Work hours,social value of leisure and globalisation

We examine how openness interacts with the coordination of consumption–leisure decisions in determining the equilibrium working hours and wage rate when there are leisure externalities (e.g., due to social interactions). The latter are modelled by allowing a worker's marginal utility of leisure to be increasing in the leisure time taken by other workers. Coordination takes the form of internalising the leisure externality and other relevant constraints (e.g., labour demand). The extent of openness is measured by the degree of capital mobility. We find that: coordination lowers equilibrium work hours and raises the wage rate; there is a U-shaped (inverse-U-shaped) relationship between work hours (wages) and the degree of coordination; coordination is welfare improving; and, the gap between the coordinated and uncoordinated work hours (and the corresponding wage rates) is affected by the extent and nature of openness.     

Forecast mean squared error reductionin the VAR(1) process

When VAR models are used to predict future outcomes, the forecast error can be substantial. Through imposition of restrictions on the off-diagonal elements of the parameter matrix, however, the information in the process may be condensed to the marginal processes. In particular, if the cross-autocorrelations in the system are small and only a small sample is available, then such a restriction may reduce the forecast mean squared error considerably.

In this paper, we propose three different techniques to decide whether to use the restricted or unrestricted model, i.e. the full VAR(1) model or only marginal AR(1) models. In a Monte Carlo simulation study, all three proposed tests have been found to behave quite differently depending on the parameter setting. One of the proposed tests stands out, however, as the preferred one and is shown to outperform other estimators for a wide range of parameter settings.     

Childlessness and Psychological Well-Being in Midlife and Old Age: An Examination of Parental Status Effects Across a Range of Outcomes

The study explores and distinguishes links between parental status (childless persons, parents with residential children, and empty nest parents) and a range of psychological well-being outcomes in midlife and old age. Data are from the first wave of the Norwegian Life Course, Ageing and Generation (NorLAG) study (n = 5,189). We separate outcomes into cognitive (life satisfaction and self-esteem) and affective (positive and negative affect, depression, loneliness) components. Parental status has a net effect on cognitive well-being among women, as childless women report significantly lower life satisfaction and self-esteem than both mothers with residential children and empty nest mothers. However, motherhood is inconsequential for affective well-being. Among men, parental status is unrelated to any of the well-being aspects. Parental status effects are not modified by age, marital status, and education. The results demonstrate the importance of investigating the effect of parental status and other objective circumstances on a range of psychological well-being outcomes. Furthermore, the results reviewed and presented indicate somewhat more positive effects of parenthood in the Nordic countries than in the US, highlighting the role of social policies in shaping the impact of parental status on well-being.     

Children and Careers: How Family Size Affects Parents’ Labor Market Outcomes in the Long Run

We estimate the effect of family size on various measures of labor market outcomes over the whole career until retirement, using instrumental variables estimation in data from Norwegian administrative registers. Parents’ number of children is instrumented with the sex mix of their first two children. We find that having additional children causes sizable reductions in labor supply for women, which fade as children mature and even turn positive for women without a college degree. Among women with a college degree, there is evidence of persistent and even increasing career penalties of family size. Having additional children reduces these women’s probability of being employed by higher-paying firms, their earnings rank within the employing firm, and their probability of being the top earner at the workplace. Some of the career effects persist long after labor supply is restored. We find no effect of family size on any of men’s labor market outcomes in either the short or long run.     

Living Near to Attractive Nature? A Well-Being Indicator for Ranking Dutch,Danish, and German Functional Urban Areas

While nature is widely acknowledged to contribute to people’s well-being, nature based well-being indicators at city-level appear to be underprovided. This study aims at filling this gap by introducing a novel indicator based on the proximity of city-residents to nature that is of high-amenity. High-amenity nature is operationalized by combining unique systematic data on people’s perceptions of what are the locations of attractive natural areas with data on natural land cover. The proposed indicator departs from the usual assumption of equal well-being from any nature, as it approximates the ‘actual’ subjective quality of nature near people’s homes in a spatially explicit way. Such indicator is used to rank 148 ‘cities’ in the Netherlands, Denmark, and Germany. International comparability of the indicator is enhanced by the use of a definition of cities as functional urban areas (FUAs), which are consistently identified across countries. Results demonstrate that the average ‘nearness’ of FUA populations to high amenity nature varies widely across the observed FUAs. A key finding, that complements insights from existing city-level indicators, is that while populations of FUAs with higher population densities may live relatively far from nature in general, they also live, on average, closer to high-amenity nature than inhabitants of lower density FUAs. Our results may stimulate policy-debates on how to combine urban agglomeration with access to natural amenities in order to account for people’s wellbeing.     

Adaptive multiple importance sampling for Gaussian processes

In applications of Gaussian processes (GPs) where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. This is normally done by means of standard Markov chain Monte Carlo (MCMC) algorithms, which require repeated expensive calculations involving the marginal likelihood. Motivated by the desire to avoid the inefficiencies of MCMC algorithms rejecting a considerable amount of expensive proposals, this paper develops an alternative inference framework based on adaptive multiple importance sampling (AMIS). In particular, this paper studies the application of AMIS for GPs in the case of a Gaussian likelihood, and proposes a novel pseudo-marginal-based AMIS algorithm for non-Gaussian likelihoods, where the marginal likelihood is unbiasedly estimated. The results suggest that the proposed framework outperforms MCMC-based inference of covariance parameters in a wide range of scenarios.     

Palm Distributions for Log Gaussian Cox Processes

This paper establishes a remarkable result regarding Palm distributions for a log Gaussian Cox process: the reduced Palm distribution for a log Gaussian Cox process is itself a log Gaussian Cox process that only differs from the original log Gaussian Cox process in the intensity function. This new result is used to study functional summaries for log Gaussian Cox processes.