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Determinants of house prices and new construction activity: An empirical investigation of the Namibian housing market

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  • Tafirenyika Sunde
  • Paul-Francois Muzindutsi

    (Namibia University of Science and Technology, Namibia
    University of KwaZulu-Natal, South Africa)

Abstract

The demand for and supply of housing are heterogeneous and differ across countries, provinces and cities. In the Namibian context, the housing market has experienced a substantial increase in house prices. Such an unexpected growth rate in house prices suggests that the Namibian housing market may not be sustainable in the long term. This means that there is a high probability of a housing price bubble in Namibia if the house prices continue to increase. The aim of this study was to conduct an econometric analysis of endogenous and exogenous determinants of house prices and new construction activity in Namibia. This study also attempted to establish whether there is evidence of overvaluation of house prices in the Namibian housing market and this is important in identifying the possibility of a housing price bubble in Namibia. In addition, the study is relevant during the current period where Namibia is faced with a continuous increase in house prices. A restricted VAR model with a Johansen cointegration approach was used to analyse monthly data from January 2000 to December 2014. The selection of the data set was aimed at providing representatives for various housing demand drivers and housing supply determinants. For modelling on the supply side, new construction investment as a percentage of GDP was employed. The other variables incorporated as exogenous variables include the economic growth rate, the consumer price index, nominal wages as a percentage of GDP, the short-term interest rate, mortgage loans as a share of GDP and population in the 15-64 cohort as a percentage of GDP. Results show that the house price index in Namibia has proved more sensitive to changes in population, mortgage loans and inflation; whereas the construction activities were found to be more sensitive to the house price index and inflation. Granger causality results show that there is a bidirectional causality between the house price index and new construction activity in Namibia. The study therefore found evidence of overvaluation of house prices in the Namibian housing market, which may lead to a house price bubble in the Namibian economy. Namibian policymakers, through the Bank of Namibia, should come up with policies which ensure that the majority of mortgages given by the banks are for constructing new houses instead of financing the purchase of existing houses.

Suggested Citation

  • Tafirenyika Sunde & Paul-Francois Muzindutsi, 2017. "Determinants of house prices and new construction activity: An empirical investigation of the Namibian housing market," Journal of Developing Areas, Tennessee State University, College of Business, vol. 51(3), pages 389-407, July-Sept.
    • Handle: RePEc:jda:journl:vol.51:year:2017:issue3:pp:389-407
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    1. Changwen Zhao & Jiang Du, 2007. "Causality Between FDI and Economic Growth in China," Chinese Economy, Taylor & Francis Journals, vol. 40(6), pages 68-82, November.
    2. Holly, Sean & Jones, Natasha, 1997. "House prices since the 1940s: Cointegration, demography and asymmetries," Economic Modelling, Elsevier, vol. 14(4), pages 549-565, October.
    3. Kostas Tsatsaronis & Haibin Zhu, 2004. "What drives housing price dynamics: cross-country evidence," BIS Quarterly Review, Bank for International Settlements, March.
    4. Theodore Panagiotidis & Panagiotis Printzis, 2016. "On the macroeconomic determinants of the housing market in Greece: a VECM approach," International Economics and Economic Policy, Springer, vol. 13(3), pages 387-409, July.
    5. Sheilla Nyasha & Nicholas M. Odhiambo, 2015. "The Impact of Banks and Stock Market Development on Economic Growth in South Africa: an ARDL-bounds Testing Approach," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 9(1), March.
    6. Agnello, Luca & Schuknecht, Ludger, 2011. "Booms and busts in housing markets: Determinants and implications," Journal of Housing Economics, Elsevier, vol. 20(3), pages 171-190, September.
    7. Stiglitz, Joseph E, 1990. "Symposium on Bubbles," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 13-18, Spring.
    8. Charles Goodhart & Boris Hofmann, 2008. "House prices, money, credit, and the macroeconomy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 24(1), pages 180-205, spring.
    9. Matteo Iacoviello & Stefano Neri, 2010. "Housing Market Spillovers: Evidence from an Estimated DSGE Model," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(2), pages 125-164, April.
    10. Vahram Stepanyan & Mr. Tigran Poghosyan & Aidyn Bibolov, 2010. "House Price Determinants in Selected Countries of the Former Soviet Union," IMF Working Papers 2010/104, International Monetary Fund.
    11. Leung, Charles, 2004. "Macroeconomics and housing: a review of the literature," Journal of Housing Economics, Elsevier, vol. 13(4), pages 249-267, December.
    12. Richard Meese & Nancy Wallace, 2003. "House Price Dynamics and Market Fundamentals: The Parisian Housing Market," Urban Studies, Urban Studies Journal Limited, vol. 40(5-6), pages 1027-1045, May.
    13. Boris Hofmann, 2003. "Bank Lending and Property Prices: Some International Evidence," Working Papers 222003, Hong Kong Institute for Monetary Research.
    14. N. Apergis & A. Rezitis, 2003. "Housing prices and macroeconomic factors in Greece: prospects within the EMU," Applied Economics Letters, Taylor & Francis Journals, vol. 10(12), pages 799-804.
    15. Mankiw, N. Gregory & Weil, David N., 1989. "The baby boom, the baby bust, and the housing market," Regional Science and Urban Economics, Elsevier, vol. 19(2), pages 235-258, May.
    16. Karol Jan Borowiecki, 2009. "The Determinants of House Prices and Construction: An Empirical Investigation of the Swiss Housing Economy," International Real Estate Review, Global Social Science Institute, vol. 12(3), pages 193-220.
    17. Jorge M. Andraz & Paulo M.M. Rodrigues, 2010. "What causes economic growth in Portugal: exports or inward FDI?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 37(3), pages 267-287, August.
    18. Chung-Fu Lai, 2016. "Effects of Demographic Structure and Tax Policies on Real Estate Prices," Applied Economics and Finance, Redfame publishing, vol. 3(2), pages 88-96, May.
    19. Nicholas Apergis, 2003. "Housing Prices and Macroeconomic Factors: Prospects within the European Monetary Union," International Real Estate Review, Global Social Science Institute, vol. 6(1), pages 63-74.
    20. Nicholas Apergis, 2003. "Housing Prices and Macroeconomic Factors: Prospects within the European Monetary Union," International Real Estate Review, Asian Real Estate Society, vol. 6(1), pages 63-47.
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    More about this item

    Keywords

    house prices; property market; cointegration; VAR model; Namibia;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General

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