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Using Employee Level Data in a Firm Level Econometric Study

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  • Nathalie Greenan
  • Jacques Mairesse

Abstract

In this paper, we make the general point that econometric studies of the firm can be effectively and substantially enriched by using information collected from employees, even if only a few of them are surveyed per firm. Though variables measured on the basis of the answers of very few employees per firm are subject to very important sampling errors, they can be usefully included in a model specified at the firm level. In the first part of the paper, we show that in estimating parameters of interest in a regression model of the firm, the biases arising from the sampling errors in the employee based variables can be assessed, as long as we have a large enough sub-sample of firms with at least two or with more (randomly chosen) surveyed employees. Dans cet article, nous mettons en avant et argumentons l'idée suivant laquelle les études économétriques sur les entreprises peuvent être efficacement et substantiellement enrichies à l'aide d'informations obtenues aupres de leurs employés, même si seuls quelques-uns par entreprise, deux ou trois par exemple, sont interrogés. Alors même que les variables mesurées à partir des réponses d'un très petit nombre d'employés par entreprise sont sujettes à d'importantes erreurs d'échantillonnage, elles peuvent être utilement incorporées dans un modèle économétrique spécifié au niveau de l'entreprise. Dans une première partie de l'article, nous montrons, pour un modèle de régression linéaire, que les biais d'estimation sur les paramètres d'intérêt qui proviennent de telles erreurs d'échantillonnage, peuvent être corrigés, si on dispose au minimum d'un sous-échantillon (suffisamment grand) d'entreprises où on a pu interroger, au moins, deux employés choisis au hasard. Dans la deuxième partie de l'article, nous considérons, à titre d'exemple, l'estimation de la relation entre le salaire moyen des entreprises (connu directement à partir de leurs données comptables) et la proportion de leurs employés de sexe féminin, telle qu'elle peut être elle-même estimée à partir du sexe de un, deux ou trois salariés choisis au hasard par entreprise. En guise de test, nous comparons les estimations établies sur cette base avec celles obtenues sur la base de la vraie proportion d'employés de sexe féminin (c'est à dire la proportion pour tous les employés), que nous pouvons connaitre aussi, par ailleurs, directement auprès des entreprises. Cette analyse est effectuée sur deux échantillons appariés entreprises-salariés, relatifs à environ 2500 entreprises, en 1987 et 1993, pour l'industrie et les services en France, entreprises où un, deux et trois employés ont été interrogés pour respectivement 75 %, 15 % et 10 % d'entre elles.

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Bibliographic Info

Paper provided by CIRANO in its series CIRANO Working Papers with number 99s-12.

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Date of creation: 01 Mar 1999
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Handle: RePEc:cir:cirwor:99s-12

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Keywords: Linked employer-employee data; errors in variables; pseudo-panel; wage gender differentials; Données appariées entreprises-salariés; modèles à erreurs sur les variables; pseudo-panels; écarts salariaux hommes-femmes.;

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References

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  1. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," Harvard Institute of Economic Research Working Papers 1719, Harvard - Institute of Economic Research.
  2. David Card & Thomas Lemieux, 1993. "Wage Dispersion, Returns to Skill, and Black-White Wage Differentials," NBER Working Papers 4365, National Bureau of Economic Research, Inc.
  3. Nathalie Greenan & Jacques Mairesse, 1996. "Computers and Productivity in France: Some Evidence," NBER Working Papers 5836, National Bureau of Economic Research, Inc.
  4. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
  5. Haegeland, T. & Klette, T.J., 1998. "Do Higher Wages Reflect Higher Productivity? Education, Gender and Experience Premiums in a Matched Plant-Worker Data Set," Memorandum 24/1998, Oslo University, Department of Economics.
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Cited by:
  1. Judith K. Hellerstein & David Neumark, 2002. "Ethnicity, Language, and Workplace Segregation: Evidence from a New Matched Employer-Employee Data Set," NBER Working Papers 9037, National Bureau of Economic Research, Inc.
  2. Christophe Nordman & François-Charles Wolff, 2007. "On-the-job learning and earnings in Benin, Morocco and Senegal," Working Papers DT/2007/09, DIAL (Développement, Institutions et Mondialisation).
  3. Böckerman, Petri & Ilmakunnas, Pekka, 2010. "The job satisfaction-productivity nexus: A study using matched survey and register data," MPRA Paper 23348, University Library of Munich, Germany.
  4. Stepan Jurajda & Heike Harmgart, 2002. "Sex Segregation and Wage Gaps in East and West Germany," CERGE-EI Working Papers wp202, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
  5. Christophe J. NORDMAN & François-Charles WOLFF, 2012. "On-The-Job Learning And Earnings: Comparative Evidence From Morocco And Senegal," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 35, pages 151-176.
  6. Nathalie Greenan & Jacques Mairesse, 2006. "Un équipement de recherche pour observer et analyser les réorganisations d'entreprises," Revue économique, Presses de Sciences-Po, vol. 57(6), pages 1121-1135.
  7. Tilahun Temesgen, 2006. "Decomposing Gender Wage Differentials in Urban Ethiopia: Evidence from Linked Employer-Employee (LEE) Manufacturing Survey Data," Global Economic Review, Taylor and Francis Journals, vol. 35(1), pages 43-66.
  8. Nathalie Greenan & Jacques Mairesse, 2006. "Les changements organisationnels, l'informatisation des entreprises et le travail des salariés. Un exercice de mesure à partir de données couplées entreprises/salariés," Revue économique, Presses de Sciences-Po, vol. 57(6), pages 1137-1175.
  9. Nordman, Christophe J. & Wolff, François-Charles, 2009. "Is there a glass ceiling in Morocco? Evidence from matched worker-firm data," Open Access publications from Université Paris-Dauphine urn:hdl:123456789/4344, Université Paris-Dauphine.
  10. Christophe J. Nordman & François-Charles Wolff, 2009. "Gender differences in pay in African manufacturing firms," Working Papers hal-00421227, HAL.
  11. Devereux, Paul J., 2007. "Improved Errors-in-Variables Estimators for Grouped Data," CEPR Discussion Papers 6167, C.E.P.R. Discussion Papers.

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