This paper provides a preliminary analysis of the institutional determinants of the timing of COVID-19 related school closures, focusing on the role of democracy and administrative state capacity. To this end, the paper reports a set of survival analyses of school closures around the world in February and March of 2020. Relying foremost on an analysis of the number of days to school closure after the day of the 10th confirmed case of COVID-19 in 134 countries, the paper finds that other things being equal, democratic countries tended to implement school closures more quickly than those with a more authoritarian regime, while countries with higher government effectiveness tended to take longer than those with less effective state apparatuses. Similar, yet-with respect to democracy-less substantial results are retrieved in a supplementary analysis of 158 countries, where the starting point is instead the day of China's first COVID-19 related school closure. Note that these results are preliminary and that the paper is not intended to evaluate, and does not say anything about, the appropriateness or effectiveness of any particular school closure strategy.
Comparative scholars fundamentally disagree about the impact of partisan politics in modern welfare states, particularly in certain ‘new’ policy areas such as active labor market policy (ALMP). Using new data on 900 ALMP programs across Europe, this study attempts to reconcile a long-standing dispute between the traditional ‘power resources’ approach and the ‘insider/outsider’ approach pioneered by Rueda. The study argues that both left-wing and right-wing governments invest in ALMP but that politics still matter because parties’ preferences regarding unemployment differ. The left is more inclined to expand programs primarily designed to reduce unemployment, which exclusively target ‘core’ groups in, or at risk of, unemployment, and programs in which participants are no longer counted among the unemployed. In contrast, both sides are equally prone to expand programs that also—or instead—target people who are not yet participating in the labor market, which thus also—or instead—serve to increase labor supply.
Employment subsidy programs have experienced considerable expansion across Europe in recent decades. To date, most studies analyzing this policy shift have assumed that these programs are largely equivalent in terms of their designs, effects, and explanations. In contrast, this article argues that employment subsidies are best understood as versatile multi-purpose tools that can be used as means to rather different distributional ends. Using Multiple Correspondence Analysis to explore novel data from hundreds of employment subsidy programs across Europe, this article develops a new typology based on two overarching trade-offs. The typology highlights that employment subsidies may be designed to counteract as well as to sustain insider/outsider divides in the labor market, and that they may be designed to tackle either structural or cyclical labor market problems. In a first empirical evaluation of the typology, programs with different designs are found to vary systematically in terms of distributional outcomes and starting conditions.
We develop a general approach to measuring electoral competitiveness for parties and governments, which is distinct from existing approaches in two ways. First, it allows us to estimate the actual probabilityof re-electing the incumbent into office, which lies closer to the theoretical concept of interest than most widely used proxies. Second, it incorporates both pre-electoral competitiveness—that is, the uncertainty about the outcome of the upcoming election—and post-electoral competitiveness—that is, the uncertainty concerning who will form the government given a certain election result. The approach can be applied to, and compared across, a multitude of institutional settings and is particularly advantageous in analyses of multiparty democracies. To demonstrate its full potential, we first apply the approach on 1,700 local government elections in Sweden. Three advantages over existing approaches are documented: Our election probability measure shows substantial variation over the election cycle, it can be accurately measured for a single party as well as a government, and it is more capable of predicting re-election into office than any previous measure of electoral competitiveness. A second application on 400 national elections in 34 democracies shows that the approach also works well in a more challenging cross-national setting.
This study investigates the institutional determinants of the timing of COVID-19 related school closures around the world, focusing on the role of democracy and administrative state capacity. Relying foremost on Cox proportional hazards models of up to 167 countries observed daily between late January and early April of 2020, the study finds that other things being equal, democratic countries tended to implement school closures quicker than those with a more authoritarian regime, while countries with high government effectiveness tended to take longer than those with less effective state apparatuses. A supplementary analysis that distinguishes between the two democratic dimensions of competition and participation indicates that it is the existence of competitive elections that prompts democratic leaders to respond more rapidly. Lastly, auxiliary evidence indicates that demography and family systems may also help determine countries' pandemic responses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.