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Quality reporting in a short-term business survey based on administrative data. M. Carla Congia Fabio Rapiti ISTAT - Italy. European Conference on Quality in Official Statistics Session on Quality reporting. Rome, 8-11 July 2008. Outline.

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Quality reporting

in a short-term business survey based on administrative data

M. Carla Congia

Fabio Rapiti

ISTAT - Italy

European Conference on Quality in Official Statistics

Session on Quality reporting

Rome, 8-11 July 2008



Quality reporting

  • The Italian Oros Survey
  • Quality issues in using administrative data
  • Peculiarities of data quality assessment
  • Oros quality indicators and reporting
  • Final remarks

Q2008 - Rome, 8-11 July 2008


The Oros Survey

Quality reporting

  • Since 2003 the Oros survey has released quarterly indicators on gross wages and total labour cost per FTE covering all size enterprises in the private non-agricultural sector (C to K sections Nace Rev. 1.1)
  • Based on extensive use of administrative data (National Social Security Institute - INPS) combined with survey data on Large firms with more than 500 employees (Monthly Large Enterprise Survey)
  • Provisional estimates based on the “provisional population” are released with a 70-days delay
  • Final estimates are produced after 5 quarters on the basis of the “whole population” and complete updated information
  • Meets also the requirements of the European regulations:
    • STS - Short-Term Statistics
    • LCI - Labour Cost Index (hourly labour cost index)

Q2008 - Rome, 8-11 July 2008


The administrative source

Quality reporting

  • National Social Security Institute - INPS
  • All Italian firms in the private sector with at least one employee have to pay monthly social security contributions to INPS(roughly 1.3 million employers and 12 millions employees)
  • DM10 form
  • The Monthly Declaration is a highly detailed grid where information on total employment, wage-bills, paid days, overtime hours and social contributions is identified by specific administrative codes (about 5,000 valid codes)
  • Each DM10 lays in several records(8 on average)
  • Data capturing
  • Every firm monthly transmits to INPS the DM10 in electronic format, not later than 30 days after the reference period
  • Then the whole raw declarations are redirected to Istat at 35 days from the end of the reference period (about 10 millions records each month)

Q2008 - Rome, 8-11 July 2008


The administrative data exploiting strategy

Quality reporting

A constrain became an opportunity

At first INPS could not aggregate in the very strict time scheduled the DM10 data in the format required for Oros purposes. So the Istat strategy became

“Catch what you can” “as quick as you can”

from a typical “one collection-for one single output/product”

  • to focus on the “whole data source”- the wage and contribution system
  • Advantages
    • microdata are exactly those sent by firms and this allows a more direct control of the aggregation/translation process
    • a lot of information available for many other different statistical purposes
  • Disadvantages
    • a complex preliminary phase of checks and computation inside the single DM10 to get to the target variables at micro level
    • a lot of data not necessarily useful for short-term objectives

Q2008 - Rome, 8-11 July 2008


Quality issues in using INPS administrative data

Quality reporting

  • The Oros challenge is to produce short-term indicators processing
  • a huge quantity of very detailed microdata
  • in a very short time scheduled
  • coping with the frequent changes in the basic INPS metadata
    • enterprises have to use DM10 form to take advantage of labour cost’s reduction policies and these contribution laws continuously change
  • After preliminary studies INPS data have been considered to be suitable for Oros purposes but still statisticians have
  • no quarterly ex-ante control
  • over the quality of the raw administrative data
  • Only a complex quality-oriented production process can assure
  • ex-post quality
  • coping with unusual problems

Q2008 - Rome, 8-11 July 2008


Quality issues in using INPS administrative data

Quality reporting

Fragmented and insufficient Inps metadata

In-house Metadata database

Highly disaggregated raw data

Preliminary checks and accurate translation into statistical variables

Integration with LE Survey data

Checks to avoid double counting

Continuos legislation changes

Final key checks -


Q2008 - Rome, 8-11 July 2008


Peculiarities of data quality assessment

Quality reporting

  • Relating to quality assessment of administrative data Eurostat recommends to produce: a source-specific report and a product-specific one
  • In the Oros case the non-conventional use of administrative data implies that the two reports overlap…….while new approaches on administrative data quality assessment are empirically explored
  • Oros practice has been developed trying:
  • to find better tools to assess quality
  • to manage the measurement of rather new indicators on:
    • efficient and stable data capturing
    • completeness and consistency of metadata
    • stable traslation/retrieval of target statistical variables
    • correct integration with LE survey data
  • to quarterly produce quality indicators along the whole production process
  • to meet both Istat and Eurostat requests on quality reporting

Q2008 - Rome, 8-11 July 2008


Oros quality reporting: an overview



Survey Documentation and Methodological Handbook

Metadata in SDDS


Oros PR explanatory


SIDI information system for survey documentation

Istat Quality Report

LCI Quality Report

Oros Process Monitoring Report


Quarterly LCI meta information


Quality reporting

Survey Documentation and Methodological Handbook

  • Initial basic quality assessment of the INPS administrative source to evaluate the suitability for the production of quarterly labour market indicators
  • Concepts and definitions of variables and population
  • Translation scheme of administrative information into statistical variables
  • Coverage
  • Reference time
  • Accuracy
  • Stability over time
  • And obviously contening more about…….. the survey methods and the description of the whole production process

Q2008 - Rome, 8-11 July 2008


Quality reporting

Metadata in SDDS format

  • Metadata in Special Dissemination Data Standard format used to deliver information to the IMF
  • Base pagedata, access by the public, integrity and quality
  • Summary methodology statementskey featuresenabling users to assess the suitability of the data for their purposes
  • totally qualitative and compiled once: itis updated following the relevant changes in the methodology
  • compiled for the 3 outputs and different users efforts to systematize
    • Oros ConIstat - short-term indicators’TSdatabase on Istat web-site
    • Oros Eurostat
    • LCI Eurostat
    • STS Eurostat

Q2008 - Rome, 8-11 July 2008


Quality reporting

Process Monitoring Report 1

Quantitative indicators to keep continuosly under control and improve the quality along the whole Oros production process

Some of them are also warning indicators  : signal decisive problems or detect sources of error

Main quality indicators for some key steps of the process:

  • Number of monthly records
  • Number of DM10 forms
  • Time lag between scheduled and actual delivery dates



  • Date of last updating of DM10 metadata on INPS web-site
  • Number of new and expired DM10 codes by type
  • Rate of new DM10 codes to include/exclude
  • Number of official INPS acts to analyse




Q2008 - Rome, 8-11 July 2008


Quality reporting

Process Monitoring Report 2

  • DM10 codes error rate=Number of impossible codes/Total number of codes
  • DM10 codes edit rate=Number of codes changed by editing/Number of impossible codes
  • Rate of duplicate units=Number of duplicate units/Total number of units

Preliminary checks on administrative data

  • Edit rate=Number of unit edited/ Total number of units in scope for the item
  • Total contribution to key estimates from edited values=Total weighted quantity for edited values on total weighted quantity for all final values

Micro editing

Q2008 - Rome, 8-11 July 2008


Quality reporting

Process Monitoring Report 3

  • Number of units manually checked due to record linkage problems (i.e. mergers or split-ups recorded in different times)


with LEsurvey data

  • Number of suspicious aggregates identified automatically by TERROR or through graphical checks
  • Number of outliers treated at micro or macro level
  • Total contribution to the estimates from treated values
  • Length of the homogeneous time series


Q2008 - Rome, 8-11 July 2008


Quality reporting

Istat Quality Report

  • Still experimental Oros has been involved in the pilot test
  • quality indicators within a framework of a qualitative report coherent with Eurostat quality components
  • disseminated within the System on the Quality (SIQual) available on Istat website
  • external-user oriented
  • subset of standard quality indicators appropriately chosen within those available from the Information System for Survey Documentation (SIDI)
    • Response Rate
    • Indicators on the Revision policy (MR, MAR)
    • Timeliness for provisional data release
    • Timeliness for definitive data release
    • Length of the homogeneous time series
  • description of non-sampling error, relevance, accessibility

Q2008 - Rome, 8-11 July 2008


Quality reporting

LCI Quality Report

Required by Eurostat to evaluate the quality of national LCI used to produce the European aggregate index LCI was established with an “harmonization of output” and not “harmonization of input” approach

  • since 2004 the LCI QR has been annually produced
  • standard structure based on Eurostat dimensions of quality with a further aspect “completeness”
  • main standard quality indicators used:
      • Revision policy (MR, MAR)
      • Timeliness for provisional data release
  • description of method for compiling hours worked (LCI denominator)

Quarterly LCI meta information

  • Standard Template mainly qualitative release-specific
    • Changes in the labour market (collective agreements, laws) which has an impact on wages and labour cost
    • Reasons of revisions in NSA, WDA and SA data

Q2008 - Rome, 8-11 July 2008


Final remarks

Quality reporting

The Oros innovative quarterly use of administrative data forces to monitor peculiar aspects of quality not usually taken into consideration in the standard quality assessment approach suggested by Eurostat

Several specific indicators to assess the quality of the process, in particular the metadata updating and the translation/aggregation of raw INPS data, have been implemented but they need to be more systematized

These specific indicators are essential from the producer point of view, but they could also be used to report to the users the quality of some key issues

On the other hand, the Oros survey satisfies the internal (SIDI, SiQual) and external (Eurostat) requests of standard quality reports

A better integration of all the reviewed quality reporting tools is desirable but only partially achievable

Q2008 - Rome, 8-11 July 2008