Abstract
The family home is often the single most valuable asset, when it is passed down generations. In recent years, this pathway towards homeownership has become more complex. Young people are increasingly depending on their parents, both financially (deposit) and in-kind (guarantor, living rent-free at parental home), to acquire their first home. This paper contributes to this debate by investigating the influence of bequests and in-kind generational transfers on housing wealth pathways. Based on the British Household Panel Study, this paper shows that receiving an inheritance seems less relevant than other socio-demographic control variables. Still life-time renters are significantly missing out on inheritances. However, young people who are living with their parents are benefiting from this in-kind support in the long term and are able to purchase their first home earlier than independent mortgagers who are saving up for a deposit while renting. These results are discussed in the wider context of housing policy, welfare and generational support.
Acknowledgements
An earlier version of this paper had been presented at the ISA World Congress 2014. I am grateful to Hannah Zagel (Humboldt Universität, Berlin) for her methodological advice on sequence analysis. Also thanks to Christian Lennartz, Richard Ronald and Beverley Searle for their feedback on earlier drafts. The British Household Panel Study (BHPS) was made available through the UK Data Service, originally collected by the Institute for Social and Economic Research (University of Essex). Neither the original collectors nor the data provider bear any responsibility for the analyses or interpretations presented here.
Notes
1. The numbers indicate the variable codes for each element which are used in some of the presented results.
2. Respondents underreport the take-out of an additional mortgage (Benito, Citation2009). Therefore, Ong et al. (Citation2013) suggest to measure in situ equity withdrawal as an increase of total mortgage debt from 2001 onwards. Due to missing and modified variables in earlier waves, this indicator could not be used here and is measured conservatively with the mgxtra variable.
3. All analytical steps have been estimated with the sq commands in STATA (Brzinsky-Fay et al., Citation2006).
4. The substitution cost matrix is based on transition frequencies (Halpin & Chan, Citation1998). Distance matrices were calculated with Needleman-Wunsch algorithm. These estimations were the basis for clustering with Ward’s method.
5. Several models with respondents’ social class and different class scales were tested, but insignificant and therefore not reported in the final results.