Using Employee Level Data in a Firm Level Econometric Study
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).
|Date of creation:||Mar 1999|
|Publication status:||published as Haltiwanger, John C. (ed.) The creation and analysis of employer-employee matched data, Contributions to Economic Analysis, vol. 241. Amsterdam; New York and Oxford: Elsevier Science, North-Holland, 1999.|
|Contact details of provider:|| Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.|
Web page: http://www.nber.org
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Zvi Griliches & Jacques Mairesse, 1995.
"Production Functions: The Search for Identification,"
NBER Working Papers
5067, National Bureau of Economic Research, Inc.
- Z, Griliches & Jacques Mairesse, 1997. "Production Functions : The Search for Identification," Working Papers 97-30, Centre de Recherche en Economie et Statistique.
- Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," Harvard Institute of Economic Research Working Papers 1719, Harvard - Institute of Economic Research.
- 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.
- 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.
- Nathalie Greenan & Jacques Mairesse, 1996. "Computers and Productivity in France: Some Evidence," NBER Working Papers 5836, National Bureau of Economic Research, Inc.
- Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
- 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.
- 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.
- David Card & Thomas Lemieux, 1993. "Wage Dispersion, Returns to Skill, and Black-White Wage Differentials," Working Papers 691, Princeton University, Department of Economics, Industrial Relations Section..
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:7028. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.