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Housing and Financial Asset Allocations of Heterogeneous Homeowners

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  • Zhechun He

Abstract

Market constraints (e.g. borrowing constraint, no-short-selling constraint) are important for household portfolio choices especially for housing. A structural model naturally generates alternative portfolio regimes with different binding constraints. But empirically we cannot observe which households are constrained in safe, risky or housing finance and housing. We use a semiparametric approach on data from Wealth and Asset Survey (WAS) to determine this. We find distinct patterns of housing and financial assets allocation among homeowners by fitting a multivariate Gaussian mixture model via a censored data expectation-maximisation (EM) algorithm. Estimation results reveal that on average about 80% of the households are no-short-selling constrained in risky asset investment and with low net worth. Among other things, we find that households who are younger, less educated with lower income are more likely to be no-short-selling constrained in risky asset investment and with lower net worth. Our predicted regime classification is aligned to those of the structural model.

Suggested Citation

  • Zhechun He, 2017. "Housing and Financial Asset Allocations of Heterogeneous Homeowners," Discussion Papers 17/07, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:17/07
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    References listed on IDEAS

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    More about this item

    Keywords

    Sequence Risk; household finance; borrowing constraint; no-short-selling constraint; Gaussian mixture model; censored data EM algorithm; semi-parametric;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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