The Impact of Public Services Expenditure on the Spanish Income Distribution

This paper performs an assessment and imputation of the benefits produced to the individuals and households well-being by the public services provision. This analysis is very relevant in the current framework of economic crisis of the European economies. Although most of the papers in the literature compare countries, decentralization processes are included in this paper by accounting the effect of public expenditure on regional health care and education upon the levels of inequality and rates of poverty in each Spanish region. This case is relevant because of the high decentralization degree of the Spanish political structure and the persistent regional disparities. The results show a clear downward tendency in both phenomena following imputation, although education shows a greater impact. Furthermore, a decomposition, used in this context for the first time, of the effects shows the very relevant redistributive effect of this public expenditure.     

The eigenstructure of block-structured correlation matrices and its implications for principal component analysis

Block-structured correlation matrices are correlation matrices in which the p variables are subdivided into homogeneous groups, with equal correlations for variables within each group, and equal correlations between any given pair of variables from different groups. Block-structured correlation matrices arise as approximations for certain data sets’ true correlation matrices. A block structure in a correlation matrix entails a certain number of properties regarding its eigendecomposition and, therefore, a principal component analysis of the underlying data. This paper explores these properties, both from an algebraic and a geometric perspective, and discusses their robustness. Suggestions are also made regarding the choice of variables to be subjected to a principal component analysis, when in the presence of (approximately) block-structured variables.     

Exposure to Traffic and Risk of Hospitalization Due to Injuries

Research on the risk of motor vehicle injuries and their relationship with the amount of travel has been only partially analyzed. The few individual exposure assessments are related to very specific subsets of the driving and traveling populations. This study analyzes the relationship between kilometers traveled and hospitalization due to motor vehicle injuries. Twelve thousand three hundred and sixty nine Spanish university graduates from the Seguimiento Universidad de Navarra multipurpose cohort study were evaluated. They had not been hospitalized due to motor vehicle injuries at baseline and were followed up to eight years. Biannual questionnaires allowed for self‐reporting of kilometers traveled in motor vehicles, together with incidence of hospitalization. Covariates in the Cox regression models included age and gender and baseline use of safety belt while driving, driving a vehicle with driver‐side airbag, driving a motorcycle, and drinking and driving. There were 49,766 participant‐years with an average yearly travel of 7,828 km per person‐year. Thirty‐six subjects reported a first hospitalization event during this time. The adjusted hazard ratio per additional kilometer traveled was 1.00005 (95% confidence interval 1.000013 to 1.000086). Even the smallest of reductions in the amount of kilometers traveled (from an average of 3,250 km per year to 1,000) has a statistically significant protective effect on the likelihood of sustaining hospitalization due to motor vehicle injury (aHR 0.9, 95% CI 0.78 to 0.98). In light of current policies aimed to reduce motorized traffic due to environmental concerns, it may be appropriate to consider the additional health benefit related to reductions in injuries.     

The Generalized Pascal Triangle and the Matrix Variate Jensen-Logistic Distribution

This article defines the so called Generalized Matrix Variate Jensen-Logistic distribution. The relevant applications of this class of distributions in Configuration Shape Theory consist of a more efficient computation, supported by the corresponding inference. This demands the solution of two important problems: (1) the development of analytical and efficient formulae for their k-th derivatives and (2) the use of the derivatives to transform the configuration density into a polynomial density under some special matrix Kummer relation, indexed in this case by the Jensen-Logistic kernel. In this article, we solve these problems by deriving a simple formula for the k-th derivative of the density function, avoiding the usual partition theory framework and using a generalization of Pascal triangles. Then we apply the results by obtaining the associated Jensen-Logistic Kummer relations and the configuration polynomial density in the setting of Statistical Shape Theory.     

Aggregating Political Dimensions: Of the Feasibility of Political Indicators

Political indicators are widely used in academic writing and decision making, but remain controversial. This paper discusses the problems related to the aggregation functions they use. Almost always, political indicators are aggregated by weighted averages or summations. The use of such functions is based on untenable assumptions (existence of homogeneous substitution rates, total compensation, and strict monotonicity). We show through concrete examples how these hidden assumptions are likely to produce results that are basically an artifact of ad hoc decisions, which additionally contradict very fundamental notions common to all credible political theories. We suggest, also through example, that some—necessarily partial—solutions are possible.     

The price of risk with incomplete knowledge on the utility function*

When a risk is exchanged, the exact value for the minimum price (positive or negative) that the purchaser (investor, or insurer) is willing to pay is given by the certainty equivalent wealth level, which in turn depends on his specific utility function. When this utility function is unknown, then only a sufficient condition on the price can ever be found. This paper provides methods for calculating such a sufficient condition, when only limited information on the utility function is known.     

Political election on legal retirement age

In the context of the current debate surrounding the reform of pension systems, this paper analyzes the political economy of the legal retirement age. Using a life-cycle model in which individuals differ by age and by wage, we analyze the outcome of a majority voting process on the legal retirement age in a Pay-As-You-Go pension system. The results show that the older an individual is, the closer her optimal retirement age is to the status quo age. That is, the status quo retirement age acts as a magnet. Additionally, we find that the preferred legal retirement age of most of the working population increases when the pension system is more redistributive. We also observe a positive relationship between the preferred legal retirement age and the status quo age.     

To participate or not to participate: that is the question

Do I wish to participate or not to participate in this program? That is the question that young people ask themselves when considering a new opportunity. What can be done to increase the likelihood that they will choose to participate in out-of-school-time (OST) programs? This chapter describes a qualitative study that examined reasons for participating or not participating in OST programs. Some common reasons emerged, but the study also revealed differences among youth from different ethnic groups. It is clear that those who design and conduct programs must understand the processes through which diverse adolescents initiate their participation in programs and either persist or drop out. Given the apparent benefits of active participation in youth programs, it is important to remove barriers and increase access and, equally important, design programs that are of interest to youth in the contexts in which they live.