National Institute of Statistics - Italy

1. UNITED NATIONS STATISTICAL COMMISSION and ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS COMBINING SURVEY AND ADMINISTRATIVE DATA IN THE ITALIAN EU-SILC EXPERIENCE: POSITIVE AND CRITICAL ASPECTS Work session on statistical and data editing Vienna 21-23 April 2008 Topic (ii): Editing administrative data and combining source National Institute of Statistics - Italy Claudio Ceccarelli, Lucia Coppola, Andrea Cutillo, Davide Di Laurea

2. Eu-Silc and It-Silc • Main aims • collecting a large set of qualitative and quantitative data at individual and household level • providing cross and longitudinal data for measuring income and living condition • Sample design in Italian Eu-Silc (It-Silc) • adopting rotational sampling design composed of 4 rotational sub-samples • each sub-sample to be followed-up during 4 years • Survey techniques in It-Silc • adopting PAPI strategy with interviewer

3. Administrative data in It-Silc To improve data quality, It-Silc uses: • Population register (PR) • to provide correct identification to trace sample units in order to reduce the effect of attrition • in calibration estimators • Tax registers (TR) • to reduce or remove selective non-response and memory effect and/or telescoping • to reduce total non-response effects

4. Tracing rules and population register • Define target population • draw initial sample from register of sampling municipalities • During the fieldwork • PR used to combine sample information about household and individuals • After fieldwork completion PR used • to integrate incomplete information carried-out from each waves of survey • to control the cross sectional and longitudinal consistencies about demographic variables

5. Tax registers and survey data • Main steps of the integration process • Performed at the micro-level (exact matching technique) with survey data • Harmonization: sources have ≠ concepts, definitions and classifications for income Example: cooperatives members do perceive • dep. work income for Italian fiscal rules • self-employment income according to EU-SILC regulations • Complex statistical data editing to make data consistent: • Income components for year t-1 from the two sources • ILO and self-defined Status in employment in time t • Choice of the pertinent income value

6. Administrative data and total non response • Population and tax registers to reduce the effect of non response • Segmentation method by CHAID algorithm • Better accuracy of the estimates does not imply greater variability in respect of stratum correction • Characteristics from population register: demographic size and territorial domain of the municipality; household size and household head nationality • Tax registers: type and amount of income • Important issue in Italy: tax avoidance more frequent in particular sub-groups

7. Remarks • Positive aspects • accuracy • completeness • comparability • macro-level cross and longitudinal coherence • Critical aspects • micro-level longitudinal consistency • timing for accessibility of tax register imply decrease of timeliness

8. Future developments • Longitudinal checks of tax registers to increase micro-level longitudinal consistency • Add new rules in cross-sectional editing to increase longitudinal data quality • Introduce selective/macro editing methods to control large variations in cross-sectional data and particular transitions in different waves