The Power of the Last Word in Legislative Policy Making

We examine legislative policy making in institutions with two empirically relevant features: agenda setting occurs in real time and the default policy evolves. We demonstrate that these institutions select Condorcet winners when they exist, provided a sufficient number of individuals have opportunities to make proposals. In policy spaces with either pork barrel or pure redistributional politics (where a Condorcet winner does not exist), the last proposer is effectively a dictator or near‐dictator under relatively weak conditions.     

ENDOGENOUS LOBBYING

In this article, we present a citizen‐candidate model of representative democracy with endogenous lobbying. We find that lobbying induces policy compromise and always affects equilibrium policy outcomes. In particular, even though the policy preferences of lobbies are relatively extreme, lobbying biases the outcome of the political process toward the center of the policy space, and extreme policies cannot emerge in equilibrium. Moreover, in equilibrium, not all lobbies participate in the policy‐making process. (JEL: D72, D74, D78)     

Female Asylum-Seekers in the Netherlands: An Empirical Study

This article presents the findings from a study into the chances for refugee status, or a temporary residence permit, for three cohorts of male and female asylum-seekers to the Netherlands. The study investigated whether men and women with similar backgrounds in terms of country of origin, social and demographic characteristics have a similar likelihood of obtaining permission to stay in the Netherlands.
The quantitative findings are corroborated with an in-depth qualitative study of refugees' files from the Immigration and Naturalization Service (IND), as well as with an experiment in which decision-making personnel were asked to judge hypothetical case studies of refugees in which gender as well as other gender-specific properties were systematically varied.
We recommend that further in-depth studies be conducted to capture elements in the decision-making process that could not be investigated in our kind of large-scale study.     

Strategic, sincere, and heuristic voting under four election rules: an experimental study

We report on laboratory experiments on voting. In a setting where subjects have single-peaked preferences, we find that the rational choice theory provides very good predictions of actual individual behavior in one-round and approval voting elections but fares poorly in explaining vote choice under two-round elections. We conclude that voters behave strategically as far as strategic computations are not too demanding, in which case they rely on simple heuristics (under two-round voting) or they just vote sincerely (under single transferable vote).     

Efficiency and Equilibrium with Dynamic Increasing Aggregate Returns due to Demand Complementarities

When do dynamic nonconvexities at the disaggregate level translate into dynamic nonconvexities at the aggregate level? We address this question in a framework where the production of differentiated intermediate inputs is subject to dynamic nonconvexities, and we show that the answer depends on the degree of Hicks-Allen complementarity (substitutability) between differentiated inputs. In our simplest model, a generalization of Judd (1985) and Grossman and Helpman (1991) among many others, there are dynamic nonconvexities at the aggregate level if and only if differentiated inputs are Hicks-Allen complements. We also compare dynamic equilibrium and optimal allocations in the presence of aggregate dynamic nonconvexities due to Hicks-Allen complementarities between differentiated inputs.     

Flexible clustering via hidden hierarchical Dirichlet priors

The Bayesian approach to inference stands out for naturally allowing borrowing information across heterogeneous populations, with different samples possibly sharing the same distribution. A popular Bayesian nonparametric model for clustering probability distributions is the nested Dirichlet process, which however has the drawback of grouping distributions in a single cluster when ties are observed across samples. With the goal of achieving a flexible and effective clustering method for both samples and observations, we investigate a nonparametric prior that arises as the composition of two different discrete random structures and derive a closed-form expression for the induced distribution of the random partition, the fundamental tool regulating the clustering behavior of the model. On the one hand, this allows to gain a deeper insight into the theoretical properties of the model and, on the other hand, it yields an MCMC algorithm for evaluating Bayesian inferences of interest. Moreover, we single out limitations of this algorithm when working with more than two populations and, consequently, devise an alternative more efficient sampling scheme, which as a by-product, allows testing homogeneity between different populations. Finally, we perform a comparison with the nested Dirichlet process and provide illustrative examples of both synthetic and real data.     

Column generation approach for the point-feature cartographic label placement problem

This paper proposes a column generation approach for the Point-Feature Cartographic Label Placement problem (PFCLP). The column generation is based on a Lagrangean relaxation with clusters proposed for problems modeled by conflict graphs. The PFCLP can be represented by a conflict graph where vertices are positions for each label and edges are potential overlaps between labels (vertices). The conflict graph is decomposed into clusters forming a block diagonal matrix with coupling constraints that is known as a restricted master problem (RMP) in a Dantzig-Wolfe decomposition context. The clusters’ sub-problems are similar to the PFCLP and are used to generate new improved columns to RMP. This approach was tested on PFCLP instances presented in the literature providing in reasonable times better solutions than all those known and determining optimal solutions for some difficult large-scale instances.     

Social work with middle‐class Spanish families: The challenge of the work–family conflict

In the current economic crisis, middle‐class families often find themselves immersed in a process of downward social mobility. These are families in which both spouses work, and where many relational conflicts begin in the sphere of work–family reconciliation and the allocation of household responsibilities. This article presents the results of a research study we conducted on middle‐class families in Spain. We focus specifically on the problems associated with work–family reconciliation and gender, and the mitigating role played by social support. Based on our results, we want to call the attention to a prevalent and ‘new’ conflict in family‐based practice social work in Spain: the work–family conflict.     

Bounds for the Expected Time to Extinction and the Probability of Extinction in the Galton-Watson Process

Upper bounds for the expected time to extinction in the Galton-Watson process are obtained. We also found upper and lower bounds for the probability of extinction of this process. These bounds improve some bounds previously obtained by other authors.     

Outlier detection in contingency tables based on minimal patterns

A new technique for the detection of outliers in contingency tables is introduced, where outliers are unusual cell counts with respect to classical loglinear Poisson models. Subsets of cell counts called minimal patterns are defined, corresponding to non-singular design matrices and leading to potentially uncontaminated maximum-likelihood estimates of the model parameters and thereby the expected cell counts. A criterion to easily produce minimal patterns in the two-way case under independence is derived, based on the analysis of the positions of the chosen cells. A simulation study and a couple of real-data examples are presented to illustrate the performance of the newly developed outlier identification algorithm, and to compare it with other existing methods.