Social Capital and Wages: An Econometric Evaluation of Social Networking's Effects

Abstract. The goal of this paper is to get an econometric evaluation of the effects of the social network's mobilization, as a job search strategy, on wages. We make use of switching regression models to deal simultaneously with an endogenous selection issue in the network's choice and the existence of two different regimes of wage determination. Econometric estimates provide evidence for the existence of a selection effect on the choice of network but, after correcting the selection bias on the wage equations, the effect of social network on wages is negative.     

Estimating Long Memory in Volatility

We consider semiparametric estimation of the memory parameter in a model that includes as special cases both long‐memory stochastic volatility and fractionally integrated exponential GARCH (FIEGARCH) models. Under our general model the logarithms of the squared returns can be decomposed into the sum of a long‐memory signal and a white noise. We consider periodogram‐based estimators using a local Whittle criterion function. We allow the optional inclusion of an additional term to account for possible correlation between the signal and noise processes, as would occur in the FIEGARCH model. We also allow for potential nonstationarity in volatility by allowing the signal process to have a memory parameter d^*1/2. We show that the local Whittle estimator is consistent for d^*∈(0,1). We also show that the local Whittle estimator is asymptotically normal for d^*∈(0,3/4) and essentially recovers the optimal semiparametric rate of convergence for this problem. In particular, if the spectral density of the short‐memory component of the signal is sufficiently smooth, a convergence rate of n^2/5−δ for d^*∈(0,3/4) can be attained, where n is the sample size and δ>0 is arbitrarily small. This represents a strong improvement over the performance of existing semiparametric estimators of persistence in volatility. We also prove that the standard Gaussian semiparametric estimator is asymptotically normal if d^*=0. This yields a test for long memory in volatility.     

The sexual partnerships of people with serious mental illness

We compared the sexualities of people with serious mental illness and the general population using the National Health and Social Life Survey (Laumann et al., 1994) and the Indiana Mental Health Services and HIV Risk Study (Wright, 2003). We investigated whether and how the sexual behaviors and relationships of people with serious mental illness differ from the general populations and identified factors differently influencing the organization of sexuality in these two groups. We found evidence that the relationships of people with serious mental illness are characterized by less intimacy and commitment than those of the general population. Additionally, although people with serious mental illness use condoms more consistently, they are also more likely to have concurrent relationships and tend to have sex sooner with new partners, which may contribute to a higher risk of contracting HIV. Our findings point to a need for a paradigm shift in the way that clinicians and researchers conceptualize and manage client sexuality. A less individualistic approach that takes into consideration the relationship context and social and institutional constraints is needed.     

Sexual identity development among gay, lesbian, and bisexual youths: consistency and change over time

A longitudinal report of 156 gay, lesbian, and bisexual youths examined changes in sexual identity over time. Fifty-seven percent of the youths remained consistently self-identified as gay/lesbian, 18% transited from bisexual to gay/lesbian, and 15% consistently identified as bisexual over time. Although youths who consistently identified as gay/lesbian did not differ from other youths on time since experiencing sexual developmental milestones, they reported current sexual orientation and sexual behaviors that were more same-sex centered and they scored higher on aspects of the identity integration process (e.g., more certain, comfortable, and accepting of their same-sex sexuality, more involved in gay-related social activities, more possessing of positive attitudes toward homosexuality, and more comfortable with others knowing about their sexuality) than youths who transited to a gay/lesbian identity and youths who consistently identified as bisexual. Contrary to the hypothesis that females are more sexually fluid than males, female youths were less likely to change identities than male youths. The finding that youths who transited to a gay/lesbian identity differed from consistently gay/lesbian youths suggests that identity integration continues after the adoption of a gay/lesbian sexual identity.     

Cumulative Correspondence Analysis of Two-Way Ordinal Contingency Tables

A suitable measure of association for two ordered variables is the doubly cumulative chi-squared statistic (Hirotsu, 1994 Hirotsu , C. ( 1994 ). Modelling and analysing the generalized interaction . Proc. Third IEEE Conf. Control Applic. 2 : 1283 – 1288 .[Crossref] , [Google Scholar]). This statistic is obtained by considering the cumulative sum of cell frequencies across the variables. In this article, we explore the development of correspondence analysis which takes into account the presence of two ordered variables by partitioning the doubly cumulative chi-squared statistic.     

Parametric survival densities from phase-type models

After a brief historical survey of parametric survival models, from actuarial, biomedical, demographical and engineering sources, this paper discusses the persistent reasons why parametric models still play an important role in exploratory statistical research. The phase-type models are advanced as a flexible family of latent-class models with interpretable components. These models are now supported by computational statistical methods that make numerical calculation of likelihoods and statistical estimation of parameters feasible in theory for quite complicated settings. However, consideration of Fisher Information and likelihood-ratio type tests to discriminate between model families indicates that only the simplest phase-type model topologies can be stably estimated in practice, even on rather large datasets. An example of a parametric model with features of mixtures, multiple stages or ‘hits’, and a trapping-state is given to illustrate simple computational tools in R, both on simulated data and on a large SEER 1992–2002 breast-cancer dataset.     

Disaggregated spatial modelling for areal unit categorical data

Summary.  We consider joint spatial modelling of areal multivariate categorical data assuming a multiway contingency table for the variables, modelled by using a log-linear model, and connected across units by using spatial random effects. With no distinction regarding whether variables are response or explanatory, we do not limit inference to conditional probabilities, as in customary spatial logistic regression. With joint probabilities we can calculate arbitrary marginal and conditional probabilities without having to refit models to investigate different hypotheses. Flexible aggregation allows us to investigate subgroups of interest; flexible conditioning enables not only the study of outcomes given risk factors but also retrospective study of risk factors given outcomes. A benefit of joint spatial modelling is the opportunity to reveal disparities in health in a richer fashion, e.g. across space for any particular group of cells, across groups of cells at a particular location, and, hence, potential space–group interaction. We illustrate with an analysis of birth records for the state of North Carolina and compare with spatial logistic regression.     

The analysis of dependence for three ways contingency tables with ordinal variables: A case study of patient satisfaction data

For many questionnaires and surveys in the marketing, business, and health disciplines, items often involve ordinal scales (such as the Likert scale and rating scale) that are associated in sometimes complex ways. Techniques such as classical correspondence analysis provide a simple graphical means of describing the nature of the association. However, the procedure does not allow the researcher to specify how one item may be associated with another, nor does the analysis allow for the ordinal structure of the scales to be reflected. This article presents a graphical approach that can help the researcher to study in depth the complex association of the items and reflect the structure of the items. We will demonstrate the applicability of this approach using data collected from a study that involves identifying major factors that influence the level of patient satisfaction in a Neapolitan hospital.     

The impact of government expenditure on economic growth: How sensitive to the level of development?

Previous studies generally find mixed empirical evidence on the relationship between government spending and economic growth. In this paper, we re-examine the causal relationship between government expenditure and economic growth by conducting the panel Granger causality test recently developed by (Hurlin, 2004) and (Hurlin, 2005) and by utilizing a richer panel data set which includes 182 countries that cover the period from 1950 to 2004. Our empirical results strongly support both Wagner's law and the hypothesis that government spending is helpful to economic growth regardless of how we measure the government size and economic growth. When the countries are disaggregated by income levels and the degree of corruption, our results also confirm the bi-directional causality between government activities and economic growth for the different subsamples of countries, with the exception of the low-income countries. It is suggested that the distinct feature of the low-income countries is likely owing to their inefficient governments and inferior institutions.