The primary goal of this study is to contribute on the literature on poverty by looking at household economic hardship in relation to the housing cost burden. Being one of the most significant outlays in a household balance, housing costs may indeed cause households to reduce non-housing expenditure such as health care, education, food, and clothing, thus creating serious household economic hardship. Using microdata from the European Union Statistics on Income and Living Conditions dataset (EU-SILC) regarding five European countries (Italy, Germany, UK, Spain, and France) we have examined the predictive power of housing costs in explaining family economic hardship. Furthermore, we have jointly estimated the effect of the housing cost burden upon economic hardship for renters versus home-owners paying mortgages. Results showed that housing costs represent a non negligible burden in all the five European countries. Moreover, home ownership was found to significantly reduce household hardship status.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Mammen et al. (2014) highlighted the extent to which poverty status as well as its trajectory is determined by more than just income or employability. Albeit focusing on poverty and well being in rural areas, the authors emphasized that not only poverty, but also the process to exit or enter into poverty has a multidimensional nature.
In this regard, expectations for a high capital gain represent an incentive to become a home-owner (Goodman 1990).
According to the Eurofund Seminar Report on Working Poverty “workers living in a household where at least one member works and where the overall income of the household (including social transfers and after taxation) remain below the poverty line (60 % of median equivalized income) are defined as working poor”.
On this regard, this study allows to consider jointly institutional country-level factors and micro-level mechanisms.
Boarini and d'Ercole (2006) found that the probability of experiencing material deprivation is twice as large among those in the lower quartile of the income distribution than for those in the middle quartile, although these differences vary greatly across countries.
Bárcena-Martín et al. (2013) consider deprivation as the inability to afford at least four out of nine items: to pay utility bills; to keep their home adequately warm; to pay unexpected expenses; to eat meat, fish, or a protein equivalent every second day; to enjoy a week’s holiday away from home; to have a car; to have a washing machine; to have a colour TV; and to have a telephone.
Information as social exclusion and housing-condition is collected at household level, while labour, education and health information come at personal level.
EU-SILC documentation states that “the person responsible for the accommodation is the one owning or renting the accommodation. If the accommodation is provided at no cost, the person to whom the accommodation is provided is the responsible person. If two persons share responsibility for the accommodation, the oldest person is considered to be responsible”.
Indeed, the work intensity indicator that is used in order to calculate one of the indicators of hardship only refers to the population in the age range 18–59.
See appendix for a detailed definition of material deprivation, low work intensity and risk of poverty according to EUROSTAT.
A similar measure of poverty has been used by Watson and Webb (2009)
The usage of such a self-reported measure of hardship may capture households who experience a lower level of welfare than their peers, but who may not face hardship in absolute sense. From this perspective, the usage of alternative hardship measures allows to check for the robustness of results to different measurement of households’ hardship status.
For example, the US Department of Housing and Urban Development, Office of Policy Development and Research (2007) considers households paying more than 30 % of gross income for housing as cost burdened, while those paying 50 % or more are considered severely cost burdened.
Brandolini et al. (2013), analysing the determinants of perceived housing cost burden, found indeed this measure to be strongly correlated to the effective housing cost sustained by households.
According to Boeri and Brandolini (2005), subjective factors such as disappointed expectations, high income mobility and high income inequality are good candidates to explain Italian households poverty perception.
In this regard, MacLennan et al. (1998) noticed how different levels of financial market regulation affect differently housing market in different countries.
When looking at results by country (Tables 14, 15 in the Appendix) results are confirmed.
The definition of social renting differs in the five countries taken into account (Pittini and Laino 2011).
The fact that home ownership rate in Italy is the lowest with respect to other countries is not surprising. Indeed, descriptive statistics only refer to households with outstanding mortgage, while in Italy the majority of households count on parental help. This is in line with statistics provided by Georgarakos et al. (2010) using HCHP.
We are only considering houses which are mortgage-burdened, and in Italy only a minority of households have mortgages (Georgarakos et al. 2010). This may explain a level of home ownership that is not as high as expected.
Including social renters into the analysis would allow for a substantial degree of heterogeneity across countries. Social renting in EU countries differs indeed in terms of tenures, providers, beneficiaries and funding arrangements (Housing Europe Review 2012).
This is in line with Brandolini et al. (2013), who eventually found that home-ownership, as well as living in a rent-free accommodation, affected negatively the subjective measure of housing cost burden. Furthermore, households with mortgages in Italy and Spain were more likely to declare heavy housing cost burdens.
Households who are not homeowners would probably allocate money in private pension plans, saving accounts, or private insurance, thus limiting their spending capacity.
Two stage procedures such as Heckman (1979) are approximate, since they do not allow making distributional assumptions regarding estimators.
Miranda and Rabe-Hesketh (2006) noticed that their method differed from bivariate probit for the parametrization of the variance-covariance matrix, where the variances of the errors were set to be 1.
Particularly, it is an indicator regarding price changes of residential properties purchased by households (flats, detached houses, terraced houses, etc.), both newly-built and existing ones, independently of their final use and independently of their previous owners. Data come from ECB statistical warehouse.
Furthermore, there is evidence that ignoring endogeneity of tenure status leads to biased coefficients. In the specification with H2 and HBU, when endogeneity is not considered being a home owner reduces the probability to face material hardship (H2) of 18 %. This probability is almost 60 % when endogeneity is taken into account. Similar results hold when other specifications are considered.
In this regard, expanding households’ access to financial products and enhancing their functioning plays a non negligible role in helping households to reduce hardship. See, for example, Huang et al (2014) who examined the correlation between the probability of experiencing hardship (defined as self-reported inability to meet basic needs) correlated with financial capability in a sample of older Asian immigrants. A related study (Leonard and Di 2014) as well highlighted the role played by financial behaviour. Focused on asset poverty (defined as having a net worth to sustain income for 3 months above the federal income poverty level, or net worth equal to 25 % of the annual income poverty level), they stated that financial behaviour directed towards debt minimization and inclusion of productive assets may reduce the likelihood of asset poverty re-entry.
On this regard, we can assume that the ignorability hypothesis holds for our data. First of all, ignorability implies distinctness of parameters of the data model and the missing data mechanism. Second, the missing at random (MAR) hypothesis is also assumed, implying that the probability that an observation is missing may depend on observed values but not on missing ones. On this regard, we are including a set of controls (i.e. income, household size and composition) that can predict the probability of not reporting missing information. Further, it is often difficult to establish a clear border line between the MAR and Missing not at random (MNAR) assumption. However, as pointed out by Schafer and Graham (2002), multiple imputation can still be unbiased with NMAR data even if we assume data is MAR. Moreover, multiple imputation does not require that nonresponse is ignorable (Schafer 1999), so that inferences created under any kind of assumptions for the missing-data mechanism will be valid.
As shown in the tables that have been inserted in the appendix, the coefficient associated to housing cost is slightly higher when missing values are imputed using both methods of imputation. Therefore, when the observations with missing values in the key variables are deleted from the sample, a downward bias in the coefficient associated to housing cost is present.
Alessie, R., Hochguertel, S., & Van Soest, A. (2002). Household portfolios in the Netherlands. In L. Guiso, M. Haliassos, & T. Jappelli (Eds.), Household portfolios (pp. 341–388). Cambridge: MIT Press.
Amemiya, T. (1978). The estimation of a simultaneous equation generalized probit model. Econometrica Journal of the Econometric Society, 46(5), 1193–1205. doi:10.2307/1911443.
Atkinson, A. B., Cantillon, B., Marlier, E., & Nolan, B. (2002). Social indicators. The EU and social inclusion. Oxford: Oxford University Press.
Ayala, L., Jurado, A., & Pérez-Mayo, J. (2011). Income poverty and multidimensional deprivation: Lessons from cross-regional analysis. Review of income and wealth, 57(1), 40–60. doi:10.1111/j.1475-4991.2010.00393.x.
Banks, J., Blundell, R., Oldfield, Z., & Smith, J. P. (2004). House price volatility and housing ownership over the life cycle (UCL Discussion Papers in Economics 04–09). University College London: London, UK. Retrieved from http://discovery.ucl.ac.uk/2561/1/2561.pdf?origin=publication_detail.
Banks, J., Blundell, R., & Smith, J. P. (2003). Wealth portfolios in the US and the UK. In D. Wise (Ed.), Perspectives on the economics of ageing (pp. 205–246). Chicago: Chicago University Press.
Bárcena-Martín, E., Lacomba, B., Moro-Egido, A. I., & Pérez-Moreno, S. (2013). Country differences in material deprivation in Europe. Review of Income and Wealth: Advance online publication. doi:10.1111/roiw.12030.
Bardone, L., & Guio, A.C. (2005). In-work poverty, in Eurostat (ed.), Statistics in Focus-Population and Social Conditions (publication no. 5/2005), Luxembourg, EUROSTAT. Retrieved from http://ec.europa.eu/employment_social/social_inclusion/docs/statistics5-2005_en.pdf.
Benito, A., (2007) Housing equity as a buffer: evidence from UK households (Working paper no. 324). Retrieved from http://www.bankofengland.co.uk/research/Documents/workingpapers/2007/WP324.pdf.
Boarini, R., & d’Ercole, M. M. (2006). Measures of material deprivation in OECD Countries (No. 37). OECD Publishing. doi:10.1787/866767270205.
Boeri T., & Brandolini A. (2005). The age of discontent: Italian households at the beginning of the decade, (IZA discussion paper No. 1530). Retrieved from http://iza.org/dp1530.pdf.
Bosch, K. (1998). Poverty and assets in Belgium. Review of Income and Wealth, 44(2), 215–228. doi:10.1111/j.1475-4991.1998.tb00269.x.
Bostic, R. W., & Lee, K. O. (2008). Mortgages, risk, and homeownership among low-and moderate-income families. The American Economic Review, 98(2), 310–314. doi:10.1257/aer.98.2.310.
Brandolini, M., Coroneo, F., Giarda, E., & Moriconi, C., & See, S.G. (2013). Differences in perceptions of the housing cost burden among European countries (Nota di lavoro Prometeia 2010-01). Retrieved from Prometeia website: http://www.prometeia.it/it-it/ricerca/note-di-lavoro.aspx?idC=63274&LN=it-IT.
Cantillon, S., & Nolan, B. (1998). Are married women more deprived than their husbands? Journal of Social Policy, 27(02), 151–171. doi:10.1017/s0047279498005261.
Charles, K.K., Hurst, E., & Roussanov, N.L. (2007). Conspicuous consumption and race, (NBER Working Paper No. W13392). Retrieved from NBER website: http://www.nber.org/papers/w13392.pdf?new_window=1.
Childers, T.L., & Rao, A.R. (1992). The influence of familial and peer-based reference groups on consumer decisions. Journal of Consumer Research, 19(2), 198–211. Retrieved from http://www.jstor.org/stable/2489328.
Chiuri, M. C., & Jappelli, T. (2003). Financial market imperfections and home ownership: a comparative study. European Economic Review, 47(5), 857–875. doi:10.1016/S0014-2921(02)00273-8.
Christelis, D., Jappelli, T., Paccagnella, O., & Weber, G. (2009). Income, wealth and financial fragility in Europe. Journal of European Social Policy, 19(4), 359–376. doi:10.1177/1350506809341516.
Conley, D., & Gifford, B. (2006). Home ownership, social insurance, and the welfare state. In Sociological Forum, 21, 55–82. doi:10.1007/s11206-006-9003-9.
European Foundation for the Improvement of Living and Working Conditions (EUROFUND) (2010) Working Poor in Europe. Retrieved from EUROFUND website: http://www.eurofound.europa.eu/pubdocs/2010/25/en/1/EF1025EN.pdf.
EUROSTAT (2002) European Social Statistics. Income, Poverty and Social Exclusion: 2nd Report, European Commission, Luxembourg. Retrieved from http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-BP-02-008/EN/KS-BP-02-008-EN.PDF.
EUROSTAT, (2013) Handbook of residential property prices, 2013. Retrieved from http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-RA-12-022/EN/KS-RA-12-022-EN.PDF.
Ferrer-i-Carbonell, A. (2005). Income and well-being: an empirical analysis of the comparison income effect. Journal of Public Economics, 89(5), 997–1019. doi:10.1016/j.jpubeco.2004.06.003.
Figari, F. (2012). Cross-national differences in determinants of multiple deprivation in Europe. The Journal of Economic Inequality, 10(3), 397–418. doi:10.1007/s10888-010-9157-9.
Fusco A., (2012) The relationship between income and housing deprivation in Luxembourg: a longitudinal analysis (Working Paper Series 2012-10). Retrieved from CEPS/INSTEAD website: http://www.ceps.lu/?type=module&id=104&tmp=1822.
Georgarakos, D., Lojschova, A., & Ward-Warmedinger, M. (2010). Mortgage Indebtedness and Household Financial Distress. Working Paper series No. 1156, European Central Bank.
Goodman, A. C. (1990). Demographics of individual housing demand. Regional Science and Urban Economics, 20(1), 83–102. doi:10.1016/0166-0462(90)90026-Y.
Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47, 153–162. Retrieved from http://www.jstor.org/stable/1912352.
Heflin, C., Sandberg, J., & Rafail, P. (2009). Structure of material hardship in US households: An examination of the coherence behind common measures of well-being. Social Problems, 56(4), 746–764. doi:10.1525/sp.2009.56.4.746.
Hong, H., Kubik, J. D., & Stein, J. C. (2004). Social interaction and stock market participation. Journal of Finance, 59(1), 137–163. doi:10.1111/j.1540-6261.2004.00629.x.
Huang, J., Nam, Y., & Lee, E. J. (2014). Financial capability and economic hardship among low-income older asian immigrants in a supported employment program. Journal of Family and Economic Issues. doi:10.1007/s10834-014-9398-z.
Kessler, D., & Wolff, E. N. (1991). A comparative analysis of household wealth patterns in France and the United States. Review of Income and Wealth, 37(3), 249–266. doi:10.1111/j.1475-4991.1991.tb00370.x.
Kurz, K., & Blossfeld, H. P. (2004). Home ownership and social inequality in comparative perspective. Stanford: Stanford University Press.
Kutty, N. K. (2005). A new measure of housing affordability: Estimates and analytical results. Housing Policy Debate, 16(1), 113–142. doi:10.1080/10511482.2005.9521536.
Labeaga, J.M., Molina J.A., & Navarro M. (2007) Income satisfaction and deprivation in Spain (IZA Discussion Paper no.2702). Retrieved from IZA website: http://hdl.handle.net/10419/34552.
Layte, R., Nolan, B., & Whelan, C.T. (2001). Reassessing income and deprivation approaches to the measurement of poverty in the Republic of Ireland. Economic and Social Review, 32(3), 239–262. Retrieved from http://www.esr.ie/ESR_papers/vol32_3/Vol32_3RLayte3.pdf.
Leonard, T., & Di, W. (2014). Is household wealth sustainable? An examination of asset poverty reentry after an exit. Journal of Family and Economic Issues, 35(2), 131–144. doi:10.1007/s10834-013-9357-0.
Maclennan, D., Muellbauer, J., & Stephens, M. (1998). Asymmetries in housing and financial market institutions and EMU. Oxford Review of Economic Policy, 14(3), 54–80. doi:10.1093/oxrep/14.3.54.
Maddala, G. (1996). Limited-dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press.
Mammen, S., Dolan, E., & Seiling, S.B. (2014). Explaining the poverty dynamics of rural families using an economic well-being continuum. Journal of Family and Economic Issues. Advance online publication. doi:10.1007/s10834-014-9405-4.
Marx, I., & Verbist, G. (1998). Low-paid work and poverty: a cross-country perspective. In S. Bazen (Ed.), Low-wage employment in Europe (pp. 63–86). Cheltenham: Edward Elgar.
Mayer, S. E., & Jencks, C. (1989). Poverty and the distribution of material hardship. Journal of Human Resources, 24(1), 88–114. doi:10.2307/145934.
Melzer, B. T. (2011). The real costs of credit access: Evidence from the payday lending market. The Quarterly Journal of Economics, 126(1), 517–555. doi:10.1093/qje/qjq009.
Mimura, Y. (2008). Housing cost burden, poverty status, and economic hardship among low-income families. Journal of Family and Economic Issues, 29(1), 152–165. doi:10.1007/s10834-007-9085-4.
Miranda, A., & Rabe-Hesketh, S. (2006). Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables. Stata Journal, 6(3), 285–308. Retrieved from http://www.stata-journal.com/article.html?article=st0107.
Nolan, B., & Whelan, C. T. (2010). Using non-monetary deprivation indicators to analyse poverty and social exclusion in rich countries: Lessons from Europe? Journal of Policy Analysis and Management, 29, 305–323. doi:10.1002/pam.20493.
Nolan, B., & Whelan, C. T. (2011). Poverty and deprivation in Europe, OUP Catalogue. Oxford: Oxford University Press.
Peña-Casas R., & Latta M. (2004). Working poor in the European Union, European Foundation for the Improvement of Living and Working Conditions, Dublin. Retrieved from http://www.eurofound.europa.eu/pubdocs/2010/25/en/1/EF1025EN.pdf.
Pittini, A., & Laino, E. (2011). Housing Europe review: The nuts and bolts of European social housing systems, CECODHAS Housing Europe’s Observatory, Brussels. Retrieved from http://archive.housingeurope.eu/archive.housingeurope.eu/uploads/file_/HER%202012%20EN%20web2_1.pdf.
Prawitz, A. D., Kalkowski, J. C., & Cohart, J. (2013). Responses to economic pressure by low-income families: Financial distress and hopefulness. Journal of Family and Economic Issues, 34(1), 29–40. doi:10.1007/s10834-012-9288-1.
Schafer, J. L. (1999). Multiple imputation: a primer. Statistical Methods in Medical Research, 8(1), 3–15. doi:10.1177/096228029900800102.
Schafer, J. L., & Graham, J. W. (2002). Missing data: our view of the state of the art. Psychological Methods, 7(2), 147–177. doi:10.1037//1082-989X.7.2.147.
Stone, M. E. (2006). What is housing affordability? The case for the residual income approach. Housing Policy Debate, 17(1), 151–184. doi:10.1080/10511482.2006.9521564.
Sullivan, J. X., Turner, L., & Danziger, S. (2008). The relationship between income and material hardship. Journal of Policy Analysis and Management, 27(1), 63–81. doi:10.1002/pam.20307.
Townsend, P. (1979). Poverty in the United Kingdom. Harmondsworth: Penguin.
US Department of Housing and Urban Development, Office of Policy Development and Research (2007). Affordable housing needs 2005: Report to Congress. Washington, DC: Government Printing Office. Retrieved from http://www.huduser.org/Publications/pdf/AffHsgNeeds.pdf.
Valentino, S. W., Moore, J. E., Cleveland, M. J., Greenberg, M. T., & Tan, X. (2014). Profiles of financial stress over time using subgroup analysis. Journal of Family and Economic Issues, 35(1), 51–64. doi:10.1007/s10834-012-9345-9.
Van Dam, R., Geurts, V., & Pannecoucke, I. (2003). Housing tenure, housing costs and poverty in Flanders (Belgium). Journal of Housing and the Built Environment, 18(1), 1–23. doi:10.1023/A:1022429825185.
Venti, S. F., & Wise, D. A. (2004). Aging and housing equity: another look. Wealth portfolios in the US and the UK. In D. Wise (Ed.), Perspectives on the economics of ageing (pp. 127–175). Chicago: Chicago University Press.
Watson, D., & Webb, R. (2009). Do Europeans view their homes as castles? Homeownership and poverty perception throughout Europe. Urban Studies, 46(9), 1787–1805. doi:10.1177/0042098009106020.
Wolff, E. N. (1994). Trends in household wealth in the United States, 1962–83 and 1983–89. Review of Income and Wealth, 40(2), 143–174. doi:10.1111/j.1475-4991.1994.tb00056.x.
Yates, J., & Bradbury, B. (2010). Home ownership as a (crumbling) fourth pillar of social insurance in Australia. Journal of Housing and the Built Environment, 25(2), 193–211. doi:10.1007/s10901-010-9187-4.
Housing Cost (HC)
Monthly housing costs sustained by owners include the following components: mortgage principal repayment, mortgage interest payments (net of any tax relief), gross of housing benefits, (i.e., housing benefits should not be deducted from the total housing cost), structural insurance, mandatory services and charges (sewage removal, refuse removal, etc.), regular maintenance and repairs, taxes, and the cost of utilities (water, electricity, gas and heating).
Monthly housing costs sustained by renters include the following components: rent payments, gross of housing benefits (i.e., housing benefits should not be deducted from the total housing cost), structural insurance (if paid by the tenants), services and charges (sewage removal, refuse removal, etc.) (if paid by the tenants), taxes on dwelling (if applicable), regular maintenance and repairs and the cost of utilities (water, electricity, gas and heating).
Housing Cost Financial Burden (HBU)
Households were asked the following question: “Please think of your total housing costs including mortgage repayment (instalment and interest) or rent, insurance and service charges (sewage removal, refuse removal, regular maintenance, repairs and other charges). To what extent are these costs a financial burden to you?”. Households are considered to perceive high financial burden if they declare housing costs to be a heavy burden.
Material Deprivation (H2)
Material deprivation refers to households’ inability to afford at least three of the following items:
to pay rent, mortgage or utility bills;
to keep the home adequately warm;
to face unexpected expenses;
to eat meat or proteins regularly;
to go on holiday;
to own a television set;
to own a washing machine;
to own a car;
to own a telephone.
When the household cannot afford at least four of the above items it comes to be severe material deprivation. Material deprivation does not refer to the case when the household does not own the item for reason different from their affordability (i.e., the household does not need the good).
Eurostat defines work intensity as the ratio of the total number of months that all working-age household members have worked during the income reference year and the total number of months the same household members theoretically could have worked in the same period. A working-age person is a person aged 18–59 years, with the exclusion of students in the age group between 18 and 24 years.
Risk of Poverty
A householder is at risk of poverty if her income is relatively low compared with other residents in the country where she lives. In particular, risk of poverty refers to having an equivalised disposable income below the risk of poverty threshold, set at 60 % of the national median equivalised disposable income after social transfers.
Probit Regression, by Country
About this article
Cite this article
Deidda, M. Economic Hardship, Housing Cost Burden and Tenure Status: Evidence from EU-SILC. J Fam Econ Iss 36, 531–556 (2015). https://doi.org/10.1007/s10834-014-9431-2
- Financial distress
- Household finance
- Housing cost burden
- Tenure status