Un modèle de prix de l'immobilier pour estimer l'ampleur de la bulle américaine
AbstractHouse prices in the Us have experienced a sharp rise between 2000 and 2006, followed by a historical decline (nominal prices had not decreased since World War II), which resembles the correction of a speculative bubble. To assess the existence and the magnitude of this bubble, we estimate a model of house prices with different structural determinants in rural and urban areas. In rural areas, housing supply can adjust to demand (through new constructions) and prices should reflect construction costs. In urban areas, where housing supply is constrained, prices are driven by fluctuations in housing demand. We estimate an error correcting model between 1975 and 2000 and find that house prices in the us are suitably explained by such determinants during this period, and that prices in urban and rural areas have a comparable weight in the national prices. At their peak in 2006, house prices in the Us were approximately 30% higher than suggested by this model. We consider that this overvaluation was mainly due to a relaxation of mortgage credit standards, speculative behaviour of economic agents due to excessive expectations of housing price increases and possibly a certain lack of competition in the construction industry. Classification JEL : E37, G12, R21, R37
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Bibliographic InfoArticle provided by Presses de Sciences-Po in its journal Revue économique.
Volume (Year): 60 (2009)
Issue (Month): 1 ()
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Find related papers by JEL classification:
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
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- Jean-Paul Pollin, 2010. "Commentaire : Articuler les explications pour comprendre la bulle immobilière," Économie et Statistique, Programme National Persée, vol. 438(1), pages 173-179.
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