Abstract
This article examines the extent to which the relationship between leaving home and entry into poverty among young people is causal: that is, how far poverty entry is the result of leaving home, rather than arising from heterogeneity or selection. Using propensity score matching, we estimate the effect of home-leaving on entry into poverty and deprivation, with data from the European Community Household Panel. We find that leaving home does have a causal effect on poverty entry, particularly in Scandinavian countries; cross-national differences are partly, but not fully, explained by differences in destinations on leaving home.
Résumé
Cet article analyse la relation de causalité entre le départ de la maison et l’entrée dans la pauvreté des jeunes, en posant la question de savoir si l’entrée dans la pauvreté résulte du départ de la maison, ou bien plutôt de phénomènes d’hétérogénéité ou de sélection. En utilisant une méthode d’appariement par scores de propension, nous estimons l’effet du départ de la maison sur l’entrée dans la pauvreté et le dénuement, à l’aide de données du Panel Européen des Ménages. Nous montrons qu’il existe une relation de cause à effet entre le départ de la maison et l’entrée dans la pauvreté, particulièrement dans les pays scandinaves; les différences entre pays sont partiellement expliquées par des différences dans la destination des jeunes au départ de la maison.
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Notes
Different definitions of child poverty are used in the literature. The most common approach is to compute poverty rates for those aged 17 and younger, but other have used an age limit of 15.
Poverty rates refer here to the Headcount poverty rate, where poverty is defined by belonging to a household where the total net equivalised household income is less than 60% of the median income of the relevant country and year.
For the purposes of cross-sectional analysis this is not a problem—but because household income is measured retrospectively, it makes it impossible to analyse the links between living arrangements and incomes.
The fact that this procedure was not implemented for Finland does not make a huge difference on the estimates. We have estimated the models both with and without this adjustment for all countries, and although our approach is the appropriate one, the impact on the estimates is relatively modest. In other words, this does not explain why leaving home in Finland has the strongest effect on entering poverty.
All of the reported analysis is implemented using the psmatch2 module in STATA (Leuven and Sianesi 2003). In all PSM algorithms, there is a trade-off between bias and variance. We found that nearest neighbour methods gave the best reduction in bias. Increasing the number of neighbours reduces the variance of estimates (since more information is used), but increases bias (since the mean quality of the matches will be lower). In this analysis, we found that using three neighbours gave the most acceptable balance between reduced variance and increased bias.
As a consistency check, we also perform the same analysis using radius matching with a bandwidth of 0.01, which is analogous to the nearest neighbour method with calliper 0.01, except that the control group is based on a distance-weighted average of many more observations, some with worse matches. Therefore, the variance is lower, but the bias higher. For the sake of brevity, we do not report these estimates in the article, but they are available from the authors on request.
Table A2 also contains a number of indicators of the quality of the matching process, namely, the reduction in bias due to matching and the number of cases lost due to trimming and conditioning on the common support.
The results discussed in this section focus on the 20–24 age group; however, ATTs for all age groups, plus bootstrapped standard errors, are shown in Table A3 in the Appendix. In general, the effect of leaving home on poverty entry is lower for older age groups, which is not surprising, given that older youths tend to have higher income and more stable employment.
Quality indicators and bootstrap errors for these new ATT are not shown in the Appendix, but are available from the authors upon request.
Unfortunately, small sample size did not allow this ATT to be estimated for couples in Denmark, so we cannot say whether this is a “Scandinavian” effect, or an effect restricted to Finland.
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Acknowledgements
This article forms part of the project “Poverty Among Youth: International Lessons for the UK”, funded by the Joseph Rowntree Foundation Grant no. 803554 under the Ladders Out of Poverty programme. The ECHP data used in the analysis were produced and made available by Eurostat. All errors and inconsistencies in the article are our own.
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Aassve, A., Davia, M.A., Iacovou, M. et al. Does Leaving Home Make You Poor? Evidence from 13 European Countries. Eur J Population 23, 315–338 (2007). https://doi.org/10.1007/s10680-007-9135-5
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DOI: https://doi.org/10.1007/s10680-007-9135-5