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Social Indicators Research
Published in: Social Indicators Research 1/2022

28-11-2021 | Original Research

What Matters for the Wellbeing of Mothers and Children in Material  Hardship? Application of a Modified Indicator Framework

Authors: Leah Haines, Arthur Grimes

Published in: Social Indicators Research | Issue 1/2022

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Abstract

We examine determinants of subjective wellbeing (SWB) for mothers of dependent children in material hardship, using a modification of the New Zealand Treasury’s Living Standards Framework (LSF) and data from the General Social Survey. We convert the LSF—an indicator dashboard—into a tool for prioritising social policies by placing SWB at the head of a hierarchy of wellbeing domains. Several determinants of these mothers’ SWB conform to standard findings; however, two important differences stand out. One is the lack of a protective effect from employment on SWB for this group (unlike the protective effect for males). The other is a positive relationship between a mother’s SWB and satisfaction with her own skills/knowledge; this effect is particularly strong for sole mothers in hardship, dominating any effect of qualifications on SWB. The analysis demonstrates both a practical use of a modified LSF, and the value of taking a gender-specific approach to analysing wellbeing.
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Appendix
Available only for authorised users
Footnotes
1
Māori are the indigenous population of New Zealand; the Pacific population are migrants (or descendants of migrants) from Pacific Island nations.
 
2
The Child Poverty Reduction Act specifies 10 distinct measures of child poverty, including measures related to income and material hardship. Given that New Zealand is a developed country, each of these measures can be interpreted as a relative (rather than absolute) poverty measure.
 
3
In our sample from the 2012 GSS, 81% of sole parents with dependent children are female.
 
4
The 2012 survey is the most recent GSS available for use outside of Stats NZ’s confidential datalabs. It includes questions relevant to our study that were not repeated in subsequent social surveys.
 
5
A longer list of candidate variables was initially identified but we imposed a restriction that the candidate questions had to have at least 8000 responses (out of the full sample of 8455) to mitigate issues of selection bias.
 
6
Given that this is an ordered logistic regression (i.e. with more than two Likert scale categories), the interpretation of the odds ratio (OR) is that for a one unit change in the independent variable, the odds for cases in a group that is greater than k is OR times those for cases in a group that is less than or equal to k. In turn the odds are defined as p/(1 − p) where p is the probability of being in the relevant group. Hence an odds ratio greater (resp. less) than one implies a positive (resp. negative) association between the independent variable and SWB. Significance is reported relative to an odds ratio of 1 (i.e. a null hypothesis of no effect).
 
7
One note of caution in interpreting this variable, and some other variables, is that the question relates to a self-assessment as does the dependent variable raising the potential for common method variance (Williams & Brown, 1994). Helliwell and Huang (2010) note that the inclusion of other self-assessed variables in the regression (such as our inclusion of satisfaction with the environment) may help to mitigate this bias.
 
8
Not being in the labour force indicates that the individual is not employed and is not looking for work.
 
9
It is interesting to note that having too much free time has a significantly negative association with SWB for all groups, significantly so for the all male and all female groups.
 
10
This means, for instance, that our notional comparator has the average age and ‘average ethnicity’ of the sample. The probabilities in Table 4 are calculated using the margins option in Stata.
 
11
We do not report the effects of a larger shift in material wellbeing since a counterfactual that exceeds the hardship cut-off lies outside the support for this variable in the regression estimated for this population sub-group.
 
12
The analysis presents average effects for each group. It is likely that some mothers experience positive impacts on their wellbeing from employment while others do not.
 
13
There has been no time use survey in New Zealand since 2010 despite calls that this information is vital for addressing questions such as those analysed in this paper (Waring, 2018).
 
14
In response to the Covid19 crisis, from July 2020 the minimum work hours requirement has been removed.
 
15
Again we caveat this observation by noting that the magnitude of the estimated effect may be inflated by common method variance although the inclusion of other self-reported satisfaction measures as independent variables helps to mitigate this potential source of bias.
 
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Metadata
Title
What Matters for the Wellbeing of Mothers and Children in Material  Hardship? Application of a Modified Indicator Framework
Authors
Leah Haines
Arthur Grimes
Publication date
28-11-2021
Publisher
Springer Netherlands
Published in
Social Indicators Research / Issue 1/2022
Print ISSN: 0303-8300
Electronic ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-021-02845-x

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