This study aims to investigate how country-level characteristics influence the relationship between the adoption of international accounting standards and perceptions of corruption.
A quantitative analysis was conducted involving data from 130 countries, using information from Transparency International, the International Federation of Accountants and the World Bank.
The findings indicate that economic factors and law enforcement significantly strengthen the relationship between international accounting standards adoption and corruption perception. Cultural dimensions such as power distance and uncertainty avoidance moderate this relationship. Interestingly, this study reveals that the adoption of these standards is positively associated with corruption perception in developing countries but not in less developed and developed countries. This association is significantly positive in hybrid-regime and authoritarian countries, whereas it is weak in full-democracy and flawed-democracy countries.
The results offer several practical insights: countries adopting international accounting standards should consider country-level factors to improve implementation; multinational businesses can strategically choose countries with these standards and supportive characteristics for greater transparency; auditing firms can make informed decisions about engagements by evaluating the local implementation of these standards; international standard setters can see how accounting and auditing standards may reduce corruption perceptions in specific environments; and international financial institutions should consider each country’s context when requiring the adoption of these standards for loans in developing or less developed countries, enhancing their overall effectiveness.
This study enhances the understanding of international accounting standards by examining both private and public sector standards. It uniquely investigates how country-level characteristics, including economic, cultural, political and legal factors, serve as contingent factors.
