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Citations for "Subsampling inference in threshold autoregressive models"

by Jesús Gonzalo & Michael Wolf

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  1. Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2008. "THRET: Threshold Regression with Endogenous Threshold Variables," University of Cyprus Working Papers in Economics 3-2008, University of Cyprus Department of Economics.
  2. Li, Dong & Ling, Shiqing, 2012. "On the least squares estimation of multiple-regime threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 167(1), pages 240-253.
  3. Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2008. "Structural Threshold Regression," Discussion Papers Series, Department of Economics, Tufts University 0717, Department of Economics, Tufts University.
  4. Jesús Gonzalo & Michael Wolf, 2001. "Subsampling inference in threshold autoregressive models," Economics Working Papers 573, Department of Economics and Business, Universitat Pompeu Fabra.
  5. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2010. "Regime Specific Predictability in Predictive Regressions," MPRA Paper 29190, University Library of Munich, Germany.
  6. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
  7. Kapetanios, G. & Tzavalis, E., 2010. "Modeling structural breaks in economic relationships using large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 417-436, March.
  8. Li, Jing, 2011. "Bootstrap prediction intervals for SETAR models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 320-332, April.
  9. Sokbae Lee & Myunghwan Seo, 2007. "Semiparametric Estimation Of A Binaryresponse Model With A Change-Pointdue To A Covariate Threshold," STICERD - Econometrics Paper Series /2007/516, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  10. Camponovo, Lorenzo & Scaillet, Olivier & Trojani, Fabio, 2012. "Robust subsampling," Journal of Econometrics, Elsevier, vol. 167(1), pages 197-210.
  11. Claudio Pizzi & Francesca Parpinel, 2011. "Evolutionary computational approach in TAR model estimation," Working Papers 2011_26, Department of Economics, University of Venice "Ca' Foscari".
  12. Donayre, Luiggi & Eo, Yunjong & Morley, James, 2014. "Improving Likelihood-Ratio-Based Confidence Intervals for Threshold Parameters in Finite Samples," Working Papers 2014-04, University of Sydney, School of Economics.
  13. Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014. "A nonlinear panel data model of cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 179(2), pages 134-157.
  14. Ellen Hamaker & Zhiyong Zhang & Han Maas, 2009. "Using Threshold Autoregressive Models to Study Dyadic Interactions," Psychometrika, Springer, vol. 74(4), pages 727-745, December.
  15. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
  16. Oliver Linton & Myunghwan Seo, 2005. "A smoothed least squares estimator for threshold regression models," LSE Research Online Documents on Economics 4434, London School of Economics and Political Science, LSE Library.
  17. Yu, Ping, 2012. "Likelihood estimation and inference in threshold regression," Journal of Econometrics, Elsevier, vol. 167(1), pages 274-294.
  18. Dong Li & Shiqing Ling & Jean-Michel Zakoian, 2013. "Asymptotic Inference in Multiple-Threshold Nonlinear Time Series Models," Working Papers 2013-51, Centre de Recherche en Economie et Statistique.
  19. Myung Hwan Seo, 2007. "Estimation of Nonlinear Error CorrectionModels," STICERD - Econometrics Paper Series /2007/517, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  20. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, 07.
  21. Deniz Baglan & Emre Yoldas, 2013. "Government debt and macroeconomic activity: a predictive analysis for advanced economies," Finance and Economics Discussion Series 2013-05, Board of Governors of the Federal Reserve System (U.S.).