We characterize the dynamics of relative house prices, construction rates and population growth across US cities. In response to fluctuations in relative incomes, we find that population growth rates adjust more rapidly than construction rates in the short run and that price appreciation exhibits considerable serial correlation in the shortrun and mean reversion in the long-run. We develop a competitive search model of the housing market in which construction, the entry of buyers, house prices and rents are endogenously determined in equilibrium. Our theory generates dynamics that are qualitatively consistent with our empirical observations. In particular, in a version of the economy calibrated to match long-run features of the housing market in U.S. cities, variation in the time it takes to sell a house (i.e. the house's liquidity) induces house values and transaction prices to exhibit momentum, or serially correlated growth.
house prices liquidity search construction dynamic panel