Professors,Ideology and Housework

This paper presents, for the first time, multivariate analyses of Canadian national data and tests the relationship between class-based egalitarianism and housework for married and cohabiting male and female university professors in 2000. Consistent with evidence in the general population, gender accounts for more variation in housework than a host of other predictors (i.e., class- and gender-based ideology, institutional contexts and resources, available time, presence of children, age, minority racial status, and religiosity). Nevertheless, these forces play important roles in increasing or decreasing domestic labor contributions of both male and female academics. Among these, professors who possess class-based egalitarian views do more housework, and egalitarianism increases domestic labor contributions of males and decreases that of females.     

Do Work Demands and Resources Predict Work-to-Family Conflict and Facilitation? A Study of Iranian Male Employees

This study examined the effects of some work demands-resources on two dimensions of work-to-family interface among Iranian employees. The results of canonical correlation and multiple-regression showed that among work resources (i.e., social support and autonomy), social support was associated negatively with work-to-family conflict and autonomy was associated positively with work-to-family facilitation. Also, among work demands (i.e., job demands and working hours), job demands were associated with both work-to-family conflict and work-to-family facilitation. Unlike previous studies, working hours shows a positive association with work-to-family facilitation, which may be explained by the specific cultural context in Iran. The findings of the study will be of importance to employees and organizations.

Understanding the demographic implications of climate change: estimates of localized population predictions under future scenarios of sea-level rise

Significant advances have been made to understand the interrelationship between humans and the environment in recent years, yet research has not produced useful localized estimates that link population forecasts to environmental change. Coarse, static population estimates that have little information on projected growth or spatial variability mask substantial impacts of environmental change on especially vulnerable populations. We estimate that 20 million people in the United States will be affected by sea-level rise by 2030 in selected regions that represent a range of sociodemographic characteristics and corresponding risks of vulnerability. Our results show that the impact of sea-level rise extends beyond the directly impacted counties due to migration networks that link inland and coastal areas and their populations. Substantial rates of population growth and migration are serious considerations for developing mitigation, adaptation, and planning strategies, and for future research on the social, demographic, and political dimensions of climate change.     

Are Educational Mismatches Responsible for the ‘Inequality Increasing Effect’ of Education?

This paper asks whether educational mismatches can account for the positive association between education and wage inequality found in the data. We use two different data sources, the European Community Household Panel and the Portuguese Labour Force Survey, and consider several types of mismatch, including overqualification, underqualification and skills mismatch. We test our hypothesis using two different measurement methods, the ‘statistical’ and the ‘subjective’ approach. The results are robust to the different choices and unambiguously show that the positive effect of education on wage inequality is not due to the prevalence of educational mismatches in the labour market.     

Simple methods for evaluating and comparing binary experiments

We consider a confidence parametrization of binary information sources in terms of appropriate likelihood ratios. This parametrization is used for Bayesian belief updates and for the equivalent comparison of binary experiments. In contrast to the standard parametrization of a binary information source in terms of its specificity and its sensitivity, one of the two confidence parameters is sufficient for a Bayesian belief update conditional on a signal realization. We introduce a confidence-augmented receiver operating characteristic for comparisons of binary experiments for a class of “balanced” decision problems, relative to which the confidence order offers a higher resolution than Blackwell’s informativeness order.

Where observation is concerned, Chance favors only the prepared mind. —Louis Pasteur (1822–1895).

     

Models and estimation for systems with recurrent events and usage processes

This paper considers settings where populations of units may experience recurrent events, termed failures for convenience, and where the units are subject to varying levels of usage. We provide joint models for the recurrent events and usage processes, which facilitate analysis of their relationship as well as prediction of failures. Data on usage are often incomplete and we show how to implement maximum likelihood estimation in such cases. Random effects models with linear usage processes and gamma usage processes are considered in some detail. Data on automobile warranty claims are used to illustrate the proposed models and estimation methodology.     

Warteschlangen-Modelle in der Produktionsplanung – Möglichkeiten und Grenzen

Production Management often tried to apply queueing models to describe the flow of products and parts. These approaches usually apply very simple queueing models. Due to mathematical problems implied by general waiting line models, an adaptation to real life problems fails often. In this paper, some simple models discussed in production management are presented and it is shown why they failed to be generalized. Afterwards, we try to find a way how to model the simple case of flow shop production using generalized queueing models: First decomposition of serial waiting lines and approximation of the system by a sequence of independent stations. Afterwards the approach of recent literature to consider again the entire system simultaneously is sketched, and it is argued that these approaches are restricted as well to small problems     

Selective Out-Migration from Florida

I test if selective out-migration of unhealthy seniors explains why disability rates are so much lower for Florida, as compared to the national average. This particular area of research is timely given the significant demographic changes relating to aging. Moreover, this study contributes to the body of literature examining migration with respect to disability and widowhood. Using State Federal Information Processing Standard (FIPS) and Public Use Microdata Areas (PUMA), I create national maps showing disability rates for the following age-groups: 50–59, 60–69, and 70+. After creating maps in ARCGIS and conducting univariate and clustering analysis on mobility disability and personal care limitation, I employ multinomial logit (MNL) analysis to test if individuals with disability are more likely to out-migrate from Florida. The regression analyses lend support to the relaxed Litwak and Longino (The Gerontologist, 27(3): 266–272, 1987) second-move hypothesis, which claims individuals with progressively worse health are more likely to undertake another move to be closer to family and friends. I state “relaxed” because the data does not allow one to determine the reason for migration—only that migration occurred during the past year. This research informs policy-makers to recognize that elderly in better health may migrate to places such as Arizona and Florida due to amenity-seeking behavior, but unhealthy elderly are more likely to leave these states due to assistance-seeking behavior. This out-migration can place excess demand on health services for the incoming regions, which requires state and local government to ensure resources are in place. Also noteworthy, my results are less likely to be flawed by erroneous age and sex data in the public use microdata samples (IPUMS) since I stack the 2006 and 2007 American Community Survey (ACS). A recent working studies by Alexander et al. (Inaccurate age and sex data in the Census PUMS files: Evidence and implications. Munich: CESifo, 2010) shows inaccuracies in the IPUMS for the 1 and 5% 2000 Census, the 2003–2006 ACS, the 2005–2007 3-year ACS, and the 2004–2009 current population survey (CPS) files.