Consuming Youth: Timorese in the Resistance Against Indonesian Occupation

This article explores the role played by risk-seeking Timorese youth, known as the New Generation (Geraçao Foun), in the resistance movement against Indonesian occupation (1975–1999). It discusses the capture, regimentation and marginalisation of youthful radicalism by the national resistance movement. The paper looks at these processes of youth revolutionary involvement sympathetically though the memories of former participants in the clandestine struggle and is representative of a new reflexive phase in young Timorese' post-colonial self-realisation. This phase is decidedly non-triumphalist, one which dwells on the inability to be ‘recompensed’ for the dreams that were captured and lives that were side-tracked in a conflict that consumed youth.     

Being Under Time Pressure: The Case of Workers with Disabilities

This article examines levels of time stress reported by people with and without disabilities. Using data at an individual level from the Time Use Survey for Spain in 2002–2003, we estimate an ordered probit model to investigate the determinants of time stress by disability status. We find that disabled individuals work fewer hours, have more free time and engage in more household labour as compared to the non-disabled. The estimation results show that disabled workers (especially those who are severely or moderately limited in their daily activities) suffer from more stress than their non-disabled counterparts. In addition, longer working hours increase the levels of time stress reported by all individuals, but more intensely so among disabled workers.     

Smith D.H.: Determinants of Individual Prosociality and of Collective Social Solidarity–Cohesion: A Literature Review

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Fractional approaches for the distribution of innovation sequence of INAR(1) processes

Abstract

In this paper, we present a fractional decomposition of the probability generating function of the innovation process of the first-order non-negative integer-valued autoregressive [INAR(1)] process to obtain the corresponding probability mass function. We also provide a comprehensive review of integer-valued time series models, based on the concept of thinning operators with geometric-type marginals. In particular, we develop two fractional approaches to obtain the distribution of innovation processes of the INAR(1) model and show that the distribution of the innovations sequence has geometric-type distribution. These approaches are discussed in detail and illustrated through a few examples.     

Label‐ and Level‐Invariant Graphical Log‐Linear Models

We introduce two types of graphical log‐linear models: label‐ and level‐invariant models for triangle‐free graphs. These models generalise symmetry concepts in graphical log‐linear models and provide a tool with which to model symmetry in the discrete case. A label‐invariant model is category‐invariant and is preserved after permuting some of the vertices according to transformations that maintain the graph, whereas a level‐invariant model equates expected frequencies according to a given set of permutations. These new models can both be seen as instances of a new type of graphical log‐linear model termed the restricted graphical log‐linear model, or RGLL, in which equality restrictions on subsets of main effects and first‐order interactions are imposed. Their likelihood equations and graphical representation can be obtained from those derived for the RGLL models.     

Do Cooperatives with Better Economic–Financial Indicators also have Better Socioeconomic Performance?

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - The overall performance of cooperatives is related to economic–financial results and actions focused on benefits for...     

Alternative diff-in-diffs estimators with several pretreatment periods

This paper deals with the identification of treatment effects using difference-in-differences estimators when several pretreatment periods are available. We define a family of identifying nonnested assumptions that lead to alternative difference-in-differences estimators. We show that the most usual difference-in-differences estimators imply equivalence conditions for the identifying nonnested assumptions. We further propose a model that can be used to test multiple equivalence conditions without imposing any of them. We conduct a Monte Carlo analysis and apply our approach to several recent papers to show its practical relevance.     

Generalised Variance Function Estimation for Binary Variables in Large‐Scale Sample Surveys

Generalised variance function (GVF) models are data analysis techniques often used in large‐scale sample surveys to approximate the design variance of point estimators for population means and proportions. Some potential advantages of the GVF approach include operational simplicity, more stable sampling errors estimates and providing a convenient method of summarising results when a high number of survey variables is considered. In this paper, several parametric and nonparametric methods for GVF estimation with binary variables are proposed and compared. The behavior of these estimators is analysed under heteroscedasticity and in the presence of outliers and influential observations. An empirical study based on the annual survey of living conditions in Galicia (a region in the northwest of Spain) illustrates the behaviour of the proposed estimators.