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A comparison of sample and register based survey: the case of labour market data

A comparison of sample and register based survey: the case of labour market data. De Gregorio C., Filipponi D., Martini A., Rocchetti I. Contents Survey(LFS) – ADMIN Strategic issue Previous ESS research Long term innovation process Our purposes Answers and new questions

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A comparison of sample and register based survey: the case of labour market data

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  1. A comparison of sample and register based survey:the case of labour market data De Gregorio C., Filipponi D., Martini A., Rocchetti I.

  2. Contents Survey(LFS) – ADMIN Strategic issue Previous ESS research Long term innovation process Our purposes Answers and new questions Innovation leverage in several fields

  3. Microdata LFS vs. ADMIN Integration: labour input measurement Definition of employment, Regular vs Irregular First: employment status comparison ADMIN wrt: LFS reference week, Employed and Self-employed.

  4. Ourpurposes Managinginconsistencies between LFS and ADMIN MeasuringRegular and Irregular employment Assessing Accuracy of LFS and ADMIN (Assumed error models, MSE’s derivation and computation, No considered benchmark ) Estimating ADMIN Over-coverage (precision) Estimating ADMIN Under-coverage (irregular) Estimating LFS Under-coverage (understatement)

  5. Our model: LFS sample REGULAR “ADMIN employed” status “True” status IRREGULAR “LFS employed” status NOT EMPLOYED

  6. Inconsistencies REGULAR IRREGULAR

  7. Our model • Hypotheses (to simplify) • If LFS employed then employed • If True Regular then ADMIN employed • No LFS Non-response or substitution bias • ADMIN exhaustive and with no error • No problems with record linkage • Key estimates • Probability of being truly employed if “ADMIN employed” • Rate & number of LFS false negatives • Probability of being truly employed if “LFS not employed” • Assume it’s OK!

  8. Compare LFS and ADMIN MSE • Error model for LFS employment status (z) given the true employment status (y) and • Error model for ADMIN employment status (x) and ADMIN under-coverage (irregular employment) ADMIN over-coverage (false employment signal)

  9. MSE by domain LFS >95% of total MSE - given “true” employment, population and sample size ADMIN Linear locus of “low impact” on MSE

  10. LFS MSE: depends on the probability of under-coverage • ADMIN MSE : balance of two opposite errors

  11. To conclude • LFS & ADMIN both have errors • LFS has sampling and under-coverage errors • Apparently ADMIN performs better, as the sources of errors tend to compensate • ADMIN worsens in the domains with higher irregularity rates • ADMIN produces higher errors at micro-level • For analysis purposes, survey and ADMIN data should be integrated further • An efficient usage of exhaustive ADMIN data should count on survey based estimates of actual employment status

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