Tall claims? Sense and nonsense about the importance of height of US presidents

According to both the scientific literature and popular media, all one needs to win a US presidential election is to be taller than one's opponent. Yet, such claims are often based on an arbitrary selection of elections, and inadequate statistical analysis. Using data on all presidential elections, we show that height is indeed an important factor in the US presidential elections. Candidates that were taller than their opponents received more popular votes, although they were not significantly more likely to win the actual election. Taller presidents were also more likely to be reelected. In addition, presidents were, on average, much taller than men from the same birth cohort. The advantage of taller candidates is potentially explained by perceptions associated with height: taller presidents are rated by experts as ‘greater’, and having more leadership and communication skills. We conclude that height is an important characteristic in choosing and evaluating political leaders.     

A statistic to check model adequacy in time series

A simple statistic is suggested to examine if the assumptions on variances in a fitted time series model is valid or not. The properties of the statistic are discussed and examples are considered.     

Bayesian regression under combinations of constraints

A Bayesian method for regression under several types of constraints is proposed. The constraints can be range-restricted and include shape restrictions, constraints on the value of the regression function, smoothness conditions and combinations of these types of constraints. The support of the prior distribution is included in the set of piecewise linear functions. It is shown that the proposed prior can be arbitrarily close to the distribution induced by the addition of a polynomial plus an (m−1)-fold integrated Brownian motion. Hence, despite its piecewise linearity, the regression function behaves (approximately) like an m−1 times continuously differentiable random function. Furthermore, thanks to the piecewise linear property, many combinations of constraints can easily be considered. The regression function is estimated by the posterior mode computed by a simulated annealing algorithm. The constraints on the shape and the values of the regression function are taken into account thanks to the proposal distribution, while the smoothness condition is handled by the acceptation step. Simulations from the posterior distribution are obtained by a Gibbs sampling algorithm.     

Determinanten des Wiedereinstiegs von Müttern in den Arbeitsmarkt in Vollzeit oder Teilzeit

This paper deals with the question which determinants influence the re-entry of mothers on the labor market after the first childbirth. Contrary to existing studies it is possible to distinguish empirically between full time and part time employment after re-entry by employing the newly available BASiD-data. Theoretical arguments indicate that women decide deliberately for a part or full time job due to labor market restriction, their household und family situation and institutional rules which vary in time. Empirically this paper focuses on mothers in West Germany because the data includes a long observation period before reunification. Based on event history models we can show that the determinants for full and part time re-entries differ substantially. Hence it can be reasoned that full and part time jobs for re-entry after birth are not simple substitutes for the women.     

STIRring the grid: engaging energy systems design and planning in the context of urban sociotechnical imaginaries

Since the first electrification systems were established in the United States between 1910 and 1930, energy systems governance at the municipal level has included competing visions for how engineering design and energy policy-making should foster particular social outcomes. Using Phoenix as a representative metropolitan area, and the cases of distributed generation and in-home power management devices as examples, this paper explores how the norms and values embedded in energy systems design and planning shape how residents experience change in the energy grid. Through these case studies, the authors argue that such “sociotechnical imaginaries” – collectively formed visions of social life related to science and technology development – are a crucial, yet overlooked, pathway for social science to engage in fostering socially reflexive mechanisms in energy development. To conclude, the authors outline a research program for applying the established methodology of socio-technical integration research (STIR) in order to develop socially reflexive capacities in municipal energy producing, regulating, and planning institutions. Such a program has the ability to produce a deeper intellectual understanding of how energy development occurs, and in doing so generate new pathways for fostering cultural and material changes in the structure of contemporary energy systems.     

A Conceptual Base for ‘Second-Generation’ Programs in Gerontological Social Work

A framework developed by Vance promises better understanding of the mechanisms by which various kinds of severely deprived environments produce high rates of cognitive, emotional, and personality disabilities. Effort is focused on assessing how Vance's concepts may aid in reconceptualizing and reorganizing much Human Behavior and Social Environment content to facilitate the integration of seemingly unrelated findings and conflicting theories on the relationship between disability, poverty, and alienation. The potential for enhancing teaching and development of interventive strategies is explored.     

Missing observations in time series

A method based on forecasting techniques is proposed to estimate missing observations in time series. Using mean squares, this method is compared to the minimum mean square estimate.     

Forecasting contemporal time series aggregates

Forecast of a contemporal aggregate of several time series can be obtained from ‘1’ an aggregate series, ‘2’ individual component processes, or ‘3’ a joint multiple forecasting model. Through general Hilbert space theory and some illustrative examples, this paper establishes the relative efficiencies among the three methods     

Use of Biological Markers in Risk Assessment1

Measurements of intermediate end points in the carcinogenic process may reduce uncertainty in human risk assessment from bioassay data, by identifying sources of interspecies variation and dose nonlinearity. This paper describes desirable properties of such markers: persistence, predictive power, temporal relevance, and consistency across dose rate and species. We illustrate these properties by evaluating markers for squamous cell nasal carcinoma in rodents exposed to formaldehyde. We also discuss design issues for bioassays that evaluate markers and tumors simultaneously at necropsy.