While the literature on delegation has discussed at length the benefits of creating independent regulatory agencies (IRAs), not much attention has been paid to the conceptualization and operationalization of agency independence. In this study, we argue that existing attempts to operationalize the formal political independence of IRAs suffer from a number of conceptual and methodological flaws. To address these, we define what we understand by independence, and in particular formal independence from politics. Using new data gathered from 175 IRAs world- wide, we model formal independence as a latent trait. We find that some items commonly used to measure independence – notably, the method used to appoint agency executives and the scope of the agency’s competences – are unrelated to formal independence. We close by showing that our revised measure partially changes conclusions about the determinants and consequences of formal independenc

Regulation by independent agencies, rather than ministries, is believed to result in better policy outcomes. Yet this belief requires one to accept a complex causal chain leading from formal independence to actual independence from politics, to policy decisions and, ultimately, to policy outcomes. In this study, we analyze the link between the formal and actual independence of regulatory agencies in Western Europe. New data on the appointment of chief executives of these agencies is used to create a proxy for the actual independence of agencies from politics. The analysis demonstrates that formal independence is an important determinant of actual independence, but the rule of law and the number of veto players matter as well.

Political scientists interested in estimating how public opinion varies by constituency have developed several strategies for supplementing limited constituency survey data with additional sources of information. We present two evaluation studies in the previously unexamined context of British constituency-level opinion: an external validation study of party vote share in the 2010 general election and a cross-validation of opinion toward the European Union. We find that most of the gains over direct estimation come from the inclusion of constituency-level predictors, which are also the easiest source of additional information to incorporate. Individual-level predictors combined with post-stratification particularly improve estimates from unrepresentative samples, and geographic local smoothing can compensate for weak constituency-level predictors. We argue that these findings are likely to be representative of applications of these methods where the number of constituencies is large.

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I show how results from the United Kingdom's referendum on membership of the European Union can be remapped from local authority level to parliamentary constituency level through the use of a scaled Poisson regression model which incorporates demographic information from lower level geographies. I use these estimates to show how the geographic distribution of signatures to a petition for a second referendum was strongly associated with how constituencies voted in the actual referendum.