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Does large volatility help?—stochastic population forecasting technology in explaining real estate price process

  • Yuan Cheng
  • Xuehui Han

    ()

This paper investigates the association between real estate demand and the volatility of population changes. In a financial liberalized housing market, the housing mortgage loan implies insurance function to homeowners through the default option. Larger expected volatilities in the population imply a higher value of the default option. When analyzing the impact of the long-term population development on housing prices, the traditional deterministic population forecasting employed by previous research provides limited credibility. By means of the newly developed stochastic population forecasting methodology and counterfactual numerical simulations, we found a huge volatility associated with long-term population forecasting. A positive correlation between the expected volatility of population changes and real estate demand is ascertained. Copyright Springer-Verlag 2013

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File URL: http://hdl.handle.net/10.1007/s00148-010-0349-1
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Article provided by Springer in its journal Journal of Population Economics.

Volume (Year): 26 (2013)
Issue (Month): 1 (January)
Pages: 323-356

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Handle: RePEc:spr:jopoec:v:26:y:2013:i:1:p:323-356
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  1. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2009. "Moral and Social Constraints to Strategic Default on Mortgages," EIEF Working Papers Series 0905, Einaudi Institute for Economics and Finance (EIEF), revised Jun 2009.
  2. Nathalie Girouard & Mike Kennedy & Paul van den Noord & Christophe André, 2006. "Recent House Price Developments: The Role of Fundamentals," OECD Economics Department Working Papers 475, OECD Publishing.
  3. Andrew B. Abel, 2002. "The Effects of a Baby Boom on Stock Prices and Capital Accumulation in the Presence of Social Security," NBER Working Papers 9210, National Bureau of Economic Research, Inc.
  4. Jan Hoem & Dan Madien & Jørgen Nielsen & Else-Marie Ohlsen & Hans Hansen & Bo Rennermalm, 1981. "Experiments in modelling recent Danish fertility curves," Demography, Springer, vol. 18(2), pages 231-244, May.
  5. 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.
  6. Andrew B. Abel, 2001. "Will Bequests Attenuate The Predicted Meltdown In Stock Prices When Baby Boomers Retire?," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 589-595, November.
  7. Han, Xuehui, 2010. "Housing demand in Shanghai: A discrete choice approach," China Economic Review, Elsevier, vol. 21(2), pages 355-376, June.
  8. Hilary W. Hoynes & Daniel L. McFadden, 1996. "The Impact of Demographics on Housing and Nonhousing Wealth in the United States," NBER Chapters, in: The Economic Effects of Aging in the United States and Japan, pages 153-194 National Bureau of Economic Research, Inc.
  9. James B. Kau & Taewon Kim, 1994. "Waiting to Default: The Value of Delay," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 22(3), pages 539-551.
  10. Chester Foster & Robert Order, 1985. "FHA Terminations: A Prelude to Rational Mortgage Pricing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 13(3), pages 273-291.
  11. Mario Fortin & André Leclerc, 2000. "Demographic Changes and Real Housing Prices in Canada," Cahiers de recherche 00-06, Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke.
  12. James M. Poterba, 2001. "Demographic Structure And Asset Returns," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 565-584, November.
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