Convergence Trends in Euro Economies: Financial Crisis Recovery and the COVID-19 Pandemic

Abstract

The configurative comparative method, Dynamic Pattern Synthesis (DPS) is used to replicate previous research into the impact of the euro on economic convergence. The DPS method ensures a forensic examination of the diverse variable patterns that influence cluster memberships. As with previous research conclusions, there are multiple patterns of convergence and divergence. Consistent clusters across the time periods compared are Germany, the Netherlands, Luxembourg, and Ireland; Slovakia and Estonia; Italy, Spain, and Slovenia; and Portugal and Greece. The variable patterns most likely to influence cluster definitions are differences in GDP per capita, productivity, and investment, although there are other differing variable patterns that influence specific smaller cluster memberships and the consistency of memberships over time. Externalities undermine nominal convergence. An example is the divergence of the experience of consumer inflation between 2016 and 2022. Nevertheless, some convergence in long-term interest rates is achieved. There is also divergence in the real convergence target of GDP per capita. As regards structural changes, productivity differences widen, and investment as a percentage of GDP converges during COVID-19. The theoretical implications are that the complex dynamics between collaboration, competitive markets, and global instabilities makes convergence unlikely. Real convergence, such as reducing the distribution differences of GDP per capita, is only likely to be possible over many decades, and needs considerable government interventions. Complex systems theory informs us that limits to convergence are inevitable in dynamic systems where events bring unplanned divergences.