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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).

Suggested Citation

  • Jacques Mairesse & Nathalie Greenan, 1999. "Using Employee Level Data in a Firm Level Econometric Study," NBER Working Papers 7028, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:7028
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    References listed on IDEAS

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    1. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," NBER Working Papers 5067, National Bureau of Economic Research, Inc.
    2. Nathalie Greenana & Jacques Mairesse, 2000. "Computers And Productivity In France: Some Evidence," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 9(3), pages 275-315.
    3. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    4. 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.
    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, Statistics Norway, Research Department.
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    Citations

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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. Judith K. Hellerstein & David Neumark, 2003. "Ethnicity, Language, and Workplace Segregation: Evidence from a New Matched Employer-Employee Data Set," Annals of Economics and Statistics, GENES, issue 71-72, pages 1-15.
    3. Christophe J. Nordman & François-Charles Wolff, 2009. "Is There a Glass Ceiling in Morocco? Evidence from Matched Worker--Firm Data," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 18(4), pages 592-633, August.
    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 - Economics Institute, Prague.
    5. repec:dau:papers:123456789/4344 is not listed on IDEAS
    6. Erling Barth & Alex Bryson & James C. Davis & Richard Freeman, 2014. "It's Where You Work: Increases in Earnings Dispersion across Establishments and Individuals in the U.S," NBER Working Papers 20447, National Bureau of Economic Research, Inc.
    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. repec:dau:papers:123456789/5948 is not listed on IDEAS
    9. Christophe J. Nordman & François-Charles Wolff, 2009. "Gender differences in pay in African manufacturing firms," Working Papers hal-00421227, HAL.
    10. repec:eee:labchp:v:3:y:1999:i:pb:p:2629-2710 is not listed on IDEAS
    11. Devereux, Paul J., 2007. "Improved Errors-in-Variables Estimators for Grouped Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 278-287, July.
    12. repec:dau:papers:123456789/4333 is not listed on IDEAS
    13. Petri Böckerman & Pekka Ilmakunnas, 2012. "The Job Satisfaction-Productivity Nexus: A Study Using Matched Survey and Register Data," ILR Review, Cornell University, ILR School, vol. 65(2), pages 244-262, April.
    14. 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).
    15. 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.
    16. 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.

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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