Macroeconomic forecast uncertainty in the euro area

Authors

  • Victor Lopez-Perez Universidad Politecnica de Cartagena

DOI:

https://doi.org/10.12775/EQUIL.2016.001

Keywords:

macroeconomic uncertainty, Gini index, performance-based weights, Survey of Professional Forecasters, European Central Bank

Abstract

This paper estimates aggregate measures of macroeconomic uncertainty from individual density forecasts by professional forecasters. The methodology used in the paper improves on the existing literature along two dimensions. Firstly, it controls for changes to the composition of the panel of respondents to the survey. And secondly, it assigns more weight to the information submitted by forecasters with better forecasting performance. Using data from the European Central Bank?s Survey of Professional Forecasters from 1999 Q1 to 2014 Q3, the paper finds that the effects of changes in the composition of the panel on aggregate uncertainty can be large in a statistical and economic sense. It also finds that the estimates of aggregate uncertainty that use performance-based weights differ significantly from the simple averages used in the literature and their dynamics are more consistent with the dynamics displayed by the estimates of uncertainty computed from financial indicators.

Downloads

Download data is not yet available.

References

Abel, J., Rich, R., Song, J. & Tracy, J. (2015). The measurement and behavior of uncertainty: evidence from the ECB Survey of Professional Forecasters. Journal of Applied Econometrics. http://dx.doi.org/10.1002/jae.2430(Forthcoming)
Baker, S. R., Bloom, N. & Davis, S. J. (2015). Measuring economic policy uncertainty. NBER Working Paper 21633. Cambridge, MA.
Basu, S., & Bundick, B. (2014). Uncertainty shocks in a model of effective demand. Federal Reserve Bank of Kansas City Working Paper 14-15. http://dx.doi.org/10.2139/ssrn.2531066.
Batchelor, R., & Dua, P. (1996). Empirical measures of inflation uncertainty: a cautionary note. Applied Economics, 28(3). http://dx.doi.org/10.1080/ 000368496328704.
Bekaert, G., Hoerova, M. & Lo Duca, M. (2013). Risk, uncertainty and monetary policy. Journal of Monetary Economics, 60(7). http://dx.doi.org/10.1016/ j.jmoneco.2013.06.003.
Billio, M., Casarin, R., Ravazzolo, F. & van Dijk, H. (2013). Time-varying combinations of predictive densities using nonlinear filtering. Journal of Econometrics, 177(2). http://dx.doi.org/10.1016/j.jeconom.2013.04.009.
Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3). http://dx.doi.org/10.3982/ecta6248.
Boero, G., Smith, J. & Wallis, K. F. (2008). Uncertainty and disagreement in economic prediction: the Bank of England Survey of External Forecasters. The Economic Journal, 118(530). http://dx.doi.org/10.1111/j.1468-0297.2008 .02162.x.
Boero, G., Smith, J. & Wallis, K. F. (2015). The measurement and characteristics of professional forecasters? uncertainty. Journal of Applied Econometrics. http://dx.doi.org/10.1002/jae.2400 (Forthcoming).
Caballero, R. J. (1990). Consumption puzzles and precautionary savings. Journal of Monetary Economics, 25(1). http://dx.doi.org/10.1016/0304-3932(90)90048-9.
Capistrán, C., & Timmermann, A. (2009). Forecast combination with entry and exit of experts. Journal of Business and Economic Statistics, 27(4). http://dx.doi.org/10.1198/jbes.2009.07211.
Conflitti, C. (2011). Measuring uncertainty and disagreement in the European Survey of Professional Forecasters. Journal of Business Cycle Measurement and Analysis, 2. http://dx.doi.org/10.1787/jbcma-2011-5kg0p9zzp26k.
Conflitti, C., De Mol, C. & Giannone, D. (2015). Optimal combination of survey forecasts. International Journal of Forecasting, 31(4). http://dx.doi.org/10.1016 /j.ijforecast.2015.03.009.
ECB (2014). Fifteen years of the ECB Survey of Professional Forecasters. ECB Monthly Bulletin, January.
Engelberg, J., Manski, C. F. & Williams, J. (2011). Assessing the temporal variation of macroeconomic forecasts by a panel of changing composition. Journal of Applied Econometrics, 26(7). http://dx.doi.org/10.1002/jae.1206.
Garcia, J. A., & Manzanares, A. (2007). What can probability forecasts tell us about inflation risks? ECB Working Paper 825. Frankfurt am Main.
Geweke, J., & Amisano, G. (2010). Optimal prediction pools. Journal of Econometrics, 164(1). http://dx.doi.org/10.1016/j.jeconom.2011.02.017.
Genre, V., Kenny, G., Meyler, A. & Timmermann, A. (2013). Combining expert forecasts: can anything beat the simple average? International Journal of Forecasting, 29(1). http://dx.doi.org/10.1016/j.ijforecast.2012.06.004.
Giannone, D., Henry, J., Lalik, M. & Modugno, M. (2010). An area-wide real-time database for the euro area. ECB Working Paper 1145. Frankfurt am Main.
Gini, C. (1955). Variabilit? e mutabilit?. In E. Pizzeti and T. Salvemini (Eds.). Memorie di metodologica statistica. Rome: Libreria Eredi Virgilio Veschi.
Giordani, P., & Söderlind, P. (2003). Inflation forecast uncertainty. European Economic Review, 47(6). http://dx.doi.org/10.1016/S0014-2921(02)00236-2.
Gneiting, T., & Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102(477). http://dx.doi.org/10.1198/016214506000001437.
Hall, S. G., & Mitchell, J. (2005). Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ?fan? charts of inflation. Oxford Bulletin of Economics and Statistics, 67(s1). http://dx.doi.org/10.1111/j.1468-0084.2005.00149.x.
Hall, S. G., & Mitchell, J. (2007). Combining density forecasts. International Journal of Forecasting, 23(1), http://dx.doi.org/10.1016/j.ijforecast.2006 .08.001.
Jore, A. S., Mitchell, J. & Vahey, S. P. (2010). Combining forecast densities from VARs with uncertain instabilities. Journal of Applied Econometrics, 25(4). http://dx.doi.org/10.1002/jae.1162.
Kascha, C., & Ravazzolo, F. (2010). Combining inflation density forecasts. Journal of Forecasting, 29(1-2). http://dx.doi.org/10.1002/for.1147.
Kenny, G., Kostka, T. & Masera, F. (2015). Density characteristics and density forecast performance: a panel analysis. Empirical Economics, 48(3). http://dx.doi.org/10.1007/s00181-014-0815-9.
Leahy, J. V., & Whited, T. M. (1996). The effect of uncertainty on investment: some stylized facts. Journal of Money, Credit and Banking, 28(1). http://dx.doi.org/10.2307/2077967.
Lorenz, M. O. (1905). Methods of measuring the concentration of wealth. Publications of the American Statistical Association, 9(70). http://dx.doi.org/10.23 07/2276207.
Moore, D., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2). http://dx.doi.org/10.1037/0033-295X.115.2.502.
Neamtiu, M., Shroff, N., White, H. D. & Williams, C. D. (2014). The impact of ambiguity on managerial investment and cash holdings. Journal of Business Finance & Accounting, 41(7-8). http://dx.doi.org/10.1111/jbfa.12079.
Rich, R., & Tracy, J. (2010). The relationships among expected inflation, disagreement, and uncertainty: evidence from matched point and density forecasts. Review of Economics and Statistics, 92(1). http://dx.doi.org/10.1162/ rest.2009.11167.
Smith, J., & Wallis, K. F. (2009). A simple explanation of the forecast combination puzzle. Oxford Bulletin of Economics and Statistics, 71(3). http://dx.doi.org/10.1111/j.1468-0084.2008.00541.x.
Stock, J. H., & Watson, M. W. (2004). Combination forecasts of output growth in a seven-country data set. Journal of Forecasting, 23(6). http://dx.doi.org/10.1002/for.928.
Wallis, K. F. (2006). A note on the calculation of entropy from histograms. MPRA Working Paper 52856. Munich.

Downloads

Published

2016-03-31

How to Cite

Lopez-Perez, V. (2016). Macroeconomic forecast uncertainty in the euro area. Equilibrium. Quarterly Journal of Economics and Economic Policy, 11(1), 9–41. https://doi.org/10.12775/EQUIL.2016.001

Issue

Section

Monetary policy and interdependencies among financial markets

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.