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Étendue et conséquences des erreurs de mesure dans les données individuelles d'enquête : une évaluation à partir des données appariées des enquêtes Emploi et Revenus Fiscaux

Author

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  • Arnaud Lefranc
  • Cyrille Hagneré

Abstract

[fre] Cet article examine la qualité des réponses individuelles aux enquêtes Emploi de l’INSEE. Nous rappelons tout d’abord les conséquences possibles de l’existence d’erreurs de mesure pour l’analyse économétrique et présentons les principales statistiques permettant d’évaluer la qualité des données déclarées. Nous procédons ensuite à une évaluation de la qualité des déclarations salariales fournies en réponse à l’enquête Emploi à partir de données appariant une partie des enquêtes Emploi et les déclarations fiscales de revenus d’activité contenues dans les enquêtes Revenus Fiscaux. Nous examinons successivement la qualité des déclarations de niveaux de salaire et de variation interannuelles de salaire et discutons la contribution des comportements d’arrondi aux erreurs de mesure observées. [eng] This paper assesses the quality of responses to the labor-force survey conducted by the French National Institute of Statistics (INSEE). We summarize the possible impact of measurement error on econometric estimates and discuss the main statistical measures of response quality. We then estimate the reliability of earnings figures reported by respondents to the labor-force survey. For this purpose, we use a sub-sample of the survey that can be matched to data from a survey of tax returns. We gauge the extent of measurement error in reported earnings levels and annual changes in earnings, and we assess the contribution of rounding error to total measured error.

Suggested Citation

  • Arnaud Lefranc & Cyrille Hagneré, 2006. "Étendue et conséquences des erreurs de mesure dans les données individuelles d'enquête : une évaluation à partir des données appariées des enquêtes Emploi et Revenus Fiscaux," Économie et Prévision, Programme National Persée, vol. 174(3), pages 131-154.
  • Handle: RePEc:prs:ecoprv:ecop_0249-4744_2006_num_174_3_7957
    DOI: 10.3406/ecop.2006.7957
    Note: DOI:10.3406/ecop.2006.7957
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    1. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
    2. Thierry Magnac & Michael Visser, 1999. "Transition Models With Measurement Errors," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 466-474, August.
    3. Pischke, Jorn-Steffen, 1995. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 305-314, July.
    4. Mellow, Wesley & Sider, Hal, 1983. "Accuracy of Response in Labor Market Surveys: Evidence and Implications," Journal of Labor Economics, University of Chicago Press, vol. 1(4), pages 331-344, October.
    5. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-532, October.
    6. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
    7. Christine Lagarenne & Nadine Legendre, 2000. "Les travailleurs pauvres en France : facteurs individuels et familiaux," Économie et Statistique, Programme National Persée, vol. 335(1), pages 3-25.
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    1. Arenas, Andreu & Malgouyres, Clément, 2018. "Countercyclical school attainment and intergenerational mobility," Labour Economics, Elsevier, vol. 53(C), pages 97-111.

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