Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices∗

We show how simple statistical techniques for capturing critical transitions used in natural sciences, fail to capture economic regime shifts. This implies that we need to use model-based approaches to identify critical transitions. We apply a heterogenous agents model in a standard housing market model to show that these family of models generate non-linear responses that can capture such transitions. We estimate this model for the United States and the Netherlands and find that first, the data does capture the heterogeneity in expectations and, second, that the qualitative predictions of such nonlinear models are very different to standard linear benchmarks. It would be important to identify which approach can serve best as an early warning indicator.

[1]  Marten Scheffer,et al.  Critical Transitions in Nature and Society , 2009 .

[2]  Piet Eichholtz,et al.  House Prices and Fundamentals: 355 Years of Evidence , 2012 .

[3]  Jan Sieber,et al.  Climate tipping as a noisy bifurcation: a predictive technique , 2010, 1007.1376.

[4]  Carmen M. Reinhart,et al.  Leading Indicators of Currency Crises , 1997, SSRN Electronic Journal.

[5]  Remco C. J. Zwinkels,et al.  Chasing Trends in the U.S. Housing Market , 2011 .

[6]  Morris A. Davis,et al.  What moves housing markets: A variance decomposition of the rent-price ratio , 2009 .

[7]  Pierre Monnin,et al.  National Centre of Competence in Research Financial Valuation and Risk Management Working Paper No . 356 Fundamental Real Estate Prices : An Empirical Estimation with International Data , 2007 .

[8]  F. Westerhoff,et al.  Structural stochastic volatility in asset pricing dynamics: Estimation and model contest , 2012 .

[9]  U. Erlandsson,et al.  Regime switching as an alternative early warning system of currency crises - an application to South-East Asia , 2004 .

[10]  Hein van Bohemen,et al.  Critical Transitions In Nature And Society, Princeton Studies in Complexity, M. Scheffer. Princeton University Press (2009), ISBN 0691122040, 30,95 US$ , 2010 .

[11]  Remco C. J. Zwinkels,et al.  Behavioural Heterogeneity and Shift-Contagion: Evidence from the Asian Crisis , 2008 .

[12]  Andrew Berg,et al.  Predicting currency crises:: The indicators approach and an alternative , 1999 .

[13]  Tae Yoon Kim,et al.  An early warning system for detection of financial crisis using financial market volatility , 2006, Expert Syst. J. Knowl. Eng..

[14]  Sebastiano Manzan,et al.  Behavioral Heterogeneity in Stock Prices , 2005 .

[15]  S. Carpenter,et al.  Early-warning signals for critical transitions , 2009, Nature.

[16]  Eduardo Borensztein,et al.  Assessing Early Warning Systems: How Have They Worked in Practice? , 2004, SSRN Electronic Journal.

[17]  E. Davis,et al.  Could Early Warning Systems Have Helped To Predict the Sub-Prime Crisis? , 2008, National Institute Economic Review.

[18]  Remco C. J. Zwinkels,et al.  Heterogeneity of Agents and Exchange Rate Dynamics: Evidence from the EMS , 2006 .

[19]  C. Himmelberg,et al.  Assessing High House Prices: Bubbles, Fundamentals, and Misperceptions , 2005 .

[20]  Jonathan D. Cryer,et al.  Time Series Analysis , 1986 .

[21]  Asli Demirgüç-Kunt,et al.  Cross-Country Empirical Studies of Systemic Bank Distress: A Survey , 2005, National Institute Economic Review.

[22]  J. Poterba Taxation and Housing: Old Questions, New Answers , 1992 .

[23]  W. Brock,et al.  Heterogeneous beliefs and routes to chaos in a simple asset pricing model , 1998 .

[24]  Thomas Lux,et al.  Rational Forecasts or Social Opinion Dynamics? Identification of Interaction Effects in a Business Climate Survey , 2009 .

[25]  P. Ditlevsen,et al.  Tipping points: Early warning and wishful thinking , 2010 .

[26]  Sean D. Campbell,et al.  A Trend and Variance Decomposition of the Rent-Price Ratio in Housing Markets , 2006 .

[27]  E. Davis,et al.  Comparing early warning systems for banking crises , 2008 .

[28]  Asli Demirgüç-Kunt,et al.  Cross-Country Empirical Studies of Systemic Bank Distress: A Survey , 2005, National Institute Economic Review.

[29]  Bertrand Candelon,et al.  A cautious note on the use of panel models to predict financial crises , 2008 .