The Gatekeeping Function of Trust in Cross‐sector Social Partnerships

Hunger and deprivation, lack of education, sanitation, and health care are only a few pressing issues related to poverty in developing countries. Addressing such complex social issues requires pooling complementary resources of the civil, public, and private sector. Over the last decade, stakeholders tried to cocreate innovative solutions in cross‐sector social partnerships (CSSPs) at the base of the economic pyramid (BoP), but collaboration proved to be very challenging. Practitioners become increasingly frustrated with operational differences, intransparency, and mismatched goals in partnerships. This study unravels the black box of collaboration and delivers empirical insights on trust and power in CSSPs based on social exchange theory. Structural equation modeling (SEM) enables us explore relationships beyond case‐based insights. Our rigorous empirical analysis covers 207 interorganizational relationships and outlines a crucial gatekeeping function of trust in CSSPs. Findings provide strong empirical support for conceptual works calling for an “integrative orientation” in CSSPs. Furthermore, we pinpoint the role of intermediates and draw implications for future research.     

Impact of Public and Private Cash Transfers on Poverty and Inequality: Evidence from Vietnam

This article investigates the extent to which public and private transfers affected poverty and inequality in Vietnam in the mid‐2000s. It finds that the impact of public transfers on poverty was negligible, due to the low coverage of the poor and the relatively small amounts transferred. Moreover, the effect of the receipt of transfers on expenditures was small: recipients decreased the labour supply and only a limited amount of the extra income went to current consumption. Domestic private transfers were somewhat more successful in reducing poverty. With most public and private transfers going to non‐poor households, inequality was only marginally affected.     

Gay Community Involvement: Its Interrelationships and Associations With Internet Use and HIV Risk Behaviors in Swedish Men Who Have Sex With Men

We measured aspects of “community involvement” chosen for men who have sex with men (MSM) in Sweden (gay places, media accessed, Internet, gay festivals, and social engagement, measured as proportion of gay friends) in two Swedish Internet-based samples from 2006 (n?=?3,202) and 2008 (n?=?4,715). Data showed low to moderate reliability with a moderate (0.57) alpha coefficient. While there is moderate internal consistency, as might be anticipated from measures of actual community involvement, they can be treated as scales. The Internet scale indicated the lowest reliability, perhaps due to respondents having Internet sites of primary choice, rather than a high level of usage across several sites. A hypothesized lack of correlation between traditional domains of the gay community and the Internet did not appear: correlations between the Internet measure and the other measures were positive and significant, but among the lowest correlations obtained between the community measures, ranging from 0.06 to 0.24. Those who use the Internet extensively are less likely to be involved in other aspects of the community. Sexual risk was associated with high social engagement at sexual meeting sites and with Internet use. Gay community involvement, including the Internet community, may be complex and associated with both increase in HIV sexual risk behaviors (by measuring use of sexual risk sites) and preventive measures (HIV testing).     

The impact of early-life economic conditionson cause-specific mortality during adulthood

The aim of this study is to assess the effects of economic conditions in early life on cause-specific mortality during adulthood. The analyses are performed on a unique historical sample of 14,520 Dutch individuals born in 1880–1918, who are followed throughout life. The economic conditions in early life are characterized using cyclical variations in annual real per capital gross domestic product during pregnancy and the first year of life. Exposure to recessions in early life appears to significantly increase cancer mortality risks of older males and females. It also significantly increases other mortality risks especially for older females. The residual life expectancies are up to about 8 and 6 % lower for male and female cancer mortality, respectively, and up to about 5 % lower for female cardiovascular mortality. Our analyses show that cardiovascular and cancer mortality risks are related and that not taking this association into account leads to biased inference.     

Visualizing Count Data Regressions Using Rootograms

The rootogram is a graphical tool associated with the work of J. W. Tukey that was originally used for assessing goodness of fit of univariate distributions. Here, we extend the rootogram to regression models and show that this is particularly useful for diagnosing and treating issues such as overdispersion and/or excess zeros in count data models. We also introduce a weighted version of the rootogram that can be applied out of sample or to (weighted) subsets of the data, for example, in finite mixture models. An empirical illustration revisiting a well-known dataset from ethology is included, for which a negative binomial hurdle model is employed. Supplementary materials providing two further illustrations are available online: the first, using data from public health, employs a two-component finite mixture of negative binomial models; the second, using data from finance, involves underdispersion. An R implementation of our tools is available in the R package countreg. It also contains the data and replication code.     

Sharpening Jensen's Inequality

This article proposes a new sharpened version of Jensen's inequality. The proposed new bound is simple and insightful, is broadly applicable by imposing minimum assumptions, and provides fairly accurate results in spite of its simple form. Applications to the moment generating function, power mean inequalities, and Rao-Blackwell estimation are presented. This presentation can be incorporated in any calculus-based statistical course.     

Job Durations With Worker- and Firm-Specific Effects: MCMC Estimation With Longitudinal Employer–Employee Data

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the variation in job durations into the relative contribution of the worker and the firm. We also allow the unobserved terms to be correlated in a model that is primarily relevant for markets with small firms. For the empirical analysis, we use a Portuguese longitudinal matched employer–employee dataset. The model is estimated with a Bayesian Markov chain Monte Carlo (MCMC) estimation method. The results imply that unobserved firm characteristics explain almost 40% of the systematic variation in log job durations. In addition, we find a positive correlation between unobserved worker and firm characteristics.