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Technological Progress In A Model Of The Housing Land Cycle


  • Richard Arnott

    (Department of Economics, Boston College)

  • Alex Anas



A stationary-state perfect foresight model is developed in which housing and land are treated as investment assets convertible to each other at some costs. Investors hold either land or housing and are heterogeneous in the i. i. d idiosyncratic shocks to their conversion costs in every time period. Hence, there are endogenously determined probabilities that a unit of land will be converted to housing ("construction probability") in any given time period. This model is used to analyze the effects of a decrease in construction cost on the asset prices of land and housing, on housing rent and on the stationary stocks of land and housing. A decrease in construction cost always raises land value, that may either raise or lower housing values and increases both the construction and the demolition probabilities. The housing stock increases (decreases) if the construction probability increases proportionally more (less) than the demolition probability. Since housing rent is inversely related to the stock of housing, the fall in construction costs may cause rents to rise. Thus paradoxically, technological progress may hurt renters. The moral of the model is important: in contrast to models of the housing market without land or to models of the housing market without land or to models in which land price is exogenous, the long run supply price of housing is not fully determined by construction cost, but depends as well on demolition cost and on the endogenous value of the land.

Suggested Citation

  • Richard Arnott & Alex Anas, 1993. "Technological Progress In A Model Of The Housing Land Cycle," Boston College Working Papers in Economics 240, Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:240

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    Cited by:

    1. Mansur, Erin T. & Quigley, John M. & Raphael, Steven & Smolensky, Eugene, 2002. "Examining policies to reduce homelessness using a general equilibrium model of the housing market," Journal of Urban Economics, Elsevier, vol. 52(2), pages 316-340, September.
    2. Gibb, Kenneth, 2000. "Modelling Housing Choice and Demand in a Social Housing System: The Case of Glasgow," Berkeley Program on Housing and Urban Policy, Working Paper Series qt40j453z6, Berkeley Program on Housing and Urban Policy.
    3. Anas, Alex & Arnott, Richard J., 1997. "Taxes and allowances in a dynamic equilibrium model of urban housing with a size--quality hierarchy," Regional Science and Urban Economics, Elsevier, vol. 27(4-5), pages 547-580, August.
    4. Kenneth Gibb & Geoff Meen & Daniel Mackay, 2001. "Choice and Demand in a Social Housing System: Policy Simulations for Glasgow," ERES eres2001_172, European Real Estate Society (ERES).
    5. Alex Anas, 2003. "Taxes on Buildings and Land in a Dynamic Model of Real Estate Markets," Urban/Regional 0302004, University Library of Munich, Germany.
    6. André De Palma & Stef Proost & Saskia Van Der Loo, 2013. "A small model of equilibrium mechanisms in a city," Working Papers halshs-00841105, HAL.
    7. Quigley, John M. & Raphael, Steven & Smolensky, Eugene, 2001. "Homelessness in California," Berkeley Program on Housing and Urban Policy, Working Paper Series qt2pg3f4ns, Berkeley Program on Housing and Urban Policy.

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