A study of orientational ordering in a fluid of dipolar Gay-Berne molecules using density-functional theory

Published versio

Self-Rated Health in the Baltic Countries, 1994–1999

Numerous studies have examined the explanations of mortality fluctuations in the former USSR during the last decade of the twentieth century-a time of considerable political and socio-economic changes-but fewer studies have considered the health of these populations during this period. Using individual data from the Norbalt surveys held in 1994 and 1999 in the three Baltic countries, we examine the determinants of self-rated health in the three countries and for the two periods, by way of Bayesian structural equation modelling and directed acyclic graphs. The model takes into account, as possible determinants, alcohol consumption, physical health, psychological distress, education, locus of control, and social support. A major result is the remarkable stability of the model's parameters whatever the country, year, gender, ethnicity, or age-group. Particular attention is given to the role of alcohol consumption and to the association observed between better self-assessed health and higher drinking. © 2010 Springer Science+Business Media B.V

Causal explanation: recursive decompositions and mechanisms

This chapter deals with causal explanation in quantitative‐oriented social sciences. In the framework of statistical modelling, we first develop a formal structural modelling approach which is meant to shape causal explanation. Recursive decomposition and exogeneity are given a major role for explaining social phenomena. Then, based on the main features of structural models, the recursive decomposition is interpreted as a mechanism and exogenous variables as causal factors. Arguments from statistical methodology are first offered and then submitted to critical evaluation

Bayesian Testing and Testing Bayesians.

economic models ; econometrics

Quasi Linear Bayes Estimation in Stratified Finite Populations.

economic models

Causal attribution in block-recursive social systems: a structural modeling perspective

One method for causal analysis in the social sciences is structural modeling. Structural models, as used in this article, model the (causal) mechanism for a social phenomenon by recursively decomposing the multivariate distribution of the variables of interest. Often, however, one does not achieve a complete decomposition in terms of single variables but in terms of “blocks” of variables only. Papers giving an overview of this issue are nevertheless rare. The purpose of this article is to categorize distinct types of block-recursivity and to examine, in a multidisciplinary perspective, the implications of block-recursivity for causal attribution. A probabilistic approach to causality is first developed in the framework of a structural model. The article then examines block-recursivity due to the presence of contingent conditions, of interaction, and of conjunctive causes. It also discusses causal attribution when information on the ordering of the variables is incomplete. The article concludes by emphasizing, in particular, the importance of properly specifying the population of reference

Inferring causality through counterfactuals in observational studies. Some epistemological issues

This paper contributes to the debate on the virtues and vices of counterfactuals as a basis for causal inference. The goal is to put the counterfactual approach in an epistemological perspective. We discuss a number of issues, ranging from its non-observable basis to the parallelisms drawn between the counterfactual approach in statistics and in philosophy. We argue that the question is not to oppose or to endorse the counterfactual approach as a matter of principle, but to decide what modelling framework is best to adopt depending on the research context

Inferring causal relations by modelling structures

This paper provides an overview of structural modelling in its close relation to explanation and causation. It stems from previous works by the authors and stresses the role and importance of the notions of invariance, recursive decomposition, exogeneity and background knowledge. It closes with some considerations about the importance of the structural approach for practicing scientists