The recent financial crisis caused by a collapse of the housing market propelled the U.S. economy into the Great Recession. A notable development during the crisis period was a slump in business investment in tandem with a sharp decline in land prices (Figure 1). The crisis has generated substantial interest in understanding the links between the housing market and the macroeconomy. Although it is widely accepted that house prices could have an important influence on macroeconomic fluctuations, quantitative studies in a general equilibrium framework have been scant.
This paper aims to fill part of this gap by modeling, through econometric estimation, the links between land-price dynamics and macroeconomic fluctuations in a quantitative general equilibrium framework. We focus on land prices because most of the fluctuations in house prices are driven by land prices rather than by the cost of structures (Davis and Heathcote, 2007). We first establish evidence that land prices move together with macroeconomic variables not just in the Great Recession period, but also for the entire sample period from 1975 to 2010.
The first column of Figure 2 displays the estimated impulse responses of land prices and business investment following a shock to the land price series. These impulse responses are estimated from a bivariate Bayesian vector autoregression (BVAR) model with the Sims and Zha (1998) prior. A positive shock to land prices leads to persistent increases in both land prices and business investment. The last two columns of the figure show that the shock also leads to persistent increases in labor hours and consumption, although the magnitudes of the responses are not as large as that of investment.
To understand these salient features of the data, we build a dynamic stochastic general equilibrium (DSGE) model that is a generalization of Kiyotaki and Moore (1997). A strand of recent DSGE literature on house prices assumes that a subset of households are credit constrained and these households use land or houses as collateral to finance consumption expenditures (Iacoviello, 2005; Iacoviello and Neri, 2010; Favilukis, Ludvigson, and Nieuwer-burgh, 2011). These models with credit-constrained households are capable of explaining positive co-movements between house prices and consumption expenditures, but in general they have difficulty delivering positive co-movements between land prices and business investment (Iacoviello and Neri, 2010). To overcome this difficulty, we assume that firms, instead of households, are credit constrained. In particular we assume that firms finance investment spending by using land as a collateral asset. Thus, in our model, a shock that drives up land prices raises firms’ borrowing capacity and facilitates an expansion in investment and production.
