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Parameter constancy, mean square forecast errors, and measuring forecast performance: an exposition, extensions, and illustration

Citations

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Cited by:

  1. Conrad, Christian, 2010. "Non-negativity conditions for the hyperbolic GARCH model," Journal of Econometrics, Elsevier, vol. 157(2), pages 441-457, August.
  2. repec:awi:wpaper:0472 is not listed on IDEAS
  3. Carmine Trecroci & Juan Vega, 2002. "The information content of M3 for future inflation in the Euro area," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(1), pages 22-53, March.
  4. MacDonald, Ronald & Nagayasu, Jun, 1998. "On the Japanese Yen-U.S. Dollar Exchange Rate: A Structural Econometric Model Based on Real Interest Differentials," Journal of the Japanese and International Economies, Elsevier, vol. 12(1), pages 75-102, March.
  5. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
  6. Chad Fulton & Kirstin Hubrich, 2021. "Forecasting US Inflation in Real Time," Econometrics, MDPI, vol. 9(4), pages 1-20, October.
  7. Massimiliano Marcellino, "undated". "Further Results on MSFE Encompassing," Working Papers 143, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  8. Nicoletti Altimari, Sergio, 2001. "Does money lead inflation in the euro area?," Working Paper Series 63, European Central Bank.
  9. Francis X. Diebold & Roberto S. Mariano, 1991. "Comparing predictive accuracy I: an asymptotic test," Discussion Paper / Institute for Empirical Macroeconomics 52, Federal Reserve Bank of Minneapolis.
  10. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
  11. Neil R. Ericsson, 2008. "The Fragility of Sensitivity Analysis: An Encompassing Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 895-914, December.
  12. West, Kenneth D., 2001. "Encompassing tests when no model is encompassing," Journal of Econometrics, Elsevier, vol. 105(1), pages 287-308, November.
  13. Jansen, Eilev S., 2004. "Modelling inflation in the euro area," Working Paper Series 322, European Central Bank.
  14. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
  15. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
  16. Philip Franses, 2014. "Evaluating CPB’s Forecasts," De Economist, Springer, vol. 162(3), pages 215-221, September.
  17. Mihaela BRATU (SIMIONESCU), 2012. "A Strategy To Improve The Gdp Index Forcasts In Romania Using Moving Average Models Of Historical Errors Of The Dobrescu Macromodel," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 128-138, December.
  18. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
  19. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  20. Neil R. Ericsson & John S. Irons, 1995. "The Lucas critique in practice: theory without measurement," International Finance Discussion Papers 506, Board of Governors of the Federal Reserve System (U.S.).
  21. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
  22. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
  23. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
  24. David F. Hendry & Michael P. Clements, 1994. "Can Econometrics Improve Economic Forecasting?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 130(III), pages 267-298, September.
  25. Neil R. Ericsson, 2000. "Predictable uncertainty in economic forecasting," International Finance Discussion Papers 695, Board of Governors of the Federal Reserve System (U.S.).
  26. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
  27. Jaime R. Marquez, 1992. "Real exchange rates: measurement and implications for predicting U.S. external imbalances," International Finance Discussion Papers 427, Board of Governors of the Federal Reserve System (U.S.).
  28. Trecroci, Carmine & Vega, Juan Luis, 2000. "The information content of M3 for future inflation," Working Paper Series 33, European Central Bank.
  29. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
  30. Duo Qin & Sophie van Huellen & Qing Chao Wang & Thanos Moraitis, 2022. "Algorithmic Modelling of Financial Conditions for Macro Predictive Purposes: Pilot Application to USA Data," Econometrics, MDPI, vol. 10(2), pages 1-22, April.
  31. Neil R. Ericsson & David F. Hendry & Hong-Anh Tran, 1993. "Cointegration, seasonality, encompassing, and the demand for money in the United Kingdom," International Finance Discussion Papers 457, Board of Governors of the Federal Reserve System (U.S.).
  32. Aron, Janine & Muellbauer, John, 2012. "Improving forecasting in an emerging economy, South Africa: Changing trends, long run restrictions and disaggregation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 456-476.
  33. Eitrheim, Oyvind & Husebo, Tore Anders & Nymoen, Ragnar, 1999. "Equilibrium-correction vs. differencing in macroeconometric forecasting," Economic Modelling, Elsevier, vol. 16(4), pages 515-544, December.
  34. Dreger, Christian & Wolters, Jürgen, 2016. "On the Empirical Relevance of the Lucas Critique: the Case of Euro Area Money Demand," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 43(1), pages 61-82.
  35. Neil R. Ericsson, David F. Hendry & Kevin M. Prestiwch, "undated". "The UK Demand for Broad Money over the Long run," Economics Papers W29, Economics Group, Nuffield College, University of Oxford.
  36. Neil R. Ericsson, 2001. "Forecast uncertainty in economic modeling," International Finance Discussion Papers 697, Board of Governors of the Federal Reserve System (U.S.).
  37. Andrew B. Martinez, 2011. "Comparing Government Forecasts of the United States’ Gross Federal Debt," Working Papers 2011-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  38. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
  39. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
  40. 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.
  41. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
  42. Ashiya, Masahiro, 2007. "Forecast accuracy of the Japanese government: Its year-ahead GDP forecast is too optimistic," Japan and the World Economy, Elsevier, vol. 19(1), pages 68-85, January.
  43. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
  44. Michael S. Lee-Browne, 2019. "Estimating monetary policy rules in small open economies," Working Papers 2019-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  45. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
  46. Bardsen, Gunnar & Eitrheim, Oyvind & Jansen, Eilev S. & Nymoen, Ragnar, 2005. "The Econometrics of Macroeconomic Modelling," OUP Catalogue, Oxford University Press, number 9780199246502.
  47. Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
  48. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
  49. Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
  50. Ryan Ratcliff, 2010. "Predicting nominal exchange rate movements using skewness information from options prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 75-92.
  51. McMillan, David G. & Ruiz, Isabel, 2009. "Volatility persistence, long memory and time-varying unconditional mean: Evidence from 10 equity indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(2), pages 578-595, May.
  52. Robert Sollis, 2005. "Predicting returns and volatility with macroeconomic variables: evidence from tests of encompassing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(3), pages 221-231.
  53. Philip Hans Franses, 2011. "Model selection for forecast combination," Applied Economics, Taylor & Francis Journals, vol. 43(14), pages 1721-1727.
  54. Zidong An & Joao Tovar Jalles, 2020. "On the performance of US fiscal forecasts: government vs. private information," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(2), pages 367-391, June.
  55. Janine Aron & John Muellbauer, 2013. "New Methods for Forecasting Inflation, Applied to the US," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(5), pages 637-661, October.
  56. Clements, Michael P. & Hendry, David F., 1997. "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, Elsevier, vol. 13(3), pages 341-355, September.
  57. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
  58. Ericsson Neil R., 2008. "Comment on "Economic Forecasting in a Changing World" (by Michael Clements and David Hendry)," Capitalism and Society, De Gruyter, vol. 3(2), pages 1-18, October.
  59. Shiu-Sheng Chen, 2005. "A note on in-sample and out-of-sample tests for Granger causality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 453-464.
  60. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
  61. Hondroyiannis, George & Swamy, P. A. V. B. & Tavlas, George S., 2001. "Modelling the long-run demand for money in the United Kingdom: a random coefficient analysis," Economic Modelling, Elsevier, vol. 18(3), pages 475-501, August.
  62. Martinez, Andrew B., 2015. "How good are US government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 312-324.
  63. Mark P. Taylor & L. Bainaud, 1996. "Prévision du taux de change dollar canadien contre dollar américain : une approche en termes de "fondamentaux"," Économie et Prévision, Programme National Persée, vol. 123(2), pages 45-51.
  64. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
  65. Jing-Zhi Huang & Zhan Shi, 2023. "Machine-Learning-Based Return Predictors and the Spanning Controversy in Macro-Finance," Management Science, INFORMS, vol. 69(3), pages 1780-1804, March.
  66. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, 06.
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