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Measuring Technological Change Using a Latent Variable Approach

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  • Gao, X M

Abstract

The state of technology is an unobservable variable in transformation functions. The study introduces a latent variable structural equation approach to modelling technological change in US agriculture. The proposed approach combines the parametric production (cost) function and the discrete total factor productivity index approaches together and minimises measurement errors. The technological change for the US agriculture is assumed to be caused by agricultural research, extension, and the farmers' educational backgrounds. The results are compared with the conventional total factor productivity measurement and show that the estimated technology index has a higher annual growth rate than the discrete total-factor-productivity index estimates. Copyright 1994 by Oxford University Press.

Suggested Citation

  • Gao, X M, 1994. "Measuring Technological Change Using a Latent Variable Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 21(1), pages 113-129.
    • Handle: RePEc:oup:erevae:v:21:y:1994:i:1:p:113-29
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    Cited by:

    1. Buonanno, Paolo & Carraro, Carlo & Galeotti, Marzio, 2003. "Endogenous induced technical change and the costs of Kyoto," Resource and Energy Economics, Elsevier, vol. 25(1), pages 11-34, February.
    2. Esposti, Roberto & Pierani, Pierpaolo, 2000. "Modelling technical change in Italian agriculture: a latent variable approach," Agricultural Economics, Blackwell, vol. 22(3), pages 261-270, April.
    3. Carraro, Carlo & Galeotti, Marzio & Gallo, Massimo, 1996. "Environmental taxation and unemployment: Some evidence on the 'double dividend hypothesis' in Europe," Journal of Public Economics, Elsevier, vol. 62(1-2), pages 141-181, October.
    4. Roberto Esposti & Pierpaolo Pierani, 1997. "The Source of Technical Change in Italian Agriculture: A Latent Variable Approach," Wisconsin-Madison Agricultural and Applied Economics Staff Papers 411, Wisconsin-Madison Agricultural and Applied Economics Department.
    5. Roberto Esposti, 2000. "Stochastic Technical Change and Procyclical TFP The Case of Italian Agriculture," Journal of Productivity Analysis, Springer, vol. 14(2), pages 119-141, September.

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