Abstract
This paper examines the impact of housing tenure choice on unemployment duration in Belgium using EU-SILC micro data. We contribute to the literature in distinguishing homeowners with mortgage payments and outright homeowners. Accounting for tenure endogeneity and unobserved heterogeneity, we find that homeowners with a mortgage exit unemployment first, while outright owners stay unemployed the longest. Tenants take an intermediate position. Our results emphasize the key role of housing costs in the link between housing tenure and labour market outcomes. Considered together with the results of recent macroeconomic research on housing and employment in Belgium, this paper provides indirect evidence for significant negative effects of homeownership on the labour market and the economy beyond the owners themselves.
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Notes
Munch et al. (2006) only make the broad subdivision between homeowners and non-homeowners. Battu et al. (2008) split up the group of non-homeowners into public and private tenants. Brunet and Lesueur (2009) distinguish tenants and people living free of charge (mainly young people living in their parents’ home).
van Ewijk et al. (2007) raised the hypothesis of externalities from homeownership already a few years ago. The effects of ownership on the economy beyond the owners themselves that they mention, however, are mostly positive and do not directly concern the labour market. Homeowners, for example, may support local schools more and invest more in child rearing, improving childrens’ cognitive and behavioural outcomes.
Unsurprisingly, the above mentioned empirical literature studying geographical mobility leaves us with mostly ambiguous answers to the question whether outright owners or mortgagees are more geographically mobile. For example, in a cross-section of 23 OECD countries, Caldera Sánchez and Andrews (2011) find outright owners to be less residentially mobile than owners with mortgage payments in 15 countries. They observe the opposite in 4 other countries. In 4 last countries, one of which is Belgium, there is no significant difference between outright owners and mortgagees in this respect. Isebaert (2013), by contrast, uses panel data and finds mortgagees to be less geographically mobile than outright owners in Belgium. Thereby, the only robust empirical result across studies seems to be that tenants are more residentially mobile than owners.
Vastmans and Buyst (2011) reveal that monthly mortgage payments account for 24.6 % of a household’s net monthly income, on average. Housing costs of outright owners, by contrast, are limited to maintenance costs. As to the distinction between homeowners with a mortgage and tenants, Heylen et al. (2007) report a mean rental price in the Flemish region in 2005 of 396€ , while the mean mortgage payment was equal to 564€ . The latter clearly represents the heaviest burden on the household budget. Furthermore, tenants experience lower costs of maintenance. Rouwendal (2009, figure 12) reports comparable data for the Netherlands. He confirms that net out-of-pocket housing costs are clearly higher for mortgagees than for tenants, at least among young and middle-aged households.
Possible destinations are retirement, being permanently disabled or taking up domestic tasks and care responsibilities.
The only explanatory variable that we allow to vary during unemployment spells is the regional unemployment rate. This variable is strictly exogenous all the way. It contributes to the model by capturing the business cycle at the regional level. Belgium consists of three regions (Flanders, Wallonia and Brussels).
The interpolation that we impose assigns the yearly observation in EU-SILC to 6 months before and 6 months after the moment of measurement (around March). This also brings the advantage of a larger sample. When new households enter the panel in year y, data is collected also about their labour market situation in the 12 months of \({y-1}\). Spells that start in October of \({y-1}\) can therefore also be included in our sample.
Coulson and Fisher argue that regional homeownership rates may affect wage setting and other costs of doing business in a region. This may affect individuals’ chances on the labour market. The use of regional homeownership rates as instrument would then be invalid. We emphasize that our results do not in any way depend on the use of this particular instrument (see Sect. 5.2).
The hazard rate is defined as the probability to flow into employment at date \(t\) conditional on being unemployed up to \(t\). See Kiefer (1988) for an introduction into duration analysis.
To avoid cumbersome notation, we ignore that the regional unemployment rate is a time-varying covariate.
An alternative identification strategy, as used by Munch et al. (2006), Van Vuuren and van Leuvensteijn (2007) and De Graaff and van Leuvensteijn (2013) is to exploit the multiple spell feature of the data. If multiple unemployment spells are available for a specific employee and if the homeownership status of this employee varies over these spells, then the effect of homeownership on unemployment duration is theoretically identified. The existence of multiple spells ensures in this strategy that the modelled unobserved heterogeneity distribution captures “within individual” effects. However, using this strategy is not an option in our case. Only 105 individuals in our sample have two or more non-left-censored unemployment spells during their observation period. Among these 105 individuals, only six workers change their housing status.
To avoid cumbersome notation, we simplified the notation for theta.
The methodology as advocated by these authors boils down to the assumption that a sample consists of a finite number of subsamples with different levels of time-invariant unobservable effects. Then, for all subsamples the corresponding proportions are estimated as well as the impact of the unobserved differences on the outcomes.
We impose this normalisation since we allow for a constant term in the vector of observed characteristics x.
We take both the locations and the probabilities of the mass points to be unknown parameters without constraining the correlation between \(u_{1},\, u_{2,}\) and \(v\). Allowing only perfect correlation or no correlation or a priori limiting the number of heterogeneity types to an arbitrary number—the latter constraint is adopted in most of the mentioned former contributions—may lead to biased estimates, as shown by Gaure et al. (2007). The estimation procedure for gathering the probabilities and locations of the mass points is implemented according to the latter authors.
\(1-\exp (-0.50) = 0.39\).
The percentages that we mention have been derived from the EU-SILC database by Dol and Neuteboom (2009).
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Acknowledgments
We thank Bart Cockx, Gerdie Everaert, Carine Smolders, Claire Dujardin, Andrew J. Oswald, Jan Rouwendal, Aico van Vuuren, Michael Rosholm, Tobias Brändle and two anonymous referees for their constructive comments during the development of this paper. We also benefited from comments received at various national conferences and workshops, the 2013 Spring Meeting of Young Economists (Aarhus, June 2013) and the 2013 EALE Conference (Torino, September 2013). Finally, we gratefully acknowledge support from the Policy Research Centre ‘Steunpunt Fiscaliteit en Begroting’ funded by the Flemish government.
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Baert, S., Heylen, F. & Isebaert, D. Does Homeownership Lead to Longer Unemployment Spells? The Role of Mortgage Payments. De Economist 162, 263–286 (2014). https://doi.org/10.1007/s10645-014-9236-6
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DOI: https://doi.org/10.1007/s10645-014-9236-6