A continuous spatio-temporal model for house prices in the USA

Márcio Laurini

The Annals of Regional Science, 2017, vol. 58, issue 1, No 10, 235-269

Abstract: Abstract We revisit the studies on the evolution of house prices in the USA using a spatio-temporal model estimated using a Bayesian method. This method introduces a new specification of an error correction model with random effects measured continuously in space. This model allows observing the deviations from the co-integration relationship in each analyzed location and a clearer interpretation of the house price dynamics between 1975 and 2011 for 381 metropolitan areas in the USA. The results indicate the presence of a housing price cycle, consistent with the patterns observed in the analyzed period.

JEL-codes: C11 C21 C33 (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s00168-016-0801-6

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