Abstract
In this paper panel data is used to estimate the relationship between geographic reference income and subjective wellbeing in Australia. Recent cross-sectional US-based studies suggest that the income of other people in a neighbourhood—geographic reference income—impacts on individual wellbeing but is mediated by geographic scale. On controlling for a household’s own income, subjective wellbeing is raised by neighbourhood income and lowered by region-wide income. However, these findings could be driven by the self-selection of innately happy or unhappy individuals into higher-income areas. This study’s methodology takes advantage of panel-data modelling to show that unobserved individual heterogeneity is in fact correlated with reference income, but on curbing its impacts through the inclusion of fixed-effects we find that there is still a positive relationship between reference income and subjective wellbeing at the neighbourhood level. However, we detect no relationship at the region-wide level. Additionally, the subjective wellbeing relationship is the same no matter an individual’s rank in the distribution of incomes within an area. The neighbourhood wellbeing relationship has implications for policies addressing residential segregation and social mixing.
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Data Availability
This empirical paper uses general-purpose survey data from the restricted version of the Household, Income and Labour Dynamics in Australia (HILDA) survey. To access this data, eligible researchers are required to submit an application to the surveys managers, The Melbourne Institute at the University of Melbourne. We also use Australian equivalised household income data for small areas that is not freely available and must be licensed from the Australian Bureau of Statistics.
Notes
See https://ministers.treasury.gov.au/ministers/jim-chalmers-2022/media-releases/release-national-wellbeing-framework. The report itself is available at: https://treasury.gov.au/publication/p2023-mwm
See Broxterman et al. (2019) for a series of papers discussing endogenous amenities and the consumer city.
For information on the design of the HILDA Survey see Watson & Wooden (2012).
New members of a household that were part of the original sample frame participate in surveys from the year that they join the household. A top-up sample of individuals and households was also added to the survey in wave 11 (2011).
Authors own calculation using the HILDA Survey waves 1, 6, 11, and 16.
We use this method of equivalence as it is the same method used for the equivalised income data reported in the Australian Census, which is our source of reference group income. This method was performed by first calculating a household’s equivalence factor that allocates points to each person in a household (1 point to the first adult, 0.5 points to each additional person who is 15 years and over, and 0.3 to each child under the age of 15). Household income was then divided by the sum of the points allocated to each person (the equivalence factor).
CPI data was obtained from Australian Bureau of Statistics catalogue 6401.0 – Consumer Price Index, Australia.
Access to the Restricted Release of the HILDA Survey was required for this research, as it contains the location of responding households at the neighbourhood level. The confidentialised release of the HILDA Survey, referred to as the general release, does not contain detailed geography—location is limited to city-wide or regional measures, such as the household’s greater capital city, section of state, and remoteness area.
The borders of a small number of SA2s changed over the study period. We ensure concordance of the SA2 data by employing consistent 2011 ASGS border definitions across all census years.
The population of SA2s generally ranges between 3000 and 25,000 persons, with an average population of 10,000 (ABS, 2020).
As based on the individual’s Section of State classification in the Australian Statistical Geography Standard (ASGS).
For example, popular econometrics and statistical software package Stata provides only a random-effects specification for its ordered logit or ordered probit panel-data models (StataCorp, 2021).
The author estimated an ordered probit model as a robustness check, but only on the cross-sectional data.
All prior studies of reference income and wellbeing log transform their income variables, and so we also follow this convention.
Senik (2008) does not offer a rationale for the 41 years of age threshold, but it likely represents the early career stage of LFP, characterised by the strongest opportunities for positive earnings growth. This is evidenced in the 2016 Australian census, which documents a peak in the median earnings of full-time workers at 41 years (ABS, 2016).
We considered the inclusion of measures of social capital, including participation in i’s local community. However, these measures are contained in the voluntary self-completion questionnaire of the HILDA Survey, which have lower levels of response compared to our other predictors, significantly reducing model sample size.
The maximum household income observed is $4,594,092. Removing the bottom and top five percent of observations, as ranked by household income, reduces the average to $60,134 and the standard deviation to a less extreme $31,512.
The application of Wald tests to REWB models is demonstrated in Schunck (2013).
A less positive interpretation could be applied to social mixing. An influx of lower-income residents into higher-income neighbourhoods would raise the wellbeing of new residents, as reference incomes are higher relative to their previous neighbourhood. However, if this influx of lower-income residents lowers reference income, the wellbeing of existing residents will be reduced.
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Acknowledgements
This paper uses unit record data from HILDA. HILDA 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 authors and should not be attributed to the Australian Government, DSS or the Melbourne Institute. http://dx.doi.org/10.26193/0LPD4U
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Phelps, C., Harris, M.N., Rowley, S. et al. Geographic Reference Income and the Subjective Wellbeing of Australians. J Happiness Stud 24, 2855–2880 (2023). https://doi.org/10.1007/s10902-023-00707-6
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DOI: https://doi.org/10.1007/s10902-023-00707-6