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The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach

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Cited by:

  1. Chang, Chia-Lin & de Bruijn, Bert & Franses, Philip Hans & McAleer, Michael, 2013. "Analyzing fixed-event forecast revisions," International Journal of Forecasting, Elsevier, vol. 29(4), pages 622-627.
  2. Jos Jansen & Jasper de Winter, 2016. "Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries," DNB Working Papers 507, Netherlands Central Bank, Research Department.
  3. Konstantin A. Kholodilin & Dirk Ulbricht & Georg Wagner, 2014. "Are the Economic Sanctions against Russia Effective?," DIW Roundup: Politik im Fokus 28, DIW Berlin, German Institute for Economic Research.
  4. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
  5. Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2021. "Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 290-314.
  6. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
  7. Filip Novotný & Marie Raková, 2011. "Assessment of Consensus Forecasts Accuracy: The Czech National Bank Perspective," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 348-366, August.
  8. Reslow, André, 2019. "Inefficient Use of Competitors'Forecasts?," Working Paper Series 380, Sveriges Riksbank (Central Bank of Sweden).
  9. Ullrich Heilemann & Karsten Müller, 2018. "Wenig Unterschiede – Zur Treffsicherheit Internationaler Prognosen und Prognostiker [Few differences—on the accuracy of international forecasts and forecaster]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 195-233, December.
  10. Marcos Bujosa & Antonio García‐Ferrer & Aránzazu de Juan & Antonio Martín‐Arroyo, 2020. "Evaluating early warning and coincident indicators of business cycles using smooth trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 1-17, January.
  11. Bruno Deschamps, 2015. "Are aggregate corporate earnings forecasts unbiased and efficient?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 803-818, November.
  12. Dovern, Jonas & Jannsen, Nils, 2017. "Systematic errors in growth expectations over the business cycle," International Journal of Forecasting, Elsevier, vol. 33(4), pages 760-769.
  13. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
  14. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  15. Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
  16. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
  17. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
  18. Raghav Goyal & Michael K. Adjemian, 2023. "Information rigidities in USDA crop production forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(5), pages 1405-1425, October.
  19. Jörg Döpke & Ulrich Fritsche & Boriss Siliverstovs, 2010. "Evaluating German business cycle forecasts under an asymmetric loss function," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-18.
  20. Rybacki, Jakub, 2020. "Polish GDP Forecast Errors: A Tale of Ineffectiveness," MPRA Paper 98952, University Library of Munich, Germany.
  21. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2013. "Information Rigidities in Economic Growth Forecasts: Evidence from a Large International Panel," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79936, Verein für Socialpolitik / German Economic Association.
  22. Drechsel, Katja & Scheufele, Rolf, 2011. "The Financial Crisis from a Forecaster’s Perspective," IWH Discussion Papers 5/2011, Halle Institute for Economic Research (IWH).
  23. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
  24. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  25. Eva A. Arnold, 2013. "The Role of Data Revisions and Disagreement in Professional Forecasts," Macroeconomics and Finance Series 201303, University of Hamburg, Department of Socioeconomics.
  26. Sergey V. Smirnov & Daria A. Avdeeva, 2016. "Wishful Bias in Predicting Us Recessions: Indirect Evidence," HSE Working papers WP BRP 135/EC/2016, National Research University Higher School of Economics.
  27. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
  28. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
  29. Deschamps, Bruno & Ioannidis, Christos & Ka, Kook, 2020. "High-frequency credit spread information and macroeconomic forecast revision," International Journal of Forecasting, Elsevier, vol. 36(2), pages 358-372.
  30. Dovern, Jonas & Weisser, Johannes, 2011. "Accuracy, unbiasedness and efficiency of professional macroeconomic forecasts: An empirical comparison for the G7," International Journal of Forecasting, Elsevier, vol. 27(2), pages 452-465.
  31. Emilian Dobrescu, 2014. "A Hybrid Forecasting Approach," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(35), pages 390-390, February.
  32. de Haan, Leo & Hessel, Jeroen & van den End, Jan Willem, 2014. "Are European sovereign bonds fairly priced? The role of modelling uncertainty," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 239-267.
  33. Barrera Chaupis, Carlos, 2016. "Expectations' Dispersion & Convergence towards Central Banks' IR forecasts: Chile, Colombia, Mexico, Peru & United Kingdom, 2004-2014," MPRA Paper 85410, University Library of Munich, Germany, revised 12 Dec 2016.
  34. Dovern, Jonas & Fritsche, Ulrich & Loungani, Prakash & Tamirisa, Natalia, 2015. "Information rigidities: Comparing average and individual forecasts for a large international panel," International Journal of Forecasting, Elsevier, vol. 31(1), pages 144-154.
  35. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
  36. Trabelsi, Emna, 2016. "Central bank transparency and the consensus forecast: What does The Economist poll of forecasters tell us?," Research in International Business and Finance, Elsevier, vol. 38(C), pages 338-359.
  37. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, September.
  38. Papastamos, Dimitrios & Matysiak, George & Stevenson, Simon, 2015. "Assessing the accuracy and dispersion of real estate investment forecasts," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 141-152.
  39. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.
  40. Jansen, W. Jos & Jin, Xiaowen & de Winter, Jasper M., 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 411-436.
  41. Vereda, Luciano & Savignon, João & Gouveia da Silva, Tarciso, 2024. "A theory-based method to evaluate the impact of central bank inflation forecasts on private inflation expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1069-1084.
  42. Dovern, Jonas & Weisser, Johannes, 2008. "Are they really rational? Assessing professional macro-economic forecasts from the G7-countries," Kiel Working Papers 1447, Kiel Institute for the World Economy (IfW Kiel).
  43. Cristiane Gea & Luciano Vereda & Eduardo Ogasawara, 2024. "Detection of Uncertainty Events in the Brazilian Economic and Financial Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1507-1538, September.
  44. Jakub Rybacki, 2021. "Polish GDP forecast errors: a tale of inefficiency," Bank i Kredyt, Narodowy Bank Polski, vol. 52(2), pages 123-142.
  45. Deschamps, Bruno & Ioannidis, Christos, 2013. "Can rational stubbornness explain forecast biases?," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 141-151.
  46. Franses, Ph.H.B.F., 2019. "Professional Forecasters and January," Econometric Institute Research Papers EI2019-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  47. Jakub Rybacki & Michał Gniazdowski, 2023. "Macroeconomic forecasting in Poland: lessons from the external shocks," Bank i Kredyt, Narodowy Bank Polski, vol. 54(1), pages 45-64.
  48. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, September.
  49. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
  50. Dimitrios Papastamos & George Matysiak & Simon Stevenson, 2014. "A Comparative Analysis of the Accuracy and Uncertainty in Real Estate and Macroeconomic Forecasts," Real Estate & Planning Working Papers rep-wp2014-06, Henley Business School, University of Reading.
  51. Alfredo Pistelli M., 2012. "Análisis de Sesgos y Eficiencia en Proyecciones de Consensus Forecasts," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 98-104, April.
  52. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," University of Göttingen Working Papers in Economics 195, University of Goettingen, Department of Economics.
  53. Sergey V. Smirnov, 2014. "Predicting US Recessions: Does a Wishful Bias Exist?," HSE Working papers WP BRP 77/EC/2014, National Research University Higher School of Economics.
  54. de Mendonça, Helder Ferreira & de Deus, Joseph David Barroso Vasconcelos, 2019. "Central bank forecasts and private expectations: An empirical assessment from three emerging economies," Economic Modelling, Elsevier, vol. 83(C), pages 234-244.
  55. Vereda, Luciano & Savignon, João & Gouveia da Silva, Tarciso, 2021. "A new method to assess the degree of information rigidity using fixed-event forecasts," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1576-1589.
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