1. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November. [Downloadable!] (restricted)
   Other versions:
   • Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics. [Downloadable!]
   • Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society. [Downloadable!]
   • Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City. [Downloadable!]
2. 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 123-41, March-Apr. [Downloadable!]
   Other versions:
   • Clements, Michael P & Smith, Jeremy, 1996. "A Monte Carlo Study of the Forecasting Performance of Empirical Setar Models," The Warwick Economics Research Paper Series (TWERPS) 464, University of Warwick, Department of Economics.
3. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May. [Downloadable!] (restricted)
   Other versions:
   • Kilian, Lutz & Taylor, Mark P, 2001. "Why is it so Difficult to Beat the Random Walk Forecast of Exchange Rates?," CEPR Discussion Papers 3024, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
   • Lutz Kilian & Mark P. Taylor, 2001. "Why Is It So Difficult to Beat the Random Walk Forecast of Exchange Rates?," Working Papers 464, Research Seminar in International Economics, University of Michigan. [Downloadable!]
   • Lutz Kilian & Mark P. Taylor, 2001. "Why is it so difficult to beat the random walk forecast of exchange rates," Working Paper Series 088, European Central Bank. [Downloadable!]
   • Lutz Kilian & Mark P. Taylor, 2001. "Why is it so difficult to beat the Random Walk Forecast of Exchange Rates?," Tinbergen Institute Discussion Papers 01-031/4, Tinbergen Institute. [Downloadable!]
4. B. Siliverstovs & D.J. Van Dijk, 2003. "Forecasting industrial production with linear, nonlinear and structural change models," Econometric Institute Report 321, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
   Other versions:
   • Siliverstovs, B. & Dijk, D.J.C. van, 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Report EI 2003-16 Revision_Date:, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
5. Krolzig, Hans-Martin & Hendry, David F., 2001. "Computer automation of general-to-specific model selection procedures," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 831-866, June. [Downloadable!] (restricted)
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   • Hans-Martin Krolzig & David Hendry, 1999. "Computer Automation of General-to-Specific Model Selection Procedures," Computing in Economics and Finance 1999 314, Society for Computational Economics.
   • Hans-Martin Krolzig & David Hendry, 2000. "Computer Automation of General-to-Specific Model Selection Procedures," Economics Series Working Papers 003, University of Oxford, Department of Economics.
   • Hans-Martin Krolzig, 2000. "Computer Automation of General-to-Specific Model Selection Procedures," Econometric Society World Congress 2000 Contributed Papers 0411, Econometric Society. [Downloadable!]
6. Boero, Gianna & Marrocu, Emanuela, 2002. "The Performance of Non-linear Exchange Rate Models: A Forecasting Comparison," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 513-42, November.
7. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C47-C75.
8. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June. [Downloadable!] (restricted)
9. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March. [Downloadable!] (restricted)
10. Norman R. Swanson & Halbert White, 1992. "A Model Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," University of California at San Diego, Economics Working Paper Series 92-39, Department of Economics, UC San Diego.
    Other versions:
    • Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-75, July.
11. Heravi, Saeed & Osborn, Denise R. & Birchenhall, C. R., 2004. "Linear versus neural network forecasts for European industrial production series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 435-446. [Downloadable!] (restricted)
12. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De. [Downloadable!] (restricted)
13. G. Rech & T. Teräsvirta & R. Tschernig, . "A Simple variable selection technique for nonlinear models," Sonderforschungsbereich 373 1999-26, Humboldt Universitaet Berlin.
    Other versions:
    • Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," Working Paper Series in Economics and Finance 296, Stockholm School of Economics, revised 06 Apr 2000.
14. Marcellino, Massimiliano, 2002. "Instability and Non-Linearity in the EMU," CEPR Discussion Papers 3312, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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    • Massimiliano Marcellino, . "Instability and non-linearity in the EMU," Working Papers 211, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
15. Skalin, Joakim & Ter svirta, Timo, 2002. "Modeling Asymmetries And Moving Equilibria In Unemployment Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 6(02), pages 202-241, April. [Downloadable!]
16. Timo TerŠsvirta & Chien-Fu Lin & Clive W.J. Granger, 1991. "Power of the Neural Network Linearity Test," University of California at San Diego, Economics Working Paper Series 91-01, Department of Economics, UC San Diego.
17. Tkacz, Greg, 2001. "Neural network forecasting of Canadian GDP growth," International Journal of Forecasting, Elsevier, vol. 17(1), pages 57-69. [Downloadable!] (restricted)
18. Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002. "Building neural network models for time series: A statistical approach," Working Paper Series in Economics and Finance 508, Stockholm School of Economics. [Downloadable!]
    Other versions:
    • Marcelo C. Medeiros & Timo Terasvirta & Gianluigi Rech, 2002. "Building Neural Network Models for Time Series: A Statistical Approach," Textos para discussão 461, Department of Economics PUC-Rio (Brazil). [Downloadable!]
    • Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75. [Downloadable!]
19. Rech, Gianluigi, 2002. "Forecasting with artificial neural network models," Working Paper Series in Economics and Finance 491, Stockholm School of Economics. [Downloadable!]
20. van Dijk, Dick & Teräsvirta, Timo & Franses, Philip Hans, 2000. "Smooth Transition Autoregressive Models - A Survey of Recent Developments," Working Paper Series in Economics and Finance 380, Stockholm School of Economics, revised 17 Jan 2001. [Downloadable!]
    Other versions:
    • D. van Dijk & T. Terasvirta & P.H. Franses, 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Report 200, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    • Dijk, D.J.C. van & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Report EI 2000-23/A Revision_Dat, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    • Dick van Dijk & Timo Teräsvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models - A Survey Of Recent Developments," Econometric Reviews, Taylor and Francis Journals, vol. 21(1), pages 1-47. [Downloadable!] (restricted)

Cited by:
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1. Costas Milas & Ilias Lekkos & Theodore Panagiotidis, 2006. "Forecasting interest rate swap spreads using domestic and international risk factors: Evidence from linear and non-linear models," Keele Economics Research Papers KERP 2006/05, Centre for Economic Research, Keele University. [Downloadable!]
   Other versions:
   • Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2006. "Forecasting interest rate swap spreads using domestic and international risk factors: Evidence from linear and non-linear models," Discussion Paper Series 2006_6, Department of Economics, Loughborough University, revised Mar 2006. [Downloadable!]
   • Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2007. "Forecasting interest rate swap spreads using domestic and international risk factors: evidence from linear and non-linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 601-619. [Downloadable!]
2. Jonathan B. Hill, 2004. "Consistent and Non-Degenerate Model Specification Tests Against Smooth Transition Alternatives," Working Papers 0406, Florida International University, Department of Economics. [Downloadable!]
3. Balagtas, Joseph V. & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association). [Downloadable!]
4. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis. [Downloadable!]
   Other versions:
   • Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399. [Downloadable!] (restricted)
5. Nikolay Robinzonov & Klaus Wohlrabe, 2008. "Freedom of Choice in Macroeconomic Forecasting: An Illustration with German Industrial Production and Linear Models," Ifo Working Paper Series Ifo Working Paper No. 57, Ifo Institute for Economic Research at the University of Munich. [Downloadable!]
6. Ralf Becker & Denise Osborn, 2007. "Weighted smooth transition regressions," The School of Economics Discussion Paper Series 0724, Economics, The University of Manchester. [Downloadable!]
7. Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2005. "On the predictability of common risk factors in the US and UK interest rate swap markets:Evidence from non-linear and linear models," Keele Economics Research Papers KERP 2005/13, Centre for Economic Research, Keele University. [Downloadable!]
   Other versions:
   • Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2005. "On the predictability of common risk factors in the US and UK interest rate swap markets: Evidence from non-linear and linear models," Discussion Paper Series 2005_9, Department of Economics, Loughborough University, revised Sep 2005. [Downloadable!]