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The quality of the population census in France

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  1. The quality of the population census in France Olivier Lefebvre, Insee

  2. Plan of the presentation • Short brief about french census • The management of the census quality • General principles • Sampling frames • Data collection • Data processing • Dissemination

  3. The method of the new census • Two major principles • Data collection in rotation (annual surveys) • Resorting to sample surveys for large communes (more than 10000 inhabitants) • The sampling base:the located buildings register (répertoire d’immeubles localisés - RIL) • Special case of persons not living in ordinary dwellings (institutions, homeless people, nomads)

  4. The proceedings of the census survey • The same modus operandi as in 1999 for the habitants : deposit-withdrawal of the questionnaires by the enumerator • A « non surveyed dwelling form » (called FLNE in french) in case of impossibility of contacting people or refusal

  5. The questionnaires • The dwelling data sheet • The individual bulletin

  6. Year N-1 Year N Juin Jui. Août Sep. Oct. Nov. Déc. Jan Fév. Mar Avril Mai Juin Jui. Août Sep. Nov. Déc. Jan The schedule of a campaign Oct. RIL Expertise Sampling Setting-up of organisation Preparation Training Communication Collection Reception Controls Data processing Dissemination

  7. Evaluation Campaign Improvements The management of the census quality • A continuous evaluation approach • Enabled through the annual feature of the operation • Based on systematic overall results

  8. The national commission for the evaluation of the census • Under the rule of the CNIS (National Council for Statistical Information) • Presided over by a senator • It associates communes, the data users (researchers, administrations, municipalities), the Insee • It enables an exchange on data collection, control protocols, useful in improving the processes • It must give an opinion on the texts governing the organisation of the census

  9. The management of quality, process by process • Sampling frames • Data collection • Data processing • Dissemination

  10. Sampling frames • The « quality » survey of the RIL • An annual survey to assess • The surpluses and the deficits • The surplus-deficit balance • The proportion of communes for which the quality is deemed mediocre • The sample : 190 000 addresses and 520 000 dwellings • The results • 0.9 % of dwellings in deficit, 1.4 % in surplus • one commune out of eight beyond 2.5% of deficit • A level of quality higher than that of usual geographical registers • A regular improvement process

  11. Sampling frames (2) • The action plans • To improve the quality of the RIL with targetted operations • Decided and implemented by the Regional Directorates in relation with the communes • As a function of the strong points and the weak points detected locally • Training of communes, fieldwork… • Allowing for an operational management of quality because targetted on specific problems and based on the closeness between the regional teams and the communes • The future efforts: reduce the surpluses and arrive at level surplus-deficit balance

  12. Data collection • The control procedures during the data collection • The follow-up and control upon the initiative of the communes • The controls at the Insee after the data collection (reception-control, in office control, controls in the field)

  13. The control procedure during data collection • A precise data collection protocol • Checked by the municipal officer • And by the supervisor

  14. Follow-up and control system upon the initiative of the communes • Upstream from the data collection • Validation of the sample • Control-validation of the field to be observed carried-out by the enumerator • Follow-up of the data collection • Follow-up of the progress of work of the enumerator • Follow-up of key indicators : FLNE, vacant dwellings, quality of the log book of the tour-visits

  15. The controls at the Insee after data collection • Successive « sorting » • The step of reception-registering of the questionnaires • Establishment of indicators • Communes with insufficient scores subject to in-depth control (approx. 10% of the communes) • Desk controls • Verification with the help of the housing Tax files • On the exhaustiveness of the dwellings, the FLNE, the structure of main/not main residence • In field controls

  16. The in-field controls • They are done by Insee agents • They relate to the communes whose quality is presumed insufficient • Most often, they confirm the data collection • The errors detected are corrected • N.B. these controls are not representative, therefore their results cannot be extrapolated

  17. The in-field controls 23 500 controls of dwellings Of which: 2 800 in the communes of more than 10 000 inhabitants  30 000 in-field controls 6 400 controls of addresses Of which: 3 600 in the communes of less than 10 000 inhabitants 500 controls by telephone

  18. Zoom on controls of dwellings 85 % : verification of a FLNE 9 % : verification of a main residence 6 % : verification of secondary residence, vacant dwelling or occasional dwelling

  19. Results of controls of FLNE • In 85% of the cases, the household enumerator finds the information • Most often, the FLNE does concern a main residence and the number of persons is correctly estimated • In 10 % of the cases, FLNEs have been wrongly provided (for non-main residences)

  20. Data processing • Data input • Quality criteria specifically defined in the specifications • securing of transports and data • maximum rate of error by category of variables • Control of discrepancies by « flashage » • … and evaluated by an independent control process (sample that has been input twice and arbitration)

  21. Data processing (2) • Encoding • Quality control work station for : • Assessing the quality of the automatic coding and manual correction • Estimating a « threshold » of percentage of bulletins « non codable » • The contributions of this approach : • adding to the expert systemfiles • the improvement of training and protocols (precisions added in codification rules) • A finer management of quality, without going in for « excess quality »

  22. Data processing (3) • Data editing and imputation • Anayse the share of non responses or incoherent responses • Imputation of missing data or data presumed non-coherent (hot-deck procedure) • They are fine-tuned year after year, in view of the quality of the variables produced

  23. Dissemination • A step prepared with the users • Define with them the products and services : two groups of the CNIS • Assess their satisfaction : groups of the CNIS and satisfaction surveys • A systematic validation of the data before dissemination • At the national level and in each regional directorate

  24. Any questions ?