Industry Learning Environments and the Heterogeneity of Firm Performance
This paper characterizes inter-industry heterogeneity in rates of learning-by-doing and examines how industry learning rates are connected with firm performance. Using data from the Census Bureau and Compustat, we measure the industry learning rate as the coefficient on cumulative output in a production function. We find that learning rates vary considerably among industries and are higher in industries with greater R&D, advertising, and capital intensity. More importantly, we find that higher rates of learning are associated with wider dispersion of Tobin’s q and profitability among firms in the industry. Together, these findings suggest that learning intensity represents an important characteristic of the industry environment.
|Date of creation:||Dec 2006|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (301) 763-6460
Fax: (301) 763-5935
Web page: http://www.census.gov/ces
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.:
- Irwin, Douglas A & Klenow, Peter J, 1994. "Learning-by-Doing Spillovers in the Semiconductor Industry," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1200-1227, December.
- Zvi Griliches & Jacques Mairesse, 1995.
"Production Functions: The Search for Identification,"
Harvard Institute of Economic Research Working Papers
1719, Harvard - Institute of Economic Research.
- 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.
- Bahk, Byong-Hong & Gort, Michael, 1993. "Decomposing Learning by Doing in New Plants," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 561-83, August.
- Gary P. Pisano & Richard M.J. Bohmer & Amy C. Edmondson, 2001. "Organizational Differences in Rates of Learning: Evidence from the Adoption of Minimally Invasive Cardiac Surgery," Management Science, INFORMS, vol. 47(6), pages 752-768, June.
- S. Baranzoni & P. Bianchi & L. Lambertini, 2000. "Market Structure," Working Papers 368, Dipartimento Scienze Economiche, Universita' di Bologna.
- Gavin Sinclair & Steven Klepper & Wesley Cohen, 2000. "What's Experience Got to Do With It? Sources of Cost Reduction in a Large Specialty Chemicals Producer," Management Science, INFORMS, vol. 46(1), pages 28-45, January.
- Malerba, Franco, 1992. "Learning by Firms and Incremental Technical Change," Economic Journal, Royal Economic Society, vol. 102(413), pages 845-59, July.
- Gruber, Harald, 2000. "The evolution of market structure in semiconductors: the role of product standards," Research Policy, Elsevier, vol. 29(6), pages 725-740, June.
- John F. Muth, 1986. "Search Theory and the Manufacturing Progress Function," Management Science, INFORMS, vol. 32(8), pages 948-962, August.
- S.A. Lippman & R.P. Rumelt, 1982. "Uncertain Imitability: An Analysis of Interfirm Differences in Efficiency under Competition," Bell Journal of Economics, The RAND Corporation, vol. 13(2), pages 418-438, Autumn.
When requesting a correction, please mention this item's handle: RePEc:cen:wpaper:06-29. 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: (Fariha Kamal)
If references are entirely missing, you can add them using this form.