Fox thanks the National Science Foundation, the NET Institute, the Olin Foundation, and the Stigler Center for generous funding. Smeets gratefully acknowledges financial support from the Danish Council for Independent Research in Social Sciences and the Marie Curie Program of the European Commission (MEIF-2003-501280). Thanks for helpful discussions with Daniel Ackerberg, Allan Collard-Wexler, Ulrich Doraszelski, Tor Eriksson, Jan de Loecker, Amil Petrin, Chad Syverson, Johannes Van Biesebroeck, and Frédéric Warzynski. We appreciate remarks by seminar participants at Aarhus University, CAED, the Econometric Society, IIOC, Jornadas de Economia Industrial, NYU Stern and Texas A & M. Thanks to the professional staff at the Center for Corporate Performance for hospitality and for help integrating the KØB and IDA data sets. Please address correspondence to: Jeremy T. Fox, Department of Economics, University of Michigan, 238 Lorch Hall, 611 Tappan Ave., Ann Arbor, MI 48109-1220. Phone: 734 330-2854; Fax: 734 274-2331. E-mail: firstname.lastname@example.org.
DOES INPUT QUALITY DRIVE MEASURED DIFFERENCES IN FIRM PRODUCTIVITY?*
Article first published online: 23 NOV 2011
© (2011) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association
International Economic Review
Volume 52, Issue 4, pages 961–989, November 2011
How to Cite
Fox, J. T. and Smeets, V. (2011), DOES INPUT QUALITY DRIVE MEASURED DIFFERENCES IN FIRM PRODUCTIVITY?. International Economic Review, 52: 961–989. doi: 10.1111/j.1468-2354.2011.00656.x
Manuscript received September 2008; revised June 2010.
- Issue published online: 23 NOV 2011
- Article first published online: 23 NOV 2011
One explanation for productivity dispersion is that the quality of inputs differs across firms. We add labor market history variables such as experience and firm and industry tenure, as well as general human capital measures such as schooling and sex. Adding these variables decreases the ratio of the 90th to 10th productivity quantiles from 3.27 to 2.68 across eight Danish manufacturing and service industries. We also use the wage bill and worker fixed effects. We find that the wage bill explains as much dispersion as human capital measures.