Gabriel S. Lee

Time-Varying Uncertainty and the Credit Channel

We extend the Carlstrom and Fuerst (1997) agency cost model of business cycles by including time varying uncertainty in the technology shocks that affect capital production. We first demonstrate that standard linearization methods can be used to solve the model yet second moments enter the economys equilibrium policy functions. We then demonstrate that an increase in uncertainty causes, ceteris paribus, a fall in investment supply. A second key result is that time varying uncertainty results in countercyclical bankruptcy rates - a finding which is consistent with the data and opposite the result in Carlstrom and Fuerst. Third, we show that persistence of uncertainty affects both quantitatively and qualitatively the behavior of the economy. However, the shocks to uncertainty imply a quantitatively small role for uncertainty over the business cycle. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.)

The Endowment Effect, Status Quo Bias and Loss Aversion: Rational Alternative Explanation

The endowment effect, status quo bias, and loss aversion are robust and well documented results from experimental psychology. They introduce a wedge between the prices at which one is willing to sell or buy a good. The objective of this paper is to address this wedge. We show that the presence of asymmetric information in a rational-agent framework can also account for the endowment effect, status quo bias and loss aversion without invoking psychology-based explanations proposed in the past.

Housing cycles and the period of production

US fixed residential investment is one of the most periodic economic time series. A theory of housing cycles is analysed on the basis of the period of housing construction. Substantial lags between planning and completion phases of housing construction cause housing investment to respond cyclically to exogenous shocks in demand and production costs. Known structural parameters of the housing industry provide sharp numerical benchmarks for the resulting dynamic system. The calibrated model with two construction lags describes the housing data and cycles well.

Rationale Erklärungen für Immobilienpreis Bubbles: Die Auswirkungen von Risikoschocks auf die Wohnimmobilienpreisvolatilität und die Volatilität von Investitionen in Wohnimmobilien

Abstract The dramatic world-wide housing boom and bust cycles during the last few years are often described in the media as “bubbles” and were largely caused by irrational exuberance due to the liberalization of housing finance (i.e. credit market irregularities in the U.S.: the subprime markets and mortgage structured products). Following Dorofeenko et al (2011), this paper, however, argues that many of the business and housing stylized facts, especially, the U.S. housing price and residential investment volatilites can be explained by analyzing the role of uncertainty (risk) in the framework of a Real Business Cycle model that includes a housing sector with financial information frictions. Consequently, we show for the U.S., these large housing price and residential investment boom and bust cycles are at least were driven largely by economic fundamentals with irrationality (or psychology) at most in the background.

Effects of Macroeconomic Uncertainty and Labor Demand Shocks on the Housing Market: Effects of Macroeconomic Uncertainty and Labor Demand Shocks

This paper shows that macroeconomic uncertainty affects the housing market in two signi?ficant ways. First, uncertainty shocks adversely affect housing prices but not the quantities that are traded. Controlling for a broad set of variables in fi?xed-effects regressions, we ?find that uncertainty shocks reduce both housing prices and median sales prices in the amount of 1.4% and 1.8%, respectively, but the effect is not statistically signi?cant for the percentage changes of all homes sold. Second, when both uncertainty and local demand shocks are introduced, the effects of uncertainty on the housing market dominate that of local labor demand shocks on housing prices, median sell prices, the share of houses selling for loss, and transactions. The aforementioned effects are largest for the states that exhibit relatively high housing price volatilities, suggesting real options effects in the housing market during the times of high uncertainty.

Effects of Uncertainty and Labor Demand Shocks on the Housing Market

This paper investigates the simultaneous effects of uncertainty and locallabor demand shocks on the U.S. housing market. We use binaryuncertainty indicators and a Bartik (1991) index to quantify bothuncertainty and labor demand shocks. Controlling for a broad set ofvariables in fixed-effects regressions, we find uncertainty shocks exhibitsmall adverse level effects, where housing prices and median sell pricesdecrease in the amount of 1.4% and 1.8%, respectively, and thepercentage loss of houses selling increase by .52%-points. Moreimportantly, however, when both shocks are introduced the effects ofuncertainty shocks on the housing market dominate that of local labordemand shocks on housing prices, median sell prices, the share of housesselling for loss, transactions and homes sold as foreclosure. These resultslends to the support for the presence of real options effects in the housingmarket.