Econometric Estimation of Distance Functions and Associated Measures of Productivity and Efficiency Change
The economically-relevant characteristics of multi-input multi-output production technologies can be represented using distance functions. The econometric approach to estimating these functions typically involves factoring out one of the outputs or inputs and estimating the resulting equation using maximum likelihood methods. A problem with this approach is that the outputs or inputs that are not factored out may be correlated with the composite error term. Fernandez, Koop and Steel (2000, p. 58) have developed a Bayesian solution to this so-called â€˜endogeneityâ€™ problem. O'Donnell (2007) has adapted the approach to the estimation of directional distance functions. This paper shows how the approach can be used to estimate Shephard (1953) distance functions and an associated index of total factor productivity (TFP) change. The TFP index is a new multiplicatively-complete index that satisfies most, if not all, economically-relevant tests and axioms from index number theory. The fact that it is multiplicatively-complete means it can be exhaustively decomposed into a measure of technical change and various measures of efficiency change. The decomposition can be implemented without the use of price data and without making any assumptions concerning either the optimising behaviour of firms or the degree of competition in product markets. The methodology is illustrated using state-level quantity data on U.S. agricultural inputs and outputs over the period 1960-2004. Results are summarised in terms of the characteristics (e.g., means) of estimated probability densities for measures of TFP change, technical change and output-oriented measures of efficiency change.
|Date of creation:||Mar 2011|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +61 7 3365 6570
Fax: +61 7 3365 7299
Web page: http://www.uq.edu.au/economics/
More information through EDIRC
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.:
- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
- Christopher J. O'Donnell, 2012.
"Nonparametric Estimates of the Components of Productivity and Profitability Change in U.S. Agriculture,"
American Journal of Agricultural Economics,
Agricultural and Applied Economics Association, vol. 94(4), pages 873-890.
- C.J. O'Donnell, 2010. "Nonparametric Estimates Of The Components Of Productivity And Profitability Change In U.S. Agriculture," CEPA Working Papers Series WP022010, School of Economics, University of Queensland, Australia.
- 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., 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.
- 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.
- C.J. O'Donnell, 2008. "An aggregate quantity-price framework for measuring and Decomposing productivity and profitability change," CEPA Working Papers Series WP072008, School of Economics, University of Queensland, Australia.
- Fernandez, Carmen & Koop, Gary & Steel, Mark, 2000.
"A Bayesian analysis of multiple-output production frontiers,"
Journal of Econometrics,
Elsevier, vol. 98(1), pages 47-79, September.
- Carmen Fernandez & Gary Koop & M. F. J. Steel, 2004. "A Bayesian analysis of multiple-output production frontiers," ESE Discussion Papers 21, Edinburgh School of Economics, University of Edinburgh.
- O'Donnell, Christopher J., 2007. "Estimating the Characteristics of Polluting Technologies," 2007 Conference (51st), February 13-16, 2007, Queenstown, New Zealand 10413, Australian Agricultural and Resource Economics Society.
- Atkinson, Scott E & Cornwell, Christopher & Honerkamp, Olaf, 2003. "Measuring and Decomposing Productivity Change: Stochastic Distance Function Estimation versus Data Envelopment Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 284-94, April.
- Bjurek, Hans, 1996. " The Malmquist Total Factor Productivity Index," Scandinavian Journal of Economics, Wiley Blackwell, vol. 98(2), pages 303-13, June.
- Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, June.
- Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
- V. Eldon Ball & Charles Hallahan & Richard Nehring, 2004. "Convergence of Productivity: An Analysis of the Catch-up Hypothesis within a Panel of States," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1315-1321.
- Kopp, Raymond J. & Mullahy, John, 1990. "Moment-based estimation and testing of stochastic frontier models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 165-183.
When requesting a correction, please mention this item's handle: RePEc:qld:uqcepa:61. 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: (SOE IT)
If references are entirely missing, you can add them using this form.