Nan-Kuang Chen

House Price, Mortgage Premium, and Business Fluctuations

This paper investigates the transmission mechanism of mortgage premium to characterize the relationship between the housing market and business cycle for the U.S. We find that mortgage premium is crucial for the amplification and propagation of the model to match the main properties of U.S. housing market and business cycles. The counterfactual analysis suggests that had the Federal Reserve raised the interest rate in 2003Q1, it would have curbed the housing market boom before the crisis, yet failed to alleviate the precipitous decline in housing market activity after the crisis. Moreover, the pre-emptive monetary policy aimed to contain the housing market boom can effectively lower volatilities of major economic aggregates; however, it also exerts a significantly negative effect on the levels of these economic aggregates. Thus, using monetary policy to stabilize asset price inflation involves a trade-off between the volatility and the level of economic activity.

STOCK PRICE VOLATILITY, NEGATIVE AUTOCORRELATION AND THE CONSUMPTION–WEALTH RATIO: THE CASE OF CONSTANT FUNDAMENTALS

Based on infinite horizon models, previous theoretical works show that the empirical stock price movement is not justified by the changes in dividends. The present paper provides a simple overlapping generations model with constant fundamentals in which the stock price displays volatility and negative autocorrelation even without changes in dividend. The horizon of the agents matters. In addition, as in recent empirical works, the aggregate consumption–wealth ratio ‘predicts’ the asset return. Thus, this framework may be useful in understanding different stylized facts in asset pricing. Directions for future research are also discussed.

Identifying and forecasting house prices: a macroeconomic perspective

This paper studies the forecasting performance of macroeconomic variables on housing returns and on the possible shifts of regimes in house price cycles. We motivate our empirical analysis based on a general equilibrium model, and use a Markov switching model to identify two regimes of housing returns: the high volatility (‘boom-bust’) regime and the low volatility (‘tranquil’) regime. Given US data –, we find that with a single-regime model inflation rate and federal funds rate perform better than other economic aggregates in predicting housing returns. Using the Markov switching model, inflation rate and the federal funds rate are the most consistent predictor for in-sample and out-of-sample forecast of the probability of the ‘boom-bust’ regime. The results imply that motives for inflation hedging and changes in monetary policy matter for the movements of future housing returns and the possible shifts of regimes in house price cycles.

Credit Constraint and the Asymmetric Monetary Policy Effect on House Prices

We study the possible asymmetric effect of monetary policy on house prices under different credit regimes. We first derive the implications of a theoretical model in which agents may be collateral‐constrained. We then empirically examine the implications of the model using the threshold vector autoregression model. Two different measures reflecting the tightness of the credit market are computed to serve as the threshold variable. We find that house prices react to a monetary shock initially more strongly but the effect is less persistent in a credit boom regime than in a normal credit regime. This result is consistent with the findings of our theoretical model.