Determinants of Real House Price Dynamics

Abstract

We explore the dynamics of real house prices by estimating serial correlation and mean reversion coefficients from a panel data set of 62 metro areas from 1979-1995. The serial correlation and reversion parameters are then shown to vary cross sectionally with city size, real income growth, population growth, and real construction costs. Serial correlation is higher in metro areas with higher real income, population growth and real construction costs. Mean reversion is greater in large metro areas and faster-growing cities with lower construction costs. Empirically, substantial overshooting of prices can occur in high real construction cost areas, which have high serial correlation and low mean reversion, such as the coastal cities of Boston,

Exploring Metropolitan Housing Price Volatility

“…First, it builds upon the literature on the efficiency of housing markets and the predictability of real estate returns (see for example Case and Shiller, 1989, 1990, Gillen et al, 2001, Gu, 2002, Cappozza et al 2004, Miller and Sklarz, 1986, among others) because this paper incorporates a rational expectation model of home value appreciation that allows predictable expected appreciation rates. This paper also builds upon the literature in the return and risk characteristics of real estate (see Bond et al, 2003, Capozza et al, 2002, Capozza et al, 2003, Capozza et al 2004, Case et al, 1999, Goetzmann, 1993 by investigating the sources of the volatility of housing markets. It also builds upon the literature on the relations between the housing market and economy and demographics (see for example Case and Mayer, 1996, Clapp and Giaccotto, 1994, Dispasquale and Wheaton, 1994, Leung, 2003, Quigley, 1990, and Reichert, 1990, among others) because the dynamical interrelations between the housing volatility and economic and demographic variables are studied.…”

Immigration and housing rents in American cities

“…All of the adjustment in the short run comes through changes in the demand for space of residents. 11 For expected immigration shocks, or for learning about the dynamic effects of unexpected shocks, we have to consider both the adjustment of the housing supply, the response of native population, and changes in housing space consumption.…”

Immigrants and the City: The Relevance of Immigration on Housing Price Gradient

“…Even if neoclassical economic theory assumes that land is more valuable in city centers due to greater accessibility, and more amenities and employment opportunities (see, among others, [34][35][36][37][38]), other factors may affect this phenomenon. In the present case, we examined how a major evolution in Italy's demographics, with an increasing proportion of immigrants in its urban populations, might affect the housing price gradient, in terms of both sign and magnitude.…”

“…Their studies focused on the effect of location on the prices of land, from the inner city to the fringe: access to infrastructure, job opportunities, and amenities increases the prices of central areas versus fringe areas. DiPasquale & Wheaton [37], and Capozza et al [38] subsequently further developed this theory, focusing on different socio-economic conditions and amenities as key factors influencing the price gradient. While natural amenities have more effect on the housing price gradient between cities [39,40], proximity to important urban nodes influences it within them, especially in non-monocentric cities [41] and metropolitan areas.…”