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Can we estimate macroforecasters’ mis-behavior?

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  • Chini, Emilio Zanetti

Abstract

We answer positively to this question by using Maximum Lq-Likelihood (or Deformed Likelihood) estimator. This is based on a parameter which measures the aggregate quote of judgment in the forecasting (game-based) system formed by three players—Forecaster, Policy Maker and Reality. For the first time in econometric literature, we apply this estimator to a dynamic system and derive a robust version of the Kalman Filter—the Deformed Kalman Filter (DKF). The evidence from U.S. data suggests that the judgmental dynamics exists and is correlated (but not coincident) with the phases of the Business Cycle. Furthermore its knowledge improves in-sample as well as out-of-sample estimation.

Suggested Citation

  • Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
  • Handle: RePEc:eee:dyncon:v:149:y:2023:i:c:s0165188923000386
    DOI: 10.1016/j.jedc.2023.104632
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    as
    1. Cosmin Ilut & Rosen Valchev, 2023. "Economic Agents as Imperfect Problem Solvers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 313-362.
    2. Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020. "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, vol. 110(9), pages 2748-2782, September.
    3. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    4. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    5. Carlos Capistr¡N & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    6. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    7. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
    8. Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2018. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 107-123.
    9. Richard K. Crump & Stefano Eusepi, 2016. "Fundamental Disagreement: How Much and Why?," Liberty Street Economics 20160113, Federal Reserve Bank of New York.
    10. Francesco Bianchi & Sydney C. Ludvigson & Sai Ma, 2022. "Belief Distortions and Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 112(7), pages 2269-2315, July.
    11. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    12. Andrade, Philippe & Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "Fundamental disagreement," Journal of Monetary Economics, Elsevier, vol. 83(C), pages 106-128.
    13. Pietro Ortoleva, 2012. "Modeling the Change of Paradigm: Non-Bayesian Reactions to Unexpected News," American Economic Review, American Economic Association, vol. 102(6), pages 2410-2436, October.
    14. 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.
    15. Gianna Boero & Jeremy Smith & Kenneth F. Wallis, 2008. "Uncertainty and Disagreement in Economic Prediction: The Bank of England Survey of External Forecasters," Economic Journal, Royal Economic Society, vol. 118(530), pages 1107-1127, July.
    16. Gaglianone, Wagner Piazza & Giacomini, Raffaella & Issler, João Victor & Skreta, Vasiliki, 2022. "Incentive-driven inattention," Journal of Econometrics, Elsevier, vol. 231(1), pages 188-212.
    17. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, December.
    18. Michael P. Clements, 2014. "Forecast Uncertainty- Ex Ante and Ex Post : U.S. Inflation and Output Growth," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 206-216, April.
    19. Francesca Monti, 2010. "Combining Judgment and Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(8), pages 1641-1662, December.
    20. Pedro Bordalo & Nicola Gennaioli & Rafael La Porta & Andrei Shleifer, 2019. "Diagnostic Expectations and Stock Returns," Journal of Finance, American Finance Association, vol. 74(6), pages 2839-2874, December.
    21. J. Bradford De Long & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1989. "The Size and Incidence of the Losses from Noise Trading," Journal of Finance, American Finance Association, vol. 44(3), pages 681-696, July.
    22. Lars E O Svensson, 2005. "Monetary Policy with Judgment: Forecast Targeting," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    23. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions," American Economic Review, American Economic Association, vol. 105(5), pages 650-655, May.
    24. Vladimir Vovk & Glenn Shafer, 2005. "Good randomized sequential probability forecasting is always possible," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 747-763, November.
    25. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias in Macroeconomic Forecasts," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 293-318.
    26. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    27. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December.
    28. Townsend, Robert M, 1978. "Market Anticipations, Rational Expectations, and Bayesian Analysis," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(2), pages 481-494, June.
    29. Peter Burridge & A. M. Robert Taylor, 2006. "Additive Outlier Detection Via Extreme‐Value Theory," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 685-701, September.
    30. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
    31. Sebastiano Manzan, 2011. "Differential Interpretation in the Survey of Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 993-1017, August.
    32. Orphanides, Athanasios, 2003. "Monetary policy evaluation with noisy information," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 605-631, April.
    33. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    34. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    35. Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2020. "Heterogeneity, Inattention, and Bayesian Updates," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 282-309, January.
    36. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2018. "The Formation of Expectations, Inflation, and the Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1447-1491, December.
    37. Dean Croushore & Tom Stark, 2019. "Fifty Years of the Survey of Professional Forecasters," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 4(4), pages 1-11, October.
    38. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    39. Tilman Ehrbeck & Robert Waldmann, 1996. "Why Are Professional Forecasters Biased? Agency versus Behavioral Explanations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(1), pages 21-40.
    40. Carlos Capistrán & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2‐3), pages 365-396, March.
    41. Ottaviani, Marco & Sorensen, Peter, 2001. "Information aggregation in debate: who should speak first?," Journal of Public Economics, Elsevier, vol. 81(3), pages 393-421, September.
    42. Casey, Eddie, 2020. "Do macroeconomic forecasters use macroeconomics to forecast?," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1439-1453.
    43. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    44. Manganelli, Simone, 2009. "Forecasting With Judgment," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 553-563.
    45. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
    46. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    47. Townsend, Robert M, 1983. "Forecasting the Forecasts of Others," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 546-588, August.
    48. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    49. Sebastiano Manzan, 2011. "Differential Interpretation in the Survey of Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 993-1017, August.
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    More about this item

    Keywords

    Deformed likelihood; Dynamic systems; Judgment; Repeated games; Robust filtering;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E7 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics

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