Does Migration Make You Happy?:A Longitudinal Study of Internal Migration and Subjective Well-Being

The majority of modelling studies on consequences of internal migration focus almost exclusively on the labour market outcomes and the material well-being of migrants. We investigate whether individuals who migrate within the UK become happier after the move than they were before it and whether the effect is permanent or transient. Using life satisfaction responses from 12 waves of the British Household Panel Survey (BHPS) and employing a fixed-effects model, we derive a temporal pattern of migrants’ subjective wellbeing (SWB) around the time of the migration event. Our findings make an original contribution by revealing for the first time that, on average, migration is preceded by a period when individuals experience a significant decline in happiness. The boost that is received through migration appears to bring people back to their initial level of happiness. As opposed to labour market outcomes of migration, SWB outcomes do not differ significantly between men and women. Perhaps surprisingly, long-distance migrants are at least as happy as short-distance migrants despite the higher social costs that are involved

General and specific utility measures for synthetic data

Data holders can produce synthetic versions of datasets when concerns about potential disclosure restrict the availability of the original records. This paper is concerned with methods to judge whether such synthetic data have a distribution that is comparable to that of the original data, what we will term general utility. We consider how general utility compares with specific utility, the similarity of results of analyses from the synthetic data and the original data. We adapt a previous general measure of data utility, the propensity score mean-squared-error (pMSE), to the specific case of synthetic data and derive its distribution for the case when the correct synthesis model is used to create the synthetic data. Our asymptotic results are confirmed by a simulation study. We also consider two specific utility measures, confidence interval overlap and standardized difference in summary statistics, which we compare with the general utility results. We present two examples examining this comparison of general and specific utility to real data syntheses and make recommendations for their use for evaluating synthetic data

Difficult Life Events, Selective Migration and Spatial Inequalities in Mental Health in the UK

Objective: Research has indicated that people moving towards neighbourhoods with disadvantaged socio-economic status have poor health, in particular mental health, but the reasons for this are unclear. This study aims to assess why people moving towards more socio-economically deprived areas have poor mental health. It focuses upon the role of difficult life events that may both trigger moves and damage mental health. This study investigates how mental health and socio-spatial patterns of mobility vary between people moving following difficult life events and for other reasons.<p></p> Methods: Longitudinal analysis of British Household Panel Survey data describing adults’ moves between annual survey waves, pooled over ten years, 1996-2006 (N=122,892 observations). Respondents were defined as ‘difficult life event movers’ if they had experienced relationship breakdown, housing eviction/repossession, or job loss between waves. Respondents were categorised as moving to more or less deprived quintiles using their Census Area Statistic residential ward Carstairs score. Mental health was indicated by self-reported mental health problems. Binary logistic regression models of weighted data were adjusted for age, sex, education and social class.<p></p> Results: The migration rate over one year was 8.5%; 14.1% of movers had experienced a difficult life event during this time period. Adjusted regression model odds of mental health problems among difficult life event movers were 1.67 (95% CI 1.35-2.07) relative to other movers. Odds of difficult life events movers, compared to other movers, moving to a less deprived area, relative to an area with a similar level of deprivation, were 0.70 (95% CI 0.58-0.84). Odds of mental health problems among difficult life event movers relocating to more deprived areas were highly elevated at 2.40 (95% CI 1.63-3.53), relative to stayers.<p></p> Conclusion: Difficult life events may influence health selective patterns of migration and socio-spatial trajectories, reducing moves to less deprived neighbourhoods among people with mental illness

The price of mobility

This paper addresses the question concerning the price of geographic mobility in various labour market and migration scenarios. Pivotal points are expected mobility premiums which are sufficient to tip the scales in favour of moving to a geographically distinct location. These premiums are first derived within a theoretical model, accounting not only for location-specific amenity levels or labour market conditions, but also for heterogeneous personality traits and preferences. Derived hypotheses demonstrate that—in presence of heterogeneous psychic costs or adjustment capabilities—expected mobility premiums can remain distinctly positive even in an unemployment scenario. Furthermore, adjustment capabilities are to a large extent related to earlier mobility experiences, implying that labour mobility is partially learnable