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Replication Data for: Lobbying, Learning, and Policy Reinvention: An Examination of the American States’ Drunk Driving Laws

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DataCite Commons2025-05-12 更新2025-05-17 收录
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/Z6EZG3
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资源简介:
Scholars have consistently shown that learning of successful policies in other states leads to higher likelihood of policy adoption. This study extends this finding two ways. First, policy learning can also lead to more comprehensive adoption of successful policies. Second, the effect of policy learning on policy comprehensiveness is conditional on lobbying by interest groups, an alternative source of information about policy success. To test these hypotheses, we conduct a directed dyad-year analysis using a dataset on American state drunk driving regulations from 1983 to 2000. The results show that more comprehensive policy adoption by states is positively related to policy success in other states when lobbying by Mothers Against Drunk Driving (MADD) is relatively low. Moreover, lobbying by MADD increases policy comprehensiveness when policy success is relatively low. This study advances the literature by examining the conditional effects of lobbying on the relationship between policy learning and policy reinvention.
提供机构:
Harvard Dataverse
创建时间:
2018-09-20
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