This paper models co-movements in house prices using a copula-based approach that allows for asymmetric contemporaneous and dynamic dependence between prices in different locations. The models consider both US co-movements across different census divisions and international co-movements across different OECD countries. Results show evidence of strong contemporaneous tail dependence among US census divisions, indicating that extreme price movements in different areas tend to happen in tandem. On the international level, by contrast, results find almost no evidence of contemporaneous or dynamic linkages in house price movements between different countries. These results hold important implications for informing upon risk embedded in mortgage backed securities.
This is a preview of subscription content, log in to check access.
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
Global CDO volume numbers come from a Securities Industry and Financial Markets Association press release, dated 11/21/2011.
A debt of gratitude is owed to Gavin Asdorian for generously providing the data.
See “Housing Boom North of the Border” in the 3/29/2011 issue of the Wall Street Journal.
When using generalized error distributions for the innovations, four of the series (S. Atlantic, France, Netherlands, and Belgium) failed to converge. Thus, those series instead assume that errors follow Gaussian distributions.
Allen F (2005) Modelling financial instability. Natl Inst Econ Rev 192:57–67
Bollerslev T (1986) Generalized autoregressive conditional heteroscedasticity. J Econom 31:307–327
Bollerslev T (1987) A conditionally heteroskedastic time series model for speculative prices and rates of return. Rev Econ Stat 69:542–547
Breusch T (1978) Testing for autocorrelation in dynamic linear models. Aust Econ Pap 17:334–355
Bu R, Giet L, Hadri K, Lubrano M (2011) Modeling multivariate interest rates using time-varying copulas and reducible nonlinear stochastic differential equations. J Financ Econom 9:198–236
Calhoun C (1996) OFHEO house price indexes: HPI technical description. Federal Housing Finance Agency technical report
Cameron AC, Trivedi P (2005) Microeconometrics: methods and applications. Cambridge University Press, New York
Case K, Shiller R (1989) The efficiency of the market for single-family homes. Am Econ Rev 79:125–137
Case K, Quigley J, Shiller R (2003) Comparing wealth effects: the stock market versus the housing market. Working paper, University of California, Berkeley
Chen X, Fan Y (2006) Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification. J Econom 135:125–154
Coval J, Jurek J, Stafford E (2009) The economics of structured finance. J Econ Perspect 23:3–25
Deb P, Trivedi P, Varangis P (1996) Excess co-movement in commodity prices reconsidered. J Appl Econom 11:275–291
Engel R (2002) Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models. J Bus Econ Stat 20:339–350
Forbes K, Rigobon R (2002) No contagion, only interdependence: measuring stock market comovements. J Financ LVII:2223–2261
Fu D (2007) National, regional and metro-specific factors on the U.S. housing market. Federal Reserve Bank of Dallas working paper
Girouard N, Kennedy M, van den Noord P, Andre C (2006) Recent house price developments: the role of fundamentals. Working paper #475, OECD
Glosten L, Jagannathan R, Runkle D (1993) On the relation between the expected value and the volatility of the nominal excess return on stocks. J Financ 48:1779–1801
Godfrey L (1978) Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica 46:1293–1302
Granger C, Newbold P (1974) Spurious regressions in econometrics. J Econom 2:111–120
Ho A, Huynh K, Jacho-Chávez D (2014) Nonparametric estimation of copulas: application to housing crisis. Working paper, Emory University
Jarque C, Bera A (1987) A test for normality of observations and regression residuals. Int Stat Rev 55:163–172
Joe H (1997) Multivariate models and dependence concepts. Chapman & Hall, London
King M, Wadhwani S (1990) Transmission of volatility between stock markets. Biometrika 86:169–187
Kiyotaki N, Moore J (1997) Credit chains. J Polit Econ 105:211–248
Li D (2000) On default correlation: a copula function approach. J Fixed Income 9:43–54
Longi F, Solnik B (1995) Is the correlation in international equity returns constant: 1960–1990. J Int Money Financ 14:3–26
Lux T (1995) Herd behaviour, bubbles and crashes. Econ J 105:881–896
Manchin S, Salvanes K, Pelkonen P (2012) Education and mobility. J Eur Econ Assoc 10:417–450
Manner H (2010) Testing for asymmetric dependence. Stud Nonlinear Dyn Econom 14:1–30
Nelsen R (2006) An introduction to copulas, 2nd edn. Springer, New York
Palaro H, Hotta L (2006) Using conditional copula to estimate value at risk. J Data Sci 4:93–115
Patton A (2006) Modelling asymmetric exchange rate dependence. Int Econ Rev 47:527–556
Pericoli M, Sbracia M (2003) A primer on financial contagion. J Econ Surv 17:571–608
Pontines V (2010) Fat-tails and house prices in OECD countries. Appl Econ Lett 17:1373–1377
Ramchand L, Susmel R (1998) Volatility and cross correlation across major stock markets. J Empir Financ 5:397–416
Rodriguez J (2007) Measuring financial contagion: a copula approach. J Empir Financ 14:401–423
Shiller R (2007) Understanding recent trends in house prices and home ownership. NBER Working paper #13553
Sklar A (1973) Random variables, joint distributions, and copulas. Kybernetica 9:449–460
Topol R (1991) Bubbles and volatility of stock prices: effect of mimetic contagion. Econ J 101:786–800
Trivedi P, Zimmer D (2009) Pitfalls in modeling dependence structures: explorations with copulas. In: Castle J, Shephard N (eds) The methodology and practice of econometrics: a festschrift in honour of David F Hendry. Oxford University Press, New York, pp 149–172
Xu Q, Li X-M (2009) Estimation of dynamic asymmetric tail dependencies: an empirical study on Asian developed futures markets. Appl Financ Econ 19:273–290
Zhu H (2003) The importance of property markets for monetary policy and financial stability. Bank for International Settlements working paper no. 21
Zimmer D (2012) The role of copulas in the housing crisis. Rev Econ Stat 94:607–620
About this article
Cite this article
Zimmer, D.M. Asymmetric dependence in house prices: evidence from USA and international data. Empir Econ 49, 161–183 (2015). https://doi.org/10.1007/s00181-014-0859-x