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Dynamics of job satisfaction around internal migrations: a panel analysis of young people in Britain and Australia

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Abstract

There is ample evidence that internal migration is a vehicle for upwards economic and social mobility, particularly amongst young educated people, with studies documenting favourable effects on objective labour market outcomes such as employment status, earnings and occupational standing. However, this literature has been more silent about the potential effects of internal migration on subjective measures of utility. In this paper I use panel data from Australia and Britain and panel regression models to examine whether and how internal migration is associated with young people’s self-reported job satisfaction, paying attention to the time dynamics underpinning the associations. This enables gaining a more holistic picture of the outcomes associated with internal migration during early adulthood. Key findings indicate that long-distance and work-motivated migrations have positive and statistically significant effects on the job satisfaction of young people in Britain and Australia, particularly amongst those who hold university degrees. Additionally, the results reveal time patterns in the ways in which job satisfaction and residential mobility intersect: long-term trends in job dissatisfaction can trigger internal migration, and internal migration can set long-term onwards trends in job satisfaction. I conclude by calling for further research on the outcomes of internal migration on subjective well-being leveraging the properties of panel data and using a life course approach.

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Notes

  1. These arguments resonate with emerging literature on ‘post-move’ satisfaction. This has largely focused on the effects on happiness and life satisfaction of interregional and international migration. For an overview, see Simpson (2011).

  2. Attrition rates in both surveys are relatively low. As an illustration, respondent retention rates for the last available survey wave were 92.3 % in the HILDA Survey and 95 % in the BHPS. As can be expected, migrants’ attrition rates are larger than non-migrants’ attrition rates in both the HILDA Survey (Watson and Wooden 2009) and the BHPS (Buck 2000), but existing literature on the outcomes of internal migration using these data argues that this does not distort results (Taylor 2007; Rabe and Taylor 2010; Perales and Vidal 2013; Nowok et al. 2013).

  3. I also exclude individuals who entered the survey in ‘top up’ samples in waves 7, 9 and 11 of the BHPS (their inclusion hampers national representativeness) and wave 11 in the HILDA Survey (they are only observed in one survey wave).

  4. The BHPS includes also measures of satisfaction with promotion prospects, relations with the boss and the use of initiative at work, but these are not available in all survey waves.

  5. Readers interested in the measurement properties and issues associated with these measures of job satisfaction are referred to the work of Kristensen and Westergaard-Nielsen (2006) and Conti and Pudney (2011).

  6. This was accomplished through the following transformation: new score \(=\) (original score \(-1)^{*}(10/6)\).

  7. These variables refer only to the first migration observed during the observation window which may or may not coincide with the first actual migration undertaken by the respondent. This is a generalised issue in internal migration research using household panels and a caveat of my analyses. The effect of internal migration on job satisfaction may vary depending on whether or not the observed move is the first move an individual has experienced since labour market entry. If this was the case, this may introduce noise in the analyses.

  8. Job satisfaction variables are actually ordered variables, but assuming cardinality in fixed-effect modelling has been shown to be unproblematic (Ferrer-i-Carbonell and Frijters 2004).

  9. I choose the 90 % level instead of the more common 95 % level for two reasons. First, as seen in Table 2, long-distance and work-related internal migrations are rare events. Even in large datasets such as those used here, this translates into low statistical power and a risk of Type II errors. Second, fixed-effect models provide estimates which are less biased than those from other specifications (e.g. OLS or random-effect models) but this is at the expense of sacrificing efficiency. In fixed-effect models only the within-individual variability in the panel data is used and all between-individual variability is discarded on the grounds that it may be ‘contaminated’ by unobservables. This makes these models relatively inefficient and likely to feature large standard errors.

  10. In separate analyses I tested whether moving to certain regions/states was associated with greater overall job satisfaction returns to migration, using models including interactions between migration and region/state variables. Few of the interaction effects were statistically significant. In the BHPS data, relative to moving over a long distance to London, moving to the East Midlands or Scotland was associated with higher overall job satisfaction. Relative to moving for work-related reasons to London, moving to Wales was associated with lower overall job satisfaction. None of the interactions between migration and state of residence were statistically significant in the Australian data, with New South Wales as the reference category. These results are available from the author upon request.

  11. It is also possible that, for moves motivated by individuals involuntarily losing their jobs, such trends simply reflect increasing job insecurity (leading to decreasing satisfaction) as the job separation approaches (Blanchflower and Oswald 1999).

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Acknowledgments

I would like to thank Sergi Vidal for helpful discussions and suggestions. The BHPS data used in this paper were made available through the Economic and Social Research Council (ESRC) Data Archive. The BHPS data were originally collected by the ESRC Research Centre on Micro-social Change at the University of Essex (now incorporated within the Institute for Social and Economic Research). Neither the original collectors of the data nor the Archive bears any responsibility for the analyses or interpretations presented here. This paper also uses unit record data from the HILDA Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the author and should not be attributed to either DSS or the Melbourne Institute.

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  1. ARC Centre of Excellence for Children and Families over the Life Course, Institute for Social Science Research, The University of Queensland, Long Pocket Precinct, 80 Meiers Rd, Building C, Indooroopilly, Brisbane, QLD, 4068, Australia

    Francisco Perales

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Correspondence to Francisco Perales.

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Perales, F. Dynamics of job satisfaction around internal migrations: a panel analysis of young people in Britain and Australia. Ann Reg Sci 59, 577–601 (2017). https://doi.org/10.1007/s00168-015-0728-3

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