John Landis (Institute of Urban and Regional Development, University of California at Berkeley) Vicki Elmer (Institute of Urban and Regional Development, University of California at Berkeley) Matt Zook (Institute of Urban and Regional Development, University of California at Berkeley)
Abstract
This paper uses employment and output in high-tech industries, venture capital funding, and the number of dot-com firms per 1000 private workers, at the metropolitan level, to identify their contribution to differences in housing market outcomes. Housing prices in New Economy markets are found to be higher, peakier and more volatile than in old economy markets. Homeownership rates are found to be lower in new economy metro areas while crowding is found to be higher. Although the distribution of housing values, cost, and rents was more equal in New Economy markets, the cause would seem to be differences in metro area income levels, with poorer MSA's having greater inequalities. Regression analysis is used to identify the contribution of traditional supply and demand factors such as job growth, income, residential construction, as well as New Economy indicators, to housing market outcomes. Rather than being fundamentally different, New Economy housing markets are found to be faster and more extreme versions of traditional housing markets.
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