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A multivariate evaluation of German output growth and inflation forecasts

Author

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  • Jens J. Krüger

    (Darmstadt University of Technology)

Abstract

We examine the joint efficiency of German output growth and inflation forecasts using a multivariate loss function which allows for loss asymmetry and different degrees of curvature. Efficiency is evaluated with respect to financial market variables as stock market returns and interest spreads. Thereby we find evidence that the loss function is approximately linear with a considerable degree of asymmetry. Compared to the situation where the two forecasted variables are considered univariately, forecast efficiency is also rejected more frequently. Adding a forward-looking survey-based expectations indicator leads to even stronger rejections of forecast efficiency.

Suggested Citation

  • Jens J. Krüger, 2014. "A multivariate evaluation of German output growth and inflation forecasts," Economics Bulletin, AccessEcon, vol. 34(3), pages 1410-1418.
    • Handle: RePEc:ebl:ecbull:eb-13-00634
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    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. Hoffman, Dennis L & Pagan, Adrian R, 1989. "Post-Sample Prediction Tests for Generalized Method of Moments Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 51(3), pages 333-343, August.
    4. 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.
    5. Capistrán, Carlos, 2008. "Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1415-1427, November.
    6. Krüger, Jens & Hoss, Julian, 2012. "German Business Cycle Forecasts, Asymmetric Loss and Financial Variables," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63652, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Krüger, Jens J. & Hoss, Julian, 2012. "German business cycle forecasts, asymmetric loss and financial variables," Economics Letters, Elsevier, vol. 114(3), pages 284-287.
    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. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    10. 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.
    11. Krol, Robert, 2013. "Evaluating state revenue forecasting under a flexible loss function," International Journal of Forecasting, Elsevier, vol. 29(2), pages 282-289.
    12. Jörg Döpke & Ulrich Fritsche & Boriss Siliverstovs, 2010. "Evaluating German business cycle forecasts under an asymmetric loss function," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-18.
    13. Arturo Estrella & Mary R. Trubin, 2006. "The yield curve as a leading indicator: some practical issues," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 12(Jul).
    14. Adrian, Tobias & Estrella, Arturo, 2008. "Monetary tightening cycles and the predictability of economic activity," Economics Letters, Elsevier, vol. 99(2), pages 260-264, May.
    15. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
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    Cited by:

    1. Jörg Döpke & Ulrich Fritsche & Karsten Müller, 2018. "Has Macroeconomic Forecasting changed after the Great Recession? - Panel-based Evidence on Accuracy and Forecaster Behaviour from Germany," Macroeconomics and Finance Series 201803, University of Hamburg, Department of Socioeconomics.

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    More about this item

    Keywords

    macroeconomic forecasting; asymmetric loss; financial markets; survey expectations;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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