This article analyses the evolution over time of perceived corruption for a large set of countries worldwide. To proxy corruption, we use the recently proposed Bayesian Corruption Index (Standaert, S. (2015). Divining the level of corruption: A bayesian state space approach, Journal of Comparative Economics , 43(3), 782–803). We employ the test developed by (Phillips, P., & Sul, D. (2007). Transition modeling and econometric convergence tests. Econometrica, 75, 1771–1855) that enables the endogenous determination of convergence clubs for countries over time. Having divided countries into convergence clubs, we explore whether each club differs from the others in terms of their competitiveness ranking. In particular, drawing on the 2019 Global Competitiveness Report, we focus not only on the global competitiveness score, but also on the first and the fifth pillars of competitiveness: institutions and health, respectively. Mean and median scores for clubs confirm the general rule that low perceived corruption levels tend to be associated with high-income countries with established democracies, high-quality healthcare systems, and relatively low-income inequality. However, countries such as Spain and Italy, which are innovation-driven economies with excellent scores in the health pillar, are in the worst club for perceived corruption, suggesting there are additional idiosyncratic aspects that could drive perceived corruption levels.