Zukunftsangst! Fear of (and hope for) the huture and its impact on life satisfaction

The thoughts that an individual has about the future contribute substantially to their life satisfaction in a positive or negative direction. This is a result found via five different methods, some of which control for personality and disposition and the potential endogeneity of thoughts and life satisfaction. The reduction in life satisfaction experienced by individuals who report being pessimistic is greater than that for well-known objective statuses like unemployment. Including individuals' thoughts about the future substantially increases the explanatory power of standard life satisfaction models. Life satisfaction is made up of objective and subjective factors and methods exist to account for their potential endogeneity to enhance our understanding of well-being. This investigation is an example of such an analysis combining a subjective factor, thoughts about the future (treated as endogenous), with more standard objective factors to aid understanding regarding well-being

What the leaving child does matters

This study is an empirical investigation of the empty nest syndrome, commonly understood as a situation where there are feelings of loss or loneliness for mothers and/or fathers following the departure of the last child from the family home. This investigation makes use of rich, longitudinal, nationally representative German data to assess whether there is evidence for such a syndrome. Furthermore, the analysis considers the role of two key economic variables: consumption and leisure via the standard economic concept of utility maximisation. The analysis highlights a conflict between what economic theory predicts - more disposable income and a gain of leisure time - and the psychological (and cultural) notion of the lonely, sad empty nester. This conflict is an empirical question and here it is resolved via an assessment of the change in life satisfaction that is reported when parents become empty nesters. Importantly, this investigation also tracks what the last child leaving the household goes on to do: The found reduced life satisfaction seems to be wholly moderated if the last child leaves the nest for the purposes of education, but not if for purposes of employment

temporary employment and the midlife nadir in human well-being

Temporary employees rank lower than permanent employees on various measures of mental and physical health, including well-being. In parallel, much research has shown that the relationship between age and well-being traces an approximate U-shape, with a nadir in midlife. Temporary employment may well have different associations with well-being across the lifespan, likely harming people in midlife more than at the start of their working lives. Using over twenty years of the German Socio-economic panel (SOEP), this investigation considers the relationship between temporary employment, age and well-being. In doing so, it both sheds new light on the relationship between temporary employment and well-being, and explores a reason for the oft-found U-shaped relationship between age and well-being. The results show that temporary employment deepens the U-shape in midlife, and that this result holds when many socioeconomic factors as well as the industry, region, cohort, personality, employment security and job worries are taken into account. Furthermore, the investigation considers transitions between permanent and temporary employment and uses these to assess causation and selection

Heaven knows I’m miserable now: overeducation and reduced life satisfaction

This study is an investigation into relative overeducation and life satisfaction using British longitudinal data. The focus is on young people rather than the whole of the life cycle, an arguably more homogenous group. Such a focus means that the overeducation variable does not simply capture the increased participation in Higher Education of the young. The hypothesis is that there is a negative relationship between being overeducated and life satisfaction. Overeducation is measured using the realised matches approach, a statistical measurement comparing an individual’s years of schooling with the average for one of two employment based reference groups. Using dynamic panel analysis, to account for the presence of serial correlation, such an association is found: the relatively overeducated seem to be relatively less happy

Overeducation, gender, income and life satisfaction. Panel evidence from Korea

One reason often put forward for South Korea’s rapid economic growth has been the rising level of educational attainment of its workforce. Correspondingly, the proportion of Koreans who complete tertiary education has also rapidly increased (and is also considerably higher than the OECD average). Such increases raise the possibility of overeducation if the amount of jobs which require such education do not increase at a similar pace. Among the consequences of overeducation are reduced life satisfaction and underutilised human capital. Given that Korean females are better educated than males, and they also face more discrimination in the labour market, the consequences of overeducation are likely to differ by gender. Using Korean panel data and both a subjective and objective measure of overeducation, the results are consistent with females having lower aspirations despite their high levels of education, and indicate that a more female friendly labour market could address the country’s currently underutilised human capital, for the benefit of the females themselves, as well as males, and the Korean economy

Issues in the Estimation of Dynamic Happiness Models: A Comment on "Does Childhood Predict Adult Life Satisfaction?"

This paper offers methodological comments on a recent (November 2014) Economic Journal article. The comments consider its use of a dynamic model – the inclusion of a lagged dependent variable – and its approach to estimation. By way of critique, the authors highlight general issues regarding dynamic panel analysis that are still less fully appreciated in the economics of happiness literature than elsewhere in economics and other quantitative social sciences. This discussion of methodological issues arising from dynamic estimation may be of practical assistance to researchers new to the field and/or to dynamic modelling

Age and Happiness

This entry summarises quantitative research endeavours regarding the relationship between age and happiness. Firstly, the dominant finding in the literature is discussed: that, on average, happiness starts off high in early adulthood and declines to a midlife low and then, following the midlife low, average happiness increases again until retirement. As the discussion highlights, this midlife low finding has been found around the world, and at different time periods, with different datasets and methods. This entry also shows how some individuals suffer more at midlife than others, and discusses why this might be the case. While the dominant finding is largely (though not wholly) accepted, reasons for its existence and how it might be mitigated are less clear and remain to some extent a puzzle. The recommendations aim for more understanding here and regarding other trends at different parts of the lifecycle

A Note on Modelling Dynamics in Happiness Estimations

This short note discusses two alternative ways to model dynamics in happiness regressions. A explained, this may be important when standard fixed effects estimates have serial correlation in the residuals, but is also potentially useful when serial correlation is not a problem for providing new insights in the happiness of economics area. The note discusses modelling dynamics two ways the note discusses are via a lagged dependent variable, and via an AR(1) process. The usefulness and statistical appropriateness of each is discussed with reference to happiness. Finally, a flow chart is provided summarising key decisions regarding the choice regarding, and potential necessity of, modelling dynamics

A Note on Modelling Dynamics in Happiness Estimations

This short note discusses two alternative ways to model dynamics in happiness regressions. As explained, this may be important when standard fixed effects estimates have serial correlation in the residuals, but is also potentially useful when serial correlation is not a problem for investigations within the happiness of economics area. The two ways the note discusses modelling dynamics are via a lagged dependent variable, and via an AR(1) process. The usefulness and statistical appropriateness of each is discussed with reference to happiness. Finally, a flow chart is provided summarising key decisions regarding the choice about, and potential necessity of, modelling dynamics

A Note on Modelling Dynamics in Happiness Estimations

This short note discusses two alternative ways to model dynamics in happiness regressions. As explained, this may be important when standard fixed effects estimates have serial correlation in the residuals, but is also potentially useful when serial correlation is not a problem for investigations within the happiness of economics area. The two ways the note discusses modelling dynamics are via a lagged dependent variable, and via an AR(1) process. The usefulness and statistical appropriateness of each is discussed with reference to happiness. Finally, a flow chart is provided summarising key decisions regarding the choice about, and potential necessity of, modelling dynamics