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This paper aims to examine income convergence among the Euro members from 1995 to 2021.

This study uses Phillips and Sul’s test (2007, 2009) extended by Lyncker and Thoennessen’s (2017) algorithm jointly with β and σ  – convergence analysis and a traditional growth equation.

This analysis identifies three clubs of countries in terms of gross domestic product (GDP) per capita with notable disparities between and within them, which implies that the theory of optimal currency areas has not been fulfilled.

These results rule out the core/periphery divide as presented in the literature to date. Finally, by estimating an endogenous economic growth model, this study finds the primary factors underpinning the differences between the three stationary states: labor productivity, physical and human capital, investment and international trade.

This study aims to identify structural breaks in the current account and the periods between these breaks, which the authors name stability spells, and study their characteristics and determinants.

Using data from the IMF and the World Bank, this study applies the Lee and Strazicich test to endogenously identify breaks and the Heckman selection model to simultaneously study the determinants of structural breaks and current-account changes after breaks.

This study identifies 212 significant structural breaks and 341 stability spells. These spells become shorter and more volatile the further they are from equilibrium, and half of them last 10 years or less. The results show that economic growth and foreign-exchange piling are particularly useful to prevent breaks, while lower per capita income increases exposure to break risks.

This study introduces the concept of current-account stability spells to refer to the periods between structural breaks. These spells are then studied to determine their main characteristics. The authors also apply a global perspective in their analysis, using a wide sample of 181 economies between 1980 and 2018 and considering positive and negative breaks in both level and trend.

This paper aims to apply regression-tree analysis to capture the nonlinear effects of corruption on economic growth. Using data of 103 countries for the period 1996–2017, the authors endogenously detect two distinct areas in corruption quality in which the members share the same model of economic growth.

The authors apply regression tree analysis to capture the nonlinearity of the influences. This methodology allows us to split endogenously the whole sample of countries and characterize the different ways through which corruption impacts economic growth in each group of countries.

The traditional determinants of economic growth have different impacts on countries depending on their level of corruption, which, in turn, confirms the parameter heterogeneity of the Solow model found in other strands of the literature.

The authors apply a new approach to a worldwide sample obtaining novel results.