This paper studies the relationship between the house price‐to‐income ratio (PIR) and economic fundamentals, and investigates the long‐horizon forecastability of the PIR. We first construct a small DSGE model to derive a dynamic expression of PIR, linking PIR to macroeconomic fundamentals and the stance of monetary policy. Based on the theoretically derived PIR, variance decomposition suggests that interest rate and real income growth appear to be the main sources for the deviations of PIR. Using the difference between actual PIR and the estimated fundamental PIR as the predictor, we find that both in‐sample and out‐of‐sample forecastability of the PIR over the future dynamics of PIR are significant.

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 1975Q1-2008Q4, 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 insample 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.

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