Despite evidence that aggregate housing price are predictable, a random walk in time and independence in space are two maintained hypotheses in the empirical models for housing price measurement used by government and commercial companies. This paper examines the price discovery process in individual dwellings over time and space by relaxing both assumptions, using data from the Singapore private condominium market. We develop a model that tests directly the hypotheses that the prices of individual dwellings follow a random walk over time and that the price of an individual dwelling is independent of the price of a neighboring dwelling. The model is general enough to include other widely used models of housing price determination, such as Bailey, Muth, and Nourse (1963), Case and Shiller (1987) and Redfearn and Quigley (2000), as special cases. The empirical results clearly support mean reversion in housing prices and also diffusion of innovations over space. Our estimates of the level of housing prices, derived from a generalized repeat sales model, suggest that serial and spatial correlation matters in the computation of price indices and the estimation of price levels. investment returns is completely absent.
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Paper provided by EconWPA in its series Macroeconomics with number
0303011.
Find related papers by JEL classification: E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data R32 - Urban, Rural, and Regional Economics - - Production Analysis and Firm Location - - - Other Production and Pricing Analysis
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