Dissertation Abstract
The European Court of Justice (ECJ) has fostered the development of a common European legal order, and in doing so, has asserted itself and its supremacy more, and more successfully, than any other international court. It has maintained features of international courts such as its composition of one judge per member state, while employing other tools of national high courts such as en banc decisions and organization into chambers, that together hide internal dissent and shield the ECJ from direct monitoring or curbing by the member states. The same shield has frustrated efforts to quantify the court’s responsiveness to member states, with limited evidence that the ECJ yields to some member-state interest some of the time, but nonetheless has advanced integration beyond national governments’ wishes. This equivocation arises at least in part from a failure to include relevant information about the court’s composition and organization.
In fact, the six-year renewable terms of judges, their previous qualifications and affiliations, and the internal organization into chambers all provide prior information that can and should be incorporated into a more complete model of judicial behavior. I develop an extension of the well-studied item-response model to infer judges’ preferences, using the structured ecological data from the cases they heard and relevant prior information about judges and the national governments that appoint them as well as information about cases.I offer new, more rigorous tests for existing theoretical hypotheses about the ECJ’s deference to certain actors and preference for integration. The model is applicable to other settings of structured ecological data. Many other national and international courts hear cases in subset chambers, and relevant prior information should be included rather than ignored in models of judicial behavior.
Preliminary Results
I presented a poster about the model, with results from a subset of cases and judges at the PolMeth 2009 Summer Meeting. Please see this short paper summarizing these encouraging results.
Other Projects
Gabel, Matthew J., Simon Hix, and Michael Malecki. “From Preferences to Behavior: Modeling MEPs’ Roll-Call Voting Behavior”. Presented at Midwest Political Science Association Annual Meeting, 4–7 April 2008.
This paper uses my extension of MCMCpack, a hierarchical item-response theory (IRT) model with covariates on ideal points θ for exogenous preference and party.
Other research projects include a paper on satisfaction with democracy at the European level and its interaction with national institutions and politics. Presented as a poster at APSA 2007; a draft of the paper will be available soon.
With Brian F. Crisp, I’m investigating how legislators
operate in the unusual institutional context of a nationwide
district with preference voting (a form of
semi-open list). More to the point, do legislators cultivate
geographic constituencies using these preference votes? Do
parties?
Another project is an attempt to explore the empirical implications of informational cascades in the incidence of strikes. A draft of the paper is available on request. How do union leaders and members decide to strike? What information do they have about the probability of success and of reprisal? Moreover, I argue that what they learn about these probabilities and others' assessments influences the course of events.
Hierarchical IRT in MCMCpack (MCMCirtHier1d)
I made a poster for PolMeth 2008 about the model, perhaps a bit glib, but I liked it and had fun making it.
A set of covariates Xj are used to predict ideal points θ ~ N(X'β, σ2) with standard Normal, IG prior on β and σ2. The full conditional distribution for (binary) θ is described in Fox 2007. a,b∈η is the typical IRT update. β and σ2 are Normal regression updates.
The figure below shows the reduced autocorrelation function plot or the result of using parameter expansion (PX). PX greatly reduces autocorrelation in what is in effect a random-effects probit model, and I would hope to be able to include the technique in writing future samplers. PX introduces an unidentified parameter α for the residual variance in the latent data (Liu and Wu 1999).
Files
Social Web
facebook.com/Malecki