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Monitoring Structural Change

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Author Info
Chu, Chia-Shang James
Stinchcombe, Maxwell
White, Halbert

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Abstract

Contemporary tests for structural change are designed to detect a structural break within a given historical data set of fixed size. Due to the law of the iterated logarithm, these one-shot tests cannot be applied to monitor out-of-sample stability each time new data arrive. The authors propose and analyze two real-time monitoring procedures with controlled size asymptotically: the fluctuation and CUSUM monitoring procedures. Simulation results show that the proposed monitoring procedures indeed have controlled asymptotic size and that detection timing depends on the magnitude of parameter change, the signal to noise ratio, and the location of the out-of-sample break point. Copyright 1996 by The Econometric Society.

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Publisher Info
Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 64 (1996)
Issue (Month): 5 (September)
Pages: 1045-65
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Handle: RePEc:ecm:emetrp:v:64:y:1996:i:5:p:1045-65

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  1. F. Carsoule & P.H.B.F. Franses, 1999. "Monitoring time-varying parameters in an autoregression," Econometric Institute Report 165, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
  2. Pavel Cizek & Wolfgang Härdle & Vladimir Spokoiny, 2008. "Adaptive pointwise estimation in time-inhomogeneous time-series models," SFB 649 Discussion Papers SFB649DP2008-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  3. David Hendry & Michael P. Clements, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Papers 2002-W11, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
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  4. Allan Timmermann & M. Hashem Pesaran, 2003. "How Costly is it to Ignore Breaks when Forecasting the Direction of a Time Series?," CESifo Working Paper Series CESifo Working Paper No. , CESifo GmbH. [Downloadable!]
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  5. F. Carsoule & Ph.H.B.F. Franses, 1999. "Monitoring structural change in variance, with an application to European nominal exchange rate volatility," Econometric Institute Report 154, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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  6. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," NBER Working Papers 6845, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  7. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper 2007-35, Tilburg University, Center for Economic Research. [Downloadable!]
  8. Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, Center for Economic and Financial Research (CEFIR). [Downloadable!]
  9. Vasyl Golosnoy, 2007. "Sequential monitoring of minimum variance portfolio," AStA Advances in Statistical Analysis, Springer, vol. 91(1), pages 39-55, March. [Downloadable!] (restricted)
  10. E. Andersson & D. Bock & M. Frisén, 2006. "Some statistical aspects of methods for detection of turning points in business cycles," Journal of Applied Statistics, Taylor and Francis Journals, vol. 33(3), pages 257-278, April. [Downloadable!] (restricted)
  11. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO. [Downloadable!]
  12. Massimo Guidolin, 2005. "Pessimistic beliefs under rational learning: quantitative implications for the equity premium puzzle," Working Papers 2005-005, Federal Reserve Bank of St. Louis. [Downloadable!]
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  13. Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series CESifo Working Paper No. , CESifo GmbH. [Downloadable!]
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