• Medientyp: E-Book
  • Titel: Electoral Democracy and Human Development
  • Beteiligte: Gerring, John [VerfasserIn]; Knutsen, Carl Henrik [VerfasserIn]; Skaaning, Svend-Erik [VerfasserIn]; Teorell, Jan [VerfasserIn]; Coppedge, Michael [VerfasserIn]; Lindberg, Staffan I. [VerfasserIn]; Maguire, Matthew [VerfasserIn]
  • Erschienen: [S.l.]: SSRN, 2016
  • Erschienen in: V-Dem Working Paper 2015:9 Edited
  • Umfang: 1 Online-Ressource (62 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.2652180
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 1, 2016 erstellt
  • Beschreibung: This study attempts to reconcile competing positions in the debate over whether democracy improves human development by showing that some aspects of democracy – but not others – affect human development. Specifically, we argue that the “electoral” aspect of democracy improves human development while aspects related to citizen empowerment do not (or scarcely so). Likewise, composite indices of democracy bear only a weak relationship to human development, especially if they do not take the mutual dependence between electoral components into account in their aggregation procedures. We argue, finally, that public policies serve as a key causal mechanism in this relationship. Electoral competition incentivizes politicians to provide public goods and services, and these, in turn, save lives. This set of hypotheses is tested in a more rigorous fashion than has hitherto been possible. First, we enlist a new dataset compiled by the CLIO Infra project that measures mortality – infant mortality, child mortality, and life expectancy – for most sovereign countries over the course of the twentieth century. Second, we draw on a new political institutions dataset – Varieties of Democracy (V- Dem) – that provides highly differentiated measures of democracy, measured annually for most sovereign countries from 1900 to the present. Third, we apply a diverse set of empirical tests including fixed effects, lagged dependent variables, first-difference, system GMM, and instrumental variables. Considered together, these tests mitigate concerns about causal identification
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