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Systematized and Path-independent Measurement of Biased Technical Change

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Author Info
Tsunehiro Otsuki () (Osaka School of International Public Policy, Osaka University)

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Abstract

The sample-specificity and path-dependence of the data envelopment analysis (DEA) based technical change index as a component of Malmquist indexes prevent us from obtaining overall and systematic information on technical change. This paper develops a pathindependent method to estimate technical change using a systematized set of controlled input- output vectors and visualization of the DEA frontiers. The application to the panel datasets of agricultural production in the Brazil Amazon in 1975-1995 indicates non-Hicks-neutral technical change, with crossings of frontiers in both the 1975-1985 and the 1985-1995 periods. The alternative measure of overall technical change shows that moderate technological progress may have occurred on the whole in 1975-1995. The results also show heterogeneous trends across products. The mean of the sample-specific technical change scores are found to be quite different from the overall technical change measure.

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File URL: http://www2.econ.osaka-u.ac.jp/library/global/dp/0911.pdf
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Publisher Info
Paper provided by Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP) in its series Discussion Papers in Economics and Business with number 09-11.

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Length: 14 pages
Date of creation: Apr 2009
Date of revision:
Handle: RePEc:osk:wpaper:0911

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Web page: http://www.econ.osaka-u.ac.jp/
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Related research
Keywords: Data envelopment analysis; Path dependence; Agricultural intensification;

Find related papers by JEL classification:
D24 - Microeconomics - - Production and Organizations - - - Production; Capital and Total Factor Productivity; Capacity
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General

This paper has been announced in the following NEP Reports:

References listed on IDEAS
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  1. Chen, Yao & Iqbal Ali, Agha, 2004. "DEA Malmquist productivity measure: New insights with an application to computer industry," European Journal of Operational Research, Elsevier, vol. 159(1), pages 239-249, November. [Downloadable!] (restricted)
  2. David R. Lee & Christopher B. Barrett & John G. McPeak, 2006. "Policy, technology, and management strategies for achieving sustainable agricultural intensification," Agricultural Economics, International Association of Agricultural Economists, vol. 34(2), pages 123-127, 03. [Downloadable!] (restricted)
  3. Fare, Rolf, et al, 1997. " Biased Technical Change and the Malmquist Productivity Index," Scandinavian Journal of Economics, Blackwell Publishing, vol. 99(1), pages 119-27, March. [Downloadable!] (restricted)
  4. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November. [Downloadable!] (restricted)
  5. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March. [Downloadable!] (restricted)
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This page was last updated on 2009-12-1.


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