Political Ambition and Legislative Behavior in the European Parliament

Members of the European Parliament (MEP) typically follow one of two career paths, either advancing within the European Parliament itself or returning to higher office in their home states. We argue that these different ambitions condition legislative behavior. Specifically, MEPs seeking domestic careers defect from group-leadership votes more frequently and oppose legislation that expands the purview of supranational institutions. We show how individual, domestic-party, and national level variables shape the careers available to MEPs and, in turn, their voting choices. To test the argument, we analyze MEPs' roll-call voting behavior in the 5th session of the EP (1999-2004) using a random effects model that captures idiosyncrasies in voting behavior across both individual MEPs and specific roll-call votes.published or submitted for publicationnot peer reviewe

The Scythe Statistical Library: An Open Source C++ Library for Statistical Computation

The Scythe Statistical Library is an open source C++ library for statistical computation. It includes a suite of matrix manipulation functions, a suite of pseudo-random number generators, and a suite of numerical optimization routines. Programs written using Scythe are generally much faster than those written in commonly used interpreted languages, such as R and \proglang{MATLAB}; and can be compiled on any system with the GNU GCC compiler (and perhaps with other C++ compilers). One of the primary design goals of the Scythe developers has been ease of use for non-expert C++ programmers. Ease of use is provided through three primary mechanisms: (1) operator and function over-loading, (2) numerous pre-fabricated utility functions, and (3) clear documentation and example programs. Additionally, Scythe is quite flexible and entirely extensible because the source code is available to all users under the GNU General Public License.

Experts, Coders, and Crowds: An analysis of substitutability

Recent work suggests that crowd workers can replace experts and trained coders in common coding tasks. However, while many political science applications require coders to both and relevant information and provide judgment, current studies focus on a limited domain in which experts provide text for crowd workers to code. To address potential over-generalization, we introduce a typology of data producing actors - experts, coders, and crowds - and hypothesize factors which affect crowd-expert substitutability. We use this typology to guide a comparison of data from crowdsourced and expert surveys. Our results provide sharp scope conditions for the substitutability of crowd workers: when coding tasks require contextual and conceptual knowledge, crowds produce substantively dierent data from coders and experts. We also find that crowd workers can cost more than experts in the context of cross-national panels, and that one purported advantage of crowdsourcing - replicability - is undercut by an insucient number of crowd workers

What Makes Experts Reliable?

Many datasets use experts to code latent quantities of interest. However, scholars have not explored either the factors affecting expert reliability or the degree to which these factors influence estimates of latent concepts. Here we systematically analyze potential correlates of expert reliability using six randomly selected variables from a cross-national panel dataset, V-Dem v8. The V-Dem project includes a diverse group of over 3,000 experts and uses an IRT model to incorporate variation in both expert reliability and scale perception into its data aggregation process. In the process, the IRT model produces an estimate of expert reliability, which affects the relative contribution of an expert to the model. We examine a variety of factors that could correlate with reliability, and find little evidence of theoretically-untenable bias due to expert characteristics. On the other hand, there is evidence that attentive and condent experts who have a basic contextual knowledge of the concept of democracy are more reliable

Experts, coders and crowds: An analysis of substitutability

Political scientists increasingly use crowdworkers to produce data, predominantly in the context of coding researcher-curated text or to retrieve simple data from the internet. In this article, we provide a theoretical and empirical basis for understanding when crowdworkers can provide data of sufficient quality to substitute for other types of coders. First, we introduce a typology of data-producing actors – experts, trained coders and crowds – and hypothesize factors that affect the substitutability of crowdworkers. We then examine how crowdworkers perform across coding tasks that vary along multiple dimensions of difficulty: information verifiability, availability and complexity. The results provide scope conditions bounding the substitutability of crowdworkers in political science applications. Although crowds can substitute for trained coders in the context of relatively simple information retrieval tasks, there is little evidence that crowdworkers can substitute for experts, whose tasks require both information retrieval and data synthesis.publishedVersio

The diffusion of financial supervisory governance ideas

Who is watching the financial services industry? Since 1980, there have been multiple waves of thought about whether the ministry of finance, the central bank, a specialized regulator or some combination of these should have supervisory authority. These waves have been associated with the convergence of actual practices. How much and through what channels did internationally promoted ideas about supervisory 'best practice' influence institutional design choices? I use a new dataset of 83 countries and jurisdictions between the 1980s and 2007 to examine the diffusion of supervisory ideas. With this data, I employ Cox Proportional Hazard and Competing Risks Event History Analyses to evaluate the possible causal roles best practice policy ideas might have played. I find that banking crises and certain peer groups can encourage policy convergence on heavily promoted ideas

Conceptual and Measurement Issues in Assessing Democratic Backsliding

During the past decade, analyses drawing on several democracy measures have shown a global trend of democratic retrenchment. While these democracy measures use radically different methodologies, most partially or fully rely on subjective judgments to produce estimates of the level of democracy within states. Such projects continuously grapple with balancing conceptual coverage with the potential for bias (Munck and Verkuilen 2002; Przeworski et al. 2000). Little and Meng (L&M) (2023) reintroduce this debate, arguing that “objective” measures of democracy show little evidence of recent global democratic backsliding.1 By extension, they posit that time-varying expert bias drives the appearance of democratic retrenchment in measures that incorporate expert judgments. In this article, we engage with (1) broader debates on democracy measurement and democratic backsliding, and (2) L&M’s specific data and conclusions