The M3-Competition: results, conclusions and implications

Citations

Cited by:

1. 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.
2. Armstrong, J. Scott, 2007. "Significance tests harm progress in forecasting," International Journal of Forecasting, Elsevier, vol. 23(2), pages 321-327.
   • Armstrong, J. Scott, 2007. "Significance Tests Harm Progress in Forecasting," MPRA Paper 81664, University Library of Munich, Germany.
3. Pantelis Agathangelou & Demetris Trihinas & Ioannis Katakis, 2020. "A Multi-Factor Analysis of Forecasting Methods: A Study on the M4 Competition," Data, MDPI, vol. 5(2), pages 1-24, April.
4. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
   • Li Li & Yanfei Kang & Feng Li, 2021. "Bayesian forecast combination using time-varying features," Papers 2108.02082, arXiv.org, revised Jun 2022.
5. Kang, Yanfei & Spiliotis, Evangelos & Petropoulos, Fotios & Athiniotis, Nikolaos & Li, Feng & Assimakopoulos, Vassilios, 2021. "Déjà vu: A data-centric forecasting approach through time series cross-similarity," Journal of Business Research, Elsevier, vol. 132(C), pages 719-731.
6. Gorr, Wilpen L. & Schneider, Matthew J., 2013. "Large-change forecast accuracy: Reanalysis of M3-Competition data using receiver operating characteristic analysis," International Journal of Forecasting, Elsevier, vol. 29(2), pages 274-281.
7. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
8. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
   • Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
9. Fritsch, Markus & Haupt, Harry & Schnurbus, Joachim, 2025. "Efficiency of poll-based multi-period forecasting systems for German state elections," International Journal of Forecasting, Elsevier, vol. 41(2), pages 670-688.
10. Spiliotis, Evangelos & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2019. "Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors," International Journal of Production Economics, Elsevier, vol. 209(C), pages 92-102.
11. Sbrana, Giacomo & Silvestrini, Andrea, 2020. "Forecasting with the damped trend model using the structural approach," International Journal of Production Economics, Elsevier, vol. 226(C).
12. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
    • David Hendry, 2011. "Unpredictability in Economic Analyis, Econometric Modelling and Forecasting," Economics Series Working Papers 551, University of Oxford, Department of Economics.
    • David F. Hendry & Grayham E. Mizon, 2013. "Unpredictability in Economic Analysis, Econometric Modeling and Forecasting," Economics Papers 2013-W04, Economics Group, Nuffield College, University of Oxford.
13. S. Buxton & Kostas Nikolopoulos & M. Khammash & P. Stern, 2015. "Modelling and Forecasting Branded and Generic Pharmaceutical Life Cycles: Assessment of the Number of Dispensed Units," Working Papers 15004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
14. Bouckaert, Nicolas & Van den Heede, Koen & Van de Voorde, Carine, 2018. "Improving the forecasting of hospital services: A comparison between projections and actual utilization of hospital services," Health Policy, Elsevier, vol. 122(7), pages 728-736.
15. Thomas Åstebro & Samir Elhedhli, 2006. "The Effectiveness of Simple Decision Heuristics: Forecasting Commercial Success for Early-Stage Ventures," Management Science, INFORMS, vol. 52(3), pages 395-409, March.
    • Thomas Astebro & Samir Elhedhli, 2006. "The effectiveness of simple decision heuristics : Forecasting commercial success for early-stage ventures," Post-Print hal-00476866, HAL.
16. Sailesh BHAGHOE & Gavin OOFT, 2023. "Nowcasting quarterly GDP growth in Suriname with factor-MIDAS and mixed-frequency VAR models," Journal of Economics and Political Economy, EconSciences Journals, vol. 10(1), pages 1-18, March.
    • Sailesh Bhaghoe & Gavin Ooft, 2021. "Nowcasting Quarterly GDP Growth in Suriname with Factor-MIDAS and Mixed-Frequency VAR Models," Studies in Applied Economics 176, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
17. Thomakos, Dimitrios D. & Guerard, John Jr., 2004. "Naive, ARIMA, nonparametric, transfer function and VAR models: A comparison of forecasting performance," International Journal of Forecasting, Elsevier, vol. 20(1), pages 53-67.
18. de Vilmarest, Joseph & Werge, Nicklas, 2025. "An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1514-1520.
19. Athanasopoulos, George & Hyndman, Rob J., 2011. "The value of feedback in forecasting competitions," International Journal of Forecasting, Elsevier, vol. 27(3), pages 845-849.
    • Athanasopoulos, George & Hyndman, Rob J., 2011. "The value of feedback in forecasting competitions," International Journal of Forecasting, Elsevier, vol. 27(3), pages 845-849, July.
    • George Athanasopoulos & Rob J Hyndman, 2011. "The value of feedback in forecasting competitions," Monash Econometrics and Business Statistics Working Papers 3/11, Monash University, Department of Econometrics and Business Statistics.
20. J. Bermúdez & J. Segura & E. Vercher, 2008. "SIOPRED: a prediction and optimisation integrated system for demand," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 258-271, December.
21. Nedeljković, Miroslav & Potrebić, Velibor, 2020. "Forecasting of Apple Production in the Republic of Srpska," Western Balkan Journal of Agricultural Economics and Rural Development (WBJAERD), Institute of Agricultural Economics, vol. 2(01), January.
22. J D Bermúdez & J V Segura & E Vercher, 2006. "Improving demand forecasting accuracy using nonlinear programming software," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 94-100, January.
23. George Athanasopoulos & Nikolaos Kourentzes, 2021. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 10/21, Monash University, Department of Econometrics and Business Statistics.
24. Ericsson, Neil R., 2017. "Economic forecasting in theory and practice: An interview with David F. Hendry," International Journal of Forecasting, Elsevier, vol. 33(2), pages 523-542.
    • Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice: An Interview with David F. Hendry," Working Papers 2016-012, The George Washington University, The Center for Economic Research.
    • Neil R. Ericsson, 2016. "Economic Forecasting in Theory and Practice : An Interview with David F. Hendry," International Finance Discussion Papers 1184, Board of Governors of the Federal Reserve System (U.S.).
25. Naoum Tsolakis & Jagjit Singh Srai, 2018. "Mapping supply dynamics in renewable feedstock enabled industries: A systems theory perspective on ‘green’ pharmaceuticals," Operations Management Research, Springer, vol. 11(3), pages 83-104, December.
26. Dean W. Wichern & Benito E. Flores, 2005. "Evaluating forecasts: a look at aggregate bias and accuracy measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 433-451.
27. Van Belle, Jente & Crevits, Ruben & Verbeke, Wouter, 2023. "Improving forecast stability using deep learning," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1333-1350.
28. Hyndman, Rob J. & Koehler, Anne B. & Snyder, Ralph D. & Grose, Simone, 2002. "A state space framework for automatic forecasting using exponential smoothing methods," International Journal of Forecasting, Elsevier, vol. 18(3), pages 439-454.
    • Hyndman, R.J. & Koehler, A.B. & Snyder, R.D. & Grose, S., 2000. "A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods," Monash Econometrics and Business Statistics Working Papers 9/00, Monash University, Department of Econometrics and Business Statistics.
29. David Aikman & Mirta Galesic & Gerd Gigerenzer & Sujit Kapadia & Konstantinos Katsikopoulos & Amit Kothiyal & Emma Murphy & Tobias Neumann, 2021. "Taking uncertainty seriously: simplicity versus complexity in financial regulation [Uncertainty in macroeconomic policy-making: art or science?]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(2), pages 317-345.
    • Aikman, David & Galesic, Mirta & Gigerenzer, Gerd & Kapadia, Sujit & Katsikopolous, Konstantinos & Kothiyal, Amit & Murphy, Emma & Neumann, Tobias, 2014. "Taking Uncertainty Seriously: Simplicity versus Complexity in Financial Regulation," MPRA Paper 59908, University Library of Munich, Germany.
30. Scheibehenne, Benjamin & Broder, Arndt, 2007. "Predicting Wimbledon 2005 tennis results by mere player name recognition," International Journal of Forecasting, Elsevier, vol. 23(3), pages 415-426.
31. Taylor, James W., 2003. "Exponential smoothing with a damped multiplicative trend," International Journal of Forecasting, Elsevier, vol. 19(4), pages 715-725.
32. Hendry, David F. & Mizon, Grayham E., 2001. "Reformulating empirical macro-econometric modelling," Discussion Paper Series In Economics And Econometrics 104, Economics Division, School of Social Sciences, University of Southampton.
33. Wong, W.K. & Guo, Z.X. & Leung, S.Y.S., 2010. "Partially connected feedforward neural networks on Apollonian networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5298-5307.
34. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    • Jennifer Castle & Jurgen Doornik & David Hendry, 2018. "Selecting a Model for Forecasting," Economics Series Working Papers 861, University of Oxford, Department of Economics.
35. Brighton, Henry & Gigerenzer, Gerd, 2015. "The bias bias," Journal of Business Research, Elsevier, vol. 68(8), pages 1772-1784.
36. E S Gardner & E McKenzie, 2011. "Why the damped trend works," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1177-1180, June.
37. David Orrell, 2019. "Commentary on 'Addressing the Malaise in Neoclassical Economics: A Call for Partial Models'," Economic Thought, World Economics Association, vol. 8(1), pages 53-55, June.
38. Chiang, Chung-Yean & Lin, Winston T. & Suresh, Nallan C., 2016. "An empirically-simulated investigation of the impact of demand forecasting on the bullwhip effect: Evidence from U.S. auto industry," International Journal of Production Economics, Elsevier, vol. 177(C), pages 53-65.
39. Wallström, Peter & Segerstedt, Anders, 2010. "Evaluation of forecasting error measurements and techniques for intermittent demand," International Journal of Production Economics, Elsevier, vol. 128(2), pages 625-636, December.
40. Miller, Don M. & Williams, Dan, 2004. "Damping seasonal factors: Shrinkage estimators for the X-12-ARIMA program," International Journal of Forecasting, Elsevier, vol. 20(4), pages 529-549.
41. Gardner, Everette Shaw & Acar, Yavuz, 2016. "The forecastability quotient reconsidered," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1208-1211.
42. Wellens, Arnoud P. & Udenio, Maxi & Boute, Robert N., 2022. "Transfer learning for hierarchical forecasting: Reducing computational efforts of M5 winning methods," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1482-1491.
43. Johannes Müller-Trede & Shoham Choshen-Hillel & Meir Barneron & Ilan Yaniv, 2018. "The Wisdom of Crowds in Matters of Taste," Management Science, INFORMS, vol. 64(4), pages 1779-1803, April.
44. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    • David Hendry & Michael P. Clements, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Papers 2002-W11, Economics Group, Nuffield College, University of Oxford.
    • Clements, Michael P. & Hendry, David F., 2001. "Economic forecasting: some lessons from recent research," Working Paper Series 82, European Central Bank.
    • Hendry, David F & Michael P. Clements, 2002. "Economic Forecasting: Some Lessons from Recent Research," Royal Economic Society Annual Conference 2002 99, Royal Economic Society.
    • David Hendry & Michael P. Clements & Department of Economics & University of Warwick, 2001. "Economic Forecasting: Some Lessons from Recent Research," Economics Series Working Papers 78, University of Oxford, Department of Economics.
45. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
46. Makridakis, Spyros & Taleb, Nassim, 2009. "Decision making and planning under low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 716-733, October.
47. Cui, Geng & Imura, Naoto & Nishinari, Katsuhiro & Ezaki, Takahiro, 2025. "On order smoothing interpolating the order-up-to and constant order policies," Omega, Elsevier, vol. 136(C).
48. Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2015. "Forecasting Multivariate Time Series with the Theta Method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 220-229, April.
    • Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2013. "Forecasting multivariate time series with the Theta Method," Working Papers 13004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
49. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
50. Ahumada, H. & Cornejo, M., 2016. "Forecasting food prices: The case of corn, soybeans and wheat," International Journal of Forecasting, Elsevier, vol. 32(3), pages 838-848.
51. Taleb, Nassim Nicholas, 2009. "Errors, robustness, and the fourth quadrant," International Journal of Forecasting, Elsevier, vol. 25(4), pages 744-759, October.
52. Gaojun Zhang & Jinfeng Wu & Bing Pan & Junyi Li & Minjie Ma & Muzi Zhang & Jian Wang, 2017. "Improving daily occupancy forecasting accuracy for hotels based on EEMD-ARIMA model," Tourism Economics, , vol. 23(7), pages 1496-1514, November.
53. Jaap Spreeuw & Iqbal Owadally & Muhammad Kashif, 2022. "Projecting Mortality Rates Using a Markov Chain," Mathematics, MDPI, vol. 10(7), pages 1-18, April.
54. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
55. Madden, Gary G & Coble-Neal, Grant, 2004. "Internet traffic dynamics," MPRA Paper 10827, University Library of Munich, Germany.
56. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
57. Tao Xiong & Miao Li & Jia Cao, 2023. "Do Futures Prices Help Forecast Spot Prices? Evidence from China’s New Live Hog Futures," Agriculture, MDPI, vol. 13(9), pages 1-16, August.
58. Oreshkin, Boris N. & Dudek, Grzegorz & Pełka, Paweł & Turkina, Ekaterina, 2021. "N-BEATS neural network for mid-term electricity load forecasting," Applied Energy, Elsevier, vol. 293(C).
59. Puchalsky, Weslly & Ribeiro, Gabriel Trierweiler & da Veiga, Claudimar Pereira & Freire, Roberto Zanetti & Santos Coelho, Leandro dos, 2018. "Agribusiness time series forecasting using Wavelet neural networks and metaheuristic optimization: An analysis of the soybean sack price and perishable products demand," International Journal of Production Economics, Elsevier, vol. 203(C), pages 174-189.
60. Athanasopoulos, George & Hyndman, Rob J. & Song, Haiyan & Wu, Doris C., 2011. "The tourism forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 822-844.
    • Athanasopoulos, George & Hyndman, Rob J. & Song, Haiyan & Wu, Doris C., 2011. "The tourism forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 822-844, July.
    • George Athanasopoulos & Rob J Hyndman & Haiyan Song & Doris C Wu, 2008. "The tourism forecasting competition," Monash Econometrics and Business Statistics Working Papers 10/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.
61. Darin, Sarah Goodrich & Stellwagen, Eric, 2020. "Forecasting the M4 competition weekly data: Forecast Pro’s winning approach," International Journal of Forecasting, Elsevier, vol. 36(1), pages 135-141.
62. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
    • Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
63. Mun, Mak Kit & Chong, Choo Wei, 2018. "Forecasting Movie Demand Using Total and Split Exponential Smoothing," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 52(2), pages 81-94.
64. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
65. João A. Bastos, 2019. "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 231-242, October.
    • Bastos, João A., 2019. "Forecasting the capacity of mobile networks," MPRA Paper 92727, University Library of Munich, Germany.
66. Rajapaksha, Dilini & Bergmeir, Christoph & Hyndman, Rob J., 2023. "LoMEF: A framework to produce local explanations for global model time series forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1424-1447.
67. Dean Fantazzini, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
    • Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
68. Petropoulos, Fotios & Svetunkov, Ivan, 2020. "A simple combination of univariate models," International Journal of Forecasting, Elsevier, vol. 36(1), pages 110-115.
69. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    • Timmermann Allan & Capistrán Carlos, 2006. "Forecast Combination with Entry and Exit of Experts," Working Papers 2006-08, Banco de México.
    • Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
70. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
71. 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.
72. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
73. Nicholas G. Reich & Justin Lessler & Krzysztof Sakrejda & Stephen A. Lauer & Sopon Iamsirithaworn & Derek A. T. Cummings, 2016. "Case Study in Evaluating Time Series Prediction Models Using the Relative Mean Absolute Error," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 285-292, July.
74. Avci, Ezgi & Ketter, Wolfgang & van Heck, Eric, 2018. "Managing electricity price modeling risk via ensemble forecasting: The case of Turkey," Energy Policy, Elsevier, vol. 123(C), pages 390-403.
75. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E., 2010. "Judging the judges through accuracy-implication metrics: The case of inventory forecasting," International Journal of Forecasting, Elsevier, vol. 26(1), pages 134-143, January.
76. Neubauer, Lukas & Filzmoser, Peter, 2024. "Improving forecasts for heterogeneous time series by “averaging”, with application to food demand forecasts," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1622-1645.
77. Han, Weiwei & Wang, Xun & Petropoulos, Fotios & Wang, Jing, 2019. "Brain imaging and forecasting: Insights from judgmental model selection," Omega, Elsevier, vol. 87(C), pages 1-9.
78. Dimitrios Sarris & Evangelos Spiliotis & Vassilios Assimakopoulos, 2020. "Exploiting resampling techniques for model selection in forecasting: an empirical evaluation using out-of-sample tests," Operational Research, Springer, vol. 20(2), pages 701-721, June.
79. İhsan Erdem Kayral & Tuğba Sarı & Nisa Şansel Tandoğan Aktepe, 2023. "Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey," Sustainability, MDPI, vol. 15(22), pages 1-20, November.
80. Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
81. Kumar Shivam & Jong-Chyuan Tzou & Shang-Chen Wu, 2020. "Multi-Step Short-Term Wind Speed Prediction Using a Residual Dilated Causal Convolutional Network with Nonlinear Attention," Energies, MDPI, vol. 13(7), pages 1-29, April.
82. Giuseppe Ciaburro & Gino Iannace, 2021. "Machine Learning-Based Algorithms to Knowledge Extraction from Time Series Data: A Review," Data, MDPI, vol. 6(6), pages 1-30, May.
83. Hendry, David F. & Mizon, Grayham E., 2001. "Reformulating empirical macro-econometric modelling," Discussion Paper Series In Economics And Econometrics 0104, Economics Division, School of Social Sciences, University of Southampton.
84. Sbrana, Giacomo & Silvestrini, Andrea, 2025. "The structural Theta method and its predictive performance in the M4-Competition," International Journal of Forecasting, Elsevier, vol. 41(3), pages 940-952.
    • Giacomo Sbrana & Andrea Silvestrini, 2024. "The structural Theta method and its predictive performance in the M4-Competition," Temi di discussione (Economic working papers) 1457, Bank of Italy, Economic Research and International Relations Area.
85. Daniel C Medina & Sally E Findley & Boubacar Guindo & Seydou Doumbia, 2007. "Forecasting Non-Stationary Diarrhea, Acute Respiratory Infection, and Malaria Time-Series in Niono, Mali," PLOS ONE, Public Library of Science, vol. 2(11), pages 1-13, November.
86. Hyndman, Rob J., 2020. "A brief history of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 36(1), pages 7-14.
    • Rob J Hyndman, 2019. "A Brief History of Forecasting Competitions," Monash Econometrics and Business Statistics Working Papers 3/19, Monash University, Department of Econometrics and Business Statistics.
87. Adam Nelson-Archer & Aleia Sen & Meena Al Hasani & Sofia Davila & Jessica Le & Omar Abbouchi, 2025. "Forecasting Labor Markets with LSTNet: A Multi-Scale Deep Learning Approach," Papers 2507.01979, arXiv.org.
88. Joanna Bruzda, 2020. "Multistep quantile forecasts for supply chain and logistics operations: bootstrapping, the GARCH model and quantile regression based approaches," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 309-336, March.
89. Jaganathan, Srihari & Prakash, P.K.S., 2020. "A combination-based forecasting method for the M4-competition," International Journal of Forecasting, Elsevier, vol. 36(1), pages 98-104.
90. Lu, Emiao & Handl, Julia & Xu, Dong-ling, 2018. "Determining analogies based on the integration of multiple information sources," International Journal of Forecasting, Elsevier, vol. 34(3), pages 507-528.
91. Milan Bašta, 2018. "Time series forecasting with a prior wavelet-based denoising step," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2018(1), pages 5-24.
92. Johannes Müller-Trede & Shoham Choshen-Hillel & Meir Barneron & Ilan Yaniv, 2017. "The Wisdom of Crowds in Matters of Taste," Discussion Paper Series dp709, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
93. Konstantinos Nikolopoulos, 2010. "Forecasting with quantitative methods: the impact of special events in time series," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 947-955.
94. Souhaib Ben Taieb & Rob J Hyndman, 2014. "Boosting multi-step autoregressive forecasts," Monash Econometrics and Business Statistics Working Papers 13/14, Monash University, Department of Econometrics and Business Statistics.
95. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    • Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
96. Li, Xixi & Bai, Yun & Kang, Yanfei, 2022. "Exploring the social influence of the Kaggle virtual community on the M5 competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1507-1518.
97. Łukasz Lenart & Agnieszka Leszczyńska-Paczesna, 2016. "Do market prices improve the accuracy of inflation forecasting in Poland? A disaggregated approach," Bank i Kredyt, Narodowy Bank Polski, vol. 47(5), pages 365-394.
98. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
99. Zhuo Chen & Seong-Hoon Cho & Neelam Poudyal & Roland K. Roberts, 2009. "Forecasting Housing Prices under Different Market Segmentation Assumptions," Urban Studies, Urban Studies Journal Limited, vol. 46(1), pages 167-187, January.
100. 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.
101. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2017. "Persistence and cycles in the us federal funds rate," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 1-8.
     • Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in the US Federal Funds Rate," Discussion Papers of DIW Berlin 1255, DIW Berlin, German Institute for Economic Research.
     • Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in the US Federal Funds Rate," CESifo Working Paper Series 4035, CESifo.
102. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
103. Taylor, James W., 2007. "Forecasting daily supermarket sales using exponentially weighted quantile regression," European Journal of Operational Research, Elsevier, vol. 178(1), pages 154-167, April.
104. Chan, Chi Kin & Witt, Stephen F. & Lee, Y.C.E. & Song, H., 2010. "Tourism forecast combination using the CUSUM technique," Tourism Management, Elsevier, vol. 31(6), pages 891-897.
105. J D Bermúdez & J V Segura & E Vercher, 2010. "Bayesian forecasting with the Holt–Winters model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 164-171, January.
106. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
     • Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Does forecast combination improve Norges Bank inflation forecasts?," Working Paper 2009/01, Norges Bank.
107. Petropoulos, Fotios & Wang, Xun & Disney, Stephen M., 2019. "The inventory performance of forecasting methods: Evidence from the M3 competition data," International Journal of Forecasting, Elsevier, vol. 35(1), pages 251-265.
108. Kolassa, Stephan, 2011. "Combining exponential smoothing forecasts using Akaike weights," International Journal of Forecasting, Elsevier, vol. 27(2), pages 238-251, April.
109. Brent Moritz & Enno Siemsen & Mirko Kremer, 2014. "Judgmental Forecasting: Cognitive Reflection and Decision Speed," Production and Operations Management, Production and Operations Management Society, vol. 23(7), pages 1146-1160, July.
110. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Combination of long term and short term forecasts, with application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 27(3), pages 870-886, July.
111. Debabrata Mukhopadhyay & Nityananda Sarkar, 2013. "Stock Returns Under Alternative Volatility and Distributional Assumptions: The Case for India," International Econometric Review (IER), Econometric Research Association, vol. 5(1), pages 1-19, April.
112. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
113. Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.
114. Fotios Petropoulos & Evangelos Spiliotis, 2021. "The Wisdom of the Data: Getting the Most Out of Univariate Time Series Forecasting," Forecasting, MDPI, vol. 3(3), pages 1-20, June.
115. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
116. Bojer, Casper Solheim & Meldgaard, Jens Peder, 2021. "Kaggle forecasting competitions: An overlooked learning opportunity," International Journal of Forecasting, Elsevier, vol. 37(2), pages 587-603.
117. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
118. Anton Antonov GERUNOV, 2016. "Automating Analytics: Forecasting Time Series in Economics and Business," Journal of Economics and Political Economy, KSP Journals, vol. 3(2), pages 340-349, June.
     • Gerunov, Anton, 2016. "Automating Analytics: Forecasting Time Series in Economics and Business," MPRA Paper 71010, University Library of Munich, Germany.
119. Fennell, Mark & Murphy, James E. & Armstrong, Cristina & Gallagher, Tommy & Osborne, Bruce, 2012. "Plant Spread Simulator: A model for simulating large-scale directed dispersal processes across heterogeneous environments," Ecological Modelling, Elsevier, vol. 230(C), pages 1-10.
120. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "M5 accuracy competition: Results, findings, and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1346-1364.
121. Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2017. "Forecasting with temporal hierarchies," European Journal of Operational Research, Elsevier, vol. 262(1), pages 60-74.
     • George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
     • Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2015. "Forecasting with Temporal Hierarchies," MPRA Paper 66362, University Library of Munich, Germany.
122. Lin, Jiahe & Michailidis, George, 2024. "A multi-task encoder-dual-decoder framework for mixed frequency data prediction," International Journal of Forecasting, Elsevier, vol. 40(3), pages 942-957.
123. Vitor Azevedo & Georg Sebastian Kaiser & Sebastian Mueller, 2023. "Stock market anomalies and machine learning across the globe," Journal of Asset Management, Palgrave Macmillan, vol. 24(5), pages 419-441, September.
124. Ferbar Tratar, Liljana, 2015. "Forecasting method for noisy demand," International Journal of Production Economics, Elsevier, vol. 161(C), pages 64-73.
125. Claudio M. Rocco & Kash Barker & Jose Moronta, 2022. "Determining the best algorithm to detect community structures in networks: application to power systems," Environment Systems and Decisions, Springer, vol. 42(2), pages 251-264, June.
126. James W. Taylor, 2008. "A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center," Management Science, INFORMS, vol. 54(2), pages 253-265, February.
127. Syntetos, Aris A. & Boylan, John E., 2005. "The accuracy of intermittent demand estimates," International Journal of Forecasting, Elsevier, vol. 21(2), pages 303-314.
128. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "Predicting/hypothesizing the findings of the M5 competition," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1337-1345.
129. Choe, Geon Ho & Choi, So Eun & Jang, Hyun Jin, 2020. "Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
130. Clements, Michael P. & Beatriz Galvao, Ana, "undated". "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," Economic Research Papers 270771, University of Warwick - Department of Economics.
     • Clements, Michael P. & Galvão, Ana Beatriz, 2010. "Real-time Forecasting of Inflation and Output Growth in the Presence of Data Revisions," The Warwick Economics Research Paper Series (TWERPS) 953, University of Warwick, Department of Economics.
131. Toyin Clottey, 2016. "Development and evaluation of a rolling horizon purchasing policy for cores," International Journal of Production Research, Taylor & Francis Journals, vol. 54(9), pages 2780-2790, May.
132. Anton A. Romanov & Aleksey A. Filippov & Valeria V. Voronina & Gleb Guskov & Nadezhda G. Yarushkina, 2021. "Modeling the Context of the Problem Domain of Time Series with Type-2 Fuzzy Sets," Mathematics, MDPI, vol. 9(22), pages 1-16, November.
133. Bjørnland, Hilde C. & Gerdrup, Karsten & Jore, Anne Sofie & Smith, Christie & Thorsrud, Leif Anders, 2011. "Weights and pools for a Norwegian density combination," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 61-76, January.
     • Hilde Bjørnland & Karsten Gerdrup & Christie Smith & Anne Sofie Jore & Leif Anders Thorsrud, 2010. "Weights and pools for a Norwegian density combination," Working Paper 2010/06, Norges Bank.
134. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2018. "The M4 Competition: Results, findings, conclusion and way forward," International Journal of Forecasting, Elsevier, vol. 34(4), pages 802-808.
135. Ahmad M Awajan & Mohd Tahir Ismail & S AL Wadi, 2018. "Improving forecasting accuracy for stock market data using EMD-HW bagging," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-20, July.
136. Fildes, Robert & Petropoulos, Fotios, 2015. "Is there a Golden Rule?," Journal of Business Research, Elsevier, vol. 68(8), pages 1742-1745.
137. K. K. Furmanov & Yu. V. Turovets, 2024. "Assessing the Impact of External Shocks on the Development of the Manufacturing Industry," Studies on Russian Economic Development, Springer, vol. 35(5), pages 697-706, October.
138. Jiří Šindelář, 2019. "Sales forecasting in financial distribution: a comparison of quantitative forecasting methods," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 24(3), pages 69-80, December.
139. Beaumont, Adrian N., 2014. "Data transforms with exponential smoothing methods of forecasting," International Journal of Forecasting, Elsevier, vol. 30(4), pages 918-927.
140. A A Syntetos & J E Boylan & S M Disney, 2009. "Forecasting for inventory planning: a 50-year review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 149-160, May.
141. Clements Michael P. & Hendry David F., 2008. "Economic Forecasting in a Changing World," Capitalism and Society, De Gruyter, vol. 3(2), pages 1-20, October.
142. Prestwich, S.D. & Tarim, S.A. & Rossi, R., 2021. "Intermittency and obsolescence: A Croston method with linear decay," International Journal of Forecasting, Elsevier, vol. 37(2), pages 708-715.
143. Magdalena Sycińska-Dziarnowska & Liliana Szyszka-Sommerfeld & Karolina Kłoda & Michele Simeone & Krzysztof Woźniak & Gianrico Spagnuolo, 2021. "Mental Health Interest and Its Prediction during the COVID-19 Pandemic Using Google Trends," IJERPH, MDPI, vol. 18(23), pages 1-14, November.
144. Villegas, Marco A. & Pedregal, Diego J., 2019. "Automatic selection of unobserved components models for supply chain forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 157-169.
145. Firuz Kamalov & Hana Sulieman & Sherif Moussa & Jorge Avante Reyes & Murodbek Safaraliev, 2024. "Powering Electricity Forecasting with Transfer Learning," Energies, MDPI, vol. 17(3), pages 1-13, January.
146. Hendry, David F., 2006. "Robustifying forecasts from equilibrium-correction systems," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 399-426.
147. Spithourakis, Georgios P. & Petropoulos, Fotios & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2015. "Amplifying the learning effects via a Forecasting and Foresight Support System," International Journal of Forecasting, Elsevier, vol. 31(1), pages 20-32.
148. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2021. "Point and interval forecasting of electricity supply via pruned ensembles," Energy, Elsevier, vol. 232(C).
149. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
     • Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.
150. Petropoulos, Fotios & Makridakis, Spyros & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2014. "‘Horses for Courses’ in demand forecasting," European Journal of Operational Research, Elsevier, vol. 237(1), pages 152-163.
151. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
152. Theodorou, Evangelos & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2025. "Forecast accuracy and inventory performance: Insights on their relationship from the M5 competition data," European Journal of Operational Research, Elsevier, vol. 322(2), pages 414-426.
153. de Silva, Ashton J, 2010. "Forecasting Australian Macroeconomic variables, evaluating innovations state space approaches," MPRA Paper 27411, University Library of Munich, Germany.
154. Madden, Gary & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," Telecommunications Policy, Elsevier, vol. 31(1), pages 31-44, February.
     • Madden, Gary G & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," MPRA Paper 14739, University Library of Munich, Germany.
155. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
156. Spiliotis, Evangelos & Assimakopoulos, Vassilios & Makridakis, Spyros, 2020. "Generalizing the Theta method for automatic forecasting," European Journal of Operational Research, Elsevier, vol. 284(2), pages 550-558.
157. Korbinian Dress & Stefan Lessmann & Hans-Jorg von Mettenheim, 2017. "Residual Value Forecasting Using Asymmetric Cost Functions," Papers 1707.02736, arXiv.org.
158. Kusters, Ulrich & McCullough, B.D. & Bell, Michael, 2006. "Forecasting software: Past, present and future," International Journal of Forecasting, Elsevier, vol. 22(3), pages 599-615.
159. Spiliotis, Evangelos & Kouloumos, Andreas & Assimakopoulos, Vassilios & Makridakis, Spyros, 2020. "Are forecasting competitions data representative of the reality?," International Journal of Forecasting, Elsevier, vol. 36(1), pages 37-53.
160. Makridakis, Spyros & Hogarth, Robin M. & Gaba, Anil, 2009. "Forecasting and uncertainty in the economic and business world," International Journal of Forecasting, Elsevier, vol. 25(4), pages 794-812, October.
161. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
162. I Horowitz, 2003. "Preference-neutral attribute weights in the journal-ranking problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(5), pages 452-457, May.
163. Theocharis, Zoe & Harvey, Nigel, 2019. "When does more mean worse? Accuracy of judgmental forecasting is nonlinearly related to length of data series," Omega, Elsevier, vol. 87(C), pages 10-19.
164. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
165. Souhaib Ben Taieb & Rob J Hyndman, 2012. "Recursive and direct multi-step forecasting: the best of both worlds," Monash Econometrics and Business Statistics Working Papers 19/12, Monash University, Department of Econometrics and Business Statistics.
166. David Orrell, 2017. "A Quantum Theory of Money and Value, Part 2: The Uncertainty Principle," Economic Thought, World Economics Association, vol. 6(2), pages 14-26, September.
167. Miller, Don M. & Williams, Dan, 2003. "Shrinkage estimators of time series seasonal factors and their effect on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 19(4), pages 669-684.
168. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2022. "Accuracy indicators for evaluating retrospective performance of energy system models," Applied Energy, Elsevier, vol. 325(C).
169. Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017. "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, vol. 33(2), pages 345-358.
     • Yanfei Kang & Rob J. Hyndman & Kate Smith-Miles, 2016. "Visualising forecasting Algorithm Performance using Time Series Instance Spaces," Monash Econometrics and Business Statistics Working Papers 10/16, Monash University, Department of Econometrics and Business Statistics.
170. Godahewa, Rakshitha & Bergmeir, Christoph & Erkin Baz, Zeynep & Zhu, Chengjun & Song, Zhangdi & García, Salvador & Benavides, Dario, 2025. "On forecast stability," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1539-1558.
171. K. Maris & K. Nikolopoulos & K. Giannelos & V. Assimakopoulos, 2007. "Options trading driven by volatility directional accuracy," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 253-260.
172. Dantas, Tiago Mendes & Cyrino Oliveira, Fernando Luiz, 2018. "Improving time series forecasting: An approach combining bootstrap aggregation, clusters and exponential smoothing," International Journal of Forecasting, Elsevier, vol. 34(4), pages 748-761.
173. Buda Baji'c & Sr{dj}an Mili'cevi'c & Aleksandar Anti'c & Slobodan Markovi'c & Nemanja Tomi'c, 2024. "Neural Network Modeling for Forecasting Tourism Demand in Stopi\'{c}a Cave: A Serbian Cave Tourism Study," Papers 2404.04974, arXiv.org.
174. Mahsa Ashouri & Kate Cai & Furen Lin & Galit Shmueli, 2018. "Assessing the Value of an Information System for Developing Predictive Analytics: The Case of Forecasting School-Level Demand in Taiwan," Service Science, INFORMS, vol. 10(1), pages 58-75, March.
175. Negi, Gaurav Singh & Mohan, Harshit & Gupta, Mukul K. & Singh, Rajesh & Gehlot, Anita & Thakur, Amit Kumar & Dogra, Sudhanshu & Gupta, Lovi Raj, 2026. "Leveraging machine learning for optimized microgrid management: Advances, applications, challenges, and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PC).
176. Adham Alsharkawi & Emran Al-Sherqawi & Kamal Khandakji & Musa Al-Yaman, 2025. "Advanced Global CO 2 Emissions Forecasting: Enhancing Accuracy and Stability Across Diverse Regions," Sustainability, MDPI, vol. 17(15), pages 1-19, July.
177. Semenoglou, Artemios-Anargyros & Spiliotis, Evangelos & Makridakis, Spyros & Assimakopoulos, Vassilios, 2021. "Investigating the accuracy of cross-learning time series forecasting methods," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1072-1084.
178. Sofia-ira KTENA & Fotios PETROPOULOS & Polychronis KOUTSOLIAKOS & Dimitrios MICHOS & Vassilios ASSIMAKOPOULOS, 2011. "Forecasting Sales in a Sugar Factory," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 1(7), pages 1-12, December.
179. Davis, Lauren B. & Jiang, Steven X. & Morgan, Shona D. & Nuamah, Isaac A. & Terry, Jessica R., 2016. "Analysis and prediction of food donation behavior for a domestic hunger relief organization," International Journal of Production Economics, Elsevier, vol. 182(C), pages 26-37.
180. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, December.
181. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, January.
     • Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, November.
182. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
183. Jennifer L. Castle & Michael P. Clements & David F. Hendry, 2016. "An Overview of Forecasting Facing Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 3-23, September.
     • Jennifer Castle & David Hendry & Michael P. Clements, 2016. "An Overview of Forecasting Facing Breaks," Economics Series Working Papers 779, University of Oxford, Department of Economics.
184. Hyndman, Rob J. & Billah, Baki, 2003. "Unmasking the Theta method," International Journal of Forecasting, Elsevier, vol. 19(2), pages 287-290.
     • Hyndman, R.J. & Billah, B., 2001. "Unmasking the Theta Method," Monash Econometrics and Business Statistics Working Papers 5/01, Monash University, Department of Econometrics and Business Statistics.
185. Li, Qinyun & Disney, Stephen M. & Gaalman, Gerard, 2014. "Avoiding the bullwhip effect using Damped Trend forecasting and the Order-Up-To replenishment policy," International Journal of Production Economics, Elsevier, vol. 149(C), pages 3-16.
186. Warren Liao, T. & Chang, P.C., 2010. "Impacts of forecast, inventory policy, and lead time on supply chain inventory--A numerical study," International Journal of Production Economics, Elsevier, vol. 128(2), pages 527-537, December.
187. Luis A. Gil-Alana & Juncal Cunado & Fernando Perez de Gracia, 2008. "Tourism in the Canary Islands: forecasting using several seasonal time series models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 621-636.
     • Juncal Cuñado & Luis A. Gil-Alaña, 2007. "Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models," Faculty Working Papers 02/07, School of Economics and Business Administration, University of Navarra.
188. Jennifer L. Castle & David F. Hendry, 2010. "Nowcasting from disaggregates in the face of location shifts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 200-214.
189. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
     • Nikolay Robinzonov & Klaus Wohlrabe, 2008. "Freedom of Choice in Macroeconomic Forecasting: An Illustration with German Industrial Production and Linear Models," ifo Working Paper Series 57, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
190. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).
191. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
192. 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.
193. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
194. Wong, W.K. & Guo, Z.X., 2010. "A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm," International Journal of Production Economics, Elsevier, vol. 128(2), pages 614-624, December.
195. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
     • Nikolaos Kourentzes & George Athanasopoulos, 2019. "Elucidate Structure in Intermittent Demand Series," Monash Econometrics and Business Statistics Working Papers 27/19, Monash University, Department of Econometrics and Business Statistics.
196. Ferbar Tratar, Liljana & Mojškerc, Blaž & Toman, Aleš, 2016. "Demand forecasting with four-parameter exponential smoothing," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 162-173.
197. Mauro Bernardi & Lea Petrella, 2015. "Multiple seasonal cycles forecasting model: the Italian electricity demand," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 671-695, November.
198. Makridakis, Spyros & Taleb, Nassim, 2009. "Living in a world of low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 840-844, October.
199. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
     • Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques," CREATES Research Papers 2011-27, Department of Economics and Business Economics, Aarhus University.
200. Dress, Korbinian & Lessmann, Stefan & von Mettenheim, Hans-Jörg, 2018. "Residual value forecasting using asymmetric cost functions," International Journal of Forecasting, Elsevier, vol. 34(4), pages 551-565.
201. Lingbing Feng & Yanlin Shi, 2018. "Forecasting mortality rates: multivariate or univariate models?," Journal of Population Research, Springer, vol. 35(3), pages 289-318, September.
202. Andrea Kolková & Aleksandr Kljuènikov, 2021. "Demand forecasting: an alternative approach based on technical indicator Pbands," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 1063-1094, December.
203. Francesco Dainelli & Alessio Mengoni, 2025. "Review of Prospective Financial Statements: Stationary vs. Forward-Looking Assessments," JRFM, MDPI, vol. 18(6), pages 1-20, May.
204. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
205. Green, Kesten C. & Armstrong, J. Scott, 2015. "Simple versus complex forecasting: The evidence," Journal of Business Research, Elsevier, vol. 68(8), pages 1678-1685.
206. Armstrong, J. Scott, 2006. "Findings from evidence-based forecasting: Methods for reducing forecast error," International Journal of Forecasting, Elsevier, vol. 22(3), pages 583-598.
207. J. D. Bermudez & J. V. Segura & E. Vercher, 2007. "Holt-Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1075-1090.
208. Fiorucci, Jose Augusto & Louzada, Francisco, 2020. "GROEC: Combination method via Generalized Rolling Origin Evaluation," International Journal of Forecasting, Elsevier, vol. 36(1), pages 105-109.
209. George Athanasopoulos & Nikolaos Kourentzes, 2020. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 2/20, Monash University, Department of Econometrics and Business Statistics.
210. Godahewa, Rakshitha & Bergmeir, Christoph & Webb, Geoffrey I. & Montero-Manso, Pablo, 2023. "An accurate and fully-automated ensemble model for weekly time series forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 641-658.
211. Hilde C. Bjørnland & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud & Christie Smith, 2010. "Does forecast combination improve Norges Bank inflation forecasts?," Working Papers No 2/2010, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
212. Mirko Kremer & Brent Moritz & Enno Siemsen, 2011. "Demand Forecasting Behavior: System Neglect and Change Detection," Management Science, INFORMS, vol. 57(10), pages 1827-1843, October.
213. Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011. "Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660.
     • Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011. "Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660, July.
214. Jane M. Binner & Logan J. Kelly & Jonathan A. Tepper, 2025. "Professional Forecasters vs. Shallow Neural Network Ensembles: Assessing Inflation Prediction Accuracy," JRFM, MDPI, vol. 18(4), pages 1-16, March.
215. Athanasopoulos, George & Kourentzes, Nikolaos, 2023. "On the evaluation of hierarchical forecasts," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1502-1511.
216. Taylor, James W., 2004. "Volatility forecasting with smooth transition exponential smoothing," International Journal of Forecasting, Elsevier, vol. 20(2), pages 273-286.
217. Hendry, David F. & Mizon, Grayham E., 2014. "Unpredictability in economic analysis, econometric modeling and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 186-195.
     • Nolte, Stephan & Grethe, Harald, 2008. "Der Markt für Zucker," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 57(1).
     • Nolte, Stephan & Grethe, Harald, 2009. "Der Markt für Zucker," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 58(1).
     • Nolte, Stephan & Grethe, Harald, 2010. "Der Markt für Zucker," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 60.
     • Nolte, Stephan & Grethe, Harald, 2009. "Der Markt für Zucker," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 58(1).
     • Nolte, Stephan & Grethe, Harald, 2008. "Der Markt für Zucker," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 57(1).
     • Nolte, Stephan & Grethe, Harald, 2009. "Der Markt für Zucker," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 59.
     • Nolte, Stephan & Grethe, Harald, 2008. "Der Markt für Zucker," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 57(1).
     • Nolte, Stephan & Grethe, Harald, 2009. "Der Markt für Zucker," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 58(1).
     • Nolte, Stephan & Grethe, Harald, 2009. "Der Markt für Zucker," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 59.
     • Ruttan, Vernon W., 1977. "Induced innovation and agricultural development," Food Policy, Elsevier, vol. 2(3), pages 196-216, August.
     • Senauer, Benjamin, 1989. "Major Consumer Trends Affecting the U.S. Food System," Choices, Agricultural and Applied Economics Association, vol. 4(4).
     • Clement A. Tisdell, 2007. "Sustainable Agriculture," Chapters, in: Handbook of Sustainable Development, chapter 22 Edward Elgar Publishing.
     • Thomas Grebel & Andreas Pyka & Horst Hanusch, 2003. "An Evolutionary Approach to the Theory of Entrepreneurship," Industry and Innovation, Taylor & Francis Journals, vol. 10(4), pages 493-514.
     • Friebel, Guido & Schnedler, Wendelin, 2011. "Team governance: Empowerment or hierarchical control," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 1-13, April.
     • Llavador, Humberto & Solano-García, Angel, 2011. "Immigration policy with partisan parties," Journal of Public Economics, Elsevier, vol. 95(1), pages 134-142.
     • Brañas-Garza, Pablo & Espinosa, María Paz & Rey-Biel, Pedro, 2011. "Travelers’ types," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1), pages 25-36.
     • J. Galí & D. López-Salido & J. Vallés, 2003. "Understanding the effects of government spending on consumption," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
     • Jordi Galí & Luca Gambetti, 2013. "The Effects of Monetary Policy on Stock Market Bubbles: Some Evidence," NBER Chapters, in: Lessons from the Financial Crisis for Monetary Policy National Bureau of Economic Research, Inc.
     • Alison Booth & Melvyn Coles, 2010. "Education, Matching, and the Allocative Value of Romance," Journal of the European Economic Association, MIT Press, vol. 8(4), pages 744-775, 06.
     • Olivier Jean Blanchard & Jordi Galí, 2005. "Real wage rigidities and the New Keynesian model," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
     • Jordi Galí & Frank Smets & Rafael Wouters, 2011. "Unemployment in an Estimated New Keynesian Model," NBER Chapters, in: NBER Macroeconomics Annual 2011, Volume 26, pages 329-360 National Bureau of Economic Research, Inc.
     • Broner, Fernando & Gelos, Gaston & Reinhart, Carmen, 2004. "When in peril, retrench: testing the portfolio channel of contagion," Proceedings, Federal Reserve Bank of San Francisco, issue Jun, pages 1-34.
     • Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November.
     • Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-76, August.
     • Edgerton, David & Wells, Curt, 1994. "Critical Values for the Cusumsq Statistic in Medium and Large Sized Samples," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 56(3), pages 355-65, August.
     • Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November.
     • Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-76, August.
     • Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July.
     • Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July.
     • Gregory, Allan W. & Hansen, Bruce E., 1996. "Residual-based tests for cointegration in models with regime shifts," Journal of Econometrics, Elsevier, vol. 70(1), pages 99-126, January.
     • Peter Pedroni, 2000. "Fully Modified OLS for Heterogeneous Cointegrated Panels," Department of Economics Working Papers 2000-03, Department of Economics, Williams College.
     • Peter C.B. Phillips & Pierre Perron, 1986. "Testing for a Unit Root in Time Series Regression," Cowles Foundation Discussion Papers 795R, Cowles Foundation for Research in Economics, Yale University, revised Sep 1987.
     • Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
     • Phillips, Peter C B & Ouliaris, S, 1990. "Asymptotic Properties of Residual Based Tests for Cointegration," Econometrica, Econometric Society, vol. 58(1), pages 165-93, January.
     • Phillips, Peter C B & Ouliaris, S, 1990. "Asymptotic Properties of Residual Based Tests for Cointegration," Econometrica, Econometric Society, vol. 58(1), pages 165-93, January.
     • Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
     • Kenji Nishizaki & Toshitaka Sekine & Yuichi Ueno & Yuko Kawai, 2013. "Chronic deflation in Japan," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 9-19 Bank for International Settlements.
     • Klaus Wohlrabe, 2012. "ifo Konjunkturtest Juli 2012 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(15), pages 67-69, 08.
     • Klaus Wohlrabe, 2012. "ifo Konjunkturtest Juni 2012 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(12), pages 55-57, 06.
     • Klaus Wohlrabe, 2012. "ifo Konjunkturtest Juli 2012 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(15), pages 67-69, 08.
     • Klaus Wohlrabe, 2012. "ifo Konjunkturtest Juni 2012 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 65(12), pages 55-57, 06.
     • Klaus Abberger, 2010. "ifo Konjunkturtest Juli 2010 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(14), pages 44-46, 07.
     • Klaus Abberger, 2010. "ifo Konjunkturtest Juni 2010 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(12), pages 69-71, 06.
     • Klaus Abberger, 2010. "ifo Konjunkturtest Juli 2010 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(14), pages 44-46, 07.
     • Klaus Abberger, 2010. "ifo Konjunkturtest Juni 2010 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 63(12), pages 69-71, 06.
     • Klaus Abberger, 2008. "ifo Konjunkturtest Juli 2008 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(14), pages 46-48, 07.
     • Klaus Abberger, 2008. "ifo Konjunkturtest Juni 2008 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(12), pages 61-63, 06.
     • Gernot Nerb & Anna Stangl, 2008. "ifo Indikator für das Weltwirtschaftsklima weiter gesunken," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(23), pages 53-61, December.
     • Klaus Abberger, 2008. "ifo Konjunkturtest Juli 2008 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(14), pages 46-48, 07.
     • Klaus Abberger, 2008. "ifo Konjunkturtest Juni 2008 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(12), pages 61-63, 06.
     • Gernot Nerb & Anna Stangl, 2008. "ifo Indikator für das Weltwirtschaftsklima weiter gesunken," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(10), pages 44-53, 05.
     • Gernot Nerb & Anna Stangl, 2008. "ifo Indikator für das Weltwirtschaftsklima weiter gesunken," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(16), pages 35-42, 08.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juli 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(14), pages 28-29, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juli 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(15), pages 41-42, 08.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juli 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(15), pages 52-53, 08.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juli 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(15), pages 40-41, 08.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juni 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(12), pages 42-43, 06.
     • Hans G. Russ, 2002. "ifo Konjunkturtest Juni 2002 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 55(13), pages 44-45, 07.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juni 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(12), pages 55-56, 06.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juni 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(13), pages 49-50, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juni 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(12), pages 55-56, 06.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juli 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(14), pages 28-29, 07.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juli 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(15), pages 40-41, 08.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juli 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(15), pages 52-53, 08.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juli 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(15), pages 41-42, 08.
     • Hans G. Russ, 2002. "ifo Konjunkturtest Juni 2002 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 55(13), pages 44-45, 07.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juni 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(12), pages 42-43, 06.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juni 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(13), pages 49-50, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juni 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(12), pages 55-56, 06.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juni 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(12), pages 55-56, 06.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juli 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(15), pages 40-41, 08.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juli 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(15), pages 52-53, 08.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juli 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(14), pages 28-29, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juli 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(15), pages 41-42, 08.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juni 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(12), pages 55-56, 06.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juni 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(12), pages 55-56, 06.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juni 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(13), pages 49-50, 07.
     • Hans G. Russ, 2002. "ifo Konjunkturtest Juni 2002 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 55(13), pages 44-45, 07.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juni 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(12), pages 42-43, 06.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juli 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(15), pages 40-41, 08.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juli 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(15), pages 52-53, 08.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juli 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(14), pages 28-29, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juli 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(15), pages 41-42, 08.
     • Hans G. Russ, 2002. "ifo Konjunkturtest Juni 2002 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 55(13), pages 44-45, 07.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juni 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(12), pages 42-43, 06.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juni 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(13), pages 49-50, 07.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juni 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(12), pages 55-56, 06.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juni 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(12), pages 55-56, 06.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juli 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(15), pages 40-41, 08.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juli 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(15), pages 52-53, 08.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juli 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(14), pages 28-29, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juli 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(15), pages 41-42, 08.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juni 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(12), pages 55-56, 06.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juni 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(12), pages 55-56, 06.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juni 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(13), pages 49-50, 07.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juni 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(12), pages 42-43, 06.
     • Hans G. Russ, 2002. "ifo Konjunkturtest Juni 2002 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 55(13), pages 44-45, 07.
     • Hans G. Russ, 2004. "ifo Konjunkturtest Juli 2004 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 57(14), pages 28-29, 07.
     • Hans G. Russ, 2006. "ifo Konjunkturtest Juli 2006 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(15), pages 41-42, 08.
     • Hans G. Russ, 2003. "ifo Konjunkturtest Juli 2003 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 56(15), pages 40-41, 08.
     • Hans G. Russ, 2005. "ifo Konjunkturtest Juli 2005 in Kürze," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 58(15), pages 52-53, 08.
     • Owens, Trudy & Hoddinott, John & Kinsey, Bill, 2003. "The Impact of Agricultural Extension on Farm Production in Resettlement Areas of Zimbabwe," Economic Development and Cultural Change, University of Chicago Press, vol. 51(2), pages 337-57, January.
     • Facchini, Giovanni & Steinhardt, Max Friedrich, 2011. "What drives U.S. immigration policy? Evidence from congressional roll call votes," Journal of Public Economics, Elsevier, vol. 95(7), pages 734-743.
     • Davide Castellani & Giorgia Giovannetti, 2010. "Productivity and the international firm: dissecting heterogeneity," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 13(1), pages 25-42.
     • Artjoms Ivlevs & Jaime De Melo, 2010. "FDI, the Brain Drain and Trade: Channels and Evidence," Annals of Economics and Statistics, GENES, issue 97-98, pages 103-121.
     • Julien Gourdon & Nicolas Maystre & Jaime de Melo, 2008. "Openness, inequality and poverty: Endowments matter," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 17(3), pages 343-378.
     • Robert N. McCauley, 2012. "Risk-on/risk-off, capital flows, leverage and safe assets," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 8(3), pages 281-298, August.
     • Robert N. McCauley, 2012. "Risk-on/risk-off, capital flows, leverage and safe assets," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 8(3), pages 281-298, August.
     • Lars E. O. Svensson & Michael Woodford, 2000. "Indicator variables for optimal policy," Proceedings, Federal Reserve Bank of San Francisco.
     • Miklós Koren & Silvana Tenreyro, 2007. "Technological diversification," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
     • Keith Kuester & Volker Wieland, 2010. "Insurance Policies for Monetary Policy in the Euro Area," Journal of the European Economic Association, European Economic Association, vol. 8(4), pages 872-912, 06.
     • Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages C25-C44, February.
     • Domenico Giannone & Michele Lenza, 2010. "The Feldstein-Horioka Fact," NBER Chapters, in: NBER International Seminar on Macroeconomics 2009, pages 103-117 National Bureau of Economic Research, Inc.
     • Christian Dreger & Hans-Eggert Reimers & Barbara Roffia, 2007. "Long-Run Money Demand in the New EU Member States with Exchange Rate Effects," Eastern European Economics, Taylor & Francis Journals, vol. 45(2), pages 75-94, April.
     • Christian Daude & Marcel Fratzscher, 2007. "The pecking order of cross-border investment," CGFS Papers chapters, in: Bank for International Settlements (ed.), Research on global financial stability: the use of BIS international financial statistics, volume 29, pages 53-89 Bank for International Settlements.
     • Reint Gropp & Jukka M. Vesala & Giuseppe Vulpes, 2002. "Equity and bond market signals as leading indicators of bank fragility," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
     • Kalin Nikolov, 2012. "Bubbles, banks and financial stability," Research Bulletin, European Central Bank, vol. 15, pages 2-6.
     • Forbes, Kristin J. & Fratzscher, Marcel & Kostka, Thomas & Straub, Roland, 2012. "Bubble thy neighbor: portfolio effects and externalities from capital controls," Proceedings, Federal Reserve Bank of San Francisco, issue Nov, pages 1-48.
     • Marcel Fratzscher, 2012. "Capital Controls and Foreign Exchange Policy," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(2), pages 66-98, August.
     • Geert Bekaert & Marie Hoerova, 2010. "Risk, uncertainty and monetary policy," Research Bulletin, European Central Bank, vol. 10, pages 11-13.
     • António Afonso & João Tovar Jalles, 2013. "Fiscal Composition and Long-term Growth," Chapters in SUERF Studies, SUERF - The European Money and Finance Forum.
     • Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14, pages C45-C90, 02.
     • Marcel Fratzscher, 2011. "Capital Flows, Push versus Pull Factors and the Global Financial Crisis," NBER Chapters, in: Global Financial Crisis National Bureau of Economic Research, Inc.
     • Hendry, David F. & Hubrich, Kirstin, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(2), pages 216-227.
     • Elena Bobeica & Paulo Esteves & António Rua & Karsten Staehr, 2016. "Exports and domestic demand pressure: a dynamic panel data model for the euro area countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 152(1), pages 107-125, February.
     • Peter Hördahl & David Vestin, 2005. "Interpreting Implied Risk-Neutral Densities: The Role of Risk Premia," Review of Finance, European Finance Association, vol. 9(1), pages 97-137.
     • Charles Engel & Kenneth D. West, 2003. "Exchange rates and fundamentals," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
     • Pierpaolo Benigno & Michael Woodford, 2003. "Optimal monetary and fiscal policy: a linear-quadratic approach," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
     • J. Galí & D. López-Salido & J. Vallés, 2003. "Understanding the effects of government spending on consumption," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
     • Athanasios Orphanides & John C. Williams, 2003. "The decline of activist stabilization policy: natural rate misperceptions, learning, and expectations," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
     • Fabrice Collard & Harris Dellas, 2003. "The great inflation of the 1970s," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
     • Banbura, Marta & Rünstler, Gerhard, 2011. "A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP," International Journal of Forecasting, Elsevier, vol. 27(2), pages 333-346, April.
     • Stephen Bond & Dietmar Harhoff & John Van Reenen, 2005. "Investment, R&D and Financial Constraints in Britain and Germany," Annals of Economics and Statistics, GENES, issue 79-80, pages 433-460.
     • Nick Bloom & Mark Schankerman & John Van Reenen, 2005. "Identifying technology spillovers and product market rivalry," Proceedings, Federal Reserve Bank of San Francisco.
     • Francesco Caselli & Silvana Tenreyro, 2004. "Is Poland the next Spain?," Communities and Banking, Federal Reserve Bank of Boston.
     • Saul Lach & Mark Schankerman, 2003. "Incentives and invention in universities," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
     • Nick Bloom & Mark Schankerman & John Van Reenen, 2005. "Identifying technology spillovers and product market rivalry," Proceedings, Federal Reserve Bank of San Francisco.
     • Miklós Koren & Silvana Tenreyro, 2007. "Technological diversification," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
     • Christopher A. Pissarides, 2009. "The Unemployment Volatility Puzzle: Is Wage Stickiness the Answer?," Econometrica, Econometric Society, vol. 77(5), pages 1339-1369, 09.
     • Saul Lach & Mark Schankerman, 2003. "Incentives and invention in universities," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
     • Nick Bloom & Mark Schankerman & John Van Reenen, 2005. "Identifying technology spillovers and product market rivalry," Proceedings, Federal Reserve Bank of San Francisco.
     • Nick Bloom & Mark Schankerman & John Van Reenen, 2005. "Identifying technology spillovers and product market rivalry," Proceedings, Federal Reserve Bank of San Francisco.
     • Jo Blanden & Stephen Machin, 2004. "Educational Inequality and the Expansion of UK Higher Education," Scottish Journal of Political Economy, Scottish Economic Society, vol. 51(2), pages 230-249, 05.
     • Anthony J. Venables, 2006. "Shifts in economic geography and their causes," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 15-39.
     • Eva Catarineu-Rabell & Patricia Jackson & Dimitrios P. Tsomocos, 2002. "Procyclicality and the New Basel Accord: banks' choice of loan rating system," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
     • Jean-Charles Rochet & Jean Tirole, 2003. "Platform Competition in Two-Sided Markets," Journal of the European Economic Association, MIT Press, vol. 1(4), pages 990-1029, 06.
     • Larcinese, Valentino & Puglisi, Riccardo & Snyder, James M., 2011. "Partisan bias in economic news: Evidence on the agenda-setting behavior of U.S. newspapers," Journal of Public Economics, Elsevier, vol. 95(9), pages 1178-1189.
     • Saul Lach & Mark Schankerman, 2003. "Incentives and invention in universities," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
     • Richard Freeman & John Van Reenen, 2009. "What if Congress Doubled R&D Spending on the Physical Sciences?," NBER Chapters, in: Innovation Policy and the Economy, Volume 9, pages 1-38 National Bureau of Economic Research, Inc.
     • Richard Perkins & Eric Neumayer, 2010. "Geographic variations in the early diffusion of corporate voluntary standards: comparing ISO 14001 and the Global Compact," Environment and Planning A, Pion Ltd, London, vol. 42(2), pages 347-365, February.
     • Richard B. Freeman, 2007. "When Workers Share in Profits: Effort and Responses to Shirking," Rivista di Politica Economica, SIPI Spa, vol. 97(6), pages 9-36, November-.
     • Robert C. Allen & Jean‐Pascal Bassino & Debin Ma & Christine Moll‐Murata & Jan Luiten Van Zanden, 2011. "Wages, prices, and living standards in China, 1738–1925: in comparison with Europe, Japan, and India," Economic History Review, Economic History Society, vol. 64(s1), pages 8-38, February.
     • Nick Bloom & Mark Schankerman & John Van Reenen, 2005. "Identifying technology spillovers and product market rivalry," Proceedings, Federal Reserve Bank of San Francisco.
     • Miklós Koren & Silvana Tenreyro, 2007. "Technological diversification," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
     • Nancy Holman & Gabriel M Ahlfeldt, 2015. "No escape? The coordination problem in heritage preservation," Environment and Planning A, Pion Ltd, London, vol. 47(1), pages 172-187, January.
     • Paul Beaudry & David A. Green & Benjamin M. Sand, 2013. "The Great Reversal in the Demand for Skill and Cognitive Tasks," NBER Chapters, in: Labor Markets in the Aftermath of the Great Recession, pages 199-247 National Bureau of Economic Research, Inc.
     • Giuseppe Moscarini & Fabien Postel-Vinay, 2013. "Did the Job Ladder Fail after the Great Recession?," NBER Chapters, in: Labor Markets in the Aftermath of the Great Recession, pages 55-93 National Bureau of Economic Research, Inc.
     • Nuno Ferreira da Cruz & Pedro Simões & Rui Cunha Marques, 2013. "The hurdles of local governments with PPP contracts in the waste sector," Environment and Planning C: Government and Policy, Pion Ltd, London, vol. 31(2), pages 292-307, April.
     • Eric Neumayer & Peter Nunnenkamp & Martin Roy, 2016. "Are stricter investment rules contagious? Host country competition for foreign direct investment through international agreements," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 152(1), pages 177-213, February.
     • Joseph Seidel & Yang Xu, 2016. "MHTEXP: Stata module to perform multiple hypothesis testing correction procedure," Statistical Software Components S458153, Boston College Department of Economics.
     • Heike Hennig-Schmidt & Bettina Rockenbach & Abdolkarim Sadrieh, 2010. "In Search Of Workers' Real Effort Reciprocity-A Field and a Laboratory Experiment," Journal of the European Economic Association, MIT Press, vol. 8(4), pages 817-837, 06.
     • Karlan, Dean & List, John A. & Shafir, Eldar, 2011. "Small matches and charitable giving: Evidence from a natural field experiment," Journal of Public Economics, Elsevier, vol. 95(5), pages 344-350.
     • Matthew T. Cole & Amélie Guillin, 2015. "The determinants of trade agreements in services vs. goods," International Economics, CEPII research center, issue 144, pages 66-82.
     • Yilmazkuday, Hakan, 2016. "Forecasting the Great Trade Collapse," International Economics, Elsevier, vol. 147(C), pages 145-154.
     • Georgy Idrisov & Yuri Bobylev & Arseny Mamedov & Olga Morgunova & Mikhail Khromov & Sergey Tsukhlo & Olesia Rasenko, 2015. "Online Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 15, pages 1-26, November.
     • Georgy Idrisov & Mikhail Khromov & Evgeny Goryunov & Alexander Knobel & Yuri Ponomarev & Alexander Deryugin & Julia Florinskaya & Nikita Mkrtchan, 2015. "Online Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 16, pages 1-26, November.
     • Alexander Knobel & Yuri Bobylev & Alexandra Bozhechkova & Pavel Trunin & Mikhail Khromov & Natalia Shagaida & Vasily Uzun & Elena Avraamova & D. Loginov, 2015. "Online Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-economic Development," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 14, pages 1-26, October.
     • Firanchuk Alexander & Shagaida Natalia & Mamedov Arseny & Fomina Elena & Zubarevich Natalia, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 26, pages 1-27, May.
     • Drobyshevsky Sergey & Turuntseva Marina & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Averkiev Vladimir & Shishkina Ekaterina & Florinskaya Yulia & Mkrtchian N. & S, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 24, pages 1-27, April.
     • Sergey Drobyshevsky & Marina Turuntseva & Michael Khromov & Yuri Bobylev & Arseny Mamedov & Evgenia Fomina & Viktoria Petrenko & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 19, pages 1-26, January.
     • Arseny Mamedov & Evgenia Fomina & Alexandra Bozhechkova & Sergey Tsukhlo & Pavel Trunin & Victor Lyashok, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 20, pages 1-26, February.
     • Sergey Drobyshevsky & Marina Turuntseva & Michael Khromov & Yuri Bobylev & Arseny Mamedov & Evgenia Fomina & Viktoria Petrenko & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 19, pages 1-26, January.
     • Arseny Mamedov & Evgenia Fomina & Alexandra Bozhechkova & Sergey Tsukhlo & Pavel Trunin & Victor Lyashok, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 20, pages 1-22, February.
     • Sergey Drobyshevsky & Mikhail Khromov & Maria Kazakova & Sergey Tsukhlo & Natalia Shagaida & Natalia Zubarevich, 2015. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 17, pages 1-26, December.
     • Mikhail Khromov & Sergey Drobyshevsky & Maria Kazakova & Sergey Tsukhlo & Natalia Shagaida & Natalia Zubarevich, 2015. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 17, pages 1-26, December.
     • Drobyshevsky Sergey & Turuntseva Marina & Bobylev Yuri & Rasenko O. & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Averkiev Vladimir & Shagaida Natalia & Kiyutsevskaya Ann, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 28, pages 1-28, June.
     • Drobyshevsky Sergey & Turuntseva Marina & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Averkiev Vladimir & Shishkina Ekaterina & Uzun Vasily & Flor, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 24, pages 1-27, April.
     • Drobyshevsky Sergey & Turuntseva Marina & Bobylev Yuri & Rasenko O. & Bozhechkova Alexandra & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Khromov Mikhail & Averkiev Vladimir & Shagaida Nat, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 28, pages 1-28, June.
     • Arseny Mamedov & Evgenia Fomina & Mikhail Khromov & Natalia Shagaida & Natalia Zubarevich & Pavel Pavlov & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 21, pages 1-30, February.
     • Sergey Drobyshevsky & Marina Turuntseva & Michael Khromov & Yuri Bobylev & Arseny Mamedov & Evgenia Fomina & Viktoria Petrenko & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 19, pages 1-26, January.
     • Idrisov Georgy & Bozhechkova Alexandra & Trunin Pavel & Khromov Mikhail & Tsukhlo Sergey & Goryunov Evgeny & Deryugin Alexander & Kaukin Andrey, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 25, pages 1-22, April.
     • Firanchuk Alexander & Shagaida Natalia & Mamedov Arseny & Fomina Elena & Zubarevich Natalia, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 26, pages 1-27, May.
     • Alexandra Bozhechkova & Alexander Knobel & Sergey Tsukhlo & Elena Grishina & Pavel Trunin & Alexander Firanchuk & Olga Berezinskaya, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 22, pages 1-27, March.
     • Sergey Drobyshevsky & Marina Turuntseva & Michael Khromov & Yuri Bobylev & Arseny Mamedov & Evgenia Fomina & Viktoria Petrenko & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 19, pages 1-26, January.
     • Idrisov Georgy & Bozhechkova Alexandra & Trunin Pavel & Khromov Mikhail & Tsukhlo Sergey & Goryunov Evgeny & Deryugin Alexander & Kaukin Andrey, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 25, pages 1-22, April.
     • Loginov D. & Trunin Pavel & Knobel Alexander & Firanchuk Alexander & Goryunov Evgeny & Kiyutsevskaya Anna & Larionova M. & Sakharov A. & Shelepov A. & Avraamova A., 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 29, pages 1-26, June.
     • Arseny Mamedov & Evgenia Fomina & Mikhail Khromov & Natalia Shagaida & Natalia Zubarevich & Pavel Pavlov & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 21, pages 1-30, February.
     • Idrisov Georgy & Loginova D. & Knobel Alexander & Firanchuk Alexander & Tsukhlo Sergey & Uzun Vasily & Kaukin Andrey & Zubarevich Natalia, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 32, pages 1-27, September.
     • Arseny Mamedov & Evgenia Fomina & Mikhail Khromov & Andrei Kaukin & Natalia Shagaida & Natalia Zubarevich & Pavel Pavlov & Vasily Uzun, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 21, pages 1-30, February.
     • Mikhail Khromov & Yuri Bobylev & Sergey Tsukhlo & E. Avraamova & D. Loginov & O. Rasenko & Ekaterina Ponomareva & Sergey Sudakov, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 23, pages 1-27, March.
     • Firanchuk Alexander & Shagaida Natalia & Mamedov Arseny & Fomina Elena & Zubarevich Natalia, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 26, pages 1-27, May.
     • Alexandra Bozhechkova & Alexander Knobel & Georgy Idrisov & Yuri Ponomarev & Sergey Tsukhlo & Pavel Trunin & Sergey Sudakov & Alexandra Burdyak & Elena Grishina, 2015. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 18, pages 1-26, December.
     • Mikhail Khromov & Sergey Drobyshevsky & Maria Kazakova & Sergey Tsukhlo & Natalia Shagaida & Natalia Zubarevich, 2015. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development (In Russian), Gaidar Institute for Economic Policy, issue 17, pages 1-26, December.
     • Bozhechkova Alexandra & Trunin Pavel & Grishina Elena & Khromov Mikhail & Tsukhlo Sergey & Deryugin Alexander & Burdyak Alexandra, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 31, pages 1-27, July.
     • Arseny Mamedov & Evgenia Fomina & Alexandra Bozhechkova & Sergey Tsukhlo & Pavel Trunin & Victor Lyashok, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Economic Outlook. Trends and Challenges of Socio-Economic Development, Gaidar Institute for Economic Policy, issue 20, pages 1-22, February.
     • Idrisov Georgy & Loginova D. & Knobel Alexander & Firanchuk Alexander & Tsukhlo Sergey & Uzun Vasily & Kaukin Andrey & Zubarevich Natalia, 2016. "Online Monitoring of Russia's Economic Outlook," Monitoring of Russia's Econom
     • Emrah Gulay & Serkan Aras, 2024. "Does a meta-combining method lead to more accurate forecasts in the decision-making process?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(3), pages 101-124.
     • repec:nbp:nbpbik:v:47:y:2016:i:6:p:365-394 is not listed on IDEAS
     • Tine Van Calster & Filip Van den Bossche & Bart Baesens & Wilfried Lemahieu, 2020. "Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective," Papers 2002.00949, arXiv.org.
     • Olivares, Kin G. & Challu, Cristian & Marcjasz, Grzegorz & Weron, Rafał & Dubrawski, Artur, 2023. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," International Journal of Forecasting, Elsevier, vol. 39(2), pages 884-900.
       • Kin G. Olivares & Cristian Challu & Grzegorz Marcjasz & Rafal Weron & Artur Dubrawski, 2021. "Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx," WORking papers in Management Science (WORMS) WORMS/21/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
     • Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
       • Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
     • Koehler, Anne B. & Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "A study of outliers in the exponential smoothing approach to forecasting," International Journal of Forecasting, Elsevier, vol. 28(2), pages 477-484.
     • J. Scott Armstrong & Ruth Pagell, 2003. "The Ombudsman: Reaping Benefits from Management Research: Lessons from the Forecasting Principles Project," Interfaces, INFORMS, vol. 33(6), pages 91-111, December.
     • Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
       • Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
     • Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
     • Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011. "Optimal combination forecasts for hierarchical time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
       • Rob J. Hyndman & Roman A. Ahmed & George Athanasopoulos, 2007. "Optimal combination forecasts for hierarchical time series," Monash Econometrics and Business Statistics Working Papers 9/07, Monash University, Department of Econometrics and Business Statistics.
     • Klinger, Sabine & Heilemann, Ullrich, 2005. "Zu wenig Wettbewerb? Zu Stand und Entwicklung der Genauigkeit makroökonomischer Prognosen," Technical Reports 2005,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
     • Pritularga, Kandrika F. & Svetunkov, Ivan & Kourentzes, Nikolaos, 2023. "Shrinkage estimator for exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1351-1365.
     • Sebastian M. Blanc & Thomas Setzer, 2020. "Bias–Variance Trade-Off and Shrinkage of Weights in Forecast Combination," Management Science, INFORMS, vol. 66(12), pages 5720-5737, December.
     • De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
     • 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.
     • Xiong, Tao & Bao, Yukun & Hu, Zhongyi, 2013. "Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices," Energy Economics, Elsevier, vol. 40(C), pages 405-415.
     • Thomson, Mary E. & Pollock, Andrew C. & Önkal, Dilek & Gönül, M. Sinan, 2019. "Combining forecasts: Performance and coherence," International Journal of Forecasting, Elsevier, vol. 35(2), pages 474-484.
     • Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
     • Kavitha Ganesan & Udhayakumar Annamalai & Nagarajan Deivanayagampillai, 2019. "An integrated new threshold FCMs Markov chain based forecasting model for analyzing the power of stock trading trend," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-19, December.
     • Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
     • Wellens, Arnoud P. & Boute, Robert N. & Udenio, Maximiliano, 2024. "Simplifying tree-based methods for retail sales forecasting with explanatory variables," European Journal of Operational Research, Elsevier, vol. 314(2), pages 523-539.
     • Feddersen, Leif & Cleophas, Catherine, 2026. "Hierarchical neural additive models for interpretable demand forecasts," International Journal of Forecasting, Elsevier, vol. 42(1), pages 216-234.
     • Fildes, Robert & Kourentzes, Nikolaos, 2011. "Validation and forecasting accuracy in models of climate change," International Journal of Forecasting, Elsevier, vol. 27(4), pages 968-995, October.
     • Hayat, Aziz & Bhatti, M. Ishaq, 2013. "Masking of volatility by seasonal adjustment methods," Economic Modelling, Elsevier, vol. 33(C), pages 676-688.
     • Fildes, Robert & Nikolopoulos, Konstantinos, 2006. "Spyros Makridakis: An interview with the International Journal of Forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 625-636.
     • Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
     • Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
     • Blanc, Sebastian M. & Setzer, Thomas, 2016. "When to choose the simple average in forecast combination," Journal of Business Research, Elsevier, vol. 69(10), pages 3951-3962.
     • Meira, Erick & Cyrino Oliveira, Fernando Luiz & Jeon, Jooyoung, 2021. "Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals," International Journal of Forecasting, Elsevier, vol. 37(2), pages 547-568.
     • Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
     • Fiorucci, Jose A. & Pellegrini, Tiago R. & Louzada, Francisco & Petropoulos, Fotios & Koehler, Anne B., 2016. "Models for optimising the theta method and their relationship to state space models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1151-1161.
     • Poloni, Federico & Sbrana, Giacomo, 2015. "A note on forecasting demand using the multivariate exponential smoothing framework," International Journal of Production Economics, Elsevier, vol. 162(C), pages 143-150.
     • Anton A. Gerunov, 2022. "Performance of 109 Machine Learning Algorithms across Five Forecasting Tasks: Employee Behavior Modeling, Online Communication, House Pricing, IT Support and Demand Planning," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 15-43.
     • Spyros Makridakis & Fotios Petropoulos & Yanfei Kang, 2023. "Large Language Models: Their Success and Impact," Forecasting, MDPI, vol. 5(3), pages 1-14, August.
     • Hill, Arthur V. & Zhang, Weiyong & Burch, Gerald F., 2015. "Forecasting the forecastability quotient for inventory management," International Journal of Forecasting, Elsevier, vol. 31(3), pages 651-663.
     • James W. Taylor, 2004. "Smooth transition exponential smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 385-404.
     • Katsikopoulos, Konstantinos V. & Şimşek, Özgür & Buckmann, Marcus & Gigerenzer, Gerd, 2022. "Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?," International Journal of Forecasting, Elsevier, vol. 38(2), pages 613-619.
     • Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 672-688, July.
     • J V Hansen & J B McDonald & R D Nelson, 2006. "Some evidence on forecasting time-series with support vector machines," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1053-1063, September.
     • Antonio Fernández-Cano & Manuel Torralbo & Mónica Vallejo, 2012. "Time series of scientific growth in Spanish doctoral theses (1848–2009)," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 15-36, April.
     • 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.
     • Vicky Bamiatzi & Konstantinos Bozos & Konstantinos Nikolopoulos, 2010. "On the predictability of firm performance via simple time-series and econometric models: evidence from UK SMEs," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 279-282, February.
     • Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
     • Ralph D. Snyder & Anne B. Koehler, 2008. "A View of Damped Trend as Incorporating a Tracking Signal into a State Space Model," Monash Econometrics and Business Statistics Working Papers 7/08, Monash University, Department of Econometrics and Business Statistics.
     • López Menéndez, Ana Jesús & Pérez Suárez, Rigoberto, 2017. "Forecasting Performance and Information Measures. Revisiting the M-Competition /Evaluación de Predicciones y Medidas de Información. Reexamen de la M-Competición," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 299-314, Mayo.
     • Alysha M De Livera, 2010. "Automatic forecasting with a modified exponential smoothing state space framework," Monash Econometrics and Business Statistics Working Papers 10/10, Monash University, Department of Econometrics and Business Statistics.
     • Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
     • Gould, Phillip G. & Koehler, Anne B. & Ord, J. Keith & Snyder, Ralph D. & Hyndman, Rob J. & Vahid-Araghi, Farshid, 2008. "Forecasting time series with multiple seasonal patterns," European Journal of Operational Research, Elsevier, vol. 191(1), pages 207-222, November.
     • Fotios Petropoulos & Spyros Makridakis, 2020. "Forecasting the novel coronavirus COVID-19," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-8, March.
     • Kück, Mirko & Freitag, Michael, 2021. "Forecasting of customer demands for production planning by local k-nearest neighbor models," International Journal of Production Economics, Elsevier, vol. 231(C).
     • Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "The M5 competition: Background, organization, and implementation," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1325-1336.
     • Barrow, Devon K. & Crone, Sven F., 2016. "A comparison of AdaBoost algorithms for time series forecast combination," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1103-1119.
     • Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.
     • Clements, Michael P., 2003. "Some possible directions for future research," International Journal of Forecasting, Elsevier, vol. 19(1), pages 1-3.
     • Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
       • Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging using Predictive Measures," Working Paper Series 191, Sveriges Riksbank (Central Bank of Sweden).
       • Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging Using Predictive Measures," CEPR Discussion Papers 5268, C.E.P.R. Discussion Papers.
     • Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
     • Litsiou, Konstantia & Polychronakis, Yiannis & Karami, Azhdar & Nikolopoulos, Konstantinos, 2022. "Relative performance of judgmental methods for forecasting the success of megaprojects," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1185-1196.
     • Adriano Koshiyama & Nick Firoozye & Philip Treleaven, 2021. "Generative adversarial networks for financial trading strategies fine-tuning and combination," Quantitative Finance, Taylor & Francis Journals, vol. 21(5), pages 797-813, May.
       • Adriano Koshiyama & Nick Firoozye & Philip Treleaven, 2019. "Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination," Papers 1901.01751, arXiv.org, revised Mar 2019.
     • José V. Segura-Heras & José D. Bermúdez & Ana Corberán-Vallet & Enriqueta Vercher, 2022. "Analysis of Weighting Strategies for Improving the Accuracy of Combined Forecasts," Mathematics, MDPI, vol. 10(5), pages 1-12, February.
     • Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
     • De Baets, Shari & Harvey, Nigel, 2020. "Using judgment to select and adjust forecasts from statistical models," European Journal of Operational Research, Elsevier, vol. 284(3), pages 882-895.
     • Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.
     • 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.
       • Timmermann, Allan, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
       • Marco Aiolfi & Carlos Capistrán & Allan Timmermann, 2010. "Forecast Combinations," CREATES Research Papers 2010-21, Department of Economics and Business Economics, Aarhus University.
       • Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
     • Kott, Alexander & Perconti, Philip, 2018. "Long-term forecasts of military technologies for a 20–30 year horizon: An empirical assessment of accuracy," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 272-279.
     • Syntetos, Aris A. & Zied Babai, M. & Gardner, Everette S., 2015. "Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping," Journal of Business Research, Elsevier, vol. 68(8), pages 1746-1752.
     • Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
       • Rob J. Hyndman & Anne B. Koehler, 2005. "Another Look at Measures of Forecast Accuracy," Monash Econometrics and Business Statistics Working Papers 13/05, Monash University, Department of Econometrics and Business Statistics.
     • Billah, Baki & King, Maxwell L. & Snyder, Ralph D. & Koehler, Anne B., 2006. "Exponential smoothing model selection for forecasting," International Journal of Forecasting, Elsevier, vol. 22(2), pages 239-247.
       • Baki Billah & Maxwell L King & Ralph D Snyder & Anne B Koehler, 2005. "Exponential Smoothing Model Selection for Forecasting," Monash Econometrics and Business Statistics Working Papers 6/05, Monash University, Department of Econometrics and Business Statistics.
     • Petropoulos, Fotios & Goodwin, Paul & Fildes, Robert, 2017. "Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge," International Journal of Forecasting, Elsevier, vol. 33(1), pages 314-324.
     • Barrow, Devon K. & Crone, Sven F., 2016. "Cross-validation aggregation for combining autoregressive neural network forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1120-1137.
     • Dalla Valle, Alessandra & Furlan, Claudia, 2014. "Diffusion of nuclear energy in some developing countries," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 143-153.
     • Nikolopoulos, Konstantinos & Buxton, Samantha & Khammash, Marwan & Stern, Philip, 2016. "Forecasting branded and generic pharmaceuticals," International Journal of Forecasting, Elsevier, vol. 32(2), pages 344-357.
     • Moor, A. & La Vecchia, D. & Ronchetti, E., 2025. "On the use of the cumulant generating function for inference on time series," Computational Statistics & Data Analysis, Elsevier, vol. 201(C).
     • Sonnleitner, Benedikt & Stapf, Jelena & Wulff, Kai, 2024. "Benchmarking short term forecasts of regional banknote lodgements and withdrawals," Discussion Papers 39/2024, Deutsche Bundesbank.
     • Tsionas, Mike G., 2021. "Bayesian forecasting with the structural damped trend model," International Journal of Production Economics, Elsevier, vol. 234(C).
     • Fildes, Robert & Petropoulos, Fotios, 2013. "An evaluation of simple forecasting model selection rules," MPRA Paper 51772, University Library of Munich, Germany.
     • Ahmed Nafidi & Ghizlane Moutabir & Ramón Gutiérrez-Sánchez, 2019. "Stochastic Brennan–Schwartz Diffusion Process: Statistical Computation and Application," Mathematics, MDPI, vol. 7(11), pages 1-16, November.
     • repec:jss:jstsof:27:i03 is not listed on IDEAS
     • Lolli, F. & Gamberini, R. & Regattieri, A. & Balugani, E. & Gatos, T. & Gucci, S., 2017. "Single-hidden layer neural networks for forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 116-128.
     • Forbes, William & Hudson, Robert & Skerratt, Len & Soufian, Mona, 2015. "Which heuristics can aid financial-decision-making?," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 199-210.
     • Sonnleitner, Benedikt & Kourentzes, Nikolaos & Ehrig, Claudia & Pflaum, Alexander, 2025. "Forecasting for optimization in road freight transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 204(C).
     • Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
     • Bergmeir, Christoph & Hyndman, Rob J. & Benítez, José M., 2016. "Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation," International Journal of Forecasting, Elsevier, vol. 32(2), pages 303-312.
       • Christoph Bergmeir & Rob J Hyndman & Jose M Benitez, 2014. "Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation," Monash Econometrics and Business Statistics Working Papers 11/14, Monash University, Department of Econometrics and Business Statistics.
     • Spyros Makridakis & Chris Fry & Fotios Petropoulos & Evangelos Spiliotis, 2022. "The Future of Forecasting Competitions: Design Attributes and Principles," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 96-113, April.
     • Ord, Keith, 2004. "Charles Holt's report on exponentially weighted moving averages: an introduction and appreciation," International Journal of Forecasting, Elsevier, vol. 20(1), pages 1-3.
     • Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
     • Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
     • Erjiang E & Ming Yu & Xin Tian & Ye Tao, 2022. "Dynamic Model Selection Based on Demand Pattern Classification in Retail Sales Forecasting," Mathematics, MDPI, vol. 10(17), pages 1-16, September.
     • Kalantari, Mahdi, 2021. "Forecasting COVID-19 pandemic using optimal singular spectrum analysis," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
     • Li, Qinyun & Gaalman, Gerard & Disney, Stephen M., 2023. "On the equivalence of the proportional and damped trend order-up-to policies: An eigenvalue analysis," International Journal of Production Economics, Elsevier, vol. 265(C).
     • Philippe St-Aubin & Bruno Agard, 2022. "Precision and Reliability of Forecasts Performance Metrics," Forecasting, MDPI, vol. 4(4), pages 1-22, October.
     • Yanlin Shi & Sixian Tang & Jackie Li, 2020. "A Two-Population Extension of the Exponential Smoothing State Space Model with a Smoothing Penalisation Scheme," Risks, MDPI, vol. 8(3), pages 1-18, June.
     • George Athanasopoulos & D. Poskitt & Farshid Vahid, 2012. "Two Canonical VARMA Forms: Scalar Component Models Vis-à-Vis the Echelon Form," Econometric Reviews, Taylor & Francis Journals, vol. 31(1), pages 60-83.
       • George Athanasopoulos & D.S. Poskitt & Farshid Vahid, 2007. "Two canonical VARMA forms: Scalar component models vis-à-vis the Echelon form," Monash Econometrics and Business Statistics Working Papers 10/07, Monash University, Department of Econometrics and Business Statistics, revised May 2009.
     • Kourentzes, Nikolaos & Petropoulos, Fotios, 2016. "Forecasting with multivariate temporal aggregation: The case of promotional modelling," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 145-153.
     • Sbrana, Giacomo & Silvestrini, Andrea, 2022. "Random coefficient state-space model: Estimation and performance in M3–M4 competitions," International Journal of Forecasting, Elsevier, vol. 38(1), pages 352-366.
     • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting"," IREA Working Papers 201701, University of Barcelona, Research Institute of Applied Economics, revised Jan 2017.
       • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
     • Lars Lien Ankile & Kjartan Krange, 2022. "Deep Learning and Linear Programming for Automated Ensemble Forecasting and Interpretation," Papers 2201.00426, arXiv.org, revised Nov 2022.
     • McKenzie, Eddie & Gardner Jr., Everette S., 2010. "Damped trend exponential smoothing: A modelling viewpoint," International Journal of Forecasting, Elsevier, vol. 26(4), pages 661-665, October.
     • R Fildes & B Kingsman, 2011. "Incorporating demand uncertainty and forecast error in supply chain planning models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 483-500, March.
     • Katsikopoulos, Konstantinos V. & Durbach, Ian N. & Stewart, Theodor J., 2018. "When should we use simple decision models? A synthesis of various research strands," Omega, Elsevier, vol. 81(C), pages 17-25.
     • Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
     • Zanoli, Raffaele & Gambelli, Danilo & Vairo, Daniela, 2012. "Scenarios of the organic food market in Europe," Food Policy, Elsevier, vol. 37(1), pages 41-57.
     • Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
     • Nikolopoulos, Konstantinos & Petropoulos, Fotios & Rodrigues, Vasco Sanchez & Pettit, Stephen & Beresford, Anthony, 2022. "A disaster response model driven by spatial–temporal forecasts," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1214-1220.
     • Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizons," Tourism Economics, , vol. 27(2), pages 273-291, March.
     • Babai, M.Z. & Ali, M.M. & Boylan, J.E. & Syntetos, A.A., 2013. "Forecasting and inventory performance in a two-stage supply chain with ARIMA(0,1,1) demand: Theory and empirical analysis," International Journal of Production Economics, Elsevier, vol. 143(2), pages 463-471.
     • Gary Madden & Joachim Tan, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," Applied Economics, Taylor & Francis Journals, vol. 40(14), pages 1775-1787.
       • Madden, Gary G & Tan, Joachim, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," MPRA Paper 13005, University Library of Munich, Germany.
     • Svetunkov, Ivan & Kourentzes, Nikolaos, 2015. "Complex Exponential Smoothing," MPRA Paper 69394, University Library of Munich, Germany.
     • David Aikman & Mirta Galesic & Gerd Gigerenzer & Sujit Kapadia & Konstantinos Katsikopoulos & Amit Kothiyal & Emma Murphy & Tobias Neumann, 2014. "Financial Stability Paper No 28: Taking uncertainty seriously - simplicity versus complexity in financial regulation," Bank of England Financial Stability Papers 28, Bank of England.
     • Xu, Yongzhuo & Kang, Bingyi, 2025. "A novel model based on graph kernel and S-R score in visibility graph for time series forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 674(C).
     • Ji Wu & Xian Cheng & Stephen Shaoyi Liao, 2020. "Tourism forecast combination using the stochastic frontier analysis technique," Tourism Economics, , vol. 26(7), pages 1086-1107, November.
     • Petropoulos, Fotios & Hyndman, Rob J. & Bergmeir, Christoph, 2018. "Exploring the sources of uncertainty: Why does bagging for time series forecasting work?," European Journal of Operational Research, Elsevier, vol. 268(2), pages 545-554.
     • Michael P. Clements & David F. Hendry, 2005. "Guest Editors’ Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
     • Adam Elbourne & Henk Kranendonk & Rob Luginbuhl & Bert Smid & Martin Vromans, 2008. "Evaluating CPB's published GDP growth forecasts; a comparison with individual and pooled VAR based forecasts," CPB Document 172, CPB Netherlands Bureau for Economic Policy Analysis.
     • Ma, Shaohui & Fildes, Robert, 2020. "Forecasting third-party mobile payments with implications for customer flow prediction," International Journal of Forecasting, Elsevier, vol. 36(3), pages 739-760.
     • Smyl, Slawek & Bergmeir, Christoph & Dokumentov, Alexander & Long, Xueying & Wibowo, Erwin & Schmidt, Daniel, 2025. "Local and global trend Bayesian exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 41(1), pages 111-127.
     • Philip Hans Franses, 2020. "IMA(1,1) as a new benchmark for forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 27(17), pages 1419-1423, October.
       • Franses, Ph.H.B.F., 2019. "IMA(1,1) as a new benchmark for forecast evaluation," Econometric Institute Research Papers EI2019-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
     • Davide De Gaetano, 2017. "Forecasting With Garch Models Under Structural Breaks: An Approach Based On Combinations Across Estimation Windows," Departmental Working Papers of Economics - University 'Roma Tre' 0219, Department of Economics - University Roma Tre.
     • Gerald Forkuor & Ozias K L Hounkpatin & Gerhard Welp & Michael Thiel, 2017. "High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-21, January.
     • Madden, Gary G & Coble-Neal, Grant, 2005. "Forecasting international bandwidth capability," MPRA Paper 10822, University Library of Munich, Germany.
     • Karsten R. Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Evaluating ensemble density combination - forecasting GDP and inflation," Working Paper 2009/19, Norges Bank.
     • Joanna Bruzda, 2016. "Quantile forecasting in operational planning and inventory management – an initial empirical verification," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 5-20.
     • Kourentzes, Nikolaos & Saayman, Andrea & Jean-Pierre, Philippe & Provenzano, Davide & Sahli, Mondher & Seetaram, Neelu & Volo, Serena, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team," Annals of Tourism Research, Elsevier, vol. 88(C).
       • Nikolaos Kourentzes & Andrea Saayman & Philippe Jean-Pierre & Davide Provenzano & Mondher Sahli & Neelu Seetaram & Serena Volo, 2021. "Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team," Post-Print hal-03286786, HAL.
     • Gardner Jr., Everette S. & Diaz-Saiz, Joaquin, 2008. "Exponential smoothing in the telecommunications data," International Journal of Forecasting, Elsevier, vol. 24(1), pages 170-174.
     • Athanasopoulos, George & Vahid, Farshid, 2008. "VARMA versus VAR for Macroeconomic Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 237-252, April.
       • George Athanasopoulos & Farshid Vahid, 2006. "VARMA versus VAR for Macroeconomic Forecasting," Monash Econometrics and Business Statistics Working Papers 4/06, Monash University, Department of Econometrics and Business Statistics.
     • Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
     • Hibon, Michele & Evgeniou, Theodoros, 2005. "To combine or not to combine: selecting among forecasts and their combinations," International Journal of Forecasting, Elsevier, vol. 21(1), pages 15-24.
     • Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
     • Miroslav Navratil & Andrea Kolkova, 2019. "Decomposition and Forecasting Time Series in the Business Economy Using Prophet Forecasting Model," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 26-39.
     • Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
     • Deepa Mishra & Angappa Gunasekaran & Thanos Papadopoulos & Stephen J. Childe, 2018. "Big Data and supply chain management: a review and bibliometric analysis," Annals of Operations Research, Springer, vol. 270(1), pages 313-336, November.
     • E. Vercher & A. Corberán-Vallet & J. Segura & J. Bermúdez, 2012. "Initial conditions estimation for improving forecast accuracy in exponential smoothing," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 517-533, July.
     • Lawrence, Michael & O'Connor, Marcus, 2005. "Judgmental forecasting in the presence of loss functions," International Journal of Forecasting, Elsevier, vol. 21(1), pages 3-14.
     • Qing Qin & Lingxiao Li, 2025. "A VMD-Based Four-Stage Hybrid Forecasting Model with Error Correction for Complex Coal Price Series," Mathematics, MDPI, vol. 13(18), pages 1-24, September.
     • J W Taylor, 2011. "Multi-item sales forecasting with total and split exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 555-563, March.
     • Davide Provenzano & Serena Volo, 2022. "Tourism recovery amid COVID-19: The case of Lombardy, Italy," Tourism Economics, , vol. 28(1), pages 110-130, February.
     • Mishra, G. C. & Singh, A., . "A Study on Forecasting Prices of Groundnut Oil in Delhi by Arima Methodology and Artificial Neural Networks," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 5(3), pages 1-10.
     • Athanasopoulos, George & Ahmed, Roman A. & Hyndman, Rob J., 2009. "Hierarchical forecasts for Australian domestic tourism," International Journal of Forecasting, Elsevier, vol. 25(1), pages 146-166.
       • George Athanasopoulos & Roman A. Ahmed & Rob J. Hyndman, 2007. "Hierarchical forecasts for Australian domestic tourism," Monash Econometrics and Business Statistics Working Papers 12/07, Monash University, Department of Econometrics and Business Statistics, revised Nov 2007.
     • Petropoulos, Fotios & Spiliotis, Evangelos, 2025. "Judgmental selection of parameters for simple forecasting models," European Journal of Operational Research, Elsevier, vol. 323(3), pages 780-794.
     • Syed Mithun Ali & Amanat Ur Rahman & Golam Kabir & Sanjoy Kumar Paul, 2024. "Artificial Intelligence Approach to Predict Supply Chain Performance: Implications for Sustainability," Sustainability, MDPI, vol. 16(6), pages 1-31, March.
     • Thiyanga S Talagala & Rob J Hyndman & George Athanasopoulos, 2018. "Meta-learning how to forecast time series," Monash Econometrics and Business Statistics Working Papers 6/18, Monash University, Department of Econometrics and Business Statistics.
     • Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2020. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," Applied Energy, Elsevier, vol. 261(C).
     • Kyriazi, Foteini & Thomakos, Dimitrios D. & Guerard, John B., 2019. "Adaptive learning forecasting, with applications in forecasting agricultural prices," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1356-1369.
     • Muzi Zhang & Junyi Li & Bing Pan & Gaojun Zhang, 2018. "Weekly Hotel Occupancy Forecasting of a Tourism Destination," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
     • Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, vol. 25(4), pages 760-772, October.
     • Chellai, Fatih, 2025. "A Proposal for a Unified Forecast Accuracy Index (UFAI): Toward Multidimensional and Context-Aware Forecast Evaluation," MPRA Paper 127449, University Library of Munich, Germany.
     • Eren Bas & Erol Egrioglu & Ufuk Yolcu, 2021. "Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm," Forecasting, MDPI, vol. 3(4), pages 1-11, November.
     • Bozos, Konstantinos & Nikolopoulos, Konstantinos, 2011. "Forecasting the value effect of seasoned equity offering announcements," European Journal of Operational Research, Elsevier, vol. 214(2), pages 418-427, October.
     • Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
     • Doornik, Jurgen A. & Castle, Jennifer L. & Hendry, David F., 2020. "Card forecasts for M4," International Journal of Forecasting, Elsevier, vol. 36(1), pages 129-134.
     • Gang Cheng & Sicong Wang & Yuhong Yang, 2015. "Forecast Combination under Heavy-Tailed Errors," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
     • Dinesh Reddy Vangumalli & Konstantinos Nikolopoulos & Konstantia Litsiou, 2019. "Clustering, Forecasting and Cluster Forecasting: using k-medoids, k-NNs and random forests for cluster selection," Working Papers 19016, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
     • Tratar, Liljana Ferbar, 2010. "Joint optimisation of demand forecasting and stock control parameters," International Journal of Production Economics, Elsevier, vol. 127(1), pages 173-179, September.
     • Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
     • Sbrana, Giacomo & Silvestrini, Andrea, 2023. "The RWDAR model: A novel state-space approach to forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 922-937.
     • Bekiroglu, Korkut & Duru, Okan & Gulay, Emrah & Su, Rong & Lagoa, Constantino, 2018. "Predictive analytics of crude oil prices by utilizing the intelligent model search engine," Applied Energy, Elsevier, vol. 228(C), pages 2387-2397.
     • Dellino, G. & Laudadio, T. & Mari, R. & Mastronardi, N. & Meloni, C., 2018. "Microforecasting methods for fresh food supply chain management: A computational study," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 147(C), pages 100-120.
     • Makridakis, Spyros & Spiliotis, Evangelos & Hollyman, Ross & Petropoulos, Fotios & Swanson, Norman & Gaba, Anil, 2025. "The M6 forecasting competition: Bridging the gap between forecasting and investment decisions," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1315-1354.
     • Bermudez, J.D. & Segura, J.V. & Vercher, E., 2006. "A decision support system methodology for forecasting of time series based on soft computing," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 177-191, November.
     • Ronald W. Butler & Marc S. Paolella, 2017. "Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
     • Dantas, Tiago Mendes & Cyrino Oliveira, Fernando Luiz & Varela Repolho, Hugo Miguel, 2017. "Air transportation demand forecast through Bagging Holt Winters methods," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 116-123.
     • Jerker Denrell & Christina Fang & Chengwei Liu, 2015. "Perspective—Chance Explanations in the Management Sciences," Organization Science, INFORMS, vol. 26(3), pages 923-940, June.
     • Emrouznejad, Ali & Rostami-Tabar, Bahman & Petridis, Konstantinos, 2016. "A novel ranking procedure for forecasting approaches using Data Envelopment Analysis," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 235-243.
     • Gamber, Edward N. & Smith, Julie K., 2009. "Are the Fed's inflation forecasts still superior to the private sector's?," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 240-251, June.
       • Edward N. Gamber & Julie K. Smith, 2007. "Are the Fed’s Inflation Forecasts Still Superior to the Private Sector’s?," Working Papers 2007-002, The George Washington University, The Center for Economic Research, revised Jul 2008.
     • Roy Verbaan & Wilko Bolt & Carin van der Cruijsen, 2017. "Using debit card payments data for nowcasting Dutch household consumption," DNB Working Papers 571, Netherlands Central Bank, Research Department.
     • Fildes, Robert, 2006. "The forecasting journals and their contribution to forecasting research: Citation analysis and expert opinion," International Journal of Forecasting, Elsevier, vol. 22(3), pages 415-432.
     • Syed Ali Asad Rizvi & Stephen J. Roberts & Michael A. Osborne & Favour Nyikosa, 2017. "A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes," Papers 1705.00891, arXiv.org.
     • de Oliveira, Erick Meira & Cyrino Oliveira, Fernando Luiz, 2018. "Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods," Energy, Elsevier, vol. 144(C), pages 776-788.
     • David F. Hendry, 2004. "Unpredictability and the Foundations of Economic Forecasting," Econometric Society 2004 Australasian Meetings 27, Econometric Society.
       • David F. Hendry, 2004. "Unpredictability and the Foundations of Economic Forecasting," Economics Papers 2004-W15, Economics Group, Nuffield College, University of Oxford.
     • Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
     • Koning, Alex J. & Franses, Philip Hans & Hibon, Michele & Stekler, H.O., 2005. "The M3 competition: Statistical tests of the results," International Journal of Forecasting, Elsevier, vol. 21(3), pages 397-409.
     • Gardner, Everette S., 2015. "Conservative forecasting with the damped trend," Journal of Business Research, Elsevier, vol. 68(8), pages 1739-1741.
     • J Mingers, 2006. "A critique of statistical modelling in management science from a critical realist perspective: its role within multimethodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(2), pages 202-219, February.
     • R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
     • Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1109, Universitá degli Studi di Milano.
       • Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2016. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," MPRA Paper 76308, University Library of Munich, Germany.
       • Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
     • Robert Fildes & Gary Madden & Joachim Tan, 2007. "Optimal forecasting model selection and data characteristics," Applied Financial Economics, Taylor & Francis Journals, vol. 17(15), pages 1251-1264.
       • Fildes, Robert & Madden, Gary & Tan, Joachim, 2007. "Optimal forecasting model selection and data characteristics," MPRA Paper 10819, University Library of Munich, Germany.
     • Dmitry Kucharavy & Eric Schenk & Roland de Guio, 2009. "Long-Run Forecasting of Emerging Technologies with Logistic Models and Growth of Knowledge," Post-Print halshs-00440438, HAL.
     • J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
       • J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, University of Reading, revised 01 Aug 2020.
     • Robert R. Andrawis & Amir F. Atiya, 2009. "A new Bayesian formulation for Holt's exponential smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 218-234.
     • N. N. Taleb & R. Douady, 2013. "Mathematical definition, mapping, and detection of (anti)fragility," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1677-1689, November.
       • Nassim N. Taleb & Raphael Douady, 2012. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Papers 1208.1189, arXiv.org.
       • Nassim Nicholas Taleb & Raphaël Douady, 2014. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Documents de travail du Centre d'Economie de la Sorbonne 14093, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
       • Nassim Nicholas Taleb & Raphaël Douady, 2014. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01151340, HAL.
       • N. N. Taleb & Raphaël Douady, 2013. "Mathematical Definition, Mapping, and Detection of (Anti)fragility," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01052645, HAL.
       • Nassim Nicholas Taleb & Raphaël Douady, 2014. "Mathematical Definition, Mapping, and Detection of (Anti)Fragility," Post-Print hal-01151340, HAL.
       • N. N. Taleb & Raphaël Douady, 2013. "Mathematical Definition, Mapping, and Detection of (Anti)fragility," Post-Print hal-01052645, HAL.
     • Kolassa, Stephan, 2011. "Combining exponential smoothing forecasts using Akaike weights," International Journal of Forecasting, Elsevier, vol. 27(2), pages 238-251.
     • Snyder, Ralph D. & Koehler, Anne B., 2009. "Incorporating a tracking signal into a state space model," International Journal of Forecasting, Elsevier, vol. 25(3), pages 526-530, July.
     • Babai, M. Zied & Ali, Mohammad M. & Nikolopoulos, Konstantinos, 2012. "Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis," Omega, Elsevier, vol. 40(6), pages 713-721.