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The performance of alternative forecasting methods for SETAR models

Citations

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Cited by:

  1. Jha, Girish K. & Sinha, Kanchan, 2013. "Agricultural Price Forecasting Using Neural Network Model: An Innovative Information Delivery System," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 26(2).
  2. McMillan, David G., 2009. "The confusing time-series behaviour of real exchange rates: Are asymmetries important?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 692-711, October.
  3. Pentti Saikkonen & Antti Ripatti, 2000. "On the Estimation of Euler Equations in the Presence of a Potential Regime Shift," Manchester School, University of Manchester, vol. 68(s1), pages 92-121.
  4. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
  5. Pentti Saikkonen & Antti Ripatti, 2000. "On the Estimation of Euler Equations in the Presence of a Potential Regime Shift," Manchester School, University of Manchester, vol. 68(s1), pages 92-121.
  6. repec:zbw:bofrdp:1999_020 is not listed on IDEAS
  7. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
  8. Terui, Nobuhiko & van Dijk, Herman K., 2002. "Combined forecasts from linear and nonlinear time series models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 421-438.
  9. Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
  10. Huanxing Yang, 2010. "Information aggregation and investment cycles with strategic complementarity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 43(2), pages 281-311, May.
  11. Pawel Milobedzki, 2010. "The Term Structure of the Polish Interbank Rates. A Note on the Symmetry of their Reversion to the Mean," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 10, pages 81-95.
  12. G. Boero & E. Marrocu, 2001. "Evaluating non-linear models on point and interval forecasts: an application with exchange rate returns," Working Paper CRENoS 200110, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  13. Andrew Phiri, 2012. "Threshold effects and inflation persistence in South Africa," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 4(3), pages 247-269, July.
  14. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
  15. Crespo-Cuaresma, Jesus, 2000. "Forecasting European GDP Using Self-Exciting Threshold Autoregressive Models. A Warning," Economics Series 79, Institute for Advanced Studies.
  16. Boero, Gianna & Marrocu, Emanuela, 2004. "The performance of SETAR models: a regime conditional evaluation of point, interval and density forecasts," International Journal of Forecasting, Elsevier, vol. 20(2), pages 305-320.
  17. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
  18. Clements, Michael P & Smith, Jeremy, 1999. "A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 123-141, March-Apr.
  19. Philippe Goulet Coulombe, 2020. "To Bag is to Prune," Papers 2008.07063, arXiv.org, revised Jun 2021.
  20. Clements, Michael P. & Galvao, Ana Beatriz, 2004. "A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure," International Journal of Forecasting, Elsevier, vol. 20(2), pages 219-236.
  21. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
  22. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
  23. Philippe Goulet Coulombe, 2021. "The Macroeconomy as a Random Forest," Working Papers 21-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
  24. repec:lan:wpaper:2587 is not listed on IDEAS
  25. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
  26. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
  27. Markku Lanne, 2003. "Testing the Expectations Hypothesis of the Term Structure of Interest Rates in the Presence of a Potential Regime Shift," Manchester School, University of Manchester, vol. 71(s1), pages 54-67, September.
  28. Clementrs, Michael P. & Smith, Jeremy, 1997. "A Monte Carlo study of the forecasting performance of empirical SETAR models," Economic Research Papers 268734, University of Warwick - Department of Economics.
  29. Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.
  30. Hans-Martin Krolzig, 2000. "Predicting Markov-Switching Vector Autoregressive Processes," Economics Series Working Papers 2000-W31, University of Oxford, Department of Economics.
  31. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  32. Philippe Goulet Coulombe, 2021. "To Bag is to Prune," Working Papers 21-03, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Jun 2021.
  33. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332.
  34. repec:lan:wpaper:2444 is not listed on IDEAS
  35. Grabowski Daniel & Winker Peter & Staszewska-Bystrova Anna, 2017. "Generating prediction bands for path forecasts from SETAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-18, December.
  36. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
  37. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
  38. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 1210, University of Nevada, Las Vegas , Department of Economics.
  39. Fabio Gobbi, 2021. "Evaluating Forecasts from State-Dependent Autoregressive Models for US GDP Growth Rate. Comparison with Alternative Approaches," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-7.
  40. Duarte, A. & Venetis, I. & Payá, I., 2004. "Curva de rendimientos y crecimiento de la producción real en la UEM: eficiencia y estabilidad predictiva./Yield Curve and Real Output Growth in the EMU: Efficiency and Predictive Stability," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 22, pages 1-21, Abril.
  41. Hui Feng & Jia Liu, 2003. "A SETAR model for Canadian GDP: non-linearities and forecast comparisons," Applied Economics, Taylor & Francis Journals, vol. 35(18), pages 1957-1964.
  42. Markku Lanne, 2003. "Testing the Expectations Hypothesis of the Term Structure of Interest Rates in the Presence of a Potential Regime Shift," Manchester School, University of Manchester, vol. 71(s1), pages 54-67, September.
  43. G. Boero & E. Marrocu, 2000. "La performance di modelli non lineari per i tassi di cambio: un'applicazione con dati a diversa frequenza," Working Paper CRENoS 200014, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  44. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
  45. Ruthira Naraidoo & Ivan Paya, 2010. "Forecasting Monetary Rules in South Africa," Working Papers 201007, University of Pretoria, Department of Economics.
  46. repec:zbw:bofrdp:1999_006 is not listed on IDEAS
  47. Milena Hoyos & Mario Galindo, 2011. "Comparación de los modelos SETAR y STAR para el índice de empleo industrial colombiano," Documentos de Trabajo, Escuela de Economía 8347, Universidad Nacional de Colombia, FCE, CID.
  48. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
  49. David McMillan, 2008. "Non-linear cointegration and adjustment: an asymmetric exponential smooth-transition model for US interest rates," Empirical Economics, Springer, vol. 35(3), pages 591-606, November.
  50. repec:lan:wpaper:2364 is not listed on IDEAS
  51. Ahmad, Saad & Civelli, Andrea, 2016. "Globalization and inflation: A threshold investigation," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 283-304.
  52. Manzan, Sebastiano & Zerom, Dawit, 2008. "A bootstrap-based non-parametric forecast density," International Journal of Forecasting, Elsevier, vol. 24(3), pages 535-550.
  53. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
  54. Amendola, Alessandra & Christian, Francq, 2009. "Concepts and tools for nonlinear time series modelling," MPRA Paper 15140, University Library of Munich, Germany.
  55. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
  56. Zacharias Psaradakis & Fabio Spagnolo, 2005. "Forecast performance of nonlinear error-correction models with multiple regimes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 119-138.
  57. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
  58. Yuzhi Cai, 2005. "A forecasting procedure for nonlinear autoregressive time series models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(5), pages 335-351.
  59. De Gooijer, Jan G. & Ray, Bonnie K., 2003. "Modeling vector nonlinear time series using POLYMARS," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 73-90, February.
  60. Paulo M.M. Rodrigues & Nazarii Salish, 2011. "Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns," Working Papers w201128, Banco de Portugal, Economics and Research Department.
  61. Harvill, Jane L. & Ray, Bonnie K., 2005. "A note on multi-step forecasting with functional coefficient autoregressive models," International Journal of Forecasting, Elsevier, vol. 21(4), pages 717-727.
  62. Clements, Michael P. & Galvão, Ana Beatriz C., 2003. "Testing The Expectations Theory Of The Term Structure Of Interest Rates In Threshold Models," Macroeconomic Dynamics, Cambridge University Press, vol. 7(4), pages 567-585, September.
  63. Leonardo Souza & Alvaro Veiga & Marcelo C. Medeiros, 2002. "Evaluating the performance of GARCH models using White´s Reality Check," Textos para discussão 453, Department of Economics PUC-Rio (Brazil).
  64. Holt, Matthew T. & Craig, Lee A., 2006. "AJAE Appendix: Nonlinear Dynamics and Structural Change in the U.S. Hog-Corn Ratio: A Time-Varying Star Approach," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 88(1), pages 1-16, February.
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