IDEAS home Printed from https://ideas.repec.org/f/c/pst377.html

Herman O. Stekler

(deceased)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, The Center for Economic Research.

    Mentioned in:

    1. In the black Labour: some issues
      by chris dillow in Stumbling and Mumbling on 2011-12-04 18:33:14

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.

    Mentioned in:

    1. An evaluation of the forecasts of the federal reserve: a pooled approach (Journal of Applied Econometrics 2007) in ReplicationWiki ()

Working papers

  1. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.

    Cited by:

    1. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    2. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    3. Manjhi, Ganesh & Shah, Raashid, 2025. "What do sentiments of budget speeches mean for stock returns?," Economic Modelling, Elsevier, vol. 151(C).
    4. Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020. "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers 2042, Banco de España.
    5. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
    6. Rambaccussing, Dooruj & Kwiatkowski, Andrzej, 2020. "Forecasting with news sentiment: Evidence with UK newspapers," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1501-1516.
    7. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    8. Foltas, Alexander, 2025. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," HWWI Working Paper Series 5/2025, Hamburg Institute of International Economics (HWWI).
    9. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    10. 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.
    11. Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2020. "The Power of Narratives in Economic Forecasts," Finance and Economics Discussion Series 2020-001, Board of Governors of the Federal Reserve System (U.S.).
    12. Haavio, Markus & Heikkinen, Joni & Jalasjoki, Pirkka & Kilponen, Juha & Paloviita, Maritta & Vänni, Ilona, 2024. "Reading between the lines: Uncovering asymmetry in the central bank loss function," Bank of Finland Research Discussion Papers 6/2024, Bank of Finland.

  2. Paul Goodwin & Dilek Önkal & Herman O. Stekler, 2017. "What if you are not Bayesian? The consequences for decisions involving risk," Working Papers 2017-003, The George Washington University, The Center for Economic Research.

    Cited by:

    1. David L. Dickinson & Parker Reid, 2023. "Gambling habits and Probability Judgements in a Bayesian Task Environment," Working Papers 23-03, Department of Economics, Appalachian State University.
    2. Liu, Hui-hui & Song, Yao-yao & Liu, Xiao-xiao & Yang, Guo-liang, 2020. "Aggregating the DEA prospect cross-efficiency with an application to state key laboratories in China," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).

  3. Gabriel Mathy & Herman O. Stekler, 2017. "Was the Deflation of the Depression Anticipated? An Inference Using Real-time Data," Working Papers 2017-004, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.
    2. Thies Clifford F., 2021. "Expectations of a Post-Wwii Depression," Studia Historiae Oeconomicae, Sciendo, vol. 39(1), pages 145-162, December.
    3. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    4. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    5. Gabriel Mathy & Yongchen Zhao, 2025. "Could Diffusion Indexes Have Forecasted the Great Depression?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 320-338, March.

  4. Gabriel Mathy & Herman O. Stekler, 2016. "Expectations and Forecasting during the Great Depression: Real-Time Evidence from the Business Press," Working Papers 2016-011, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    2. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    3. 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.
    4. Gabriel Mathy & Yongchen Zhao, 2023. "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers 2023-05, Towson University, Department of Economics, revised Sep 2023.
    5. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    6. Thies Clifford F., 2021. "Expectations of a Post-Wwii Depression," Studia Historiae Oeconomicae, Sciendo, vol. 39(1), pages 145-162, December.
    7. Gabriel Mathy & Christian Roatta, 2018. "Forecasting the 1937-1938 Recession: Quantifying Contemporary Newspaper Forecasts," Working Papers 2018-004, The George Washington University, The Center for Economic Research.
    8. Gabriel Mathy & Herman O. Stekler, 2017. "Was the Deflation of the Depression Anticipated? An Inference Using Real-time Data," Working Papers 2017-004, The George Washington University, The Center for Economic Research.
    9. Ulrich Fritsche & Johannes Puckelwald, 2018. "Deciphering Professional Forecasters’ Stories - Analyzing a Corpus of Textual Predictions for the German Economy," Macroeconomics and Finance Series 201804, University of Hamburg, Department of Socioeconomics.
    10. Gabriel Mathy & Yongchen Zhao, 2025. "Could Diffusion Indexes Have Forecasted the Great Depression?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 320-338, March.

  5. Herman O. Stekler & Tianyu Ye, 2016. "Evaluating a Leading Indicator: An Application: the Term Spread," Working Papers 2016-004, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Aguilar, Pablo & Vázquez, Jesús, 2025. "Multi-period Euler-equation learning and term structure," Economic Modelling, Elsevier, vol. 153(C).

  6. Kevin Kovacs & Bryan Boulier & Herman O. Stekler, 2016. "Nowcasting German Turning Points Using CUSUM Analysis," Working Papers 2016-014, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.

  7. Herman O. Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-006, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Gabriel Mathy & Yongchen Zhao, 2023. "Could Diffusion Indexes Have Forecasted the Great Depression?," Working Papers 2023-05, Towson University, Department of Economics, revised Sep 2023.
    2. Gabriel Mathy & Yongchen Zhao, 2025. "Could Diffusion Indexes Have Forecasted the Great Depression?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 320-338, March.

  8. Hans Christian Muller-Droge & Tara M. Sinclair & H.O. Stekler, 2014. "Evaluating Forecasts of a Vector of Variables: a German Forecasting Competition," CAMA Working Papers 2014-55, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Inske Pirschel & Maik H. Wolters, 2018. "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, vol. 55(2), pages 573-596, September.
    2. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
    3. 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.
    4. Mihaela SIMIONESCU, 2015. "The Evaluation of Global Accuracy of Romanian Inflation Rate Predictions Using Mahalanobis Distance," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(1), pages 133-149, March.
    5. Dovern, Jonas, 2015. "A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data," European Economic Review, Elsevier, vol. 80(C), pages 16-35.

  9. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    2. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    3. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, The Center for Economic Research.
    4. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.

  10. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, The Center for Economic Research.
    2. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    3. Pierre L. Siklos, 2020. "U.S. Monetary Policy since the 1950s and the Changing Content of FOMC Minutes," Southern Economic Journal, John Wiley & Sons, vol. 86(3), pages 1192-1213, January.
    4. 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.
    5. 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.
    6. Kotłowski, Jacek, 2025. "The role of central bank forecasts in uncertain times," Economic Modelling, Elsevier, vol. 151(C).
    7. Lixiong Yang, 2022. "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, vol. 62(2), pages 533-551, February.
    8. Constantin Bürgi, 2020. "Expectation Formation and the Persistence of Shocks," Working Papers 2020-005, The George Washington University, The Center for Economic Research, revised Sep 2020.
    9. Kuethe, Todd H. & Hubbs, Todd & Sanders, Dwight R., 2018. "Evaluating the USDA’s Net Farm Income Forecast," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(3), September.
    10. Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, University of Hamburg, Department of Socioeconomics.
    11. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2024. "The bias of the ECB inflation projections: A State-dependent analysis," Bank of Finland Research Discussion Papers 4/2024, Bank of Finland.
    12. Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2025. "The Bias of the ECB Inflation Projections: A State‐Dependent Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(3), pages 922-940, April.
    13. 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.
    14. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    15. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
    16. Travis J. Berge, 2020. "Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate," Finance and Economics Discussion Series 2020-012r1, Board of Governors of the Federal Reserve System (U.S.), revised 14 Apr 2021.
    17. 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.).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Jacobs, Jan P.A.M. & van Norden, Simon, 2016. "Why are initial estimates of productivity growth so unreliable?," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 200-213.
    23. 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.
    24. 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.
    25. 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.

  11. Tara M. Sinclair & H.O. Stekler & Warren Carnow, 2012. "Evaluating A Vector Of The Fed’S Forecasts," Working Papers 2012-002, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    2. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
    3. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    4. 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.
    5. 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.
    6. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    7. Binder, Carola Conces & Wetzel, Samantha, 2018. "The FOMC versus the staff, revisited: When do policymakers add value?," Economics Letters, Elsevier, vol. 171(C), pages 72-75.
    8. 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.

  12. Tara M. Sinclair & H.O. Stekler & Warren Carnow, 2012. "A New Approach For Evaluating Economic Forecasts," Working Papers 2012-004, The George Washington University, The Center for Economic Research.

    Cited by:

    1. David Hendry & Andrew B. Martinez, 2016. "Evaluating Multi-Step System Forecasts with Relatively Few Forecast-Error Observations," Economics Series Working Papers 784, University of Oxford, Department of Economics.
    2. Kim, Jong Min & Jun, Mina & Kim, Chung K., 2018. "The Effects of Culture on Consumers' Consumption and Generation of Online Reviews," Journal of Interactive Marketing, Elsevier, vol. 43(C), pages 134-150.
    3. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    4. Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
    5. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    6. Stekler, Herman & Symington, Hilary, 2016. "Evaluating qualitative forecasts: The FOMC minutes, 2006–2010," International Journal of Forecasting, Elsevier, vol. 32(2), pages 559-570.
    7. An, Zidong & Ball, Laurence & Jalles, Joao & Loungani, Prakash, 2019. "Do IMF forecasts respect Okun’s law? Evidence for advanced and developing economies," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1131-1142.
    8. Laurence M. Ball & João Tovar Jalles & Mr. Prakash Loungani, 2014. "Do Forecasters Believe in Okun’s Law? An Assessment of Unemployment and Output Forecasts," IMF Working Papers 2014/024, International Monetary Fund.
    9. Tim Köhler & Jörg Döpke, 2023. "Will the last be the first? Ranking German macroeconomic forecasters based on different criteria," Empirical Economics, Springer, vol. 64(2), pages 797-832, February.
    10. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    11. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    12. Sinclair, Tara M. & Stekler, H.O. & Carnow, Warren, 2015. "Evaluating a vector of the Fed’s forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 157-164.
    13. 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.
    14. Döhrn, Roland, 2015. "Der Prognostiker des Jahres: Ein Zufallsergebnis? Möglichkeiten einer mehrdimensionalen Evaluierung von Konjunkturprognosen," IBES Diskussionsbeiträge 208, University of Duisburg-Essen, Institute of Business and Economic Studie (IBES).
    15. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, The Center for Economic Research.
    16. 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.
    17. 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.
    18. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.
    19. Eicher, Theo S. & Rollinson, Yuan Gao, 2023. "The accuracy of IMF crises nowcasts," International Journal of Forecasting, Elsevier, vol. 39(1), pages 431-449.

  13. Kathryn Lundquist & H.O. Stekler, 2011. "The Forecasting Performance of Business Economists During the Great Recession," Working Papers 2011-004, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.

  14. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
    2. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    3. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, The Center for Economic Research.
    4. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.

  15. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.

    Cited by:

    1. Mr. Manik L. Shrestha & Mr. Marco Marini, 2013. "Quarterly GDP Revisions in G-20 Countries: Evidence from the 2008 Financial Crisis," IMF Working Papers 2013/060, International Monetary Fund.
    2. Jürgen Bierbaumer & Sandra Bilek-Steindl & Marcus Scheiblecker, 2015. "Analysis of the Revisions to the Quarterly National Accounts Since the Introduction of Flash Estimates in 2005," WIFO Bulletin, WIFO, vol. 20(2), pages 14-30, February.
    3. Jürgen Bierbaumer & Sandra Bilek-Steindl & Marcus Scheiblecker, 2014. "Revisionsanalyse der vierteljährlichen Volkswirtschaftlichen Gesamtrechnung seit Einführung der Schnellschätzung im Jahr 2005," WIFO Monatsberichte (monthly reports), WIFO, vol. 87(10), pages 693-710, October.

  16. Ms. Natalia T. Tamirisa & Mr. Prakash Loungani & Mr. Herman O. Stekler, 2011. "Information Rigidity in Growth Forecasts: Some Cross-Country Evidence," IMF Working Papers 2011/125, International Monetary Fund.

    Cited by:

    1. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
    2. Emna Trabelsi, 2016. "Central Bank Transparency and the consensus forecast: What does The Economist poll of forecasters tell us?," Post-Print hal-01121434, HAL.
    3. António Afonso & João Tovar Jalles, 2017. "Fiscal Activism and Price Volatility: Evidence from Advanced and Emerging Economies," Working Papers Department of Economics 2017/04, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    4. Anton Cheremukhin & Antonella Tutino, 2014. "Asymmetric firm dynamics under rational inattention," Working Papers 1411, Federal Reserve Bank of Dallas.
    5. Yoichi Tsuchiya, 2024. "Conservatism and information rigidity of the European Bank for Reconstruction and Development's growth forecast: Quarter‐century assessment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1399-1421, August.
    6. Ms. Ghada Fayad & Mr. Roberto Perrelli, 2014. "Growth Surprises and Synchronized Slowdowns in Emerging Markets––An Empirical Investigation," IMF Working Papers 2014/173, International Monetary Fund.
    7. Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
    8. 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.
    9. 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.
    10. Yingying Xu & Zhixin Liu & Zichao Jia & Chi-Wei Su, 2017. "Is time-variant information stickiness state-dependent?," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(3), pages 169-187, December.
    11. Qiu, Yajie & Deschamps, Bruno, 2025. "Peer influence in macroeconomic predictions," Journal of Economic Behavior & Organization, Elsevier, vol. 236(C).
    12. Hur, Joonyoung, 2018. "Time-varying information rigidities and fluctuations in professional forecasters' disagreement," Economic Modelling, Elsevier, vol. 75(C), pages 117-131.
    13. Rybacki, Jakub, 2020. "Polish GDP Forecast Errors: A Tale of Ineffectiveness," MPRA Paper 98952, University Library of Munich, Germany.
    14. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Schröder, Christian & Sonnenberg, Nils, 2024. "Deutsche Wirtschaft in Frührjahr 2024: Erholung mit Hindernissen [German Economy in Spring 2024: Recovery with Obstacles]," Kieler Konjunkturberichte 112, Kiel Institute for the World Economy.
    15. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    16. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    17. Jonas Dovern & Mr. Ulrich Fritsche & Mr. Prakash Loungani & Ms. Natalia T. Tamirisa, 2013. "Information Rigidities in Economic Growth Forecasts: Evidence from a Large International Panel," IMF Working Papers 2013/056, International Monetary Fund.
    18. 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.
    19. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.
    20. Strunz, Franziska & Gödl, Maximilian, 2023. "An Evaluation of Professional Forecasts for the German Economy," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277707, Verein für Socialpolitik / German Economic Association.
    21. Joao Tovar Jalles, 2015. "How Quickly is News Incorporated in Fiscal Forecasts?," Economics Bulletin, AccessEcon, vol. 35(4), pages 2802-2812.
    22. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    23. Rybacki Jakub, 2020. "Macroeconomic forecasting in Poland: The role of forecasting competitions," Central European Economic Journal, Sciendo, vol. 7(54), pages 1-11, January.
    24. Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Papers No 03/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    25. Qiu, Yajie & Deschamps, Bruno & Liu, Xiaoquan, 2024. "Uncertainty and macroeconomic forecasts: Evidence from survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 463-480.
    26. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    27. Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 175-189.
    28. Thomas F. P. Wiesen & Paul M. Beaumont, 2024. "A joint impulse response function for vector autoregressive models," Empirical Economics, Springer, vol. 66(4), pages 1553-1585, April.
    29. Boysen-Hogrefe, Jens & Groll, Dominik & Hoffmann, Timo & Jannsen, Nils & Kooths, Stefan & Krohn, Johanna & Reents, Jan & Schröder, Christian, 2025. "Deutsche Konjunktur im Frühjahr 2025: Finanzpolitik dreht mächtig auf," Kieler Konjunkturberichte 122, Kiel Institute for the World Economy.
    30. 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.
    31. Sheng, Xuguang (Simon), 2015. "Evaluating the economic forecasts of FOMC members," International Journal of Forecasting, Elsevier, vol. 31(1), pages 165-175.
    32. Goldstein, Nathan & Zilberfarb, Ben-Zion, 2021. "Do forecasters really care about consensus?," Economic Modelling, Elsevier, vol. 100(C).
    33. 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.
    34. Peter Tillmann, 2011. "Reputation and Forecast Revisions: Evidence from the FOMC," MAGKS Papers on Economics 201128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    35. Jakub Rybacki, 2021. "Polish GDP forecast errors: a tale of inefficiency," Bank i Kredyt, Narodowy Bank Polski, vol. 52(2), pages 123-142.
    36. 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.
    37. Jalles, João Tovar & Karibzhanov, Iskander & Loungani, Prakash, 2015. "Cross-country evidence on the quality of private sector fiscal forecasts," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 186-201.
    38. Zidong An & João Tovar Jalles & Mr. Prakash Loungani, 2018. "How Well Do Economists Forecast Recessions?," IMF Working Papers 2018/039, International Monetary Fund.
    39. Lehmann Robert & Wollmershäuser Timo, 2020. "The macroeconomic projections of the German government: A comparison to an independent forecasting institution," German Economic Review, De Gruyter, vol. 21(2), pages 235-270, June.
    40. Dongao Li & Songdong Shen, 2022. "Social Environment and Healthy Investment Behavior: Joint Influence of Culture and Institution on China," IJERPH, MDPI, vol. 19(1), pages 1-17, January.
    41. Kuo-Hsuan Chin, 2019. "New Keynesian Phillips Curve with time-varying parameters," Empirical Economics, Springer, vol. 57(6), pages 1869-1889, December.
    42. Cheremukhin, Anton & Tutino, Antonella, 2016. "Information rigidities and asymmetric business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 142-158.
    43. Mr. Olivier Coibion & Mr. Yuriy Gorodnichenko, 2012. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," IMF Working Papers 2012/296, International Monetary Fund.
    44. 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.

  17. Tara M. Sinclair & H.O. Stekler, 2011. "Examining the Quality of Early GDP Component Estimates," Working Papers 2011-001, The George Washington University, The Center for Economic Research, revised Dec 2011.

    Cited by:

    1. Bruno Ducoudré & Paul Hubert & Guilhem Tabarly, 2020. "The state-dependence of output revisions," Documents de Travail de l'OFCE 2020-04, Observatoire Francais des Conjonctures Economiques (OFCE).
    2. Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
    3. Lixiong Yang, 2022. "Threshold mixed data sampling (TMIDAS) regression models with an application to GDP forecast errors," Empirical Economics, Springer, vol. 62(2), pages 533-551, February.
    4. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    5. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    6. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    7. Theo S. Eicher & David J. Kuenzel & Mr. Chris Papageorgiou & Mr. Charalambos Christofides, 2018. "Forecasts in Times of Crises," IMF Working Papers 2018/048, International Monetary Fund.
    8. Andrew B. Martinez, 2025. "Real-time Hurricane Damage Nowcasts," Working Papers 2025-006, The George Washington University, The Center for Economic Research.
    9. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
    10. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.
    11. Funashima, Yoshito & Iizuka, Nobuo & Ohtsuka, Yoshihiro, 2020. "GDP announcements and stock prices," Journal of Economics and Business, Elsevier, vol. 108(C).
    12. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    13. Martinez, Andrew & Schibuola, Alex, 2021. "The Expectations Gap: An Alternative Measure of Economic Slack," Working Papers 11284, George Mason University, Mercatus Center.
    14. Hans Christian Müller-Dröge & Tara M. Sinclair & Herman O. Stekler, 2014. "Evaluating Forecasts Of A Vector Of Variables: A German Forecasting Competition," Working Papers 2014-004, The George Washington University, The Center for Economic Research.
    15. Danae Scherman Teitelboim, 2020. "Revisiones en cuentas nacionales trimestrales Chile 2006-2019," Economic Statistics Series 131, Central Bank of Chile.
    16. Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
    17. 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.
    18. Eugen Scarlat, 2016. "Connectivity - Based Clustering of GDP Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 23-38, March.
    19. Ignacio Martínez, 2021. "Deepening GDP revision analysis: GDP bias breakdown and compositional change," Economic Statistics Series 136, Central Bank of Chile.
    20. Olga Isengildina‐Massa & Berna Karali & Todd H. Kuethe & Ani L. Katchova, 2021. "Joint Evaluation of the System of USDA's Farm Income Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 1140-1160, September.
    21. 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.
    22. Fosten, Jack & Nandi, Shaoni, 2025. "Nowcasting U.S. state-level CO2 emissions and energy consumption," International Journal of Forecasting, Elsevier, vol. 41(1), pages 20-30.
    23. Andrew B. Martinez & Alexander D. Schibuola & David Beckworth, 2025. "The Reliability of the Nominal GDP Expectations Gap," Working Papers 2025-004, The George Washington University, The Center for Economic Research.

  18. H.O. Stekler & Andrew Klein, 2011. "Predicting the Outcomes of NCAA Basketball Championship Games," Working Papers 2011-003, The George Washington University, The Center for Economic Research.

    Cited by:

    1. David Bergman & Jason Imbrogno, 2017. "Surviving a National Football League Survivor Pool," Operations Research, INFORMS, vol. 65(5), pages 1343-1354, October.
    2. Manner Hans, 2016. "Modeling and forecasting the outcomes of NBA basketball games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 31-41, March.

  19. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, The Center for Economic Research, revised Feb 2012.

    Cited by:

    1. Dopke, Jorg & Fritsche, Ulrich, 2006. "When do forecasters disagree? An assessment of German growth and inflation forecast dispersion," International Journal of Forecasting, Elsevier, vol. 22(1), pages 125-135.
    2. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, The Center for Economic Research.
    3. Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
    4. Reto Cueni & Bruno S. Frey, 2014. "Forecasts and Reactivity," CREMA Working Paper Series 2014-10, Center for Research in Economics, Management and the Arts (CREMA).
    5. Wolfgang Nierhaus, 2013. "Konjunkturprognosen heute – Möglichkeiten und Probleme," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(01), pages 25-32, January.
    6. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, The Center for Economic Research.
    7. Heilemann Ullrich, 2004. "Besser geht’s nicht – Genauigkeitsgrenzen von Konjunkturprognosen / As Good as it Gets – Limits of Accuracy of Macroeconomic Short Term Forecasts," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(1-2), pages 51-64, February.

  20. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2009. "Can the Fed Predict the State of the Economy?," Working Papers 2009-001, The George Washington University, The Center for Economic Research, revised Mar 2010.

    Cited by:

    1. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    2. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Central banks’ inflation forecasts under asymmetric loss: Evidence from four Latin-American countries," Economics Letters, Elsevier, vol. 129(C), pages 66-70.
    3. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    4. 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.
    5. Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
    6. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    7. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
    8. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    9. Eicher, Theo S. & Kawai, Reina, 2024. "Systemic bias of IMF reserve and debt forecasts for program countries," International Journal of Forecasting, Elsevier, vol. 40(3), pages 985-1001.
    10. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    11. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    12. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    13. Michael T. Belongia & Peter N. Ireland, 2018. "Monetary Policy Lessons from the Greenbook," Boston College Working Papers in Economics 955, Boston College Department of Economics.
    14. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2024. "The bias of the ECB inflation projections: A State-dependent analysis," Bank of Finland Research Discussion Papers 4/2024, Bank of Finland.
    15. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    16. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.
    17. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.
    18. Pao‐Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2021. "Do Fed Forecast Errors Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 686-712, June.
    19. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
    20. Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2025. "The Bias of the ECB Inflation Projections: A State‐Dependent Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(3), pages 922-940, April.
    21. Constantin Bürgi & Tara M. Sinclair, 2020. "What Does Forecaster Disagreement Tell Us about the State of the Economy?," Working Papers 2020-001, The George Washington University, The Center for Economic Research.
    22. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    23. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
    24. Henning Fischer & Marta García-Bárzana & Peter Tillmann & Peter Winker, 2012. "Evaluating FOMC forecast ranges: an interval data approach," MAGKS Papers on Economics 201213, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    25. Julia Estefania‐Flores & Davide Furceri & Siddharth Kothari & Jonathan D. Ostry, 2023. "Worse than you think: Public debt forecast errors in advanced and developing economies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 685-714, April.
    26. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    27. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    28. Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2017. "What's the Story? A New Perspective on the Value of Economic Forecasts," Finance and Economics Discussion Series 2017-107, Board of Governors of the Federal Reserve System (U.S.).
    29. 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.
    30. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
    31. 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.
    32. 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.
    33. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    34. 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.
    35. Eicher, Theo S. & Kawai, Reina, 2023. "IMF trade forecasts for crisis countries: Bias, inefficiency, and their origins," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1615-1639.
    36. Fatemi, Ali & Fooladi, Iraj & Zhao, Yonggan & Ma, Zongming, 2024. "On the superior performance of SRI funds," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 567-581.
    37. 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.
    38. Eunkyu Seong & Seojeong Lee, 2025. "Are the Bank of Korea's Inflation Forecasts Biased Toward the Target?," Papers 2512.16068, arXiv.org.
    39. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.
    40. Baghestani, Hamid & AbuAl-Foul, Bassam M., 2017. "Comparing Federal Reserve, Blue Chip, and time series forecasts of US output growth," Journal of Economics and Business, Elsevier, vol. 89(C), pages 47-56.
    41. Christopher A. Hollrah & Steven A. Sharpe & Nitish R. Sinha, 2020. "The Power of Narratives in Economic Forecasts," Finance and Economics Discussion Series 2020-001, Board of Governors of the Federal Reserve System (U.S.).
    42. Rossi, Barbara & Sekhposyan, Tatevik, 2016. "Forecast Rationality Tests in the Presence of Instabilities, With Applications to Federal Reserve and Survey Forecasts," CEPR Discussion Papers 11391, C.E.P.R. Discussion Papers.
    43. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.
    44. 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.
    45. Clintin P. Davis-Stober & David V. Budescu & Stephen B. Broomell & Jason Dana, 2015. "The Composition of Optimally Wise Crowds," Decision Analysis, INFORMS, vol. 12(3), pages 130-143.
    46. Eicher, Theo S. & Rollinson, Yuan Gao, 2023. "The accuracy of IMF crises nowcasts," International Journal of Forecasting, Elsevier, vol. 39(1), pages 431-449.

  21. Tara Sinclair & H.O. Stekler & Elizabeth Reid & Edward N. Gamber, 2009. "Jointly Evaluating GDP and Inflation Forcasts in the Context of the Taylor Rule," Working Papers 2008-05, The George Washington University, Institute for International Economic Policy.

    Cited by:

    1. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.

  22. Bryan L. Boulier & Herman O. Stekler & Jason Coburn & Timothy Rankins, 2009. "Evaluating National Football League Draft Choices: The Passing Game," Working Papers 2009-003, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Geoffrey N Tuck & Shane A Richards, 2019. "Risk equivalence as an alternative to balancing mean value when trading draft selections and players in major sporting leagues," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-15, May.
    2. Jemuel Chandrakumaran & Mark Stewart & Preety Srivastava, 2023. "Valuing Australian football league draft picks," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-24, October.
    3. René Böheim & Mario Lackner, 2011. "Returns to Education in Professional Football," Economics working papers 2011-02, Department of Economics, Johannes Kepler University Linz, Austria.
    4. Kendall Weir & Stephen Wu, 2014. "Criminal Records and the Labor Market for Professional Athletes," Journal of Sports Economics, , vol. 15(6), pages 617-635, December.
    5. Craig, J. Dean & Winchester, Niven, 2021. "Predicting the national football league potential of college quarterbacks," European Journal of Operational Research, Elsevier, vol. 295(2), pages 733-743.
    6. W. David Allen, 2015. "The Demand for Younger and Older Workers," Journal of Sports Economics, , vol. 16(2), pages 127-158, February.
    7. Dennis Coates & Babatunde Oguntimein, 2008. "The Length and Success of NBA Careers: Does College Production Predict Professional Outcomes?," Working Papers 0806, International Association of Sports Economists;North American Association of Sports Economists.

  23. Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Štrumbelj, Erik & Vračar, Petar, 2012. "Simulating a basketball match with a homogeneous Markov model and forecasting the outcome," International Journal of Forecasting, Elsevier, vol. 28(2), pages 532-542.
    2. Peeters, Thomas, 2018. "Testing the Wisdom of Crowds in the field: Transfermarkt valuations and international soccer results," International Journal of Forecasting, Elsevier, vol. 34(1), pages 17-29.
    3. Jörg Döpke & Tim Köhler & Lars Tegtmeier, 2024. "Are they worth it? – An evaluation of predictions for NBA ‘Fantasy Sports’," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(1), pages 142-165, March.
    4. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
    5. Vittorio Maniezzo & Fabian Andres Aspee Encina, 2022. "Predictive Analytics for Real-time Auction Bidding Support: a Case on Fantasy Football," SN Operations Research Forum, Springer, vol. 3(3), pages 1-23, September.
    6. 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.
    7. June Buchanan & Yun Shen, 2021. "Gambling and marketing: a systematic literature review using HistCite," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(2), pages 2837-2851, June.
    8. Carl Singleton & J. James Reade & Alsdair Brown, 2018. "Going with your Gut: The (In)accuracy of Forecast Revisions in a Football Score Prediction Game," Working Papers 2018-006, The George Washington University, The Center for Economic Research.
    9. Alexis Direr, 2013. "Are betting markets efficient? Evidence from European Football Championships," Applied Economics, Taylor & Francis Journals, vol. 45(3), pages 343-356, January.
    10. Vaughan Williams Leighton & Liu Chunping & Dixon Lerato & Gerrard Hannah, 2021. "How well do Elo-based ratings predict professional tennis matches?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 91-105, June.
    11. Schlembach, Christoph & Schmidt, Sascha L. & Schreyer, Dominik & Wunderlich, Linus, 2022. "Forecasting the Olympic medal distribution – A socioeconomic machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Vincenzo Candila & Antonio Scognamillo, 2019. "On the Longshot Bias in Tennis Betting Markets: The Casco Normalization," Working Papers 3_236, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    13. Christoph Schlembach & Sascha L. Schmidt & Dominik Schreyer & Linus Wunderlich, 2020. "Forecasting the Olympic medal distribution during a pandemic: a socio-economic machine learning model," Papers 2012.04378, arXiv.org, revised Jun 2021.
    14. Kovalchik, Stephanie & Reid, Machar, 2019. "A calibration method with dynamic updates for within-match forecasting of wins in tennis," International Journal of Forecasting, Elsevier, vol. 35(2), pages 756-766.
    15. Hubáček, Ondřej & Šourek, Gustav & Železný, Filip, 2019. "Exploiting sports-betting market using machine learning," International Journal of Forecasting, Elsevier, vol. 35(2), pages 783-796.
    16. Baker, Rose D. & McHale, Ian G., 2013. "Forecasting exact scores in National Football League games," International Journal of Forecasting, Elsevier, vol. 29(1), pages 122-130.
    17. Li, Yongjun & Wang, Lizheng & Li, Feng, 2021. "A data-driven prediction approach for sports team performance and its application to National Basketball Association," Omega, Elsevier, vol. 98(C).
    18. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
    19. Coussement, Kristof & De Bock, Koen W., 2013. "Customer churn prediction in the online gambling industry: The beneficial effect of ensemble learning," Journal of Business Research, Elsevier, vol. 66(9), pages 1629-1636.
    20. Manner Hans, 2016. "Modeling and forecasting the outcomes of NBA basketball games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 31-41, March.
    21. Erik Å trumbelj, 2016. "A Comment on the Bias of Probabilities Derived From Betting Odds and Their Use in Measuring Outcome Uncertainty," Journal of Sports Economics, , vol. 17(1), pages 12-26, January.
    22. Hubáček, Ondřej & Šír, Gustav, 2023. "Beating the market with a bad predictive model," International Journal of Forecasting, Elsevier, vol. 39(2), pages 691-719.
    23. Jeon, Gyuhyeon & Park, Juyong, 2021. "Characterizing patterns of scoring and ties in competitive sports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    24. Song, Kai & Shi, Jian, 2020. "A gamma process based in-play prediction model for National Basketball Association games," European Journal of Operational Research, Elsevier, vol. 283(2), pages 706-713.
    25. B. Jay Coleman, 2014. "Minimum violations and predictive meta‐rankings for college football," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(1), pages 17-33, February.
    26. Delen, Dursun & Cogdell, Douglas & Kasap, Nihat, 2012. "A comparative analysis of data mining methods in predicting NCAA bowl outcomes," International Journal of Forecasting, Elsevier, vol. 28(2), pages 543-552.

  24. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2008. "Are 'unbiased' forecasts really unbiased? Another look at the Fed forecasts," Working Papers 2008-010, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Theo S. Eicher & David J. Kuenzel & Mr. Chris Papageorgiou & Mr. Charalambos Christofides, 2018. "Forecasts in Times of Crises," IMF Working Papers 2018/048, International Monetary Fund.

  25. ChiUng Song & Bryan L. Boulier & Herman O. Stekler, 2008. "Measuring Consensus in Binary Forecasts: NFL Game Predictions," Working Papers 2008-006, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.

  26. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, The Center for Economic Research.

    Cited by:

    1. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, The Center for Economic Research, revised Feb 2012.
    2. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina & Wolters, Maik H., 2017. "Deutsche Konjunktur im Herbst 2017 - Deutsche Wirtschaft nähert sich der Hochkonjunktur [German Economy Autumn 2017 - German economy approaches boom period]," Kieler Konjunkturberichte 35, Kiel Institute for the World Economy.
    3. Dovern, Jonas & Jannsen, Nils, 2017. "Systematische Prognosefehler in unterschiedlichen Konjunkturphasen," Kiel Insight 2017.15, Kiel Institute for the World Economy.
    4. 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.
    5. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, The Center for Economic Research.

  27. Tara M. Sinclair & Edward N. Gamber & H.O. Stekler & Elizabeth Reid, 2008. "Jointly Evaluating the Federal Reserve’s Forecasts of GDP Growth and Inflation," Working Papers 2008-002, The George Washington University, The Center for Economic Research, revised Mar 2011.

    Cited by:

    1. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    2. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Michael T. Belongia & Peter N. Ireland, 2018. "Monetary Policy Lessons from the Greenbook," Boston College Working Papers in Economics 955, Boston College Department of Economics.
    4. Pao‐Lin Tien & Tara M. Sinclair & Edward N. Gamber, 2021. "Do Fed Forecast Errors Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 686-712, June.
    5. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    6. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    7. Sinclair, Tara M. & Stekler, H.O. & Carnow, Warren, 2015. "Evaluating a vector of the Fed’s forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 157-164.
    8. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
    9. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    10. Zisimos Koustas & Jean-Francois Lamarche, 2009. "Instrumental variable estimation of a nonlinear Taylor rule," Working Papers 0909, Brock University, Department of Economics, revised Jul 2010.

  28. Kajal Lahiri & Herman O. Stekler & Wenxiong Yao & Peg Young, 2003. "Monthly Output Index for the U.S. Transportation Sector," Discussion Papers 03-12, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Lahiri, Kajal & Yao, Vincent Wenxiong, 2006. "Economic indicators for the US transportation sector," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(10), pages 872-887, December.
    2. Lahiri, Kajal & Yao, Wenxiong, 2004. "A dynamic factor model of the coincident indicators for the US transportation sector," MPRA Paper 22360, University Library of Munich, Germany.
    3. Kajal Lahiri, Wenxiong Yao, and Peg Young, 2003. "Cycles in the Transportation Sector and the Aggregate Economy," Discussion Papers 03-14, University at Albany, SUNY, Department of Economics.
    4. Yao, Vincent W. & Sloboda, Brian W., 2005. "Forecasting Cycles in the Transportation Sector," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 44(2).
    5. Kajal Lahiri & Wenxiong Yao, 2004. "The predictive power of an experimental transportation output index," Applied Economics Letters, Taylor & Francis Journals, vol. 11(3), pages 149-152.
    6. Yetkiner, Hakan & Beyzatlar, Mehmet Aldonat, 2020. "The Granger-causality between wealth and transportation: A panel data approach," Transport Policy, Elsevier, vol. 97(C), pages 19-25.
    7. Yao, Vincent W. & Solboda, Brian, 2005. "Forecasting Cycles in the Transportation Sector," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208159, Transportation Research Forum.
    8. Jason Angelopoulos, 2017. "Creating and assessing composite indicators: Dynamic applications for the port industry and seaborne trade," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 126-159, March.
    9. Roumen Vesselinov, 2012. "New Composite Indicators for Bulgarian Business Cycle," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 5(2), pages 101-111, August.
    10. Wanyu Yang & Xuebing Ouyang & Tiezhu Li, 2023. "Research on the Regional Transport Development Index and Its Application in Decision Making and Sustainable Development of Transport Services: A Case Study in Yunnan Province, China," Sustainability, MDPI, vol. 15(3), pages 1-16, January.

Articles

  1. 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.
    See citations under working paper version above.
  2. Goodwin, Paul & Önkal, Dilek & Stekler, Herman O., 2018. "What if you are not Bayesian? The consequences for decisions involving risk," European Journal of Operational Research, Elsevier, vol. 266(1), pages 238-246.
    See citations under working paper version above.
  3. Gabriel Mathy & Herman Stekler, 2018. "Was the deflation of the depression anticipated? An inference using real-time data," Journal of Economic Methodology, Taylor & Francis Journals, vol. 25(2), pages 117-125, April.
    See citations under working paper version above.
  4. Mathy, Gabriel & Stekler, Herman, 2017. "Expectations and forecasting during the Great Depression: Real-time evidence from the business press," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 1-15.
    See citations under working paper version above.
  5. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.

    Cited by:

    1. Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.

  6. Herman O. Stekler & Tianyu Ye, 2017. "Evaluating a leading indicator: an application—the term spread," Empirical Economics, Springer, vol. 53(1), pages 183-194, August.
    See citations under working paper version above.
  7. Stekler, Herman & Symington, Hilary, 2016. "Evaluating qualitative forecasts: The FOMC minutes, 2006–2010," International Journal of Forecasting, Elsevier, vol. 32(2), pages 559-570.

    Cited by:

    1. Tadle, Raul Cruz, 2022. "FOMC minutes sentiments and their impact on financial markets," Journal of Economics and Business, Elsevier, vol. 118(C).
    2. 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.
    3. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    5. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.
    6. Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    7. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.
    8. Anastasiou, Dimitris & Krokida, Styliani-Iris & Tsouknidis, Dimitris & Drakos, Konstantinos, 2023. "Can the tone of central bankers’ speeches discourage potential bank borrowers in the Eurozone?," Journal of International Money and Finance, Elsevier, vol. 139(C).
    9. Emma Catalfamo, 2018. "French Nowcasts of the US Economy during the Great Recession: A Textual Analysis," Working Papers 2018-001, The George Washington University, The Center for Economic Research.
    10. 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.
    11. S. Yanki Kalfa & Jaime Marquez, 2021. "Forecasting FOMC Forecasts," Econometrics, MDPI, vol. 9(3), pages 1-21, September.
    12. Eugster, Patrick & Uhl, Matthias W., 2024. "Forecasting inflation using sentiment," Economics Letters, Elsevier, vol. 236(C).
    13. Hendry, David F., 2018. "Deciding between alternative approaches in macroeconomics," International Journal of Forecasting, Elsevier, vol. 34(1), pages 119-135.
    14. Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
    15. Ricardo Correa & Keshav Garud & Juan M. Londono & Nathan Mislang, 2017. "Sentiment in Central Banks' Financial Stability Reports," International Finance Discussion Papers 1203, Board of Governors of the Federal Reserve System (U.S.).
    16. Huang, Yu-Lieh & Kuan, Chung-Ming, 2021. "Economic prediction with the FOMC minutes: An application of text mining," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 751-761.
    17. Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020. "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers 2042, Banco de España.
    18. 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.).
    19. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
    20. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
    21. Jennifer Castle & David Hendry, 2016. "Policy Analysis, Forediction, and Forecast Failure," Economics Series Working Papers 809, University of Oxford, Department of Economics.
    22. Wonseong Kim & Christina Niklaus & Choong Lyol Lee & Siegfried Handschuh, 2025. "DisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts," Papers 2501.04959, arXiv.org, revised Mar 2026.
    23. Rambaccussing, Dooruj & Kwiatkowski, Andrzej, 2020. "Forecasting with news sentiment: Evidence with UK newspapers," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1501-1516.
    24. 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.
    25. Stijn Claessens & Ricardo Correa & Juan M. Londono, 2021. "Financial Stability Governance and Central Bank Communications," International Finance Discussion Papers 1328, Board of Governors of the Federal Reserve System (U.S.).
    26. Domenico Lombardi, Pierre Siklos, Samantha St. Amand, 2018. "Asset Price Spillovers From Unconventional Monetary Policy: A Global Empirical Perspective," LCERPA Working Papers 0109, Laurier Centre for Economic Research and Policy Analysis, revised 30 Jan 2018.
    27. Aromi, J. Daniel, 2020. "Linking words in economic discourse: Implications for macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1517-1530.
    28. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    29. 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.
    30. Jennifer L. Castle & David F. Hendry & Andrew B. Martinez, 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance," Econometrics, MDPI, vol. 5(3), pages 1-27, September.
    31. Maria Elvira Mancino & Simona Sanfelici, 2020. "Identifying financial instability conditions using high frequency data," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 221-242, January.
    32. Gu, Chen & Chen, Denghui & Stan, Raluca & Shen, Aizhong, 2022. "It is not just What you say, but How you say it: Why tonality matters in central bank communication," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 216-231.
    33. Foltas, Alexander, 2024. "Inefficient forecast narratives: A BERT-based approach," Working Papers 45, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    34. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    35. 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.
    36. Ruman, Asif M., 2023. "A Comparative Textual Study of FOMC Transcripts Through Inflation Peaks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 87(C).
    37. Gabriel Mathy & Christian Roatta, 2018. "Forecasting the 1937-1938 Recession: Quantifying Contemporary Newspaper Forecasts," Working Papers 2018-004, The George Washington University, The Center for Economic Research.
    38. Gabriel Mathy & Herman O. Stekler, 2017. "Was the Deflation of the Depression Anticipated? An Inference Using Real-time Data," Working Papers 2017-004, The George Washington University, The Center for Economic Research.
    39. Mathy, Gabriel & Stekler, Herman, 2017. "Expectations and forecasting during the Great Depression: Real-time evidence from the business press," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 1-15.
    40. 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.
    41. Reid, Monique & Siklos, Pierre & Plessis, Stan Du, 2021. "What drives household inflation expectations in South Africa? Demographics and anchoring under inflation targeting," Economic Systems, Elsevier, vol. 45(3).
    42. Dooruj Rambaccussing & Andrzej Kwiatkowski, 2024. "The nexus between national and regional reporting of economic news: Evidence from the United Kingdom and Scotland," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 371-393, April.

  8. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
    See citations under working paper version above.
  9. Sinclair, Tara M. & Stekler, H.O. & Carnow, Warren, 2015. "Evaluating a vector of the Fed’s forecasts," International Journal of Forecasting, Elsevier, vol. 31(1), pages 157-164.
    See citations under working paper version above.
  10. Hutson, Mark & Joutz, Fred & Stekler, Herman, 2014. "Interpreting and evaluating CESIfo's World Economic Survey directional forecasts," Economic Modelling, Elsevier, vol. 38(C), pages 6-11.

    Cited by:

    1. Tsuchiya, Yoichi, 2016. "Do production managers predict turning points? A directional analysis," Economic Modelling, Elsevier, vol. 58(C), pages 1-8.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    6. 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.
    7. Behrens, Christoph & Pierdzioch, Christian & Risse, Marian, 2018. "Testing the optimality of inflation forecasts under flexible loss with random forests," Economic Modelling, Elsevier, vol. 72(C), pages 270-277.
    8. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88, October.
    9. Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," CESifo Working Paper Series 7691, CESifo.
    10. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2017. "Forecasting GDP all over the World: Evidence from Comprehensive Survey Data," MPRA Paper 81772, University Library of Munich, Germany.
    11. Boumans Dorine & Garnitz Johanna, 2017. "Ifo World Economic Survey Database – An International Economic Expert Survey," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 71-80, February.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    13. 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.
    14. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    15. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.

  11. Herman O Stekler & Raj M Talwar, 2013. "Forecasting the Downturn of the Great Recession," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 48(2), pages 113-120, April.

    Cited by:

    1. Stekler, Herman & Symington, Hilary, 2016. "Evaluating qualitative forecasts: The FOMC minutes, 2006–2010," International Journal of Forecasting, Elsevier, vol. 32(2), pages 559-570.
    2. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
    3. 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.
    4. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, The Center for Economic Research.

  12. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    See citations under working paper version above.
  13. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.
    See citations under working paper version above.
  14. H.O. Stekler & Huixia Zhang, 2013. "An evaluation of Chinese economic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(4), pages 251-259, November.

    Cited by:

    1. 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.
    2. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
    3. Tsuchiya, Yoichi, 2016. "Asymmetric loss and rationality of Chinese renminbi forecasts: An implication for the trade between China and the US," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 116-127.
    4. Shiqun Li & Baosheng Zhang, 2016. "Research of Coalbed Methane Development Well-Type Optimization Method Based on Unit Technical Cost," Sustainability, MDPI, vol. 8(9), pages 1-12, August.
    5. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.

  15. Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.

    Cited by:

    1. Christian Pierdzioch, 2023. "A bootstrap test of the time-varying efficiency of German growth forecasts," Economics Bulletin, AccessEcon, vol. 43(1), pages 679-687.
    2. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    3. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. 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).
    5. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.
    6. Foltas, Alexander & Pierdzioch, Christian, 2020. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Working Papers 22, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    7. 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.
    8. 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.
    9. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, The Center for Economic Research.
    10. 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.
    11. Mihaela Simionescu, 2015. "The Accuracy Analysis of Inflation Rate Forecasts in Euro Area," Global Economic Observer, "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences;Institute for World Economy of the Romanian Academy, vol. 3(1), pages 80-85, May.
    12. Tim Köhler & Jörg Döpke, 2023. "Will the last be the first? Ranking German macroeconomic forecasters based on different criteria," Empirical Economics, Springer, vol. 64(2), pages 797-832, February.
    13. Strunz, Franziska & Gödl, Maximilian, 2023. "An Evaluation of Professional Forecasts for the German Economy," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277707, Verein für Socialpolitik / German Economic Association.
    14. Hans Christian Müller-Dröge & Tara M. Sinclair & Herman O. Stekler, 2014. "Evaluating Forecasts Of A Vector Of Variables: A German Forecasting Competition," Working Papers 2014-004, The George Washington University, The Center for Economic Research.
    15. 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.
    16. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    17. Mihaela SIMIONESCU, 2014. "Improving The Inflation Rate Forecasts Of Romanian Experts Using A Fixed-Effects Models Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 13, pages 87-102, June.
    18. Simionescu Mihaela, 2015. "Kalman Filter or VAR Models to Predict Unemployment Rate in Romania?," Naše gospodarstvo/Our economy, Sciendo, vol. 61(3), pages 3-21, June.
    19. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    20. Wolfgang Nierhaus, 2014. "Wirtschaftskonjunktur 2013: Prognose und Wirklichkeit," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(02), pages 41-46, January.
    21. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.
    22. 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.
    23. Lehmann Robert & Wollmershäuser Timo, 2020. "The macroeconomic projections of the German government: A comparison to an independent forecasting institution," German Economic Review, De Gruyter, vol. 21(2), pages 235-270, June.
    24. Tim Köhler, 2025. "Do the Sentiments of Forecasters Help Predict Recessions? Evidence from Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 21(2), pages 185-212, December.
    25. Heilemann Ullrich, 2015. "Literaturbeitrag / Review Paper. Macroeconometric Models – From “Little Science” to “Big Science”," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(1), pages 82-89, February.
    26. Mihaela Simionescu, 2015. "A Comparative Analysis Of Macroeconomic Forecasts Accuracy In Spain And Romania," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 6(1), pages 67-74.

  16. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    See citations under working paper version above.
  17. Kathryn Lundquist & Herman O Stekler, 2012. "Interpreting the Performance of Business Economists During the Great Recession," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 47(2), pages 148-154, April.

    Cited by:

    1. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.
    2. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.
    3. Mick van Rooijen & Dorinth W. van Dijk & Jasper M. de Winter, 2025. "Designing a Nowcasting Model for GDP Growth: A Practical Approach," De Economist, Springer, vol. 173(4), pages 665-704, December.
    4. Stekler, Herman & Symington, Hilary, 2016. "Evaluating qualitative forecasts: The FOMC minutes, 2006–2010," International Journal of Forecasting, Elsevier, vol. 32(2), pages 559-570.
    5. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
    6. Amrendra Pandey & Jagadish Shettigar & Amarnath Bose, 2021. "Evaluation of the Inflation Forecasting Process of the Reserve Bank of India: A Text Analysis Approach," SAGE Open, , vol. 11(3), pages 21582440211, July.
    7. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
    8. 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.
    9. Gabriel Mathy & Herman O. Stekler, 2016. "Expectations and Forecasting during the Great Depression: Real-Time Evidence from the Business Press," Working Papers 2016-011, The George Washington University, The Center for Economic Research.
    10. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    11. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    12. Gabriel Mathy & Herman O. Stekler, 2017. "Was the Deflation of the Depression Anticipated? An Inference Using Real-time Data," Working Papers 2017-004, The George Washington University, The Center for Economic Research.
    13. Ulrich Fritsche & Johannes Puckelwald, 2018. "Deciphering Professional Forecasters’ Stories - Analyzing a Corpus of Textual Predictions for the German Economy," Macroeconomics and Finance Series 201804, University of Hamburg, Department of Socioeconomics.
    14. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, The Center for Economic Research.

  18. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    See citations under working paper version above.
  19. Stekler Herman O. & Klein Andrew, 2012. "Predicting the Outcomes of NCAA Basketball Championship Games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-10, March.
    See citations under working paper version above.
  20. Sinclair, Tara M. & Joutz, Fred & Stekler, H.O., 2010. "Can the Fed predict the state of the economy?," Economics Letters, Elsevier, vol. 108(1), pages 28-32, July.
    See citations under working paper version above.
  21. Boulier, Bryan L. & Stekler, H.O. & Coburn, Jason & Rankins, Timothy, 2010. "Evaluating National Football League draft choices: The passing game," International Journal of Forecasting, Elsevier, vol. 26(3), pages 589-605, July.
    See citations under working paper version above.
  22. Tara Sinclair & H. O. Stekler & L. Kitzinger, 2010. "Directional forecasts of GDP and inflation: a joint evaluation with an application to Federal Reserve predictions," Applied Economics, Taylor & Francis Journals, vol. 42(18), pages 2289-2297.

    Cited by:

    1. Pierdzioch, Christian & Rülke, Jan-Christoph, 2015. "On the directional accuracy of forecasts of emerging market exchange rates," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 369-376.
    2. Tsuchiya, Yoichi, 2013. "Do corporate executives have accurate predictions for the economy? A directional analysis," Economic Modelling, Elsevier, vol. 30(C), pages 167-174.
    3. Hamid Baghestani, 2011. "A directional analysis of Federal Reserve predictions of growth in unit labor costs and productivity," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(3), pages 303-311.
    4. Hamid Baghestani, 2016. "Interest rate movements and US consumers’ inflation forecast errors: is there a link?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(3), pages 623-630, July.
    5. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    6. Baghestani, Hamid & Toledo, Hugo, 2017. "Do analysts' forecasts of term spread differential help predict directional change in exchange rates?," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 62-69.
    7. Tsuchiya, Yoichi, 2016. "Do production managers predict turning points? A directional analysis," Economic Modelling, Elsevier, vol. 58(C), pages 1-8.
    8. 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).
    9. Thitithep Sitthiyot & Kanyarat Holasut, 2024. "A simple method for joint evaluation of skill in directional forecasts of multiple variables," Papers 2402.01142, arXiv.org.
    10. Tsuchiya, Yoichi, 2013. "Are government and IMF forecasts useful? An application of a new market-timing test," Economics Letters, Elsevier, vol. 118(1), pages 118-120.
    11. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    12. Hamid Baghestani & Mohammad Arzaghi & Ilker Kaya, 2015. "On the accuracy of Blue Chip forecasts of interest rates and country risk premiums," Applied Economics, Taylor & Francis Journals, vol. 47(2), pages 113-122, January.
    13. Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).
    14. 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.
    15. Gamber, Edward N. & Smith, Julie K. & McNamara, Dylan C., 2014. "Where is the Fed in the distribution of forecasters?," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 296-312.
    16. Hamid Baghestani & Ilker Kaya & Samer Kherfi, 2013. "Do changes in consumers' home buying attitudes predict directional change in home sales?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(5), pages 411-415, March.
    17. IIZUKA Nobuo, 2013. "Predicting Business Cycle Phases by Professional Forecasters－ Are They Useful ?," ESRI Discussion paper series 305, Economic and Social Research Institute (ESRI).
    18. Y. Tsuchiya, 2014. "Are consumer sentiments useful in Japan? An application of a new market-timing test," Applied Economics Letters, Taylor & Francis Journals, vol. 21(5), pages 356-359, March.
    19. Baghestani, Hamid, 2015. "Predicting gasoline prices using Michigan survey data," Energy Economics, Elsevier, vol. 50(C), pages 27-32.
    20. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.
    21. 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.
    22. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    23. Hamid Baghestani, 2014. "On the loss structure of federal reserve forecasts of output growth," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(3), pages 518-527, July.
    24. Baris Soybilgen & Ege Yazgan, 2016. "An Evaluation Of Inflation Expectations In Turkey," Working Papers 1601, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    25. Hamid Baghestani & Bassam M. AbuAl-Foul, 2019. "Dynamics between Oil Prices and UAE Effective Exchange Rates: An Empirical Examination," Review of Economics & Finance, Better Advances Press, Canada, vol. 16, pages 89-103, May.
    26. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    27. Mihaela SIMIONESCU, 2015. "The Evaluation of Global Accuracy of Romanian Inflation Rate Predictions Using Mahalanobis Distance," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(1), pages 133-149, March.
    28. Tsuchiya, Yoichi, 2016. "Directional analysis of fiscal sustainability: Revisiting Domar's debt sustainability condition," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 189-201.
    29. Baghestani, Hamid & Chazi, Abdelaziz & Khallaf, Ashraf, 2019. "A directional analysis of oil prices and real exchange rates in BRIC countries," Research in International Business and Finance, Elsevier, vol. 50(C), pages 450-456.
    30. Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data," Working Papers 24/2014, Stellenbosch University, Department of Economics.
    31. Hamid Baghestani & Jorg Bley, 2020. "Do directional predictions of US gasoline prices reveal asymmetries?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 348-360, April.
    32. Baghestani, Hamid & Toledo, Hugo, 2019. "Oil prices and real exchange rates in the NAFTA region," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 253-264.
    33. Hamid Baghestani & Liliana Danila, 2014. "Interest Rate and Exchange Rate Forecasting in the Czech Republic: Do Analysts Know Better than a Random Walk?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 282-295, September.
    34. Anusha, "undated". "Evaluating reliability of some symmetric and asymmetric univariate filters," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-030, Indira Gandhi Institute of Development Research, Mumbai, India.
    35. Y. Tsuchiya, 2014. "A directional evaluation of corporate executives' exchange rate forecasts," Applied Economics, Taylor & Francis Journals, vol. 46(1), pages 95-101, January.
    36. Yoichi Tsuchiya, 2012. "Is the Purchasing Managers' Index useful for assessing the economy's strength? A directional analysis," Economics Bulletin, AccessEcon, vol. 32(2), pages 1302-1311.
    37. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.
    38. Hamid Baghestani & Paul Williams, 2017. "Does customer satisfaction have directional predictability for U.S. discretionary spending?," Applied Economics, Taylor & Francis Journals, vol. 49(54), pages 5504-5511, November.
    39. Baghestani, Hamid & AbuAl-Foul, Bassam M., 2017. "Comparing Federal Reserve, Blue Chip, and time series forecasts of US output growth," Journal of Economics and Business, Elsevier, vol. 89(C), pages 47-56.
    40. Hamid Baghestani, 2013. "Evaluating Federal Reserve predictions of growth in consumer spending," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1637-1646, May.
    41. Hamid Baghestani, 2017. "Do US consumer survey data help beat the random walk in forecasting mortgage rates?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343017-134, January.
    42. Baghestani, Hamid, 2021. "Predicting growth in US durables spending using consumer durables-buying attitudes," Journal of Business Research, Elsevier, vol. 131(C), pages 327-336.
    43. Hamid Baghestani & Cassia Marchon, 2015. "On the accuracy of private forecasts of inflation and growth in Brazil," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 370-381, April.

  23. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
    See citations under working paper version above.
  24. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2009. "Measuring consensus in binary forecasts: NFL game predictions," International Journal of Forecasting, Elsevier, vol. 25(1), pages 182-191.
    See citations under working paper version above.
  25. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.

    Cited by:

    1. 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.
    2. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    3. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    4. Xiao, Jinzhi & Lence, Sergio H. & Hart, Chad E., 2015. "Do analysts forecast the ending stocks or the USDA forecasts?," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205759, Agricultural and Applied Economics Association.
    5. Paul Hubert, 2015. "Revisiting the greenbook's relative forecasting performance," Post-Print hal-01087522, HAL.
    6. Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2025. "Testing the efficiency of oil price forecast revisions in times of COVID-19 and the Russia–Ukraine conflict," Journal of Commodity Markets, Elsevier, vol. 40(C).
    7. 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.
    8. 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.
    9. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    10. Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, University of Hamburg, Department of Socioeconomics.
    11. Paul Hubert, 2010. "Monetary policy, imperfect information and the expectations channel [Politique monétaire,information imparfaite et canal des anticipations]," Sciences Po Economics Publications (main) tel-04095385, HAL.
    12. Granziera, Eleonora & Jalasjoki, Pirkka & Paloviita, Maritta, 2024. "The bias of the ECB inflation projections: A State-dependent analysis," Bank of Finland Research Discussion Papers 4/2024, Bank of Finland.
    13. Dean Croushore & Simon van Norden, 2017. "Fiscal Surprises at the FOMC," CIRANO Working Papers 2017s-09, CIRANO.
    14. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
    15. 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.
    16. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.
    17. Strunz, Franziska & Gödl, Maximilian, 2023. "An Evaluation of Professional Forecasts for the German Economy," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277707, Verein für Socialpolitik / German Economic Association.
    18. Eleonora Granziera & Pirkka Jalasjoki & Maritta Paloviita, 2025. "The Bias of the ECB Inflation Projections: A State‐Dependent Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(3), pages 922-940, April.
    19. Silvija Vlah Jerić & Mihovil Anđelinović, 2019. "Evaluating Croatian stock index forecasts," Empirical Economics, Springer, vol. 56(4), pages 1325-1339, April.
    20. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
    21. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    22. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    23. 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.
    24. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    25. Kajal Lahiri, 2012. "Comment on "Forecast Rationality Tests Based on Multi-Horizon Bounds" by Andrew Patton and Allan Timmermann. Journal of Business and Economic Statistics, No. 1, Vol. 30, 2012, pp.1-17," Discussion Papers 12-10, University at Albany, SUNY, Department of Economics.
    26. Hans Christian Müller-Dröge & Tara M. Sinclair & Herman O. Stekler, 2014. "Evaluating Forecasts Of A Vector Of Variables: A German Forecasting Competition," Working Papers 2014-004, The George Washington University, The Center for Economic Research.
    27. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    28. Eleni Argiri & Stephen G. Hall & Angeliki Momtsia & Daphne Marina Papadopoulou & Ifigeneia Skotida & George S. Tavlas & Yongli Wang, 2024. "An evaluation of the inflation forecasting performance of the European Central Bank, the Federal Reserve, and the Bank of England," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 932-947, July.
    29. Mihaela SIMIONESCU, 2015. "The Evaluation of Global Accuracy of Romanian Inflation Rate Predictions Using Mahalanobis Distance," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(1), pages 133-149, March.
    30. Paul Hubert, 2011. "Do central banks forecast influence private agents ? Forecasting performance vs. signals," Documents de Travail de l'OFCE 2011-20, Observatoire Francais des Conjonctures Economiques (OFCE).
    31. 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.
    32. Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
    33. Lillian R. Gaeto & Sandeep Mazumder, 2019. "Measuring the Accuracy of Federal Reserve Forecasts," Southern Economic Journal, John Wiley & Sons, vol. 85(3), pages 960-984, January.
    34. 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.
    35. 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.
    36. Sheng, Xuguang (Simon), 2015. "Evaluating the economic forecasts of FOMC members," International Journal of Forecasting, Elsevier, vol. 31(1), pages 165-175.
    37. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    38. 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.
    39. 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.
    40. Peter Tillmann, 2011. "Reputation and Forecast Revisions: Evidence from the FOMC," MAGKS Papers on Economics 201128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    41. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, The Center for Economic Research.
    42. Davies, Antony, 2006. "A framework for decomposing shocks and measuring volatilities derived from multi-dimensional panel data of survey forecasts," International Journal of Forecasting, Elsevier, vol. 22(2), pages 373-393.
    43. Binder, Carola Conces & Wetzel, Samantha, 2018. "The FOMC versus the staff, revisited: When do policymakers add value?," Economics Letters, Elsevier, vol. 171(C), pages 72-75.
    44. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    45. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    46. Eunkyu Seong & Seojeong Lee, 2025. "Are the Bank of Korea's Inflation Forecasts Biased Toward the Target?," Papers 2512.16068, arXiv.org.
    47. Deschamps, Bruno & Ioannidis, Christos, 2013. "Can rational stubbornness explain forecast biases?," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 141-151.
    48. Xiao, Jinzhi & Lence, Sergio H. & Hart, Chad, 2014. "Usda And Private Analysts' Forecasts Of Ending Stocks: How Good Are They?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170642, Agricultural and Applied Economics Association.
    49. Jones, Adam T. & Ogden, Richard E., 2017. "A day late and a dollar short: The effect of policy uncertainty on fed forecast errors," Economic Analysis and Policy, Elsevier, vol. 54(C), pages 112-122.
    50. 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.
    51. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.
    52. 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.

  26. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.

    Cited by:

    1. Mihaela Bratu (Simionescu), 2013. "How to Improve the SPF Forecasts?," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(2), pages 153-165, April.
    2. Mihaela Bratu (Simionescu), 2013. "Using The Econometric Approach To Improve The Accuracy Of Gdp Deflator Forecasts," EuroEconomica, Danubius University of Galati, issue 1(32), pages 70-76, May.
    3. Constantin Mitru? & Mihaela Bratu (Simionescu), 2013. "The Indicators’ Inadequacy and the Predictions’ Accuracy," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(4), pages 430-442, August.
    4. Mihaela BRATU SIMIONESCU, 2012. "Two Quantitative Forecasting Methods For Macroeconomic Indicators In Czech Republic," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 3(1), pages 71-87.
    5. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
    6. Junttila, Juha & Korhonen, Marko, 2011. "Utilizing financial market information in forecasting real growth, inflation and real exchange rate," International Review of Economics & Finance, Elsevier, vol. 20(2), pages 281-301, April.
    7. Mihaela BRATU (SIMIONESCU), 2012. "A Strategy To Improve The Gdp Index Forcasts In Romania Using Moving Average Models Of Historical Errors Of The Dobrescu Macromodel," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 128-138, December.
    8. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
    9. Athanassios Petralias & Sotirios Petros & Pródromos Prodromídis, 2013. "Greece in Recession: Economic predictions, mispredictions and policy implications," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 75, Hellenic Observatory, LSE.
    10. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.
    11. María del Carmen Ramos-Herrera & Simón Sosvilla-Rivero, 2017. "Inflation, real economic growth and unemployment expectations: An empirical analysis based on the ECB Survey of Professional Forecasters," Working Papers 17-02, Asociación Española de Economía y Finanzas Internacionales.

  27. Stekler, H.O., 2007. "Significance tests harm progress in forecasting: Comment," International Journal of Forecasting, Elsevier, vol. 23(2), pages 329-330.

    Cited by:

    1. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.

  28. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.

    Cited by:

    1. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    2. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    3. Julia Eichholz & Thorsten Knauer & Sandra Winkelmann, 2023. "Digital Maturity of Forecasting and its Impact in Times of Crisis," Schmalenbach Journal of Business Research, Springer, vol. 75(4), pages 443-481, December.
    4. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey among professional forecasters," Working Papers 2017-002, The George Washington University, The Center for Economic Research.
    5. 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.
    6. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
    7. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    8. Franses, Philip Hans, 2008. "Merging models and experts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 31-33.
    9. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    10. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
    11. Dimitrios Papastamos & Fotis Mouzakis & Simon Stevenson, 2014. "Rationality and Momentum in Real Estate Investment Forecasts," Real Estate & Planning Working Papers rep-wp2014-07, Henley Business School, University of Reading.
    12. Konstantinos Nikolopoulos & Waleed S. Alghassab & Konstantia Litsiou & Stelios Sapountzis, 2019. "Long-Term Economic Forecasting with Structured Analogies and Interaction Groups," Working Papers 19018, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    13. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    14. Abounoori, Abbas Ali & Naderi, Esmaeil & Gandali Alikhani, Nadiya & Amiri, Ashkan, 2013. "Financial Time Series Forecasting by Developing a Hybrid Intelligent System," MPRA Paper 45615, University Library of Munich, Germany.
    15. 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.
    16. Wang, Fangzhi & Liao, Hua, 2022. "Unexpected economic growth and oil price shocks," Energy Economics, Elsevier, vol. 116(C).
    17. Foltas, Alexander, 2025. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," HWWI Working Paper Series 5/2025, Hamburg Institute of International Economics (HWWI).
    18. 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.
    19. José Antonio Gibanel Salazar, 2014. "Economic models: comparative analysis of their adjustment and prediction capacities," Contribuciones a la Economía, Servicios Académicos Intercontinentales SL, issue 2014-05, November.
    20. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey of professional forecasters," Macroeconomics and Finance Series 201701, University of Hamburg, Department of Socioeconomics.
    21. 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.
    22. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    23. Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.
    24. Tzu-Pu CHANG, Ray Yeutien CHOU & Ray Yeutien CHOU, 2018. "Anchoring Effect on Macroeconomic Forecasts : A Heterogeneity Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 134-147, December.
    25. Aikman, David & Barwell, Richard, 2026. "Reactions to the Bernanke Review from Bank of England watchers," International Journal of Forecasting, Elsevier, vol. 42(1), pages 3-12.
    26. Kexin Ding & Ani L. Katchova, 2024. "Testing the optimality of USDA's WASDE forecasts under unknown loss," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 846-865, October.
    27. Coroneo, Laura, 2026. "Forecasting for monetary policy," International Journal of Forecasting, Elsevier, vol. 42(1), pages 22-33.
    28. Franses, Philip Hans & Legerstee, Rianne, 2009. "Properties of expert adjustments on model-based SKU-level forecasts," International Journal of Forecasting, Elsevier, vol. 25(1), pages 35-47.

  29. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2007. "The comparative accuracy of judgmental and model forecasts of American football games," International Journal of Forecasting, Elsevier, vol. 23(3), pages 405-413.

    Cited by:

    1. Valeria Croce & Karl W. Wöber, 2011. "Judgemental Forecasting Support Systems in Tourism," Tourism Economics, , vol. 17(4), pages 709-724, August.
    2. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
    3. Jain, Kriti & Bearden, J. Neil & Filipowicz, Allan, 2013. "Depression and forecast accuracy: Evidence from the 2010 FIFA World Cup," International Journal of Forecasting, Elsevier, vol. 29(1), pages 69-79.
    4. Andreas Heuer & Oliver Rubner, 2014. "Optimizing the Prediction Process: From Statistical Concepts to the Case Study of Soccer," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-9, September.
    5. Strumbelj, E. & Sikonja, M. Robnik, 2010. "Online bookmakers' odds as forecasts: The case of European soccer leagues," International Journal of Forecasting, Elsevier, vol. 26(3), pages 482-488, July.
    6. Hubáček, Ondřej & Šourek, Gustav & Železný, Filip, 2019. "Exploiting sports-betting market using machine learning," International Journal of Forecasting, Elsevier, vol. 35(2), pages 783-796.
    7. Bernardo, Giovanni & Ruberti, Massimo & Verona, Roberto, 2015. "Testing semi-strong efficiency in a fixed odds betting market: Evidence from principal European football leagues," MPRA Paper 66414, University Library of Munich, Germany.
    8. ChiUng Song & Bryan L. Boulier & Herman O. Stekler, 2008. "Measuring Consensus in Binary Forecasts: NFL Game Predictions," Working Papers 2008-006, The George Washington University, The Center for Economic Research.
    9. Bernardo, Giovanni & Ruberti, Massimo & Verona, Roberto, 2019. "Semi-strong inefficiency in the fixed odds betting market: Underestimating the positive impact of head coach replacement in the main European soccer leagues," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 239-246.
    10. Wunderlich, Fabian & Memmert, Daniel, 2020. "Are betting returns a useful measure of accuracy in (sports) forecasting?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 713-722.
    11. Radek Janhuba, 2016. "Do Victories and Losses Matter? Effects of Football on Life Satisfaction," CERGE-EI Working Papers wp579, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    12. Hubáček, Ondřej & Šír, Gustav, 2023. "Beating the market with a bad predictive model," International Journal of Forecasting, Elsevier, vol. 39(2), pages 691-719.
    13. Kyle J. Kain & Trevon D. Logan, 2014. "Are Sports Betting Markets Prediction Markets?," Journal of Sports Economics, , vol. 15(1), pages 45-63, February.
    14. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    15. Jacek P Dmochowski, 2023. "A statistical theory of optimal decision-making in sports betting," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-22, June.
    16. Delen, Dursun & Cogdell, Douglas & Kasap, Nihat, 2012. "A comparative analysis of data mining methods in predicting NCAA bowl outcomes," International Journal of Forecasting, Elsevier, vol. 28(2), pages 543-552.
    17. B. Jay Coleman, 2017. "Team Travel Effects and the College Football Betting Market," Journal of Sports Economics, , vol. 18(4), pages 388-425, May.

  30. Bryan Boulier & H. O. Stekler & Sarah Amundson, 2006. "Testing the efficiency of the National Football League betting market," Applied Economics, Taylor & Francis Journals, vol. 38(3), pages 279-284.

    Cited by:

    1. Michael A. Roach, 2018. "Testing Labor Market Efficiency Across Position Groups in the NFL," Journal of Sports Economics, , vol. 19(8), pages 1093-1121, December.
    2. Johnnie Johnson & Alistair Bruce & Jiejun Yu, 2010. "The ordinal efficiency of betting markets: an exploded logit approach," Applied Economics, Taylor & Francis Journals, vol. 42(29), pages 3703-3709.
    3. Justin L. Davis & Kevin Krieger, 2017. "Preseason bias in the NFL and NBA betting markets," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1204-1212, March.
    4. N. Winchester & R. T. Stefani, 2013. "An innovative approach to National Football League standings using bonus points," Applied Economics, Taylor & Francis Journals, vol. 45(1), pages 123-134, January.
    5. Justin Cox & Adam L. Schwartz & Bonnie F. Van Ness & Robert A. Van Ness, 2021. "The Predictive Power of College Football Spreads: Regular Season Versus Bowl Games," Journal of Sports Economics, , vol. 22(3), pages 251-273, April.
    6. Feess, Eberhard & Müller, Helge & Schumacher, Christoph, 2016. "Estimating risk preferences of bettors with different bet sizes," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1102-1112.
    7. 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.
    8. Steven Caudill, 2009. "OSU and LSU: easy to spell but did they belong? Using the method of paired comparisons to evaluate the BCS rankings and the NCAA football championship game 2007-08," Applied Economics, Taylor & Francis Journals, vol. 41(25), pages 3225-3230.
    9. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
    10. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    11. Justin Davis & Andy Fodor & Luke McElfresh & Kevin Kreiger, 2015. "Exploiting Week 2 Bias in the NFL Betting Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 9(1), pages 53-67.
    12. Richard Borghesi, 2008. "Weather biases in the NFL totals market," Applied Financial Economics, Taylor & Francis Journals, vol. 18(12), pages 947-953.

  31. 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.

    Cited by:

    1. Armstrong, J. Scott, 2007. "Significance Tests Harm Progress in Forecasting," MPRA Paper 81664, University Library of Munich, Germany.
    2. 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.
    3. 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.
    4. 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.
    5. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    6. Chelsey Hill & James Li & Matthew J. Schneider & Martin T. Wells, 2021. "The tensor auto‐regressive model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 636-652, July.
    7. Rombouts, Jeroen & Ternes, Marie & Wilms, Ines, 2025. "Cross-temporal forecast reconciliation at digital platforms with machine learning," International Journal of Forecasting, Elsevier, vol. 41(1), pages 321-344.
    8. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.
    9. 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.
    10. Chiew, Ernest & Choong, Shin Siang, 2022. "A solution for M5 Forecasting - Uncertainty: Hybrid gradient boosting and autoregressive recurrent neural network for quantile estimation," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1442-1447.
    11. 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.
    12. Evangelos Spiliotis & Spyros Makridakis & Artemios-Anargyros Semenoglou & Vassilios Assimakopoulos, 2022. "Comparison of statistical and machine learning methods for daily SKU demand forecasting," Operational Research, Springer, vol. 22(3), pages 3037-3061, July.
    13. Ulrich, Matthias & Jahnke, Hermann & Langrock, Roland & Pesch, Robert & Senge, Robin, 2022. "Classification-based model selection in retail demand forecasting," International Journal of Forecasting, Elsevier, vol. 38(1), pages 209-223.
    14. Vuong, Van-Dai & Nguyen, Luong-Ha & Goulet, James-A., 2025. "Coupling LSTM neural networks and state-space models through analytically tractable inference," International Journal of Forecasting, Elsevier, vol. 41(1), pages 128-140.
    15. Kathryn S Taylor & James W Taylor, 2022. "Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-25, March.
    16. Fotios Petropoulos & Enno Siemsen, 2023. "Forecast Selection and Representativeness," Management Science, INFORMS, vol. 69(5), pages 2672-2690, May.
    17. Wang, Xiaoqian & Kang, Yanfei & Hyndman, Rob J. & Li, Feng, 2023. "Distributed ARIMA models for ultra-long time series," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1163-1184.
    18. Girolimetto, Daniele & Athanasopoulos, George & Di Fonzo, Tommaso & Hyndman, Rob J., 2024. "Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1134-1151.
    19. Kang, Yanfei & Cao, Wei & Petropoulos, Fotios & Li, Feng, 2022. "Forecast with forecasts: Diversity matters," European Journal of Operational Research, Elsevier, vol. 301(1), pages 180-190.
    20. Zhang, Bohan & Panagiotelis, Anastasios & Li, Han, 2025. "Constructing hierarchical time series through clustering: Is there an optimal way for forecasting?," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1022-1036.
    21. 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.
    22. 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.
    23. Svetunkov, Ivan & Chen, Huijing & Boylan, John E., 2023. "A new taxonomy for vector exponential smoothing and its application to seasonal time series," European Journal of Operational Research, Elsevier, vol. 304(3), pages 964-980.
    24. Willem P Sijp & Anastasios Panagiotelis, 2024. "Estimating granular house price distributions in the Australian market using Gaussian mixtures," Papers 2404.05178, arXiv.org.
    25. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
    26. Kourentzes, Nikolaos, 2014. "On intermittent demand model optimisation and selection," International Journal of Production Economics, Elsevier, vol. 156(C), pages 180-190.
    27. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
    28. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
    29. 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.
    30. 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.
    31. Zhang, Bohan & Panagiotelis, Anastasios & Kang, Yanfei, 2024. "Discrete forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 318(1), pages 143-153.
    32. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios & Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "The M5 uncertainty competition: Results, findings and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1365-1385.
    33. Shovon Sengupta & Sunny Kumar Singh & Tanujit Chakraborty, 2025. "Macroeconomic Forecasting for the G7 countries under Uncertainty Shocks," Papers 2510.23347, arXiv.org.
    34. Jeon, Jooyoung & Panagiotelis, Anastasios & Petropoulos, Fotios, 2019. "Probabilistic forecast reconciliation with applications to wind power and electric load," European Journal of Operational Research, Elsevier, vol. 279(2), pages 364-379.
    35. Ortega, Luz C. & Otero, Luis Daniel & Solomon, Mitchell & Otero, Carlos E. & Fabregas, Aldo, 2023. "Deep learning models for visibility forecasting using climatological data," International Journal of Forecasting, Elsevier, vol. 39(2), pages 992-1004.
    36. 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).
    37. 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.
    38. Daniele Girolimetto & Tommaso Di Fonzo, 2024. "Point and probabilistic forecast reconciliation for general linearly constrained multiple time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(2), pages 581-607, April.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. Ord, Keith, 2007. "Comments on "significance tests harm progress in forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 331-332.
    44. 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.
    45. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2023. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Papers 2401.00249, arXiv.org, revised Jul 2024.
    46. Ma, Shaohui & Fildes, Robert, 2021. "Retail sales forecasting with meta-learning," European Journal of Operational Research, Elsevier, vol. 288(1), pages 111-128.
    47. 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.
    48. Taylor, James W. & Taylor, Kathryn S., 2023. "Combining probabilistic forecasts of COVID-19 mortality in the United States," European Journal of Operational Research, Elsevier, vol. 304(1), pages 25-41.
    49. 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.
    50. Donia Besher & Anirban Sengupta & Tanujit Chakraborty, 2025. "Probabilistic Forecasting of Climate Policy Uncertainty: The Role of Macro-financial Variables and Google Search Data," Papers 2507.12276, arXiv.org, revised Jan 2026.
    51. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, Enero-Abr.
    52. Tuominen, Jalmari & Pulkkinen, Eetu & Peltonen, Jaakko & Kanniainen, Juho & Oksala, Niku & Palomäki, Ari & Roine, Antti, 2024. "Forecasting emergency department occupancy with advanced machine learning models and multivariable input," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1410-1420.
    53. Sengupta, Shovon & Chakraborty, Tanujit & Singh, Sunny Kumar, 2025. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," International Journal of Forecasting, Elsevier, vol. 41(3), pages 953-981.
    54. Tanujit Chakraborty & Donia Besher & Madhurima Panja & Shovon Sengupta, 2025. "Neural ARFIMA model for forecasting BRIC exchange rates with long memory under oil shocks and policy uncertainties," Papers 2509.06697, arXiv.org.
    55. 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.
    56. Di Fonzo, Tommaso & Girolimetto, Daniele, 2023. "Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives," International Journal of Forecasting, Elsevier, vol. 39(1), pages 39-57.
    57. 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.
    58. 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.
    59. Di Fonzo, Tommaso & Girolimetto, Daniele, 2024. "Forecast combination-based forecast reconciliation: Insights and extensions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 490-514.
    60. Sarmas, Elissaios & Spiliotis, Evangelos & Stamatopoulos, Efstathios & Marinakis, Vangelis & Doukas, Haris, 2023. "Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models," Renewable Energy, Elsevier, vol. 216(C).
    61. Spiliotis, Evangelos & Makridakis, Spyros & Kaltsounis, Anastasios & Assimakopoulos, Vassilios, 2021. "Product sales probabilistic forecasting: An empirical evaluation using the M5 competition data," International Journal of Production Economics, Elsevier, vol. 240(C).
    62. Abolghasemi, Mahdi & Girolimetto, Daniele & Di Fonzo, Tommaso, 2025. "Improving cross-temporal forecasts reconciliation accuracy and utility in energy market," Applied Energy, Elsevier, vol. 394(C).
    63. 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.
    64. 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.
    65. Davide Provenzano & Serena Volo, 2022. "Tourism recovery amid COVID-19: The case of Lombardy, Italy," Tourism Economics, , vol. 28(1), pages 110-130, February.
    66. 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.
    67. Stekler, H.O., 2007. "Significance tests harm progress in forecasting: Comment," International Journal of Forecasting, Elsevier, vol. 23(2), pages 329-330.
    68. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.
    69. 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.

  32. Robert Goldfarb & H. O. Stekler & Joel David, 2005. "Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(4), pages 517-542.

    Cited by:

    1. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.
    2. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    3. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.
    5. Emma Catalfamo, 2018. "French Nowcasts of the US Economy during the Great Recession: A Textual Analysis," Working Papers 2018-001, The George Washington University, The Center for Economic Research.
    6. Stekler, Herman & Symington, Hilary, 2016. "Evaluating qualitative forecasts: The FOMC minutes, 2006–2010," International Journal of Forecasting, Elsevier, vol. 32(2), pages 559-570.
    7. Kathryn Lundquist & H.O. Stekler, 2011. "The Forecasting Performance of Business Economists During the Great Recession," Working Papers 2011-004, The George Washington University, The Center for Economic Research.
    8. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
    9. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    10. Gabriel Mathy & Herman O. Stekler, 2016. "Expectations and Forecasting during the Great Depression: Real-Time Evidence from the Business Press," Working Papers 2016-011, The George Washington University, The Center for Economic Research.
    11. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    12. 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.
    13. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, The Center for Economic Research.
    14. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    15. Gabriel Mathy & Christian Roatta, 2018. "Forecasting the 1937-1938 Recession: Quantifying Contemporary Newspaper Forecasts," Working Papers 2018-004, The George Washington University, The Center for Economic Research.
    16. Gabriel Mathy & Herman O. Stekler, 2017. "Was the Deflation of the Depression Anticipated? An Inference Using Real-time Data," Working Papers 2017-004, The George Washington University, The Center for Economic Research.
    17. Gabriel Mathy & Yongchen Zhao, 2025. "Could Diffusion Indexes Have Forecasted the Great Depression?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 320-338, March.
    18. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, The Center for Economic Research.
    19. Nakilcioğlu, Emin & Rizvanolli, Anisa & Rendel, Olaf, 2022. "Workload forecasting of a logistic node using Bayesian neural networks," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 237-264, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    20. Green, Kesten C. & Armstrong, J. Scott, 2007. "Structured analogies for forecasting," International Journal of Forecasting, Elsevier, vol. 23(3), pages 365-376.
    21. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.

  33. Stekler, H. O. & Petrei, G., 2003. "Diagnostics for evaluating the value and rationality of economic forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 735-742.

    Cited by:

    1. Eva A. Arnold, 2013. "The role of data revisions and disagreement in professional forecasts," NBP Working Papers 153, Narodowy Bank Polski.
    2. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.
    3. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.

  34. Boulier, Bryan L. & Stekler, H. O., 2003. "Predicting the outcomes of National Football League games," International Journal of Forecasting, Elsevier, vol. 19(2), pages 257-270.

    Cited by:

    1. Barajas, Angel & Fernández-Jardón, Carlos & Crolley, Liz, 2005. "Does sports performance influence revenues and economic results in Spanish football?," MPRA Paper 3234, University Library of Munich, Germany.
    2. 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.
    3. Andersson, Patric & Edman, Jan & Ekman, Mattias, 2005. "Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts," International Journal of Forecasting, Elsevier, vol. 21(3), pages 565-576.
    4. Yiwen Xu & Ying Wang & Yang Yang, 2024. "The Impact of Air Pollution on Game Outcome," Journal of Sports Economics, , vol. 25(5), pages 557-582, June.
    5. Vittorio Maniezzo & Fabian Andres Aspee Encina, 2022. "Predictive Analytics for Real-time Auction Bidding Support: a Case on Fantasy Football," SN Operations Research Forum, Springer, vol. 3(3), pages 1-23, September.
    6. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
    7. Claudio Boido & Mauro Aliano & Giuseppe Galloppo, 2023. "Top-flight European football teams and stock returns: market reactions to sporting events," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(4), pages 1041-1061, December.
    8. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
    9. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2007. "The comparative accuracy of judgmental and model forecasts of American football games," International Journal of Forecasting, Elsevier, vol. 23(3), pages 405-413.
    10. Alessandro Innocenti & Tommaso Nannicini & Roberto Ricciuti, 2012. "The Importance of Betting Early," Labsi Experimental Economics Laboratory University of Siena 037, University of Siena.
    11. Forrest, David & Sanz, Ismael & Tena, J.D., 2010. "Forecasting national team medal totals at the Summer Olympic Games," International Journal of Forecasting, Elsevier, vol. 26(3), pages 576-588, July.
    12. Simmons, Rob, 2004. "The analysis of sports forecasting: Modeling parallels between sports gambling and financial markets: William S. Mallios, Kluwer Academic Publishers, Boston & Dordrecht, 2000, 312 pages, ISBN 0-7923-7713-3, $138.50," International Journal of Forecasting, Elsevier, vol. 20(1), pages 149-150.
    13. Pascal Courty & Jeffrey Cisyk, 2024. "Sports injuries and game stakes: Concussions in the National Football League," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 430-448, January.
    14. Carlos Sáenz-Royo, 2017. "A plausible Decision Heuristics Model: Fallibility of human judgment as an endogenous problem," Working Papers 2017/04, Economics Department, Universitat Jaume I, Castellón (Spain).
    15. Ruud H. Koning & Ian G. McHale, 2012. "Estimating Match and World Cup Winning Probabilities," Chapters, in: Wolfgang Maennig & Andrew Zimbalist (ed.), International Handbook on the Economics of Mega Sporting Events, chapter 11, Edward Elgar Publishing.
    16. Egon Franck & Erwin Verbeek & Stephan Nüesch, 2008. "Prediction Accuracy of Different Market Structures – Bookmakers versus a Betting Exchange," Working Papers 0096, University of Zurich, Institute for Strategy and Business Economics (ISU), revised 2009.
    17. Justin Cox & Adam L. Schwartz & Bonnie F. Van Ness & Robert A. Van Ness, 2021. "The Predictive Power of College Football Spreads: Regular Season Versus Bowl Games," Journal of Sports Economics, , vol. 22(3), pages 251-273, April.
    18. Oberstone Joel, 2009. "Differentiating the Top English Premier League Football Clubs from the Rest of the Pack: Identifying the Keys to Success," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-29, July.
    19. Baker, Rose D. & McHale, Ian G., 2013. "Forecasting exact scores in National Football League games," International Journal of Forecasting, Elsevier, vol. 29(1), pages 122-130.
    20. Yu, Dian & Gao, Jianjun & Wang, Tongyao, 2022. "Betting market equilibrium with heterogeneous beliefs: A prospect theory-based model," European Journal of Operational Research, Elsevier, vol. 298(1), pages 137-151.
    21. 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.
    22. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    23. Barajas, Angel, 2004. "Modelo de valoración de clubes de fútbol basado en los factores clave de su negocio [Valuation model for football clubs based on the key factors of their business]," MPRA Paper 13158, University Library of Munich, Germany.
    24. Sperb, Luis Felipe Costa & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2019. "Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 35(1), pages 321-335.
    25. Herman O. Stekler, 2007. "Sports Forecasting," Working Papers 2007-001, The George Washington University, The Center for Economic Research, revised Jan 2007.
    26. West Brady T & Lamsal Madhur, 2008. "A New Application of Linear Modeling in the Prediction of College Football Bowl Outcomes and the Development of Team Ratings," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(3), pages 1-21, July.
    27. Nancy Ammon Jianakoplos & Martin Shields, 2012. "Practice or Profits," Journal of Sports Economics, , vol. 13(4), pages 451-465, August.
    28. Joshua D. Pitts, 2016. "Determinants of Success in the National Football League’s Postseason," Journal of Sports Economics, , vol. 17(1), pages 86-111, January.
    29. Bryan Boulier & H. O. Stekler & Sarah Amundson, 2006. "Testing the efficiency of the National Football League betting market," Applied Economics, Taylor & Francis Journals, vol. 38(3), pages 279-284.
    30. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    31. Niven Winchester & Raymond T. Stefani, 2009. "An innovative approach to National Football League standings using optimal bonus points," Working Papers 0905, University of Otago, Department of Economics, revised Jun 2009.
    32. Matthew Gentzkow & Jesse Shapiro, 2005. "Media Bias and Reputation," NBER Working Papers 11664, National Bureau of Economic Research, Inc.
    33. Fentaw Abegaz & Ernst Wit, 2015. "Copula Gaussian graphical models with penalized ascent Monte Carlo EM algorithm," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(4), pages 419-441, November.
    34. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    35. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    36. Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, vol. 25(4), pages 760-772, October.
    37. Andersson, Patric & Ekman, Mattias & Edman, Jan, 2003. "Forecasting the fast and frugal way: A study of performance and information-processing strategies of experts and non-experts when predicting the World Cup 2002 in soccer," SSE/EFI Working Paper Series in Business Administration 2003:9, Stockholm School of Economics.

  35. Stekler, H. O., 2003. "Improving our ability to predict the unusual event," International Journal of Forecasting, Elsevier, vol. 19(2), pages 161-163.

    Cited by:

    1. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    2. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Cheong Kin Wan & Jen Sim Ho, 2022. "Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting," JRFM, MDPI, vol. 15(7), pages 1-47, June.
    3. Robert Goldfarb & H. O. Stekler & Joel David, 2005. "Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(4), pages 517-542.

  36. Robert S. Goldfarb & H. O. Stekler, 2002. "Wheat from Chaff: Meta-Analysis as Quantitative Literature Review: Comment," Journal of Economic Perspectives, American Economic Association, vol. 16(3), pages 225-226, Summer.

    Cited by:

    1. Sebastian Gechert & Henner Will, 2012. "Fiscal Multipliers: A Meta Regression Analysis," IMK Working Paper 97-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    2. Jon Nelson & Peter Kennedy, 2009. "The Use (and Abuse) of Meta-Analysis in Environmental and Natural Resource Economics: An Assessment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 345-377, March.
    3. Sebastian Gechert, 2013. "What fiscal policy is most effective? A Meta Regression Analysis," IMK Working Paper 117-2013, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.

  37. Fildes, Robert & Stekler, Herman, 2002. "Reply to the comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 503-505, December.

    Cited by:

    1. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
    2. Hamid Baghestani, 2011. "A directional analysis of Federal Reserve predictions of growth in unit labor costs and productivity," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(3), pages 303-311.
    3. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    4. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    5. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, The Center for Economic Research.
    6. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    7. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.
    8. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    9. Anqiang Huang & Kin Keung Lai & Han Qiao & Shouyang Wang & Zhenji Zhang, 2018. "Does Interval Knowledge Sharpen Forecasting Models? Evidence from China’s Typical Ports," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 467-483, March.
    10. Hagenhoff, Tim & Lustenhouwer, Joep, 2023. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    11. Nicholas Taylor, 2014. "Economic forecast quality: information timeliness and data vintage effects," Empirical Economics, Springer, vol. 46(1), pages 145-174, February.
    12. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    13. Anqiang Huang & Han Qiao & Shouyang Wang & John Liu, 2016. "Improving Forecasting Performance by Exploiting Expert Knowledge: Evidence from Guangzhou Port," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 387-401, March.
    14. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ growth forecasts: an evaluation," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    15. Rickard Nyman & Paul Ormerod, 2017. "Predicting Economic Recessions Using Machine Learning Algorithms," Papers 1701.01428, arXiv.org.
    16. 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).
    17. Guillaume Chevillon, 2007. "Direct Multi‐Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    18. Franses, Ph.H.B.F., 2003. "Do we make better forecasts these days? A survey amongst academics," Econometric Institute Research Papers EI 2003-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Chevillon, Guillaume & Hendry, David F., 2005. "Non-parametric direct multi-step estimation for forecasting economic processes," International Journal of Forecasting, Elsevier, vol. 21(2), pages 201-218.
    20. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    21. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.
    22. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey among professional forecasters," Working Papers 2017-002, The George Washington University, The Center for Economic Research.
    23. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
    24. Philip Hans Franses, 2004. "Do We Think We Make Better Forecasts Than in the Past? A Survey of Academics," Interfaces, INFORMS, vol. 34(6), pages 466-468, December.
    25. 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.
    26. David Tucket & Antoine Mandel & Diana Mangalagiu & Allen Abramson & Jochen Hinkel & Konstantinos Katsikopoulos & Alan Kirman & Thierry Malleret & Igor Mozetic & Paul Ormerod & Robert Elliot Smith & To, 2015. "Uncertainty, Decision Science, and Policy Making: A Manifesto for a Research Agenda," PSE-Ecole d'économie de Paris (Postprint) hal-02057279, HAL.
    27. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    28. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    29. Hector M. Zarate-Solano & Daniel R. Zapata-Sanabria, 2017. "Clustering and forecasting inflation expectations using the World Economic Survey: the case of the 2014 oil price shock on inflation targeting countries," Borradores de Economia 993, Banco de la Republica de Colombia.
    30. Bahman Rostami-Tabar & Mohammad M Ali & Tao Hong & Rob J Hyndman & Michael D Porter & Aris Syntetos, 2020. "Forecasting for Social Good," Monash Econometrics and Business Statistics Working Papers 37/20, Monash University, Department of Econometrics and Business Statistics.
    31. 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.
    32. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2008. "Are 'unbiased' forecasts really unbiased? Another look at the Fed forecasts," Working Papers 2008-010, The George Washington University, The Center for Economic Research.
    33. Pedersen, Michael, 2025. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," International Journal of Forecasting, Elsevier, vol. 41(2), pages 475-486.
    34. Rickard Nyman & Paul Ormerod, 2020. "Understanding the Great Recession Using Machine Learning Algorithms," Papers 2001.02115, arXiv.org.
    35. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    36. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.
    37. 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.
    38. Brandt, Patrick T. & Freeman, John R. & Schrodt, Philip A., 2014. "Evaluating forecasts of political conflict dynamics," International Journal of Forecasting, Elsevier, vol. 30(4), pages 944-962.
    39. 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.
    40. Higgins, Matthew L. & Mishra, Sagarika, 2014. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Economic Modelling, Elsevier, vol. 38(C), pages 627-632.
    41. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
    42. Krkoska, Libor & Teksoz, Utku, 2009. "How reliable are forecasts of GDP growth and inflation for countries with limited coverage?," Economic Systems, Elsevier, vol. 33(4), pages 376-388, December.
    43. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    44. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.
    45. Schmidt, Torsten & Vosen, Simeon, 2012. "Using Internet Data to Account for Special Events in Economic Forecasting," Ruhr Economic Papers 382, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    46. Kieran Mc Morrow & Werner Roeger & Valerie Vandermeulen, 2017. "Evaluating Medium Term Forecasting Methods and their Implications for EU Output Gap Calculations," European Economy - Discussion Papers 070, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    47. Gerit Vogt, 2009. "Konjunkturprognose in Deutschland. Ein Beitrag zur Prognose der gesamtwirtschaftlichen Entwicklung auf Bundes- und Länderebene," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 36, October.
    48. Andrew Crawley & Adam Daigneault & Jonathan Gendron, 2025. "Maine's Forestry and Logging Industry: Building a Model for Forecasting," Papers 2503.06087, arXiv.org.
    49. Alper Saricioglu & Mujde Erol Genevois & Michele Cedolin, 2025. "Impact of COVID-19 on The Bullwhip Effect Across U.S. Industries," Papers 2506.06368, arXiv.org.
    50. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    51. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    52. Gultekin Isiklar & Kajal Lahiri & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross‐country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725, September.
    53. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    54. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    55. Giovanni Cicceri & Giuseppe Inserra & Michele Limosani, 2020. "A Machine Learning Approach to Forecast Economic Recessions—An Italian Case Study," Mathematics, MDPI, vol. 8(2), pages 1-20, February.
    56. Gabriel Mathy & Herman O. Stekler, 2016. "Expectations and Forecasting during the Great Depression: Real-Time Evidence from the Business Press," Working Papers 2016-011, The George Washington University, The Center for Economic Research.
    57. Foltas, Alexander, 2025. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," HWWI Working Paper Series 5/2025, Hamburg Institute of International Economics (HWWI).
    58. Krkoska, Libor & Teksoz, Utku, 2007. "Accuracy of GDP growth forecasts for transition countries: Ten years of forecasting assessed," International Journal of Forecasting, Elsevier, vol. 23(1), pages 29-45.
    59. Natalia Shmatko & Alina Lavrynenko & Dirk Meissner, 2017. "Communicating Company Innovation Culture: Assessment Through Job Advertisements Analysis," HSE Working papers WP BRP 74/STI/2017, National Research University Higher School of Economics.
    60. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, The Center for Economic Research.
    61. Manu Sharma & Vinish Kathuria, 2025. "Macroeconomic Nowcasting: What can Central Banks Learn from a Structured Literature Review?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 23(2), pages 333-388, June.
    62. 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.
    63. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    64. Christopher F. Baum & John Barkoulas, 2006. "Long-memory forecasting of US monetary indices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(4), pages 291-302.
    65. Jakab M., Zoltán & Kovács, Mihály András & Kiss, Gergely, 2006. "Mit tanultunk?. A jegybanki előrejelzések szerepe az inflációs cél követésének első öt évében Magyarországon [What are we studying?. The role of central-bank forecasts in Hungarian inflation targeting]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1101-1134.
    66. Singleton, Carl & Reade, J. James & Brown, Alasdair, 2020. "Going with your gut: The (In)accuracy of forecast revisions in a football score prediction game," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    67. 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.
    68. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    69. H.O. Stekler & Huixia Zhang, 2013. "An evaluation of Chinese economic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(4), pages 251-259, November.
    70. Heilemann, Ullrich & Stekler, H. O., 2003. "Has the accuracy of German macroeconomic forecasts improved?," Technical Reports 2003,31, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    71. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey of professional forecasters," Macroeconomics and Finance Series 201701, University of Hamburg, Department of Socioeconomics.
    72. 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.
    73. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Working Papers 0686, University of Heidelberg, Department of Economics.
    74. Robert Goldfarb & H. O. Stekler & Joel David, 2005. "Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(4), pages 517-542.
    75. Ashiya, Masahiro, 2007. "Forecast accuracy of the Japanese government: Its year-ahead GDP forecast is too optimistic," Japan and the World Economy, Elsevier, vol. 19(1), pages 68-85, January.
    76. 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.
    77. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    78. Tsuchiya, Yoichi, 2012. "Evaluating Japanese corporate executives’ forecasts under an asymmetric loss function," Economics Letters, Elsevier, vol. 116(3), pages 601-603.
    79. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," BERG Working Paper Series 163, Bamberg University, Bamberg Economic Research Group.
    80. Vincze, János & Bíró, Anikó & Elek, Péter, 2007. "Szimulációk és érzékenységvizsgálatok a magyar gazdaság egy középméretű makromodelljével [Simulations and sensitivity analyses with a medium-sized macro model of the Hungarian economy]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 774-799.
    81. Robert Ewing & David Gruen & John Hawkins, 2005. "Forecasting the macro economy," Economic Roundup, The Treasury, Australian Government, issue 2, pages 11-25, June.
    82. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
    83. Tim Köhler, 2025. "Do the Sentiments of Forecasters Help Predict Recessions? Evidence from Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 21(2), pages 185-212, December.
    84. Constantinou Anthony Costa & Fenton Norman Elliott, 2012. "Solving the Problem of Inadequate Scoring Rules for Assessing Probabilistic Football Forecast Models," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-14, March.
    85. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    86. 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.
    87. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
    88. Coroneo, Laura, 2026. "Forecasting for monetary policy," International Journal of Forecasting, Elsevier, vol. 42(1), pages 22-33.
    89. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
    90. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.
    91. Fomin, M., 2016. "Business cycles and acquisition policy: Analysis of M&A deals of metallurgical companies," Working Papers 6441, Graduate School of Management, St. Petersburg State University.
    92. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
    93. 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.
    94. María del Carmen Ramos-Herrera & Simón Sosvilla-Rivero, 2017. "Inflation, real economic growth and unemployment expectations: An empirical analysis based on the ECB Survey of Professional Forecasters," Working Papers 17-02, Asociación Española de Economía y Finanzas Internacionales.

  38. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.

    Cited by:

    1. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2015. "Robust approaches to forecasting," International Journal of Forecasting, Elsevier, vol. 31(1), pages 99-112.
    2. Hamid Baghestani, 2011. "A directional analysis of Federal Reserve predictions of growth in unit labor costs and productivity," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(3), pages 303-311.
    3. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    4. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
    5. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, The Center for Economic Research.
    6. Céspedes, Luis Felipe & Jalil, Munir A., 2006. "Comments," LSE Research Online Documents on Economics 123188, London School of Economics and Political Science, LSE Library.
    7. Foltas, Alexander, 2023. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," Working Papers 44, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    8. Jacob T. Jones & Tara M. Sinclair & Herman O. Stekler, 2018. "A Textual Analysis of the Bank of England Growth Forecasts," Working Papers 2018-005, The George Washington University, The Center for Economic Research, revised May 2019.
    9. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    10. Anqiang Huang & Kin Keung Lai & Han Qiao & Shouyang Wang & Zhenji Zhang, 2018. "Does Interval Knowledge Sharpen Forecasting Models? Evidence from China’s Typical Ports," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 467-483, March.
    11. Hagenhoff, Tim & Lustenhouwer, Joep, 2023. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    12. Nicholas Taylor, 2014. "Economic forecast quality: information timeliness and data vintage effects," Empirical Economics, Springer, vol. 46(1), pages 145-174, February.
    13. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    14. David Hendry & Guillaume Chevillon, 2004. "Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes," Economics Series Working Papers 196, University of Oxford, Department of Economics.
    15. Anqiang Huang & Han Qiao & Shouyang Wang & John Liu, 2016. "Improving Forecasting Performance by Exploiting Expert Knowledge: Evidence from Guangzhou Port," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 387-401, March.
    16. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ growth forecasts: an evaluation," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    17. Michael Pedersen, 2024. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," Papers 2404.04105, arXiv.org.
    18. Rickard Nyman & Paul Ormerod, 2017. "Predicting Economic Recessions Using Machine Learning Algorithms," Papers 1701.01428, arXiv.org.
    19. 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).
    20. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, The Center for Economic Research, revised Feb 2012.
    21. Guillaume Chevillon, 2007. "Direct Multi‐Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    22. Franses, Ph.H.B.F., 2003. "Do we make better forecasts these days? A survey amongst academics," Econometric Institute Research Papers EI 2003-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    24. Kovacs Kevin & Boulier Bryan & Stekler Herman, 2017. "Nowcasting: Identifying German Cyclical Turning Points," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(4), pages 329-341, August.
    25. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey among professional forecasters," Working Papers 2017-002, The George Washington University, The Center for Economic Research.
    26. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
    27. Philip Hans Franses, 2004. "Do We Think We Make Better Forecasts Than in the Past? A Survey of Academics," Interfaces, INFORMS, vol. 34(6), pages 466-468, December.
    28. 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.
    29. David Tucket & Antoine Mandel & Diana Mangalagiu & Allen Abramson & Jochen Hinkel & Konstantinos Katsikopoulos & Alan Kirman & Thierry Malleret & Igor Mozetic & Paul Ormerod & Robert Elliot Smith & To, 2015. "Uncertainty, Decision Science, and Policy Making: A Manifesto for a Research Agenda," PSE-Ecole d'économie de Paris (Postprint) hal-02057279, HAL.
    30. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    31. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    32. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
    33. Hector M. Zarate-Solano & Daniel R. Zapata-Sanabria, 2017. "Clustering and forecasting inflation expectations using the World Economic Survey: the case of the 2014 oil price shock on inflation targeting countries," Borradores de Economia 993, Banco de la Republica de Colombia.
    34. Bahman Rostami-Tabar & Mohammad M Ali & Tao Hong & Rob J Hyndman & Michael D Porter & Aris Syntetos, 2020. "Forecasting for Social Good," Monash Econometrics and Business Statistics Working Papers 37/20, Monash University, Department of Econometrics and Business Statistics.
    35. Joerg Doepke & Ulrich Fritsche & Boriss Siliverstovs, 2009. "Evaluating German business cycle forecasts under an asymmetric loss function," KOF Working papers 09-237, KOF Swiss Economic Institute, ETH Zurich.
    36. 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.
    37. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2008. "Are 'unbiased' forecasts really unbiased? Another look at the Fed forecasts," Working Papers 2008-010, The George Washington University, The Center for Economic Research.
    38. Esa Mangeloja, 2003. "Structural testing of Business Cycles," Macroeconomics 0308004, University Library of Munich, Germany.
    39. Rickard Nyman & Paul Ormerod, 2020. "Understanding the Great Recession Using Machine Learning Algorithms," Papers 2001.02115, arXiv.org.
    40. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    41. Drechsel, Katja & Giesen, Sebastian & Lindner, Axel, 2014. "Outperforming IMF Forecasts by the Use of Leading Indicators," IWH Discussion Papers 4/2014, Halle Institute for Economic Research (IWH).
    42. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.
    43. 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.
    44. Brandt, Patrick T. & Freeman, John R. & Schrodt, Philip A., 2014. "Evaluating forecasts of political conflict dynamics," International Journal of Forecasting, Elsevier, vol. 30(4), pages 944-962.
    45. 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.
    46. Higgins, Matthew L. & Mishra, Sagarika, 2014. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Economic Modelling, Elsevier, vol. 38(C), pages 627-632.
    47. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
    48. John Barkoulas & Christopher F. Baum, 2003. "Long-Memory Forecasting of U.S. Monetary Indices," Boston College Working Papers in Economics 558, Boston College Department of Economics.
    49. Krkoska, Libor & Teksoz, Utku, 2009. "How reliable are forecasts of GDP growth and inflation for countries with limited coverage?," Economic Systems, Elsevier, vol. 33(4), pages 376-388, December.
    50. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    51. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.
    52. Schmidt, Torsten & Vosen, Simeon, 2012. "Using Internet Data to Account for Special Events in Economic Forecasting," Ruhr Economic Papers 382, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    53. Kieran Mc Morrow & Werner Roeger & Valerie Vandermeulen, 2017. "Evaluating Medium Term Forecasting Methods and their Implications for EU Output Gap Calculations," European Economy - Discussion Papers 070, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    54. Gerit Vogt, 2009. "Konjunkturprognose in Deutschland. Ein Beitrag zur Prognose der gesamtwirtschaftlichen Entwicklung auf Bundes- und Länderebene," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 36, October.
    55. Andrew Crawley & Adam Daigneault & Jonathan Gendron, 2025. "Maine's Forestry and Logging Industry: Building a Model for Forecasting," Papers 2503.06087, arXiv.org.
    56. Alper Saricioglu & Mujde Erol Genevois & Michele Cedolin, 2025. "Impact of COVID-19 on The Bullwhip Effect Across U.S. Industries," Papers 2506.06368, arXiv.org.
    57. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    58. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    59. Gultekin Isiklar & Kajal Lahiri & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross‐country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725, September.
    60. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    61. Friedrich Fritzer & Gabriel Moser & Johann Scharler, 2002. "Forecasting Austrian HICP and its Components using VAR and ARIMA Models," Working Papers 73, Oesterreichische Nationalbank (Austrian Central Bank).
    62. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    63. Giovanni Cicceri & Giuseppe Inserra & Michele Limosani, 2020. "A Machine Learning Approach to Forecast Economic Recessions—An Italian Case Study," Mathematics, MDPI, vol. 8(2), pages 1-20, February.
    64. Gabriel Mathy & Herman O. Stekler, 2016. "Expectations and Forecasting during the Great Depression: Real-Time Evidence from the Business Press," Working Papers 2016-011, The George Washington University, The Center for Economic Research.
    65. Foltas, Alexander, 2025. "Quantifying priorities in business cycle reports: Analysis of recurring textual patterns around peaks and troughs," HWWI Working Paper Series 5/2025, Hamburg Institute of International Economics (HWWI).
    66. Krkoska, Libor & Teksoz, Utku, 2007. "Accuracy of GDP growth forecasts for transition countries: Ten years of forecasting assessed," International Journal of Forecasting, Elsevier, vol. 23(1), pages 29-45.
    67. Natalia Shmatko & Alina Lavrynenko & Dirk Meissner, 2017. "Communicating Company Innovation Culture: Assessment Through Job Advertisements Analysis," HSE Working papers WP BRP 74/STI/2017, National Research University Higher School of Economics.
    68. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, The Center for Economic Research.
    69. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, The Center for Economic Research.
    70. Manu Sharma & Vinish Kathuria, 2025. "Macroeconomic Nowcasting: What can Central Banks Learn from a Structured Literature Review?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 23(2), pages 333-388, June.
    71. Foltas, Alexander, 2024. "Inefficient forecast narratives: A BERT-based approach," Working Papers 45, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    72. 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.
    73. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    74. Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
    75. Jan Babecky & Jiri Podpiera, 2008. "Inflation Forecasts Errors in the Czech Republic: Evidence from a Panel of Institutions," Occasional Publications - Chapters in Edited Volumes, in: Katerina Smidkova (ed.), Evaluation of the Fulfilment of the CNB's Inflation Targets 1998-2007, chapter 6, pages 77-85, Czech National Bank, Research and Statistics Department.
    76. Jakab M., Zoltán & Kovács, Mihály András & Kiss, Gergely, 2006. "Mit tanultunk?. A jegybanki előrejelzések szerepe az inflációs cél követésének első öt évében Magyarországon [What are we studying?. The role of central-bank forecasts in Hungarian inflation targeting]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1101-1134.
    77. Singleton, Carl & Reade, J. James & Brown, Alasdair, 2020. "Going with your gut: The (In)accuracy of forecast revisions in a football score prediction game," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    78. 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.
    79. Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.
    80. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    81. H.O. Stekler & Huixia Zhang, 2013. "An evaluation of Chinese economic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(4), pages 251-259, November.
    82. Jörg Döpke & Ulrich Fritsche & Gabi Waldhof, 2017. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey of professional forecasters," Macroeconomics and Finance Series 201701, University of Hamburg, Department of Socioeconomics.
    83. Jordi Pons-Novell, 2006. "An analysis of a panel of Spanish GDP forecasts," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1287-1292.
    84. 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.
    85. 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.
    86. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Working Papers 0686, University of Heidelberg, Department of Economics.
    87. Robert Goldfarb & H. O. Stekler & Joel David, 2005. "Methodological issues in forecasting: Insights from the egregious business forecast errors of late 1930," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(4), pages 517-542.
    88. Heinisch, Katja, 2024. "Step by step - A quarterly evaluation of EU Commission's GDP forecasts," IWH Discussion Papers 22/2024, Halle Institute for Economic Research (IWH).
    89. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, The Center for Economic Research.
    90. Barot, Bharat, 2007. "Empirical Studies in Consumption, House Prices and the Accuracy of European Growth and Inflation Forecasts," Working Papers 98, National Institute of Economic Research.
    91. Ashiya, Masahiro, 2007. "Forecast accuracy of the Japanese government: Its year-ahead GDP forecast is too optimistic," Japan and the World Economy, Elsevier, vol. 19(1), pages 68-85, January.
    92. 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.
    93. Paul Gallimore & Pat McAllister, 2005. "The Production and Consumption of Commercial Real Estate Market Forecasts," Real Estate & Planning Working Papers rep-wp2005-06, Henley Business School, University of Reading.
    94. Öller, Lars-Erik & Barot, Bharat, 2000. "The Accuracy of European Growth and Inflation Forecasts," Working Papers 72, National Institute of Economic Research.
    95. Paul Gallimore & Patrick McAllister, 2004. "Expert judgement in the Processes of Commercial Property Market Forecasting," Real Estate & Planning Working Papers rep-wp2004-11, Henley Business School, University of Reading.
    96. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    97. Tsuchiya, Yoichi, 2012. "Evaluating Japanese corporate executives’ forecasts under an asymmetric loss function," Economics Letters, Elsevier, vol. 116(3), pages 601-603.
    98. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," BERG Working Paper Series 163, Bamberg University, Bamberg Economic Research Group.
    99. Clements, Michael P, 2006. "Internal consistency of survey respondents.forecasts : Evidence based on the Survey of Professional Forecasters," The Warwick Economics Research Paper Series (TWERPS) 772, University of Warwick, Department of Economics.
    100. Vincze, János & Bíró, Anikó & Elek, Péter, 2007. "Szimulációk és érzékenységvizsgálatok a magyar gazdaság egy középméretű makromodelljével [Simulations and sensitivity analyses with a medium-sized macro model of the Hungarian economy]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 774-799.
    101. Robert Ewing & David Gruen & John Hawkins, 2005. "Forecasting the macro economy," Economic Roundup, The Treasury, Australian Government, issue 2, pages 11-25, June.
    102. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.
    103. Tim Köhler, 2025. "Do the Sentiments of Forecasters Help Predict Recessions? Evidence from Germany," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 21(2), pages 185-212, December.
    104. Constantinou Anthony Costa & Fenton Norman Elliott, 2012. "Solving the Problem of Inadequate Scoring Rules for Assessing Probabilistic Football Forecast Models," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-14, March.
    105. Jef Vuchelen & Maria-Isabel Gutierrez, 2005. "Do the OECD 24 month horizon growth forecasts for the G7-countries contain information?," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 855-862.
    106. Huiwen Lai & Eric C. Y. Ng, 2020. "On business cycle forecasting," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-26, December.
    107. 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.
    108. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
    109. Coroneo, Laura, 2026. "Forecasting for monetary policy," International Journal of Forecasting, Elsevier, vol. 42(1), pages 22-33.
    110. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
    111. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.
    112. Heilemann Ullrich, 2004. "Besser geht’s nicht – Genauigkeitsgrenzen von Konjunkturprognosen / As Good as it Gets – Limits of Accuracy of Macroeconomic Short Term Forecasts," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(1-2), pages 51-64, February.
    113. Fomin, M., 2016. "Business cycles and acquisition policy: Analysis of M&A deals of metallurgical companies," Working Papers 6441, Graduate School of Management, St. Petersburg State University.
    114. Kunst, Robert M., 2003. "Testing for Relative Predictive Accuracy: A Critical Viewpoint," Economics Series 130, Institute for Advanced Studies.
    115. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
    116. 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.
    117. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.
    118. María del Carmen Ramos-Herrera & Simón Sosvilla-Rivero, 2017. "Inflation, real economic growth and unemployment expectations: An empirical analysis based on the ECB Survey of Professional Forecasters," Working Papers 17-02, Asociación Española de Economía y Finanzas Internacionales.

  39. Robert S. Goldfarb & H. O. Stekler, 2001. "Combining the Results of rationality Studies: What Did We know and When Did We know It?," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 36(1), pages 269-300, January.

    Cited by:

    1. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    2. Stekler, H.O., 2007. "Significance tests harm progress in forecasting: Comment," International Journal of Forecasting, Elsevier, vol. 23(2), pages 329-330.

  40. Bryan Boulier & H. O. Stekler, 2001. "The term spread as a cyclical indicator: a forecasting evaluation," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 403-409.

    Cited by:

    1. Alexandra Krystalogianni & George Matysiak & Sotiris Tsolacos, 2004. "Forecasting UK commercial real estate cycle phases with leading indicators: a probit approach," Applied Economics, Taylor & Francis Journals, vol. 36(20), pages 2347-2356.
    2. Masashi Hasegawa & Yuichi Fukuta, 2011. "An empirical analysis of information in the yield spread on future recessions in Japan," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1865-1881.
    3. Herman O. Stekler & Tianyu Ye, 2017. "Evaluating a leading indicator: an application—the term spread," Empirical Economics, Springer, vol. 53(1), pages 183-194, August.
    4. Alexandra Krystaloyianni & George Matysiak & Sotiris Tsolacos, 2004. "Forecasting UK Real Estate Cycle Phases With Leading Indicators: A Probit Approach," Real Estate & Planning Working Papers rep-wp2004-15, Henley Business School, University of Reading.

  41. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.

    Cited by:

    1. Baghestani, Hamid & Kherfi, Samer, 2008. "How well do U.S. consumers predict the direction of change in interest rates?," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(4), pages 725-732, November.
    2. 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.
    3. Tsuchiya, Yoichi, 2013. "Do corporate executives have accurate predictions for the economy? A directional analysis," Economic Modelling, Elsevier, vol. 30(C), pages 167-174.
    4. Hamid Baghestani, 2008. "Predicting capacity utilization: Federal Reserve vs time-series models," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 32(1), pages 47-57, January.
    5. Hamid Baghestani, 2006. "An evaluation of the professional forecasts of U.S. long‐term interest rates," Review of Financial Economics, John Wiley & Sons, vol. 15(2), pages 177-191.
    6. Hamid Baghestani, 2011. "A directional analysis of Federal Reserve predictions of growth in unit labor costs and productivity," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(3), pages 303-311.
    7. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    8. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    9. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    10. Baghestani, Hamid, 2008. "Federal Reserve versus private information: Who is the best unemployment rate predictor," Journal of Policy Modeling, Elsevier, vol. 30(1), pages 101-110.
    11. Baghestani, Hamid, 2006. "An evaluation of the professional forecasts of U.S. long-term interest rates," Review of Financial Economics, Elsevier, vol. 15(2), pages 177-191.
    12. Hetzel, Robert L., 1998. "U.S. monetary policy and monetary policy and the ESCB," ZEI Working Papers B 09-1998, University of Bonn, ZEI - Center for European Integration Studies.
    13. Masahiro Ashiya, 2009. "Strategic bias and professional affiliations of macroeconomic forecasters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 120-130.
    14. Xie, Zixiong & Hsu, Shih-Hsun, 2016. "Time varying biases and the state of the economy," International Journal of Forecasting, Elsevier, vol. 32(3), pages 716-725.
    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. Tsuchiya, Yoichi, 2016. "Do production managers predict turning points? A directional analysis," Economic Modelling, Elsevier, vol. 58(C), pages 1-8.
    17. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    18. Masahiro Ashiya, 2006. "Are 16-month-ahead forecasts useful? A directional analysis of Japanese GDP forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 201-207.
    19. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2009. "Can the Fed Predict the State of the Economy?," Working Papers 2009-001, The George Washington University, The Center for Economic Research, revised Mar 2010.
    20. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141.
    21. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    22. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    23. Hamid Baghestani, 2010. "Predicting the direction of change in aggregate demand growth and its components," Economics Bulletin, AccessEcon, vol. 30(1), pages 292-302.
    24. Baghestani, Hamid, 2011. "Federal Reserve and private forecasts of growth in investment," Journal of Economics and Business, Elsevier, vol. 63(4), pages 290-305, July.
    25. Michael T. Belongia & Peter N. Ireland, 2018. "Monetary Policy Lessons from the Greenbook," Boston College Working Papers in Economics 955, Boston College Department of Economics.
    26. Tara M. Sinclair & Fred Joutz & Herman O. Stekler, 2008. "Are 'unbiased' forecasts really unbiased? Another look at the Fed forecasts," Working Papers 2008-010, The George Washington University, The Center for Economic Research.
    27. 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.
    28. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
    29. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    30. William T. Gavin, 2003. "FOMC forecasts: is all the information in the central tendency?," Working Papers 2003-002, Federal Reserve Bank of St. Louis.
    31. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
    32. Francisco J. Eransus & Alfonso Novales Cinca, 2011. "A statistical test for forecast evaluation under a discrete loss function," Documentos de Trabajo del ICAE 2011-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    33. Gamber, Edward N. & Smith, Julie K. & McNamara, Dylan C., 2014. "Where is the Fed in the distribution of forecasters?," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 296-312.
    34. Jeff Messina & Tara M. Sinclair & Herman O. Stekler, 2014. "What Can We Learn From Revisions To The Greenbook Forecasts?," Working Papers 2014-003, The George Washington University, The Center for Economic Research.
    35. Bespalova, Olga, 2020. "GDP forecasts: Informational asymmetry of the SPF and FOMC minutes," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1531-1540.
    36. William T. Gavin & Rachel J. Mandal, 2002. "Evaluating FOMC forecasts," Working Papers 2001-005, Federal Reserve Bank of St. Louis.
    37. Yetman, James, 2006. "Are speed limit policies robust?," Journal of Macroeconomics, Elsevier, vol. 28(4), pages 665-679, December.
    38. 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.
    39. Pablo Pincheira, 2012. "A Joint Test of Superior Predictive Ability for Chilean Inflation Forecasts," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(3), pages 04-39, December.
    40. Clements, Michael P & Galvão, Ana Beatriz, 2006. "Macroeconomic Forecasting with Mixed Frequency Data : Forecasting US output growth and inflation," The Warwick Economics Research Paper Series (TWERPS) 773, University of Warwick, Department of Economics.
    41. William T. Gavin & Geetanjali Pande, 2008. "FOMC consensus forecasts," Review, Federal Reserve Bank of St. Louis, vol. 90(May), pages 149-164.
    42. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    43. Paul Hubert, 2009. "Informational Advantage and Influence of Communicating Central Banks," Documents de Travail de l'OFCE 2009-04, Observatoire Francais des Conjonctures Economiques (OFCE).
    44. Tara M. Sinclair & H. O. Stekler & Warren Carnow, 2012. "A new approach for evaluating economic forecasts," Economics Bulletin, AccessEcon, vol. 32(3), pages 2332-2342.
    45. Greer, Mark, 2003. "Directional accuracy tests of long-term interest rate forecasts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 291-298.
    46. Fred Joutz & Michael P. Clements & Herman O. Stekler, 2007. "An evaluation of the forecasts of the federal reserve: a pooled approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 121-136.
    47. Eleni Argiri & Stephen G. Hall & Angeliki Momtsia & Daphne Marina Papadopoulou & Ifigeneia Skotida & George S. Tavlas & Yongli Wang, 2024. "An evaluation of the inflation forecasting performance of the European Central Bank, the Federal Reserve, and the Bank of England," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 932-947, July.
    48. 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.
    49. Giordani, Paolo, 2001. "An Alternative Explanation of the Price Puzzle," Working Paper Series 125, Sveriges Riksbank (Central Bank of Sweden).
    50. Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
    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. Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
    53. Tsuchiya, Yoichi, 2016. "Directional analysis of fiscal sustainability: Revisiting Domar's debt sustainability condition," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 189-201.
    54. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers 2008-073, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    55. Baghestani, Hamid, 2009. "Forecasting in efficient bond markets: Do experts know better?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 624-630, October.
    56. Tara Sinclair & H. O. Stekler & L. Kitzinger, 2010. "Directional forecasts of GDP and inflation: a joint evaluation with an application to Federal Reserve predictions," Applied Economics, Taylor & Francis Journals, vol. 42(18), pages 2289-2297.
    57. Paul Hubert, 2009. "An Empirical Review of Federal Reserve’s Informational Advantage," Documents de Travail de l'OFCE 2009-03, Observatoire Francais des Conjonctures Economiques (OFCE).
    58. Hamid Baghestani, 2008. "Consensus vs. Time‐series Forecasts of US 30‐year Home Mortgage Rates," Journal of Property Research, Taylor & Francis Journals, vol. 25(1), pages 45-60, January.
    59. Baghestani, Hamid, 2008. "A random walk approach to predicting US 30-year home mortgage rates," Journal of Housing Economics, Elsevier, vol. 17(3), pages 225-233, September.
    60. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    61. 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.
    62. Masahiro Ashiya, 2003. "The directional accuracy of 15-months-ahead forecasts made by the IMF," Applied Economics Letters, Taylor & Francis Journals, vol. 10(6), pages 331-333.
    63. Ashiya, Masahiro, 2007. "Forecast accuracy of the Japanese government: Its year-ahead GDP forecast is too optimistic," Japan and the World Economy, Elsevier, vol. 19(1), pages 68-85, January.
    64. Pincheira, Pablo & Hardy, Nicolas, 2022. "Correlation Based Tests of Predictability," MPRA Paper 112014, University Library of Munich, Germany.
    65. Y. Tsuchiya, 2014. "A directional evaluation of corporate executives' exchange rate forecasts," Applied Economics, Taylor & Francis Journals, vol. 46(1), pages 95-101, January.
    66. Yoichi Tsuchiya, 2012. "Is the Purchasing Managers' Index useful for assessing the economy's strength? A directional analysis," Economics Bulletin, AccessEcon, vol. 32(2), pages 1302-1311.
    67. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.
    68. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.
    69. Jones, Adam T. & Ogden, Richard E., 2017. "A day late and a dollar short: The effect of policy uncertainty on fed forecast errors," Economic Analysis and Policy, Elsevier, vol. 54(C), pages 112-122.
    70. Hamid Baghestani, 2013. "Evaluating Federal Reserve predictions of growth in consumer spending," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1637-1646, May.
    71. Baghestani, Hamid, 2006. "Federal reserve vs. private forecasts of real net exports," Economics Letters, Elsevier, vol. 91(3), pages 349-353, June.
    72. 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.
    73. 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.
    74. 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.
    75. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.

  42. Boulier, Bryan L. & Stekler, H. O., 2000. "The term spread as a monthly cyclical indicator: an evaluation," Economics Letters, Elsevier, vol. 66(1), pages 79-83, January.

    Cited by:

    1. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    2. Stijn Claessens & M. Ayhan Kose, 2017. "Asset Prices and Macroeconomic Outcomes: A Survey," CAMA Working Papers 2017-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Ng, Eric C.Y., 2012. "Forecasting US recessions with various risk factors and dynamic probit models," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 112-125.
    4. Matthew C. Li, 2014. "The US zero-coupon yield spread as a predictor of excess daily stock market volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 24(13), pages 889-906, July.
    5. Masashi Hasegawa & Yuichi Fukuta, 2011. "An empirical analysis of information in the yield spread on future recessions in Japan," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1865-1881.
    6. Panopoulou, Ekaterini, 2007. "Predictive financial models of the euro area: A new evaluation test," International Journal of Forecasting, Elsevier, vol. 23(4), pages 695-705.
    7. John G Powell & Sirimon Treepongkaruna, 2012. "Recession fears as self-fulfilling prophecies? Influence on stock returns and output," Australian Journal of Management, Australian School of Business, vol. 37(2), pages 231-260, August.
    8. Bruinshoofd, W.A. & Candelon, B. & Raabe, K., 2005. "Banking sector strength and the transmission of currency crises," Research Memorandum 022, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    9. Breitung, Jorg & Candelon, Bertrand, 2006. "Testing for short- and long-run causality: A frequency-domain approach," Journal of Econometrics, Elsevier, vol. 132(2), pages 363-378, June.

  43. Robert S. Goldfarb & H. O. Stekler, 2000. "Why Do Empirical Results Change? Forecasts as Tests of Rational Expectations," History of Political Economy, Duke University Press, vol. 32(5), pages 95-116, Supplemen.

    Cited by:

    1. Adam Fforde, 2004. "Persuasion: Reflections on Economics, Data and the 'Homogeneity Assumption'," Department of Economics - Working Papers Series 919, The University of Melbourne.

  44. Fintzen, David & Stekler, H. O., 1999. "Why did forecasters fail to predict the 1990 recession?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 309-323, July.

    Cited by:

    1. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, The Center for Economic Research.
    2. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    3. Abdalla, Ahmed & Carabias, Jose M. & Patatoukas, Panos N., 2021. "The real-time macro content of corporate financial reports: a dynamic factor model approach," LSE Research Online Documents on Economics 108539, London School of Economics and Political Science, LSE Library.
    4. Chua, Chew Lian & Tsiaplias, Sarantis, 2011. "Predicting economic contractions and expansions with the aid of professional forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 438-451, April.
    5. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, The Center for Economic Research, revised Feb 2012.
    6. Mark T. Bradshaw & Lawrence D. Brown & Kelly Huang, 2013. "Do sell-side analysts exhibit differential target price forecasting ability?," Review of Accounting Studies, Springer, vol. 18(4), pages 930-955, December.
    7. Österholm, Pär, 2012. "The limited usefulness of macroeconomic Bayesian VARs when estimating the probability of a US recession," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 76-86.
    8. Loungani, Prakash, 2001. "How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth," International Journal of Forecasting, Elsevier, vol. 17(3), pages 419-432.
    9. Abdalla, Ahmed M. & Carabias, Jose M. & Patatoukas, Panos N., 2021. "The real-time macro content of corporate financial reports: A dynamic factor model approach," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 260-280.
    10. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.
    11. Dimitrios Papastamos & Fotis Mouzakis & Simon Stevenson, 2014. "Rationality and Momentum in Real Estate Investment Forecasts," Real Estate & Planning Working Papers rep-wp2014-07, Henley Business School, University of Reading.
    12. Celik Ozdes & Volkan Ş. Ediger & Deniz Eroglu, 2025. "Forecasting critical economic & political events via electricity consumption patterns in the United States of America and Turkey," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-14, December.
    13. Döpke, Jörg, 2000. "Macroeconomic Forecasts and the Nature of Economic Shocks in Germany," Kiel Working Papers 972, Kiel Institute for the World Economy.
    14. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    15. Constantin Bürgi & Tara M. Sinclair, 2020. "What Does Forecaster Disagreement Tell Us about the State of the Economy?," Working Papers 2020-001, The George Washington University, The Center for Economic Research.
    16. Higgins, Huong Ngo, 2002. "Analysts' forecasts of Japanese firms' earnings: additional evidence," The International Journal of Accounting, Elsevier, vol. 37(4), pages 371-394.
    17. 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.
    18. Mark T. Bradshaw & Michael S. Drake & James N. Myers & Linda A. Myers, 2012. "A re-examination of analysts’ superiority over time-series forecasts of annual earnings," Review of Accounting Studies, Springer, vol. 17(4), pages 944-968, December.
    19. Ana Beatriz C. Galvão, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487, May.
    20. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, The Center for Economic Research.
    21. 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.
    22. Lars-Erik Öller & Lasse Koskinen, 2004. "A classifying procedure for signalling turning points," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 197-214.
    23. 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.
    24. Heilemann, Ullrich, 2002. "Increasing the transparency of macroeconometric forecasts: a report from the trenches," International Journal of Forecasting, Elsevier, vol. 18(1), pages 85-105.
    25. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    26. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    27. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.
    28. Zidong An & João Tovar Jalles & Mr. Prakash Loungani, 2018. "How Well Do Economists Forecast Recessions?," IMF Working Papers 2018/039, International Monetary Fund.
    29. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.

  45. Boulier, Bryan L. & Stekler, H. O., 1999. "Are sports seedings good predictors?: an evaluation," International Journal of Forecasting, Elsevier, vol. 15(1), pages 83-91, February.

    Cited by:

    1. Nicholas G. Hall & Chris N. Potts, 2012. "A Proposal for Redesign of the FedEx Cup Playoff Series on the PGA TOUR," Interfaces, INFORMS, vol. 42(2), pages 166-179, April.
    2. 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.
    3. Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
    4. Klaassen, Franc J. G. M. & Magnus, Jan R., 2003. "Forecasting the winner of a tennis match," European Journal of Operational Research, Elsevier, vol. 148(2), pages 257-267, July.
    5. Kurt Rotthoff & Danielle Zanzalari & John Jasina, 2011. "What are the odds? A measure of the small sample problems," Applied Economics Letters, Taylor & Francis Journals, vol. 18(12), pages 1139-1143.
    6. Selçuk Özaydın & Thomas Könecke, 2024. "Match-Level Uncertainty in Professional Tennis Revisited—A Novel Approach Applied for the Time Between 2010 and 2019," Journal of Sports Economics, , vol. 25(4), pages 507-532, May.
    7. Todd Kuethe & Timothy Zimmer, 2008. "Major Conference Bias and the NCAA Men's Basketball Tournament," Economics Bulletin, AccessEcon, vol. 12(17), pages 1-6.
    8. Boulier, Bryan L. & Stekler, H. O., 2003. "Predicting the outcomes of National Football League games," International Journal of Forecasting, Elsevier, vol. 19(2), pages 257-270.
    9. Andersson, Patric & Edman, Jan & Ekman, Mattias, 2005. "Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts," International Journal of Forecasting, Elsevier, vol. 21(3), pages 565-576.
    10. Stekler Herman O. & Klein Andrew, 2012. "Predicting the Outcomes of NCAA Basketball Championship Games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-10, March.
    11. Ferda Halicioglu, 2005. "Can We Predict The Outcome Of The International Football Tournaments : The Case Of Euro 2000?," Microeconomics 0503008, University Library of Munich, Germany.
    12. Blackburn McKinley L., 2013. "Ranking the performance of tennis players: an application to women’s professional tennis," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(4), pages 367-378, December.
    13. Kovalchik Stephanie Ann, 2016. "Searching for the GOAT of tennis win prediction," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(3), pages 127-138, September.
    14. Andrew J. Leach, 2003. "SubGame, set and match. Identifying Incentive Response in a Tournament," Cahiers de recherche 04-02, HEC Montréal, Institut d'économie appliquée.
    15. Morris Tracy L. & Bokhari Faryal H., 2012. "The Dreaded Middle Seeds - Are They the Worst Seeds in the NCAA Basketball Tournament?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(2), pages 1-13, June.
    16. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
    17. Jain, Kriti & Bearden, J. Neil & Filipowicz, Allan, 2013. "Depression and forecast accuracy: Evidence from the 2010 FIFA World Cup," International Journal of Forecasting, Elsevier, vol. 29(1), pages 69-79.
    18. Rose D. Baker & Ian G. McHale, 2013. "Optimal Betting Under Parameter Uncertainty: Improving the Kelly Criterion," Decision Analysis, INFORMS, vol. 10(3), pages 189-199, September.
    19. Alessandro Innocenti & Tommaso Nannicini & Roberto Ricciuti, 2012. "The Importance of Betting Early," Labsi Experimental Economics Laboratory University of Siena 037, University of Siena.
    20. Ira Horowitz, 2018. "Competitive Balance in the NBA Playoffs," The American Economist, Sage Publications, vol. 63(2), pages 215-227, October.
    21. Paul Kvam & Joel S. Sokol, 2006. "A logistic regression/Markov chain model for NCAA basketball," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 788-803, December.
    22. Kovalchik, Stephanie & Reid, Machar, 2019. "A calibration method with dynamic updates for within-match forecasting of wins in tennis," International Journal of Forecasting, Elsevier, vol. 35(2), pages 756-766.
    23. Coleman Jay & Lynch Allen K, 2009. "NCAA Tournament Games: The Real Nitty-Gritty," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-27, July.
    24. Steven Caudill & Norman Godwin, 2002. "Heterogeneous skewness in binary choice models: Predicting outcomes in the men's NCAA basketball tournament," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 991-1001.
    25. Lopez Michael J. & Matthews Gregory J., 2015. "Building an NCAA men’s basketball predictive model and quantifying its success," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(1), pages 5-12, March.
    26. Alberto Arcagni & Vincenzo Candila & Rosanna Grassi, 2023. "A new model for predicting the winner in tennis based on the eigenvector centrality," Annals of Operations Research, Springer, vol. 325(1), pages 615-632, June.
    27. Yuan Lo-Hua & Liu Anthony & Yeh Alec & Kaufman Aaron & Reece Andrew & Bull Peter & Franks Alex & Wang Sherrie & Illushin Dmitri & Bornn Luke, 2015. "A mixture-of-modelers approach to forecasting NCAA tournament outcomes," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(1), pages 13-27, March.
    28. Ferda HALICIOGLU, 2005. "Forecasting the Professional Team Sporting Events: Evidence from Euro 2000 and 2004 Football Tournaments," Industrial Organization 0508001, University Library of Munich, Germany.
    29. Caudill, Steven B., 2003. "Predicting discrete outcomes with the maximum score estimator: the case of the NCAA men's basketball tournament," International Journal of Forecasting, Elsevier, vol. 19(2), pages 313-317.
    30. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630, April.
    31. Karlsson, Niklas & Lunander, Anders, 2020. "Choosing Opponents in Skiing Sprint Elimination Tournaments," Working Papers 2020:6, Örebro University, School of Business, revised 01 Sep 2020.
    32. Karpov, Alexander, 2015. "A theory of knockout tournament seedings," Working Papers 0600, University of Heidelberg, Department of Economics.
    33. B. Jay Coleman & J. Michael DuMond & Allen K. Lynch, 2010. "Evidence of bias in NCAA tournament selection and seeding," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 431-452.
    34. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630.
    35. Ludden Ian G. & Khatibi Arash & King Douglas M. & Jacobson Sheldon H., 2020. "Models for generating NCAA men’s basketball tournament bracket pools," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 16(1), pages 1-15, March.
    36. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    37. Julio del Corral, 2009. "Competitive Balance and Match Uncertainty in Grand-Slam Tennis," Journal of Sports Economics, , vol. 10(6), pages 563-581, December.
    38. Herman O. Stekler, 2007. "Sports Forecasting," Working Papers 2007-001, The George Washington University, The Center for Economic Research, revised Jan 2007.
    39. Manner Hans, 2016. "Modeling and forecasting the outcomes of NBA basketball games," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 31-41, March.
    40. Lebovic, James H. & Sigelman, Lee, 2001. "The forecasting accuracy and determinants of football rankings," International Journal of Forecasting, Elsevier, vol. 17(1), pages 105-120.
    41. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    42. Vincenzo Candila & Lucio Palazzo, 2020. "Neural Networks and Betting Strategies for Tennis," Risks, MDPI, vol. 8(3), pages 1-19, June.
    43. Irons David J. & Buckley Stephen & Paulden Tim, 2014. "Developing an improved tennis ranking system," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(2), pages 109-118, June.
    44. Halkos, George & Tzeremes, Nickolaos, 2012. "Evaluating professional tennis players’ career performance: A Data Envelopment Analysis approach," MPRA Paper 41516, University Library of Munich, Germany.
    45. Bryan Clair & David Letscher, 2007. "Optimal Strategies for Sports Betting Pools," Operations Research, INFORMS, vol. 55(6), pages 1163-1177, December.
    46. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    47. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    48. Michael Cary & Heather Stephens, 2023. "Gendered Consequences of COVID-19 Among Professional Tennis Players," Journal of Sports Economics, , vol. 24(2), pages 241-266, February.
    49. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.
    50. Goldstein, Daniel G. & Gigerenzer, Gerd, 2009. "Fast and frugal forecasting," International Journal of Forecasting, Elsevier, vol. 25(4), pages 760-772, October.
    51. Andersson, Patric & Ekman, Mattias & Edman, Jan, 2003. "Forecasting the fast and frugal way: A study of performance and information-processing strategies of experts and non-experts when predicting the World Cup 2002 in soccer," SSE/EFI Working Paper Series in Business Administration 2003:9, Stockholm School of Economics.

  46. Joutz, Frederick L. & Stekler, H. O., 1999. "An Evaluation of Federal Reserve Forecasting: Comment," Journal of Macroeconomics, Elsevier, vol. 21(1), pages 179-187, January.

    Cited by:

    1. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.

  47. Frederick Joutz & H. O. Stekler, 1998. "Data revisions and forecasting," Applied Economics, Taylor & Francis Journals, vol. 30(8), pages 1011-1016.

    Cited by:

    1. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    2. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    3. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    4. Hasan Bakhshi & George Kapetanios & Anthony Yates, 2003. "Rational expectations and fixed-event forecasts: an application to UK inflation," Bank of England working papers 176, Bank of England.
    5. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    6. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    7. Christis Tombazos, 2003. "New light on the 'impressionistic view' of the balancing item in Australia's balance of payments accounts," Applied Economics, Taylor & Francis Journals, vol. 35(12), pages 1369-1378.
    8. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
    9. Jordi Pons-Novell, 2006. "An analysis of a panel of Spanish GDP forecasts," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1287-1292.
    10. Jordi Pons, 2001. "The rationality of price forecasts: a directional analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 287-290.

  48. M. H. Schnader & H. O. Stekler, 1998. "Sources of turning point forecast errors," Applied Economics Letters, Taylor & Francis Journals, vol. 5(8), pages 519-521.

    Cited by:

    1. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    2. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    3. Goodwin, Paul & Önkal, Dilek & Stekler, Herman O., 2018. "What if you are not Bayesian? The consequences for decisions involving risk," European Journal of Operational Research, Elsevier, vol. 266(1), pages 238-246.
    4. Goodwin, Paul, 2015. "When simple alternatives to Bayes formula work well: Reducing the cognitive load when updating probability forecasts," Journal of Business Research, Elsevier, vol. 68(8), pages 1686-1691.

  49. Kolb, R. A. & Stekler, H. O., 1996. "Is there a consensus among financial forecasters?," International Journal of Forecasting, Elsevier, vol. 12(4), pages 455-464, December.

    Cited by:

    1. Dopke, Jorg & Fritsche, Ulrich, 2006. "When do forecasters disagree? An assessment of German growth and inflation forecast dispersion," International Journal of Forecasting, Elsevier, vol. 22(1), pages 125-135.
    2. Audretsch, David B. & Stadtmann, Georg, 2005. "Biases in FX-forecasts: Evidence from panel data," Global Finance Journal, Elsevier, vol. 16(1), pages 99-111, August.
    3. Carl S Bonham & Richard H Cohen, 2000. "To Aggregate, Pool, or Neither: Testing the Rational Expectations Hypothesis Using Survey Data," Working Papers 200003, University of Hawaii at Manoa, Department of Economics.
    4. Fintzen, David & Stekler, H. O., 1999. "Why did forecasters fail to predict the 1990 recession?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 309-323, July.
    5. Frenkel, Michael & Rülke, Jan-Christoph & Stadtmann, Georg, 2009. "Two currencies, one model? Evidence from the Wall Street Journal forecast poll," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 588-596, October.
    6. ChiUng Song & Bryan L. Boulier & Herman O. Stekler, 2008. "Measuring Consensus in Binary Forecasts: NFL Game Predictions," Working Papers 2008-006, The George Washington University, The Center for Economic Research.
    7. Christian Dreger & Georg Stadtmann, 2008. "What drives heterogeneity in foreign exchange rate expectations: insights from a new survey," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(4), pages 360-367.
    8. Christian Dreger & Georg Stadtmann, 2006. "What Drives Heterogeneity in Foreign Exchange Rate Expectations: Deep Insights from a New Survey," Discussion Papers of DIW Berlin 624, DIW Berlin, German Institute for Economic Research.
    9. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    10. Reitz, Stefan & Ruelke, Jan & Stadtmann, Georg, 2009. "Are oil-price-forecasters finally right? -- Regressive expectations towards more fundamental values of the oil price," MPRA Paper 15607, University Library of Munich, Germany.
    11. H.O. Stekler & Kazuta Sakamoto, 2008. "Evaluating Current Year Forecasts Made During the Year: A Japanese Example," Working Papers 2008-005, The George Washington University, The Center for Economic Research.
    12. Ruelke, Jan C. & Frenkel, Michael R. & Stadtmann, Georg, 2010. "Expectations on the yen/dollar exchange rate - Evidence from the Wall Street Journal forecast poll," Journal of the Japanese and International Economies, Elsevier, vol. 24(3), pages 355-368, September.
    13. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    14. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
    15. Frank A.G. den Butter & Pieter W. Jansen, 2008. "Beating the Random Walk: a Performance Assessment of Long-term Interest Rate Forecasts," Tinbergen Institute Discussion Papers 08-102/3, Tinbergen Institute.
    16. Pierdzioch, Christian & Rülke, Jan Christoph & Stadtmann, Georg, 2012. "House price forecasts in times of crisis: Do forecasters herd?," Discussion Papers 318, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    17. Nickel, Christiane & Rother, Philipp & Rülke, Jan C., 2009. "Fiscal variables and bond spreads: evidence from eastern European countries and Turkey," Working Paper Series 1101, European Central Bank.
    18. Koske, Isabell & Stadtmann, Georg, 2009. "Exchange rate expectations: The role of person specific forward looking variables," Economics Letters, Elsevier, vol. 105(3), pages 221-223, December.

  50. Kolb, R. A. & Stekler, H. O., 1993. "Are economic forecasts significantly better than naive predictions? An appropriate test," International Journal of Forecasting, Elsevier, vol. 9(1), pages 117-120, April.

    Cited by:

    1. Fullerton, Thomas M., Jr. & Molina, Angel L., Jr. & Walke, Adam G., 2010. "Tolls, Exchange Rates, and Northbound International Bridge Traffic from Mexico," MPRA Paper 59586, University Library of Munich, Germany, revised 22 Jun 2012.
    2. Fullerton, Thomas M., Jr. & Kelley, Brian W., 2008. "El Paso Housing Sector Econometric Forecast Accuracy," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 40(01), pages 1-18, April.
    3. Adam G. Walke & Thomas M. Fullerton Jr., 2019. "Metropolitan Hotel Sector Forecast Accuracy in El Paso," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(2), pages 179-191, June.
    4. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    5. William Briggs & David Ruppert, 2005. "Assessing the Skill of Yes/No Predictions," Biometrics, The International Biometric Society, vol. 61(3), pages 799-807, September.
    6. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
    7. Thomas Fullerton & Roberto Tinajero & Jorge Mendoza Cota, 2007. "An Empirical Analysis of Tijuana Water Consumption," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 35(3), pages 357-369, September.
    8. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
    9. Thomas Fullerton & Roberto Tinajero & Martha Barraza de Anda, 2006. "Short-Term Water Consumption Patterns in Ciudad Juárez, Mexico," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 34(4), pages 467-479, December.
    10. Vogl, Markus & Kojić, Milena & Sharma, Abhishek & Stanisic, Nikola, 2025. "Decoding financial markets: Empirical DGPs as the key to model selection and forecasting excellence – A proof of concept," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 666(C).

  51. Schnader, M. H. & Stekler, H. O., 1991. "Do consensus forecasts exist?," International Journal of Forecasting, Elsevier, vol. 7(2), pages 165-170, August.

    Cited by:

    1. Fintzen, David & Stekler, H. O., 1999. "Why did forecasters fail to predict the 1990 recession?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 309-323, July.
    2. Patrick Mcallister & Graeme Newell & George Matysiak, 2008. "Agreement and Accuracy in Consensus Forecasts of the UK Commercial Property Market," Journal of Property Research, Taylor & Francis Journals, vol. 25(1), pages 1-22, June.
    3. Pat McAllister & Graeme Newell & George Matysiak, 2005. "Analysing Uk Real Estate Market Forecast Disagreement," Real Estate & Planning Working Papers rep-wp2005-13, Henley Business School, University of Reading.
    4. ChiUng Song & Bryan L. Boulier & Herman O. Stekler, 2008. "Measuring Consensus in Binary Forecasts: NFL Game Predictions," Working Papers 2008-006, The George Washington University, The Center for Economic Research.
    5. Kolb, R. A. & Stekler, H. O., 1996. "Is there a consensus among financial forecasters?," International Journal of Forecasting, Elsevier, vol. 12(4), pages 455-464, December.
    6. Wegener, Michael & Westerhoff, Frank & Zaklan, Georg, 2009. "A Metzlerian business cycle model with nonlinear heterogeneous expectations," Economic Modelling, Elsevier, vol. 26(3), pages 715-720, May.
    7. Pat McAllister & Graeme Newell & George Matysiak, 2005. "An Evaluation Of The Performance Of UK Real Estate Forecasters," Real Estate & Planning Working Papers rep-wp2005-23, Henley Business School, University of Reading.
    8. H.O. Stekler & Kazuta Sakamoto, 2008. "Evaluating Current Year Forecasts Made During the Year: A Japanese Example," Working Papers 2008-005, The George Washington University, The Center for Economic Research.
    9. Sheng, Xuguang (Simon), 2015. "Evaluating the economic forecasts of FOMC members," International Journal of Forecasting, Elsevier, vol. 31(1), pages 165-175.
    10. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    11. Liu, Qiqi & Li, Rui & Cai, Weiguang & Huo, Tengfei, 2025. "Will China follow the same process of building carbon peak as the US? Evidence from the building carbon peak pattern," Energy, Elsevier, vol. 333(C).
    12. de Menezes, Lilian M. & Bunn, Derek W., 1998. "The persistence of specification problems in the distribution of combined forecast errors," International Journal of Forecasting, Elsevier, vol. 14(3), pages 415-426, September.
    13. Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.

  52. Stekler, H. O., 1991. "Macroeconomic forecast evaluation techniques," International Journal of Forecasting, Elsevier, vol. 7(3), pages 375-384, November.

    Cited by:

    1. Jansen, Dennis W. & Kishan, Ruby Pandey, 1996. "An evaluation of federal reserve forecasting," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 89-109.
    2. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    3. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, The Center for Economic Research, revised Feb 2012.
    4. Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, University Library of Munich, Germany.
    5. Prem P. Talwar & Edward J. Chambers, 1993. "Forecasting Provincial Business Indicator Variables and Forecast Evaluation," Urban Studies, Urban Studies Journal Limited, vol. 30(10), pages 1763-1773, December.
    6. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    7. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    8. Zidong An & João Tovar Jalles, 2020. "On the Performance of US Fiscal Forecasts: Government vs. Private Information," Working Papers REM 2020/0130, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    9. Döpke, Jörg & Langfeldt, Enno, 1995. "Zur Qualität von Konjunkturprognosen für Westdeutschland 1976-1994," Kiel Discussion Papers 247, Kiel Institute for the World Economy.
    10. Timotej Jagric, 2003. "Forecasting with leading economic indicators - a non-linear approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2003(1), pages 68-83.
    11. 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.
    12. 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.
    13. Monjazeb, Mohammad Reza & Amiri, Hossein & Movahedi, Akram, 2024. "Wholesale electricity price forecasting by Quantile Regression and Kalman Filter method," Energy, Elsevier, vol. 290(C).
    14. Adolfo Rodríguez-Vargas, 2019. "Univariate Forecasts for Costa Rican Inflation With Stochastic Volatility and GARCH Effects," Documentos de Trabajo 1604, Banco Central de Costa Rica.
    15. Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
    16. Ullrich Heilemann & Herman O. Stekler, 2013. "Has The Accuracy of Macroeconomic Forecasts for Germany Improved?," German Economic Review, Verein für Socialpolitik, vol. 14(2), pages 235-253, May.
    17. Wu, Yih-Jiuan, 1998. "Exchange rate forecasting: an application of radial basis function neural networks," ISU General Staff Papers 1998010108000013540, Iowa State University, Department of Economics.
    18. Yousaf Raza, Muhammad & Lin, Boqiang, 2021. "Oil for Pakistan: What are the main factors affecting the oil import?," Energy, Elsevier, vol. 237(C).
    19. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, The Center for Economic Research.
    20. Jagric Timotej, 2003. "A Nonlinear Approach to Forecasting with Leading Economic Indicators," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(2), pages 1-20, July.
    21. Maung, Kenwin & Swanson, Norman R., 2025. "A survey of models and methods used for forecasting when investing in financial markets," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1355-1382.
    22. Jef Vuchelen & Maria-Isabel Gutierrez, 2005. "Do the OECD 24 month horizon growth forecasts for the G7-countries contain information?," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 855-862.
    23. Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.
    24. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
    25. Mc Cracken, Michael W., 2000. "Robust out-of-sample inference," Journal of Econometrics, Elsevier, vol. 99(2), pages 195-223, December.
    26. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    27. 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.
    28. Allan, Grant, 2013. "Evaluating the usefulness of forecasts of relative growth," SIRE Discussion Papers 2013-10, Scottish Institute for Research in Economics (SIRE).

  53. Kolb, R. A. & Stekler, H. O., 1990. "The lead and accuracy of macroeconomic forecasts," Journal of Macroeconomics, Elsevier, vol. 12(1), pages 111-123.

    Cited by:

    1. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    2. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.
    3. Fullerton, Jr., Thomas M. & Taylor West, Carol A., 1998. "Regional Econometric Housing Start Forecast Accuracy in Florida," The Review of Regional Studies, Southern Regional Science Association, vol. 28(3), pages 15-42, Winter.
    4. Masahiro Ashiya, 2003. "The directional accuracy of 15-months-ahead forecasts made by the IMF," Applied Economics Letters, Taylor & Francis Journals, vol. 10(6), pages 331-333.
    5. Nathan Goldstein & Ben‐Zion Zilberfarb, 2023. "The closer we get, the better we are?," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 364-376, April.

  54. Schnader, M H & Stekler, H O, 1990. "Evaluating Predictions of Change," The Journal of Business, University of Chicago Press, vol. 63(1), pages 99-107, January.

    Cited by:

    1. Pierdzioch, Christian & Rülke, Jan-Christoph, 2015. "On the directional accuracy of forecasts of emerging market exchange rates," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 369-376.
    2. Tsuchiya, Yoichi, 2013. "Do corporate executives have accurate predictions for the economy? A directional analysis," Economic Modelling, Elsevier, vol. 30(C), pages 167-174.
    3. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    4. Baghestani, Hamid & Toledo, Hugo, 2017. "Do analysts' forecasts of term spread differential help predict directional change in exchange rates?," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 62-69.
    5. Tsuchiya, Yoichi, 2016. "Do production managers predict turning points? A directional analysis," Economic Modelling, Elsevier, vol. 58(C), pages 1-8.
    6. Masahiro Ashiya, 2006. "Are 16-month-ahead forecasts useful? A directional analysis of Japanese GDP forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 201-207.
    7. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
    8. Tsuchiya, Yoichi, 2013. "Are government and IMF forecasts useful? An application of a new market-timing test," Economics Letters, Elsevier, vol. 118(1), pages 118-120.
    9. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.
    10. Baghestani, Hamid, 2011. "Federal Reserve and private forecasts of growth in investment," Journal of Economics and Business, Elsevier, vol. 63(4), pages 290-305, July.
    11. Kosei Fukuda, 2009. "Forecasting growth cycle turning points using US and Japanese professional forecasters," Empirical Economics, Springer, vol. 36(2), pages 243-267, May.
    12. Blaskowitz, Oliver J. & Herwartz, Helmut, 2009. "On economic evaluation of directional forecasts," SFB 649 Discussion Papers 2009-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    13. McCracken, Michael W., 2004. "Parameter estimation and tests of equal forecast accuracy between non-nested models," International Journal of Forecasting, Elsevier, vol. 20(3), pages 503-514.
    14. Tae-Hwan Kima & Paul Mizena & Alan Thanaset, 2007. "Predicting Directional Changes in Interest Rates: Gains from Using Information from Monetary Indicators," Discussion Papers 07/07, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    15. Adam G. Walke & Thomas M. Fullerton Jr., 2019. "Metropolitan Hotel Sector Forecast Accuracy in El Paso," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(2), pages 179-191, June.
    16. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    17. IIZUKA Nobuo, 2013. "Predicting Business Cycle Phases by Professional Forecasters－ Are They Useful ?," ESRI Discussion paper series 305, Economic and Social Research Institute (ESRI).
    18. Kajal Lahiri, Wenxiong Yao, and Peg Young, 2003. "Cycles in the Transportation Sector and the Aggregate Economy," Discussion Papers 03-14, University at Albany, SUNY, Department of Economics.
    19. 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(01), pages 1-16, April.
    20. Clementrs, Michael P. & Smith, Jeremy, "undated". "A Monte Carlo study of the forecasting performance of empirical SETAR models," Economic Research Papers 268734, University of Warwick - Department of Economics.
    21. Baghestani, Hamid, 2015. "Predicting gasoline prices using Michigan survey data," Energy Economics, Elsevier, vol. 50(C), pages 27-32.
    22. Mihaela Simionescu, 2014. "Directional accuracy for inflation and unemployment rate predictions in Romania," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 129-138, September.
    23. Stekler, H. O. & Petrei, G., 2003. "Diagnostics for evaluating the value and rationality of economic forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 735-742.
    24. Baris Soybilgen & Ege Yazgan, 2016. "An Evaluation Of Inflation Expectations In Turkey," Working Papers 1601, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    25. Greer, Mark, 2003. "Directional accuracy tests of long-term interest rate forecasts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 291-298.
    26. Hamid Baghestani & Bassam M. AbuAl-Foul, 2019. "Dynamics between Oil Prices and UAE Effective Exchange Rates: An Empirical Examination," Review of Economics & Finance, Better Advances Press, Canada, vol. 16, pages 89-103, May.
    27. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    28. 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.
    29. John D. Burger & Francis E. Warnock & Veronica Cacdac Warnock, 2018. "Benchmarking Portfolio Flows," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 66(3), pages 527-563, September.
    30. Tsuchiya, Yoichi, 2016. "Directional analysis of fiscal sustainability: Revisiting Domar's debt sustainability condition," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 189-201.
    31. Tae-Hwan Kim & Paul Mizen & Alan Thanaset, 2006. "Forecasting changes in UK interest rates," Discussion Papers 06/06, University of Nottingham, Granger Centre for Time Series Econometrics.
    32. Baghestani, Hamid & Chazi, Abdelaziz & Khallaf, Ashraf, 2019. "A directional analysis of oil prices and real exchange rates in BRIC countries," Research in International Business and Finance, Elsevier, vol. 50(C), pages 450-456.
    33. Ash, J. C. K. & Smyth, D. J. & Heravi, S. M., 1998. "Are OECD forecasts rational and useful?: a directional analysis," International Journal of Forecasting, Elsevier, vol. 14(3), pages 381-391, September.
    34. Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data," Working Papers 24/2014, Stellenbosch University, Department of Economics.
    35. Eicher, Theo S. & Kuenzel, David J. & Papageorgiou, Chris & Christofides, Charis, 2019. "Forecasts in times of crises," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1143-1159.
    36. Hamid Baghestani & Jorg Bley, 2020. "Do directional predictions of US gasoline prices reveal asymmetries?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 348-360, April.
    37. Baghestani, Hamid & Toledo, Hugo, 2019. "Oil prices and real exchange rates in the NAFTA region," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 253-264.
    38. Lahiri, Kajal & Peng, Huaming & Zhao, Yongchen, 2015. "Testing the value of probability forecasts for calibrated combining," International Journal of Forecasting, Elsevier, vol. 31(1), pages 113-129.
    39. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    40. Tim Meyer, 2019. "On the Directional Accuracy of United States Housing Starts Forecasts: Evidence from Survey Data," The Journal of Real Estate Finance and Economics, Springer, vol. 58(3), pages 457-488, April.
    41. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, The Center for Economic Research.
    42. Eicher, Theo S. & Kawai, Reina, 2023. "IMF trade forecasts for crisis countries: Bias, inefficiency, and their origins," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1615-1639.
    43. Anusha, "undated". "Evaluating reliability of some symmetric and asymmetric univariate filters," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-030, Indira Gandhi Institute of Development Research, Mumbai, India.
    44. Yoichi Tsuchiya, 2012. "Is the Purchasing Managers' Index useful for assessing the economy's strength? A directional analysis," Economics Bulletin, AccessEcon, vol. 32(2), pages 1302-1311.
    45. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.
    46. Baghestani, Hamid & AbuAl-Foul, Bassam M., 2017. "Comparing Federal Reserve, Blue Chip, and time series forecasts of US output growth," Journal of Economics and Business, Elsevier, vol. 89(C), pages 47-56.
    47. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.
    48. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
    49. Kim, Tae-Hwan & Thanaset Chevapatrakul & Paul Mizen, 2003. "Predicting Changes in the Interest Rate: The Performance of Taylor Rules Versus Alternatives for the United Kingdom," Royal Economic Society Annual Conference 2003 122, Royal Economic Society.
    50. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    51. Hamid Baghestani, 2017. "Do US consumer survey data help beat the random walk in forecasting mortgage rates?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343017-134, January.
    52. Baghestani, Hamid, 2021. "Predicting growth in US durables spending using consumer durables-buying attitudes," Journal of Business Research, Elsevier, vol. 131(C), pages 327-336.
    53. Allan, Grant, 2013. "Evaluating the usefulness of forecasts of relative growth," SIRE Discussion Papers 2013-10, Scottish Institute for Research in Economics (SIRE).

  55. Stekler, H. O., 1990. "Forecasting industrial bottlenecks : An analysis of alternative approaches," Economic Modelling, Elsevier, vol. 7(3), pages 263-274, July.

    Cited by:

    1. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    2. Stekler, H. O. & Beckstead, R. W., 1995. "Modeling fully employed economies," Economic Modelling, Elsevier, vol. 12(2), pages 205-210, April.

  56. Stekler, Herman O., 1988. "Who forecasts better? : Herman O. Stekler, Journal of Business and Economic Statistics 5 (1987) 155-158," International Journal of Forecasting, Elsevier, vol. 4(4), pages 631-631.

    Cited by:

    1. Wang, Kai-Li & Fawson, Christopher B. & Barrett, Christopher B. & McDonald, James B., 1998. "A Flexible Parametric Garch Model With An Application To Exchange Rates," Economics Research Institute, ERI Study Papers 28355, Utah State University, Economics Department.

  57. Lee, Douglas & Stekler, H. O., 1987. "Modeling high levels of defense expenditures: A Vietnam," Journal of Policy Modeling, Elsevier, vol. 9(3), pages 437-453.

    Cited by:

    1. Stekler, H. O. & Beckstead, R. W., 1995. "Modeling fully employed economies," Economic Modelling, Elsevier, vol. 12(2), pages 205-210, April.

  58. Stekler, H O, 1987. "Who Forecasts Better? [Economic Forecasts and Their Assessment]," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 155-158, January.

    Cited by:

    1. Christopher Barrett, 1997. "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, Taylor & Francis Journals, vol. 25(2), pages 225-236.

  59. Thomas, R. William & Stekler, H. O., 1983. "A regional forecasting model for construction activity," Regional Science and Urban Economics, Elsevier, vol. 13(4), pages 557-577, November.

    Cited by:

    1. Lopez, Carmen, 2002. "Modelos econometricos del mercado de la vivienda en las regiones españolas," Economic Development 59, University of Santiago de Compostela. Faculty of Economics and Business. Econometrics..

  60. Thomas, R. William & Stekler, H. O., 1979. "Forecasts of construction activity for states," Economics Letters, Elsevier, vol. 4(2), pages 195-199.

    Cited by:

    1. Michael Klien & Andrea Kunnert, 2014. "Baubewilligungen für Wohneinheiten in Österreich. Prognose 2014 und 2015," WIFO Studies, WIFO, number 58602.
    2. Andrea Kunnert, 2013. "Baubewilligungen für Wohneinheiten in Österreich: Prognose 2012/13 und regionale Entwicklung 2006/2011. Teilbericht 2," WIFO Studies, WIFO, number 67110.
    3. Michael Klien & Andrea Kunnert, 2015. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose 2015/16 und regionale Entwicklung 2009/2014," WIFO Studies, WIFO, number 58605.
    4. Dieter Pennerstorfer & Andrea Kunnert & Peter Huber, 2014. "Baubewilligungen für Wohneinheiten in Österreich. Prognose 2014 und 2015 und regionale Entwicklung 2008 bis 2013," WIFO Studies, WIFO, number 58601.
    5. Andrea Kunnert, 2011. "Prognose der Baubewilligungen für Wohneinheiten in Österreich 2009 bis 2011," WIFO Studies, WIFO, number 41257.
    6. Andrea Kunnert, 2013. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose 2013/14 (Teilbericht 1)," WIFO Studies, WIFO, number 58599.
    7. Michael Klien & Andrea Kunnert, 2015. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose 2014 bis 2016," WIFO Studies, WIFO, number 58604.
    8. Andrea Kunnert, 2013. "Prognose der Baubewilligungen für Wohneinheiten in Österreich 2013 und 2014. Teilbericht 4," WIFO Studies, WIFO, number 67111.
    9. Michael Klien & Andrea Kunnert, 2014. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose 2014 und 2015," WIFO Studies, WIFO, number 58603.
    10. Andrea Kunnert, 2013. "Baubewilligungen für Wohneinheiten in Österreich: Prognose 2012/2014 und regionale Entwicklung 2006/2011," WIFO Studies, WIFO, number 46678.
    11. Andrea Kunnert, 2012. "Prognose der Wohnbaubewilligungen für Wohneinheiten in Österreich 2012 und 2013. Teilbericht 1," WIFO Studies, WIFO, number 67109.
    12. Dieter Pennerstorfer & Andrea Kunnert & Peter Huber, 2014. "Baubewilligungen für neue Wohneinheiten in Österreich. Prognose 2013/2015 – Teilbericht 2," WIFO Studies, WIFO, number 58600.

  61. Stekler, H O, 1975. "Why do Forecasters Underestimate?," Economic Inquiry, Western Economic Association International, vol. 13(3), pages 445-449, September.

    Cited by:

    1. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    2. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    3. Crosetto, P. & Filippin, A. & Katuscak, P. & Smith, J., 2019. "Central tendency bias in belief elicitation," Working Papers 2019-04, Grenoble Applied Economics Laboratory (GAEL).

  62. Stekler, H O, 1972. "An Analysis of Turning Point Forecasts," American Economic Review, American Economic Association, vol. 62(4), pages 724-729, September.

    Cited by:

    1. Monokroussos, George, 2015. "Nowcasting in Real Time Using Popularity Priors," MPRA Paper 68594, University Library of Munich, Germany.
    2. Chua, Chew Lian & Tsiaplias, Sarantis, 2011. "Predicting economic contractions and expansions with the aid of professional forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 438-451, April.
    3. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    4. Daniel Culbertson & Tara Sinclair, 2014. "The Failure of Forecasts in the Great Recession," Challenge, Taylor & Francis Journals, vol. 57(6), pages 34-45.
    5. Kosei Fukuda, 2009. "Forecasting growth cycle turning points using US and Japanese professional forecasters," Empirical Economics, Springer, vol. 36(2), pages 243-267, May.
    6. Fintzen, David & Stekler, H. O., 1999. "Why did forecasters fail to predict the 1990 recession?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 309-323, July.
    7. 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.
    8. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    9. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    10. Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
    11. 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.
    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. 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.
    14. Stekler, H. O., 2003. "Improving our ability to predict the unusual event," International Journal of Forecasting, Elsevier, vol. 19(2), pages 161-163.
    15. Gabriel Mathy & Yongchen Zhao, 2025. "Could Diffusion Indexes Have Forecasted the Great Depression?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 320-338, March.
    16. John B. Guerard, 2024. "Sir David Hendry: An Appreciation from Wall Street and What Macroeconomics Got Right," Working Papers 2024-001, The George Washington University, The Center for Economic Research, revised Feb 2024.

  63. Enzler, Jared J & Stekler, H O, 1971. "An Analysis of the 1968-69 Economic Forecasts," The Journal of Business, University of Chicago Press, vol. 44(3), pages 271-281, July.

    Cited by:

    1. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, The Center for Economic Research.
    2. Tara Sinclair, 2008. "Asymmetry in the Business Model: Revisiting the Friedman Plucking Model," Working Papers 2008-03, The George Washington University, Institute for International Economic Policy.
    3. Sinclair Tara M, 2009. "Asymmetry in the Business Cycle: Friedman's Plucking Model with Correlated Innovations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-31, December.

  64. Stekler, H O, 1969. "Evaluation of Econometric Inventory Forecasts," The Review of Economics and Statistics, MIT Press, vol. 51(1), pages 77-83, February.

    Cited by:

    1. Victor Zarnowitz & Louis A. Lambros, 1983. "Consensus and Uncertainty in Economic Prediction," NBER Working Papers 1171, National Bureau of Economic Research, Inc.

  65. H. O. Stekler, 1968. "An Evaluation of Quarterly Judgmental Economic Forecasts," The Journal of Business, University of Chicago Press, vol. 41, pages 329-329.

    Cited by:

    1. Tsuchiya, Yoichi, 2016. "Do production managers predict turning points? A directional analysis," Economic Modelling, Elsevier, vol. 58(C), pages 1-8.
    2. Rolando Pelàez, 2007. "Ex ante forecasts of business-cycle turning points," Empirical Economics, Springer, vol. 32(1), pages 239-246, April.
    3. Joutz, Fred & Stekler, H. O., 2000. "An evaluation of the predictions of the Federal Reserve," International Journal of Forecasting, Elsevier, vol. 16(1), pages 17-38.
    4. Kosei Fukuda, 2009. "Forecasting growth cycle turning points using US and Japanese professional forecasters," Empirical Economics, Springer, vol. 36(2), pages 243-267, May.
    5. Sergey Smirnov, 2011. "Those Unpredictable Recessions," HSE Working papers WP BRP 02/EC/2011, National Research University Higher School of Economics.
    6. Geoffrey H. Moore, 1983. "Forecasting Short-Term Economic Change," NBER Chapters, in: Business Cycles, Inflation, and Forecasting, 2nd edition, pages 401-432, National Bureau of Economic Research, Inc.

  66. H. O. Stekler, 1967. "The Federal Budget as a Short-Term Forecasting Tool," The Journal of Business, University of Chicago Press, vol. 40, pages 280-280.

    Cited by:

    1. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).

  67. S. S. Alexander & H. O. Stekler, 1959. "Forecasting Industrial Production--Leading Series versus Autoregression," Journal of Political Economy, University of Chicago Press, vol. 67(4), pages 402-402.

    Cited by:

    1. de Bondt, Gabe J. & Dieden, Heinz C. & Muzikarova, Sona & Vincze, Istvan, 2014. "Modelling industrial new orders," Economic Modelling, Elsevier, vol. 41(C), pages 46-54.
    2. Neil R. Ericsson, 2017. "How Biased Are U.S. Government Forecasts of the Federal Debt?," International Finance Discussion Papers 1189, Board of Governors of the Federal Reserve System (U.S.).
    3. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, The Center for Economic Research.
    4. de Bondt, Gabe & Dieden, Heinz Christian & Muzikarova, Sona & Vincze, Istvan, 2014. "Modelling industrial new orders for the euro area," Statistics Paper Series 6, European Central Bank.
    5. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
    6. Gabe de Bondt & Heinz C. Dieden & Sona Muzikarova & Istvan Vincze, 2013. "Modeling Euro Area Industrial New Orders," EcoMod2013 5663, EcoMod.
    7. Herman O. Stekler & Tianyu Ye, 2017. "Evaluating a leading indicator: an application—the term spread," Empirical Economics, Springer, vol. 53(1), pages 183-194, August.

Chapters

  1. S. S. L. Chang & H. O. Stekler, 1977. "Fuzziness in Economic Systems, Its Modeling and Control," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 6, number 2, pages 165-174, National Bureau of Economic Research, Inc.

    Cited by:

    1. Caleiro, António, 2003. "Subjective Versus Objective Economic Measures. A fuzzy logic exercise," EconStor Preprints 142693, ZBW - Leibniz Information Centre for Economics.
    2. Caleiro, António, 2005. "How is Confidence Related to Unemployment in Europe? A fuzzy logic answer," EconStor Preprints 142734, ZBW - Leibniz Information Centre for Economics.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.