This study proposes a novel and systematic theoretical framework to explain global welfare state policy differences. The existing scholarship examined ample welfare state variations, reforms, and transitions; however, it is typically limited to specific countries, regions, policies, or risks. In an endeavor to combine these theoretical and empirical insights, the global contemporary welfare state patterns remain vague. This study aims at bridging this gap in the literature by deploying an orderly and comprehensive three-step procedure. First, I formally design a three-stage global yet comparative conceptual framework that ensures consistency, inclusiveness, and compliance. Second, based on this framework, I assemble a unique comparative dataset for one-hundred-fifty countries, some of which appear for the first time in this literature. Third, I validate the framework using an advanced data reduction method named model-based cluster analysis. The results of this study demonstrate that global contemporary welfare states follow systematically divergent paths, revealing Proactive, Reactive, and Dual patterns.
Poverty, inequality and climate change are profoundly interconnected issues and represent grave threats to the future of our planet and civilization. Failure in one will result in failure in the other; thus, government responses to such threats must be meticulously coordinated, especially across environmental and welfare state programs. In recent years, a growing body of research has examined the links between these two domains, lauding the eco-welfare state as a viable path forward. As the literature on the eco-welfare state is at an early stage, this study proposes two essential theoretical and empirical contributions. First, it examines the most prominent theoretical interpretations of the concept of eco-welfare state and proposes a refined understanding. Second, using model-based cluster analysis for 42 countries, this study empirically unveils a global shift towards and the existence of an eco-welfare state.
Climate change is posing significant threats to human societies and developmental prospects. Governments continue to design and propose comprehensive climate policies aimed at tackling the climate crisis but often fail to successfully implement them. One reason is that securing public support for such policy instruments has proven to be challenging. While public opinion research has often documented a positive correlation between beliefs in climate change and policy support, it has also become clear that the presence of such beliefs is in many situations not enough for policy support. This is the starting point of our study in which we delve deeper into the link between climate change beliefs and policy support by specifically integrating risk perceptions related to climate change but also related to policy solutions. Empirically, we leverage survey data from the United States and Switzerland and employ the random forest technique to further explore the mechanisms that link climate change beliefs, risk perceptions, and policy support. We use the case of carbon taxation, which is considered a particularly effective instrument by ecological economists but seems to be particularly unpopular politically. The results of this study suggest that beliefs and risk perceptions are very important predictors of support for carbon tax policies. Furthermore, they unveil the strongest predictors and specific patterns that generate the highest support in the United States and Switzerland.
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