Productivity pathways: climate-adjusted production frontiers for the Australian broadacre cropping industry
This study introduces two advances to the aggregate productivity index methodology typically employed by ABARES. First, it accounts for the effects of climate variability on measured productivity by matching spatial climate data to individual farms in the ABARES farm surveys database. Second, a farm-level production frontier estimation technique is employed to facilitate the decomposition of productivity change into several key components, including technical change and technical efficiency change. The study makes use of farm-level data from the ABARES Australian agricultural and grazing industries survey database. An unbalanced panel dataset is constructed containing 13 430 observations (4255 farms) over the period 1977–78 to 2007–08. Spatial climate data, including winter and summer seasonal rainfall and average maximum and minimum temperatures, were obtained via the Australian Water Availability Project. These data were mapped to individual farms using Geographic Information System methods. The study employed stochastic frontier analysis methods to estimate a production frontier with time varying technical efficiency effects of the form proposed by Battese and Coelli (1992). Production frontiers are estimated for each of the three major Grains Research and Development Corporation regions: southern, northern and western. Selected climate variables are shown to display a high degree of explanatory power over farm output. The results confirm that deterioration in average climate conditions has contributed significantly to the decline in estimated productivity over the post-2000 period. Technical change is shown to be the primary driver of productivity growth in the industry in the long run, offset by a gradual decline in technical efficiency. After controlling for climate variability, a gradual decline in the rate of technical change is still observed.
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- Chambers, Christopher P. & Miller, Alan D., . "Inefficiency," Working Papers WP2011/14, University of Haifa, Department of Economics, revised 30 Nov 2011.
- Christopher O’Donnell & Robert Chambers & John Quiggin, 2010.
"Efficiency analysis in the presence of uncertainty,"
Journal of Productivity Analysis,
Springer, vol. 33(1), pages 1-17, February.
- O'Donnell, Chris & Chambers, Robert G & Quiggin, John, 2006. "Efficiency analysis in the presence of uncertainty," Risk and Sustainable Management Group Working Papers 151176, University of Queensland, School of Economics.
- Chris OÕDonnell & Robert G. Chambers & John Quiggin, . "Efficiency analysis in the presence of uncertainty," Risk & Uncertainty Working Papers WP2R06, Risk and Sustainable Management Group, University of Queensland.
- 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.
- O'Donnell, Christopher J., 2010.
"Measuring and decomposing agricultural productivity and profitability change,"
Australian Journal of Agricultural and Resource Economics,
Australian Agricultural and Resource Economics Society, vol. 54(4), December.
- Christopher J. O'Donnell, 2010. "Measuring and decomposing agricultural productivity and profitability change ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 527-560, October.
- O'Donnell, Christopher J., 2009. "Measuring And Decomposing Agricultural Productivity And Profitability Change," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47625, Australian Agricultural and Resource Economics Society.
- Sheng, Yu & Mullen, John D. & Zhao, Shiji, 2010. "Has growth in productivity in Australian broadacre agriculture slowed?," 2010 Conference (54th), February 10-12, 2010, Adelaide, Australia 59266, Australian Agricultural and Resource Economics Society.
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