Initiative in work teams: adaptation and validation of the Personal Initiative at Group Level Scale / Iniciativa en los equipos de trabajo: adaptación y validación de la Escala de Iniciativa Personal a nivel Grupal

In this study, we conceptualize personal initiative as a collective construct and adapt and validate a scale to evaluate it with a sample of 308 Spanish participants belonging to 91 work teams. Personal initiative at group level is a behavioural syndrome in which the team shows an approach to work that is self-initiated, proactive, persistent, capable of modifying the atmosphere and pro organization. As a predictive variable, we analysed the climate for initiative as well as personal initiative at group level. The resulting variables that were analysed referred to organization and team performance, with the team productivity and innovation as the criteria, analysing radical innovation. The scale has suitable psychometric properties. The results show that there is a relationship between the two predictive variables. Furthermore, personal initiative at group level is related to team productivity, while the climate for initiative is related to innovation.     

QUALITY DIFFERENCES,THIRD‐DEGREE PRICE DISCRIMINATION,AND WELFARE

We propose a model with two markets to analyze the welfare implications of price discrimination with quality differences. In each market a local firm that operates in that market only competes against a global firm that operates in both markets. Local firms produce higher‐quality goods than the global firm. If the quality levels of the local firms' products are the same, price discrimination is never welfare‐decreasing. If they differ, discrimination is welfare‐increasing if quantity increases. Because of a positive allocation effect of price discrimination, there are parameter values such that welfare increases while total output decreases with price discrimination. (JEL D43, D60)     

Analysis of the non-native flora of Ensenada, a fast growing city in northwestern Baja California

Urbanized areas show a high proportion of non-native plants and can work as dispersal points to the surrounding areas. Ensenada is a fast growing city located in the northwestern peninsula of Baja California (Mexico). It is the southern extreme of a bi-national, coastal urban corridor that extends from Los Angeles, California south to Ensenada. This corridor is part of the biodiversity hotspot of the California Floristic Province. The aim of this study was to analyze the composition and distribution of the spontaneous flora in the city of Ensenada. We systematically sampled two differentiated urban environments, vacant lots and arroyos, in 2006 and 2007. We found a total of 158 plant species, 61% of them were non-native species. Arroyo areas showed higher non-native species richness than vacant lots (21.9 vs. 13.6 species/transect) and could be potential dispersal vectors for non-native species to natural areas outside of the city, or in the reverse direction also.     

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.     

The impact of migration on the well-being of transnational families: new data from sending communities in Mexico

We present results from a new study of the effects of migration to the USA on the well-being of transnational families in high emigration communities within Mexico. Our survey measured the well-being of family members in a variety of domains: economic, health, education, and child development for a representative sample drawn from high migration municipalities. Compared to those with no recent emigrants to the USA, Mexican households sending non-caregivers to the USA appear to gain economically without contributing to problems faced by children. However, when family caregivers migrate to the USA, the remaining members in Mexico struggle to meet the family's needs and children are more vulnerable to educational, emotional, and health problems. Children in households where a caregiver migrated were more likely to have frequent illnesses (10% vs. 3%, p<0.0001), chronic illness (7% vs. 3%, p=0.011), emotional problems (10% vs. 4%, p=0.006), and behavioral problems (17% vs. 10%, p=0.018) compared with children in households where the migrant was not a caregiver. Research, policy, and program implications of these findings are discussed.     

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.