A note on interdependent happiness

Based on two models of interdependent utilities [Becker, G., 1974. A theory of social interaction, Journal of Political Economy 82, 1064–1093; Fehr, E., Schmidt, K., 1999. A theory of fairness, competition, and cooperation, Quarterly Journal of Economics 114, 817–868] we derive a functional relationship between average happiness and the standard deviation of happiness within a country. This hypothesis is supported by an empirical investigation of 71 countries which shows that the average happiness in these countries depends only on income and on the standard deviation of happiness σ. The latter may be partly based on influences beyond income, for which no data are available. Income has the expected positive influence and σ has the expected negative influence, i.e. large differences in “autonomous” happiness have a dampening influence on “effective” happiness which also takes into account the happiness of others.     

Coaching für Habilitand/innen am Beispiel der LMU München

This practice report describes coachings for junior faculty members at LMU Munich. First, we describe the challenges junior faculty members are faced with at German universities and the HR development undertaken at LMU to help junior faculty cope with these challenges. In particular, we elaborate on coachings, i. e. we describe the process and topics most frequently mentioned therein. These include the sandwich position junior faculty members find themselves in, the oftentimes informal nature of their leadership position, and the requirement to react to conflicts. Finally, we present the various ways of responding to these challenges developed within the coaching process.     

Evaluation of two school-based HIV prevention interventions in the border city of Tijuana, Mexico

This research project examined the individual and combined effectiveness of an HIV prevention workshop and a free condom distribution program in four high schools in Tijuana, Mexico. Adolescents (N = 320) completed baseline measures on sexual practices and theoretical correlates and participated in a two-part study. In Study 1, students were randomly assigned to an HIV prevention workshop or a control condition, with a 3-month follow-up assessment. Results indicate three significant workshop benefits regarding HIV transmission by altering sexual initiation, access to condoms, and traditional beliefs regarding condoms. In Study 2, we set up a condom distribution program at two of the participating schools, and students completed a 6-month follow-up assessment. Results indicate that exposure to the workshop followed by access to the condom distribution program yielded two beneficial results for reducing HIV transmission: moderating sexual initiation and increasing condom acquisition. Access to the condom distribution program alone had no effects on behavioral and psychosocial correlates of HIV transmission. We discuss implications of these results.     

Life-Coaching als Bestandteil von Führungskräfte-Coaching

Executive coaching represents a significant tool of human resources development and is applied to strengthen leadership and management skills. Regardless of specific professional issues on and around the job itself, experience reveals that personal issues should also represent an integral constituent of executive coaching. Indeed, managers do not only encounter professional challenges, but are challenged in their whole personality. Hence, executive coaching expands to life coaching. Based on a specific case study regarding work life balance the following article illustrates how life coaching may successfully be applied in a systematic manner and how the aspects function and human being are mutually dependent.     

CMHS/CSAT Collaborative Demonstration Program for Homeless Individuals

The Collaborative Demonstration Program for Homeless Individuals is providing an opportunity for several community agencies in the United States to explore innovative intervention and treatment strategies to address the needs of homeless people with co-occurring (mental illness and substance abuse) disorders. This cooperative agreement, funded jointly by the Center for Mental Health Services (CMHS) and the Center for Substance Abuse Treatment (CSAT), is a $3 million project supporting programs in various community agencies to develop, document, and evaluate programs for persons who are homeless with co-occurring disorders to be used as models in other communities. The program models include: Assertive Community Treatment, Psychosocial Rehabilitation, Therapeutic Community, and an integrated treatment model. The first phase of the two-phase project funded 16 programs in the U.S. to develop manuals within their primary treatment modalities for homeless people with co-occurring disorders. For Phase II of the project, six of the 16 model programs were competitively selected to demonstrate program impact through formal program evaluation efforts. The data derived from the various projects will be compiled into a compendium of information for state agencies and community service providers throughout the U.S.     

Choice of the ridge factor from the correlation matrix determinant

Ridge regression is the alternative method to ordinary least squares, which is mostly applied when a multiple linear regression model presents a worrying degree of collinearity. A relevant topic in ridge regression is the selection of the ridge parameter, and different proposals have been presented in the scientific literature. Since the ridge estimator is biased, its estimation is normally based on the calculation of the mean square error (MSE) without considering (to the best of our knowledge) whether the proposed value for the ridge parameter really mitigates the collinearity. With this goal and different simulations, this paper proposes to estimate the ridge parameter from the determinant of the matrix of correlation of the data, which verifies that the variance inflation factor (VIF) is lower than the traditionally established threshold. The possible relation between the VIF and the determinant of the matrix of correlation is also analysed. Finally, the contribution is illustrated with three real examples.     

Multivariate regression analysis of panel data with binary outcomes applied to unemployment data

Summary  In panel studies binary outcome measures together with time stationary and time varying explanatory variables are collected over time on the same individual. Therefore, a regression analysis for this type of data must allow for the correlation among the outcomes of an individual. The multivariate probit model of Ashford and Sowden (1970) was the first regression model for multivariate binary responses. However, a likelihood analysis of the multivariate probit model with general correlation structure for higher dimensions is intractable due to the maximization over high dimensional integrals thus severely restricting ist applicability so far. Czado (1996) developed a Markov Chain Monte Carlo (MCMC) algorithm to overcome this difficulty. In this paper we present an application of this algorithm to unemployment data from the Panel Study of Income Dynamics involving 11 waves of the panel study. In addition we adapt Bayesian model checking techniques based on the posterior predictive distribution (see for example Gelman et al. (1996)) for the multivariate probit model. These help to identify mean and correlation specification which fit the data well. C. Czado was supported by research grant OGP0089858 of the Natural Sciences and Engineering Research Council of Canada.     

Posterior consistency for the spectral density of non-Gaussian stationary time series

Various nonparametric approaches for Bayesian spectral density estimation of stationary time series have been suggested in the literature, mostly based on the Whittle likelihood approximation. A generalization of this approximation involving a nonparametric correction of a parametric likelihood has been proposed in the literature with a proof of posterior consistency for spectral density estimation in combination with the Bernstein–Dirichlet process prior for Gaussian time series. In this article, we will extend the posterior consistency result to non-Gaussian time series by employing a general consistency theorem for dependent data and misspecified models. As a special case, posterior consistency for the spectral density under the Whittle likelihood is also extended to non-Gaussian time series. Small sample properties of this approach are illustrated with several examples of non-Gaussian time series.