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Vale, S. & Camões, F. (2015). Household indebtedness and housing valuation: a quantile regression analysis using Portuguese microdata. 15th EBES Conference.

S. D. Vale and F. H. Costa,  "Household indebtedness and housing valuation: a quantile regression analysis using Portuguese microdata", in 15th EBES Conf., Lisboa, 2015

@misc{vale2015_1732200823653,
	author = "Vale, S. and Camões, F.",
	title = "Household indebtedness and housing valuation: a quantile regression analysis using Portuguese microdata",
	year = "2015",
	howpublished = "Outro",
	url = "http://www.ebesweb.org/Conferences/15th-EBES-Conference-Lisbon.aspx"
}

TY  - CPAPER
TI  - Household indebtedness and housing valuation: a quantile regression analysis using Portuguese microdata
T2  - 15th EBES Conference
AU  - Vale, S.
AU  - Camões, F.
PY  - 2015
SN  - 978-605-64002-9-2
CY  - Lisboa
UR  - http://www.ebesweb.org/Conferences/15th-EBES-Conference-Lisbon.aspx
AB  - The period that preceded the 2008 Great Recession fetched a steady increase in household indebtedness and with it an increased concern with both household sustainability and its eventual negative impact on the financial system. Household debt is related to its wellbeing imposes additional constraints on households, and contributes to extend the economic downturn length, as well as to prolong recovery.  Data show that in spite facing the same adverse economic environment not all households get indebted, a significant segment of these households having such a low income level that are kept off the credit market, and a segment at the upper tail of the income and wealth distribution having no need to apply for loans. In this paper we study Portuguese households’ indebtedness inequality by income and wealth status and how it is related to the valuation of its main residence property. We try to address how during the 1990s and 2000s the emergence of a wealth perception related to housing valuation may have secure valuable collateral and contribute to household debt overhang prompting a sustainable rolling debt scheme.  We use microdata from the 2010 Portuguese Household Finance and Consumption Survey and estimate quantile regressions trying to understand the entire conditional distribution of debt and its relationship with the selected regressions.  By fixing this empirical technique it is possible to estimate covariate effects at different points of the debt distribution while controlling for individual factors such as wealth and income levels or the heterogeneous patterns of house price valuation. Among the explanatory variables in our model we include socio-economic characteristics, the main dwelling valuation, adverse past changes and expectations regarding a close future period as well as the price and valuation of the main dwelling. We find strong nonlinearities in the coefficients particularly accentuated for those representing the number of dependents in a household and the household type, illustrating the relevance of the socio-economic household characteristics in the explanation of indebtedness. Further, a higher property valuation seems to indicate a higher level of indebtedness, accentuated through the conditional distribution.
ER  -