An improved estimator to analyse missing data

Missing data due to nonresponse, though undesirable, is a reality of any survey. In this paper we consider a situation in which, at a given time, observations are missing for one of the several auxiliary characteristics; thus the ‘missing’ phenomenon occurs for the characteristics separately but not simultaneously. A new method, making use of all the available observations, is proposed. A simulation study based on three real populations was performed to test the proposed technique.     

Mobilities

This paper reconstructs the emergence of a student mobilization that occupied a central place in the Mexican political scenario in May and June of 2012. Within the framework of a formally democratic regime with an authoritarian functioning logic, the #YoSoy132 (#IAm132) movement was launched within social networks and quickly became an agent of dissatisfaction with the role played by the media as an interested party in a flawed electoral process. The shift from spontaneous protest to organic mobilization involved extending the proposal beyond the private university to which its first members belonged. It also meant that the initial reactive position gave rise to a collective movement of a proactive nature. Although the future of this movement is still uncertain, spaces for struggle have opened up around it, which have been described as the Mexican Spring.     

The impact of childbirth on Spanish women’s decisions to leave the labor market

The present paper analyzes the effect of childbirth on Spanish women??s decisions to withdraw from paid work, defined here as the transition from employment to out of the labor force due to the requirements of household production. Decisions regarding fertility and labor market participation are interrelated and depend on individual and household characteristics, as well as external variables such as the availability of childcare services. We postulate that a female??s decision to leave the labor market is taken in a household context, and thus is the outcome which maximizes household welfare after taking into account the employment and earnings characteristics of all household members. We pay special attention to the effect of the male partner??s characteristics upon the female??s decision to withdraw from the labor market. Our empirical results show that in order to better define social and labor market policies on work and family reconciliation, increased attention should be paid to the job characteristics of males given their effect on the optimal assignment of tasks within the household following childbirth.     

F-tests with a rare pathology

ANOVA is routinely used to compare pathologies. Nevertheless, in many situations, the sample dimensions may not be known when planning the study. This is specially relevant when one of the pathologies is rare. Thus, the sample size for that pathology or for all pathologies must be considered as random. Sample selection for the non-rare pathologies may be carried out to increase the balance of the model. This leads to F-tests with random non-centrality parameters and random degrees of freedom for the errors. The distribution of such tests statistics is obtained.     

The Importance of Variables in Composite Indices: A Contribution to the Methodology and Application to Development Indices

The paper examines the issue of weights and importance in composite indices of development. Building a composite index involves several steps, one of them being the weighting of variables. The nominal weight assigned to a variable often differs from the degree to which the variable affects the scores of the overall index. The newly suggested notion of importance is based on the idea that an important indicator, if omitted from the index, causes large changes in countries’ results. We propose a method of measuring the importance and apply it to inequality variables in composite indices of development. The results show a low importance for most inequality variables, and for some of them, a large discrepancy between the nominal weights and the importance. We argue that the importance of variables should be considered in the process of index construction. This may imply a modification of the index when there is a large discrepancy between the nominal weights and importance and when the importance of some variables is extremely low. Whether any such modification is justified must be decided within the context of the particular index.

     

A new approach to truncated regression for count data

AStA Advances in Statistical Analysis - Standard Poisson and negative binomial truncated regression models for count data include the regressors in the mean of the non-truncated distribution. In...     

The Transition to Self-Employment and Perceived Skill-Mismatches: Panel Data Evidence from Eleven EU Countries

Social Indicators Research - Some studies using either objective or subjective indicators, find that self-employed individuals are less likely to be or to report being skill-mismatched in...     

The Role of Physical Context,Verbal Skills,Non‐parental Care,Social Support,and Type of Parental Discipline in the Development of ToM Capacity in Five‐Year‐Old Children

The aim of this study was to analyze the influence of family context on the performance of 5‐year‐old children (N = 70) in theory of mind (ToM) tasks. The children's performances were assessed during individual sessions held at school. Children's verbal skills were assessed using the Peabody picture vocabulary test (PPVT). Interviews were also conducted with parents in the family home in order to gather sociodemographic data and to assess diverse variables of the family context. In addition to confirming the important role played by children's verbal skills in ToM, the results also supported a potential influence of family context in ToM development through variables, such as quality of non‐parental care or level of social contact and support. The educational implications of these results are discussed in relation to family intervention.     

Complements or substitutes? The contingent role of corporate reputation on the interplay between internal R&D and external knowledge sourcing

Existing research does not provide a clear answer to the question of whether internal knowledge development and external knowledge sourcing are complementary or substitutive innovation activities. This paper adopts a contingent approach for addressing this issue by examining whether and how the interactive effect of internal R&D efforts and external knowledge sourcing on product innovation performance may be affected by the firm’s corporate reputation. In doing so, a three-way interaction model is applied to a sample of 251 Spanish high-technology manufacturing firms. Interestingly, initial results support the substitutive argument: the positive effect of internal R&D on product innovation performance diminishes as the exposure to external knowledge increases. However, in well reputed companies, interaction becomes positive, revealing a complementary effect. Thus, the study extends the traditional approach focused on determining whether internal and external knowledge sourcing are complements or substitutes by showing that their interplay depends on other firm-specific characteristics. Moreover, identifying corporate reputation as a source of complementarity between both activities provides an additional explanation of how corporate reputation contributes to a more effective management of knowledge assets.     

Multivariate models for correlated count data

In this study, we deal with the problem of overdispersion beyond extra zeros for a collection of counts that can be correlated. Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial distributions have been considered. First, we propose a multivariate count model in which all counts follow the same distribution and are correlated. Then we extend this model in a sense that correlated counts may follow different distributions. To accommodate correlation among counts, we have considered correlated random effects for each individual in the mean structure, thus inducing dependency among common observations to an individual. The method is applied to real data to investigate variation in food resources use in a species of marsupial in a locality of the Brazilian Cerrado biome.