1. Using results from revision analysis to improve compilation/estimation methods
An application to the Italian IIP
Anna Ciammola – ISTAT
Meeting of the OECD Short-term Economic
Statistics Working Party (STESWP)

2. A case study: the Italian IIP  Description of the approach
Outline
Introduction
A case study: the Italian IIP
 Description of the approach
 Presentation of the results

3. Introduction For users
Objective  Availability of all the relevant information for using appropriately the estimates of ST indicators at different stages of the revision process
provision of information about
past revisions
schedule
future revisions
(statistical and definitional)
real-time databases
gathering all the vintages
analysis of size,
bias and efficiency
of revisions

4. Introduction For producers Underlying issues
Bias in the revision process
Inefficiency in compilation of preliminary estimates
Targets
Reduction of (the size of) “avoidable” revisions
Detection of the source for bias / inefficiency

5. A case study Italian Index of Industrial Production (IIP)
Source and timing of revisions
Revision analysis
Top-down approach
Results

6. Current Year Y(t) – Reference month
1. Source and time of revisions
Y(t-3)
Y(t-2)
Y(t-1)
Current Year Y(t) – Reference month J F M A S O N D
LR CE LR CE PC
First estimate
Second estimate
Six-month revision
Annual revision LR
Late respondents CE
Correction of errors PC
Productivity coefficients

7. IIP - Revisions on raw year-on-year growth rates
2. Revision analysis
IIP - Revisions on raw year-on-year growth rates
Period: Jan-03 / Dec-07
h=1
h=12
# of revisions 60 48
MAR
0.142
0.246
RMAR
0.053
0.087 MR
0.075
0.083
SD of MR(HAC)
0.021
0.056
T-value
3.564
1.489
Significance of MR
Yes *
No *
Legend
h=1 – after one month h=12 – after 12 months
MAR – Mean Absolute Revision RMAR – Relative MAR
MR – Mean Revision SD – Standard Deviation
* a = 5%

8. IIP - Revisions after one month on raw year-on-year growth rates
2. Revision analysis
IIP - Revisions after one month on raw year-on-year growth rates

9. 3. Top-down approach Tools Revision measures ► Mean Revision
► Mean Absolute Revision
► Mean Squared Revisions (together with its
decomposition)
► …
Weighted response rates
Average contribution of components to the MR of IIP index

10. Diagram describing the top-down approach

11. 3. Top-down approach Computation of the contribution to the MR
Revision of July 2004 and January months also affected by the revision of the productivity coefficients
Simulation exercise aimed at:
1. highlighting the effect of the imputation of late respondents
2. fulfilling the condition necessary to compute the average contribution of each components

12. MIGS - Revisions after one month on raw Y-o-Y growth rates
4. Results
MIGS - Revisions after one month on raw Y-o-Y growth rates
Period: Jan-03 / Dec-07 
CND
CDU
CAP
INT
ENE
Weights %
22.9
6.1
23.8
35.5
11.7
MAR
0.272
0.415
0.378
0.223
0.149
RMAR
0.084
0.081
0.088
0.073
0.040 MR
0.092
0.072
0.042
0.143
-.003
Contribution to MR °
0.019
0.006
0.010
0.047
SD of MR(HAC)
0.103
0.071
0.030
T-value
1.962
0.694
0.589
4.724
-.079
Significance of MR
No *
Yes *
Legend CND – Consumer non durables
CDU – Consumer durables CAP – Capital goods
INT – Intermediate Goods ENE – Energy
° Period Jan-04 / Dec-07 * a = 5%

13. Revisions after one month on raw Y-o-Y growth rates
4. Results
Revisions after one month on raw Y-o-Y growth rates

14. Average weighted response rates
4. Results
Average weighted response rates
Year
Estimate
IIP
CND
CDU
CAP
INT
ENE
2004
First
91.5
93.9
94.3
90.3
88.3
97.4
Second
95.0
95.7
96.1
93.4
93.8
99.6
2005
90.2
90.6
93.5
88.1
87.9
98.7
93.3
93.1
95.4
91.3
92.4
100.0
2006
88.7
89.0
90.4
87.4
86.4
97.3
91.7
91.4
92.5
90.1
99.9
2007
83.7
84.7
82.4
80.8
80.6
97.6
87.6
88.4
86.0
85.6
84.9
99.0

15. Revisions after one month on raw Y-o-Y growth rates
4. Results
Revisions after one month on raw Y-o-Y growth rates
Period: Jan-04 / Dec-07  S NS
Weights %
32.3
67.7
MAR
0.362
0.263
RMAR
0.100
0.082 MR
0.071
Contribution to MR of INT
0.088
0.047
SD of MR(HAC)
0.066
0.050
T-value
3.985
1.407
Significance of MR
Yes *
No *
Legend
S – Selected subset of INT (19 NACE classes)
NS – Complement of S in INT (S U NS = INT)
* a = 5%

16. Revisions after one month on raw Y-o-Y growth rates
4. Results
Revisions after one month on raw Y-o-Y growth rates
Period: Jan-04 / Dec-07  S SC
Weights %
11.5
88.5
MAR
0.362
0.159
RMAR
0.100
0.055 MR
0.263
0.056
Contribution to MR of IIP
0.030
0.049
SD of MR(HAC)
0.066
0.032
T-value
3.985
1.766
Significance of MR
Yes *
No *
Legend
S – Selected subset of INT (19 NACE classes)
SC – Complement of S in IIP (S U SC = IIP)
* a = 5%

17. 4. Results Some evidences
Sectors in the subset S different in terms of either business concentration or production process (on order or not)
Reasons for revisions traced back to:
► partial information previously provided by respondents (especially small firms) and revised the month after
► estimation of the production levels of non respondents at the first release

18. 4. Results Possible countermeasures
Intensive follow up of specific groups of units (especially for large firms that work on orders)
Different methods for the imputation of non responses
► some methodological proposals already implemented in the production process of IIP  taking into account firm size  several estimators

19. Thank you! Acknowledgements Teresa Gambuti – ISTAT IIP survey
Anna Rita Mancini – ISTAT IIP survey
Thank you!