International Migration and Development in Asia: Exploring Knowledge Frameworks

There is revived interest and debate on the relation between international migration and development, with Asia emerging as one important locus for such deliberations. A number of institutions, journals, people and organizations have emerged as key players in these discussions but so far there have been few attempts to investigate the information gathered from the perspective of “knowledge production”. This paper’s objective, therefore, is to outline some of the ways in which knowledge about migration and development is being produced in Asia. We focus on selected aspects of knowledge production to identify the lenses through which much of the work is currently generated and the research imagination resulting from existing approaches.     

Characterization of a class cf discrete distributions by properties of their moment distributions

The concept of a moment distribution is here applied to the class of factorial series distributions introduced by the author (197U). Moment distributions turn out to have a simple interpretation in this case and often take on a simple form. A few examples are given to illustrate this fact     

From wage rigidity to labour market institution rigidity: A turning-point in explaining unemployment?

In this paper we offer a critical discussion about the concept of labour market rigidity in the light of recent theoretical approaches that have aimed to provide sound micro-foundations to the presence of unemployment in market economies. We point out that the concept of labour market rigidity usually referred to in such theories has changed over time, involving in succession the rigidity of wages, contracts and labour market institutions. We also appraise the factors that lead labour market institutions rigidity, stressed by the search literature, to challenge the more widespread explanation of unemployment grounded on wage rigidity. Moreover, we analyse some theoretical and empirical issues that cast doubt on the ability to deal with unemployment, disentangling the role of institutional rigidities from that of wage stickiness.     

Family Trajectories and Health: A Life Course Perspective

This paper investigates the role of family trajectory, i.e., the whole sequence of family events during the life course of early adults in shaping their health outcomes. Union formation and childbearing are jointly considered, since the two life domains are highly connected and their intersections may have an effect on health outcomes. Data come from wave I and wave IV of the National Longitudinal Study of Adolescent Health (Add Health) in the United States. The paper is divided in two parts. The first part focuses on family transitions and investigates if changes in timing (when events happen), quantum (what and how many transitions), and ordering (in what order), have an effect on the health of young women. In the second part, life course trajectories are classified into six groups representing different ideal-types of family trajectories and the association of these trajectories with health outcomes is explored. Results suggest that family trajectories play an important role on different health outcomes. Controlling for selection and background characteristics, precocious and “non-normative” transitions are associated with lower self-reported health and higher propensity of smoking and drinking.     

Local stationarity in small area estimation models

Small area estimators are often based on linear mixed models under the assumption that relationships among variables are stationary across the area of interest (Fay–Herriot models). This hypothesis is patently violated when the population is divided into heterogeneous latent subgroups. In this paper we propose a local Fay–Herriot model assisted by a Simulated Annealing algorithm to identify the latent subgroups of small areas. The value minimized through the Simulated Annealing algorithm is the sum of the estimated mean squared error (MSE) of the small area estimates. The technique is employed for small area estimates of erosion on agricultural land within the Rathbun Lake Watershed (IA, USA). The results are promising and show that introducing local stationarity in a small area model may lead to useful improvements in the performance of the estimators.     

Explaining Attitudes toward Immigrants and Immigration Policy: A Review of the Theoretical Literature

In the research literature on immigration attitudes, there are a number of theories that explain why individuals hold positive or negative opinions of certain immigrant groups and immigration policies. In this review of the literature, the theories are summarized into five categories: personal and social identity, self and group interest, cultural values and beliefs, social interaction, and multilevel theories. The majority of the theories offer explanations that favor one causal direction, focus on social psychology or the social structural environment, and assume that effects are additive rather than interactive. It is argued in this review that scholars would benefit by using multilevel theories, such as group position theory and intersectionality, in order to extend their explanatory reach past the theoretical standards and, in doing so, be able to better examine some understudied but important questions, such as why individuals often hold pro‐ and anti‐immigrant opinions simultaneously. Multilevel theories have the potential to offer a nuanced understanding of immigration attitudes.     

Illegitimate tasks as a source of work stress

Illegitimate tasks represent a task-level stressor derived from role and justice theories within the framework of “Stress-as–Offense-to-Self” (SOS; Semmer, Jacobshagen, Meier, & Elfering, 2007). Tasks are illegitimate if they violate norms about what an employee can properly be expected to do, because they are perceived as unnecessary or unreasonable; they imply a threat to one's professional identity. We report three studies testing associations between illegitimate tasks and well-being/strain. In two cross-sectional studies, illegitimate tasks predicted low self-esteem, feelings of resentment towards one's organization and burnout, controlling for role conflict, distributive injustice and social stressors in Study 1, and for distributive and procedural/interactional justice in Study 2. In Study 3, illegitimate tasks predicted two strain variables (feelings of resentment towards one's organization and irritability) over a period of two months, controlling for initial values of strain. Results confirm the unique contribution of illegitimate tasks to well-being and strain, beyond the effects of other predictors. Moreover, Study 3 demonstrated that illegitimate tasks predicted strain, rather than being predicted by it. We therefore conclude that illegitimate tasks represent an aspect of job design that deserves more attention, both in research and in decisions about task assignments.     

Inference from PseudoLikelihoods with Plug‐In Estimates

Effective implementation of likelihood inference in models for high‐dimensional data often requires a simplified treatment of nuisance parameters, with these having to be replaced by handy estimates. In addition, the likelihood function may have been simplified by means of a partial specification of the model, as is the case when composite likelihood is used. In such circumstances tests and confidence regions for the parameter of interest may be constructed using Wald type and score type statistics, defined so as to account for nuisance parameter estimation or partial specification of the likelihood. In this paper a general analytical expression for the required asymptotic covariance matrices is derived, and suggestions for obtaining Monte Carlo approximations are presented. The same matrices are involved in a rescaling adjustment of the log likelihood ratio type statistic that we propose. This adjustment restores the usual chi‐squared asymptotic distribution, which is generally invalid after the simplifications considered. The practical implication is that, for a wide variety of likelihoods and nuisance parameter estimates, confidence regions for the parameters of interest are readily computable from the rescaled log likelihood ratio type statistic as well as from the Wald type and score type statistics. Two examples, a measurement error model with full likelihood and a spatial correlation model with pairwise likelihood, illustrate and compare the procedures. Wald type and score type statistics may give rise to confidence regions with unsatisfactory shape in small and moderate samples. In addition to having satisfactory shape, regions based on the rescaled log likelihood ratio type statistic show empirical coverage in reasonable agreement with nominal confidence levels.     

Corporate Governance and the Governance of Innovation: The Case of Pharmaceutical Industry

The paper focuses on some organizationaldynamics that have characterized the pharmaceuticalindustry in the last thirty years, whenbiotechnology and the development of lifesciences have defined a new technologicalparadigm, reshaping many aspects of theindustry, especially the organization ofinnovative activity. We suggest an original interpretation of someorganizational settings, as the increasedimportance of skilled scientists within firmsand the development of inter-organizationalalliances for the division of scientific labor.Following recent theorizing on corporategovernance issues, which points out theintrinsic organizational and relationaldimensions of the resource allocation processesand strategic decision-making, we propose a roleof the organizational practices mentioned aboveon corporate governance, and, in turn, aninfluence of different governance arrangementson innovative activity. We recall moretraditional approaches to the analysis ofcorporate governance, and give a broaderinterpretation to the relevant variablesproposed. Further, relying on more recenttheories and on literature on firm's boundariesand sectoral systems of innovation, we proposeindustry-specific variables forpharmaceuticals, including internal settings aswell as relations with external actors.Preliminary empirical support is given to ourhypotheses, concerning a panel of large USpharmaceutical companies.     

A bootstrap test for time series linearity

A bootstrap algorithm is proposed for testing Gaussianity and linearity in stationary time series, and consistency of the relevant bootstrap approximations is proven rigorously for the first time. Subba Rao and Gabr (1980) and Hinich (1982) have formulated some well-known nonparametric tests for Gaussianity and linearity based on the asymptotic distribution of the normalized bispectrum. The proposed bootstrap procedure gives an alternative way to approximate the finite-sample null distribution of such test statistics. We revisit a modified form of Hinich's test utilizing kernel smoothing, and compare its performance to the bootstrap test on several simulated data sets and two real data sets—the S&P 500 returns and the quarterly US real GNP growth rate. Interestingly, Hinich's test and the proposed bootstrapped version yield substantially different results when testing Gaussianity and linearity of the GNP data.