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Understanding the behaviour of house prices and household income per capita in South Africa: Application of the asymmetric autoregressive distributed lag model

Author

Listed:
  • Anthanasius Fomum Tita

    (University of Stellenbosch)

  • Pieter Opperman

    (University of Stellenbosch)

Abstract

Homeownership by the lower and middle-income households is crucial to create wealth, particularly for South Africa with high levels of economic and wealth inequality. However, scholarship has paid little attention to how income affects the affordable housing market segment despite its systemic importance to the South African economy. This study employs the asymmetric autoregressive distributed lag model to study the effect of household income per capita on the affordable house prices in South Africa using quarterly data from 1985 to 2016. The results revealed the presence of an asymmetric long-run relationship between affordable house prices and household income per capita. The estimated asymmetric long-run coefficients of logIncome[+] and longIncome[-] are 1.080 and -4.354 respectively implying that a 1% increase/decrease in household income per capita induces a 1.08% rise/4.35% decline in affordable house prices everything being equal. We argue that given the 71.4% market share of affordable housing in all residential properties in South Africa, a persistent fall in household income can trigger a systemic crisis, particularly with mortgage securitization. Thus, policymakers should closely monitor the practice of mortgage securitization, particularly in the affordable market segment to avoid systemic risk to the economy.

Suggested Citation

  • Anthanasius Fomum Tita & Pieter Opperman, 2024. "Understanding the behaviour of house prices and household income per capita in South Africa: Application of the asymmetric autoregressive distributed lag model," ERSA Working Paper Series 68, Economic Research Southern Africa.
  • Handle: RePEc:rza:ersawp:68
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    File URL: https://ersawps.org/index.php/working-paper-series/article/view/68/45
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    Cited by:

    1. is not listed on IDEAS
    2. Kabundi, Alain & Poon, Aubrey & Wu, Ping, 2023. "A time-varying Phillips curve with global factors: Are global factors important?," Economic Modelling, Elsevier, vol. 126(C).
    3. Dladla, Pholile & Malikane, Christopher, 2022. "Inflation dynamics in an emerging market: The case of South Africa," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 262-271.
    4. Merrino, Serena, 2022. "Monetary policy and wage inequality in South Africa," Emerging Markets Review, Elsevier, vol. 53(C).
    5. Liu, Zhen & Ngo, Thanh Quang & Saydaliev, Hayot Berk & He, Huiyuan & Ali, Sajid, 2022. "How do trade openness, public expenditure and institutional performance affect unemployment in OIC countries? Evidence from the DCCE approach," Economic Systems, Elsevier, vol. 46(4).

    More about this item

    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • 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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