How Can Low‐income Countries Gain from a Framework Agreement on Climate Change? An Analysis with Integrated Assessment Modelling

By using the integrated assessment model RICE this article carries out a scenario analysis with different assumptions about international negotiations on climate change, in particular hypothesising about reduction in targets for greenhouse gas emissions, technology transfers and financial transfer programmes. It finds that, in terms of growth, developing countries and in particular sub‐Saharan Africa will benefit from agreements that reduce the level of pollution and promote technological diffusion. Moreover, when developed countries are subject to emissions limits and poor regions have no such commitments, financial transfers from rich to developing countries for adaptation and mitigation enhance pro‐poor growth and help the effectiveness of poor countries in reducing emissions.     

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

Physical activity is inversely related to drug consumption in elderly patients with cardiovascular events

Elderly patients with cardiovascular events are characterized by high drug consumptions. Whether high drug consumptions are related to physical activity is not known. In order to examine whether physical activity is related to drug consumption in the elderly, patients older than 65 years (n?=?250) with a recent cardiovascular event were studied. Physical activity was analyzed according to the Physical Activity Scale for the Elderly (PASE) score and related to drug consumption. PASE score was 72.4?±?45.0 and drug consumption was 8.3?±?2.2. Elderly patients with greater comorbidity took more drugs (8.7?±?2.1) and are less active (PASE?=?64.4?±?50.6) than patients with Cumulative Illness Rating Scale severity score higher than 1.8 than those with a score lower than 1.8 (76.3?±?41.4, p?<?0.05, and 8.0?±?2.0, p?=?0.006, respectively). Multivariate analysis correlation confirmed that PASE score is negatively associated with drug consumption (β?=??0.149, p?=?0.031), independently of several variables including comorbidity. Thus, physical activity is inversely related to drug consumption in elderly patients with cardiovascular events. This inverse relationship may be attributable to the high degree of comorbidity observed in elderly patients in whom poor level of physical activity and high drug consumption are predominant.     

A Characterization of a Matric-Variate Exponential Distribution

Suppose S is a positive definite m x m random matrix and S> Ω denotes the event that S—Ω is positive definite, Ω being a constant positive definite matrix. Under very mild regularity conditions, we show that the constraint Pr(S>Ω₁+Ω₂ | S>Ω₂) = Pr(S>Ω₁) implies that S has a Wishart distribution on m+ 1 degrees of freedom.     

The expected personality characteristics of alcohol-dependent individuals

The Big Five personality factors were used as a framework for examining the expected personality characteristics of individuals who are alcohol-dependent. In an experimental study, participants used a measure of the Big Five personality factors to rate two individuals, each described with either signs of alcohol dependence or not. The ratings of the participants showed that they expected the alcohol-dependent versions of both individuals to be less agreeable and less conscientious. The participants expected the alcohol-dependent college student to be more extraverted and the alcohol-dependent lawyer-father to be more neurotic. The expected personality characteristics of the alcohol-dependent versions of the two described persons were very similar to the actual personality characteristics of alcohol-dependent individuals. The results were consistent with prior findings regarding narrow-band personality traits related to the Big Five. The results help explain prior findings about the social handicap of problem drinking with regard to making friends, dating, marriage, and working. The findings have potential use in alcohol-problem prevention and treatment.     

Low emotional intelligence as a predictor of substance-use problems

This study explored the relationship between low emotional intelligence and substance-use problems in adults. One hundred and forty-one participants completed the Self-Administered Alcoholism Screening Test, the Drug Abuse Screening Test, an emotional intelligence scale, and a measure of psychosocial coping. Low emotional intelligence was a significant predictor of both alcohol-related problems and drug-related problems. Poorer coping predicted drug-related problems, but not alcohol-related problems. Coping was not found to be a significant mediator between emotional intelligence and substance-use problems. Possible implications for intervention and treatment efforts are discussed.     

Small area estimation: the EBLUP estimator based on spatially correlated random area effects

This paper deals with small area indirect estimators under area level random effect models when only area level data are available and the random effects are correlated. The performance of the Spatial Empirical Best Linear Unbiased Predictor (SEBLUP) is explored with a Monte Carlo simulation study on lattice data and it is applied to the results of the sample survey on Life Conditions in Tuscany (Italy). The mean squared error (MSE) problem is discussed illustrating the MSE estimator in comparison with the MSE of the empirical sampling distribution of SEBLUP estimator. A clear tendency in our empirical findings is that the introduction of spatially correlated random area effects reduce both the variance and the bias of the EBLUP estimator. Despite some residual bias, the coverage rate of our confidence intervals comes close to a nominal 95%.     

Behavioural Addictions in Adolescents and Young Adults: Results from a Prevalence Study

Our study aims to assess the prevalence of behavioural addictions in an adolescent population, evaluating the effects of gender and age, and to assess the correlations among different behavioural addictions. 2853 high school students were assessed in order to evaluate the prevalence of behavioural addictions such as Pathological Gambling (PG), Compulsive Buying (CB), Exercise Addiction (EA), Internet Addiction (IA), and Work Addiction (WA), in a population of Italian adolescents. The South Oaks Gambling Screen-Revised Adolescent (SOGS-RA), the Compulsive Buying Scale (CBS), the Exercise Addiction Inventory (EAI), the Internet Addiction Test (IAT), and the Work Addiction Risk Test (WART), were compiled anonymously by the students. Overall prevalence was 7.0% for PG, 11.3% for CB, 1.2% for IA, 7.6% for WA, 8.5% for EA. PG and EA were more common among boys, while gender had no effect on the other conditions. CB was more common among younger (<18 years old) students. The scores of all of these scales were significantly correlated. The strong correlation among different addictive behaviours is in line with the hypothesis of a common psychopathological dimension underlying these phenomena. Further studies are needed to assess personality traits and other clinical disorders associated with these problems behaviours.     

Which Domestic Firms Benefit from FDI? Evidence from Selected African Countries

The existing literature on the effects of FDI inflows on domestic firms' performance offers ambiguous evidence. Macro‐level studies suggest that the characteristics of inward FDI and the ‘absorptive capacity’ of the host economy matter in determining the sign (or the mere existence) of these effects. Studies based on micro‐level data have so far mostly focused on finding a nexus between FDI inflows and the productivity of domestic firms, suggesting that the effects might be highly heterogeneous. This article, using a recent firm‐level survey conducted by UNIDO in 19 sub‐Saharan African countries, explores the channels through which multinational enterprises may exert an impact on local firms: products’ market, input availability and costs, access to finance and export opportunities, and analyses the strategic reactions of domestic firms induced by the presence of foreign affiliates.