What factors drive the price–rent ratio for the housing market? A modified present-value analysis

Kishor, N. Kundan; Morley, James

doi:10.1016/j.jedc.2015.06.006

Cited by 54 publications

(39 citation statements)

References 30 publications

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“…Kishor and Morley () report a similar finding that variation in risk premiums explains a large fraction of housing market volatility. Cochrane () argues that most asset market puzzles and anomalies are related to large discount rate/risk premium variation.…”

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confidence: 77%

“…Mian and Sufi () use detailed zip‐code‐level data to examine the role of subprime mortgage credit expansion in fueling house price appreciation prior to the recent financial crisis. Kishor and Morley () use an unobserved component model to estimate expectations of housing market fundamentals and investigate the sources of aggregate housing market volatility. Moench and Ng () estimate a hierarchical factor model of the housing market and examine the dynamic effects of housing market shocks on consumption.…”

Section: Summary Statistics Of Housing Markets Price Changesmentioning

confidence: 99%

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Understanding Housing Market Volatility

Fairchild¹,

Ma²,

Wu³

2015

J of Money Credit Banking

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The Campbell-Shiller present value formula implies a factor structure for the price-rent ratio of housing market. Using a dynamic factor model, we decompose the price-rent ratios of 23 major housing markets into a national factor and independent local factors, and we link these factors to the economic fundamentals of the housing markets. We find that a large fraction of housing market volatility is local and that the national factor has become more important than local factors in driving housing market volatility since 1999, consistent with the findings in Del Negro and Otrok (2007). The local volatilities mostly are due to time variations of idiosyncratic housing market risk premia, not local growth. At the aggregate level, the growth and interest rate factors jointly account for less than half of the total variation in the price-rent ratio. The rest is due to the aggregate housing market risk premium and a pricing error. We find evidence that the pricing error is related to money illusion, especially at the onset of the recent housing market bubble. The rapid rise in housing prices prior to the 2008 financial crisis was accompanied by both a large increase in the pricing error and a large decrease in the housing market risk premium.JEL codes: C32, G12, R31 Keywords: dynamic factor model, housing market, price-rent ratio, risk premium, money illusion.HOUSING MARKETS ARE PARTIALLY segmented. There does not exist a centralized market for housing assets. Demographic changes, household preferences for geographic locations, and climate plus inelastic land supply can lead We would like to thank the editor, Professor Pok-sang Lam, and two anonymous referees for insightful comments and suggestions. We also thank

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confidence: 77%

Section: Summary Statistics Of Housing Markets Price Changesmentioning

confidence: 99%

Understanding Housing Market Volatility

Fairchild¹,

Ma²,

Wu³

2015

J of Money Credit Banking

View full text Add to dashboard Cite

show abstract

“…is the regime-dependent intercept of * t pr . 5 From the perspective of an econometrician, it is more realistic to assume that neither the realizations of t S nor the transition probabilities are in his/her information set. That being the case, the practical version of the present value model to be estimated can be cast into a state space form subject to Markov switching, the measurement block comprises Equations ( 3…”

Section: The Modelmentioning

confidence: 99%

“…Adapted to the housing market, the present value model provides two key implications: 1) house prices and rents should be of the same order of integration and 2) if the two variables are both nonstationary in level but stationary in first differences, they should be cointegrated so that their ratio (i.e., the price-torent ratio) is stationary. Resorting to these features, quite a few papers have applied the present value model to stock market (e.g., Campbell and Ammer [3]) or housing market (e.g., Campbell et al [4] and Kishor and Morely [5]).…”

Section: Introductionmentioning

confidence: 99%

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The Present Value Model Revisited: An Application to the Italian Price-Rent Ratio

Kim¹,

Lim²

2015

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The present value model of asset prices a la Campbell and Shiller predicts the price-rent ratio in the housing market to be stationary. The observed movements in the actual price-rent ratio, often exhibiting large and long swings in the ratio, may put into question the validity of the standard present value model. In this paper, we allow for two sources of possibly unwieldy deviations in the price-rent ratio in the standard present value model, and examine the relative importance of the standard model and the two extra features using the Italian house market data. The results strongly support the validity of the standard present value model, in which the up-and downswings in the price-rent ratio are mostly explained by the movement in the expected risk premium, whereas the bubble and regime-switching expectation does not make sizable contributions to the price-rent ratio. Our results suggest that the standard present value model is a reliable vehicle in explaining the price-rent ratio.

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Forecasting house prices in OECD economies

Kishor

Marfatia

2017

Journal of Forecasting

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In this paper, we forecast real house price growth of 16 OECD countries using information from domestic macroeconomic indicators and global measures of the housing market. Consistent with the findings for the US housing market, we find that the forecasts from an autoregressive model dominate the forecasts from the random walk model for most of the countries in our sample. More importantly, we find that the forecasts from a bivariate model that includes economically important domestic macroeconomic variables and two global indicators of the housing market significantly improve upon the univariate autoregressive model forecasts. Among all the variables, the mean square forecast error from the model with the country's domestic interest rates has the best performance for most of the countries. The country's income, industrial production, and stock markets are also found to have valuable information about the future movements in real house price growth. There is also some evidence supporting the influence of the global housing price growth in out‐of‐sample forecasting of real house price growth in these OECD countries.

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What factors drive the price–rent ratio for the housing market? A modified present-value analysis

Cited by 54 publications

References 30 publications

Understanding Housing Market Volatility

Understanding Housing Market Volatility

The Present Value Model Revisited: An Application to the Italian Price-Rent Ratio

Forecasting house prices in OECD economies

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