Most studies of policy feedback have focused on processes of self‐reinforcement through which programs bolster their own bases of political support and endure or expand over time. This article develops a theoretical framework for identifying feedback mechanisms through which policies can become self‐undermining over time, increasing the likelihood of a major change in policy orientation. We conceptualize and illustrate three types of self‐undermining feedback mechanisms that we expect to operate in democratic politics: the emergence of unanticipated losses for mobilized social interests, interactions between strategic elites and loss‐averse voters, and expansions of the menu of policy alternatives. We also advance hypotheses about the conditions under which each mechanism is likeliest to unfold. In illuminating endogenous sources of policy change, the analysis builds on efforts by both historically oriented and rationalist scholars to understand how institutions change and seeks to expand political scientists’ theoretical toolkit for explaining policy development over time.
A range of policy problems-from climate change to pension sustainability to skill shortages-confront governments with intertemporal dilemmas: trade-offs between maximizing social welfare in the present and taking care of the future. There is, moreover, substantial variation in the degree to which democratic governments are willing to invest in long-term social goods. Surprisingly, the literature on the politics of public policy has paid little explicit attention to timing as a dimension of policy choice, focusing almost exclusively on matters of cross-sectional distribution. This article develops a framework for explaining intertemporal policy choices in democracies by adapting findings from the literatures on distributive politics, political economy, and political behavior. The article makes a case for analyzing the politics of the long term as a struggle over how welfare should be allocated across groups and over how policy effects should be distributed through time.
We develop an approach to multimethod research that generates joint learning from quantitative and qualitative evidence. The framework—Bayesian integration of quantitative and qualitative data (BIQQ)—allows researchers to draw causal inferences from combinations of correlational (cross-case) and process-level (within-case) observations, given prior beliefs about causal effects, assignment propensities, and the informativeness of different kinds of causal-process evidence. In addition to posterior estimates of causal effects, the framework yields updating on the analytical assumptions underlying correlational analysis and process tracing. We illustrate the BIQQ approach with two applications to substantive issues that have received significant quantitative and qualitative treatment in political science: the origins of electoral systems and the causes of civil war. Finally, we demonstrate how the framework can yield guidance on multimethod research design, presenting results on the optimal combinations of qualitative and quantitative data collection under different research conditions.
It is widely assumed that citizens are myopic, weighing policies' short-term consequences more heavily than long-term outcomes. Yet no study of public opinion has directly examined whether or why the timing of future policy consequences shapes citizens' policy attitudes. This article reports the results of an experiment designed to test for the presence and mechanisms of time-discounting in the mass public. The analysis yields evidence of significant discounting of delayed policy benefits and indicates that citizens' policy bias towards the present derives in large part from uncertainty about the long term: uncertainty about both long-run processes of policy causation and long-term political commitments. There is, in contrast, little evidence that positive time-preferences (impatience) or consumption-smoothing are significant sources of myopic policy attitudes.
Preregistrations—records made a priori about study designs and analysis plans and placed in open repositories—are thought to strengthen the credibility and transparency of research. Different authors have put forth arguments in favor of introducing this practice in qualitative research and made suggestions for what to include in a qualitative preregistration form. The goal of this study was to gauge and understand what parts of preregistration templates qualitative researchers would find helpful and informative. We used an online Delphi study design consisting of two rounds with feedback reports in between. In total, 48 researchers participated (response rate: 16%). In round 1, panelists considered 14 proposed items relevant to include in the preregistration form, but two items had relevance scores just below our predefined criterion (68%) with mixed argument and were put forth again. We combined items where possible, leading to 11 revised items. In round 2, panelists agreed on including the two remaining items. Panelists also converged on suggested terminology and elaborations, except for two terms for which they provided clear arguments. The result is an agreement-based form for the preregistration of qualitative studies that consists of 13 items. The form will be made available as a registration option on Open Science Framework (osf.io). We believe it is important to assure that the strength of qualitative research, which is its flexibility to adapt, adjust and respond, is not lost in preregistration. The preregistration should provide a systematic starting point.
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