Journal of Economics and Finance

, Volume 36, Issue 1, pp 211–225 | Cite as

The housing bubble in real-time: the end of innocence



Market agents suffering through unanticipated boom-bust cycles would find extremely useful analytical techniques capable of serving as an early warning system. Unobserved components models and cointegration analysis are valuable in this respect. The stylized facts from unobserved components models alone do not suffice, but coupled with results from the Johansen cointegration test provided early evidence of the housing bubble and of its denouement. The paper uses real-time data vintages and shows that by 1998 the relationship between the smoothed growth rates of house prices and of per capita income was in uncharted territory. Moreover, the actual growth rates are cointegrated. This is important, as it establishes that any disequilibrium between the two becomes less tenable as its magnitude increases. By 2003, the disequilibrium was spectacular, yet it grew for another 4 years. In effect, we did not have to wait until 2008; the gruesome ending was predictable ex ante. Ironically, the greatest financial delusion of all occurred in an age that revered rationality, market efficiency, and the financial enlightenment of the TBTF actors. The empirical findings of this paper are a major problem for the rational expectations hypothesis and the remnants of the EMH.


Cointegration Unobserved Components Rationality Market Efficiency 

JEL Classification

C220 G010 D8 


  1. Bailey M, Muth R, Nourse H (1963) A regression method for real estate price index construction. Am Stat Assoc J 58:933–942CrossRefGoogle Scholar
  2. Baxter M, King R (1999) Measuring business cycles: approximate band-pass filters for economic time series. Rev Econ Stat 81:575–593CrossRefGoogle Scholar
  3. Bhargava A (1986) On the theory of testing for unit roots in observed time series. Rev Econ Stud 53:369–384CrossRefGoogle Scholar
  4. Blanchard O, Fisher S (1989) Lectures in macroeconomics. MIT Press, CambridgeGoogle Scholar
  5. Borio C, Lowe P (2002) Assessing the risk of banking crises. BIS Quarterly Review December 43 –54Google Scholar
  6. Calhoun C (1996) OFHEO house price indexes: HPI technical description. Office of Federal Housing Enterprise Oversight, WashingtonGoogle Scholar
  7. Case K, Shiller R (1989) The efficiency of the market for single-family homes. Am Econ Rev 79:125–137Google Scholar
  8. Clark P (1987) The cyclical component of U.S. economic activity. Q J Econ 102:797–814CrossRefGoogle Scholar
  9. Cochrane J (1991) A critique of the application of unit root tests. J Econ Dyn Control 15:275–284CrossRefGoogle Scholar
  10. Cogley T, Nason J (1995) Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research. J Econ Dyn Control 19:253–278CrossRefGoogle Scholar
  11. Crespo R (2008) Total factor productivity: an unobserved components approach. Appl Econ 40:2085–2097CrossRefGoogle Scholar
  12. Dickey D, Fuller W (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74:427–431CrossRefGoogle Scholar
  13. Dickey D, Fuller W (1981) Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49:1057–1072CrossRefGoogle Scholar
  14. Diebold F, Rudebusch G (1991) On the power of the Dickey-Fuller test against fractional alternatives. Econ Lett 35:155–160CrossRefGoogle Scholar
  15. Dodd C (2007) Opening statement–hearing on Mortgage market turmoil: causes and consequences. U.S. Senate Committee on Banking, Housing, and Urban AffairsGoogle Scholar
  16. Domenech R, Gomez V (2006) Estimating potential output, core inflation and the NAIRU. J Bus Econ Stat 24:354–365CrossRefGoogle Scholar
  17. Dossche M, Everaert G (2005) Measuring inflation persistence —a structural time series approach. Working Paper Series: 495, European Central BankGoogle Scholar
  18. Elliott J, Rothenberg T, Stock J (1996) Efficient tests for an autoregressive unit root. Econometrica 64:816–836CrossRefGoogle Scholar
  19. Fadiga M, Wang Y (2009) A multivariate unobserved component analysis of US housing market. J Econ Finance 33:13–26CrossRefGoogle Scholar
  20. Fama E (1998) Market efficiency, long-term returns, and behavioral finance. J Financ Econ 49:283–306CrossRefGoogle Scholar
  21. Harvey A (1989) Forecasting, structural time series models and the Kalman Filter. Cambridge University Press, New YorkGoogle Scholar
  22. Harvey A (1997) Trends, cycles and autoregressions. Econ J 107:192–201CrossRefGoogle Scholar
  23. Harvey A, Chung C (2000) Estimating the underlying change in unemployment in the UK. J R Stat Soc 163:303–339Google Scholar
  24. Harvey A, Jaeger J (1993) Detrending, stylized facts and the business cycle. J Appl Econ 8:231–247CrossRefGoogle Scholar
  25. Harvey A, Ruiz E, Sentana E (1992) Unobserved component time series models with ARCH disturbances. J Econom 52:129–157CrossRefGoogle Scholar
  26. Hassler U, Wolters J (1994) On the power of unit root tests against fractional alternatives. Econ Lett 45:1–6CrossRefGoogle Scholar
  27. Hodrick R, Prescott E (1980) Postwar U.S. business cycles: An empirical investigation. Discussion Paper No. 451, Carnegie-Mellon UniversityGoogle Scholar
  28. Huang Y, Huang C, Kuan C (2008) Reexamining the permanent income hypothesis with uncertainty in permanent and transitory innovation states. J Macroecon 30:1816–1836CrossRefGoogle Scholar
  29. Johansen S (1988) Statistical analysis of cointegration vectors. J Econ Dyn Control 12:231–254CrossRefGoogle Scholar
  30. Johansen S (1991) Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. Econometrica 59(6):1551–1580CrossRefGoogle Scholar
  31. Johansen S, Juselius K (1990) Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxf Bull Econ Stat 52(2):169–210CrossRefGoogle Scholar
  32. Juselius K (2008) The cointegrated VAR model: methodology and applications. Oxford University Press, New YorkGoogle Scholar
  33. Kindleberger CP, Aliber RZ (2005) Manias, panics, and crashes: a history of financial crises, 5th edn. Wiley, HobokenCrossRefGoogle Scholar
  34. Koopman SJ, Harvey AC, Doornik JA, Shephard N (2007) Structural time series analyser, modeller and predictor STAMP 8. Timberlake Consultants Ltd, LondonGoogle Scholar
  35. Kuttner K (1994) Estimating potential output as a latent variable. J Bus Econ Stat 12:361–368CrossRefGoogle Scholar
  36. Lee D, Schmidt P (1996) On the power of the KPSS test of stationarity against fractionally integrated alternatives. J Econom 73:285–302CrossRefGoogle Scholar
  37. Leventis A (2007) A note on the differences between the OFHEO and S&P/Case-Shiller house price indexes. Office of Federal Housing Enterprise Oversight, July 25, 2007Google Scholar
  38. Maddala GS, Kim I-M (2000) Unit roots, cointegration, and structural change. Cambridge University Press, CambridgeGoogle Scholar
  39. Nelson CR, Plosser CI (1982) Trends and random walks in macroeconomic time series. J Monet Econ 10:139–162CrossRefGoogle Scholar
  40. Ng S, Perron P (2001) Lag length selection and the construction of unit root tests with good size and power. Econometrica 69(6):1519–1554CrossRefGoogle Scholar
  41. Nyblom J, Harvey A (2005) Testing for deterministic linear trends in time series. In: Harvey A, Proietti T (eds) Readings in unobserved components models. Oxford University Press, New YorkGoogle Scholar
  42. OFHEO (2008) Revisiting the differences between the OFHEO and S&P Case-Shiller house price indexes: new explanations. Office of Federal Housing Enterprise OversightGoogle Scholar
  43. Perron P, Ng S (1996) Useful modifications to some unit root tests with dependent errors and their local asymptotic properties. Rev Econ Stud 63(3):435–463CrossRefGoogle Scholar
  44. Peláez R (2004) Dating the productivity slowdown with a structural time series model. Q Rev Econ Finance 44(2):253–264CrossRefGoogle Scholar
  45. Peláez R (2007) Earnings per share: stylized facts and new paradigms. J Behav Finance 8:198–208CrossRefGoogle Scholar
  46. Phillips PCB, Perron P (1988) Testing for a unit root in a time series regression. Biometrika 75:335–346CrossRefGoogle Scholar
  47. Reinhart C, Rogoff KS (2009) This time is different: eight centuries of financial folly. Princeton University Press, PrincetonGoogle Scholar
  48. Samuelson PA (1998) Summing up on business cycles: opening address. In: Fuhrer JC, Schuh S (eds) Beyond shocks: what causes business cycles? Boston: Federal Reserve Bank of Boston, Conference Series # 42, pp 33 –36Google Scholar
  49. Shiller R (2000) Irrational exuberance. Princeton University Press, PrincetonGoogle Scholar
  50. Shiller R (2003) From efficient markets theory to behavioral finance. J Econ Perspect 17:83–104CrossRefGoogle Scholar
  51. Stock J, Watson M (2007) Why has U.S. inflation become harder to forecast? J Money, Credit Bank 39(Supplement F):3–33CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Finance Department, College of BusinessUniversity of Houston-DowntownHoustonUSA

Personalised recommendations