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Using Employee Level Data in a Firm Level Econometric Study

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  • Jacques Mairesse
  • Nathalie Greenan

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. As an illustration in the second part of the paper, we consider the estimation of the relationship between the firm average wage (directly obtained from the firm accounts) and estimates of the proportion of female workers based on the gender of one, two or three surveyed employees per firm. As a test, we compare the estimates that we find in this way with those using the employees), which we could also directly obtain at the firm level from a firm survey. The analysis is performed on two linked employer-employee samples of about 2500 firms in the French manufacturing and services industries in 1987 and 1993, with one, two or three surveyed employees per firm (for respectively 75%, 15% and 10% of the firms).

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 7028.

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Date of creation: Mar 1999
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Handle: RePEc:nbr:nberwo:7028

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References

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  1. Card, David & Lemieux, Thomas, 1996. "Wage dispersion, returns to skill, and black-white wage differentials," Journal of Econometrics, Elsevier, vol. 74(2), pages 319-361, October.
  2. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
  3. Greenman, N. & Mairesse, J., 1996. "Computers and Productivity in France: Some Evidence," Monash Econometrics and Business Statistics Working Papers 15/96, Monash University, Department of Econometrics and Business Statistics.
  4. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," NBER Working Papers 5067, National Bureau of Economic Research, Inc.
  5. Torbjørn Hægeland & Tor Jakob Klette, 1997. "Do Higher Wages Reflect Higher Productivity? Education, Gender and Experience Premiums in a Matched Plant-Worker Data Set," Discussion Papers 208, Research Department of Statistics Norway.
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Cited by:
  1. 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.
  2. Christophe Nordman & François-Charles Wolff, 2007. "Is there a glass ceiling in Morocco? Evidence from matched worker-firm data," Working Papers DT/2007/04, DIAL (Développement, Institutions et Mondialisation).
  3. Judith HELLERSTEIN & David NEUMARK, 2003. "Ethnicity, Language, and Workplace Segregation: Evidence from a New Matched Employer-Employee Data Set," Annales d'Economie et de Statistique, ENSAE, issue 71-72, pages 19-78.
  4. Petri B?ckerman & Pekka Ilmakunnas, 2012. "The Job Satisfaction-Productivity Nexus: A Study Using Matched Survey and Register Data," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 65(2), pages 244-262, April.
  5. 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.
  6. Christophe J. Nordman & François-Charles Wolff, 2009. "Gender differences in pay in African manufacturing firms," Working Papers hal-00421227, HAL.
  7. 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.
  8. Devereux, Paul J., 2007. "Improved Errors-in-Variables Estimators for Grouped Data," CEPR Discussion Papers 6167, C.E.P.R. Discussion Papers.
  9. Tilahun Temesgen, 2006. "Decomposing Gender Wage Differentials in Urban Ethiopia: Evidence from Linked Employer-Employee (LEE) Manufacturing Survey Data," Global Economic Review, Taylor & Francis Journals, vol. 35(1), pages 43-66.
  10. 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.
  11. 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).

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