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SOME REGIME-SWITCHING MODELS FOR ECONOMIC TIME SERIES: A COMPARATIVE STUDY

Year 2022, Volume: 23 Issue: 1, 48 - 69, 30.03.2022
https://doi.org/10.18038/estubtda.881251

Abstract

References

  • [1] Granger CWJ, Andersen AP. An Introduction to Bilinear Time Series Models. Gottingen: Vandenhoek & Ruprecht, 1978.
  • [2] Tong, H. On a Threshold Model. In: Chen C, editor. Pattern Recognition and Signal Processing. Amsterdam, Sijthoff & Noordhoff, 1978, 575-586.
  • [3] Terasvirta T, Anderson H. Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models. J Appl Econom, 1992; 7: 119-136.
  • [4] Hamilton JD. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 1989; 57: 357-384.
  • [5] Tong H, Lim KS. Threshold Autoregression, Limit Cycles and Cyclical Data. J R Stat Soc, 1980; 42: 245-292.
  • [6] Chan KS, Tong H. On Estimating Thresholds in Autoregressive Models. J Time Ser Anal 1986; 7: 179-190.
  • [7] Tsay RS. Nonlinearity Tests for Time Series. Biometrika, 1986; 73: 461-466.
  • [8] Tong H. Non-linear Time Series: A Dynamical Systems Approach. USA: Oxford University Press, 1990.
  • [9] Granger CWJ, Terasvirta T. Modelling Nonlinear Economic Relationships. USA: Oxford University Press, 1993.
  • [10] Terasvirta T. Specification, Estimation and Evaluation of Smooth Transition Autoregressive Models. J Am Stat Assoc, 1994; 89: 208-218.
  • [11] Khan MY. Advanced in Applied Nonlinear Time Series Modeling. Dissertation, Munich University, Münih, Germany, 2015.
  • [12] Tong H. Threshold Models in Non-Linear Time Series Analysis. Berlin: Springer-Verlag,1983.
  • [13] Chan KS, Petruccelli JD, Tong H, Woolford SW. A Multiple-Threshold AR(1) Model. J Appl Prob, 1985; 22: 267-279.
  • [14] Petruccelli JD. On The Consistency of Least Squares Estimators for a Threshold AR(1) Model. J Time Ser Anal, 1986; 7: 269-278.
  • [15] Chan KS. Consistency and Limiting Distribution of the Least Squares Estimator of a Threshold Autoregressive Model. Ann Stat, 1993; 21: 520-533.
  • [16] Hansen BE. Inference in TAR Models. Stud Nonlinear Dyn E 1997; 2: 1-16.
  • [17] van Dijk DJC, Terasvirta T, Franses PH. Smooth Transition Autoregressive Models – A Survey of Recent Developments. Economet Rev, 2002; 21: 1-47.
  • [18] Liew VKS, Baharumshahb AZ, Lau E. Nonlinear Adjustment towards Purchasing Power Parity in ASEAN Exchange Rates, J Appl Econ, 2002; 6: 7-18.
  • [19] van Dijk DJC, Terasvirta T, Franses PH. Smooth Transition Autoregressive Models: A Survey of Recent Developments. Econometric Institute Research Report EI2000-23/A, 2000.
  • [20] Hansen BE. Sample Splitting and Threshold Estimation. Econometrica, 2000; 68: 575-603.
  • [21] Terasvirta T. Modelling Economic Relationships with Smooth Transition Regressions. In: Ullah A, Giles DEA, editors. Handbook of Applied Economic Statistics. New York, Marcel Dekker, 1998, 507-552.
  • [22] Hamilton JD. Time Series Analysis. Princeton, Princeton University Press, 1994.
  • [23] Bekiros SD. A Robust Algorithm for Parameter Estimation in Smooth Transition Autoregressive Models. Econ Lett ,2009; 103: 36-38.
  • [24] Hamilton JD. Analysis of Time Series Subject to Changes in Regime. J Econometrics, 1990; 45: 39-70.
  • [25] Franses PH, van Dijk DJC. Nonlinear Time Series Models in Empirical Finance. New York, Cambridge University Press, 2000.
  • [26] Hyndman RJ, Koehler AB. Another Look at Measures of Forecast Accuracy. Int J Forecasting, 2006; 22: 679-688.
  • [27] Dickey DA, Fuller WA. Distribution of the Estimates for Autoregressive Time Series with a Unit Root. J Am Stat Assoc, 1979; 74: 427-431.
  • [28] van Dijk DJC. Smooth Transition Models: Extensions and Outlier Robust Inference. PhD, Erasmus School of Economics, Rotterdam, Netherlands, 1999.

SOME REGIME-SWITCHING MODELS FOR ECONOMIC TIME SERIES: A COMPARATIVE STUDY

Year 2022, Volume: 23 Issue: 1, 48 - 69, 30.03.2022
https://doi.org/10.18038/estubtda.881251

Abstract

This paper mainly discusses some regime-switching models and explore their usefulness in modeling the economic time series. In recent years, several time series models have been proposed which shape the idea of the existence of different regimes produced by a stochastic process. Especially, nonlinear time series models have gained more attention because linear time series models faced various limitations. The purpose of this study is to establish the methodology of the Self-Exciting Threshold Autoregressive (SETAR) model, Smooth Transition Autoregressive (STAR) model and Markov-Switching (MSW) model from parametric nonlinear time series models in the mean and to compare these models with each other through two financial data sets. For this purpose, some theoretical information on the subject models are given without going into too much detail. In the light of the obtained theoretical information, all models are modeled by using two financial data sets. The obtained models are compared with the help of some performance criteria, measurement of relative efficiency and graph showing the relation of the actual-fitted values of the models.

References

  • [1] Granger CWJ, Andersen AP. An Introduction to Bilinear Time Series Models. Gottingen: Vandenhoek & Ruprecht, 1978.
  • [2] Tong, H. On a Threshold Model. In: Chen C, editor. Pattern Recognition and Signal Processing. Amsterdam, Sijthoff & Noordhoff, 1978, 575-586.
  • [3] Terasvirta T, Anderson H. Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models. J Appl Econom, 1992; 7: 119-136.
  • [4] Hamilton JD. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 1989; 57: 357-384.
  • [5] Tong H, Lim KS. Threshold Autoregression, Limit Cycles and Cyclical Data. J R Stat Soc, 1980; 42: 245-292.
  • [6] Chan KS, Tong H. On Estimating Thresholds in Autoregressive Models. J Time Ser Anal 1986; 7: 179-190.
  • [7] Tsay RS. Nonlinearity Tests for Time Series. Biometrika, 1986; 73: 461-466.
  • [8] Tong H. Non-linear Time Series: A Dynamical Systems Approach. USA: Oxford University Press, 1990.
  • [9] Granger CWJ, Terasvirta T. Modelling Nonlinear Economic Relationships. USA: Oxford University Press, 1993.
  • [10] Terasvirta T. Specification, Estimation and Evaluation of Smooth Transition Autoregressive Models. J Am Stat Assoc, 1994; 89: 208-218.
  • [11] Khan MY. Advanced in Applied Nonlinear Time Series Modeling. Dissertation, Munich University, Münih, Germany, 2015.
  • [12] Tong H. Threshold Models in Non-Linear Time Series Analysis. Berlin: Springer-Verlag,1983.
  • [13] Chan KS, Petruccelli JD, Tong H, Woolford SW. A Multiple-Threshold AR(1) Model. J Appl Prob, 1985; 22: 267-279.
  • [14] Petruccelli JD. On The Consistency of Least Squares Estimators for a Threshold AR(1) Model. J Time Ser Anal, 1986; 7: 269-278.
  • [15] Chan KS. Consistency and Limiting Distribution of the Least Squares Estimator of a Threshold Autoregressive Model. Ann Stat, 1993; 21: 520-533.
  • [16] Hansen BE. Inference in TAR Models. Stud Nonlinear Dyn E 1997; 2: 1-16.
  • [17] van Dijk DJC, Terasvirta T, Franses PH. Smooth Transition Autoregressive Models – A Survey of Recent Developments. Economet Rev, 2002; 21: 1-47.
  • [18] Liew VKS, Baharumshahb AZ, Lau E. Nonlinear Adjustment towards Purchasing Power Parity in ASEAN Exchange Rates, J Appl Econ, 2002; 6: 7-18.
  • [19] van Dijk DJC, Terasvirta T, Franses PH. Smooth Transition Autoregressive Models: A Survey of Recent Developments. Econometric Institute Research Report EI2000-23/A, 2000.
  • [20] Hansen BE. Sample Splitting and Threshold Estimation. Econometrica, 2000; 68: 575-603.
  • [21] Terasvirta T. Modelling Economic Relationships with Smooth Transition Regressions. In: Ullah A, Giles DEA, editors. Handbook of Applied Economic Statistics. New York, Marcel Dekker, 1998, 507-552.
  • [22] Hamilton JD. Time Series Analysis. Princeton, Princeton University Press, 1994.
  • [23] Bekiros SD. A Robust Algorithm for Parameter Estimation in Smooth Transition Autoregressive Models. Econ Lett ,2009; 103: 36-38.
  • [24] Hamilton JD. Analysis of Time Series Subject to Changes in Regime. J Econometrics, 1990; 45: 39-70.
  • [25] Franses PH, van Dijk DJC. Nonlinear Time Series Models in Empirical Finance. New York, Cambridge University Press, 2000.
  • [26] Hyndman RJ, Koehler AB. Another Look at Measures of Forecast Accuracy. Int J Forecasting, 2006; 22: 679-688.
  • [27] Dickey DA, Fuller WA. Distribution of the Estimates for Autoregressive Time Series with a Unit Root. J Am Stat Assoc, 1979; 74: 427-431.
  • [28] van Dijk DJC. Smooth Transition Models: Extensions and Outlier Robust Inference. PhD, Erasmus School of Economics, Rotterdam, Netherlands, 1999.
There are 28 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Dursun Aydın 0000-0001-8393-1270

Selman Mermi 0000-0003-3601-6971

Publication Date March 30, 2022
Published in Issue Year 2022 Volume: 23 Issue: 1

Cite

AMA Aydın D, Mermi S. SOME REGIME-SWITCHING MODELS FOR ECONOMIC TIME SERIES: A COMPARATIVE STUDY. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering. March 2022;23(1):48-69. doi:10.18038/estubtda.881251