A derivation of the money Rawlsian solution

We study the set of envy-free allocations for economies with indivisible objects and quasi-linear utility functions. We characterize the minimal amount of money necessary for its nonemptiness when negative distributions of money are not allowed. We also find that, when this is precisely the available amount of money, there is a unique way to combine objects and money such that these bundles may form an envy-free allocation. Based on this property, we describe a solution to the envy-free selection problem following a pseudo-egalitarian criterion. This solution coincides with the Money Rawlsian Solution proposed by Alkan et al. (1991).I am indebted to I. Gilboa for his valuable suggestions and his patience during the elaboration of the final version. I also wish to thank S. Barbera for his guidance in an earlier version and M. Boldrin, H. Moulin, Z. Neeman, W. Thomson and the referees for their comments. Financial support from FPU-MEC (Spain) is gratefully acknowledged.Northwestern University.     

POLITICAL REPUTATIONS AND CAMPAIGN PROMISES

We analyze conditions under which candidates' reputations may affect voters' beliefs over what policy will be implemented by the winning candidate of an election. We develop a model of repeated elections with complete information in which candidates are purely ideological. We analyze an equilibrium in which voters' strategies involve a credible threat to punish candidates who renege on their campaign promises and in which all campaign promises are believed by voters and honored by candidates. We characterize the maximal credible campaign promises and find that the degree to which promises are credible in equilibrium is an increasing function of the value of a candidate's reputation. (JEL: D8)     

Risk Perception Among Smokers: A Qualitative Study

The aim of this qualitative study is to identify the dimensions people used to assess the risk of smoking and then compare them with those used by health professionals in primary healthcare. Five discussion groups were conducted. The field work was carried out in Barcelona (Spain), from February 2005 to January 2006. Data were analyzed following a semantic‐thematic categorical content analysis (ACC‐ts). Results showed that people tend to employ stereotypical discourses when evaluating the risk of smoking. Similarly, they reassess the risk in the context of their life experience and incorporate new nuances to the arguments sustaining their behavior. Once this reassessment takes place, the decision to continue smoking emerges, and smokers come up with additional arguments justifying their habit (i.e., age, benefits related to costs). Professionals are aware of this process and its multidimensional nature. Nevertheless, their discourse loses this multidimensional feature when discussing the strategies they use at smoking cessation interventions. This qualitative study increases the understanding of various meanings that people attribute to their life experience. These assumptions may be useful for developing health practices that are closer to people. As a practical utility of these results, it would be interesting to apply a preliminary assessment of the different meanings that people attribute to smoking from their life context in risk communication.     

Making statements and approval voting

We assume that people have a need to make statements, and construct a model in which this need is the sole determinant of voting behavior. In this model, an individual selects a ballot that makes as close a statement as possible to her ideal point, where abstaining from voting is a possible (null) statement. We show that in such a model, a political system that adopts approval voting may be expected to enjoy a significantly higher rate of participation in elections than a comparable system with plurality rule.     

Forecasting time series with missing data using Holt's model

This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts.