Analysis of Productive Performance of Crop and Animal Production Systems: An Integrated Analytical Framework
This article presents a two-stage analytical framework that integrates ecological crop (animal) growth and economic frontier production models to analyse the productive efficiency of crop (animal) production systems. The ecological crop (animal) growth model estimates "potential" output levels given the genetic characteristics of crops (animals) and the physical conditions of locations where the crops (animals) are grown (reared). The economic frontier production model estimates "best practice" production levels, taking into account economic, institutional and social factors that cause farm and spatial heterogeneity. In the first stage, both ecological crop growth and economic frontier production models are estimated to calculate three measures of productive efficiency: (1) technical efficiency, as the ratio of actual to "best practice" output levels; (2) agronomic efficiency, as the ratio of actual to "potential" output levels; and (3) agro-economic efficiency, as the ratio of "best practice" to "potential" output levels. Also in the first stage, the economic frontier production model identifies factors that determine technical efficiency. In the second stage, agro-economic efficiency is analysed econometrically in relation to economic, institutional and social factors that cause farm and spatial heterogeneity. The proposed framework has several important advantages in comparison with existing proposals. Firstly, it allows the systematic incorporation of all physical, economic, institutional and social factors that cause farm and spatial heterogeneity in analysing the productive performance of crop and animal production systems. Secondly, the location-specific physical factors are not modelled symmetrically as other economic inputs of production. Thirdly, climate change and technological advancements in crop and animal sciences can be modelled in a "forward-looking" manner. Fourthly, knowledge in agronomy and data from experimental studies can be utilised for socio-economic policy analysis. The proposed framework can be easily applied in empirical studies due to the current availability of ecological crop (animal) growth models, farm or secondary data, and econometric software packages. The article highlights several directions of empirical studies that researchers may pursue in the future.
|Date of creation:||31 Aug 2011|
|Contact details of provider:|| Postal: GPO Box 2434, BRISBANE QLD 4001|
Web page: http://www.bus.qut.edu.au/faculty/economics/
More information through EDIRC
References listed on IDEAS
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.:
- Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
- Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
- Koenker,Roger, 2005.
Cambridge University Press, number 9780521845731, December.
- Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007.
"Technical efficiency in farming: a meta-regression analysis,"
Journal of Productivity Analysis,
Springer, vol. 27(1), pages 57-72, February.
- Bravo-Ureta, Boris & Solís, Daniel & Moreira, Victor & Maripani, José & Thiam, Abdourahmane & Rivas, Teodoro, 2005. "Technical Efficiency in Farming: A Meta-regression analysis," Efficiency Series Papers 2005/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
- Jin, Songqing & Huang, Jikun & Hu, Ruifa & Rozelle, Scott, 2001.
"The Creation And Spread Of Technology And Total Factor Productivity In China'S Agriculture,"
11981, University of California, Davis, Department of Agricultural and Resource Economics.
- Songqing Jin & Jikun Huang & Ruifa Hu & Scott Rozelle, 2002. "The Creation and Spread of Technology and Total Factor Productivity in China's Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(4), pages 916-930.
- Bouman, B.A.M. & van Laar, H.H., 2006. "Description and evaluation of the rice growth model ORYZA2000 under nitrogen-limited conditions," Agricultural Systems, Elsevier, vol. 87(3), pages 249-273, March.
- Hoang, Viet-Ngu & Nguyen, Trung Thanh, 2013. "Analysis of environmental efficiency variations: A nutrient balance approach," Ecological Economics, Elsevier, vol. 86(C), pages 37-46.
- Hoang, Viet-Ngu & Coelli, Tim J., 2009.
"Measurement Of Agricultural Total Factor Productivity Growth Incorporating Environmental Factors: A Nutrients Balance Approach,"
2009 Conference (53rd), February 11-13, 2009, Cairns, Australia
47636, Australian Agricultural and Resource Economics Society.
- Hoang, Viet-Ngu & Coelli, Tim, 2011. "Measurement of agricultural total factor productivity growth incorporating environmental factors: A nutrients balance approach," Journal of Environmental Economics and Management, Elsevier, vol. 62(3), pages 462-474.
- Viet-Ngu Hoang & Tim Coelli, 2009. "Measurement Of Agricultural Total Factor Productivity Growth Incorporating Environmental Factors- A Nutrients Balance Approach," CEPA Working Papers Series WP032009, School of Economics, University of Queensland, Australia.
- Omar Arias & Kevin F. Hallock & Walter Sosa Escudero, 1999.
"Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression using Twins Data,"
Department of Economics, Working Papers
016, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata.
- Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, vol. 26(1), pages 7-40.
- Johannes Sauer, 2006. "Economic Theory and Econometric Practice: Parametric Efficiency Analysis," Empirical Economics, Springer, vol. 31(4), pages 1061-1087, November.
- Cacho, O. J. & Finlayson, J. D. & Bywater, A. C., 1995. "A simulation model of grazing sheep: II. Whole farm model," Agricultural Systems, Elsevier, vol. 48(1), pages 27-50.
- Sherlund, Shane M. & Barrett, Christopher B. & Adesina, Akinwumi A., 2002. "Smallholder technical efficiency controlling for environmental production conditions," Journal of Development Economics, Elsevier, vol. 69(1), pages 85-101, October.
- Yannis Bilias & Roger Koenker, 2001. "Quantile regression for duration data: A reappraisal of the Pennsylvania Reemployment Bonus Experiments," Empirical Economics, Springer, vol. 26(1), pages 199-220.
- Bin Zhang & Colin A. Carter, 1997. "Reforms, the Weather, and Productivity Growth in China's Grain Sector," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1266-1277.
- Kaneda, Hiromitzu, 1982. "Specification of production functions for analyzing technical change and factor inputs in agricultural development," Journal of Development Economics, Elsevier, vol. 11(1), pages 97-108, August.
- de Koeijer, T. J. & Wossink, G. A. A. & van Ittersum, M. K. & Struik, P. C. & Renkema, J. A., 1999. "A conceptual model for analysing input-output coefficients in arable farming systems: from diagnosis towards design," Agricultural Systems, Elsevier, vol. 61(1), pages 33-44, July.
- Hengsdijk, H. & van Ittersum, M. K., 2002. "A goal-oriented approach to identify and engineer land use systems," Agricultural Systems, Elsevier, vol. 71(3), pages 231-247, March.
- Martin van Ittersum & Ada Wossink, 2006. "Integrating Agronomic Principles into Production Function Specification: A Dichotomy of Growth Inputs and Facilitating Inputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 203-214.
When requesting a correction, please mention this item's handle: RePEc:qut:dpaper:268. 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: (Angela Fletcher)
If references are entirely missing, you can add them using this form.