Using deep learning with satellite images enhances our understanding of human development at a granular spatial and temporal level. Most studies have focused on Africa and on a narrow set of asset-based indicators. This article leverages georeferenced village-level census data from across 40% of the population of India to train deep models that predicts 16 indicators of human well-being from Landsat 7 imagery. Based on the principles of transfer learning, the census-based model is used as a feature extractor to train another model that predicts an even larger set of developmental variables-over 90 variables-included in two rounds of the National Family Health Survey (NFHS). The census-based-feature-extractor model outperforms the current standard in the literature for most of these NFHS variables. Overall, the results show that combining satellite data with Indian Census data unlocks rich information for training deep models that track human development at an unprecedented geographical and temporal resolution.

Time-use diary data convey information about the activities an individual wasengaged in, when and for how long, and the order of these activities throughout the day.The data are usually analyzed by summarizing the time used per activity category. Theaggregates are then used to determine the mean time use of a mean individual on anaverage day. However, this approach discards information about the duration of activities,the order in which they are undertaken, and the time of day each activity is carried out.This paper outlines an alternative approach grounded in the time-geographic theoreticalframework, which takes the duration, order, and timing of activities into consideration andthus yields new knowledge. The two approaches to analyzing diary data are comparedusing a simple empirical example of gender differences in time use for paid work. Thefocus is on the effects of methodological differences rather than on the empirical outcomes.The argument is made that using an approach that takes the sequence of activities intoaccount deepens our understanding of how people organize their daily activities in thecontext of a whole day at an aggregate level.

This paper tests the relationship between financial development, quality of institutions and poverty. To this end, we reviewed the literature and selected indicators of poverty, financial development and quality of institutions. Empirically, we used the three-stage least squares method to examine a sample of 132 countries observed over the 1980-2014 period. First, we proved that financial development does not improve the situation of the poor, while the effect of institution quality on poverty and financial development depends on the choice of indicators. Our robustness analysis pointed to the sensitivity of our results to the different financial development, quality of institutions and poverty indicators.

Objective Associations between subjective status and health are still relatively unexplored. This study aimed at testing whether subjective status is uniquely confounded by psychosocial factors compared to objective status, and what factors that may predict subjective status. Design A cross-sectional analysis of a population-based, random sample of 795 middle-aged men and women from the southeast of Sweden. Questionnaires included subjective status, objective measures of socioeconomic status, life satisfaction, and a battery of psychosocial factors. Associations were controlled for effects of age and sex. Results Both subjective status and occupation were significantly associated with self-rated health also after control for psychosocial factors. Stepwise regression showed that subjective status was significantly influenced by self-rated economy, education, life satisfaction, self-esteem, trust, perceived control, and mastery. Conclusion The association between subjective status and self-rated health does not seem to be uniquely confounded by psychosocial factors. Both resource-based measures and psychological dimensions seem to influence subjective status ratings. Comparative studies are required to study whether predictors of subjective status vary between countries with different socio-political profiles.

These analyses explore the relationship between gender inequality and subjective well-being. The hypothesis was tested as to whether societal gender inequality is related to the size of gender differences in subjective well-being in various societies. Results come from comparative data sets (World Values Survey, involving 57 countries; OASIS project, involving Norway, England, Germany, Spain and Israel). The size of gender differences varied with the extent of societal gender inequality and the cultural attitudes regarding gender equality in different countries. Including individual resources like education and income in the analyses reduced the size of gender and country differences. Gender differences in subjective well-being could therefore be related to gender specific access to goal relevant resources.

This study focuses on the value that employers assign to immigrants labour market experience, from both before and after immigration, using a surveyed representative sample of the Swedish immigrant and native populations. A novel feature of the survey is that it contains a measure of immigrants actual years of labour market experience, including about work before immigration. Previous research has, in contrast, relied on so-called potential measures, risking bias in the analyses. For immigrants, results show that only pre-immigration labour market experience from the Nordic countries has a positive return. Results also show that return to labour market experience after immigration does not depend on whether the individual acquired Sweden-specific human capital before or with the entry into the labour market. Natives and immigrants, as well as immigrants with and without schooling or upbringing in Sweden, have parallel wage trajectories across labour market experience years, with immigrants being at a stable disadvantage. This is interpreted to be caused by immigrants being sorted into jobs with worse opportunities to acquire new human capital compared with natives.

This study compares health status and quality of life assessments of first-year university students with those of their same-age working counterparts. Subjects and materials for each group were gathered in 1999 from two cross-sectional data sets from the Swedish region of Östergötland, covering males and females aged 20-34 years. Subjects' perceived quality of life (QoL) and self-rated health (SRH) were assessed on a 10-point scale (Ladder scale) and a five-point scale, respectively. Gender-based comparison revealed that, for both males and females, first-year university students' average perceived QoL was lower than that of their working counterparts (p < 0.0001 in all instances). A higher proportion of students than expected rated their health as "average" or as "low" (p < 0.0001). Perceived QoL was significantly correlated with SRH in both groups. Differences in perceived QoL and SRH exist between students and their full-time working peers, and the determinants of these differences deserves greater attention. Knowledge of the determinants of SRH and perceived QoL among university students might then be translated into sound and effective public-health practice and intervention programs.