Learning at Home and Abroad: How Competition Conditions the Diffusion of Party Strategies
Sebastian Juhl and
Laron K. Williams
British Journal of Political Science, 2022, vol. 52, issue 2, 593-612
Abstract:
How do parties decide when to campaign on valence issues given high degrees of uncertainty? Although past studies have provided evidence of transnational emulation of parties' position-taking strategies, these findings do not directly apply to saliency strategies. Moreover, the exact diffusion mechanism remains largely elusive. Based on the issue saliency literature, this study develops novel theoretical propositions and argues that conscious learning enables parties to infer the relative utility of emphasizing consensual issues during an electoral campaign. The proposed theory gives rise to different expectations at the domestic and transnational levels because of the distinct logic of issue competition. By analyzing environmental issue emphasis in party manifestos, the authors find direct transnational dependencies and indirect spillover effects among the parties' saliency strategies. They identify conscious learning, rather than mere imitation or independent decision making, as the diffusion mechanism at work. Yet, in line with saliency-based theories, electoral competition mutes the diffusion of electoral strategies domestically.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cup:bjposi:v:52:y:2022:i:2:p:593-612_6
Access Statistics for this article
More articles in British Journal of Political Science from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().