P3.2

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Transcript P3.2 

Using business tendency surveys
to reduce revisions
Jan-Egbert Sturm
14 December 2009
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.
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14 December 2009
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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


International Seminar on Early Warning and Business Cycle Indicators
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Real-time data
Vintage
Final data
Evaluation
Final data
Final Partly revised
Partly revised
First-released
First-released
Time
Economic forecast
Political decisions
International Seminar on Early Warning and Business Cycle Indicators
14 December 2009
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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
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‘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
International Seminar on Early Warning and Business Cycle Indicators
14 December 2009
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Industrial production:
Comparing the first revision with the total revision
3.5
1.5
0.5
-0.5
-1.5
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2001:06
2000:12
2000:06
1999:12
1999:06
1998:12
1998:06
1997:12
1997:06
1996:12
-3.5
1996:06
-2.5
1995:12
Revision (in %-Points)
2.5
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Current account:
Data set up and revision processes
2003
2004
2005
2006
2007
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 . . Jun
...
2000
2000
2000
2000
2001
2001
2001
2001
2002
2002
2002
2002
2003
2003
2003
2003
2004
2004
2004
2004
I
II
III
IV
I
II
III
IV
I
II
III
IV
I
II
III
IV
I
II
III
IV
F
F
F
F
F
F
F
F
F
1st revision
2nd revision
3rd revision
1st winter revision
2nd winter revision
3rd winter revision
1st summer revision
2nd summer revision
3rd summer revision
To be revised next summer
To be revised next winter
Other revisions
F First release
Benchmark revision
Final data
International Seminar on Early Warning and Business Cycle Indicators
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Current account:
Significant biases? Looking at averages
Current account
Mean
Sign.
Total revisions
Early revisions
Summer revisions
Winter revisions
Benchmark revisions
Other revisions
Total revisions
Early revisions
Summer revisions
Winter revisions
Benchmark revisions
Other revisions
371.61
-27.87
656.17
-4.12
-325.46
75.69
5.2%
0.2%
7.9%
0.1%
-3.4%
0.5%
0.29
0.88
0.06
0.95
0.00
0.39
Income side
Mean
Sign.
Levels in millions of CHF
1'795.71
0.00
292.87
0.10
1'800.39
0.00
119.02
0.14
-723.09
0.00
314.03
0.02
Expenditures side
Mean
Sign.
1'424.10
320.75
1'072.20
123.13
-327.41
238.34
0.00
0.01
0.00
0.18
0.00
0.02
Relative to first release (in perc.)
0.12
3.0%
0.00
2.7%
0.92
0.4%
0.11
0.6%
0.02
3.0%
0.00
2.1%
0.83
0.2%
0.14
0.2%
0.00
-1.2%
0.00
-0.6%
0.54
0.5%
0.01
0.4%
0.00
0.01
0.00
0.18
0.00
0.02
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Output gaps:
Revision process of annual output gaps: avg.bal.panel
1.5
%-points
1.0
0.5
0.0
-0.5
-1.0
1996
1997
rev. 1
Source: OECD, calculations KOF
1998
rev. 2
1999
2000
rev. 3
rev. 4
2001
rev. 5
2002
rev. 6
2003
2004
2005
rev. 7
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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”
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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
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Industrial production:
Relationship first release and first revision
Revision (in %-Points)
3
2
1
0
-20
-15
-10
-5
0
5
10
15
20
25
30
First release IP-growth
-1
-2
-3
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Hotels
Industry
0.03
-0.02
0.05
-0.02
0.01
-0.01
0.01
0.04
0.04
-0.01
Income
Expend.
-0.03
0.01
0.15
0.23
0.14
0.16
0.08
0.26
0.04
0.00
-0.03
0.12
0.00
0.00
0.00
0.07
-0.02
0.06
-0.01
0.11
-0.03
0.03
0.15
0.09
Total revisions
Business situation
0.02
Stock of intermediate
inputs
0.01
Business situation
Cur.acc.
Business situation
Stock of intermediate
inputs
Wholesale
Business situation
Change in hotel nights
by foreigners (Y-o-Y)
Industry
Expected hotel nights
by foreigners
Wholesale
Without any KOF indicators
Change in hotel nights
by foreigners (Y-o-Y)
Hotels
Expected hotel nights
by foreigners
Without any KOF indicators
Current account: Goodness of fit (adj. R2)
Early revisions
Summer revisions
Winter 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
Expend.
-0.03
-0.02
0.25
0.41
0.20
0.34
0.16
0.53
0.07
0.09
0.05
0.24
0.02
-0.02
0.17
0.16
0.18
0.16
0.06
0.07
0.14
0.10
0.24
0.08
Benchmark revisions
Other 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
Expend.
0.35
0.40
0.37
0.38
0.36
0.38
0.36
0.39
0.39
0.38
0.34
0.43
0.01
0.04
-0.01
0.01
-0.02
0.02
0.00
0.06
-0.01
0.04
0.09
0.02
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delta=0
Hausman
LR-Test
Adj.R2
#Obs.
Revision
Revision
Revision
Revision
Revision
Revision
delta
Revision 1
Cumulative
Cumulative
Cumulative
Cumulative
Cumulative
Cumulative
Revision
Revision
Revision
Revision
Revision
Revision
gamma=0
Revision 1
Cumulative
Cumulative
Cumulative
Cumulative
Cumulative
Cumulative
gamma
Output gaps:
Regression results: Annual data
2
3
4
5
6
7
-0.22
-0.30
-0.43
-0.37
-0.42
-0.37
-0.39
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.08
0.14
0.10
0.13
0.12
0.13
0.01
0.01
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.02
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.26
0.36
0.50
0.42
0.54
0.42
0.49
304
279
279
254
254
229
229
2
3
4
5
6
7
-0.17
-0.27
-0.39
-0.40
-0.46
-0.41
-0.41
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.09
0.14
0.13
0.15
0.15
0.16
0.18
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.01
0.00
0.14
0.12
0.00
0.00
0.00
0.00
0.00
0.21
0.27
0.34
0.35
0.45
0.44
0.50
200
200
200
200
200
200
200
Significant at a 1% level
International Seminar on Early Warning and Business Cycle Indicators
14 December 2009
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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
International Seminar on Early Warning and Business Cycle Indicators
14 December 2009
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30th CIRET Conference, New York
Economic Tendency Surveys
and the Services Sector
Hosted by The Conference Board, New York, NY
14 December 2009
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:
 Papers deadline:

February 28, 2010
June 30, 2010
Further information to be found on: http://www.ciret.org
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14 December 2009
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