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.

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

Financial Data Transparency, International Institutions, and Sovereign Borrowing Costs

Recent events in international finance illustrate the close connection between the viability of a country's major private financial institutions and the sustainability of its sovereign debt. We explore the precise nature of this connection and the ways in which it shapes investors’ expectations of sovereign creditworthiness. We consider how investors use the overall level of information available about the private financial sector—and the potential risks it poses to government finances—when making decisions about investing in sovereign debt. We expect that governments providing more information about the private financial sector will have lower, and less volatile, borrowing costs. In order to test this argument, we create a new Financial Data Transparency (FDT) Index measuring governments’ willingness to release credible financial system data. Using the FDT and a sample of high-income OECD countries, we find that such transparency reduces sovereign borrowing costs. The effects are conditional on the level of public indebtedness. Transparent countries with low debt enjoy lower and less volatile borrowing costs

Modelling short‐ and long‐term characteristics of follicle stimulating hormone as predictors of severe hot flashes in the Penn Ovarian Aging Study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115996/1/rssc12102.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115996/2/rssc12102-sup-0001-Suppinfo.pd

High performance computation of landscape genomic models including local indicators of spatial association

With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics – that is the combination of landscape ecology with population genomics – include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present samβada, an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large-scale genetic and environmental data sets. samβada identifies candidate loci using genotype–environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype–environment associations. In addition, samβada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with samβada, bayenv, lfmm and an FST outlier method (FDIST approach in arlequin) and compare their results. samβada – an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada – outperforms other approaches and better suits whole-genome sequence data processing