Purpose: This study aims to better understand the phenomenon of corruption in Tunisia in relation to its impact on economic development. The period of study is 1995 to 2014. The auto-regressive distributed lag (ARDL) model is adopted to examine the existence of a long-term relationship between the above-mentioned variables and also the direct and indirect consequences of corruption on economic development in Tunisia.Design/methodology/approach: The study uses a modern econometric technique to estimating the long-term relationship (e.g. the co-integration) between corruption and economic development; using this technique also allows us to investigate the impact of corruption on economic growth.Findings: The empirical results show that corruption has a negative effect on per capita gross domestic product (GDP) in Tunisia for the period under review. This effect is described as a direct effect of corruption in the long term; specifically, declines are observed in per capita GDP, over the long run, by almost 1 per cent, following a 1 per cent increase in the level of corruption. The results also show that corruption has indirect effects via transmission channels, such as investment in physical capital, which is positively significant in the presence of corruption. The same observation is made at the level of government expenditure during the previous year, while for those of the current year, the coefficient becomes negative but not significant. With respect to human capital, the impact of corruption on education expenditures is insignificant.Originality/value: The paper begins with an overview of previous literature in this area. Given the nature of corruption and the differences in the meanings attributed to it, from one country to another and from one culture to another, the paper moves on to study the impact of corruption in Tunisia as a case study for one country with one socio-cultural environment. The authors then propose several methods and possible solutions, which could be implemented to deal with this problem.

This study examines and evaluates the dynamic causality relationship between immigration, unemployment, wages and GDP per capita in host countries with a focus on Australia. Previous research has indicated that the economic impact of immigration is significant; nonetheless, its effect on the labour market being positive or negative is inconclusive. This study uses a Vector Error Correction Model (VECM) to examine the dynamic short- and long-run nexus between these variables in Australia over the period 1980–2016. The paper provides clear evidence to policy makers on the positive spillover effect of immigration policies developed by the Australian government.

Purpose: Despite the existence of laws, regulations and sanctions, financial crime remains widespread. The Panama leaks have proven that people from all over the world are participating in money laundering and other financial crimes. This study aims to investigate the influence of national culture on financial crimes across 78 countries.Design/methodology/approach: This study uses Hofstede’s cultural framework as a basis for its hypotheses on financial crime. It also uses the Basel anti-money laundering index as a proxy for measuring the incidence of financial crime across the countries under review.Findings: The findings show that countries whose cultural profiles are characterized by low uncertainty avoidance, low individualism, high masculinity and low long-term orientation have high rates of financial crime. The finding also shows that countries whose cultural profiles are characterized by individualism or positive collectivism, uncertainty avoidance and long-term orientation have low rates of financial crime.Originality/value: Laws, regulations and sanctions are not the only factors that can help deter the crime; governments should also take a holistic approach that includes the cultural factors that encourage deterrence.

Purpose—This study examines the interaction of economic openness, governance, and money laundering. The paper’s main objective is to analyze how trade openness, foreign direct investment, and anti-corruption measures influence the risk of money laundering in specific economic blocs. Design/methodology/approach—This study analyzes these economic blocs (EU, G20, BRICS, and CIVETS) using annual data from the Basel Institute on Governance and World Bank statistics for 2012–2021. A panel-corrected standard errors (PCSE) estimator is employed to examine the relationships among the variables, accounting for cross-sectional dependence and ensuring robust parameter estimation. The corruption control index is a proxy for governance effectiveness, though it does not directly measure regulatory strength. Future research should incorporate more specific variables to evaluate the regulatory impact. Findings—This study reveals significant variations in money laundering risks by a country’s income category and economic bloc influenced by economic openness and governance structures. Economic growth and foreign direct investment (FDI) inflows exhibit contrasting effects on money-laundering risks; they tend to exacerbate risks in middle-income countries, while high-income nations demonstrated a lower risk of money laundering, likely due to more robust governance structures. Trade openness and anti-corruption measures generally reduced risks in wealthier countries, highlighting the importance of strong governance frameworks. These insights suggest that anti-money-laundering policies should be tailored to fit different regions’ unique economic and institutional contexts for enhanced effectiveness. Originality—This study employs a structured approach to analyzing a decade of panel data from key economic blocs, providing insights into the intricate relationships between governance, economic openness, and money laundering risks. Bridging the gap between theoretical research and practical, actionable strategies serves as a valuable resource for improving the effectiveness of anti-money-laundering (AML) measures on a global scale.