Abstract
Using two unique datasets from different neighborhoods in Houston, TX, which provide us data for houses with similar structure (or even same house), we test the standard model of housing values to determine how the formation of households’ expectations regarding price appreciations affects housing market prices. Using these datasets we are able to address previously encountered problems in the literature such as the lack of adjustment for quality differences, the connection between prices and rents for the different type of housing, and the spatial distribution of housing. We test whether consumer behavior leads to potentially unstable market conditions with price bubbles. Our results suggest that appreciation expectations are based on past price appreciation but at the same time they depend on the fundamental factors such as, locational and structural. These findings show a hybrid consumer behavior of rational and adaptive expectations. Finally, we show how these expectations could sometimes lead to unstable price levels.
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Notes
Stiglitz (1990) explains in detail how changes in expectations of future price of assets could lead to bubbles.
Price instability refers to a process in which, after experiencing a shock, house prices never return to the long run equilibrium value. Alternatively, house prices change erratically as time passes. In this case, one can assess whether there is any evidence for potential housing bubble pressures across different locations within a single metro area.
Dusansky and Koc (2007) show that housing is an investment asset with the potential of capital gains.
The sum of the all costs such as maintenance, repair etc. may not be exactly proportional to value, but most authors make this assumption for convenience and ease of exposition.
Since the second micro dataset contains observations for list prices and rents of the same houses, the hedonic price method is not applied.
The issue of multicollinearity is less severe when there are a large number of observations. However, the issue of multicollinearity becomes more severe when there are a small number of observations. Therefore, to circumvent the problem of multicollinearity, we use rents estimated only as a function of square feet of the house (SF).
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Hattapoglu, M., Hoxha, I. The Dependency of Rent-to-Price Ratio on Appreciation Expectations: An Empirical Approach. J Real Estate Finan Econ 49, 185–204 (2014). https://doi.org/10.1007/s11146-013-9423-2
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DOI: https://doi.org/10.1007/s11146-013-9423-2