Revisions analysis of OECD
composite leading indicators
(CLI)
Third Joint European Commission
OECD Workshop on Business and Consumer Tendency Surveys
Emmanuelle Guidetti
1
Introduction
A leading indicator is a statistic that signals the movements, up and
down, of future economic activity before they occur, and it may also
give some indication of the magnitude of those movements.
What is the purpose of the OECD CLI?
How is the OECD CLI constructed?
What is the current period performance of the CLI?
2
What is the purpose of the OECD CLI?
OECD area Composite Leading Indicator (CLI) and economic activity
(long-term average = 1)
1.08
1.06
1.04
1.02
1
0.98
0.96
0.94
Apr-07
Jan-07
Oct-06
Jul-06
Apr-06
Jan-06
Oct-05
Jul-05
Apr-05
Jan-05
Oct-04
Jul-04
Apr-04
Jan-04
Oct-03
Jul-03
Apr-03
Jan-03
Oct-02
Jul-02
Apr-02
Jan-02
Oct-01
Jul-01
Apr-01
Jan-01
Oct-00
Jul-00
Apr-00
Jan-00
Jul-99
Oct-99
Apr-99
Jan-99
0.92
OECD economic activity above the long-term average
OECD economic activity below the long-term average
OECD CLI
3
How is the OECD CLI constructed?
Selection of
Reference
series
Selection
of
components series
Weighting
PAT box
(de-trending
the series)
Normalisation
(cyclical amplitude
homogenised)
Periodicity
Transformation
(monthly basis)
Smoothing
(reduce irregularity)
Presentation of CLI
Aggregation
into a single indicator (the minimum % of
component series required is 60%)
- Amplitude adjustment (refers to the deviation
from the long-term trend of the series and
focuses on the cyclical behaviour of the indicator)
- Trend restoration (gives information about the
likely rate and amplitude of changes)
- Six months rate of change (is less volatile and
provides earlier and clearer signals for future
turning points than the CLI itself.)
4
What is the current performance of the CLI?
The aim of the current analysis on CLIs is to evaluate the
quality of the indicator when they are first released in order to:
•
identify areas where their reliability could be improved
•
provide further information to users on their use for
economic analyses.
5
Why do we have revisions?
•
Timeliness/availability
•
Frequency
•
Smoothness
•
Other factors
6
1st and 2nd
Euro area
G7
OECD area
United Kingdom
Switzerland
Sweden
Spain
Portugal
Norway
Netherlands
Italy
Ireland
Greece
Germany
France
Finland
Denmark
Belgium
Austria
Japan
Australia
United States
Mexico
Canada
Size of revisions
Revision: Rt=Lt-Pt
Mean Absolute Revision to first estimates of Year-on-Year growth rates
from Dec98 (Aug00) to Aug06
2.0
1.5
1.0
0.5
0.0
2nd and 3rd
7
Size of revisions over time
Mean Absolute Revision between 1st estimate and those published one month later for
the entire period and two sub-period
Dec98/Aug00 to Sep02
Oct02 to Aug06
Euro area
G7
OECD area
United Kingdom
Switzerland
Sweden
Spain
Portugal
Norway
Netherlands
Italy
Ireland
Greece
Germany
France
0.0
Finland
0.0
Denmark
0.5
Belgium
0.5
Austria
1.0
Japan
1.0
Australia
1.5
United States
1.5
Mexico
2.0
Canada
2.0
Dec98/Aug00 to Aug06
8
Assessment of bias
Mean revision between 1st estimate and those published one month and between
2nd and 3rd releases for year-on-year growth rate over the entire period
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1st and 2nd estimates
Euro area
G7
OECD area
United Kingdom
Switzerland
Sweden
Spain
Portugal
Norway
Netherlands
Italy
Ireland
Greece
Germany
France
Finland
Denmark
Belgium
Austria
Japan
Australia
United States
Mexico
Canada
-1.2
2nd and 3rd estimates
9
Reliability of 1st estimate as a signal of shortterm expansion or slowdown in economic
activity
First measure is the sign of the movements
around 90% of the time, for almost of the countries, the sign
of the initial estimates of year-on-year growth rates are the
same as those published one month later. This ratio
becomes 95% while talking about zone aggregates.
Second measure is the acceleration/deceleration test
Around 80% of the time, for around 40% of the countries,
the first estimate of year-on-year growth rates signals no
difference in direction with the 2nd estimates. This ratio
becomes almost 90% while talking about zone aggregates.
10
Reliability of 1st estimate to provide early signals
of turning points in economic activity
Chart to compare earlier (P) and later (M1)
estimates
OECD area
Chart to compare earlier (P) and later (M1)
estimates
Euro area
First published estimate (P)
Estimate published 1 month later (L)
Aug/06
Feb/06
Aug/05
Feb/05
Aug/04
Feb/04
Aug/03
Feb/03
Aug/02
Feb/02
Aug/01
Feb/01
Aug/06
Feb/06
Aug/05
Feb/05
Aug/04
Feb/04
-8
Aug/03
-8
Feb/03
-4
Aug/02
-4
Feb/02
0
Aug/01
0
Feb/01
4
Aug/00
4
Aug/00
8
8
First published estimate (P)
Estimate published 1 month later (L)
11
Reliability of 1st estimate to provide early signals
of turning points in economic activity
Chart to compare earlier (P) and later (M1)
estimates
Mexico
Chart to compare earlier (P) and later (M1)
estimates
United States
16
15
12
10
8
5
4
0
0
-5
-4
Aug/00
Dec/00
Apr/01
Aug/01
Dec/01
Apr/02
Aug/02
Dec/02
Apr/03
Aug/03
Dec/03
Apr/04
Aug/04
Dec/04
Apr/05
Aug/05
Dec/05
Apr/06
Jun/06
Chart to compare earlier (P) and later (M1)
estimates
Japan
First published estimate (P)
Estimate published 1 month later (L)
First published estimate (P)
Estimate published 1 month later (L)
Jun/05
First published estimate (P)
Estimate published 1 month later (L)
Dec/05
Dec/04
Jun/04
Dec/03
Jun/03
Jun/02
Dec/02
Dec/01
Jun/01
Dec/00
Jun/00
Dec/99
Dec/98
10
8
6
4
2
0
-2
-4
-6
Jun/99
Jun/05
Dec/05
Jun/04
Dec/04
Dec/03
Jun/03
Dec/02
Jun/02
Dec/01
Jun/01
Dec/00
Jun/00
Jun/99
Dec/99
Dec/98
-10
12
Conclusion
1st releases of CLI are revised frequently but the size is rather
small for most countries and negligible for aggregates.
No evidence of bias
Improvement in the reliability of the 2nd estimates
1st and 2nd estimates of year-on-year growth rates give reliable
signals of approaching cyclical turning points
It is not enough to have timely components they also need to be
smooth to guarantee small revisions. This further reinforces the
argument that smoothness is probably the most important factor
explaining revisions to the OECD CLI.
13
Investigation on the importance of smoothness
of the component series in the size of revisions
of CLI
Survey components
Financial components
Other components
Smoothness MCD
Smoothness MCD
Smoothness MCD
Response Rate of
Surveys data
Total components
1
Canada
Mexico
United States
8
7
7
Australia
Japan
7
7
Austria
Belgium
Denmark
Finland
France
Germany
Ireland
Italy
Netherlands
Norway
Portugal
Spain
Sweden
Turkey
United Kingdom
6
6
8
9
10
6
8
6
6
7
6
5
9
7
7
2
Total
142
3
2
3
3
4
1
1
5
1
2
1
2
1
1
3
1
1
2
3
2
1
13
4
5
1
1
1
1
2
1
2
1
1
1
1
1
2
2
36
3
1
4
2
65%
62%
1
2
60%
98%
1
1
2
2
1
1
1
1
3
1
1
1
1
2
1
1
1
2
1
1
1
1
1
1
1
1
1
1
6
1
1
2
10
3
17
11
0
0
2
6
11
2
56%
96%
90%
85%
77%
89%
45%
97%
80%
80%
78%
55%
77%
1
47%
1
1
1
1
1
2
1
1
Consumer
5
1
2
2
3
2
2
4
3
3
2
1
1
3
2
3
1
1
2
1
3
3
1
1
2
Manufacturing
10
71%
100%
63%
70%
70%
100%
57%
100%
70%
85%
33%
100%
14
14
Investigation on the importance of smoothness
of the component series in the size of revisions
of CLI
Business or consumer tendency component with MCD of 4 or 5 or 6
Mexico
Finished goods stocks: tendency
Production: tendency
Belgium
Production: tendency
Export order inflow: tendency
Denmark
Consumer confidence
Finland
Production: tendency
Germany
Order inflow: tendency
Ireland
Finished goods stocks : level
Employment: tendency
Order books: level
Consumer confidence
Netherlands
Production: future tendency
Order inflow: tendency
Spain
Order books/demand: tendency
Turkey
Prospects for exports
United Kingdom
Consumer confidence
15
Investigation on the importance of smoothness
of the component series in the size of revisions
of CLI
The correlation coefficient between smoothness and mean
absolute revision of first estimates of the CLIs is rather good
and equals to 0.54. The link is even stronger for second
estimates of the CLIs with an extremely high correlation
coefficient of 0.82.
The general pattern seems to be: the higher the MCD value the
higher the mean absolute revision.
16
Investigation on the importance of smoothness
of the component series in the size of revisions
of CLI
The revision analysis on Irish CLI components shows the
following:
0.70
M2-M1
R2=0.89
Mean Absolute Revision
Share prices
0.60
Spread of Interest
M1-P
Consumer indicator
Employment
Finished goods stocks
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
Order books
Mean Absolute Revision
0.50
0.40
0.30
0.20
0.10
0.00
0
1
2
3
4
5
6
MCD
17
Investigation on the importance of smoothness
of the component series in the size of revisions
of CLI
The revision analysis on German CLI components is:
0.40
R2=0. 94
Mean Absolute Revision
Mean Absolute Revision
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.30
0.20
0.10
M2-M1
Spread of Interest
Export Order Books
Finished goods stocks
M1-P
Orders inflow
Business climate
indicator
0.00
0.00
0
1
2
3
4
5
6
MCD
18
Investigation on the importance of smoothness
of the component series in the size of revisions
of CLI
If we plot together Irish and German results we can get the
following graph:
0.70
Mean Absolute Revision
0.60
R2=0. 85
0.50
0.40
0.30
0.20
0.10
0.00
0
1
2
3
MCD
4
5
6
19
END
20