Using results from revision analysis to improve compilation/estimation methods
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Anna Ciammola – ISTAT Meeting of the OECD Short-term Economic Statistics Working Party (STESWP) PowerPoint PPT Presentation


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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). Outline. Introduction A case study: the Italian IIP

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Anna Ciammola – ISTAT Meeting of the OECD Short-term Economic Statistics Working Party (STESWP)

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Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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)


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

Outline

  • Introduction

  • A case study: the Italian IIP

    Description of the approach

     Presentation of the results


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

A case study

  • Italian Index of Industrial Production (IIP)

  • Source and timing of revisions

  • Revision analysis

  • Top-down approach

  • Results


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

1. Source and time of revisions


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

2. Revision analysis

IIP - Revisions on raw year-on-year growth rates

Legend

h=1 – after one monthh=12 – after 12 months

MAR –Mean Absolute RevisionRMAR –Relative MAR

MR –Mean Revision SD –Standard Deviation

* a = 5%


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

2. Revision analysis

IIP - Revisions after one month on raw year-on-year growth rates


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

3. Top-down approach

Diagram describing the top-down approach


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

4. Results

MIGS - Revisions after one month on raw Y-o-Y growth rates

LegendCND – Consumer non durables

CDU – Consumer durables CAP –Capital goods

INT –Intermediate GoodsENE –Energy

° Period Jan-04 / Dec-07 *a = 5%


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

4. Results

Revisions after one month on raw Y-o-Y growth rates


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

4. Results

Average weighted response rates


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

4. Results

Revisions after one month on raw Y-o-Y growth rates

Legend

S–Selected subset of INT (19 NACE classes)

NS –Complement of S in INT(S U NS = INT)

* a = 5%


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

4. Results

Revisions after one month on raw Y-o-Y growth rates

Legend

S–Selected subset of INT (19 NACE classes)

SC –Complement of S in IIP(S U SC = IIP)

* a = 5%


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

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


Anna ciammola istat meeting of the oecd short term economic statistics working party steswp

  • Acknowledgements

  • Teresa Gambuti – ISTAT IIP survey

  • Anna Rita Mancini – ISTAT IIP survey

  • Thank you!


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