Dynamic Factor Demand Models and Productivity Analysis
AbstractIn this paper we discuss recent advances in modeling and estimating dynamic factor demand models, and review the use of such models in analyzing the production structure, the determinants of variable and quasi-fixed factors, and productivity growth. The paper also discusses the traditional approach to productivity analysis based on the Divisia index number methodology. Both approaches may be seen a complementary. The conventional index number approach will measure the rate of technical change correctly if certain assumptions about the underlying technology of the firm and output and input markets hold. Furthermore, the conventional index number approach is appealing in that it can be easily implemented. However, if the underlying assumptions do not hold, then the conventional index number approach will, in general, yield biased estimates of technical change. The econometric approach based on general dynamic factor demand models allows for a careful testing of various features of a postulated model. Furthermore it not only provides for estimates of technical change, but can also yield a rich set of critical information on the structure of production, the dynamics of investment in physical and R&D capital, the effects of spillovers, the depreciation rate of capital, the impact of taxes, expectations, etc. The paper also explores in terms of a Monte Carlo study how estimates of important characteristics of the production process can be affected by model misspecification. The results suggest adopting a simple specification for reasons of convenience may result in serious biases.
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Bibliographic InfoPaper provided by University of Maryland, Department of Economics in its series Electronic Working Papers with number 99-005.
Date of creation: May 1999
Date of revision:
Contact details of provider:
Postal: Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742
Web page: http://www.econ.umd.edu/
Postal: Ms. Elizabeth Martinez, Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742
Find related papers by JEL classification:
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- D2 - Microeconomics - - Production and Organizations
- O3 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights
- O4 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
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- Susanto Basu & John Fernald, 2000.
"Why is productivity procyclical? Why do we care?,"
Working Paper Series
WP-00-11, Federal Reserve Bank of Chicago.
- John G. Fernald & Susanto Basu, 1999. "Why is productivity procyclical? Why do we care?," International Finance Discussion Papers 638, Board of Governors of the Federal Reserve System (U.S.).
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- Petri Rouvinen, 2002. "The existence of R&D spillovers: A cost function estimation with random coefficients," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 11(6), pages 525-541.
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