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Reevaluating the prudence of economic forecasts in the EU: The role of instrument persistence

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  • Matei Demetrescu
  • Christoph Roling
  • Anna Titova

Abstract

Christodoulakis and Mamatzakis (2009, Journal of Applied Econometrics 24, pp. 583–606) estimate the EU Commission loss preferences for selected economic forecasts of 12 EU Member States. They employ the generalized method of moments (GMM) estimation procedure proposed by Elliott et al. (2005, Review of Economic Studies 72, pp. 1107–1125) and find the forecasts to be somewhat optimistic on average. However, this note shows the GMM estimator to possess nonstandard limiting distributions when some of the instruments are highly persistent, which is the case with one of the instruments employed by Christodoulakis and Mamatzakis. Standard distributions are recovered in some interesting particular cases which are relevant in practice. A reexamination of the EU Commission loss preferences using methods robust to persistence and a dataset extended to 2017 reveals that, while the conclusions of the original study are, by and large, still justified, the EU Commission loss preferences have become more symmetric over the whole studied period.

Suggested Citation

  • Matei Demetrescu & Christoph Roling & Anna Titova, 2021. "Reevaluating the prudence of economic forecasts in the EU: The role of instrument persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 151-161, January.
    • Handle: RePEc:wly:japmet:v:36:y:2021:i:1:p:151-161
    DOI: 10.1002/jae.2801
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    References listed on IDEAS

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    1. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    2. Nikolay Gospodinov, 2009. "A New Look at the Forward Premium Puzzle," Journal of Financial Econometrics, Oxford University Press, vol. 7(3), pages 312-338, Summer.
    3. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1107-1125.
    4. Clive W.J. Granger, 1999. "Outline of forecast theory using generalized cost functions," Spanish Economic Review, Springer;Spanish Economic Association, vol. 1(2), pages 161-173.
    5. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 8(4), pages 489-500, December.
    6. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    7. Baillie, Richard T. & Bollerslev, Tim, 2000. "The forward premium anomaly is not as bad as you think," Journal of International Money and Finance, Elsevier, vol. 19(4), pages 471-488, August.
    8. 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.
    9. Liu, Wei & Maynard, Alex, 2005. "Testing forward rate unbiasedness allowing for persistent regressors," Journal of Empirical Finance, Elsevier, vol. 12(5), pages 613-628, December.
    10. 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.
    11. 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.
    12. Alex Maynard & Peter C. B. Phillips, 2001. "Rethinking an old empirical puzzle: econometric evidence on the forward discount anomaly," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 671-708.
    13. Ulrich K. M¸ller & Graham Elliott, 2003. "Tests for Unit Roots and the Initial Condition," Econometrica, Econometric Society, vol. 71(4), pages 1269-1286, July.
    14. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    15. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
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