econstor A Service of zbw Make Your Publications Visible. Leibniz-Informationszentrum Wirtschaft Leibniz Information Centre for Economics García, Juan Angel; Manzanares, Andrés Working Paper What can probability forecasts tell us about inflation risks? ECB Working Paper, No. 825 Provided in Cooperation with: European Central Bank (ECB) Suggested Citation: García, Juan Angel; Manzanares, Andrés (2007) : What can probability forecasts tell us about inflation risks?, ECB Working Paper, No. 825 This Version is available at: http://hdl.handle.net/10419/153259 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Documents in EconStor may be saved and copied for your personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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WO R K I N G PA P E R S E R I E S N O 8 2 5 / O C TO B E R 2 0 0 7 WHAT CAN PROBABILITY FORECASTS TELL US ABOUT INFLATION RISKS? by Juan Angel García and Andrés Manzanares Wo r k i n g Pa p e r S e r i e S NO 8 25 / O c t o b e r 20 0 7 WHAT CAN PROBABILITY FORECASTS TELL US ABOUT INFLATION RISKS? 1 by Juan Angel García 2 and Andrés Manzanares 3 In 2007 all ECB publications feature a motif taken from the 20 banknote. This paper can be downloaded without charge from http://www.ecb.europa.eu or from the Social Science Research Network electronic library at http://ssrn.com /abstract_id=1020964. 1 We are very grateful to Geert Bekaert, Gonzalo Camba-Méndez, Refet Gürkaynak, Gabriel Perez-Quirós, Thomas Werner, an anonymous referee and seminar participants at the ECB and in the conference “Price Stability and Monetary Policy” organized by the Federal Reserve Banks of Dallas and Cleveland in Dallas, May 2007, for useful comments and suggestions. We are particularly indebted to Paul Söderlind for many fruitful discussions in the early stages of this project, and to Ken Wallis for very detailed suggestions. Excellent research assistance by Renate Dreiskena is also gratefully acknowledged. Any remaining errors are our responsibility. The views expressed in this paper are those of the authors and do not necessarily reflect the views of the European Central Bank. 2 Capital Markets and Financial Structure Division, DG-E, European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany; e-mail: [email protected] 3 Risk Management Division, DG-H, European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany; e-mail: [email protected] © European Central Bank, 2007 Address Kaiserstrasse 29 60311 Frankfurt am Main, Germany Postal address Postfach 16 03 19 60066 Frankfurt am Main, Germany Telephone +49 69 1344 0 Website http://www.ecb.europa.eu Fax +49 69 1344 6000 Telex 411 144 ecb d All rights reserved. Any reproduction, publication and reprint in the form of a different publication, whether printed or produced electronically, in whole or in part, is permitted only with the explicit written authorisation of the ECB or the author(s). The views expressed in this paper do not necessarily reflect those of the European Central Bank. The statement of purpose for the ECB Working Paper Series is available from the ECB website, http://www.ecb. europa.eu/pub/scientific/wps/date/html/ index.en.html ISSN 1561-0810 (print) ISSN 1725-2806 (online) CONTENTS Abstract 4 Non-technical summary 5 1 Introduction 7 2 A new methodology to analyze the SPF histograms 10 2.1 The choice of fitting criterion 11 2.2 The choice of theoretical density function 13 3 Assessing our methodology 3.1 Accuracy gains 3.2 Fitting densities to the SPF histograms: practical considerations 14 14 4 17 18 19 Four decades of inflation risks: stylized facts 4.1 Measuring inflation uncertainty 4.2 Asymmetries in inflation risks 4.3 Inflation risks and the central tendency ofinflationexpectations 16 20 5 Inflation scares and inflation risks in the 1980s 21 6 Inflation risks and the macroeconomy 24 7 Concluding remarks 26 Annexes A On the optimal fitting criterion for the SPF histograms BDecomposing the skewness of the combined forecast C Monte Carlo evidence 27 References 32 Tables and figures 35 European Central Bank Working Paper Series 45 27 29 29 ECB Working Paper Series No 825 October 2007 3 4 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 5 6 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 7 8 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 9 10 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 11 12 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 13 14 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 15 16 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 17 18 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 19 20 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 21 22 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 23 24 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 25 26 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 27 28 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 29 30 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 31 32 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 33 34 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 35 36 ECB Working Paper Series No 825 October 2007 ECB Working Paper Series No 825 October 2007 37 Figure 1: Examples of skew-normal densities Ȝ=0 (Ȗ1=0) Ȝ=-2.6 (Ȗ1=-0.6) 0.5 Ȝ=-1.5 (Ȗ1=-0.3) Ȝ=-6.3 (Ȗ1=-0.9) Probability 0.4 0.3 0.2 0.1 0.0 -3.5 -1.5 1.5 -2.5 -0.5 0.5 The densities depicted have zero mean and unit variance Figure 2: Fitting criterion gains (MSE) Ȗ1=0.9 Ȗ1=0.6 Ȗ1=0.3 Figure 3: Density gains (MSE) Ȗ1=0 0% 3.5 2.5 Ȗ1=0.9 Ȗ1=0.6 Ȗ1=0.3 Ȗ1=0 10% Mean -20% Standard deviation 0% -40% -10% Mean Standard Deviation -60% -20% Figure 4: Overall gains (MSE) Ȗ1=0.9 Ȗ1=0.6 Ȗ1=0.3 Figure 5: Overall gains from LS,N (MAE) Ȗ1=0 Ȗ1=0.9 0% 0% -20% -20% -40% -40% -60% -60% -80% Mean Standard Deviation Ȗ1=0.6 Mean Ȗ1=0.3 Ȗ1=0 Standard Deviation -80% � Note: For both the estimated mean and variance of the distribution, the charts depict the percentage reduction in the estimation error (mean absolute error (MAE) and mean square error (MSE)) of our methodology with respect to the least squares (LS) fitting criterion and/or the standard normal (N) density. Specifically, Figure 2 reports the reduction in the MSE from using our fitting criterion instead of LS for the Skew-Normal (SN) distribution, Figure 3 for using the SN instead of the N with our fitting criterion, and Figures 4 and 5 from using our fitting criterion and the SN instead of LS and the N. Results are based on 1,000 simulations from SN distributions with four different degrees of skewness Ȗ1. 38 ECB Working Paper Series No 825 October 2007 Figure 6: Skew-normal versus normal fitting 1.0 Probability 0.8 0.6 0.4 0.2 0.0 0.0 1.0 2.0 3.0 4.0 5.0 The histogram is from forecaster 541 in the 2005 Q3 SPF Figure 7: Estimated uncertainty and number of active intervals reported 3.0 Inflation uncertainty 2.5 2.0 1.5 1.0 0.5 0.0 0 1 2 3 4 5 6 7 8 9 10 11 Number of active bins Estimation results for individual probability forecasts between 1992Q1 and 2006Q1 ECB Working Paper Series No 825 October 2007 39 Figure 8: Variance of the combined distribution, average uncertainty and disagreement 3.5 Disagreement 3.0 Average uncertainty Variance of combined distribution 2.5 2.0 1.5 1.0 0.5 0.0 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005 Decomposition of the variance of the combined distribution (current-year forecasts in Q1) 50 50 40 40 30 20 10 Ȗ1<0.3 0.3<Ȗ1<0.6 Ȗ1>0.6 Skewness coefficient (absolute value) Based on 247 estimated combined densities, 1968Q4-2006Q1 ECB Working Paper Series No 825 October 2007 30 20 10 0 0 40 Figure 10: Skewness (individual forecasts) Proportion % Proportion % Figure 9: Skewness (combined forecasts) Ȗ1<0.3 0.3<Ȗ1<0.6 Ȗ1>0.6 Skewness coefficient (absolute value) Based on 8,204 estimated individual densities, 1968Q4-2006Q1 Figure 11: Alternative measures of skew (combined distribution) 4 Inflation skewness Mean-mode 3 2 1 0 -1 -2 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 Figure 12: Expected inflation and inflation risks Expect ed inflat ion and inflat ion uncert aint y 80 Variance of Agg. Dist. 4 3 86 87 85 83 88 75 74 908984 91 82 79 81 0669 70 76 78 9372 0301 92 95 77 99 05 04 9 7 02 98 96 00 94 73 71 2 1 0 0 2 4 6 8 10 Mean expect ed annual inflation rat e, % Expect ed inflat ion and risks assessment 86 87 85 83 88 4 Skew of Agg. Dist. 5 12 3 84 2 06 78 82 93 95 89 76 79 69 0201 03 73 71 05 94 92 04 77 9 7 72 70 9998 0096 91 74 90 1 0 -1 -2 0 81 80 75 2 4 6 8 10 Mean expect ed annual inflation rat e, % 12 ECB Working Paper Series No 825 October 2007 41 Figure 13: Interest rates, inflation expectations and inflation scares 20 Federal funds rate 18 10-y ear bond y ields Bond yield, % 16 14 12 10 8 6 4 77Q1 78Q1 79Q1 80Q1 81Q1 82Q1 83Q1 84Q1 85Q1 86Q1 87Q1 88Q1 89Q1 90Q1 12 Inflation exp ectations Realised inflation Long-term inflation exp ectations Annual rates, % 10 8 6 4 2 0 77Q1 78Q1 79Q1 80Q1 81Q1 82Q1 83Q1 84Q1 85Q1 86Q1 87Q1 88Q1 89Q1 90Q1 4 3 Inflation skewness Inflation uncertainty 2 1 0 -1 77Q1 78Q1 79Q1 80Q1 81Q1 82Q1 83Q1 84Q1 85Q1 86Q1 87Q1 88Q1 89Q1 90Q1 Note: Shadowed areas reflect periods of inflation scares in the bond market. Inflation expectations denote the mean of the combined distribution for current-year inflation; realized inflation is the year-end rate of growth in the GDP deflator; long-term inflation expectations are from the Philadelphia Fed. The bottom chart depicts the variance and skewness from the combined distribution for current-year inflation. 42 ECB Working Paper Series No 825 October 2007 Figure 14: Inflation and inflation risks Inflat ion and inflat ion uncert aint y 80 4 3 2 1 0 0 8687 8885 83 74 90 84 9891 82 79 06 69 70 76 93 78 72 03 9205 95 01 9997 04 98 96 02 00 73 71 77 94 2 4 6 8 Annual inflat ion, % Inflat ion and risk assessment 86 87 8885 83 4 81 10 75 Skew of Agg. Dist. Variance of Agg. Dist. 5 12 3 84 2 1 06 7882 95 93 89 76 79 03 01 02 94 9205 7369 7170 04 77 72 9897 99 96 00 91 74 90 0 -1 81 80 -2 0 2 75 4 6 8 10 Annual inflat ion rat e, % 12 Figure 15: Inflation risks and economic activity 3.0 Inflation uncertainty and economic activity Output gap (RHS) 2.0 1 1.5 0 -1 1.0 Output gap, % 2 -2 0.5 -3 0.0 81Q1 83Q1 85Q1 87Q1 89Q1 91Q1 93Q1 95Q1 97Q1 99Q1 01Q1 03Q1 05Q1 4 Risks assessment and economic activity Skew of combined forecasts Output gap (RHS) 3 Skew of combined forecast 3 -4 4 3 2 2 1 0 1 0 -1 Output gap, % Variance of combined forecast Variance of combined forecasts 2.5 4 -2 -1 -2 81Q1 83Q1 85Q1 87Q1 89Q1 91Q1 93Q1 95Q1 97Q1 99Q1 01Q1 03Q1 05Q1 -3 -4 Note: output gap is HP-filtered. Inflation uncertainty and skew are smoothed (five quarter centred moving averages) ECB Working Paper Series No 825 October 2007 43 Figure AI: Relative performance of alternative estimators, MSE Mean square error MSE Mean (50 draws) 0.054 0.049 0.044 0.039 0.034 0.029 0.024 0.019 0.014 0.009 0.004 µ=3, ı=1, Ȗ=0.9 µ=3, ı =1,Ȗ =0.3 µ=3, ı =1, Ȗ =0.6 µ=3, ı =1, Ȗ =0 Maximum likelihood Hellinger distance KullbachLeibler distance -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 Tau (criterion choice) MSE Variance (50 draws) µ=3, ı=1, Ȗ=0.9 µ=3, ı =1,Ȗ =0.3 Mean square error 0.054 0.044 µ=3, ı =1, Ȗ =0.6 µ=3, ı =1, Ȗ =0 Hellinger distance Maximum likelihood -0.8 -0.4 0.034 0.024 KullbachLeibler distance 0.014 0.004 -1.4 -1.2 -1 -0.6 -0.2 0 0.2 0.4 0.6 0.8 Tau (criterion choice) Mean square error MSE Skewness (50 draws) 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 µ=3, ı=1, Ȗ=0.9 µ=3, ı =1,Ȗ =0.3 KullbachLeibler distance -1.4 -1.2 Hellinger distance -1 -0.8 µ=3, ı =1, Ȗ =0.6 µ=3, ı =1, Ȗ =0 Maximum likelihood -0.6 -0.4 -0.2 0 Tau (criterion choice) 44 ECB Working Paper Series No 825 October 2007 0.2 0.4 0.6 0.8 European Central Bank Working Paper Series For a complete list of Working Papers published by the ECB, please visit the ECB’s website (http://www.ecb.europa.eu) 773 “Exchange rate volatility and growth in small open economies at the EMU periphery” by G. 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ECB Working Paper Series No 825 October 2007 47 Date: 12 Oct, 2007 17:42:54;Format: (420.00 x 297.00 mm);Output Profile: SPOT IC300;Preflight: Failed! WO R K I N G PA P E R S E R I E S N O 8 2 5 / O C TO B E R 2 0 0 7 WHAT CAN PROBABILITY FORECASTS TELL US ABOUT INFLATION RISKS? by Juan Angel García and Andrés Manzanares
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