14 december 2009 using business tendency surveys to reduce revisions jan-egbert sturm

14 December 2009

Using business tendency surveys to reduce revisionsJan-Egbert Sturm

14 December 2009

2International Seminar on Early Warning and Business Cycle Indicators

Underlying papers

Jacobs, J.P.A.M. and J.-E. Sturm (2005), “Do ifo indicators help explain revisions in German industrial production?”, in: Ifo Survey Data in Business Cycle and Monetary Policy Analysis, editors J.-E. Sturm and T. Wollmershäuser, Physica Verlag, 93-114.

Jacobs, J.P.A.M. and J.-E. Sturm (2008), The information content of KOF indicators on Swiss current account data revisions, Journal of Business Cycle Measurement and Analysis, 4:2, 163-183.

Graff, M. and J.-E. Sturm (2009), “The output gap revisited: Can survey data on capacity utilisation improve output gap estimates in real time?”, mimeo.

14 December 2009


Outline

Motivation Increase the information contained in preliminary data

by predicting future revisions Real-time data sets

Industrial production in Germany (time series) Current account statistics in Switzerland (system / time series) Output gap estimates of the OECD (panel data)

Business tendency surveys Ifo indicators for Germany KOF indicators for Switzerland Capacity utilisation rates in the OECD countries

Modelling strategy and empirical results

Concluding remarks

14 December 2009


Evaluation

Real-time data

Final

Partly revised

First-released

Vintage

Final data

Economic forecastPolitical decisions

Final data Partly revised

First-released

Time

14 December 2009


Real-time data sets

German industrial production (source: Statistisches Bundesamt)“Indizes der Produktion und der Arbeitsproduktivität im Produzierenden Gewerbe”, Fachserie 4, Reihe 2.1

Monthly real growth rates (for entire Germany) Vintages: 1996:3–2003:10, Coverage: 1995:12–2003:8

Swiss current account statistics (source: Swiss National Bank, Oct. 2006) Monthly vintages with quarterly (nominal) series

– Income (exports) and Expenditures (imports) categories Vintages: 1995:8–2006:9 (& 2007:7), Coverage 1995:Q2–2006:Q2

OECD output gap data (source: OECD Main Economic Indicators) Bi-annual vintages with annual or quarterly series

(for resp. 25 or 18 countries)– Estimates based on a production function approach– Output gap = (Y – Y*)/Y* ≈ y – y*

Vintages: 1995:6–2009:6, Coverage: 1996–2008 or 1995Q4–2009Q2

14 December 2009


‘Final’ release data

Besides analysing first revisions, we concentrate on the final/total revision The latter is conceptually more important

Will we ever have true final data? Industrial production

– Take most recent vintage as final release

– Allow for at least two years between first and final release Current account

– Take most recent vintage as final release

– Distinguish between different types of revisions

• Benchmark / Summer / Winter / Early / Other revisions Output gap

– Revisions do not appear to die out – no final release

14 December 2009


Industrial production:Comparing the first revision with the total revision

Rev

isio

n (

in %

-Po

ints

)

-3.5

-2.5

-1.5

-0.5

0.5

1.5

2.5

3.51

99

5:1

2

19

96

:06

19

96

:12

19

97

:06

19

97

:12

19

98

:06

19

98

:12

19

99

:06

19

99

:12

20

00

:06

20

00

:12

20

01

:06

14 December 2009


Current account:Data set up and revision processes

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S...2000 I2000 II2000 III2000 IV2001 I2001 II2001 III2001 IV2002 I2002 II2002 III2002 IV2003 I2003 II2003 III2003 IV2004 I2004 II2004 III2004 IV

1st revision To be revised next summer2nd revision 2nd winter revision 2nd summer revision To be revised next winter3rd revision 3rd winter revision 3rd summer revision

2004 2005 20062003. . Jun

2007

1st summer revision1st winter revision

FF

FF

FF

FF

F

F First release

Other revisionsBenchmark revisionFinal data

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10

International Seminar on Early Warning and Business Cycle Indicators

Current account:Significant biases? Looking at averages

Mean Sign. Mean Sign. Mean Sign.

Total revisionsEarly revisionsSummer revisionsWinter revisionsBenchmark revisionsOther revisions

Total revisionsEarly revisionsSummer revisionsWinter revisionsBenchmark revisionsOther revisions

Relative to first release (in perc.)

Income side Expenditures sideCurrent account

Levels in millions of CHF371.61 0.29-27.87 0.88656.17 0.06

-4.12 0.95-325.46 0.00

75.69 0.39

5.2% 0.120.2% 0.927.9% 0.020.1% 0.83

-3.4% 0.000.5% 0.54

1'795.71 0.00292.87 0.10

1'800.39 0.00119.02 0.14

-723.09 0.00314.03 0.02

3.0% 0.000.4% 0.113.0% 0.000.2% 0.14

-1.2% 0.000.5% 0.01

1'424.10 0.00320.75 0.01

1'072.20 0.00123.13 0.18

-327.41 0.00238.34 0.02

2.7% 0.000.6% 0.012.1% 0.000.2% 0.18

-0.6% 0.000.4% 0.02

14 December 2009

12


Output gaps: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

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

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

%-points

14 December 2009

13


Business Tendency Survey data

Business Tendency Survey data is not revised over time Ifo Business Tendency Survey for Germany

Monthly survey covering 7,000 firms

– “We judge our current business situation for product group X to be”

• Good / Satisfactorily / Bad KOF Business Tendency Surveys for Switzerland

Monthly/Quarterly surveys covering 11,000 firms

– Hotel nights foreigners (compared to last year & expectations)

– Wholesale trade business situation

– Industry business situation & stock of intermediate inputs Capacity utilisation rates

Sources: European Commission, OECD, national sources “The current level of capacity utilisation”

14 December 2009

14


Modelling strategy

Are data revisions predictable? Are first releases “informationally efficient”? Rx-R1y(t) = + yR1(t) + BTS(i,t) + (t)

– Rx-R1y(t) represent the revisions

– Hypotheses: = 0 , = 0 , = 0 Industrial production

Estimates of industrial production are based on survey results

– For firms which do not respond on time, figures from previous month were taken

– This leads to downward bias of first release of absolute growth rate Current account

The two sides of the current account are highly correlated Output gaps

Allow for fixed country effects and random time effect

14 December 2009

15


Industrial production:Relationship first release and first revision

-3

-2

-1

0

1

2

3

-20 -15 -10 -5 0 5 10 15 20 25 30

Rev

isio

n (

in %

-Po

ints

)

First release IP-growth

14 December 2009

17


Current account: Goodness of fit (adj. R2)

Whole-sale

Whole-sale

Exp

ecte

d ho

tel n

ight

s

by f

orei

gner

s

Cha

nge

in h

otel

nig

hts

by f

orei

gner

s (Y

-o-Y

)

Bus

ines

s si

tuat

ion

Bus

ines

s si

tuat

ion

Sto

ck o

f in

term

edia

te

inpu

ts

Exp

ecte

d ho

tel n

ight

s

by f

orei

gner

s

Cha

nge

in h

otel

nig

hts

by f

orei

gner

s (Y

-o-Y

)

Bus

ines

s si

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ion

Bus

ines

s si

tuat

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Sto

ck o

f in

term

edia

te

inpu

ts

Hotels IndustryW

itho

ut a

ny K

OF

indi

cato

rsHotels Industry

Wit

hout

any

KO

F in

dica

tors

Cur.acc. 0.01 0.02 0.03 -0.02 0.05 -0.02 0.01 -0.01 0.01 0.04 0.04 -0.01

Income -0.03 0.15 0.14 0.08 0.04 -0.03 0.00 0.00 -0.02 -0.01 -0.03 0.15Expend. 0.01 0.23 0.16 0.26 0.00 0.12 0.00 0.07 0.06 0.11 0.03 0.09

Total revisions Early revisions

Cur.acc. -0.02 -0.04 -0.04 -0.03 -0.04 -0.04 0.00 0.00 -0.01 0.06 0.00 -0.02

Income -0.03 0.25 0.20 0.16 0.07 0.05 0.02 0.17 0.18 0.06 0.14 0.24Expend. -0.02 0.41 0.34 0.53 0.09 0.24 -0.02 0.16 0.16 0.07 0.10 0.08

Summer revisions Winter revisions

Cur.acc. 0.01 0.00 -0.01 -0.01 0.02 0.01 0.02 -0.01 0.00 -0.01 -0.01 0.05 Income 0.35 0.37 0.36 0.36 0.39 0.34 0.01 -0.01 -0.02 0.00 -0.01 0.09Expend. 0.40 0.38 0.38 0.39 0.38 0.43 0.04 0.01 0.02 0.06 0.04 0.02

Benchmark revisions Other revisions

14 December 2009

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Output gaps:Regression results: Annual data

Revision 1Cumulative Revision 2Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7

Revision 1Cumulative Revision 2 Cumulative Revision 3 Cumulative Revision 4 Cumulative Revision 5 Cumulative Revision 6 Cumulative Revision 7

gam

ma

gam

ma=

0

-0.22 0.00

-0.30 0.00

-0.43 0.00

-0.37 0.00

-0.42 0.00

-0.37 0.00

-0.39 0.00

-0.17 0.00

-0.27 0.00

-0.39 0.00

-0.40 0.00

-0.46 0.00

-0.41 0.00

-0.41 0.00

delta

delta

=0

0.06 0.010.08 0.01

0.14 0.00

0.10 0.01

0.13 0.00

0.12 0.00

0.13 0.00

0.03 0.180.09 0.010.14 0.00

0.13 0.00

0.15 0.00

0.15 0.00

0.16 0.00

Hau

sman

LR-T

est

0.00 0.000.00 0.000.00 0.000.01 0.000.00 0.00

0.02 0.000.01 0.00

0.00 0.140.00 0.120.00 0.000.01 0.000.00 0.000.01 0.000.00 0.00

Adj

.R2

0.260.360.500.420.540.420.49

0.210.270.340.350.450.440.50

Significant at a 1% level

#Obs

.

279

254

229

200

200

200

304

279

254

229

200

200

200

200

14 December 2009

20


Conclusions

German industrial production growth: Especially the first revisions have considerable size Carry-over effect explains large part of first revision Ifo indicator helps explain initial revisions

Swiss current account statistics: Since end of the 1990s, revisions have increased in absolute size We distinguish between benchmark, summer, winter, early and other revisions

– Summer revisions are the most important KOF indicators contain information on revisions

OECD Output gaps: Revisions are of a similar magnitude as the output gap itself During the period 1995-2005 output gaps

have overall been revised towards their mean– Hence, revisions appear to be predictable

BTS data on capacity utilisation can partly explain revisions

14 December 2009

30th CIRET Conference, New York Economic Tendency Surveys and the Services SectorHosted by The Conference Board, New York, NY

14 December 2009

22


Centre for International Research on Economic Tendency Surveys (CIRET)

The overall aim of CIRET conferences is to encourage and improve communication, exchange and co-operation between academics and practitioners who conduct economic surveys, analyse survey data and develop or make use of cyclical indicators

30th CIRET Conference in New York: October 13 – October 16, 2010 Economic Tendency Surveys and the Services Sector

– Special Topic: Economic Tendency Surveys and Financial Markets

Submission Procedure Abstracts deadline: February 28, 2010 Papers deadline: June 30, 2010

Further information to be found on: http://www.ciret.org

14 december 2009 using business tendency surveys to reduce revisions jan-egbert sturm

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