The Information Content of Capacity Utilisation Rates for Output Gap Estimates

Transcription

1 The Information Content of Capacity Utilisation Rates for Output Gap Estimates Michael Graff and Jan-Egbert Sturm 15 November 2010

2 Overview Introduction and motivation Data Output gap data: OECD Economic Outlook Capacity utilisation: information from Business Tendency Surveys Empirical analysis Design Results Conclusions 15 November

3 Measurement of the output gap in real time Output gap = (Y Y*)/Y* y y* Percentage deviation of factual output from potential output Potential and factual output are unobservable in real time This is when this information is most needed as a guidance for economic and monetary policy Countercyclical fiscal policy E.g. Swiss debt brake Monetary policy in a Taylor rule framework 15 November

4 Measurement of the output gap in real time Problems with real-time estimates of output gap data End-point problem when estimating Y* Revisions in Y (and thereby Y*) Orphanides & Van Norden (2002) Revisions are of similar magnitude as the gap itself Hence, shortcomings question usefulness of output gap data in real time How can we improve the quality of output gap estimates in real time? Various remedies suggested Forecasting data points Multivariate filters Use of dynamic factor models This paper: output gap capacity utilisation from BTS 15 November

5 Some methods to estimate potential output Smoothing real GDP using a filters Hodrick-Prescott, Baxter-King, The split time trend method calculate average output growth during each cycle, where the cycle is defined as the period between peaks in economic growth Estimating potential output using a production function approach y = a + α n + (1 α) k + e e is smoothed (using HP filter) to e* (trend factor productivity) y* = a + α n* + (1 α) k + e* Where n* is potential employment calculated using an estimated non-accelerating wage rate of unemployment 15 November

6 Output gap data: OECD Economic Outlook Production function based approach Bi-annual vintages with data at a annual frequency First vintage: Jun (data covers ) Last vintage: Dec (data covers ) The resulting revision-data sets are unbalanced Annual data: 22 countries (up to 287 obs.) The largest balanced panels thereof are Annual data: 17 countries, (= 170 obs.) 15 November

7 Capacity utilisation data Sources: European Commission, OECD MEI, KOF, national sources (in case of Belgium, US, New Zealand and Canada) Business tendency survey data Question used asks for: The current level of capacity utilisation Refers mainly to means of production (physical capital) Is consistently asked in the industry sector Range Minimum: completely idle = 0 % Maximum: full utilisation of present capacity = 100 % - Few surveys allow for excess capacity utilisation > 100% Data is (almost) not revised over time 15 November

8 Output gap (vintages) Capacity utilisation (reference period) Australia 1995:Jun 2009:Dec 1996q1-2009q4 Austria 1995:Jun 2009:Dec 1996q1-2009q4 Belgium 1995:Jun 2009:Dec 1980q1-2009q4 Czech Republic 2005:Dec 2009:Dec 1993q2-2009q4 Denmark 1995:Jun 2009:Dec 1987q1-2009q4 Finland 1995:Jun 2009:Dec 1993q1-2009q4 France 1995:Jun 2009:Dec 1985q1-2009q4 Germany 1995:Jun 2009:Dec 1985q1-2009q4 Hungary 2005:Dec 2009:Dec 1996q1-2009q4 Ireland 1995:Jun 2009:Dec 1985q1-2008q2 Italy 1995:Jun 2009:Dec 1970q1-2009q4 Japan 1995:Jun 2009:Dec 1978q1-2009q4 Luxemburg 2005:Dec 2009:Dec 1985q1-2009q4 Netherlands 1995:Jun 2009:Dec 1985q1-2009q4 New Zealand 1997:Jun 2009:Dec 1970q1-2009q4 Norway 1995:Jun 2009:Dec 1987q1-2009q4 Poland 2006:Dec 2009:Dec 1992q2-2009q4 Portugal 1995:Jun 2009:Dec 1987q1-2009q4 Spain 1995:Jun 2009:Dec 1987q2-2009q4 Sweden 1995:Jun 2009:Dec 1996q1-2009q4 Switzerland 1995:Jun 2009:Dec 1970q1-2009q4 United Kingdom 1995:Jun 2009:Dec 1985q1-2009q4 Summary of the data Countries in bold are not included in the strictly balanced sample No. countries November

9 Data setup and revision process Reference Period Vintages / Release Dates Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec R8 R6 R7 R8 R4 R5 R6 R7 R8 R2 R3 R4 R5 R6 R7 R8 F4 F2 R1 F3 R2 F4 R3 R1 R4 R2 R5 R3 R6 R4 R7 R5 R8 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 R7 R8 F1 F2 F3 F4 R1 R2 R3 R4 R5 R6 F1 F2 F3 F4 R1 R2 R3 R4 F1 F2 F3 F4 R1 R2 F1 F2 F3 F4 F1 F2 Fx Rx Forecast number x Release number x Source: OECD, calculations KOF 15 November

10 Releases of annual output gaps: averaged bal.panel 2.0 % of potential GDP CU rate (in %) rel. 1 rel. 2 rel. 3 rel. 4 rel. 5 rel. 6 rel. 7 rel. 8 CU rate 79.5 Source: OECD, calculations KOF 15 November

11 Revision process of annual output gaps: avg.bal.panel 2.0 %-points CU rate (in %) rev. 1 rev. 2 rev. 3 rev. 4 rev. 5 rev. 6 rev. 7 CU rate Source: OECD, calculations KOF 15 November

12 Descriptive Statistics of the annual releases/vintages Maximum panel Strictly balanced panel (22 countries, ) (17 countries, ) Obs Mean St.D. Min. Max. Obs Mean St.D. Min. Max. Capacity utilisation (in % of full capacity) degree (in %) Output gap (in % of potential GDP) Release Release Release Release Release Release Release Release November

13 Descriptive statistics Obs. Mean Sign. St.Dev. Min. Max. Skewness Kurtosis Jarque-Bera Sign. Maximum panel Revision Cumulative Revision Cumulative Revision Cumulative Revision Cumulative Revision Cumulative Revision Cumulative Revision Strictly balanced panel Revision Cumulative Revision Cumulative Revision Cumulative Revision Cumulative Revision Cumulative Revision Cumulative Revision November

14 Estimation design Data revisions contain news revisions are orthogonal to earlier releases and not predictable y Rx (t) = y R1 (t) + ε(t), cov(y R1 (t),ε(t)) = 0 Rx = R2, R3, R4, R5, R6, R7, R8 Mincer-Zarnowitz (1969) test for forecast efficiency (in a panel data set-up) Are real time output gap estimates informationally efficient (w.r.t. Capacity Utilisation data) Are the revisions predictable? Δ Rx-R1 y(t) = α(i) + γ y R1 (i,t) + δ CU(i,t) + β(t) + ε(i,t) Δ Rx-R1 y(t) represent the cumulative revisions 1 to 7 Hypotheses: α(i) = 0, γ = 0, δ = 0 15 November

15 Regression results using increasing revision horizons (1) (2) (3) (4) (5) (6) (7) Dependent variable: R 2 -R 1 R 3 -R 1 R 4 -R 1 R 5 -R 1 R 6 -R 1 R 7 -R 1 R 8 -R 1 First release (y R 1 ) Capacity utilisation rate (-3.74) (-6.13) (-8.00) (-6.69) (-7.35) (-6.25) (-5.63) (1.53) (2.50) (2.44) (2.66) (3.29) (1.99) (2.19) Adjusted R Number of observations Number of countries Number of periods p-value LR-test for country effects p-value LR-test for time effects p-value LR-test for time and country effects November

16 Goodness-of-fit across different revisions 0.50 adj.r Revision 1 Cumulative Revision 2 Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7 without CU variable CU variable included 15 November

17 Regression results Dependent variable: cumulative revision 7 (Δ R8-R1 y) (1) (2) (3) (4) (5) First release (y R 1 ) Capacity utilisation rate Capacity utilisation rate, lagged one year (-6.09) (-5.63) (-6.00) (-5.98) (-5.91) (2.19) (2.57) (1.90) (2.52) (1.92) Adjusted R Number of observations Number of countries Number of periods p-value LR-test for country effects p-value LR-test for time effects p-value LR-test for time and country effects November

18 Conclusions Revisions in OECD output gap estimates are almost of a similar magnitude as the output gap estimates itself During the period output gaps have overall been revised upwards and towards their mean Hence, revisions appear to be predictable I.e., OECD real-time output gap estimates are not informationally efficient Business tendency survey data on capacity utilisation can partly explain revisions Results are robust to changes in the sample 15 November