker enforcement, there is less monitoring and enforcement of rules, which can facilitate inappropriate accounting practices such as earnings manipulation (Dechow et al., 1995; Healy & Wahlen, 1999; Schipper, 1989), omission of relevant information (Cohen et al., 2010; Francis, LaFond et al., 2005; Skinner, 1993), and premature recognition of revenues (Ball et al., 2000; Hope et al., 2008). Thus, enforcement plays an essential role in the quality of accounting information, influencing the credibility of financial statements and investor protection.

Environments with more severe enforcement instruments - such as greater monitoring and investor protection (Djankov et al., 2008) - influence accounting choices with varying degrees of discretion (Dechow et al., 2010) and can affect market behavior in response to share price fluctuations after financial statement disclosure (Barth, 2008). These differences are due to regulatory, behavioral, fiscal, and cultural factors that affect managers' incentives to make conservative decisions with less earnings management and greater relevance to their stakeholders (Ball et al., 2000; Choi et al., 2018; Xie et al., 2017). This level of standard enforcement monitors the information that companies disclose (Ewert & Wagenhofer, 2019) and influences the quality of this reporting. It also affects how users receive this information, given the greater reliability generated by increased oversight (Bigus & Dreyer, 2023).

From the perspective of domestic (national) and cross-border (international) M&As, significant differences may exist in the enforcement environment in which acquiring companies operate and the quality of information reported (La Porta et al., 1998; Coffee, 2002). Domestic M&As normally take place within the same country, so the acquiring and target companies are subject to the same regulatory and legal environment (La Porta et al., 1998; Coffee, 2002; Jensen, 1976). This results in the harmonization of accounting practices and simplifies accounting and operational integration while reducing regulatory and legal compliance risk (Biddle et al., 2009; Francis et al., 1999).

Therefore, domestic M&As are expected to demonstrate greater synergy in the short term because they are less complex than cross-border transactions. This creates a greater incentive for acquirers to manipulate accounting results to improve their financial position and meet investor expectations (Cohen et al., 2010; Francis, Khurana et al., 2005; Skinner, 1993). In cross-border M&As, however, the greater complexity stems from differences in accounting systems, organizational cultures, corporate governance practices, and regulatory environments between the acquiring and target companies. In this context, synergy gains are expected to occur more in the long term, which reduces the incentive for managers to manipulate results through accruals.

However, evidence suggests that, even in cross-border M&As, managers can replace earnings management via accruals with management via operating transactions. This involves adjusting actual activities, such as anticipating or postponing expenses and investments, to influence reported profits (Purayil & Lukose, 2021). Thus, less manipulation via accruals does not necessarily imply an overall reduction in earnings management but rather a possible change in strategy to achieve desired objectives. Additionally, the level of enforcement in the countries where companies are located affects these operations. In countries with lower enforcement, monitoring and control of the accounting information and figures involved in these transactions is reduced (Ball et al., 2000; Lang et al., 2008).

Little is known about how different levels of enforcement affect the relationship between the quality of reported accounting information and M&As with regard to highly indebted target companies. While acquiring companies and their stakeholders expect value creation in these transactions (Malmendier et al., 2018), there is still no consensus on the actual impact of M&As on acquiring companies' results in the post-announcement period (Capron & Pistre, 2002). Some studies highlight positive impacts on results, albeit minimal (Chatterjee, 1986; Tunyi, 2021), while others indicate that acquiring companies tend to perform worse after M&A transactions (Datta et al., 1992; Renneboog & Vansteenkiste, 2019).

Thus, the present study aims to analyze how enforcement influences the relationship between cross-border and domestic M&As involving highly indebted targets and the management of acquiring companies' earnings in G20 countries from 2010 to 2022. Analyzing the influence of enforcement on M&A transactions involving highly indebted targets is essential to understanding how different regulatory environments affect the quality of accounting information and acquiring companies' behavior.

This study contributes significantly to the literature by exploring the relationship between enforcement and reliable accounting information production. It highlights the importance of robust regulation to mitigate risks and promote investor confidence, particularly in G20 countries where international cooperation is crucial for harmonizing accounting standards and ensuring financial transparency.

Focusing on highly indebted target companies reveals the trade-off between synergy gains and increased risks in these operations, providing stakeholders with valuable insight for making informed decisions. Additionally, by addressing incentives for opportunistic behavior under agency theory, the study enhances accounting information users' understanding of typical behaviors in M&A transactions, both domestic and cross-border. This helps companies and their stakeholders plan and invest more effectively and prepare for future M&As, enabling them to better understand and communicate potential outcomes in their operating markets.

2 THEORETICAL ASSUMPTIONS

M&As are transactions between two or more legally and economically independent companies that aim to form a larger economic entity (Ernst & Häcker, 2011). This process can occur through the merger of liquid assets or through one company's acquisition of control of one or more businesses, as part of an organizational growth strategy (Hambrick & Crozier, 1985).

To achieve greater synergy and diversify their businesses by targeting technological and innovative opportunities, many companies conduct M&As with highly indebted target companies (Andrade et al., 2001; Bena & Li, 2014; Higgins & Rodriguez, 2006). However, these operations can be risky due to financial instability and uncertainty resulting from incorporation. The acquirer must supply missing resources to the acquired company to prevent shareholder wealth impairment (Bruyland & Maeseneire, 2016). This can burden the acquirer financially, increasing costs and expenses while reducing transaction and acquirer performance. Business strategies must be implemented immediately to mitigate these problems (Tang et al., 2021).

During M&A operations, managers of acquiring companies may act opportunistically, making decisions that benefit them personally (Jensen & Meckling, 1976). They may aim to overvalue pre-announcement shares and achieve post-acquisition targets, which undermines business efficiency and investments (Chu et al., 2016). Seeking synergy and incentives for opportunistic decision-making by managers of acquiring companies leads to earnings management practices in the period preceding M&As (Botsari & Meeks, 2008; Bartov et al., 2021; Erickson & Wang, 1999; Higgins, 2013).

Earnings management can be conceptualized as intentional adjustments arising from the accrual basis of accounting (Dechow & Dichev, 2002). These adjustments use the subjectivity postulated in accounting standards to manipulate external users' perception of the results reported by companies (Healy & Wahlen, 1999). There are two main forms of earnings management: via discretionary accruals and via operating activities. Accrual-based management involves accounting adjustments that have no direct impact on cash flows (Dechow et al., 2010), and it is considered less harmful to a company's long-term performance (Roychowdhury, 2006).

Studies such as that by Purayil and Lukose (2021) suggest that in cross-border M&As, reducing accrual-based management may prompt managers to replace it with activity-based management, adjusting operating transactions. However, this study focuses on accrual-based management for three main reasons. First, enforcement acts directly on accounting adjustments, making accruals a more relevant metric for assessing regulatory impact. Second, accrual-based management measurement techniques are more well-established in the literature, enabling a more robust empirical analysis (Jones, 1991; Dechow et al., 1995). Third, in the context of M&As, accounting manipulation via accruals is more evident than actual activity-based management due to the need to maintain the appearance of financial soundness in the short term (Botsari & Meeks, 2008; Erickson & Wang, 1999). Thus, although the substitution between accruals and actual activities is recognized, the approach adopted in this study is justified by its methodological alignment with the research objectives.

Additionally, the characteristics of the environment in which companies operate may affect these M&As (Xie et al., 2017) due to the varying levels of enforcement in countries where acquiring and target companies trade shares. Xie et al. (2017) demonstrate in their analysis of a country's characteristics and their relationship with M&As that, in general, the greater the economic and financial distance between the acquiring and target companies, the greater the consequences of their different levels of enforcement in aspects such as the proportion of control and time to complete the transaction. Similarly, Kim and Wu (2008) and Nguyen and Knyphausen-Aufseß (2016) demonstrate that high long-term credit ratings and lower economic uncertainty stimulate M&A transactions. This corroborates the idea that environments with high macroeconomic enforcement and less uncertainty encourage these transactions.

In the context of the quality of accounting information of companies involved in these transactions, a higher level of enforcement is related to more rigorous monitoring and supervision of the application of accounting standards. This ensures higher quality for users by supervisory bodies (Brown et al., 2014; Healy & Palepu, 2001; La Porta et al., 1998). This environment of greater enforcement improves the quality of accounting information by reducing discretion in reported results (Dechow et al., 2010). Additionally, Purayil and Lukose (2021) argue that, when negotiating with targets in countries with a high level of enforcement, acquiring companies in cross-border M&As are less likely to manipulate their results due to strict monitoring and law enforcement in these environments.

On the other hand, the quality of accounting information tends to be lower in environments with less regulatory enforcement because discretion in accounting decisions increases (Bigus & Dreyer, 2023). This is because regulatory gaps and less rigorous accounting practices can be exploited in environments with low levels of enforcement. Conversely, countries with greater enforcement discourage these practices due to stricter supervision and the greater risk of legal repercussions (Henley, 2021).

Additionally, domestic M&A transactions are more prone to earnings management due to less regulatory oversight and the expectation of improving acquiring companies' performance (Jiraporn et al., 2008; Botsari & Meeks, 2008). Cross-border M&As, on the other hand, are subject to greater scrutiny and stricter international standards and face fewer opportunities for earnings manipulation (Ho, 2010; Purayil & Lukose, 2021). In this context, hypothesis 1 (H1) of the study is formulated.

H1: Acquiring companies in M&As in countries with lower enforcement show greater earnings management in transactions with highly indebted target companies, especially domestic ones.

Hypothesis H1 is based on agency theory and the concept of information asymmetry, particularly with regard to the origins of companies involved in M&As. While regulatory and institutional similarity does not prevent earnings management in domestic transactions, it influences the manner in which it occurs. While similar rules and oversight increase the predictability of the accounting environment, they may also facilitate the identification of regulatory gaps that managers can exploit (La Porta et al., 2000). In contrast, cross-border transactions face greater challenges due to differences in regulatory environments between the countries involved. These differences can exacerbate the information asymmetry between acquiring and target companies, making earnings management more likely.

3 METHODOLOGICAL PROCEDURES

This research uses data from Refinitiv®, the World Bank, the Worldwide Governance Indicators (WGI), and the IFRS Foundation. Financial institutions were not analyzed because their capital structure is more leveraged than that of other companies, and they are subject to specific industry regulations that could undermine the comparability of the companies analyzed. Additionally, only companies that carried out M&A transactions with highly indebted targets from 2010 to 2022 were analyzed.

To provide greater comparability of the results among the companies under study, we considered only M&A transactions in which the acquirer held 100% of the target company's voting shares, either through total acquisition or through acquiring a percentage of the target company, resulting in 100% control after the acquisition. If each company carried out more than one transaction, we considered the debt of the target company with the most representative value, taking only that transaction into account for analysis purposes.

Table 1 shows the research variables. The research is based on discretionary accruals as a variable for earnings management, analyzing two models: the modified Jones model (Dechow et al., 1995) and the Pae model (2005). In the modified Jones model, discretionary accruals are defined as the difference between total accruals and non-discretionary accruals. First, the betas (β1, β2, and β3) of the Jones (1991) model are estimated. These provide the regression coefficients that explain the total accruals of the analyzed companies based on accounts such as assets from the previous period, revenue variation, and fixed assets.

Table 1
Description of variables in the earnings management analysis

Variables		Metric		Expected relationship	Theoretical basis	Data source
Dependent variables
Earnings management (EM)	Discretionary accruals	DAJ	Estimated using the modified Jones model (Dechow et al., 1995).			Refinitiv
		DAP	Estimated using the Pae model (2005).			Refinitiv
Independent variables of interest
Origin of M&A	Domestic	DOM	Dummy for domestic (national) M&A transactions, i.e., when the acquirer and the acquired company are from the same country.	+	Botsari & Meeks (2008); Jiraporn et al. (2008)	Refinitiv
	Cross-border	CRB	Dummy for cross-border M&A transactions, i.e., when the acquirer and the acquired company are from different countries.	+	Ho (2010); Purayil & Lukose (2021)	Refinitiv
Independent control variables
Size		Size	Natural logarithm of the acquiring company's total assets.	-	Dechow et al. (2010)	Refinitiv
Experience in adopting IFRS		IFRS	Time in years since the acquiring company's country of origin adopted IFRS.	-	Brown et al. (2014); Healy & Palepu (2001)	Refinitiv
Gross Domestic Product		GDP	Real GDP growth, represented by the percentage growth in GDP from one year to the next.	-	Kim & Wu (2008); Nguyen & Knyphausen-Aufseß (2016)	Standard & Poor's
Inflation		INF	Inflation rate indicator in percentage terms.	+	Henley (2021)	Standard & Poor's
Rule of Law		RL	Rule of law indicator, scaled from 0 to 100.	-	La Porta et al. (1998)	World Bank (WGI)
Regulatory Quality		RQ	Regulatory quality, scaled from 0 to 100.	-	Djankov et al. (2008)	World Bank (WGI)
Covid		Covid	Dummy representing the Covid-19 pandemic period in 2020 and 2021, taking the value 1 during this period and 0 during the others.	+	Bigus & Dreyer (2023)	-
Scenarios analyzed (segmented in the regression analysis)
Level of Enforcement	Low Enforcement	LEF	Dummy representing a low level of enforcement in the countries of origin of the acquiring companies. That is, if below average, it is considered 1; if above, it is considered 0.	+	Healy & Wahlen (1999); Schipper (1989)	World Bank, Trading Economics, Leuz (2010), Brown et al. (2014)
	High Enforcement	HEF	Dummy representing a high level of enforcement in the countries of origin of the acquiring companies. That is, if above average, it is considered 1; if below, it is considered 0.	-	Ball et al. (2000); Purayil & Lukose (2021)

• Note: Fixed sector and year effects controlled.
• Source: Prepared by the authors.

$$TACit=(∆CAit-∆Cashit)-(∆CLit-∆Debtit)-Deprit$$ (1)

$$TACit=\beta 1(1/At-1)+\beta 2(∆Rit/Ait-1)+\beta 3(PPEit/Ait-1)+\varepsilon it$$ (2)

$$TACit=("\beta 1")̂(1/At-1)+("\beta 2")̂\left(\right(∆Rit-∆CRit)/Ait-1)+("\beta 3")̂(PPEit/Ait-1)$$ (3)

where: TACit = total accruals of company i in period t; ∆CAit = change in current assets of company i from the end of period t-1 to the end of period t; ∆CLit = change in current liabilities of company i from the end of period t-1 to the end of period t; ∆Cashit = change in company i's cash and cash equivalents from the end of period t-1 to the end of period t; ∆Debtit = change in company i's short-term financing and loans from the end of period t-1 to the end of period t; and Deprit = company i's depreciation and amortization expenses during period t. All non-binary variables are weighted by total assets at the beginning of period t.

Furthermore, as shown in Equation 4, the model proposed by Pae (2005) is based on the persistence of operating cash flows in companies' accrual adjustments.

$$TACit=\alpha (1/At-1)+\beta 1\Delta Rit+\beta 2PPEit+\beta 3OCFit+\beta 4OCFit-1+\beta 5TAit-1+\epsilon it$$ (4)

where: TACit = total accruals of company i in the current period t, weighted by total assets at the beginning of period t; ∆Rit = change in net revenues of company i from period t-1 to period t, weighted by total assets at the beginning of period t; PPEit = balances of fixed assets and deferred assets (gross) of company i at the end of period t, weighted by total assets at the beginning of period t; Ait-1 = total assets of company i at the end of period t-1, weighted by total assets at the beginning of period t; OCFit = operating cash flow of company i in period t, weighted by total assets at the beginning of period t; OCFit-1 = operating cash flow of company i in period t-1, weighted by total assets at the beginning of period t; TAit-1 = total accruals of company i in period t-1, weighted by total assets at the beginning of period t; and εit = regression residual for company i in year t, considered the discretionary accruals variable of the Pae model (DAP) in this study.

The enforcement metric used in Table 2 is based on the methodologies of Leuz (2010) and Brown et al. (2014). These methodologies are widely recognized in the literature for measuring regulatory quality and the enforcement of accounting standards. For this estimate, we considered indicators reflecting regulatory rigor and enforcement effectiveness, such as economic development, real GDP per capita, securities regulation, self-dealing contracts, the rule of law, and class actions.

Leuz's (2010) metric evaluates the rigor and effectiveness of corporate reporting regulations by comparing jurisdictions based on institutional and governance variables. Securities regulation is analyzed in three dimensions: (i) disclosure requirements, measuring the transparency required of companies in public offerings of securities; (ii) accountability standards, assessing the accountability of issuers, directors, and distributors; and (iii) public enforcement, covering regulatory powers, investigative capacity, and the imposition of sanctions by regulatory authorities.

Additionally, the metric incorporates the Shareholder Protection Index by Djankov et al. (2008), which measures corporate governance through the following: (i) anti-director rights, (ii) ex ante control (preventive regulatory mechanisms), (iii) ex post control (capacity for judicial action), and (iv) public enforcement aimed at investor protection. Each country's legal system is covered by two indicators: rule of law, which measures institutional strength and confidence in compliance with rules (La Porta et al., 1998); and class actions, which reflect the existence of legal mechanisms enabling shareholders to litigate collectively against administrative abuses (Leuz, 2010).

The metric developed by Brown et al. (2014) supplements the model by considering the following six dimensions of accounting enforcement: (i) the existence of a regulatory body that monitors accounting compliance, (ii) this body's authority to establish standards, (iii) periodic audits and reviews of financial statements, (iv) the disclosure of the results of these reviews, (v) the imposition of sanctions in cases of regulatory noncompliance, and (vi) the organizational structure of the regulatory body, including the number of employees allocated to supervision per million inhabitants.

Table 2
Estimated level of enforcement for G20 countries

Country	Economic development	Real GDP per capita	Securities regulation				Self-Dealing Contracts			Rule of Law	Class actions
			Disclosure requirements	Accountability standards	Public enforcement	Anti-director rights	Ex ante control	Ex post control	Public enforcement
Argentina	0	1.29	0.5	0.22	0.58	2	0.33	0.35	0	0.18	0
Australia	1	6.08	0.75	0.66	0.9	4	0.89	0.63	0.5	2	1
Austria	1	4.7	0.25	0.11	0.17	3	0	0.43	1	2.1	0
Belgium	1	4.41	0.42	0.44	0.15	3	0.39	0.7	0.5	1.64	0
Brazil	0	0.88	0.25	0.33	0.58	5	0.22	0.32	0.5	-0.15	1
Canada	1	4.49	0.92	1	0.8	4	0.33	0.95	1	2.01	1
Denmark	1	6.01	0.58	0.55	0.37	4	0.25	0.68	0.75	1.97	0
Finland	1	4.71	0.5	0.66	0.32	4	0.14	0.77	0	2.13	0
France	1	3.89	0.75	0.22	0.77	4	0.08	0.68	0.5	1.49	1
Germany	1	4.3	0.42	0	0.22	4	0.14	0.43	1	1.91	0
Greece	1	2.02	0.33	0.5	0.32	2	0.08	0.35	0.5	0.75	0
India	0	0.21	0.92	0.66	0.67	5	0.33	0.82	0.5	0.23	1
Indonesia	0	0.41	0.5	0.66	0.62	4	0.81	0.5	0	-0.9	0
Ireland	1	9.86	0.67	0.44	0.37	5	0.78	0.8	0	1.86	0
Italy	1	3.29	0.67	0.67	0.48	2	0.17	0.68	0	0.94	0
Japan	1	3.6	0.75	0.66	0	5	0.22	0.77	0	1.82	0
Mexico	0	0.98	0.58	0.11	0.35	3	0.19	0.15	0.5	-0.37	0
Netherlands	1	5	0.5	0.89	0.47	3	0.06	0.35	0	1.97	1
Portugal	1	2.21	0.42	0.66	0.58	3	0.14	0.75	1	1.16	1
South Africa	0	0.6	0.83	0.66	0.25	5	1	0.63	0	0.3	0
Spain	1	2.74	0.5	0.66	0.33	5	0.22	0.52	1	1.38	1
Sweden	1	5.55	0.58	0.28	0.5	4	0.17	0.5	1	1.98	0
Turkey	0	1.4	0.5	0.22	0.63	3	0.33	0.52	0	0.07	0
United Kingdom	1	4.72	0.83	0.66	0.68	5	1	0.9	0	1.93	1
United States	1	6.29	1	1	0.9	3	0.33	0.98	0	1.92	1
Max.	1	9.86	1	1	0.9	5	1	0.98	1	2.13	1
Min.	0	0.21	0.25	0	0	2	0	0.15	0	-0.9	0
Mean	0.72	3.59	0.6	0.52	0.48	3.76	0.34	0.61	0.41	1.21	0.4

• Source: Prepared by the authors.

Based on these indicators, a consolidated enforcement index was developed. The values were aggregated for each country analyzed, as shown in Table 3. The final classification was based on the average of the countries in the sample and was determined by whether they were classified as "high enforcement" (above average) or "low enforcement" (below average). To increase the accuracy of the metric, the data were updated based on original estimates by Leuz (2010) and new information on economic development and GDP per capita was incorporated. More developed capital markets tend to have more sophisticated and demanding regulations regarding transparency and the quality of financial statements (Zada et al., 2021), so this update is justified. Additionally, countries with higher real GDP per capita tend to have stricter regulatory systems, reinforcing the need to adjust the metric for greater representativeness and reliability of results (Crawley, 2015).

Finally, to ensure a robust, unbiased analysis, principal component analysis (PCA) was applied to consolidate the final enforcement metric. PCA reduces the dimensionality of the data by identifying patterns and relationships between variables and ensuring that the classification of countries is based exclusively on empirical data. This approach is a methodological improvement on the metrics proposed by Leuz (2010) and Brown et al. (2014) and provides a more accurate assessment of the relationship between enforcement and earnings management in M&A transactions.

Table 3
Classification of high and low enforcement

Country	Enforcement (Leuz. 2010)		Enforcement (Brown et al.. 2014)		Enforcement (PCA)		Convergence between metrics	Present Data on Highly Indebted Targets	Final sample
	Level	Class.	Level	Class.	Level	Class.
South Africa	9.27	Low	29.00	Low	6.72	Low	Converges	Yes	7
Germany	13.42	High	44.00	High	18.36	High	Converges	Yes	32
Argentina	5.45	Low	11.00	Low	6.03	Low	Converges	Yes	2
Australia	18.41	High	52.00	High	25.13	High	Converges	Yes	29
Austria	12.76	High	27.00	Low	18.74	High	Diverges	Yes	0
Belgium	12.65	High	44.00	High	18.66	High	Converges	Yes	6
Brazil	8.93	Low	23.00	Low	6.22	Low	Converges	Yes	15
Canada	17.5	High	54.00	High	21.38	High	Converges	Yes	59
Denmark	16.16	High	49.00	High	23.95	High	Converges	Yes	4
Spain	14.35	High	42.00	High	15.68	Low	Diverges	Yes	0
United States	17.42	High	56.00	High	25.74	High	Converges	Yes	499
Finland	14.23	High	32.00	Low	20.32	High	Diverges	Yes	0
France	14.38	High	45.00	High	18.36	High	Converges	Yes	33
Greece	7.85	Low	26.00	Low	11.57	Low	Converges	Yes	2
Netherlands	14.24	High	43.00	High	20.89	High	Converges	Yes	8
India	10.34	Low	21.00	Low	6.03	Low	Converges	Yes	18
Indonesia	6.6	Low	14.00	Low	5.30	Low	Converges	No	0
Ireland	20.78	High	41.00	High	34.86	High	Converges	No	0
Italy	9.9	Low	46.00	High	15.81	Low	Diverges	Yes	0
Japan	13.82	High	34.00	Low	17.99	High	Diverges	Yes	0
Mexico	5.49	Low	25.00	Low	5.47	Low	Converges	Yes	11
Portugal	11.92	Low	29.00	Low	13.34	Low	Converges	Yes	11
United Kingdom	17.72	High	54.00	High	21.96	High	Converges	Yes	50
Sweden	15.56	High	34.00	Low	22.48	High	Diverges	Yes	0
Turkey	6.67	Low	20.00	Low	6.88	Low	Converges	Yes	3
Total									789
Mean	12.63	-	35.80	-	16.31	-	-	-	-
Standard deviation	4.29	-	13.03	-	7.88	-	-	-	-
Minimum	5.45	-	11.00	-	5.30	-	-	-	-
Maximum	20.78	-	56.00	-	34.86	-	-	-	-

• Source: Prepared by the authors.

The high debt classification was based on the average RANKVAL of each sector of the target company in the operations of the countries analyzed.

$$RANKVAL=VALNOLIA+\left(NETDEBT\right)–CASH$$ (5)

$$RANKVAL=VALNOLIA+(STRD+STD+PFDEQ)-CASH$$ (6)

where: RANKVAL corresponds to the target's net debt ranking value; VALNOLIA is the transaction value; NETDEBT is the net debt value of the target company; CASH refers to cash and securities on the date of the most recent financial information prior to the announcement of the transaction; STRD is simple debt, representing the total amount of financial obligations of the target company without any convertibility into shares or preferential characteristics; STD is short-term debt referring to obligations maturing in less than one year; and PFDEQ is the value of preferred capital corresponding to the amount of preferred shares issued by the target company, generally with hybrid characteristics between debt and equity.

Finally, for the regression analysis of earnings management, the model shown in Equations 8 and 9 was operationalized.

$$DAJii=\alpha +\beta 1DOMit+\beta 2CRBit+\beta 3Sizeit+\beta 4GDPit+\beta 5INFit+\beta 6RLit+\beta 7RQit+\beta 8Covidit+\varepsilon it$$ (7)

$$DAPii=\alpha +\beta 1DOMit+\beta 2CRBit+\beta 3Sizeit+\beta 4GDPit+\beta 5INFit+\beta 6RLit+\beta 7RQit+\beta 8Covidit+\varepsilon it$$ (8)

Notably, this model was run using regression to the mean for each enforcement level (high and low) and by segregating positive and negative earnings management proxy values for three main reasons. First, it helps identify different accounting manipulation strategies, such as inflating profits in periods of low performance or creating reserves in periods of high performance. This prevents the offsetting effects between positive and negative accruals from masking the true extent of earnings management (Dechow et al., 1995). Second, it detects practices such as creating "cookie jar reserves," which provide a greater margin of values to smooth earnings over time (Healy, 1985). Third, it offers a more detailed view of accounting practices by better controlling contextual variables and specific circumstances that influence earnings management, such as economic conditions and management objectives (Dechow et al., 2010).

4 RESULTS

Table 4 shows the descriptive statistics for the research variables.

Table 4
Descriptive statistics for the research variables

Variables	Enforcement Level	Origin	Observations	Mean	St. Deviation	Median	Minimum	Maximum
DAJ	High	DOM	1,445	-0.04731	0.20642	-0.05005	-1.25378	1.29243
		CRB	749	-0.03580	0.18738	-0.03699	-1.30888	1.21736
	Low	DOM	69	-0.03555	0.30841	-0.04829	-1.51431	1.32994
		CRB	33	0.01203	0.16973	-0.00996	-0.36128	0.57761
	Total	DOM	1,514	-0.04678	0.21201	-0.04992	-1.51431	1.32994
		CRB	782	-0.03378	0.18682	-0.03495	-1.30888	1.21736
DAP	High	DOM	1,485	-0.00426	0.19326	-0.02151	-0.80957	1.52658
		CRB	763	-0.00028	0.17714	-0.01974	-0.75414	1.53818
	Low	DOM	72	-0.00762	0.19873	-0.02082	-0.53751	0.64881
		CRB	36	0.02550	0.15420	0.01678	-0.36060	0.61912
	Total	DOM	1,557	-0.00442	0.19345	-0.02139	-0.80957	1.52658
		CRB	799	0.00088	0.17616	-0.01847	-0.75414	1.53818

• Source: Prepared by the authors.

According to Table 4, countries with a high level of enforcement have average discretionary accruals using the modified Jones model (DAJ) of -0.04731 for domestic M&As, with a standard deviation of 0.20642. This indicates greater variability than companies that carried out cross-border operations, which have a standard deviation of 0.18738. Since higher standard deviations indicate greater dispersion of regression errors and a higher likelihood of earnings management through discretionary managerial decisions, companies traded in countries with high enforcement levels and that acquire highly indebted targets from the same country tend to exhibit a greater propensity for earnings management. Lower variability in cross-border M&As can be attributed to stricter regulatory controls and greater oversight of international transactions (Dechow et al., 2010; Jiraporn et al., 2008; Botsari & Meeks, 2008).

Conversely, countries with low levels of enforcement exhibit average discretionary accruals (ADJ) of -0.03555 for domestic M&As, with a standard deviation of 0.30841. This represents the highest variability when comparing the origin of acquiring and target companies (i.e., domestic versus cross-border M&As) and the level of enforcement. This high standard deviation suggests a greater propensity for earnings management, which corroborates the hypothesis that domestic transactions in environments with lower enforcement allow for more discretionary practices.

Regarding discretionary accruals using the Pae model (DAP), the result is similar. Analyzing companies from countries with high levels of enforcement for domestic M&As (0.19326) reveals greater variability than in cross-border transactions (0.17714). This corroborates the idea that managers would be less incentivized to manipulate their results in international transactions due to greater regulatory scrutiny and strict adherence to international standards (Ho, 2010; Purayil & Lukose, 2021).

The same occurs when analyzing companies from countries with low enforcement. The standard deviation is 0.19873, which corroborates the findings in the literature that a lack of strict enforcement allows for greater flexibility in discretionary practices. This results in greater variability in earnings management proxies and a greater propensity for earnings management (Healy & Palepu, 2001). Additionally, the greater variability observed in domestic transactions in countries with low enforcement suggests that companies in these countries take advantage of less oversight to manage earnings, particularly in transactions with highly indebted target companies.

Using the research data, we performed panel data regressions on the mean (see Table 5) with outlier treatment (1% winsorization) to analyze the influence of enforcement on the relationship between cross-border and domestic M&As with highly indebted targets and the earnings management of acquiring companies in G20 countries.

As seen in Table 5, the constant is significantly negative in all models and submodels. This indicates a general trend of negative discretionary accruals. Thus, on average, companies tend to exhibit lower earnings management in both models, regardless of the level of enforcement to which they are subject. These findings show that, even with the premise that conservative practices tend to exist in more rigid regulatory environments (Dechow et al., 2010) and that earnings management reduces companies' profits, more conservative practices can be seen in M&As with highly indebted targets in different enforcement realities. This can be explained by the higher risk associated with this type of operation (Bruyland & Maeseneire, 2016) and the potential financial burdens brought about by these targets (Tang et al., 2021).

Table 5
Regression to the mean of the earnings management model

Variables	(1)		(2)		(3)		(4)		(5)		(6)
	DAJ						DAP
	All		HEF		LEF		All		HEF		LEF
Constant	-2.293***	(0.193)	-2.300***	(0.210)	-2.473***	(0.736)	-2.200***	(0.163)	-2.252***	(0.183)	-1.865***	(0.654)
DOM	-0.002	(0.007)	-0.004	(0.007)	0.041	(0.037)	-0.007	(0.006)	-0.008	(0.007)	0.015	(0.024)
CRB	0.011	(0.008)	0.007	(0.009)	0.107***	(0.034)	0.01	(0.008)	0.008	(0.008)	0.057*	(0.033)
Size	0.084***	(0.008)	0.083***	(0.009)	0.100***	(0.034)	0.089***	(0.007)	0.089***	(0.007)	0.084***	(0.030)
GDP	-0.303***	(0.116)	-0.365***	(0.122)	0.321	(0.364)	-0.360***	(0.104)	-0.418***	(0.109)	0.179	(0.304)
INF	-0.605*	(0.336)	-0.848	(0.636)	-0.302	(1.023)	-0.435	(0.282)	0.053	(0.549)	-0.599	(0.790)
RL	0.147**	(0.057)	0.144**	(0.071)	0.194	(0.140)	0.179***	(0.050)	0.215***	(0.066)	0.036	(0.144)
RQ	0.005	(0.032)	0.01	(0.045)	-0.049	(0.095)	-0.009	(0.026)	-0.04	(0.039)	0.015	(0.082)
Covid	-0.026***	(0.006)	-0.027***	(0.007)	-0.002	(0.031)	-0.026***	(0.006)	-0.027***	(0.006)	-0.005	(0.033)
Observations	7.089		6.544		545		7.413		6.829		584
Firms	779		724		55		777		722		55
R2	0.13		0.127		0.192		0.054		0.056		0.067
Adjusted R2	0.128		0.125		0.161		0.052		0.053		0.033
F-test	23.637		21.075		5.008		13.52		13.039		2.854

• ^*
  ^** , ^** , and ^* indicate significance levels of 1%, 5%, and 10%, respectively.
• Source: Prepared by the authors.

For domestic M&As, the coefficients are not statistically significant in most models. This indicates that there is no robust evidence showing that domestic M&As consistently impact discretionary accruals. In contrast, in countries with low enforcement (LEF), the DAJ model shows a positive coefficient (0.041), though it is not statistically significant. Contrary to expectations, cross-border M&As have a positive and significant impact on earnings management, particularly in countries with low enforcement (LEF).

In the DAJ model, the coefficient is 0.107 at the 1% level; in the DAP model, it is 0.057 at the 10% level. These results suggest that companies engaging in cross-border M&As in countries with low enforcement tend to engage in more earnings management, likely due to less regulatory rigidity and the greater risk associated with this type of international operation. These findings corroborate the existing literature on enforcement, which suggests that less monitoring and control by regulatory agencies provides a greater incentive for earnings manipulation (Dechow et al., 1996; Healy & Wahlen, 1999; Schipper, 1989). However, these findings do not align with the literature addressing the origin of M&As (domestic and cross-border), which suggests that domestic operations tend to exhibit greater manipulation because higher earnings are expected in the short term (Cohen et al., 2010; Francis, Khurana et al., 2005; Skinner, 1993).

Overall, the results corroborate the existing literature, which suggests that enforcement plays a crucial role in moderating earnings management practices, regardless of the context analyzed. Companies in countries with low enforcement seem more likely to manage earnings, especially in cross-border M&A contexts. This is contrary to what would be expected for this type of M&A origin. This finding is consistent with literature pointing to lower regulatory effectiveness in these countries, which allows for greater flexibility in opportunistic accounting practices (Cartwright & Cooper, 1990; Henley, 2021).

To ensure the robustness of the analysis, positive and negative discretionary accruals in the sample were also analyzed. According to the analysis, cross-border M&As have a positive and significant coefficient in the positive discretionary accruals (DAJ) models, both when all companies are analyzed and when only those with high enforcement are analyzed. The values are 0.040 and 0.039, respectively, at the 1% level. This indicates that regulatory rigidity may encourage companies to inflate their earnings to show more robust financial performance post-acquisition (Henley, 2021). Conversely, in negative discretionary accruals (NDAJ), cross-border M&As exhibit negative coefficients, though they are only significant in countries with low enforcement (LEF), with a value of -0.059 at the 5% level. This suggests that, in less stringent regulatory environments, companies reduce their profits less.

Regarding domestic M&As, significant coefficients were found only in the case of positive accruals (DAJ and DAP) with positive coefficients in countries with low enforcement (LEF). For example, the coefficient was 0.121, and it was significant at the 10% level in the positive DAP model. This indicates a lower need for aggressive earnings management practices in domestic M&As, which generally involve less regulatory and cultural complexity (Botsari & Meeks, 2008). However, in the analysis of negative accruals, the coefficients are not significant, indicating that domestic M&As do not substantially impact earnings reductions when companies manipulate profits.

An important aspect to consider is the impact of acquiring highly indebted target companies. According to the results of this study, these companies are more likely to manage their earnings downward. This is contrary to what is suggested in the literature, which states that highly indebted companies would be more likely to engage in earnings management practices to improve perceptions of their financial health (Bartov et al., 2021). Thus, this finding suggests that companies tend to adopt more conservative practices when managing earnings on average, possibly due to the greater risk and scrutiny associated with highly indebted targets (Bruyland & Maeseneire, 2016). The combination of high indebtedness and low enforcement quality can create an environment conducive to earnings management; however, the need to maintain an appearance of stability can lead to more conservative accounting practices.

Furthermore, based on the results, Hypothesis 1 is rejected. Evidence shows that companies from countries with low enforcement tend to engage in more earnings management in cross-border M&As. However, this trend is not consistently observed in domestic M&As. The dynamics of enforcement, the complexity of cross-border transactions, and the impact of acquiring highly indebted companies play crucial roles in modulating earnings management practices. These findings suggest that, although weaker enforcement permits more flexibility for aggressive accounting practices, the complexity and risks of cross-border M&As, as well as the high indebtedness of target companies, may encourage manipulation and the adoption of more conservative practices depending on the context (Cartwright & Cooper, 1990; Dechow et al., 2010).

Overall, the results indicate that enforcement plays a crucial role in moderating earnings management practices. This finding corroborates the literature suggesting that stricter regulatory environments inhibit opportunistic accounting practices. Companies in countries with low enforcement show a greater propensity to manage earnings, especially in cross-border M&A transactions. Therefore, when analyzing M&A origins, it is necessary to consider the enforcement to which these organizations are subject to analyze the quality of these companies' earnings. This analysis should consider factors jointly rather than separately.

5 CONCLUDING REMARKS

The results of the study suggest that environments with less enforcement lead to a greater tendency toward opportunistic accounting practices. This results in lower-quality accounting information from acquiring companies in M&As involving highly indebted target companies. Specifically, the study found that, in domestic transactions where companies operate within the same legal and cultural context, the expectation of short-term synergies may encourage earnings management, as suggested by previous research. However, this behavior does not manifest uniformly because other factors, such as the level of enforcement and the risk associated with transactions, also influence how companies manage their earnings.

Additionally, the high complexity and risks associated with M&As involving highly indebted target companies encourage acquiring companies to manage their earnings to appear financially healthier. In environments with greater enforcement, however, these companies tend to adopt more conservative accounting practices. This contrasts with the expectation that indebted companies will manage their earnings to improve perceptions of their financial position. This behavior suggests that the greater risk and regulatory scrutiny associated with cross-border transactions act as a deterrent to accounting manipulation.

The research also revealed that, contrary to initial hypotheses, there was no consistent trend toward greater earnings management in cross-border transactions in low-enforcement environments. The complexity and high indebtedness of target companies appear to significantly influence accounting practices. This suggests that factors other than enforcement play a crucial role in determining the quality of accounting information in M&As. Thus, the results reinforce the idea that the relationship between enforcement and earnings management is not linear and is instead mediated by the specific characteristics of transactions, such as the financial leverage of the target company and the degree of risk perceived by managers.

These findings underscore the importance of robust enforcement in ensuring the quality and relevance of accounting information. Theoretically, the research contributes by showing that high indebtedness can encourage accounting manipulation or promote conservative practices depending on the level of enforcement and M&A context. The research also emphasizes the importance of rigorous regulatory structures to increase the credibility of financial information.

However, it is important to highlight some limitations of this study. First, the research is based on data from companies in G20 countries, which limits generalization to economies with different levels of regulatory development. Additionally, the analysis focuses on earnings management via accruals without considering management via actual activities, which could be another significant form of accounting manipulation in certain contexts.

Given these limitations, future research should broaden its scope, including groups of countries with more heterogeneous regulatory characteristics and exploring the interaction between accrual-based and activity-based management. Additionally, future studies could analyze the impact of macroeconomic variables, such as economic cycles and financial crises, on earnings management in M&A transactions.

Finally, this study offers important practical contributions to managers, investors, and regulators by demonstrating how enforcement and M&A origin influence earnings management. These findings help formulate policies that promote transparency and reduce opportunistic accounting practices, thereby strengthening market confidence in M&A transactions.

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• This is a bilingual text. This article was originally written in Portuguese and published under the DOI https://doi.org/10.1590/1808-057x20252204.pt.
• This article stems from a doctoral thesis defended by the author, Vanessa Noguez Machado, in 2024.
• DATA AVAILABILITY STATEMENT
  Datasets related to this article are not publicly available.
• FUNDING
  The authors would like to thank the National Council for Scientific and Technological Development (CNPq) for its financial support in conducting this research.

Edited by

• Editor-in-Chief:
  Andson Braga de Aguiar

• Associate Editor:
  Márcia Martins Mendes De Luca

Data availability

Datasets related to this article are not publicly available.

Publication Dates

• Publication in this collection
  22 June 2026
• Date of issue
  2026

History

• Received
  29 Aug 2024
• Reviewed
  15 Oct 2024
• Accepted
  22 Apr 2025