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Roy Batchelor

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.

Working papers

  1. Roy Batchelor, 2007. "Forecaster Behaviour and Bias in Macroeconomic Forecasts," ifo Working Paper Series 39, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

    Cited by:

    1. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    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. Michael Pedersen, 2020. "Surveying the survey: What can we learn about the effects of monetary policy on inflation expectations?," Working Papers Central Bank of Chile 889, Central Bank of Chile.
    4. Pedersen, Michael, 2015. "What affects the predictions of private forecasters? The role of central bank forecasts in Chile," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1043-1055.
    5. Dovern, Jonas, 2014. "A Multivariate Analysis of Forecast Disagreement: Confronting Models of Disagreement with SPF Data," Working Papers 0571, University of Heidelberg, Department of Economics.
    6. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    7. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    8. Jonas Dovern & Ulrich Fritsche & Prakash Loungani & Natalia Tamirisa, 2014. "Information Rigidities: Comparing Average And Individual Forecasts For A Large International Panel," Working Papers 2014-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    9. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
    10. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    11. Fotis Mouzakis & Dimitrios Papastamos & Simon Stevenson, 2015. "Rationality and Momentum in Real Estate Investment Forecasts," ERES eres2015_297, European Real Estate Society (ERES).
    12. Boussios, David & Skorbiansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," Economic Research Report 327201, United States Department of Agriculture, Economic Research Service.
    13. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," CIRJE F-Series CIRJE-F-729, CIRJE, Faculty of Economics, University of Tokyo.
    14. 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.
    15. José Daniel Aromí, 2021. "Large Current Account Deficits and Neglected Vulnerabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 69(4), pages 597-623, December.
    16. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2006. "Uncertainty and disagreement in economic prediction: the Bank of England Survey of External Forecasters," Economic Research Papers 269751, University of Warwick - Department of Economics.
    17. 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 (IfW Kiel).
    18. 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.
    19. Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    21. Filip Novotny & Marie Rakova, 2010. "Assessment of Consensus Forecasts Accuracy: The Czech National Bank Perspective," Working Papers 2010/14, Czech National Bank.
    22. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, 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. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    25. Boussios, David & Skoriansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309619, United States Department of Agriculture.
    26. 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.
    27. Michael J. Lamla & Thomas Maag, 2012. "The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1325-1350, October.
    28. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    29. 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.
    30. Marcell Göttert & Robert Lehmann, 2021. "Tax Revenue Forecast Errors: Wrong Predictions of the Tax Base or the Elasticity?," CESifo Working Paper Series 9148, CESifo.
    31. Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    32. Dovern, Jonas & Weisser, Johannes, 2008. "Are they really rational? Assessing professional macro-economic forecasts from the G7-countries," Kiel Working Papers 1447, Kiel Institute for the World Economy (IfW Kiel).
    33. 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.
    34. Bruno Deschamps, 2015. "Are aggregate corporate earnings forecasts unbiased and efficient?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 803-818, November.
    35. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    36. Leandro D�Aurizio & Stefano Iezzi, 2011. "Investment forecasting with business survey data," Temi di discussione (Economic working papers) 832, Bank of Italy, Economic Research and International Relations Area.
    37. Gaurav Kumar Singh & Tathagata Bandyopadhyay, 2024. "Determinants of disagreement: Learning from inflation expectations survey of households," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 326-343, March.
    38. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
    39. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    40. Angelo Mont’Alverne Duarte & Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & João Victor Issler, 2020. "Commodity Prices and Global Economic Activity: a derived-demand approach," Working Papers Series 539, Central Bank of Brazil, Research Department.
    41. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    42. Higgins, Matthew L. & Mishra, Sagarika, 2012. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Working Papers fe_2012_10, Deakin University, Department of Economics.
    43. 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).
    44. Tillmann, Peter, 2011. "Strategic forecasting on the FOMC," European Journal of Political Economy, Elsevier, vol. 27(3), pages 547-553, September.
    45. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    46. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    47. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
    48. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
    49. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    50. 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.
    51. 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.
    52. Schupp, Claudia & Wache, Benjamin, 2014. "Wie groß ist der Einfluss von deutschen Wirtschaftsforschungsinstituten? Ein Ranking anhand von RePEc-Daten [How large is the influence of German economic research institutes? A ranking analysis us," MPRA Paper 55519, University Library of Munich, Germany.
    53. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
    54. Constantin ANGHELACHE & Cristina SACALA, 2016. "Theoretical model used for macroeconomic analysis," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(7), pages 57-60, July.
    55. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.
    56. Barrera, Carlos, 2022. "Les Prévisions des Prévisionnistes Professionnels? Perou, 2009-2017 [Professional Forecasters' Expectations? Peru, 2009-2017]," MPRA Paper 114420, University Library of Munich, Germany.
    57. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economics Research Papers 2009-091, Friedrich-Schiller-University Jena.
    58. Tsuchiya, Yoichi, 2016. "Assessing macroeconomic forecasts for Japan under an asymmetric loss function," International Journal of Forecasting, Elsevier, vol. 32(2), pages 233-242.
    59. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    60. 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.
    61. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    62. Dovern, Jonas & Jannsen, Nils, 2017. "Systematische Prognosefehler in unterschiedlichen Konjunkturphasen," Kiel Insight 2017.15, Kiel Institute for the World Economy (IfW Kiel).
    63. 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.
    64. 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.
    65. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    66. Monica Jain, 2018. "Sluggish Forecasts," Staff Working Papers 18-39, Bank of Canada.
    67. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    68. 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.
    69. 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.
    70. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," EconomiX Working Papers 2015-17, University of Paris Nanterre, EconomiX.
    71. Boussios, David & Skorbiansky, Sharon Raszap & Maclachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309616, United States Department of Agriculture.
    72. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    73. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    74. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," Working Papers hal-04141409, HAL.

Articles

  1. Roy Batchelor, 2009. "Forecasting Sharp Changes," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 13, pages 7-12, Spring.

    Cited by:

    1. Tobias F. Rötheli, 2018. "Should business rely on business cycle forecasting?," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(1), pages 121-133, March.

  2. Batchelor, Roy & Kwan, Tai Yeong, 2007. "Judgemental bootstrapping of technical traders in the bond market," International Journal of Forecasting, Elsevier, vol. 23(3), pages 427-445.

    Cited by:

    1. Adamantios Ntakaris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators," Papers 1907.09452, arXiv.org.
    2. Sobolev, Daphne, 2017. "The effect of price volatility on judgmental forecasts: The correlated response model," International Journal of Forecasting, Elsevier, vol. 33(3), pages 605-617.
    3. Yael Karlinsky-Shichor & Oded Netzer, 2024. "Automating the B2B Salesperson Pricing Decisions: A Human-Machine Hybrid Approach," Marketing Science, INFORMS, vol. 43(1), pages 138-157, January.

  3. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.

    Cited by:

    1. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    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. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    4. Michael Pedersen, 2020. "Surveying the survey: What can we learn about the effects of monetary policy on inflation expectations?," Working Papers Central Bank of Chile 889, Central Bank of Chile.
    5. Pedersen, Michael, 2015. "What affects the predictions of private forecasters? The role of central bank forecasts in Chile," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1043-1055.
    6. Dovern, Jonas, 2014. "A Multivariate Analysis of Forecast Disagreement: Confronting Models of Disagreement with SPF Data," Working Papers 0571, University of Heidelberg, Department of Economics.
    7. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    8. Jonas Dovern & Ulrich Fritsche & Prakash Loungani & Natalia Tamirisa, 2014. "Information Rigidities: Comparing Average And Individual Forecasts For A Large International Panel," Working Papers 2014-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    9. Aromí, J. Daniel, 2019. "Medium term growth forecasts: Experts vs. simple models," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1085-1099.
    10. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    11. Fotis Mouzakis & Dimitrios Papastamos & Simon Stevenson, 2015. "Rationality and Momentum in Real Estate Investment Forecasts," ERES eres2015_297, European Real Estate Society (ERES).
    12. Boussios, David & Skorbiansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," Economic Research Report 327201, United States Department of Agriculture, Economic Research Service.
    13. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," CIRJE F-Series CIRJE-F-729, CIRJE, Faculty of Economics, University of Tokyo.
    14. 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.
    15. José Daniel Aromí, 2021. "Large Current Account Deficits and Neglected Vulnerabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 69(4), pages 597-623, December.
    16. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2006. "Uncertainty and disagreement in economic prediction: the Bank of England Survey of External Forecasters," Economic Research Papers 269751, University of Warwick - Department of Economics.
    17. 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 (IfW Kiel).
    18. 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.
    19. Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    21. Filip Novotny & Marie Rakova, 2010. "Assessment of Consensus Forecasts Accuracy: The Czech National Bank Perspective," Working Papers 2010/14, Czech National Bank.
    22. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, 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. Jonas Dovern & Ulrich Fritsche, 2008. "Estimating Fundamental Cross-Section Dispersion from Fixed Event Forecasts," Discussion Papers of DIW Berlin 787, DIW Berlin, German Institute for Economic Research.
    25. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    26. Boussios, David & Skoriansky, Sharon Raszap & MacLachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309619, United States Department of Agriculture.
    27. 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.
    28. Michael J. Lamla & Thomas Maag, 2012. "The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1325-1350, October.
    29. Tsuchiya, Yoichi, 2023. "Assessing the World Bank’s growth forecasts," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 64-84.
    30. 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.
    31. Marcell Göttert & Robert Lehmann, 2021. "Tax Revenue Forecast Errors: Wrong Predictions of the Tax Base or the Elasticity?," CESifo Working Paper Series 9148, CESifo.
    32. Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    33. Dovern, Jonas & Weisser, Johannes, 2008. "Are they really rational? Assessing professional macro-economic forecasts from the G7-countries," Kiel Working Papers 1447, Kiel Institute for the World Economy (IfW Kiel).
    34. 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.
    35. Bruno Deschamps, 2015. "Are aggregate corporate earnings forecasts unbiased and efficient?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 803-818, November.
    36. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    37. Leandro D�Aurizio & Stefano Iezzi, 2011. "Investment forecasting with business survey data," Temi di discussione (Economic working papers) 832, Bank of Italy, Economic Research and International Relations Area.
    38. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
    39. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    40. Angelo Mont’Alverne Duarte & Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & João Victor Issler, 2020. "Commodity Prices and Global Economic Activity: a derived-demand approach," Working Papers Series 539, Central Bank of Brazil, Research Department.
    41. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    42. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    43. Higgins, Matthew L. & Mishra, Sagarika, 2012. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Working Papers fe_2012_10, Deakin University, Department of Economics.
    44. Singh, Gaurav Kumar & Bandyopadhyay, Tathagata, 2021. "Determinants of Disagreement: Learning from Indian Inflation Expectations Survey of Households," IIMA Working Papers WP 2021-01-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    45. 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).
    46. Tillmann, Peter, 2011. "Strategic forecasting on the FOMC," European Journal of Political Economy, Elsevier, vol. 27(3), pages 547-553, September.
    47. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    48. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    49. Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzán, Alfred G., 2014. "Combining forecasts: An application to elections," International Journal of Forecasting, Elsevier, vol. 30(1), pages 43-54.
    50. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
    51. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2014. "Evaluating Macroeconomic Forecasts: A Concise Review Of Some Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 195-208, April.
    52. 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.
    53. 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.
    54. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
    55. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
    56. Constantin ANGHELACHE & Cristina SACALA, 2016. "Theoretical model used for macroeconomic analysis," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(7), pages 57-60, July.
    57. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.
    58. Barrera, Carlos, 2022. "Les Prévisions des Prévisionnistes Professionnels? Perou, 2009-2017 [Professional Forecasters' Expectations? Peru, 2009-2017]," MPRA Paper 114420, University Library of Munich, Germany.
    59. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economics Research Papers 2009-091, Friedrich-Schiller-University Jena.
    60. Tsuchiya, Yoichi, 2016. "Assessing macroeconomic forecasts for Japan under an asymmetric loss function," International Journal of Forecasting, Elsevier, vol. 32(2), pages 233-242.
    61. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    62. 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.
    63. 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.
    64. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    65. Dovern, Jonas & Jannsen, Nils, 2017. "Systematische Prognosefehler in unterschiedlichen Konjunkturphasen," Kiel Insight 2017.15, Kiel Institute for the World Economy (IfW Kiel).
    66. 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.
    67. 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.
    68. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    69. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    70. Monica Jain, 2018. "Sluggish Forecasts," Staff Working Papers 18-39, Bank of Canada.
    71. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    72. 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.
    73. 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.
    74. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," EconomiX Working Papers 2015-17, University of Paris Nanterre, EconomiX.
    75. Boussios, David & Skorbiansky, Sharon Raszap & Maclachlan, Matthew, 2021. "Evaluating U.S. Department of Agriculture’s Long-Term Forecasts for U.S. Harvested Area," USDA Miscellaneous 309616, United States Department of Agriculture.
    76. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    77. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    78. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," Working Papers hal-04141409, HAL.

  4. Batchelor, Roy & Alizadeh, Amir & Visvikis, Ilias, 2007. "Forecasting spot and forward prices in the international freight market," International Journal of Forecasting, Elsevier, vol. 23(1), pages 101-114.

    Cited by:

    1. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    2. Jingbo Yin & Meifeng Luo & Lixian Fan, 2017. "Dynamics and interactions between spot and forward freights in the dry bulk shipping market," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(2), pages 271-288, February.
    3. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    4. Sel, Burakhan & Minner, Stefan, 2022. "A hedging policy for seaborne forward freight markets based on probabilistic forecasts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    5. Alizadeh, Amir H. & Huang, Chih-Yueh & van Dellen, Stefan, 2015. "A regime switching approach for hedging tanker shipping freight rates," Energy Economics, Elsevier, vol. 49(C), pages 44-59.
    6. Regli, Frederik & Adland, Roar, 2019. "Crude oil contango arbitrage and the floating storage decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 100-118.
    7. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.
    8. Alizadeh, Amir H., 2013. "Trading volume and volatility in the shipping forward freight market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 250-265.
    9. Saeed, Naima & Nguyen, Su & Cullinane, Kevin & Gekara, Victor & Chhetri, Prem, 2023. "Forecasting container freight rates using the Prophet forecasting method," Transport Policy, Elsevier, vol. 133(C), pages 86-107.
    10. Yuting Gong & Xueqin Wang & Mo Zhu & Ying‐En Ge & Wenming Shi, 2023. "Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 69-89, January.
    11. Fotis Papailias & Dimitrios D. Thomakos, 2013. "The Baltic Dry Index: Cyclicalities, Forecasting and Hedging Strategies," Working Paper series 65_13, Rimini Centre for Economic Analysis.
    12. Payman Eslami & Kihyo Jung & Daewon Lee & Amir Tjolleng, 2017. "Predicting tanker freight rates using parsimonious variables and a hybrid artificial neural network with an adaptive genetic algorithm," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 538-550, August.
    13. Ziaul Haque Munim & Hans-Joachim Schramm, 2017. "Forecasting container shipping freight rates for the Far East – Northern Europe trade lane," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 106-125, March.
    14. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    15. Wenming Shi & Kevin X. Li, 2017. "Themes and tools of maritime transport research during 2000-2014," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(2), pages 151-169, February.
    16. Miao Su & Keun Sik Park & Sung Hoon Bae, 2024. "A new exploration in Baltic Dry Index forecasting learning: application of a deep ensemble model," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(1), pages 21-43, March.
    17. 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.
    18. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
    19. Alexandridis, G. & Sahoo, S. & Visvikis, I., 2017. "Economic information transmissions and liquidity between shipping markets: New evidence from freight derivatives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 82-104.
    20. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    21. Adland, Roar & Alizadeh, Amir H., 2018. "Explaining price differences between physical and derivative freight contracts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 20-33.
    22. Konstantinos Gavriilidis & Dimos S. Kambouroudis & Katerina Tsakou & Dimitris S. Tsouknidis, 2018. "Volatility forecasting across tanker freight rates: the role of oil price shocks," Working Papers 2018-27, Swansea University, School of Management.
    23. N.D. Geomelos & E. Xideas, 2014. "Forecasting spot prices in bulk shipping using multivariate and univariate models," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-37, December.
    24. Jason Angelopoulos, 2017. "Time–frequency analysis of the Baltic Dry Index," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(2), pages 211-233, June.
    25. Wetzstein, Brian & Florax, Raymond & Foster, Kenneth & Binkley, James, 2021. "Transportation costs: Mississippi River barge rates," Journal of Commodity Markets, Elsevier, vol. 21(C).
    26. Manolis G. Kavussanos & Ilias D. Visvikis, 2011. "The Predictability of Non-Overlapping Forecasts: Evidence from a New Market," Multinational Finance Journal, Multinational Finance Journal, vol. 15(1-2), pages 125-156, March - J.
    27. Pouliasis, Panos K. & Papapostolou, Nikos C. & Kyriakou, Ioannis & Visvikis, Ilias D., 2018. "Shipping equity risk behavior and portfolio management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 178-200.
    28. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
    29. Regli, Frederik & Nomikos, Nikos K., 2019. "The eye in the sky – Freight rate effects of tanker supply," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 402-424.
    30. Sun, Xiaolei & Tang, Ling & Yang, Yuying & Wu, Dengsheng & Li, Jianping, 2014. "Identifying the dynamic relationship between tanker freight rates and oil prices: In the perspective of multiscale relevance," Economic Modelling, Elsevier, vol. 42(C), pages 287-295.
    31. Wolfgang Bessler & Wolfgang Drobetz & Jörg Seidel, 2008. "Ship funds as a new asset class: An empirical analysis of the relationship between spot and forward prices in freight markets," Journal of Asset Management, Palgrave Macmillan, vol. 9(2), pages 102-120, July.
    32. Sun, Xiaolin & Haralambides, Hercules & Liu, Hailong, 2019. "Dynamic spillover effects among derivative markets in tanker shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 384-409.
    33. Abouarghoub, Wessam & Nomikos, Nikos K. & Petropoulos, Fotios, 2018. "On reconciling macro and micro energy transport forecasts for strategic decision making in the tanker industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 225-238.
    34. Yang, Linghubo & Zhang, Dongxiang, 2013. "Can futures price be a powerful predictor? Frequency domain analysis on Chinese commodity market," Economic Modelling, Elsevier, vol. 35(C), pages 264-271.
    35. Ioannis Karaoulanis & Theodore Pelagidis, 2021. "Panamax markets behaviour: explaining volatility and expectations," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-24, December.
    36. Pelagidis, Theodore & Karaoulanis, Ioannis, 2021. "Capesize markets behavior: Explaining volatility and expectations," MPRA Paper 107034, University Library of Munich, Germany.
    37. Daniel Leonhardt & Antony Ware & Rudi Zagst, 2017. "A Cointegrated Regime-Switching Model Approach with Jumps Applied to Natural Gas Futures Prices," Risks, MDPI, vol. 5(3), pages 1-19, September.
    38. Spyros Makridakis & Andreas Merikas & Anna Merika & Mike G. Tsionas & Marwan Izzeldin, 2020. "A novel forecasting model for the Baltic dry index utilizing optimal squeezing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 56-68, January.
    39. Evangelia Kasimati & Nikolaos Veraros, 2017. "Is there accuracy of forward freight agreements in forecasting future freight rates? An empirical investigation," Working Papers 230, Bank of Greece.
    40. Ko, Byoung-Wook, 2018. "Dynamic patterns of dry bulk freight spot rates through the lens of a time-varying coefficient model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 319-330.
    41. Amir Alizadeh & Konstantina Kappou & Dimitris Tsouknidis & Ilias Visvikis, 2014. "Liquidity Risk Premia in the International Shipping Derivatives Market," ICMA Centre Discussion Papers in Finance icma-dp2014-15, Henley Business School, University of Reading.
    42. Georgios I. Papayiannis, 2022. "Static Hedging of Freight Risk under Model Uncertainty," Papers 2207.00862, arXiv.org.
    43. Christos Katris & Manolis G. Kavussanos, 2021. "Time series forecasting methods for the Baltic dry index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1540-1565, December.
    44. Zhang, X. & Chen, M.Y. & Wang, M.G. & Ge, Y.E. & Stanley, H.E., 2019. "A novel hybrid approach to Baltic Dry Index forecasting based on a combined dynamic fluctuation network and artificial intelligence method," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 499-516.
    45. Mhd Ruslan, Siti Marsila & Mokhtar, Kasypi, 2021. "Stock market volatility on shipping stock prices: GARCH models approach," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    46. Alizadeh, Amir H. & Kappou, Konstantina & Tsouknidis, Dimitris & Visvikis, Ilias, 2015. "Liquidity effects and FFA returns in the international shipping derivatives market," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 58-75.
    47. Alizadeh, Amir H. & Talley, Wayne K., 2011. "Vessel and voyage determinants of tanker freight rates and contract times," Transport Policy, Elsevier, vol. 18(5), pages 665-675, September.
    48. Shangkun Deng & Yingke Zhu & Xiaoru Huang & Shuangyang Duan & Zhe Fu, 2022. "High-Frequency Direction Forecasting of the Futures Market Using a Machine-Learning-Based Method," Future Internet, MDPI, vol. 14(6), pages 1-21, June.
    49. Evangelia Kasimati & Nikolaos Veraros, 2018. "Accuracy of forward freight agreements in forecasting future freight rates," Applied Economics, Taylor & Francis Journals, vol. 50(7), pages 743-756, February.
    50. Ziaul Haque Munim & Hans-Joachim Schramm, 2021. "Forecasting container freight rates for major trade routes: a comparison of artificial neural networks and conventional models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 310-327, June.
    51. Amir Alizadeh & Wayne Talley, 2011. "Microeconomic determinants of dry bulk shipping freight rates and contract times," Transportation, Springer, vol. 38(3), pages 561-579, May.

  5. Roy Batchelor & Katiuscia Manzoni, 2006. "The Dynamics Of Bond Yield Spreads Around Rating Revision Dates," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(3), pages 405-420, September.

    Cited by:

    1. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).
    2. Christopher A. Hartwell & Paul M. Vaaler, 2023. "The Price of Empire: Unrest Location and Sovereign Risk in Tsarist Russia," Papers 2309.06885, arXiv.org, revised Nov 2023.
    3. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.

  6. Armstrong, J. Scott, 2002. ""How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus": Batchelor, Roy (2001), Applied Economics, 33, pp. 225-235. E-mail address: R.A.Batchelor@," International Journal of Forecasting, Elsevier, vol. 18(3), pages 482-483.

    Cited by:

    1. 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.

  7. Roy Batchelor, 2001. "Confidence indexes and the probability of recession: a Markov switching model," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 36(1), pages 107-124, January.

    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. Maximo Camacho & Fernando Soto, 2018. "Consumer confidence’s boom and bust in Latin America," Working Papers 18/02, BBVA Bank, Economic Research Department.
    3. Hamid Baghestani & Ajalavat Viriyavipart, 2019. "Do factors influencing consumer home-buying attitudes explain output growth?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1104-1115, August.
    4. Mark J. Holmes & Brian Silverstone, 2010. "Business confidence and cyclical turning points: a Markov-switching approach," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 229-233, February.
    5. Ahmed, Walid M.A., 2020. "Stock market reactions to domestic sentiment: Panel CS-ARDL evidence," Research in International Business and Finance, Elsevier, vol. 54(C).
    6. 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.
    7. 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).

  8. Batchelor, Roy & Peel, David A., 1998. "Rationality testing under asymmetric loss," Economics Letters, Elsevier, vol. 61(1), pages 49-54, October.

    Cited by:

    1. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    2. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    3. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    4. Goodwin, Paul, 2005. "Providing support for decisions based on time series information under conditions of asymmetric loss," European Journal of Operational Research, Elsevier, vol. 163(2), pages 388-402, June.
    5. Christodoulakis, George A., 2005. "Financial forecasts in the presence of asymmetric loss aversion, skewness and excess kurtosis," Finance Research Letters, Elsevier, vol. 2(4), pages 227-233, December.
    6. Pierdzioch, Christian & Rülke, Jan-Christoph, 2013. "Do inflation targets anchor inflation expectations?," Economic Modelling, Elsevier, vol. 35(C), pages 214-223.
    7. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    8. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
    9. George A. Christodoulakis & Emmanuel C. Mamatzakis, 2008. "An assessment of the EU growth forecasts under asymmetric preferences," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 483-492.
    10. Christian Pierdzioch & Jan-Christoph Rülke & Georg Stadtmann, 2013. "Oil price forecasting under asymmetric loss," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2371-2379, June.
    11. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.
    12. Yakup ARI & Alexandros PAPADOPOULOS, 2016. "Bayesian Estimation Of The Parameters Of The Arch Model With Normal Innovations Using Lindley’S Approximation," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 217-234.
    13. 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.
    14. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.
    15. Nazaria Solferino & Robert Waldmann, 2010. "Predicting the signs of forecast errors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 476-485.
    16. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
    17. Lawrence, Michael & O'Connor, Marcus, 2005. "Judgmental forecasting in the presence of loss functions," International Journal of Forecasting, Elsevier, vol. 21(1), pages 3-14.
    18. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    19. Young Bin Ahn & Yoichi Tsuchiya, 2016. "Directional analysis of consumers’ forecasts of inflation in a small open economy: evidence from South Korea," Applied Economics, Taylor & Francis Journals, vol. 48(10), pages 854-864, February.
    20. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "On the loss function of the Bank of Canada: A note," Economics Letters, Elsevier, vol. 115(2), pages 155-159.
    21. Rohloff, Sebastian & Pierdzioch, Christian & Risse, Marian, 2014. "Fluctuations of the Real Exchange Rate, Real Interest Rates, and the Dynamics of the Price of Gold in a Small Open Economy," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100429, Verein für Socialpolitik / German Economic Association.
    22. Christian Pierdzioch & Jan-Christoph Rülke & Georg Stadtmann, 2012. "Exchange-rate forecasts and asymmetric loss: empirical evidence for the yen/dollar exchange rate," Applied Economics Letters, Taylor & Francis Journals, vol. 19(18), pages 1759-1763, December.
    23. Krol, Robert, 2013. "Evaluating state revenue forecasting under a flexible loss function," International Journal of Forecasting, Elsevier, vol. 29(2), pages 282-289.
    24. Conrad, Christian, 2017. "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168200, Verein für Socialpolitik / German Economic Association.
    25. Joerg Doepke & Ulrich Fritsche & Boriss Siliverstovs, 2009. "Evaluating German Business Cycle Forecasts Under an Asymmetric Loss Function," Macroeconomics and Finance Series 200905, University of Hamburg, Department of Socioeconomics.
    26. Rülke, Jan-Christoph & Pierdzioch, Christian, 2014. "Government Forecasts of Budget Balances Under Asymmetric Loss: International Evidence," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100317, Verein für Socialpolitik / German Economic Association.
    27. Mamatzakis, E. & Koutsomanoli-Filippaki, A., 2014. "Testing the rationality of DOE's energy price forecasts under asymmetric loss preferences," Energy Policy, Elsevier, vol. 68(C), pages 567-575.
    28. Higgins, Matthew L. & Mishra, Sagarika, 2012. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Working Papers fe_2012_10, Deakin University, Department of Economics.
    29. Bürgi, Constantin, 2017. "Bias, rationality and asymmetric loss functions," Economics Letters, Elsevier, vol. 154(C), pages 113-116.
    30. G. A. Christodoulakis & E. C. Mamatzakis, 2009. "Assessing the prudence of economic forecasts in the EU," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 583-606.
    31. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    32. Carl Bonham & Richard Cohen & Shigeyuki Abe, 2006. "The Rationality and Heterogeneity of Survey Forecasts of the Yen-Dollar Exchange Rate: A Reexamination," Working Papers 200611, University of Hawaii at Manoa, Department of Economics.
    33. MacDonald, Ronald & Nagayasu, Jun, 2015. "Currency forecast errors and carry trades at times of low interest rates: Evidence from survey data on the yen/dollar exchange rate," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 1-19.
    34. Tsuchiya, Yoichi, 2016. "Assessing macroeconomic forecasts for Japan under an asymmetric loss function," International Journal of Forecasting, Elsevier, vol. 32(2), pages 233-242.
    35. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2013. "A note on forecasting the prices of gold and silver: Asymmetric loss and forecast rationality," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(3), pages 294-301.
    36. Lena Dräger & Jan-Oliver Menz & Ulrich Fritsche, 2011. "Perceived Inflation under Loss Aversion," Macroeconomics and Finance Series 201105, University of Hamburg, Department of Socioeconomics.
    37. Ulu, Yasemin, 2013. "Multivariate test for forecast rationality under asymmetric loss functions: Recent evidence from MMS survey of inflation–output forecasts," Economics Letters, Elsevier, vol. 119(2), pages 168-171.
    38. Anatolyev, Stanislav, 2006. "Kernel estimation under linear-exponential loss," Economics Letters, Elsevier, vol. 91(1), pages 39-43, April.
    39. 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.
    40. Tsuchiya, Yoichi, 2012. "Evaluating Japanese corporate executives’ forecasts under an asymmetric loss function," Economics Letters, Elsevier, vol. 116(3), pages 601-603.

  9. Batchelor, Roy & Dua, Pami, 1998. "Improving macro-economic forecasts: The role of consumer confidence," International Journal of Forecasting, Elsevier, vol. 14(1), pages 71-81, March.

    Cited by:

    1. Blanka Škrabić Perić & Petar Sorić, 2018. "A Note on the “Economic Policy Uncertainty Index”," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(2), pages 505-526, June.
    2. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    3. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    4. Gikas Hardouvelis & Dimitrios Thomakos, 2007. "Consumer Confidence and Elections," Working Papers 0003, University of Peloponnese, Department of Economics.
    5. Pedersen, Michael, 2019. "Anomalies in macroeconomic prediction errors–evidence from Chilean private forecasters," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1100-1107.
    6. 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.
    7. Ivana Lolić & Marija Logarušić & Mirjana Čižmešija, 2022. "Recent Revision of the European Consumer Confidence Indicator: Is There any additional Space for Improvement?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(3), pages 845-863, February.
    8. Ahmed, M. Iqbal & Cassou, Steven P., 2016. "Does consumer confidence affect durable goods spending during bad and good economic times equally?," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 86-97.
    9. Bob McNabb & Karl Taylor, 2002. "Business Cycles and the Role of Confidence: Evidence from Europe," Discussion Papers in Economics 02/3, Division of Economics, School of Business, University of Leicester.
    10. Vuchelen, Jef, 2004. "Consumer sentiment and macroeconomic forecasts," Journal of Economic Psychology, Elsevier, vol. 25(4), pages 493-506, August.
    11. W. Jos Jansen & Niek J. Nahuis, 2004. "Which survey indicators are useful for monitoring consumption? Evidence from European countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 89-98.
    12. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    13. Hamid Baghestani & Ajalavat Viriyavipart, 2019. "Do factors influencing consumer home-buying attitudes explain output growth?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1104-1115, August.
    14. 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.
    15. Thomas A. Garrett & Ruben Hernandez-Murillo & Michael T. Owyang, 2005. "Does consumer sentiment predict regional consumption?," Review, Federal Reserve Bank of St. Louis, vol. 87(Mar), pages 123-135.
    16. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2007. "Consumer confidence in Europe : United in diversity," Other publications TiSEM ea8c3268-2c0b-4fcc-9d4a-6, Tilburg University, School of Economics and Management.
    17. Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023. "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 415-438, June.
    18. Allen N. Berger & Felix Irresberger & Raluca A. Roman, 2020. "Bank Size and Household Financial Sentiment: Surprising Evidence from University of Michigan Surveys of Consumers," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(S1), pages 149-191, October.
    19. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 2001. "Copycats and Common Swings: the Impact of the Use of Forecasts in Information Sets," Econometrics Working Papers Archive wp2001_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    20. 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.
    21. 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.
    22. Kevin Moran & Simplice Aime Nono, 2016. "Using Confidence Data to Forecast the Canadian Business Cycle," Cahiers de recherche 1606, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    23. Gallo, Giampiero M. & Granger, Clive William John & Jeon, Yongil, 1999. "The impact of the use of forecasts in information sets," Research Notes 99-7, Deutsche Bank Research.
    24. Caglayan, Mustafa & Xu, Bing, 2016. "Sentiment volatility and bank lending behavior," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 107-120.
    25. Sarah Gelper & Aurelie Lemmens & Christophe Croux, 2007. "Consumer sentiment and consumer spending: decomposing the Granger causal relationship in the time domain," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 1-11.
    26. Christos Papamichael & Nicoletta Pashourtidou, 2016. "The Role of Survey Data in the Construction of Short-term GDP Growth Forecasts," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 10(2), pages 77-109, December.
    27. 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.
    28. Dudek, Sławomir, 2008. "Consumer Survey Data and short-term forecasting of households consumption expenditures in Poland," MPRA Paper 19818, University Library of Munich, Germany.
    29. 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.
    30. Petar Sorić, 2018. "Consumer confidence as a GDP determinant in New EU Member States: a view from a time-varying perspective," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(2), pages 261-282, May.
    31. Giancarlo Bruno, 2014. "Consumer confidence and consumption forecast: a non-parametric approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(1), pages 37-52, February.
    32. Gelper, S. & Lemmens, A. & Croux, C., 2007. "Consumer sentiment and consumer spending : Decomposing the granger causal relationship in the time domain," Other publications TiSEM 55ac7230-2985-41f1-a42c-7, Tilburg University, School of Economics and Management.
    33. Hassan Gholipour Fereidouni & Reza Tajaddini, 2017. "Housing Wealth, Financial Wealth and Consumption Expenditure: The Role of Consumer Confidence," The Journal of Real Estate Finance and Economics, Springer, vol. 54(2), pages 216-236, February.
    34. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    35. Sudeshna Ghosh, 2021. "Consumer Confidence and Consumer Spending in Brazil: A Nonlinear Autoregressive Distributed Lag Model Analysis," Arthaniti: Journal of Economic Theory and Practice, , vol. 20(1), pages 53-85, June.
    36. James A Wilcox, 2015. "The Home Purchase Sentiment Index: A New Housing Indicator," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 50(4), pages 178-190, October.
    37. Qiu, Yue, 2020. "Forecasting the Consumer Confidence Index with tree-based MIDAS regressions," Economic Modelling, Elsevier, vol. 91(C), pages 247-256.
    38. E. Kilic & S. Cankaya, 2016. "Consumer confidence and economic activity: a factor augmented VAR approach," Applied Economics, Taylor & Francis Journals, vol. 48(32), pages 3062-3080, July.
    39. 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.
    40. Marco Malgarini & Patrizia Margani, 2005. "Psychology, consumer sentiment and household expenditures: a disaggregated analysis," ISAE Working Papers 58, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    41. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "The European Consumer: United In Diversity?," ERIM Report Series Research in Management ERS-2005-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    42. Charlotte Christiansen & Jonas Nygaard Eriksen & Stig V. Møller, 2013. "Forecasting US Recessions: The Role of Sentiments," CREATES Research Papers 2013-14, Department of Economics and Business Economics, Aarhus University.
    43. Syed Ateeb Akhter Shah & Fatima Kaneez & Arshad Riffat, 2022. "Forecasting the GDP Growth in Pakistan: The Role of Consumer Confidence," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 27(1), pages 68-88, Jan-June.
    44. Byrne, Joseph P & Lorusso, Marco & Xu, Bing, 2017. "Oil Prices and Informational Frictions: The Time-Varying Impact of Fundamentals and Expectations," MPRA Paper 80668, University Library of Munich, Germany.
    45. James Sprigg & Mark Ehlen, 2007. "Comparative dynamics in an overlapping-generations model: the effects of quasi-rational discrete choice on finding and maintaining Nash equilibrium," Computational Economics, Springer;Society for Computational Economics, vol. 29(1), pages 69-96, February.
    46. Lee, Tsung-Hsien Michael & Chen, Wenjuan, 2015. "Is there an asymmetric impact of housing on output?," SFB 649 Discussion Papers 2015-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    47. Miquel Clar & Juan-Carlos Duque & Rosina Moreno, 2007. "Forecasting business and consumer surveys indicators-a time-series models competition," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2565-2580.
    48. 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.
    49. Md. Kabir Ahmed Chowdhury & G.M. Abul Kalam Azad, 2010. "Consumer Confidence in Financial Markets," Working Papers id:3265, eSocialSciences.
    50. Mateus, Cesario & Chinthalapati, Raju & Mateus, Irina B., 2017. "Intraday industry-specific spillover effect in European equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 278-298.
    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.

  10. Batchelor, Roy & Gulley, David, 1995. "Jewellery demand and the price of gold," Resources Policy, Elsevier, vol. 21(1), pages 37-42, March.

    Cited by:

    1. Kittichok Nithisathian, 2011. "Comparative Study between the Thai and Hong Kong Fine Gold Jewelry Export Industries," Information Management and Business Review, AMH International, vol. 3(3), pages 139-147.
    2. Maria Immanuvel S & Daniel Lazar, 2022. "Does Volume of Gold Consumption Influence the World Gold Price?," JRFM, MDPI, vol. 15(7), pages 1-14, June.
    3. Ran Jing & Jiong Gong & Fang Yi, 2020. "Antitrust Fines: Experiences from China," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 57(1), pages 167-187, August.
    4. Sahoo, Manoranjan & Nayak, Pragyan Parimita & Hanhaga, Manindra & Swain, Kiranbala & Mallick, Rajat Kumar, 2023. "Exploring the asymmetric effect of remittance inflows on gold import demand: Evidence from a large gold-consuming and remittance-receiving country," Resources Policy, Elsevier, vol. 85(PB).
    5. Rockerbie, Duane W., 1999. "Gold prices and gold production: Evidence for South Africa," Resources Policy, Elsevier, vol. 25(2), pages 69-76, June.
    6. O'Connor, Fergal A. & Lucey, Brian M. & Batten, Jonathan A. & Baur, Dirk G., 2015. "The financial economics of gold — A survey," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 186-205.
    7. Ntim, Collins G. & English, John & Nwachukwu, Jacinta & Wang, Yan, 2015. "On the efficiency of the global gold markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 218-236.
    8. Osborne Jackson & Thu Tran, 2020. "Larceny in the Product Market: A Hidden Tax?," Working Papers 20-14, Federal Reserve Bank of Boston.
    9. S. Maria Immanuvel & D. Lazar, 2021. "Elasticities of Gold Demand—An Empirical Analysis Using Cointegration and Error Correction Model," Arthaniti: Journal of Economic Theory and Practice, , vol. 20(2), pages 131-142, December.
    10. Gülseven, Osman & Ekici, Özgün, 2016. "The Turkish appetite for gold: An Islamic explanation," Resources Policy, Elsevier, vol. 48(C), pages 41-49.
    11. Shafiee, Shahriar & Topal, Erkan, 2010. "An overview of global gold market and gold price forecasting," Resources Policy, Elsevier, vol. 35(3), pages 178-189, September.
    12. Mukherjee, Paramita & Mukherjee, Vivekananda & Das, Debasmita, 2017. "Estimating elasticity of import demand for gold in India," Resources Policy, Elsevier, vol. 51(C), pages 183-193.

  11. Batchelor, Roy & Dua, Pami, 1993. "Survey vs ARCH Measures of Inflation Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 55(3), pages 341-353, August.

    Cited by:

    1. da Silva Filho, Tito Nícias Teixeira, 2005. "Is there too much certainty when measuring uncertainty," MPRA Paper 16383, University Library of Munich, Germany.
    2. Kajal Lahiri & Xuguang Sheng, 2008. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," ifo Working Paper Series 60, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Kajal Lahiri & Fushang Liu, 2006. "Modelling multi‐period inflation uncertainty using a panel of density forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1199-1219, December.
    4. 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, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. John Thornton, 2007. "The Relationship between Inflation and Inflation Uncertainty in Emerging Market Economies," Southern Economic Journal, John Wiley & Sons, vol. 73(4), pages 858-870, April.
    6. Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2014. "Inflation uncertainty revisited: a proposal for robust measurement," Empirical Economics, Springer, vol. 47(4), pages 1497-1523, December.
    7. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    8. Mailand, Wilhelm, 1998. "Zum Einfluß von Unsicherheit auf die gesamtwirtschaftliche Investitionstätigkeit," HWWA Discussion Papers 57, Hamburg Institute of International Economics (HWWA).
    9. Jagjit S. Chadha & Lucio Sarno, 2002. "Short‐ and long‐run price level uncertainty under different monetary policy regimes: an international comparison," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(3), pages 183-212, July.
    10. Mailand, Wilhelm, 1998. "Zum Einfluss von Unsicherheit auf die gesamtwirtschaftliche Investitionstatigkeit," Discussion Paper Series 26305, Hamburg Institute of International Economics.

  12. Batchelor, Roy & Dua, Pami, 1992. "Survey Expectations in the Time Series Consumption Function," The Review of Economics and Statistics, MIT Press, vol. 74(4), pages 598-606, November.

    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. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    3. Sheldon H. Stein & Frank Song, 1998. "The Textbook Consumption Function: A Recent Empirical Irregularity, a Comment," The American Economist, Sage Publications, vol. 42(1), pages 112-118, March.
    4. 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.
    5. 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.
    6. 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.
    7. Berk, Jan Marc, 2000. "Consumers' inflation expectations and monetary policy in Europe," Serie Research Memoranda 0020, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. Jeffrey C. Fuhrer, 1993. "What role does consumer sentiment play in the U.S. macroeconomy?," New England Economic Review, Federal Reserve Bank of Boston, issue Jan, pages 32-44.
    9. 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.
    10. 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.
    11. Roberto Golinelli & Giuseppe Parigi, 2003. "What is this thing called confidence? A comparative analysis of consumer confidence indices in eight major countries," Temi di discussione (Economic working papers) 484, Bank of Italy, Economic Research and International Relations Area.
    12. Parigi, Giuseppe & Schlitzer, Giuseppe, 1997. "Predicting consumption of Italian households by means of survey indicators," International Journal of Forecasting, Elsevier, vol. 13(2), pages 197-209, June.
    13. Wärneryd, K.E., 1995. "Demystifying rational expectations theory through an economic-psychological model," Discussion Paper 1995-92, Tilburg University, Center for Economic Research.
    14. 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.
    15. Marc-André Gosselin & René Lalonde, 2003. "Un modèle « PAC » d'analyse et de prévision des dépense des ménages américains," Staff Working Papers 03-13, Bank of Canada.
    16. Luis Opazo, 2006. "The Backus-Smith Puzzle: The Role of Expectations," Working Papers Central Bank of Chile 395, Central Bank of Chile.
    17. Hamid Baghestani & Sehar Fatima, 2021. "Growth in US Durables Spending: Assessing the Impact of Consumer Ability and Willingness to Buy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 55-69, April.
    18. Tolar, Martin Michael, 1997. "A behavioral model of nondurable consumption expenditure," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 26(3), pages 291-302.

  13. Batchelor, Roy & Orr, Adrian, 1991. "Inflation uncertainty, inflationary shocks and the credibility of counterinflation policy," European Economic Review, Elsevier, vol. 35(7), pages 1385-1397, October.

    Cited by:

    1. Neven T. Valev & John A. Carlson, 2004. "Beliefs about Exchange-Rate Stability: Survey Evidence From the Currency Board in Bulgaria," William Davidson Institute Working Papers Series 2004-705, William Davidson Institute at the University of Michigan.
    2. N. T. Valev & J. A. Carlson, 2003. "Sources of dispersion in consumer inflation forecasts," Applied Economics Letters, Taylor & Francis Journals, vol. 10(2), pages 77-81.
    3. Conrad, Christian & Hartmann, Matthias, 2014. "Cross-sectional evidence on the relation between monetary policy, macroeconomic conditions and low-frequency inflation uncertainty," Working Papers 0574, University of Heidelberg, Department of Economics.
    4. David R. Johnson, 1997. "Expected Inflation in Canada 1988-1995: An Evaluation of Bank of Canada Credibility and the Effect of Inflation Targets," Canadian Public Policy, University of Toronto Press, vol. 23(3), pages 233-258, September.

  14. Batchelor, Roy & Dua, Pami, 1991. "Blue Chip Rationality Tests," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 23(4), pages 692-705, November.

    Cited by:

    1. Kurz, Mordecai & Motolese, Maurizio, 2006. "Risk Premia, diverse belief and beauty contests," MPRA Paper 247, University Library of Munich, Germany.
    2. Min Fan, 2006. "Heterogeneous Beliefs, the Term Structure and Time-varying Risk Premia," Annals of Finance, Springer, vol. 2(3), pages 259-285, July.
    3. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    4. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
    5. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    6. Michael Frenkel & Jin-Kyu Jung & Jan-Christoph Rülke, 2022. "Testing for the rationality of central bank interest rate forecasts," Empirical Economics, Springer, vol. 62(3), pages 1037-1078, March.
    7. Georges Prat & Remzi Uctum, 2016. "Do markets learn to rationally expect US interest rates? Evidence from survey data," Post-Print hal-01638220, HAL.
    8. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    9. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.
    10. Hori, Masahiro & 堀, 雅博 & Kawagoe, Masaaki, 2013. "Inflation Expectations Of Japanese Households: Micro Evidence From A Consumer Confidence Survey," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 54(1), pages 17-38, June.
    11. Baghestani, Hamid, 2009. "Survey evidence on forecast accuracy of U.S. term spreads," Review of Financial Economics, Elsevier, vol. 18(3), pages 156-162, August.
    12. Kurz, Mordecai, 2008. "Beauty contests under private information and diverse beliefs: How different?," Journal of Mathematical Economics, Elsevier, vol. 44(7-8), pages 762-784, July.
    13. Fotis Mouzakis & Dimitrios Papastamos & Simon Stevenson, 2015. "Rationality and Momentum in Real Estate Investment Forecasts," ERES eres2015_297, European Real Estate Society (ERES).
    14. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    15. Michael P. Clements, 2014. "Long-Run Restrictions and Survey Forecasts of Output, Consumption and Investment," ICMA Centre Discussion Papers in Finance icma-dp2014-02, Henley Business School, University of Reading.
    16. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    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. Loffler, Gunter, 2004. "An anatomy of rating through the cycle," Journal of Banking & Finance, Elsevier, vol. 28(3), pages 695-720, March.
    19. Baghestani, Hamid, 2010. "How well do experts predict interbank loan rates and spreads?," Economics Letters, Elsevier, vol. 109(1), pages 4-6, October.
    20. Roy Batchelor, 2007. "Forecaster Behaviour and Bias in Macroeconomic Forecasts," ifo Working Paper Series 39, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    21. Kurz, Mordecai & Piccillo, Giulia & Wu, Howei, 2013. "Modeling diverse expectations in an aggregated New Keynesian Model," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1403-1433.
    22. Julie Bennett & Michael T. Owyang, 2022. "On the Relative Performance of Inflation Forecasts," Review, Federal Reserve Bank of St. Louis, vol. 104(2), pages 131-148.
    23. 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.
    24. 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.
    25. Dovern, Jonas & Weisser, Johannes, 2008. "Are they really rational? Assessing professional macro-economic forecasts from the G7-countries," Kiel Working Papers 1447, Kiel Institute for the World Economy (IfW Kiel).
    26. 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.
    27. Gavin, William T. & Mandal, Rachel J., 2003. "Evaluating FOMC forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 655-667.
    28. 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.
    29. Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
    30. Georges Prat & Remzi Uctum, 2016. "Do markets learn to rationally expect US interest rates? Evidence from survey data," Working Papers hal-04141591, HAL.
    31. Carl S Bonham & Richard H Cohen, 2000. "Testing the Rational Expectations Hypothesis using Survey Data," Working Papers 200007, University of Hawaii at Manoa, Department of Economics.
    32. Kajal Lahiri & Gultekin Isiklar & 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.
    33. Hamid Baghestani, 2009. "Survey evidence on forecast accuracy of U.S. term spreads," Review of Financial Economics, John Wiley & Sons, vol. 18(3), pages 156-162, August.
    34. Batchelor, Roy & Dua, Pami, 1998. "Improving macro-economic forecasts: The role of consumer confidence," International Journal of Forecasting, Elsevier, vol. 14(1), pages 71-81, March.
    35. Mr. Christopher W. Crowe, 2010. "Consensus Forecasts and Inefficient Information Aggregation," IMF Working Papers 2010/178, International Monetary Fund.
    36. Jansen, Dennis W. & Kishan, Ruby Pandey, 1996. "An evaluation of federal reserve forecasting," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 89-109.
    37. Laurence Ball & Dean Croushore, 1998. "Expectations and the effects of monetary policy," Working Papers 98-13, Federal Reserve Bank of Philadelphia.
    38. Ronald MacDonald, 2000. "Expectations Formation and Risk in Three Financial Markets: Surveying What the Surveys Say," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 69-100, February.
    39. Masahiro Ashiya, 2009. "Strategic bias and professional affiliations of macroeconomic forecasters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 120-130.
    40. H. Bakhshi & G. Kapetanios & T. Yates, 2005. "Rational expectations and fixed-event forecasts: An application to UK inflation," Empirical Economics, Springer, vol. 30(3), pages 539-553, October.
    41. Chortareas, Georgios & Jitmaneeroj, Boonlert & Wood, Andrew, 2012. "Forecast rationality and monetary policy frameworks: Evidence from UK interest rate forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 209-231.
    42. 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.
    43. Hehui JIN, 2007. "Nominal Interest Rate Rules under Heterogeneous Beliefs," Rivista Internazionale di Scienze Sociali, Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore, vol. 115(3), pages 403-442.
    44. 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.
    45. Masahiro Ashiya, 2006. "Testing the rationality of forecast revisions made by the IMF and the OECD," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 25-36.
    46. Wärneryd, K.E., 1995. "Demystifying rational expectations theory through an economic-psychological model," Discussion Paper 1995-92, Tilburg University, Center for Economic Research.
    47. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
    48. Valente, Giorgio, 2009. "International interest rates and US monetary policy announcements: Evidence from Hong Kong and Singapore," Journal of International Money and Finance, Elsevier, vol. 28(6), pages 920-940, October.
    49. Mordecai Kurz, 2007. "Rational Diverse Beliefs and Economic Volatility," Discussion Papers 06-045, Stanford Institute for Economic Policy Research.
    50. Michael P. Clements, 2015. "Are Professional Macroeconomic Forecasters Able To Do Better Than Forecasting Trends?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(2-3), pages 349-382, March.
    51. Mordecai Kurz & Maurizio Motolese, 2011. "Diverse beliefs and time variability of risk premia," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 293-335, June.
    52. Robert W. Rich & Joseph Tracy, 2003. "Modeling uncertainty: predictive accuracy as a proxy for predictive confidence," Staff Reports 161, Federal Reserve Bank of New York.
    53. 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.
    54. 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.
    55. Michele Bagella & Leonardo Becchetti & Rocco Ciciretti, 2007. "Earning Forecast Error in US and European Stock Markets," The European Journal of Finance, Taylor & Francis Journals, vol. 13(2), pages 105-122.
    56. Karlyn Mitchell & Douglas K. Pearce, 2004. "Professional Forecasts of Interest Rates and Exchange Rates: Evidence from the Wall Street Journal's Panel of Economists," Working Paper Series 004, North Carolina State University, Department of Economics.
    57. Jordi Pons-Novell, 2003. "Strategic bias, herding behaviour and economic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 67-77.
    58. 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.
    59. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    60. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

  15. Batchelor, Roy A. & Dua, Pami, 1990. "Product differentiation in the economic forecasting industry," International Journal of Forecasting, Elsevier, vol. 6(3), pages 311-316, October.

    Cited by:

    1. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    2. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
    3. Fildes, Robert & Bretschneider, Stuart & Collopy, Fred & Lawrence, Michael & Stewart, Doug & Winklhofer, Heidi & Mentzer, John T. & Moon, Mark A., 2003. "Researching Sales Forecasting Practice: Commentaries and authors' response on "Conducting a Sales Forecasting Audit" by M.A. Moon, J.T. Mentzer & C.D. Smith," International Journal of Forecasting, Elsevier, vol. 19(1), pages 27-42.
    4. Richard H. Cohen & Carl Bonham, 2007. "Specifying the Forecast Generating Process for Exchange Rate Survey Forecasts," Working Papers 200718, University of Hawaii at Manoa, Department of Economics.
    5. Pierdzioch, Christian & Rülke, Jan Christoph & Stadtmann, Georg, 2010. "New evidence of anti-herding of oil-price forecasters," Energy Economics, Elsevier, vol. 32(6), pages 1456-1459, November.
    6. Roy Batchelor, 2007. "Forecaster Behaviour and Bias in Macroeconomic Forecasts," ifo Working Paper Series 39, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Ashiya, Masahiro, 2006. "Forecast accuracy and product differentiation of Japanese Institutional Forecasters," International Journal of Forecasting, Elsevier, vol. 22(2), pages 395-401.
    8. Christian Pierdzioch & Jan-Christoph Rülke & Georg Stadtmann, 2012. "A Note on Forecasting Emerging Market Exchange Rates: Evidence of Anti-herding," Review of International Economics, Wiley Blackwell, vol. 20(5), pages 974-984, November.
    9. Masahiro Ashiya, 2010. "Testing homogeneity of Japanese CPI forecasters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 435-441.
    10. Higgins, Matthew L. & Mishra, Sagarika, 2012. "State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth," Working Papers fe_2012_10, Deakin University, Department of Economics.
    11. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    12. Carl Bonham & Richard Cohen & Shigeyuki Abe, 2006. "The Rationality and Heterogeneity of Survey Forecasts of the Yen-Dollar Exchange Rate: A Reexamination," Working Papers 200611, University of Hawaii at Manoa, Department of Economics.
    13. Macdonald, Ronald & Marsh, Ian W., 1996. "Currency forecasters are heterogeneous: confirmation and consequences," Journal of International Money and Finance, Elsevier, vol. 15(5), pages 665-685, October.
    14. Wärneryd, K.E., 1995. "Demystifying rational expectations theory through an economic-psychological model," Discussion Paper 1995-92, Tilburg University, Center for Economic Research.
    15. Ali, Sara & Badshah, Ihsan & Demirer, Riza, 2023. "Anti-herding by hedge funds and its implications for expected returns," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 31-48.
    16. Sarah Chae & Robert F. Sarama & Cindy M. Vojtech & James Z. Wang, 2018. "The Impact of the Current Expected Credit Loss Standard (CECL) on the Timing and Comparability of Reserves," Finance and Economics Discussion Series 2018-020, Board of Governors of the Federal Reserve System (U.S.).
    17. Michael Jacobs, 2020. "A Holistic Model Validation Framework for Current Expected Credit Loss (CECL) Model Development and Implementation," IJFS, MDPI, vol. 8(2), pages 1-36, May.
    18. Pierdzioch, Christian & Schäfer, Dirk & Stadtmann, Georg, 2010. "Fly with the eagles or scratch with the chickens? Zum Herdenverhalten von Wechselkursprognostikern," Discussion Papers 287, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    19. 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.
    20. Cho, Dong W. & Hersch, Philip L., 1998. "Forecaster Characteristics and Forecast Outcomes," Journal of Economics and Business, Elsevier, vol. 50(1), pages 39-48, January.
    21. Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.

  16. Batchelor, R A, 1990. "All Forecasters Are Equal," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 143-144, January.

    Cited by:

    1. Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
    2. D'Agostino, Antonello & McQuinn, Kieran & Whelan, Karl, 2010. "Are Some Forecasters Really Better Than Others?," Research Technical Papers 5/RT/10, Central Bank of Ireland.
    3. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    4. Brice Corgnet & Cary Deck & Mark Desantis & David Porter, 2022. "Forecasting Skills in Experimental Market : Illusion or Reality?," Post-Print hal-04325544, HAL.
    5. Robert W. Rich & Joseph Tracy, 2021. "All Forecasters Are Not the Same: Time-Varying Predictive Ability across Forecast Environments," Working Papers 21-06, Federal Reserve Bank of Cleveland.
    6. 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, Department of Economics, H. O. Stekler Research Program on Forecasting.
    7. Döpke, Jörg & Waldhof, Gabi & Fritsche, Ulrich, 2018. "Theories, techniques and the formation of German business cycle forecasts: Evidence from a survey of professional forecasters," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181617, Verein für Socialpolitik / German Economic Association.
    8. Constantin Burgi, 2015. "Can A Subset Of Forecasters Beat The Simple Average In The Spf?," Working Papers 2015-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    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. 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.
    11. 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.
    12. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    13. Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
    14. 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.
    15. Ashiya, Masahiro, 2006. "Forecast accuracy and product differentiation of Japanese Institutional Forecasters," International Journal of Forecasting, Elsevier, vol. 22(2), pages 395-401.
    16. Tito Nícias Teixeira da Silva Filho, 2013. "Banks, Asset Management or Consultancies' Inflation Forecasts: is there a better forecaster out there?," Working Papers Series 310, Central Bank of Brazil, Research Department.
    17. Masahiro Ashiya, 2010. "Testing homogeneity of Japanese CPI forecasters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 435-441.
    18. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    19. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Feb 2012.
    20. 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.
    21. 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.
    22. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    23. Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.

  17. Batchelor, Roy A & Dua, Pami, 1989. "Household versus Economist Forecasts of Inflation: A Reassessment: A Note," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 21(2), pages 252-257, May.

    Cited by:

    1. Campbell, Carl M., 2011. "The formation of wage expectations in the effort and quit decisions of workers," MPRA Paper 31590, University Library of Munich, Germany.
    2. Ueda, Kozo, 2010. "Determinants of households' inflation expectations in Japan and the United States," Journal of the Japanese and International Economies, Elsevier, vol. 24(4), pages 503-518, December.
    3. Ricardo Nunes, 2010. "Inflation Dynamics: The Role of Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(6), pages 1161-1172, September.
    4. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    5. Kozo Ueda, 2009. "Determinants of Households' Inflation Expectations," IMES Discussion Paper Series 09-E-08, Institute for Monetary and Economic Studies, Bank of Japan.
    6. Wändi Bruine de Bruin & Michael F. Bryan & Simon M. Potter & Giorgio Topa & Wilbert Van der Klaauw, 2008. "Rethinking the measurement of household inflation expectations: preliminary findings," Staff Reports 359, Federal Reserve Bank of New York.
    7. Wilbert van der Klaauw & Wandi Bruine de Bruin & Giorgio Topa & Basit Zafar & Olivier Armantier, 2012. "Inflation Expectations and Behavior: Do Survey Respondents Act on their Beliefs?," 2012 Meeting Papers 121, Society for Economic Dynamics.
    8. Lloyd B. Thomas & Alan P. Grant, 2008. "The Accuracy and Rationality of US and Australian Household Inflation Forecasts: A Comparative Study of the Michigan and Melbourne Institute Surveys," The Economic Record, The Economic Society of Australia, vol. 84(265), pages 237-252, June.
    9. Vaona, Andrea, 2014. "The price-price Phillips curve in small open economies and monetary unions: Theory and empirics," Kiel Working Papers 1904, Kiel Institute for the World Economy (IfW Kiel).
    10. Campbell III, Carl M., 2008. "An efficiency wage approach to reconciling the wage curve and the Phillips curve," Labour Economics, Elsevier, vol. 15(6), pages 1388-1415, December.
    11. Kladivko, Kamil & Österholm, Pär, 2020. "Can Households Predict where the Macroeconomy is Headed?," Working Papers 2020:11, Örebro University, School of Business.
    12. John M. Roberts, 1994. "Is inflation sticky?," Working Paper Series / Economic Activity Section 152, Board of Governors of the Federal Reserve System (U.S.).
    13. Grant, Alan P. & Thomas, Lloyd B., 2001. "Supply shocks and the rationality of inflation forecasts," The Quarterly Review of Economics and Finance, Elsevier, vol. 41(4), pages 515-532.
    14. Michael F. Bryan & Brent Meyer & Nicholas B. Parker, 2014. "The inflation expectations of firms: what do they look like, are they accurate, and do they matter?," FRB Atlanta Working Paper 2014-27, Federal Reserve Bank of Atlanta.
    15. Gerberding, Christina, 2001. "The information content of survey data on expected price developments for monetary policy," Discussion Paper Series 1: Economic Studies 2001,09, Deutsche Bundesbank.
    16. Murillo Garza José Antonio & Sánchez-Romeu Paula, 2012. "Testing the Predictive Power of Mexican Consumers' Inflation Expectations," Working Papers 2012-13, Banco de México.
    17. Richard G. Anderson & Charles S. Gascon & Yang Liu, 2010. "Doubling your monetary base and surviving: some international experience," Review, Federal Reserve Bank of St. Louis, vol. 92(Nov), pages 481-506.

  18. Batchelor, R A, 1986. "Quantitative v. Qualitative Measures of Inflation Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(2), pages 99-120, May.

    Cited by:

    1. Zhang, Chengsi & Dang, Chao, 2018. "Is monetary policy forward-looking in China?," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 4-14.
    2. Tomislav Globan & Vladimir Arčabić & Petar Sorić, 2014. "Inflation in New EU Member States: A Domestically or Externally Driven Phenomenon?," EFZG Working Papers Series 1405, Faculty of Economics and Business, University of Zagreb.
    3. Tomislav Globan & Petar Sorić, 2017. "Financial integration before and after the crisis: Euler equations (re)visit European Union," EFZG Working Papers Series 1702, Faculty of Economics and Business, University of Zagreb.
    4. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    5. Paul Butzen & Catherine Fuss & Philip Vermeulen, 2002. "The impact of uncertainty on investment plans," Working Paper Research 24, National Bank of Belgium.
    6. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    7. Nilss Olekalns & Kalvinder Shields, 2008. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real Time Data are Available," Department of Economics - Working Papers Series 1040, The University of Melbourne.
    8. Petar Sorić & Ivana Lolić & Marina Matošec, 2020. "Some properties of inflation expectations in the euro area," Metroeconomica, Wiley Blackwell, vol. 71(1), pages 176-203, February.
    9. Anastasiou, Dimitrios, 2020. "Senior bank loan officers' expectations for loan demand: Evidence from the Euro-area," MPRA Paper 98903, University Library of Munich, Germany.
    10. Frijters, Paul & de New, John & Shields, Michael A., 2002. "Individual Rationality and Learning: Welfare Expectations in East Germany Post-Reunification," IZA Discussion Papers 498, Institute of Labor Economics (IZA).
    11. Binder, Carola Conces, 2016. "Estimation of historical inflation expectations," Explorations in Economic History, Elsevier, vol. 61(C), pages 1-31.
    12. Ivana Lolic & Petar Soric & Mirjana Cizmesija, 2017. "Disentangling the Relationship between News Media and Consumers' Inflation Sentiment: the Case of Croatia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(3), pages 221-249, June.
    13. Loffler, Gunter, 2005. "Avoiding the rating bounce: why rating agencies are slow to react to new information," Journal of Economic Behavior & Organization, Elsevier, vol. 56(3), pages 365-381, March.
    14. Dimitrios Anastasiou & Stelios Giannoulakis, 2021. "Are firms' expectations on the availability of external finance rational, adaptive or regressive?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 49(5), pages 833-849, June.
    15. Fuhrer, Jeff, 2017. "Expectations as a source of macroeconomic persistence: Evidence from survey expectations in a dynamic macro model," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 22-35.
    16. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    17. Reckwerth, Jürgen, 1997. "Inflation and output in Germany: The role of inflation expectations," Discussion Paper Series 1: Economic Studies 1997,05e, Deutsche Bundesbank.
    18. Berlemann, Michael, 2001. "Forecasting inflation via electronic markets: Results from a prototype market," Dresden Discussion Paper Series in Economics 06/01, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    19. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    20. Michael E. Trebing, 1998. "What's happening in manufacturing: \\"survey says...\\"," Business Review, Federal Reserve Bank of Philadelphia, issue Sep, pages 15-29.
    21. Reckwerth, Jürgen, 1997. "Der Zusammenhang zwischen Inflation und Output in Deutschland unter besonderer Berücksichtigung der Inflationserwartungen," Discussion Paper Series 1: Economic Studies 1997,05, Deutsche Bundesbank.
    22. Murillo Garza José Antonio & Sánchez-Romeu Paula, 2012. "Testing the Predictive Power of Mexican Consumers' Inflation Expectations," Working Papers 2012-13, Banco de México.

  19. Batchelor, R. A., 1986. "The psychophysics of inflation," Journal of Economic Psychology, Elsevier, vol. 7(3), pages 269-290, September.

    Cited by:

    1. Steffen Henzel & Timo Wollmershäuser, 2005. "An Alternative to the Carlson-Parkin Method for the Quantification of Qualitative Inflation Expectations: Evidence from the Ifo World Economic Survey," ifo Working Paper Series 9, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Balcombe, Kelvin, 1996. "The Carlson-Parkin method applied to NZ price expectations using QSBO survey data," Economics Letters, Elsevier, vol. 51(1), pages 51-57, April.
    3. Gross, Marco, 2009. "Nonparametric Hybrid Phillips Curves Based on Subjective Expectations: Estimates for the Euro Area," Working Paper Series 1119, European Central Bank.
    4. Lena Vogel & Jan-Oliver Menz & Ulrich Fritsche, 2009. "Prospect Theory and Inflation Perceptions - An Empirical Assessment," Macroeconomics and Finance Series 200903, University of Hamburg, Department of Socioeconomics.
    5. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    6. Wärneryd, K.E., 1995. "Demystifying rational expectations theory through an economic-psychological model," Discussion Paper 1995-92, Tilburg University, Center for Economic Research.
    7. Ranyard, Rob & Missier, Fabio Del & Bonini, Nicolao & Duxbury, Darren & Summers, Barbara, 2008. "Perceptions and expectations of price changes and inflation: A review and conceptual framework," Journal of Economic Psychology, Elsevier, vol. 29(4), pages 378-400, August.
    8. Antonides, Gerrit, 2008. "How is perceived inflation related to actual price changes in the European Union?," Journal of Economic Psychology, Elsevier, vol. 29(4), pages 417-432, August.
    9. Brandstatter, Eduard & Brandstatter, Hermann, 1996. "What's money worth? Determinants of the subjective value of money," Journal of Economic Psychology, Elsevier, vol. 17(4), pages 443-464, August.
    10. Andrew G Haldane & Mahmood Pradhan, 1992. "Testing real interest parity in the European Monetary System," Bank of England working papers 2, Bank of England.
    11. Stanisławska, Ewa & Paloviita, Maritta & Łyziak, Tomasz, 2021. "Consumer inflation views: Micro-level inconsistencies and macro-level measures," Economics Letters, Elsevier, vol. 206(C).
    12. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.
    13. Kaiser, Ulrich & Spitz, Alexandra, 2000. "Quantification of qualitative data using ordered probit models with an application to a business survey in the German service sector," ZEW Discussion Papers 00-58, ZEW - Leibniz Centre for European Economic Research.
    14. Anat Bracha & Jenny Tang, 2019. "Inflation Thresholds and Inattention," Working Papers 19-14, Federal Reserve Bank of Boston.

  20. Batchelor, R. A., 1982. "Expectations, output and inflation : The European experience," European Economic Review, Elsevier, vol. 17(1), pages 1-25.

    Cited by:

    1. Ece Oral, 2016. "Measuring Consumer Inflation Expectations in Turkey," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 2(1), pages 43-74.
    2. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    3. Rina Rosenblatt-Wisch & Rolf Scheufele, 2015. "Quantification and characteristics of household inflation expectations in Switzerland," Applied Economics, Taylor & Francis Journals, vol. 47(26), pages 2699-2716, June.
    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. Ece Oral, 2013. "Consumer Inflation Expectations in Turkey," IFC Working Papers 10, Bank for International Settlements.
    7. James Mitchell & Richard J. Smith & Martin R. Weale, 2005. "Forecasting Manufacturing Output Growth Using Firm‐Level Survey Data," Manchester School, University of Manchester, vol. 73(4), pages 479-499, July.
    8. 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.
    9. Kauppi, Eija & Lassila, Jukka & Terasvirta, Timo, 1996. "Short-term forecasting of industrial production with business survey data: experience from Finland's great depression 1990-1993," International Journal of Forecasting, Elsevier, vol. 12(3), pages 373-381, September.
    10. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    11. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    12. Reckwerth, Jürgen, 1997. "Inflation and output in Germany: The role of inflation expectations," Discussion Paper Series 1: Economic Studies 1997,05e, Deutsche Bundesbank.
    13. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    14. Akira Terai, 2010. "Estimating the distribution of inflation expectations," Economics Bulletin, AccessEcon, vol. 30(1), pages 315-329.
    15. Chris M. Alaouze, 2003. "A modified logit model for time series with an application to the pricing behaviour of manufacturing firms in Australia," Empirical Economics, Springer, vol. 28(3), pages 599-613, July.
    16. Bibiana Lanzilotta Mernies, 2016. "Taxonomia y Dinamica de las Expectativas Economicas de los Empresarios Industriales en Uruguay. Un Analisis de Conglomerados," Revista de Economía del Rosario, Universidad del Rosario, vol. 17(2), pages 229-256, February.
    17. 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.
    18. Reckwerth, Jürgen, 1997. "Der Zusammenhang zwischen Inflation und Output in Deutschland unter besonderer Berücksichtigung der Inflationserwartungen," Discussion Paper Series 1: Economic Studies 1997,05, Deutsche Bundesbank.
    19. Bibiana Lanzilotta Mernies, 2015. "Expectativas empresariales: consecuencias en el crecimiento en Uruguay," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, March.
    20. Michela Nardo, 2003. "The Quantification of Qualitative Survey Data: A Critical Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 17(5), pages 645-668, December.
    21. Benedetto Molinari, 2010. "Sticky Information and Inflation Persistence: Evidence from U.S. Data," Working Papers 10.09, Universidad Pablo de Olavide, Department of Economics.
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  21. Batchelor, R. A., 1981. "Aggregate expectations under the stable laws," Journal of Econometrics, Elsevier, vol. 16(2), pages 199-210, June.

    Cited by:

    1. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    2. Breitung Jörg, 2008. "Assessing the Rationality of Survey Expectations: The Probability Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 630-643, October.
    3. Mitchell, James, 2002. "The use of non-normal distributions in quantifying qualitative survey data on expectations," Economics Letters, Elsevier, vol. 76(1), pages 101-107, June.
    4. Ball, L. & Mankiw, G.H., 1992. "Relative-Price Change as Aggregate Supply Shocks," Harvard Institute of Economic Research Working Papers 1609, Harvard - Institute of Economic Research.
    5. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation expectations in the euro area: are consumers rational?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 591-607, September.
    6. Silva Lopes, Artur, 1994. "A "hipótese das expectativas racionais": teoria e realidade (uma visita guiada à literatura até 1992) [The "rational expectations hypothesis": theory and reality (a guided tour ," MPRA Paper 9699, University Library of Munich, Germany, revised 23 Jul 2008.
    7. James Mitchell & Richard J. Smith & Martin R. Weale, 2013. "Efficient Aggregation Of Panel Qualitative Survey Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 580-603, June.
    8. 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.
    9. McNulty, Mark S., 1985. "Information usage in the formation of price expectations: theory and econometric tests," ISU General Staff Papers 1985010108000013085, Iowa State University, Department of Economics.
    10. Bruno Giancarlo & Lupi Claudio, 2003. "Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data," ISAE Working Papers 33, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    11. James Mitchell & Richard J. Smith & Martin R. Weale, 2005. "Forecasting Manufacturing Output Growth Using Firm‐Level Survey Data," Manchester School, University of Manchester, vol. 73(4), pages 479-499, July.
    12. Constantina Kottaridi & Diego Mendez-Carbajo & Dimitrios Thomakos, 2007. "Inflation Dynamics and the Cross-Sectional Distribution of Prices in the E.U. Periphery," Working Papers 0004, University of Peloponnese, Department of Economics.
    13. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation (mis)perceptions in the euro area," Empirical Economics, Springer, vol. 39(2), pages 353-369, October.
    14. 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.
    15. Fu, Qi & So, Jacky Yuk-Chow & Li, Xiaotong, 2024. "Stable paretian distribution, return generating processes and habit formation—The implication for equity premium puzzle," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    16. Enrico D’Elia, 2005. "Using the results of qualitative surveys in quantitative analysis," ISAE Working Papers 56, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    17. D'Elia, Enrico, 1991. "La quantificazione dei risultati dei sondaggi congiunturali: un confronto tra procedure [Quantifying the results of tendency surveys: a comparison among different procedures]," MPRA Paper 16434, University Library of Munich, Germany.
    18. Ray Barrell, 1999. "Employment Security and European Labour Demand: A Panel Study Across 16 Industries," National Institute of Economic and Social Research (NIESR) Discussion Papers 148, National Institute of Economic and Social Research.
    19. Mitchell, James & Mouratidis, Kostas & Weale, Martin, 2007. "Uncertainty in UK manufacturing: Evidence from qualitative survey data," Economics Letters, Elsevier, vol. 94(2), pages 245-252, February.
    20. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    21. Jan Marc Berk, 1999. "Measuring inflation expectations: a survey data approach," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1467-1480.
    22. Patricia Fraser & Ronald MacDonald, 1993. "The Efficiency of CAC Stock Price Forecasts : a Survey Based Perspective," Revue Économique, Programme National Persée, vol. 44(5), pages 991-1000.
    23. 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.
    24. Thomas Maag, 2009. "On the accuracy of the probability method for quantifying beliefs about inflation," KOF Working papers 09-230, KOF Swiss Economic Institute, ETH Zurich.
    25. Nielsen, Hannah, 2003. "Inflation Expectations in the EU: Results from Survey Data," SFB 373 Discussion Papers 2003,13, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    26. Olivier Biau & Hélène Erkel-Rousse & Nicolas Ferrari, 2006. "Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière," Économie et Statistique, Programme National Persée, vol. 395(1), pages 91-116.

  22. R. A. Batchelor, 1975. "Household Technology and the Domestic Demand for Water," Land Economics, University of Wisconsin Press, vol. 51(3), pages 208-223.

    Cited by:

    1. Henrique Monteiro, 2010. "Residential Water Demand in Portugal: checking for efficiency-based justifications for increasing block tariffs," Working Papers Series 1 ercwp0110, ISCTE-IUL, Business Research Unit (BRU-IUL).
    2. Chicoine, David L. & Ramaurthy, Ganapathi, 1984. "An estimate of the Demand for 'Rural Water Service Under Declining Block Rate Price Schedule'," Illinois Agricultural Economics Staff Paper 244639, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    3. Frerichs, Stephen & Becker, Nir & Easter, K. William, 1987. "Alternative Price Specification For Municipal Water Demands: An Empirical Test," Economic Reports 13033, University of Minnesota, Department of Applied Economics.
    4. Ironmonger, D S & Aitken, C K & Erbas, B, 1995. "Economies of scale in energy use in adult-only households," Energy Economics, Elsevier, vol. 17(4), pages 301-310, October.
    5. Tamkinat Rauf & M. Wasif Siddiqi, 2008. "Price-setting for Residential Water: Estimation of Water Demand in Lahore," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 893-906.

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