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The Information Content of Capacity Utilisation Rates for Output Gap Estimates Michael Graff and Jan-Egbert Sturm 28 September 2010 Overview Introduction and motivation Data Output gap data: OECD Economic Outlook Capacity

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28 September 2010

The Information Content

  • f Capacity Utilisation Rates

for Output Gap Estimates

Michael Graff and Jan-Egbert Sturm

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28 September 2010 2 6th Colloquium

Overview

  • Introduction and motivation
  • Data

Output gap data: OECD Economic Outlook Capacity utilisation: information from Business Tendency Surveys

  • Empirical analysis

Design Results

  • Conclusions
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SLIDE 3

28 September 2010 3 6th Colloquium

Evaluation

Real-time data

Final Partly revised First-released

Vintage

Final data

Economic forecast Political decisions

Final data Partly revised First-released

Time

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28 September 2010 4 6th Colloquium

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
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28 September 2010 5 6th Colloquium

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
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28 September 2010 6 6th Colloquium

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

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28 September 2010 7 6th Colloquium

Output gap data: OECD Economic Outlook

  • Production function based approach
  • Bi-annual vintages with data at a annual frequency

First vintage:

  • Jun. 1995

(data covers 1970-1996) Last vintage:

  • Dec. 2009

(data covers 1970-2011)

  • 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, 1996-2005 (= 170 obs.)

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28 September 2010 8 6th Colloquium

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

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28 September 2010 9 6th Colloquium

BTS: Direct measurement of capacity utilisation

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28 September 2010 10 6th Colloquium

Summary of the data

  • Countries in bold are not included

in the strictly balanced sample

Output gap Capacity utilisation (vintages) (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

  • No. countries

22 22

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28 September 2010 11 6th Colloquium

F4 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F4 F1 F2 F3 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 F4 F3 F4 F3 F4 F3 F4 F3 F4 F3 F4 F3 F4 F3 F4 F3 F4 F3 F4 F3 F4

Data setup and revision process: Annual data

Source: OECD, calculations KOF

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 1970 … 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Fx Rx Reference Period 2002 Forecast number x Release number x Vintages / Release Dates 2007 2008 2009 1995 1996 1997 1998 1999 2000 2001 2003 2004 2005 2006 R1 R2 R3 R4 R5 R6 R7 R8 R8 R6 R4 R2 R7 R8 R5 R6 R7 R8 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R7 R8 R1 R2 R3 R4 R5 R6 R1 R2 R3 R4 R1 R2 … … … … … … … … … … … … … … … … … … … … … … … … … … … … …

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28 September 2010 12 6th Colloquium

Releases of annual output gaps: averaged bal.panel

Source: OECD, calculations KOF

  • 2.0
  • 1.5
  • 1.0
  • 0.5

0.0 0.5 1.0 1.5 2.0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

  • rel. 1
  • rel. 2
  • rel. 3
  • rel. 4
  • rel. 5
  • rel. 6
  • rel. 7
  • rel. 8

CU rate % of potential GDP 79.5 80.0 80.5 81.0 81.5 82.0 82.5 83.0 83.5 CU rate (in %)

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28 September 2010 13 6th Colloquium

Revision process of annual output gaps: avg.bal.panel

Source: OECD, calculations KOF

  • 1.0
  • 0.5

0.0 0.5 1.0 1.5 2.0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 %-points

  • rev. 4
  • rev. 5
  • rev. 6
  • rev. 2
  • rev. 1
  • rev. 7
  • rev. 3

77.5 78.5 79.5 80.5 81.5 82.5 83.5 CU rate CU rate (in %)

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28 September 2010 14 6th Colloquium

Descriptive Statistics of the annual releases/vintages

Obs Mean St.D. Min. Max. Obs Mean St.D. Min. Max. degree (in %) 353 81.51 4.40 64.54 92.30 170 81.43 2.97 74.43 87.53 Release 1 287 -0.93 1.98 -8.79 5.50 170 -0.79 1.58 -4.86 5.50 Release 2 283 -0.55 1.65 -5.73 5.68 170 -0.64 1.58 -4.27 5.68 Release 3 287 -0.40 1.75 -5.50 6.39 170 -0.53 1.64 -4.31 6.39 Release 4 283 -0.46 1.90 -7.31 6.41 170 -0.46 1.62 -4.06 6.41 Release 5 287 -0.38 1.97 -7.32 7.66 170 -0.38 1.65 -4.53 7.66 Release 6 283 -0.51 1.90 -9.54 6.77 170 -0.28 1.59 -3.16 6.77 Release 7 287 -0.48 1.96 -9.54 6.84 170 -0.24 1.64 -5.11 6.84 Release 8 283 -0.52 2.02 -9.66 6.83 170 -0.13 1.67 -4.17 6.83 Strictly balanced panel Maximum panel (22 countries, 1995-2009) (17 countries, 1996-2005) Capacity utilisation (in % of full capacity) Output gap (in % of potential GDP)

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28 September 2010 15 6th Colloquium

Descriptive statistics: Annual data

  • Obs. Mean Sign. St.Dev. Min. Max. Skewness Kurtosis Jarque-Bera Sign.

Revision 1 265 0.19 0.00 0.71 -2.90 3.06 0.09 4.44 218.09 0.00 Cumulative Revision 2 265 0.37 0.00 0.94 -2.46 3.98 0.33 1.68 36.10 0.00 Cumulative Revision 3 243 0.53 0.00 1.18 -2.51 6.83 1.27 3.97 225.36 0.00 Cumulative Revision 4 243 0.64 0.00 1.29 -3.55 6.86 0.76 2.57 90.20 0.00 Cumulative Revision 5 221 0.64 0.00 1.24 -3.99 6.14 0.49 2.38 61.01 0.00 Cumulative Revision 6 221 0.68 0.00 1.27 -3.71 5.83 0.29 1.26 17.70 0.00 Cumulative Revision 7 199 0.65 0.00 1.20 -3.95 3.90

  • 0.11

0.66 4.03 0.13 Revision 1 170 0.15 0.00 0.63 -2.42 3.06 1.12 5.13 222.31 0.00 Cumulative Revision 2 170 0.26 0.00 0.86 -2.43 3.77 0.28 1.91 28.06 0.00 Cumulative Revision 3 170 0.33 0.00 1.01 -2.51 4.61 0.74 2.39 56.18 0.00 Cumulative Revision 4 170 0.41 0.00 1.12 -3.55 3.81

  • 0.02

0.80 4.58 0.10 Cumulative Revision 5 170 0.52 0.00 1.14 -3.99 4.28 0.02 1.53 16.58 0.00 Cumulative Revision 6 170 0.56 0.00 1.21 -3.71 4.01

  • 0.01

0.88 5.50 0.06 Cumulative Revision 7 170 0.66 0.00 1.24 -3.95 3.90

  • 0.15

0.59 3.11 0.21 Maximum panel Strictly balanced panel

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28 September 2010 16 6th Colloquium

Histogram total revisions using annual data

.1 .2 .3 .4 Density

  • 4
  • 2

2 4 Cumulative Revision 7

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28 September 2010 17 6th Colloquium

Correlation coefficients between revisions

1 2 3 4 5 6 7 Revision 1 1.00 -0.18 0.14 -0.23 -0.04 -0.13 -0.08 Revision 2 1.00 -0.12 -0.06 -0.08 -0.09 -0.04 Revision 3 1.00 -0.01 -0.01 -0.07 -0.10 Revision 4 1.00 -0.17 -0.05 -0.05 Revision 5 1.00 -0.05 0.06 Revision 6 1.00 -0.12 Revision 7 1.00

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28 September 2010 18 6th Colloquium

Estimation design

  • Data revisions contain news

revisions are orthogonal to earlier releases and not predictable yRx(t) = yR1(t) + ε(t), cov(yR1(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?

  • ∆Rx-R1y(t) = α(i) + γ yR1(i,t) + δ CU(i,t) + β(t) + ε(i,t)

– ∆Rx-R1 y(t) represent the cumulative revisions 1 to 7 – Hypotheses: α(i) = 0 , γ = 0 , δ = 0

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28 September 2010 19 6th Colloquium

Regression results using increasing revision horizons

(1) (2) (3) (4) (5) (6) (7) Dependent variable: R2-R1 R3-R1 R4-R1 R5-R1 R6-R1 R7-R1 R8-R1

  • 0.22
  • 0.35
  • 0.48
  • 0.55
  • 0.59
  • 0.54
  • 0.47

(-3.74) (-6.13) (-8.00) (-6.69) (-7.35) (-6.25) (-5.63) 0.06 0.13 0.17 0.19 0.23 0.16 0.16 (1.53) (2.50) (2.44) (2.66) (3.29) (1.99) (2.19) Adjusted R2 0.19 0.26 0.32 0.37 0.47 0.45 0.49 Number of observations 170 170 170 170 170 170 170 Number of countries 17 17 17 17 17 17 17 Number of periods 10 10 10 10 10 10 10 p-value LR-test for country effects 0.05 0.09 0.00 0.00 0.00 0.00 0.00 p-value LR-test for time effects 0.00 0.00 0.00 0.00 0.00 0.00 0.00 p-value LR-test for time and country effects 0.00 0.00 0.00 0.00 0.00 0.00 0.00 First release (y R 1) Capacity utilisation rate

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28 September 2010 20 6th Colloquium

Goodness-of-fit across different revisions

0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 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 adj.R2

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28 September 2010 21 6th Colloquium

Regression results: Annual data

Dependent variable: cumulative revision 7 (Δ R8-R1y) (1) (2) (3) (4) (5)

  • 0.39
  • 0.47
  • 0.49
  • 0.42
  • 0.48

(-6.09) (-5.63) (-6.00) (-5.98) (-5.91) 0.16 0.18 0.12 (2.19) (2.57) (1.90) 0.17 0.12 (2.52) (1.92) Adjusted R2 0.47 0.49 0.49 0.50 0.50 Number of observations 170 170 167 167 167 Number of countries 17 17 17 17 17 Number of periods 10 10 10 10 10 p-value LR-test for country effects 0.00 0.00 0.00 0.00 0.00 p-value LR-test for time effects 0.00 0.00 0.00 0.00 0.00 p-value LR-test for time and country effects 0.00 0.00 0.00 0.00 0.00 First release (y R 1) Capacity utilisation rate Capacity utilisation rate, lagged one period

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28 September 2010 22 6th Colloquium

Conclusions

  • Revisions in OECD output gap estimates

are almost of a similar magnitude as the output gap estimates itself

  • During the period 1996-2005 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