Governance Structures,Multidimensional Efficiency and Firm Profitability

Using a panel data set of 361 German corporations for the period 1991–1996 we test the hypothesis that firms with more efficient governance structures have higher profitability. To determine efficiency we compare firms with respect to ownership concentration, the identity of owners, capital structure, investment and firm growth by a multi-input/multi-output Data Envelopment Analysis (DEA). This non-parametric linear programming technique considers both multiple in- and out- puts. Based on the concept of pareto efficiency, it computes an efficiency score where the associated weights of the inputs and outputs are determined endogenously. The DEA efficiency scores are then used as explanatory variables in panel data regressions of profitability. Our main finding is that the efficiency scores indeed contribute significantly to explaining profitability differences between firms, even after controlling for industry effects and unobserved systematic firm effects.     

Local attachments and transnational everyday lives: second‐generation Italians in Switzerland

Many descendants of migrants grow up in the context of lively transnational social relations to their parents' homeland. Among southern Italian migrants in Switzerland, these relations are imbued with the wish to return among the first generation, a dream fostered since the beginning of their migration after the Second World War. Second‐generation Italians have developed different ways of negotiating the transnational livelihoods fostered by their parents on the one hand, and the wish for local attachments on the other. In this article I discuss how the children of Italian migrants have created their own cultural repertoires of Italianità and belonging within Switzerland and with co‐ethnic peers, and how, for some, this sense of belonging evokes the wish for ‘roots migration’, the relocation to the parents' homeland. With the example of two trajectories of local attachment and transnationalism among members of the second generation of the same origin, I question existing work on the second generation that assumes commonalities among them on the grounds of ethnicity and region of origin.     

Feelin' groovy♪: appropriating time in home‐based telework

In this paper we present some findings from an empirical study into teleworking that challenge the received wisdom that principles of efficiency and speed determine the organisation of public and private lives. Instead, we make a case that emerging forms of work organisation such as telework entail opportunities for some individuals to rethink the relationship between life and work and to engage in questions of ‘how to live one's life’. Drawing on our research study, which combined participant observation with interview conversations with 25 teleworkers and their families, we argue that teleworking, the epitome of flexibility and instantaneousness, can, rather than always contributing to the acceleration of life, provide potential for regeneration, re‐evaluation and slowing down.     

Estimation in Discretely Observed Diffusions Killed at a Threshold

Abstract. Parameter estimation in diffusion processes from discrete observations up to a first‐passage time is clearly of practical relevance, but does not seem to have been studied so far. In neuroscience, many models for the membrane potential evolution involve the presence of an upper threshold. Data are modelled as discretely observed diffusions which are killed when the threshold is reached. Statistical inference is often based on a misspecified likelihood ignoring the presence of the threshold causing severe bias, e.g. the bias incurred in the drift parameters of the Ornstein–Uhlenbeck model for biological relevant parameters can be up to 25–100 per cent. We compute or approximate the likelihood function of the killed process. When estimating from a single trajectory, considerable bias may still be present, and the distribution of the estimates can be heavily skewed and with a huge variance. Parametric bootstrap is effective in correcting the bias. Standard asymptotic results do not apply, but consistency and asymptotic normality may be recovered when multiple trajectories are observed, if the mean first‐passage time through the threshold is finite. Numerical examples illustrate the results and an experimental data set of intracellular recordings of the membrane potential of a motoneuron is analysed.     

AFTER-SCHOOL PROGRAM EFFECTS ON BEHAVIOR: RESULTS FROM THE 21ST CENTURY COMMUNITY LEARNING CENTERS PROGRAM NATIONAL EVALUATION

This paper presents evidence on after-school programs' effects on behavior from the national evaluation of the U.S. Department of Education's 21st Century Community Learning Centers after-school program. Findings come from both of the study's components: (1) an elementary school component based on random assignment of 2,308 students in 12 school districts and (2) a middle school component based on a matched comparison design including 4,264 students in 32 districts. Key findings include higher levels of negative behavior for elementary students and some evidence of higher levels of negative behaviors for middle school students . ( JEL I21)     

Stochastic Differential Mixed-Effects Models

Abstract.  Stochastic differential equations have been shown useful in describing random continuous time processes. Biomedical experiments often imply repeated measurements on a series of experimental units and differences between units can be represented by incorporating random effects into the model. When both system noise and random effects are considered, stochastic differential mixed-effects models ensue. This class of models enables the simultaneous representation of randomness in the dynamics of the phenomena being considered and variability between experimental units, thus providing a powerful modelling tool with immediate applications in biomedicine and pharmacokinetic/pharmacodynamic studies. In most cases the likelihood function is not available, and thus maximum likelihood estimation of the unknown parameters is not possible. Here we propose a computationally fast approximated maximum likelihood procedure for the estimation of the non-random parameters and the random effects. The method is evaluated on simulations from some famous diffusion processes and on real data sets.