Housing prices and inter-urban migration

Understanding the causes and consequences of human migration has long been of interest to urban and regional economists. Empirical studies build on the theoretical results of Roback (1982) and Mueser and Graves (1995) by estimating the effects of wages, housing prices, and amenities on inter-area migration. Findings with respect to amenities are clear (e.g., Rappaport 2007), and household-level studies consistently find that relative wages or incomes increase the probability that a household will select a given location (e.g., Berger and Blomquist 1992). In contrast, the results for housing prices are inconclusive. Studies that include area-level measures (e.g., median housing price for a metropolitan area) find a mix of negative, positive, and insignificant effects on inter-area migration decisions (e.g., Hunt and Mueller 2004). Many migration studies exclude housing price measures. This paper investigates the role of housing prices in influencing inter-urban household migration decisions. An important contribution of the study is the development of a new method for representing housing prices in migration analyses. Following the approach commonly used to model wages in studies of household migration, we identify the form of the utility function for which individual-specific housing prices can be predicted for unselected areas as a function of individual characteristics. Our theoretical results guide the development of an empirical measure of housing costs that accounts for the decision to own or rent and the cost of holding housing capital. We test our housing cost measure using the 2000 PUMS to identify point-to-point migration decisions for a large sample of college-educated males residing in 291 U.S. metropolitan areas. We estimate conditional logit models of metropolitan area choice, controlling for wages, a large range of amenities, and expected housing costs. Our key finding is that our proposed housing cost measure yields the expected results (higher housing prices reduce the probability that an area is selected), which is robust to alternative specifications and samples. We re-estimate our model using three alternative metropolitan area measures of housing costs: median house price, average apartment rent, and average urban land rent. We find that these measures consistently yield counterintuitive results.