Mis-Specification and Frequency Dependence in a New Keynesian Phillips Curve

Phillips Curve, spectral regression, time series analysis

Frequency Dependence in Regression Model Coefficients: An Alternative Approach for Modeling Nonlinear Dynamic Relationships in Time Series

Phillips Curve, spectral regression, time series analysis

Mis-Specification in Phillips Curve Regressions: Quantifying Frequency Dependence in This Relationship While Allowing for Feedback.

Phillips Curve, spectral regression, time series analysis.

Time spent on work-related activities, social activities and time pressure as intermediary determinants of health disparities among elderly women and men in 5 European countries: a structural equation model

Background Psychosocial factors shape the health of older adults through complex inter-relating pathways. Besides socioeconomic factors, time use activities may explain gender inequality in self-reported health. This study investigated the role of work-related and social time use activities as determinants of health in old age. Specifically, we analysed whether the impact of stress in terms of time pressure on health mediated the relationship between work-related time use activities (i.e. housework and paid work) on self-reported health. Methods We applied structural equation models and a maximum-likelihood function to estimate the direct and indirect effects of psychosocial factors on health using pooled data from the Multinational Time Use Study on 11,168 men and 14,295 women aged 65+ from Italy, Spain, UK, France and the Netherlands. Results The fit indices for the conceptual model indicated an acceptable fit for both men and women. The results showed that socioeconomic status (SES), demographic factors, stress and work-related time use activities after retirement had a significant direct influence on self-reported health among the elderly, but the magnitude of the effects varied by gender. Social activities had a positive impact on self-reported health but had no significant impact on stress among older men and women. The indirect standardized effects of work-related activities on self-reported health was statistically significant for housework (β = − 0.006; P  0.05 among women), which implied that the paths from paid work and housework on self-reported health via stress (mediator) was very weak because their indirect effects were close to zero. Conclusions Our findings suggest that although stress in terms of time pressure has a direct negative effect on health, it does not indirectly influence the positive effects of work-related time use activities on self-reported health among elderly men and women. The results support the time availability hypothesis that the elderly may not have the same time pressure as younger adults after retirement

Genetic and environmental influences on eating patterns of twins aged ≥50 y

BACKGROUND: Clinicians and researchers could benefit from a greater understanding of the role of genetic and environmental factors in human eating behavior. OBJECTIVE: Our aim was to estimate the relative influence of genetic and environmental factors on habitual eating patterns in middle-aged and elderly men and women. DESIGN: Male and female twins (n = 4640) aged >/=50 y completed a mailed version of the National Cancer Institute food-frequency questionnaire. Factor analysis was performed to identify eating patterns among respondents. Estimates of genetic, common environmental (shared by family members), and specific environmental (unique to an individual) influences were obtained for food use, serving size, and consumption frequency by comparing monozygotic and dizygotic twin-pair groups with structural equation analysis. RESULTS: Two independent eating patterns were identified: the first consisted of items high in fat, salt, and sugar, and the second reflected healthful eating habits. Although the influence of environmental factors was larger, between 15% and 38% of the total variation in pattern 1 and between 33% and 40% in pattern 2 were explained by genetic influences. Models accounting for sex differences in genetic and environmental estimates fit the data significantly better for food use and serving size of foods in eating pattern 1 and for food use in eating pattern 2. CONCLUSION: Although 60-85% of the variability in eating patterns was associated with environmental factors, genetic influences were also apparent and there was some evidence of sex specificity. These findings may be important in crafting dietary interventions and predicting adherence to these interventions