Mental Health of Non-gamblers Versus “Normal” Gamblers Among American Indian Veterans: A Community Survey

Goal This analysis was undertaken to assess the demographic and mental health characteristics of “normal” or non-problem gamblers versus non-gamblers in a representative community sample. Sample Study participants consisted of 557 North Central American Indian veterans. Data collection included a demographic and trauma questionnaire, a computer-based Diagnostic Interview Schedule for DSM-III-R, and a treatment history algorithm. Findings Univariate analyses revealed that gamblers had greater social competence (i.e., higher education, living with a spouse) and higher lifetime psychiatric morbidity. Binary regression analysis revealed that, compared to non-gamblers, gamblers were older, more highly educated, and more apt to be married. More gamblers showed evidence for lifetime risk-taking as evidenced by Antisocial Personality Disorder and Tobacco Dependence. Conclusions Social achievement and disposable income function as prerequisites for “normal” gambling in this population, although “externalizing” or “risk-taking” disorders also serve as independent contributors to at least some gambling. The increased rate of “internalizing” or emotional disorders are only indirectly related to gambling, perhaps through increasing age or through the “externalizing” disorders.     

Centacare in the Northern Territory

Abstract

At the present time, social work in England finds itself at the crossroads. Against a backdrop of economic globalisation, it has been caught up in New Labour's modernising policy discourse that has recast social justice in terms of opportunity, inclusion, and “choice”. More recently, this has been extended by the introduction of a “respect agenda”, a reaction to the loss of community cohesion and the rise in antisocial behaviour. In the present article, two alternative paradigmatic responses are explored reflecting a debate between evidence-based practice (EBP) and critical practice (CP). These may be juxtaposed because they offer different visions of what social work could become in the future while providing two important reference points against which current practice may be judged. Whereas the former has been depicted as a “search for certainty” that largely complements the modernising discourse, CP works with both certainty and uncertainty in the quest for more emancipatory change. In practice, English social workers may manage such contradictions by looking down both roads and incorporating elements of both in their practice: adopting elements of EBP to justify their interventions and become more research minded while embracing aspects of CP to engage with structural issues that lie at the root of injustice.     

Educational disparities across regions: A multilevel analysis for Italy and Spain

In this paper, a multilevel analysis is applied to the OECD-PISA2006 data with the aim to compare factors affecting students’ achievement across Italy and Spain. The findings show that both countries are affected by strong internal regional heterogeneity, where some regions have achievement scores well above the OECD mean and other are placed among the worst performers in the OECD area. Although regional governments are more autonomous about educational policy-making in Spain, regional indicators exert a higher influence on educational results in Italy where educational system is strictly regulated by the national government.     

Modelling the Inverse Association between Breastfeeding and Contraceptive Use

Previous studies of the inverse association between breastfeeding and contraceptive use have relied on current status data on at least one of the variables. In this paper we suggest a new way of modelling the joint temporal association of the adoption of contraception and the termination of breastfeeding over the course of a birth interval. The approach is implemented with survey data from rural Mexico. It involves first estimating a competing-risks model in which both hazards are considered simultaneous, together with a set of relevant covariates. Conditional analyses are then carried out to estimate the hazards of each event conditional on the timing of the other. By comparing the covariates, we gauge the extent to which the occurrence of one event raises or lowers the hazard of the other. The results show that, in rural Mexico, the timing of the termination of breastfeeding and that of starting contraceptive use are closely related, and that there exists a surprisingly neat interval of 120 days in which the action takes place.     

Generalized order statistic processes and Pfeifer records

We introduce a uniform generalized order statistic process. It is a simple Markov process whose initial segment can be identified with a set of uniform generalized order statistics. A standard marginal transformation leads to a generalized order statistic process related to non-uniform generalized order statistics. It is then demonstrated that the nth variable in such a process has the same distribution as an nth Pfeifer record value. This process representation of Pfeifer records facilitates discussion of the possible limit laws for Pfeifer records and, in some cases, of sums thereof. Because of the close relationship between Pfeifer records and generalized order statistics, the results shed some light on the problem of determining the nature of the possible limiting distributions of the largest generalized order statistic.     

Do Central Bank Liquidity Facilities Affect Interbank Lending Rates?

In response to the global financial crisis that started in August 2007, central banks provided extraordinary amounts of liquidity to the financial system. To investigate the effect of central bank liquidity facilities on term interbank lending rates near the start of the crisis, we estimate a six-factor arbitrage-free model of U.S. Treasury yields, financial corporate bond yields, and term interbank rates. This model can account for fluctuations in the term structure of credit and liquidity spreads observed in the data. A significant shift in model estimates after the announcement of the liquidity facilities suggests that these central bank actions did help lower the liquidity premium in term interbank rates.     

Change points in nonparametric regresion functions

Estimators of location and size of jumps or discontinuities in a regression function and/or its derivatives are proposed. The estimators are based on the analysis of residuals obtained from the locally weighted least squares regression. The proposed estimators adapt to both fixed and random designs. The asymptotic properties of the estimators are investigated. The method is illustrated through simulation studies.     

GMM Estimation of Count-Panel-Data Models With Fixed Effects and Predetermined Instruments

The “traditional” approach to the estimation of count-panel-data models with fixed effects is the conditional maximum likelihood estimator. The pseudo maximum likelihood principle can be used in these models to obtain orthogonality conditions that generate a robust estimator. This estimator is inconsistent, however, when the instruments are not strictly exogenous. This article proposes a generalized method of moments estimator for count-panel-data models with fixed effects, based on a transformation of the conditional mean specification, that is consistent even when the explanatory variables are predetermined. Two applications are discussed, the relationship between patents and research and development expenditures and the explanation of technology transfer.     

Weighting Elementary Prices in Consumer Price Index Construction Using Spatial Autocorrelation

The Consumer Price Indexes (CPI) are used in current economic systems to measure inflation. When constructing CPIs, however, official institutions have systematically overlooked the spatial dimension of elementary prices. Ignoring the fact that prices are collected at geographical locations implicitly implies considering prices as spatially independent, when in fact they are not. To solve this problem, this article proposes to weight basic price data by taking into account the spatial correlation they display. The weighted geometric and arithmetic means suggested generalize and improve the simple geometric and arithmetic means currently in use.     

A note on an integer valued time series model with Poisson–negative binomial marginal distribution

Abstract

This paper proposes a new model for autoregressive time series of counts in terms of a convolution of Poisson and negative binomial random variables, known as Poisson–negative binomial (PNB) distribution. The corresponding first-order integer valued time series models are developed and their properties are discussed. The geometric PNB and the geometric semi PNB distributions are also introduced and studied.