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Risky Business? Welfare State Reforms and Government Support in Britain and Denmark
Published online by Cambridge University Press: 02 October 2017
Abstract
Are welfare state reforms electorally dangerous for governments? Political scientists have only recently begun to study this seemingly simple question, and existing work still suffers from two shortcomings. First, it has never tested the reform–vote link with data on actual legislative decisions for enough points in time to allow robust statistical tests. Secondly, it has failed to take into account the many expansionary reforms that have occurred in recent decades. Expansions often happen in the same years as cutbacks. By focusing only on cutbacks, estimates of the effects of reforms on government popularity become biased. This article addresses both shortcomings. The results show that voters punish governments for cutbacks, but also reward them for expansions, making so-called compensation, a viable blame-avoidance strategy. The study also finds that the size of punishments and rewards is roughly the same, suggesting that voters’ well-documented negativity bias does not directly translate into electoral behavior.
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- © Cambridge University Press 2017
Footnotes
Department of Political Science, Aarhus University (emails: [email protected], [email protected], [email protected]); Department of Social Sciences, TU Kaiserslautern (email: [email protected]). We want to thank the editor and three reviewers for excellent and very thorough comments. An early version of the article was presented in the Section of Behavior and Institutions at the Department of Political Science at Aarhus University, as well as at the annual meeting of the Midwest Political Science Association in Chicago. We are grateful for the many critical and thoughtful comments we got on those occasions. Lasse Leipziger and Kristian Nicolaisen provided first-class research assistance. The research has been funded by The Danish Council for Independent Research (grant no. 4003-00013). Replication data sets are available in Harvard Dataverse at: https://dx.doi.org/10.7910/DVN/FDY0ZN and online appendices are available at https://doi.org/10.1017/S0007123417000382.
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