Transcript European Commission DG ECFIN Directorate General Economic and Financial Affairs A new survey-based indicator to track Industrial Production Olivier Biau – Angela D’Elia Fourth joint EU-OECD.

European Commission
DG ECFIN
Directorate General Economic and Financial Affairs
A new survey-based indicator
to track Industrial Production
Olivier Biau – Angela D’Elia
Fourth joint EU-OECD workshop on
business and consumer opinion surveys
Brussels, 13 October 2009
ECFIN– 13/10/2009
Slide 1
Outline
DG ECFIN
… during the crisis several indicator-based models
performed in a less satisfactory way …
• Are there alternatives to balance statistics?
• Where and how much information in
detailed answers?
• A new synthetic indicator in manufacturing
to track and forecast IP growth
• In-sample and out-of-sample performance
• Further developments
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 2
Introduction
DG ECFIN
• Survey data
– Barometer of the economic situation
– Gauge the economic stance
– … but they are qualitative
• Balance statistics
(difference between % of respondents giving positive and negative replies)
– Easy to implement, read and follow (no revisions)
– Highly correlated with hard aggregates
– … but based on restrictive assumptions
(Pesaran&Weale, 2006)
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 3
Introduction & Rationale
DG ECFIN
INDUSTRY
INDUSTRY
euro
area
INDUSTRY---euro
euroarea
area
25
65
8080
15
45
5
5
7070
6060
25
-5
5050
-15
-15
5
4040
-25
-25
-15
-35
-35
3030
-35
-45
-45
1010
-55
-55
-55
00
Jan-09
Jan-09
Jan-09
Jan-07
Jan-07
Jan-07
Jan-05
Jan-05
Jan-05
Jan-03
Jan-03
Jan-03
Jan-01
Jan-01
Jan-01
Jan-99
Jan-99
Jan-99
Jan-97
Jan-97
Jan-97
Jan-95
Jan-95
Jan-95
Jan-93
Jan-93
Jan-93
Jan-91
Jan-91
Jan-91
Jan-89
Jan-89
Jan-89
Jan-87
Jan-87
Jan-87
Jan-85
Jan-85
Jan-85
2020
Balance (nsa) Q1
Balance (nsa) Q1
Stable (nsa) Q1 -rhs
Balance (nsa) Q1
Negative (nsa) Q1 -rhs
Stable (nsa) Q1 -rhs
Evidence of moving from « do not change » to
« negative » answers
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 4
DG ECFIN
Where and how much information in detailed
answers?
• Principal components analysis (Hild, 2003; Etter et al, 2004)
– to find the « best » linear combination of 3 answer
modalities
• Regression analysis
– to identify the combination with highest explanatory
power wrt hard reference series
(y-o-y Industrial Production growth in EA)
 Dataset:
Industry Business&Consumer Survey data (Jan91 –Jun09)
Industrial Production Index (Jan91 – Apr09)
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 5
Industry survey –monthly questions
DG ECFIN
•
Q1 How has your production developed over the past 3 months? It has...
+ increased
= remained unchanged
− decreased
•
Q2 Do you consider your current overall order books to be...?
+ more than sufficient (above normal)
= sufficient (normal for the season)
− not sufficient (below normal)
•
Q3 Do you consider your current export order books to be...?
+ more than sufficient (above normal)
= sufficient (normal for the season)
− not sufficient (below normal)
•
Q4 Do you consider your current stock of finished products to be...?
+ too large (above normal)
= adequate (normal for the season)
− too small (below normal)
•
Q5 How do you expect your production to develop over the next 3 months? It
will...
+ increase
= remain unchanged
− decrease
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 6
Principal Components analysis
DG ECFIN
Explained
PC1 Loadings
variance
Q1
%+
(P)
0.56
%=
(S)
0.55
%–
(M)
-0.62
87%
Q2
0.56
0.57
-0.60
92%
Q3
0.54
0.57
-0.62
87%
Q4
-0.70
0.64
0.30
68%
Q5
0.57
0.54
-0.62
85%
PC1 = 0.55*P + 0.55*S – 0.6*M = 0.55*(P + S) – 0.62*M = 0.55* (100 – M) – 0.62*M
PC1 = a + b*M
All the relevant information is contained in the % of
respondents who give a negative answer
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 7
Regression analysis
DG ECFIN
IPt = c1 *Pt + c2 *St + c3 *Mt + ut
• M modality (negative answers) is always the most
significant for explaining IP, across all questions
• Model built on Q1 (past production) and Q5
(expected production) has the best fit (highest R2)
• For Q1, Q2 and Q5, the null hypothesis c1=c2=c
cannot be rejected
IPt = c* (Pt +St)+ c3 *Mt + ut = c* (100 - Mt)+ c3 *Mt + ut = α + β* Mt + ut
 Focus
on % of negative answers to Q1, Q2 and Q5
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 8
A new indicator to track Industrial Production
DG ECFIN
Out of the negative modality of answer to Q1, Q2
and Q5, it is possible to build 7 different indicators
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
0
-1.0
-5
-2.0
-10
-3.0
y-o-y growth
0.0
-15
M15
IP (RHS)
ECFIN – 13/10/2009
Slide 9
2009M01
2008M01
2007M01
2006M01
2005M01
2004M01
2003M01
2002M01
2001M01
2000M01
1999M01
1998M01
-25
1997M01
-5.0
1996M01
-20
1995M01
-4.0
1994M01
2
7
3
6
1
5
4
5
1993M01
-0.946
-0.817
-0.937
-0.900
-0.954
-0.923
-0.935
1.0
1992M01
M1
M2
M5
M12
M15
M25
M125
10
1991M01
Indicator Correlation Ranking
with IP
2.0
DG ECFIN
A comparison with Industrial Confidence
Indicator and Business Climate Indicator
• Correlation with Industrial Production Index
Indicator
Tn =
Correlation with IP
Tn
M15
-0.954
ICI
0.878
-5.33
BCI
0.871
-5.66
arctanh(corr )  arctanh(corr ) a
1
2 ~ N(0,1)
2
n 3
Test of equality of
correlation coefficients
 M15 correlation with IP is significantly higher than
those of ICI and BCI
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 10
In-sample analysis
M15 or ICI or BCI
DG ECFIN
The model:
Indicator
R²
IPt = a0+ a1 IPt-1 + a2 Xt + a3 Xt-1 + ut
S.E. of
regression
Durbin
Watson
h
modified
AIC
DW
M15
0.93
1.16
2.06
-1.39
3.15
ICI
0.89
1.43
2.54
-6.82
3.23
BCI
0.89
1.42
2.62
-7.67
3.21
10
5
0
-5
-10
-15
-20
-25
92
94
96
98
00
Obs erved IP
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
02
04
06
08
Fitted IP
ECFIN – 13/10/2009
Slide 11
Out-of-sample analysis (M15 vs ICI and BCI)
DG ECFIN
• One month horizon forecast
• Sample periods: Jan05 – Apr09 and Jan07 – Apr09
Jan07 – Apr09
Jan05 – Apr09
Indicator
MAE
MSE
M15
1.19
2.17
ICI
1.59
4.49
BCI
1.66
4.62
Indicator
MAE
MSE
M15
1.39
2.90
-2.57
ICI
2.04
6.90
-2.50
-2.97
BCI
2.07
6.77
-2.66
Harvey et
al test
Harvey et
al test
Harvey et al test – in small sample- the null hypothesis of no difference between the MSEs of 2 models
 M15 is significantly better in forecasting IP
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 12
Out-of-sample analysis (M15 vs ICI and BCI)
DG ECFIN
10
5
0
-5
-10
-15
-20
IP
M15_FORECAST
ICI_FORECAST
BCI_FORECAST
-25
2007
2008
• M15 was the first to signal a negative yoy growth for
IP (summer 2008)
• M15 correctly tracked the IP during the crisis, and
predicted the improvement in May09
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 13
Conclusions and further developments
DG ECFIN
• Better performance of M15 in tracking and
forecasting Industrial Production growth, especially
during last crisis
• … but M15 is not necessarily a confidence indicator
 To build a complementary confidence indicator as a
common factor over the negative answers to all the 5
questions of industry survey
 To apply same approach to other surveys of BCS
Olivier Biau – Angela D’Elia
European Commission, Economic and Financial Affairs
ECFIN – 13/10/2009
Slide 14