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Quality of Tests of Expectation Formation for Revised Data

Author

Listed:
  • Paulina Ziembińska

    (University of Warsaw, Faculty of Economic Sciences)

Abstract

The work contains discussions and simulation analyses of the expectation formation processes, taking account of the data revisions. In particular, it contains results of simulations examining statistical properties of the rationality tests and extrapolation processes, with particular focus on their behaviour in the case of short samples and data with measurement errors. The conclusions indicate that the rationality test based on the optimal regression and the proposed adaptive and accelerating tests are the most efficient and flexible. The tests showcasing best properties have been applied to a new set of macroeconomic forecasts for Poland. The results show that there are no grounds for rejecting the hypothesis on the rationality of forecasts derived from the National Bank of Poland (NBP) and the Organisation for Economic Cooperation and Development; however, this property was rejected for the European Commission. What is more, the comparative analysis indicates that only the national institution (NBP) may potentially aim the final readings of the macroeconomic data as the forecasting target. Finally, it transpires that the extrapolative models, albeit simple and intuitively interpreted, generally fail to correctly explain the forecast formation processes regarding the Polish economy.

Suggested Citation

  • Paulina Ziembińska, 2021. "Quality of Tests of Expectation Formation for Revised Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 405-453, December.
  • Handle: RePEc:psc:journl:v:13:y:2021:i:4:p:405-453
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    References listed on IDEAS

    as
    1. 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.
    2. Andrew Patton & Allan Timmermann, 2012. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17.
    3. Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
    4. Jacob A. Mincer, 1969. "Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance," NBER Books, National Bureau of Economic Research, Inc, number minc69-1, March.
    5. 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.
    6. Paweł Baranowski & Wirginia Doryń & Tomasz Łyziak & Ewa Stanisławska, 2020. "Words and deeds in managing expectations: empirical evidence on an inflation targeting economy," NBP Working Papers 326, Narodowy Bank Polski.
    7. 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.
    8. Allan Timmermann, 2007. "An Evaluation of the World Economic Outlook Forecasts," IMF Staff Papers, Palgrave Macmillan, vol. 54(1), pages 1-33, May.
    9. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    10. Pesaran, M Hashem, 1985. "Formation of Inflation Expectations in British Manufacturing Industries," Economic Journal, Royal Economic Society, vol. 95(380), pages 948-975, December.
    11. 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.
    12. Tomasz Łyziak & Xuguang Simon Sheng, 2023. "Disagreement in Consumer Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(8), pages 2215-2241, December.
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    More about this item

    Keywords

    data revisions; macroeconomic forecasts; Polish economy; rational expectations; expectation processes;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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