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The impact of housing consumption value on the spatial distribution of welfare

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  • Kilgarriff, Paul
  • Charlton, Martin
  • Foley, Ronan
  • O'Donoghue, Cathal

Abstract

The measure of a household's income should include not only monetary components but also non-monetary components and in-kind benefits, such as imputed rent. Imputed rent is the rent an owner can expect to receive were the house on the rental market. This study examined the impact of net imputed rent on the distribution of income in a spatial context. The spatial impact of net imputed rent, mortgage payments, private rent, public rent (social housing schemes) and reverse mortgage/annuity on the spatial distribution of disposable income was examined for the year 2011. A spatial microsimulation model, simulated model of the Irish local economy (SMILE), was used to simulated disposable income at a detailed spatial scale. Rental and property values are estimated at a spatial scale adopting the kriging methodology. The created rental and property data were merged into the SMILE simulated dataset to examine the impact of housing on the spatial distribution of disposable income at a small area level. Results show that the imputed cash flows from property ownership decreases the income share of those at the bottom of the income distribution and is inequality increasing, except in the case of those aged 65 +. Spatially the benefits of housing are greatest in urban areas where property values are highest. The small area measurements of imputed rent highlight the dis-equalising impact imputed rent and housing wealth has on inequality; the rich being able to consume more housing.

Suggested Citation

  • Kilgarriff, Paul & Charlton, Martin & Foley, Ronan & O'Donoghue, Cathal, 2019. "The impact of housing consumption value on the spatial distribution of welfare," Journal of Housing Economics, Elsevier, vol. 43(C), pages 118-130.
  • Handle: RePEc:eee:jhouse:v:43:y:2019:i:c:p:118-130
    DOI: 10.1016/j.jhe.2018.11.002
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    More about this item

    Keywords

    Housing; Data interpolation; Spatial analysis; Inequality; Microsimulation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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