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Social Housing Policy in a Segmented Housing Market: Indirect Effects on Markets and on Individuals

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  • Trond Arne Borgersen

    (Østfold University College)

Abstract

This paper analyses indirect effects of social housing policy (SHP) in a segmented housing market. A two segment-housing ladder, where equity determines up trading, shows how SHP-measures targeting either housing supply or housing demand impact market developments and individual housing careers. When addressing market developments the paper considers house prices and housing supply. Analysing housing careers we highlights the ability of households indirectly exposed to SHP to trade up a housing ladder. The segmented housing market model contains both multipliers, along the lines of the Balanced Budget Multiplier of Haavelmo (1945), and non-neutral price effects across segments. These features allow some novel results when discussing indirect effects of SHP. Relating SHP to up-trading and a housing ladder where households simultaneously act as buyers and sellers, we first of all show the effect of SHP on the supply of used homes, an important part of housing supply. Second, this framework makes us able to position crowding-out across market segments. Both features are novel in the SHP-discussion. The paper also shows how SHP might create negative indirect effects on the up-trading ability of households that do not benefit from SHP measures.

Suggested Citation

  • Trond Arne Borgersen, 2019. "Social Housing Policy in a Segmented Housing Market: Indirect Effects on Markets and on Individuals," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 8(2), pages 1-21, December.
    • Handle: RePEc:sek:jijoes:v:8:y:2019:i:2:p:1-21
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    References listed on IDEAS

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    1. Scanlon, Kathleen & Fernández Arrigoitia, Melissa & Whitehead, Christine M E, 2015. "Social housing in Europe," LSE Research Online Documents on Economics 62938, London School of Economics and Political Science, LSE Library.
    2. Erling Røed Larsen, 2014. "The Engel Curve of Owner-Occupied Housing Consumption," Journal of Applied Economics, Taylor & Francis Journals, vol. 17(2), pages 325-352, November.
    3. Jeremy C. Stein, 1995. "Prices and Trading Volume in the Housing Market: A Model with Down-Payment Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 379-406.
    4. Erling Røed Larsen, 2014. "The Engel curve of owner-occupied housing consumption," Journal of Applied Economics, Universidad del CEMA, vol. 17, pages 325-352, November.
    5. Sinai, Todd & Waldfogel, Joel, 2005. "Do low-income housing subsidies increase the occupied housing stock?," Journal of Public Economics, Elsevier, vol. 89(11-12), pages 2137-2164, December.
    6. Nordvik, Viggo, 2006. "Selective housing policy in local housing markets and the supply of housing," Journal of Housing Economics, Elsevier, vol. 15(4), pages 279-292, December.
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    Citations

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    Cited by:

    1. Xue Bai & Zhaoyu Xie & Bart Julien Dewancker, 2022. "Exploring the Factors Affecting User Satisfaction in Poverty Alleviation Relocation Housing for Minorities through Post-Occupancy Evaluation: A Case Study of Pu’er," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    2. Klára Čermáková & Eduard Hromada, 2022. "Change in the Affordability of Owner-Occupied Housing in the Context of Rising Energy Prices," Energies, MDPI, vol. 15(4), pages 1-18, February.
    3. Shangfa Hou & Jiaying Wang & Degui Zhu, 2022. "Has the Newly Imposed Property Tax Controlled Housing Prices? An Analysis of China’s 2009–2020 Interprovincial Panel Data," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    4. Trond-Arne Borgersen, 2022. "A Housing Market with Cournot Competition and a Third Housing Sector," International Journal of Economic Sciences, European Research Center, vol. 11(2), pages 13-27, November.
    5. Raul-Tomas Mora-Garcia & Maria-Francisca Cespedes-Lopez & V. Raul Perez-Sanchez, 2022. "Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times," Land, MDPI, vol. 11(11), pages 1-32, November.
    6. Ondřej Bednář & Andrea Čečrdlová & Božena Kadeřábková & Pavel Řežábek, 2022. "Energy Prices Impact on Inflationary Spiral," Energies, MDPI, vol. 15(9), pages 1-25, May.
    7. Judyta Kabus & Michał Dziadkiewicz, 2023. "Modern Management Methods in the Area of Public Housing Resources in the Community," Sustainability, MDPI, vol. 15(10), pages 1-28, May.

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    More about this item

    Keywords

    Housing market structure; social housing policy; indirect effects;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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