Identifying the elasticity of substitution with biased technical change
AbstractDespite being critical parameters in many economic fields, the received wisdom, in theoretical and empirical literatures, states that joint identification of the elasticity of capital-labor substitution and technical bias is infeasible. This paper challenges that pessimistic interpretation. Putting the new approach of "normalized" production functions at the heart of a Monte Carlo analysis we identify the conditions under which identification is feasible and robust. The key result is that the jointly modeling the production function and first-order conditions is superior to single-equation approaches in terms of robustly capturing production and technical parameters, especially when merged with "normalization". Our results will have fundamental implications for production-function estimation under non-neutral technical change, for understanding the empirical relevance of normalization and the variability underlying past empirical studies. JEL Classification: C22, E23, O30, 051
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Date of creation: Jan 2009
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Other versions of this item:
- Miguel A. Le�n-Ledesma & Peter McAdam & Alpo Willman, 2010. "Identifying the Elasticity of Substitution with Biased Technical Change," American Economic Review, American Economic Association, vol. 100(4), pages 1330-57, September.
- E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Capital; Investment; Capacity
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
- O41 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-08-08 (All new papers)
- NEP-ECM-2009-08-08 (Econometrics)
- NEP-EFF-2009-08-08 (Efficiency & Productivity)
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