17 October 2010 The Information Content of Capacity Utilisation Rates for Output Gap Estimates...

17 October 2010

The Information Content of Capacity Utilisation Rates for Output Gap EstimatesMichael Graff and Jan-Egbert Sturm

17 October 2010 23rd International Seminar, Moscow

Overview

Introduction and motivation Data

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

Empirical analysis Design Results

Conclusions


Evaluation

Real-time data

Final

Partly revised

First-released

Vintage

Final data

Economic forecastPolitical decisions

Final data Partly revised

First-released

Time


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


Measurement of the output gap in real time

Problems with real-time estimates of output gap data Late availability and revisions to Y

• All GDP data are either ex-post estimates, or real-time “nowcasts” or ex-ante forecasts

End-point problem when estimating Y* Orphanides & Van Norden (2002)

Revisions are of similar magnitude as the gap itself Hence, questionable 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• …• This paper: output gap capacity utilisation from BTS


Some methods to estimate potential output

Smoothing real GDP using a filter 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

ln Y = a + α ln L + (1 – α) ln K + TFPwhere L is labour, K capital and TFP ‘total factor productivity’

ln Y* = a + α ln L* + (1 – α) ln K* + TFP*,where ‘*’ denotes ‘potential’


Output gap data: OECD Economic Outlook

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

First vintage: Jun. 1995 (data cover 1970-1996) Last vintage: Dec. 2009 (data cover 1970-2011)

Bi-annual vintages with data at quarterly frequency First vintage: Dec. 2003 (data cover 1970q1-2005q4) Last vintage: Dec. 2009 (data cover 1970q1-2011q4)

The resulting revision data sets are unbalanced Annual data: 22 countries (up to 287 obs.) Quarterly data: 18 countries (up to 338 obs.)

The largest balanced panels thereof are Annual data: 17 countries, 1996-2005 (170

obs.) Quarterly data: 14 countries, 2003q3-2005q4 (140

obs.)


Capacity utilisation data

Sources: European Commission, OECD MEI, KOF, national sources (in case of Belgium and New Zealand) Business tendency survey data Question asks for assessment of 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 are (almost) not revised


BTS: Direct measurement of capacity utilisation

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3rd International Seminar, Moscow

Annual data

Countries in bold are not included in the strictly balanced sample

Output gap Capacity utilisation (vintages) (reference period)

Australia 1995:Jun–2009:Dec 1996q1-2009q4Austria 1995:Jun–2009:Dec 1996q1-2009q4Belgium 1995:Jun–2009:Dec 1980q1-2009q4Czech Republic 2005:Dec–2009:Dec 1993q2-2009q4Denmark 1995:Jun–2009:Dec 1987q1-2009q4Finland 1995:Jun–2009:Dec 1993q1-2009q4France 1995:Jun–2009:Dec 1985q1-2009q4Germany 1995:Jun–2009:Dec 1985q1-2009q4Hungary 2005:Dec–2009:Dec 1996q1-2009q4Ireland 1995:Jun–2009:Dec 1985q1-2008q2Italy 1995:Jun–2009:Dec 1970q1-2009q4Japan 1995:Jun–2009:Dec 1978q1-2009q4Luxemburg 2005:Dec–2009:Dec 1985q1-2009q4Netherlands 1995:Jun–2009:Dec 1985q1-2009q4New Zealand 1997:Jun–2009:Dec 1970q1-2009q4Norway 1995:Jun–2009:Dec 1987q1-2009q4Poland 2006:Dec–2009:Dec 1992q2-2009q4Portugal 1995:Jun–2009:Dec 1987q1-2009q4Spain 1995:Jun–2009:Dec 1987q2-2009q4Sweden 1995:Jun–2009:Dec 1996q1-2009q4Switzerland 1995:Jun–2009:Dec 1970q1-2009q4United Kingdom 1995:Jun–2009:Dec 1985q1-2009q4

No. countries 22 22

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F4F2 F3 F4

F1 F2 F3 F4F1 F2 F3 F4

F1 F2 F3F1 F2

F1 F2F1 F2

F1 F2F1 F2

F1 F2F1 F2

F1 F2F1 F2

F1 F2F1 F2

F4F3 F4

F3 F4F3 F4

F3 F4F3 F4

F3 F4F3 F4

F3 F4F3 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 Dec1970…19911992199319941995199619971998199920002001200220032004200520062007200820092010

FxRx

Ref

eren

ce P

erio

d

2002

Forecast number xRelease number x

Vintages / Release Dates2007 2008 20091995 1996 1997 1998 1999 2000 2001 2003 2004 2005 2006

R1 R2 R3 R4 R5 R6 R7 R8

R8R6R4R2

R7 R8R5 R6 R7 R8R3 R4 R5 R6 R7 R8

R1 R2 R3 R4 R5 R6 R7 R8R1 R2 R3 R4 R5 R6 R7 R8





R1 R2 R3 R4 R5 R6R1 R2 R3 R4

R1 R2

… … … … … … … … … … … … … … … … … … … … … … … … … … … … …

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Releases of annual output gaps: unbalanced panel

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Releases of annual output gaps: averaged bal. panel


-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

83.5CU rate (in %)

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Average absolute revisions of annual OG,balanced panel

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Average revisions of annual OG, balanced panel

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Cumulative revisions of annual OG, balanced panel

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Descriptive Statistics of the annual releases/vintages

Obs Mean St.D. Min. Max. Obs Mean St.D. Min. Max.

degree (in %) 353 81.5 4.40 64.5 92.3 170 81.4 2.97 74.4 87.5

Release 1 287 -0.93 1.98 -8.79 5.50 170 -0.79 1.58 -4.86 5.50Release 2 283 -0.55 1.65 -5.73 5.68 170 -0.64 1.58 -4.27 5.68Release 3 287 -0.40 1.75 -5.50 6.39 170 -0.53 1.64 -4.31 6.39Release 4 283 -0.46 1.90 -7.31 6.41 170 -0.46 1.62 -4.06 6.41Release 5 287 -0.38 1.97 -7.32 7.66 170 -0.38 1.65 -4.53 7.66Release 6 283 -0.51 1.90 -9.54 6.77 170 -0.28 1.59 -3.16 6.77Release 7 287 -0.48 1.96 -9.54 6.84 170 -0.24 1.64 -5.11 6.84Release 8 283 -0.52 2.02 -9.66 6.83 170 -0.13 1.67 -4.17 6.83

Strictly balanced panelMaximum 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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Estimation design

Data revisions contain news revisions are orthogonal to earlier releases and not predictable

yRx(t) = yR1(t) + (t), cov(yR1(t),(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) = (i) + yR1(i,t) + CU(i,t) + (t) + (i,t)

– Rx-R1y(t) represent the cumulative revisions 1 to 7

– Hypotheses: (i) = 0 , = 0 , = 0

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Efficiency regressions, 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 R20.19 0.26 0.32 0.37 0.47 0.45 0.49

Number of observations 170 170 170 170 170 170 170Number of countries 17 17 17 17 17 17 17Number 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 0.00p-value LR-test for time effects 0.00 0.00 0.00 0.00 0.00 0.00 0.00p-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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Goodness-of-fit across different revisions

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Revision 1 CumulativeRevision 2

CumulativeRevision 3





without CU variable CU variable included

adj.R2

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Additional 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 0.50Number of observations 170 170 167 167 167Number of countries 17 17 17 17 17Number of periods 10 10 10 10 10

p-value LR-test for country effects 0.00 0.00 0.00 0.00 0.00p-value LR-test for time effects 0.00 0.00 0.00 0.00 0.00p-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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… … … … … … … … … … … …

… … … … … … … … … … …

F4F4F3 F4F3 F4F2 F3 F4F2 F3 F4F1 F2 F3 F4F1 F2 F3 F4

F1 F2

Data setup and revision process: Quarterly data


Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec Jun Dec1970 I… …2003 I2003 II2003 III2003 IV2004 I2004 II2004 III2004 IV2005 I2005 II2005 III2005 IV… …2010 IV

FxRx

200920042003 2005 2006 2007 2008

Forecast number xRelease number x

Based on less informationBased on more information

Vintages / Release Dates

Ref

eren

ce P

erio

d


R2 R3 R4 R5 R6 R7 R8R2 R3 R4 R5 R6 R7 R8





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Releases of quarterly output gaps: unbalanced panel

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Average absolute revisions of quarterly OG,balanced panel

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Average revisions of quarterly OG, balanced panel

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Cumulative revisions of quarterly OG, balanced panel

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Efficiency regressions, quarterly data

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Conclusions

Revisions to OECD output gap estimates are almost of a similar magnitude as the output gap estimates

During the (short) sample period, output gaps were overall revised upwards Hence, revisions appear to be predictable without further information

Yet, in addition to this, real time BTS data on capacity add further explanatory power to explain revision process OECD real-time output gap estimates are not informationally efficient Referring to the survey data available in real time could have improved

output gap estimates Findings are robust with respect to sample and frequency

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To be done …

Carry out real-time forecasting exercise on country level Do the results hold when using other output gap estimates

(e.g. those produced by HP filters) Do other BTS data, e.g. business climate indicators, add information … (suggestions are highly appreciated)

17 October 2010 The Information Content of Capacity Utilisation Rates for Output Gap Estimates...

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