IDEAS home Printed from https://ideas.repec.org/r/cor/louvco/1991022.html
   My bibliography  Save this item

To combine or not to combine? issues of combining forecasts

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Panos K. Pouliasis & Ilias D. Visvikis & Nikos C. Papapostolou & Alexander A. Kryukov, 2020. "A novel risk management framework for natural gas markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 430-459, March.
  2. Mirakyan, Atom & Meyer-Renschhausen, Martin & Koch, Andreas, 2017. "Composite forecasting approach, application for next-day electricity price forecasting," Energy Economics, Elsevier, vol. 66(C), pages 228-237.
  3. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
  4. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
  5. Daud Ali Aser & Esin Firuzan, 2022. "Improving Forecast Accuracy Using Combined Forecasts with Regard to Structural Breaks and ARCH Innovations," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(37), pages 1-25, December.
  6. Guerrero, Víctor M., 1995. "Linear combination of information in time series analysis," DES - Working Papers. Statistics and Econometrics. WS 10340, Universidad Carlos III de Madrid. Departamento de Estadística.
  7. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50, Emerald Group Publishing Limited.
  8. Issler, João Victor & Lima, Luiz Renato, 2009. "A panel data approach to economic forecasting: The bias-corrected average forecast," Journal of Econometrics, Elsevier, vol. 152(2), pages 153-164, October.
  9. Winford H. Masanjala & Chris Papageorgiou, 2008. "Rough and lonely road to prosperity: a reexamination of the sources of growth in Africa using Bayesian model averaging," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 671-682.
  10. Mont'Alverne Duarte, Angelo & Gaglianone, Wagner Piazza & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor, 2021. "Commodity prices and global economic activity: A derived-demand approach," Energy Economics, Elsevier, vol. 96(C).
  11. Eicher, Theo S. & Papageorgiou, Chris & Roehn, Oliver, 2007. "Unraveling the fortunes of the fortunate: An Iterative Bayesian Model Averaging (IBMA) approach," Journal of Macroeconomics, Elsevier, vol. 29(3), pages 494-514, September.
  12. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
  13. 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.
  14. Alexander W. Hoffmaister & Gabriela Saborío Muñoz & Ivannia Solano Chacón & Álvaro Solera Ramírez, 2002. "Aspectos teóricos y prácticos de la adopción de un sistema de convertibilidad en Ecuador," Monetaria, CEMLA, vol. 0(1), pages 51-74, enero-mar.
  15. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
  16. Zellner, Arnold & Tobias, Justin & Ryu, Hang, 1998. "Bayesian Method of Moments (BMOM) Analysis of Parametric and Semiparametric Regression Models," CUDARE Working Papers 198660, University of California, Berkeley, Department of Agricultural and Resource Economics.
  17. Rosen Valchev & Antony Davies, 2009. "Transparency, Performance, and Agency Budgets: A Rational Expectations Modeling Approach," Working Papers 2009-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  18. Hongyue Guo & Xiaodong Liu & Zhubin Sun, 2016. "Multivariate time series prediction using a hybridization of VARMA models and Bayesian networks," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2897-2909, December.
  19. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
  20. Hsiao, Cheng & Wan, Shui Ki, 2014. "Is there an optimal forecast combination?," Journal of Econometrics, Elsevier, vol. 178(P2), pages 294-309.
  21. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
  22. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  23. Xu, Ningzhe & Nie, Qifan & Liu, Jun & Jones, Steven, 2024. "Linking short- and long-term impacts of the COVID-19 pandemic on travel behavior and travel preferences in Alabama: A machine learning-supported path analysis," Transport Policy, Elsevier, vol. 151(C), pages 46-62.
  24. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
  25. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
  26. Konstantinos Giannakas & K. Tran & Vangelis Tzouvelekas, 1999. "On the Choice of Functional Form in Stochastic Frontiers Models: A Box-Cox Approach," Working Papers 9915, University of Crete, Department of Economics.
  27. repec:hal:journl:peer-00844809 is not listed on IDEAS
  28. Marsh, L.C.Lawrence C. & Zellner, Arnold, 2004. "Bayesian solutions to graduate admissions and related selection problems," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 405-426.
  29. Zellner, Arnold, 2002. "Comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 499-502, December.
  30. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
  31. Kajal Lahiri & Fushang Liu, 2006. "ARCH Models for Multi-period Forecast Uncertainty: A Reality Check Using a Panel of Density Forecasts," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 321-363, Emerald Group Publishing Limited.
  32. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
  33. repec:ind:nipfwp:17 is not listed on IDEAS
  34. Ruiz, Edilberto & Nieto, Fabio H., 2000. "A note on linear combination of predictors," Statistics & Probability Letters, Elsevier, vol. 47(4), pages 351-356, May.
  35. George Papadopoulos & Savas Papadopoulos & Thomas Sager, 2016. "Credit risk stress testing for EU15 banks: a model combination approach," Working Papers 203, Bank of Greece.
  36. Li Li & Yanfei Kang & Fotios Petropoulos & Feng Li, 2022. "Feature-based intermittent demand forecast combinations: bias, accuracy and inventory implications," Papers 2204.08283, arXiv.org, revised Aug 2022.
  37. Poirier, Dale J., 1997. "Comparing and choosing between two models with a third model in the background," Journal of Econometrics, Elsevier, vol. 78(2), pages 139-151, June.
  38. Zellner, Arnold & Tobias, Justin, 2001. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 121-140, February.
  39. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
  40. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
  41. Elena Grubisic, 2002. "Determinantes de la evolución del crédito al sector privado en Argentina en el período 1994- 2000," Monetaria, CEMLA, vol. 0(1), pages 75-103, enero-mar.
  42. Wagner Piazza Gaglianone & João Victor Issler, 2014. "Microfounded Forecasting," Working Papers Series 372, Central Bank of Brazil, Research Department.
  43. Elliott, Graham & Timmermann, Allan, 2004. "Optimal forecast combinations under general loss functions and forecast error distributions," Journal of Econometrics, Elsevier, vol. 122(1), pages 47-79, September.
  44. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
  45. Wagner Piazza Gaglianone & Waldyr Dutra Areosa, 2016. "Financial Conditions Indicators for Brazil," Working Papers Series 435, Central Bank of Brazil, Research Department.
  46. M. Murty & Surender Kumar & Kishore Dhavala, 2007. "Measuring environmental efficiency of industry: a case study of thermal power generation in India," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(1), pages 31-50, September.
  47. Jinliang Zhang & YiMing Wei & Zhong-fu Tan & Wang Ke & Wei Tian, 2017. "A Hybrid Method for Short-Term Wind Speed Forecasting," Sustainability, MDPI, vol. 9(4), pages 1-10, April.
  48. Sune Karlsson & Tor Jacobson, 2004. "Finding good predictors for inflation: a Bayesian model averaging approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 479-496.
  49. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
  50. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
  51. Glauber Eduardo de Oliveira Santos, 2009. "Research Note: Forecasting Tourism Demand by Disaggregated Time Series – Empirical Evidence from Spain," Tourism Economics, , vol. 15(2), pages 467-472, June.
  52. Issler, João Victor & Soares, Ana Flávia, 2019. "Central Bank credibility and inflation expectations: a microfounded forecasting approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 812, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
  53. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
  54. Georgios Papadopoulos & Dionysios Chionis & Nikolaos P. Rachaniotis, 2018. "Macro-financial linkages during tranquil and crisis periods: evidence from stressed economies," Risk Management, Palgrave Macmillan, vol. 20(2), pages 142-166, May.
  55. Saghafian, Soroush & Tomlin, Brian & Biller, Stephan, 2018. "The Internet of Things and Information Fusion: Who Talks to Who?," Working Paper Series rwp18-009, Harvard University, John F. Kennedy School of Government.
  56. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
  57. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
  58. Jacques J. Polak, 2002. "Los dos enfoques de la balanza de pagos: el keynesiano y el johnsoniano," Monetaria, CEMLA, vol. 0(1), pages 1-27, enero-mar.
  59. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2017. "Forecasting economic activity by Bayesian bridge model averaging," Empirical Economics, Springer, vol. 53(1), pages 21-40, August.
  60. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
  61. Nowotarski, Jakub & Liu, Bidong & Weron, Rafał & Hong, Tao, 2016. "Improving short term load forecast accuracy via combining sister forecasts," Energy, Elsevier, vol. 98(C), pages 40-49.
  62. Francisco Marcos Rodrigues Figueiredo & Roberta Blass Staub, 2002. "Evaluación y combinación de mediciones de inflación de base para Brasil," Monetaria, CEMLA, vol. 0(1), pages 29-50, enero-mar.
  63. Li Wang & Haofei Zou & Jia Su & Ling Li & Sohail Chaudhry, 2013. "An ARIMA‐ANN Hybrid Model for Time Series Forecasting," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 244-259, May.
  64. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
  65. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
  66. Till Weigt & Bernd Wilfling, 2021. "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 686-699, July.
  67. Kumar, Surender & Gupta, Sreekant, 2004. "Resource use efficiency of US electricity generating plants during the SO2 trading regime: A distance function approach," Working Papers 04/17, National Institute of Public Finance and Policy.
  68. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
  69. Corradi, Valentina & Swanson, Norman R. & Olivetti, Claudia, 2001. "Predictive ability with cointegrated variables," Journal of Econometrics, Elsevier, vol. 104(2), pages 315-358, September.
  70. repec:fgv:epgewp:736 is not listed on IDEAS
  71. Goodness C. Aye & Eric D. Mungatana, 2013. "Evaluating The Performance Of Small Scale Maize Producers In Nigeria: An Integrated Distance Function Approach," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 25(2), pages 79-92, July.
  72. Yang, Dazhi & Yang, Guoming & Liu, Bai, 2023. "Combining quantiles of calibrated solar forecasts from ensemble numerical weather prediction," Renewable Energy, Elsevier, vol. 215(C).
  73. repec:npf:wpaper:17 is not listed on IDEAS
  74. Thomas Theobald, 2012. "Combining Recession Probability Forecasts from a Dynamic Probit Indicator," IMK Working Paper 89-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
  75. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
  76. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
  77. Tripathi Manas & Kumar Saurabh & Inani Sarveshwar Kumar, 2021. "Exchange Rate Forecasting Using Ensemble Modeling for Better Policy Implications," Journal of Time Series Econometrics, De Gruyter, vol. 13(1), pages 43-71, January.
  78. H. Kent Baker & Satish Kumar & Debidutta Pattnaik, 2021. "Research constituents, intellectual structure, and collaboration pattern in the Journal of Forecasting: A bibliometric analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 577-602, July.
  79. N.D. Geomelos & E. Xideas, 2014. "Forecasting spot prices in bulk shipping using multivariate and univariate models," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-37, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.