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The sampling distribution of forecasts from a first-order autoregression

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Cited by:

  1. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
  2. Pesaran, M.H. & Pick, A. & Timmermann, A., 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," Cambridge Working Papers in Economics 0901, Faculty of Economics, University of Cambridge.
  3. Jean Francois David & Eric Ghysels, 1989. "Y a-t-il des biais systematiques dans les annonces budgetaires canadiennes? (With English summary.)," Canadian Public Policy, University of Toronto Press, vol. 15(3), pages 313-321, September.
  4. Müller, Ulrich K. & Wang, Yulong, 2019. "Nearly weighted risk minimal unbiased estimation," Journal of Econometrics, Elsevier, vol. 209(1), pages 18-34.
  5. Kabaila, Paul & Syuhada, Khreshna, 2010. "The asymptotic efficiency of improved prediction intervals," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1348-1353, September.
  6. Simon Nik & Christian H. Weiß, 2020. "CLAR(1) point forecasting under estimation uncertainty," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(4), pages 489-516, November.
  7. Daniel W. Apley & Hyun Cheol Lee, 2010. "The effects of model parameter deviations on the variance of a linearly filtered time series," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(5), pages 460-471, August.
  8. Aman Ullah & Yong Bao & Ru Zhang, 2014. "Moment Approximation for Unit Root Models with Nonnormal Errors," Working Papers 201401, University of California at Riverside, Department of Economics.
  9. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
  10. Greenaway-McGrevy, Ryan, 2015. "Evaluating panel data forecasts under independent realization," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 108-125.
  11. Lee, Yun Shin & Scholtes, Stefan, 2014. "Empirical prediction intervals revisited," International Journal of Forecasting, Elsevier, vol. 30(2), pages 217-234.
  12. Gospodinov, Nikolay, 2002. "Median unbiased forecasts for highly persistent autoregressive processes," Journal of Econometrics, Elsevier, vol. 111(1), pages 85-101, November.
  13. Onatski, Alexei, 2015. "Asymptotic analysis of the squared estimation error in misspecified factor models," Journal of Econometrics, Elsevier, vol. 186(2), pages 388-406.
  14. Lee, Yun Shin, 2014. "A semi-parametric approach for estimating critical fractiles under autocorrelated demand," European Journal of Operational Research, Elsevier, vol. 234(1), pages 163-173.
  15. Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2017. "A Justification of Conditional Confidence Intervals," Papers 1710.00643, arXiv.org, revised Jan 2019.
  16. Bao Yong & Zhang Ru, 2013. "Estimation Bias and Feasible Conditional Forecasts from the First-Order Moving Average Model," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 63-80, July.
  17. Paolo Vidoni, 2009. "A simple procedure for computing improved prediction intervals for autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 577-590, November.
  18. Stanislav Anatolyev & Nikolay Gospodinov, 2012. "Asymptotics of near unit roots (in Russian)," Quantile, Quantile, issue 10, pages 57-71, December.
  19. Silvia Goncalves & Serena Ng, 2024. "Imputation of Counterfactual Outcomes when the Errors are Predictable," Papers 2403.08130, arXiv.org, revised May 2024.
  20. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
  21. Paolo Vidoni, 2004. "Improved prediction intervals for stochastic process models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 137-154, January.
  22. Ching‐Kang Ing & Shu‐Hui Yu, 2003. "On Estimating Conditional Mean‐Squared Prediction Error in Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 401-422, July.
  23. John L. Turner, 2004. "Local to unity, long-horizon forecasting thresholds for model selection in the AR(1)," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 513-539.
  24. Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
  25. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
  26. Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2019. "Tales from tails: On the empirical distributions of forecasting errors and their implication to risk," International Journal of Forecasting, Elsevier, vol. 35(2), pages 687-698.
  27. Paul Kabaila & Zhisong He, 2004. "The adjustment of prediction intervals to account for errors in parameter estimation," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 351-358, May.
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