IDEAS home Printed from https://ideas.repec.org/r/nbr/nberbk/minc69-1.html
   My bibliography  Save this item

Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance

Citations

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


Cited by:

  1. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
  2. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
  3. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage combination from a real-time dataset," CSEF Working Papers 274, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
  4. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
  5. Hecq, Alain & Jacobs, Jan P.A.M. & Stamatogiannis, Michalis P., 2019. "Testing for news and noise in non-stationary time series subject to multiple historical revisions," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 396-407.
  6. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
  7. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: a State dependent analysis," Research Discussion Papers 7/2021, Bank of Finland.
  8. Carola Conces Binder & Rodrigo Sekkel, 2024. "Central bank forecasting: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 342-364, April.
  9. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
  10. Chiu, Adrian & Wieladek, Tomasz, 2012. "Did output gap measurement improve over time?," Discussion Papers 36, Monetary Policy Committee Unit, Bank of England.
  11. Benchimol, Jonathan & El-Shagi, Makram, 2020. "Forecast performance in times of terrorism," Economic Modelling, Elsevier, vol. 91(C), pages 386-402.
  12. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
  13. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
  14. Rajkumar Janardanan & Xiao Qiao & K. Geert Rouwenhorst, 2019. "On commodity price limits," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(8), pages 946-961, August.
  15. Andrew C. Chang & Trace J. Levinson, 2023. "Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 88-104, January.
  16. Oliver Merz & Raphael Flepp & Egon Franck, 2019. "Does sentiment harm market efficiency? An empirical analysis using a betting exchange setting," Working Papers 381, University of Zurich, Department of Business Administration (IBW).
  17. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
  18. Zheyao Pan, 2018. "A state‐price volatility index for the U.S. government bond market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 573-597, November.
  19. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
  20. Pedersen, Michael, 2015. "What affects the predictions of private forecasters? The role of central bank forecasts in Chile," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1043-1055.
  21. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
  22. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
  23. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
  24. Cambara, Leilane de Freitas Rocha & Meurer, Roberto & Lima, Gilberto Tadeu, 2022. "Deviating from full rationality but not from theoretical consistency: The behavior of inflation expectations in Brazil," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 492-501.
  25. Magnus Kvåle Helliesen & Håvard Hungnes & Terje Skjerpen, 2022. "Revisions in the Norwegian National Accounts: accuracy, unbiasedness and efficiency in preliminary figures," Empirical Economics, Springer, vol. 62(3), pages 1079-1121, March.
  26. Alexander Foltas & Christian Pierdzioch, 2022. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
  27. Malte Knuppel & Fabian Kruger & Marc-Oliver Pohle, 2022. "Score-based calibration testing for multivariate forecast distributions," Papers 2211.16362, arXiv.org, revised Dec 2023.
  28. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
  29. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
  30. Jan P. A. M. Jacobs & Simon van Norden, 2010. "Lessons from the latest data on U.S. productivity," Working Papers 11-1, Federal Reserve Bank of Philadelphia.
  31. J. Scott Armstrong & Michael C. Grohman, 1972. "A Comparative Study of Methods for Long-Range Market Forecasting," Management Science, INFORMS, vol. 19(2), pages 211-221, October.
  32. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
  33. Pascal Bührig & Klaus Wohlrabe, 2015. "Revisionen der deutschen Industrieproduktion und die ifo Indikatoren," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(21), pages 27-31, November.
  34. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
  35. Baris Soybilgen & Ege Yazgan, 2017. "An evaluation of inflation expectations in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(1), pages 1-31–38.
  36. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
  37. Olga Isengildina-Massa & Berna Karali & Scott H. Irwin, 2013. "When do the USDA forecasters make mistakes?," Applied Economics, Taylor & Francis Journals, vol. 45(36), pages 5086-5103, December.
  38. Mahalia Jackman & Simon Naitram, 2015. "Research Note: Nowcasting Tourist Arrivals in Barbados – Just Google it!," Tourism Economics, , vol. 21(6), pages 1309-1313, December.
  39. Pericoli, Marcello & Taboga, Marco, 2012. "Bond risk premia, macroeconomic fundamentals and the exchange rate," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 42-65.
  40. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
  41. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
  42. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
  43. Bedri Kamil Onur Taş, 2016. "Does the Federal Reserve have Private Information about its Future Actions?," Economica, London School of Economics and Political Science, vol. 83(331), pages 498-517, July.
  44. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
  45. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
  46. Basistha, Arabinda & Kurov, Alexander & Wolfe, Marketa Halova, 2019. "Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility," MPRA Paper 111037, University Library of Munich, Germany.
  47. Bouwman, Kees E. & Jacobs, Jan P.A.M., 2011. "Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 784-792.
  48. Silvia Muzzioli & Luca Gambarelli & Bernard De Baets, 2018. "Indices for Financial Market Volatility Obtained Through Fuzzy Regression," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1659-1691, November.
  49. Huisman, Ronald & Van der Sar, Nico L. & Zwinkels, Remco C.J., 2021. "Volatility expectations and disagreement," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 379-393.
  50. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
  51. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
  52. Elaad, Guy & Reade, J. James & Singleton, Carl, 2020. "Information, prices and efficiency in an online betting market," Finance Research Letters, Elsevier, vol. 35(C).
  53. repec:hum:wpaper:sfb649dp2015-023 is not listed on IDEAS
  54. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
  55. Victor Zarnowitz, 1972. "Forecasting Economic Conditions: The Record and the Prospect," NBER Chapters, in: Economic Research: Retrospect and Prospect, Volume 1, The Business Cycle Today, pages 183-239, National Bureau of Economic Research, Inc.
  56. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
  57. Stanislav Bozhkov & Habin Lee & Uthayasankar Sivarajah & Stella Despoudi & Monomita Nandy, 2020. "Idiosyncratic risk and the cross-section of stock returns: the role of mean-reverting idiosyncratic volatility," Annals of Operations Research, Springer, vol. 294(1), pages 419-452, November.
  58. Iversen, Jens & Laséen, Stefan & Lundvall, Henrik & Söderström, Ulf, 2016. "Real-Time Forecasting for Monetary Policy Analysis: The Case of Sveriges Riksbank," Working Paper Series 318, Sveriges Riksbank (Central Bank of Sweden).
  59. Boussios, David & Skorbiansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," Economic Research Report 327201, United States Department of Agriculture, Economic Research Service.
  60. Clemens J. M. Kool & Daniel L. Thornton, 2015. "How Effective Is Central Bank Forward Guidance?," Review, Federal Reserve Bank of St. Louis, vol. 97(4), pages 303-322.
  61. Arai, Natsuki & Iizuka, Nobuo & Yamamoto, Yohei, 2022. "The Efficiency of the Government’s Revenue Projections," Discussion paper series HIAS-E-122, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  62. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
  63. Isengildina-Massa, Olga & MacDonald, Stephen & Xie, Ran, 2012. "A Comprehensive Evaluation of USDA Cotton Forecasts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(1), pages 1-16, April.
  64. Chiu Adrian & Wieladek Tomasz, 2013. "Is the “Great Recession” really so different from the past?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1037-1084, October.
  65. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
  66. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
  67. Julien Champagne & Guillaume Poulin-Bellisle & Rodrigo Sekkel, 2018. "Evaluating the Bank of Canada Staff Economic Projections Using a New Database of Real-Time Data and Forecasts," Staff Working Papers 18-52, Bank of Canada.
  68. J. Daniel Aromí, 2018. "GDP growth forecasts and information flows: Is there evidence of overreactions?," International Finance, Wiley Blackwell, vol. 21(2), pages 122-139, June.
  69. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
  70. Stephen K. McNees & Geoffrey M. B. Tootell, 1991. "\"Whither New England\"?," New England Economic Review, Federal Reserve Bank of Boston, issue Jul, pages 11-26.
  71. David Edmund Allen, 2020. "Stochastic Volatility and GARCH: Do Squared End-of-Day Returns Provide Similar Information?," JRFM, MDPI, vol. 13(9), pages 1-25, September.
  72. Gaglianone, Wagner Piazza & Giacomini, Raffaella & Issler, João Victor & Skreta, Vasiliki, 2022. "Incentive-driven inattention," Journal of Econometrics, Elsevier, vol. 231(1), pages 188-212.
  73. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
  74. repec:zbw:bofrdp:2017_037 is not listed on IDEAS
  75. Janis Becker & Christian Leschinski, 2021. "Estimating the volatility of asset pricing factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 269-278, March.
  76. Gács, János & Lackó, Mária, 1974. "A népgazdasági szintű tervezési magatartás vizsgálata: kísérlet néhány összefüggés elemzésére [Examination of national-level planning behaviour: An attempt at analysing some interrelations]," MPRA Paper 61834, University Library of Munich, Germany.
  77. Kashyap, Ravi, 2020. "David vs Goliath (You against the Markets), A dynamic programming approach to separate the impact and timing of trading costs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
  78. Robert Krol, 2014. "Forecast Bias of Government Agencies," Cato Journal, Cato Journal, Cato Institute, vol. 34(1), pages 99-112, Winter.
  79. Monique Reid & Pierre Siklos, 2023. "Rationality and biases insights from disaggregated firm level inflation expectations data," Working Papers 11050, South African Reserve Bank.
  80. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
  81. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
  82. Brinca Pedro, 2013. "Monetary business cycle accounting for Sweden," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1085-1119, October.
  83. Pierdzioch, Christian, 2023. "A bootstrap-based efficiency test of growth and inflation forecasts for Germany," Economics Letters, Elsevier, vol. 224(C).
  84. Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
  85. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices," SIRE Discussion Papers 2015-79, Scottish Institute for Research in Economics (SIRE).
  86. 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.
  87. Butler, David & Butler, Robert & Eakins, John, 2021. "Expert performance and crowd wisdom: Evidence from English Premier League predictions," European Journal of Operational Research, Elsevier, vol. 288(1), pages 170-182.
  88. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
  89. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.
  90. 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.
  91. Pablo Pincheira Brown & Nicolás Hardy, 2024. "The mean squared prediction error paradox," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2298-2321, September.
  92. Roland Döhrn, 2023. "Are German National Accounts informationally efficient?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 23-42, March.
  93. Leilane de Freitas Rocha Cambara & Roberto Meurer, Gilberto Tadeu Lima, 2019. "Deviating from Perfect Foresight but not from Theoretical Consistency: The Behavior of Inflation Expectations in Brazil," Working Papers, Department of Economics 2019_36, University of São Paulo (FEA-USP).
  94. Seaman, Brian & Bowman, John, 2022. "Applicability of the M5 to Forecasting at Walmart," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1468-1472.
  95. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
  96. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
  97. Boussios, David & Skoriansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309619, United States Department of Agriculture.
  98. Christopher Hansman & Harrison Hong & Áureo de Paula & Vishal Singh, 2020. "A Sticky-Price View of Hoarding," NBER Working Papers 27051, National Bureau of Economic Research, Inc.
  99. Andrew C. Chang & Trace J. Levinson, 2020. "Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting," Finance and Economics Discussion Series 2020-090, Board of Governors of the Federal Reserve System (U.S.).
  100. Heilemann Ullrich & Stekler Herman O., 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, De Gruyter, vol. 14(2), pages 235-253, May.
  101. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
  102. Jones, Jacob T. & Sinclair, Tara M. & Stekler, Herman O., 2020. "A textual analysis of Bank of England growth forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1478-1487.
  103. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
  104. Yoichi Tsuchiya, 2021. "Thirty‐year assessment of Asian Development Bank's forecasts," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 35(2), pages 18-40, November.
  105. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
  106. Victor Zarnowitz & Charlotte Boschan & Geoffrey H. Moore & Josephine Su, 1972. "Business Cycle Analysis of Econometric Model Simulations," NBER Chapters, in: Econometric Models of Cyclical Behavior, Volumes 1 and 2, pages 311-541, National Bureau of Economic Research, Inc.
  107. Shijia Song & Handong Li, 2023. "A new model for forecasting VaR and ES using intraday returns aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1039-1054, August.
  108. 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.
  109. Paulo Júlio & Pedro M. Esperança & João C. Fonseca, 2011. "Evaluating the forecast quality of GDP components," GEE Papers 0041 Classification-C52, , Gabinete de Estratégia e Estudos, Ministério da Economia, revised Oct 2011.
  110. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
  111. Nam, Minho & Go, Minji, 2018. "Nexus between Inflation, Inflation Perceptions and Expectations," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 40(3), pages 45-68.
  112. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
  113. Fardoust, Shahrokh & Dhareshwar, Ashok, 2013. "Some thoughts on making long-term forecasts for the world economy," Policy Research Working Paper Series 6705, The World Bank.
  114. repec:zbw:bofrdp:2021_007 is not listed on IDEAS
  115. Marcell Göttert & Robert Lehmann, 2021. "Tax Revenue Forecast Errors: Wrong Predictions of the Tax Base or the Elasticity?," CESifo Working Paper Series 9148, CESifo.
  116. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.
  117. Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
  118. Clements, Michael P. & Reade, J. James, 2020. "Forecasting and forecast narratives: The Bank of England Inflation Reports," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1488-1500.
  119. Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2014. "Evaluating FOMC forecast ranges: an interval data approach," Empirical Economics, Springer, vol. 47(1), pages 365-388, August.
  120. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
  121. Berg Tim Oliver, 2015. "Time Varying Fiscal Multipliers in Germany," Review of Economics, De Gruyter, vol. 66(1), pages 13-46, April.
  122. Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
  123. Francesco Chincoli & Massimo Guidolin, 2017. "Linear and nonlinear predictability in investment style factors: multivariate evidence," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 476-509, October.
  124. Sebastian Bayer & Timo Dimitriadis, 2018. "Regression Based Expected Shortfall Backtesting," Papers 1801.04112, arXiv.org, revised Sep 2019.
  125. D K Srivastava & C Bhujanga Rao, 2010. "Measuring Accuracy of Projections of Central Taxes by the Finance Commission," Working Papers 2010-052, Madras School of Economics,Chennai,India.
  126. Behrens, Christoph, 2019. "Evaluating the Joint Efficiency of German Trade Forecasts. A nonparametric multivariate approach," Working Papers 9, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
  127. Fuentes, Julieta & Poncela, Pilar & Rodríguez, Julio, 2014. "Selecting and combining experts from survey forecasts," DES - Working Papers. Statistics and Econometrics. WS ws140905, Universidad Carlos III de Madrid. Departamento de Estadística.
  128. Thomas Lustenberger & Enzo Rossi, 2022. "The Social Value of Information: A Test of a Beauty and Nonbeauty Contest," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(7), pages 2125-2148, October.
  129. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "How to Estimate Beta?," Hannover Economic Papers (HEP) dp-617, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  130. Marek RUSNAK, 2013. "Revisions to the Czech National Accounts: Properties and Predictability," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(3), pages 244-261, July.
  131. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, vol. 44(C), pages 91-118.
  132. R J Bennett, 1975. "Dynamic Systems Modelling of the North-West Region: 4. Adaptive Spatio—Temporal Forecasts," Environment and Planning A, , vol. 7(8), pages 887-898, December.
  133. Leif Anders Thorsrud, 2016. "Nowcasting using news topics Big Data versus big bank," Working Papers No 6/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  134. Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
  135. Kenneth W. Clements & Jiawei Si & Thomas Simpson, 2016. "Understanding New Resource Projects," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(3), pages 584-600, September.
  136. Yoichi Tsuchiya, 2021. "The value added of the Bank of Japan's range forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 817-833, August.
  137. Lixiong Yang, 2020. "State-dependent biases and the quality of China’s preliminary GDP announcements," Empirical Economics, Springer, vol. 59(6), pages 2663-2687, December.
  138. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
  139. Benjamin Beckers & Samya Beidas-Strom, 2015. "Forecasting the Nominal Brent Oil Price with VARs—One Model Fits All?," IMF Working Papers 2015/251, International Monetary Fund.
  140. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
  141. Kuruc, Kevin, 2022. "Are IMF rescue packages effective? A synthetic control analysis of macroeconomic crises," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 38-53.
  142. 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.
  143. Zeno Ronald R. Abenoja & Jasmin E. Dacio & Sarah Jane A. Castañares & Jan Christopher G. Ocampo & Mark Rex S. Romaraog, 2022. "The BSP's Forecasting and Policy Analysis System," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 59(1), pages 77-107, June.
  144. Eicher, Theo S. & Rollinson, Yuan Gao, 2023. "The accuracy of IMF crises nowcasts," International Journal of Forecasting, Elsevier, vol. 39(1), pages 431-449.
  145. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
  146. Julien Champagne & Guillaume Poulin‐Bellisle & Rodrigo Sekkel, 2020. "Introducing the Bank of Canada staff economic projections database," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 114-129, January.
  147. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2023. "The accuracy and informativeness of agricultural baselines," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1116-1148, August.
  148. Schanne, Norbert, 2012. "The formation of experts' expectations on labour markets : do they run with the pack?," IAB-Discussion Paper 201225, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  149. 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.
  150. Francesco Audrino & Simon D. Knaus, 2016. "Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1485-1521, December.
  151. Thomas Dimpfl & Tobias Langen, 2019. "How Unemployment Affects Bond Prices: A Mixed Frequency Google Nowcasting Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 551-573, August.
  152. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
  153. Ayala, Astrid & Blazsek, Szabolcs, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
  154. MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017. "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper 87545, University Library of Munich, Germany.
  155. Oikonomou, Ioannis & Stancu, Andrei & Symeonidis, Lazaros & Wese Simen, Chardin, 2019. "The information content of short-term options," Journal of Financial Markets, Elsevier, vol. 46(C).
  156. 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.
  157. Guy, Kester & Lowe, Shane, 2012. "Tracing the Liquidity Effects on Bank Stability in Barbados," MPRA Paper 52205, University Library of Munich, Germany.
  158. Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2021. "The Bias and Efficiency of the ECB Inflation Projections: a State Dependent Analysis," Working Paper 2021/1, Norges Bank.
  159. Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
  160. Agnès Bénassy-Quéré & Hélène Raymond, 1996. "Les erreurs de prévision de change ont-elles des caractéristiques hétérogènes ?," Économie et Prévision, Programme National Persée, vol. 125(4), pages 137-157.
  161. Juan Manuel Julio Román, 2011. "Modeling Data Revisions," Borradores de Economia 7929, Banco de la Republica.
  162. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
  163. Patrick Rizzetto, 2018. "GDP by Industry in Real Time: Are Revisions Well Behaved?," Staff Analytical Notes 2018-40, Bank of Canada.
  164. repec:ags:aaea22:335690 is not listed on IDEAS
  165. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
  166. Christensen, Bent Jesper & Kjær, Mads Markvart & Veliyev, Bezirgen, 2023. "The incremental information in the yield curve about future interest rate risk," Journal of Banking & Finance, Elsevier, vol. 155(C).
  167. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
  168. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
  169. Hakki Ozturk & Umit Erol & Asli Yuksel, 2016. "Extreme Value Volatility Estimators and Realized Volatility of Istanbul Stock Exchange: Evidence from Emerging Market," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(8), pages 1-71, August.
  170. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
  171. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
  172. Richard D. F. Harris & Jian Shen & Evarist Stoja, 2010. "The Limits to Minimum‐Variance Hedging," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(5‐6), pages 737-761, June.
  173. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
  174. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2018. "How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 139-169, January.
  175. Behrens, Christoph, 2020. "German trade forecasts since 1970: An evaluation using the panel dimension," Working Papers 26, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
  176. Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
  177. William J. Frazer & Jr., 1973. "An Assessment of the Impact of the Computer," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 109(IV), pages 579-595, December.
  178. Duan, Fang, 2022. "Forecasting risk measures based on structural breaks in the correlation matrix," Ruhr Economic Papers 945, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  179. Jianlei Han & Martina Linnenluecke & Zhangxin Liu & Zheyao Pan & Tom Smith, 2019. "A general equilibrium approach to pricing volatility risk," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-18, April.
  180. Kaelo Ntwaepelo & Grivas Chiyaba, 2022. "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers em-dp2022-06, Department of Economics, University of Reading.
  181. Dooyeon Cho & Dong-Eun Rhee, 2015. "An assessment of inflation targeting in a quantitative monetary business cycle framework: evidence from four early adopters," Applied Economics, Taylor & Francis Journals, vol. 47(32), pages 3395-3413, July.
  182. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  183. Jörg Döpke & Ulrich Fritsche & Karsten Müller, 2018. "Has Macroeconomic Forecasting changed after the Great Recession? - Panel-based Evidence on Accuracy and Forecaster Behaviour from Germany," Macroeconomics and Finance Series 201803, University of Hamburg, Department of Socioeconomics.
  184. Pincheira, Pablo & Hardy, Nicolas, 2020. "The Mean Squared Prediction Error Paradox: A summary," MPRA Paper 105020, University Library of Munich, Germany.
  185. repec:ags:jrapmc:122314 is not listed on IDEAS
  186. Peter, Eckley, 2015. "(Non)rationality of consumer inflation perceptions," MPRA Paper 77082, University Library of Munich, Germany.
  187. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
  188. Reade, J. James & Vaughan Williams, Leighton, 2019. "Polls to probabilities: Comparing prediction markets and opinion polls," International Journal of Forecasting, Elsevier, vol. 35(1), pages 336-350.
  189. Guy Elaad, 2020. "Home-field advantage and biased prediction markets in English soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 27(14), pages 1170-1174, July.
  190. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model," MPRA Paper 58554, University Library of Munich, Germany.
  191. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
  192. Hempenius, A.L., 1981. "Forecast accuracy analysis : Applied to forecasts of the Dutch Central Planning Bureau, 1964-1978," Other publications TiSEM d96d78f5-f5e0-43f3-93c2-6, Tilburg University, School of Economics and Management.
  193. Kempkes, Gerhard, 2012. "Cyclical adjustment in fiscal rules: Some evidence on real-time bias for EU-15 countries," Discussion Papers 15/2012, Deutsche Bundesbank.
  194. Regmi, Hari & Kuethe, Todd H. & Foster, Kenneth A., 2022. "Evaluation of USDA's Agricultural Exports Projections," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322363, Agricultural and Applied Economics Association.
  195. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
  196. repec:zbw:bofitp:2015_012 is not listed on IDEAS
  197. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
  198. Breuer Christian, 2015. "On the Rationality of Medium-Term Tax Revenue Forecasts: Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(1), pages 22-40, February.
  199. Julieta Caunedo & Riccardo Dicecio & Ivana Komunjer & Michael T. Owyang, 2020. "Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(1), pages 205-228, February.
  200. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
  201. Miller, Thomas W. & Rapach, David E., 2013. "An intra-week efficiency analysis of bookie-quoted NFL betting lines in NYC," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 10-23.
  202. Klaus-Peter Hellwig, 2018. "Overfitting in Judgment-based Economic Forecasts: The Case of IMF Growth Projections," IMF Working Papers 2018/260, International Monetary Fund.
  203. Clements, Michael P., 2021. "Rounding behaviour of professional macro-forecasters," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1614-1631.
  204. Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
  205. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
  206. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
  207. German Rodikov & Nino Antulov-Fantulin, 2023. "Introducing the $\sigma$-Cell: Unifying GARCH, Stochastic Fluctuations and Evolving Mechanisms in RNN-based Volatility Forecasting," Papers 2309.01565, arXiv.org.
  208. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
  209. Chen, Chun-Hung & Yu, Wei-Choun & Zivot, Eric, 2012. "Predicting stock volatility using after-hours information: Evidence from the NASDAQ actively traded stocks," International Journal of Forecasting, Elsevier, vol. 28(2), pages 366-383.
  210. André Binette & Dmitri Tchebotarev, 2017. "Evaluating Real GDP Growth Forecasts in the Bank of Canada Monetary Policy Report," Staff Analytical Notes 17-21, Bank of Canada.
  211. Bengtsson, Ola & Ekeblom, Daniel, 2014. "The Bright but Right View? New Evidence on Entrepreneurial Optimism," Working Papers 2014:1, Lund University, Department of Economics.
  212. Enders, Walter & Pascalau, Razvan, 2015. "Pretesting for multi-step-ahead exchange rate forecasts with STAR models," International Journal of Forecasting, Elsevier, vol. 31(2), pages 473-487.
  213. Xiao, Jihong & Wen, Fenghua & Zhao, Yupei & Wang, Xiong, 2021. "The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 311-333.
  214. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
  215. Ilias Filippou & James Mitchell & My T. Nguyen, 2023. "The FOMC versus the Staff: Do Policymakers Add Value in Their Tales?," Working Papers 23-20, Federal Reserve Bank of Cleveland.
  216. Lena Dr䧥r & Jan-Oliver Menz & Ulrich Fritsche, 2014. "Perceived inflation under loss aversion," Applied Economics, Taylor & Francis Journals, vol. 46(3), pages 282-293, January.
  217. Frank-Oliver Aldenhoff, 2007. "Are economic forecasts of the International Monetary Fund politically biased? A public choice analysis," The Review of International Organizations, Springer, vol. 2(3), pages 239-260, September.
  218. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
  219. Ravi Kashyap, 2016. "Hong Kong -- Shanghai Connect / Hong Kong -- Beijing Disconnect (?): Scaling the Great Wall of Chinese Securities Trading Costs," Papers 1603.01341, arXiv.org, revised Sep 2019.
  220. 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.
  221. Brown, Alasdair & Yang, Fuyu, 2019. "The wisdom of large and small crowds: Evidence from repeated natural experiments in sports betting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 288-296.
  222. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2021. "The bias and efficiency of the ECB inflation projections: A state dependent analysis," Bank of Finland Research Discussion Papers 7/2021, Bank of Finland.
  223. Isengildina Massa, Olga & Stewart, Shamar & Hassman, Colburn H., 2021. "RETURN DIVERGENCE IN COMMODITY ETFs: NATURE AND CAUSES," 2021 Annual Meeting, August 1-3, Austin, Texas 313896, Agricultural and Applied Economics Association.
  224. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
  225. Hempenius, A.L., 1981. "Forecast accuracy analysis : Applied to forecasts of the Dutch Central Planning Bureau, 1964-1978," Research Memorandum FEW 90, Tilburg University, School of Economics and Management.
  226. Kenneth Eva & Fabian Winkler, 2023. "A Comprehensive Empirical Evaluation of Biases in Expectation Formation," Finance and Economics Discussion Series 2023-042, Board of Governors of the Federal Reserve System (U.S.).
  227. Various, 1971. "Papers by Staff Members on Research Priorities," NBER Chapters, in: New Directions in Economic Research, pages 1-70, National Bureau of Economic Research, Inc.
  228. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
  229. Alasdair Brown & Fuyu Yang, 2021. "Framing effects and the market selection hypothesis: Evidence from real‐world isomorphic bets," Southern Economic Journal, John Wiley & Sons, vol. 88(1), pages 399-413, July.
  230. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.
  231. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
  232. repec:zbw:bofrdp:037 is not listed on IDEAS
  233. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2018. "Forecasting With Social Media: Evidence From Tweets On Soccer Matches," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1748-1763, July.
  234. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
  235. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
  236. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
  237. Lauter, Tobias & Prokopczuk, Marcel, 2022. "Measuring commodity market quality," Journal of Banking & Finance, Elsevier, vol. 145(C).
  238. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
  239. 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.
  240. Panagiotis Lazaris & Anastasios Petropoulos & Vasileios Siakoulis & Evangelos Stavroulakis & Nikolaos Vlachogiannakis, 2021. "Interest rate pass through in the deposit and loan products provided by Greek banks," Working Papers 287, Bank of Greece.
  241. Boussios, David & Skorbiansky, Sharon Raszap & Maclachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309616, United States Department of Agriculture.
  242. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.
  243. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  244. Cenesizoglu, Tolga & de Oliveira Ferrazoli Ribeiro, Fabio & Reeves, Jonathan J., 2017. "Beta forecasting at long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 936-957.
  245. D K Srivastava & C Bhujanga Rao, 2010. "Measuring Accuracy of Projections of Central Taxes by the Finance Commission," Finance Working Papers 23064, East Asian Bureau of Economic Research.
  246. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.
  247. Timmermann, Allan & Burjack, Rafael & Qu, Ritong, 2019. "Fluctuations in Economic Uncertainty and Transmission of Monetary Policy Shocks: Evidence Using Daily Surveys from Brazil," CEPR Discussion Papers 14097, C.E.P.R. Discussion Papers.
  248. Anupam Dutta & Debojyoti Das, 2022. "Forecasting realized volatility: New evidence from time‐varying jumps in VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2165-2189, December.
  249. Xinyu Wu & Haibin Xie, 2019. "Volatility forecasting using stochastic conditional range model with leverage effect," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(5), pages 1156-1170, September.
  250. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.
  251. Weyerstrass, Klaus, 2015. "Forecasting Accuracy of a Multi-Country Macroeconometric Model for the Former Yugoslavia/Capacidad predictiva de los modelos estructurales frente a modelos de series temporales. Aplicación a un sistem," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 463-486, Mayo.
  252. Brown, Alasdair & Reade, J. James & Vaughan Williams, Leighton, 2019. "When are prediction market prices most informative?," International Journal of Forecasting, Elsevier, vol. 35(1), pages 420-428.
  253. repec:zbw:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  254. Ruhnau, Oliver & Hennig, Patrick & Madlener, Reinhard, 2020. "Economic implications of forecasting electricity generation from variable renewable energy sources," Renewable Energy, Elsevier, vol. 161(C), pages 1318-1327.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.