Effects of model specification, short-run, and long-run inefficiency: an empirical analysis of stochastic
frontier models

https://doi.org/10.17221/341/2017-AGRICECONCitation:ALEM H. (2018): Effects of model specification, short-run, and long-run inefficiency: an empirical analysis of stochastic frontier models. Agric. Econ. – Czech, 64: 508-516.
download PDF

This paper examines the recent advances in stochastic frontier (SF) models and its implications for the performance of Norwegian crop-producing farms. In contrast to the previous studies, we used a cost function in multiple input-output frameworks to estimate both long-run (persistent) and short-run (transient) inefficiency. The empirical analysis is based on unbalanced farm-level panel data for 1991–2013 with 3 885 observations from 455 Norwegian farms specialising in crop production. We estimated seven SF panel data models grouped into four categories regarding the assumptions used to the nature of inefficiency. The estimated cost efficiency scores varied from 53–95%, showing that the results are sensitive to how the inefficiency is modeled and interpreted.

Abdulai A., Tietje H. (2007): Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms. European Review of Agricultural Economics, 34, 393-416  https://doi.org/10.1093/erae/jbm023
Aigner Dennis, Lovell C.A.Knox, Schmidt Peter (1977): Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21-37  https://doi.org/10.1016/0304-4076(77)90052-5
Balana Bedru Babulo, Vinten Andy, Slee Bill (2011): A review on cost-effectiveness analysis of agri-environmental measures related to the EU WFD: Key issues, methods, and applications. Ecological Economics, 70, 1021-1031  https://doi.org/10.1016/j.ecolecon.2010.12.020
Battese George E., Coelli Tim J. (1988): Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data. Journal of Econometrics, 38, 387-399  https://doi.org/10.1016/0304-4076(88)90053-X
Battese G.E., Coelli T.J. (1992): Frontier production functions, technical efficiency, and panel data: with application to paddy farmers in India. In: Thomas R., Gulledge Jr. T.R., Lovell C.A.K. (eds): International applications of productivity and efficiency. Springer Netherlands.
Battese George E., Corra Greg S. (1977): ESTIMATION OF A PRODUCTION FRONTIER MODEL: WITH APPLICATION TO THE PASTORAL ZONE OF EASTERN AUSTRALIA. Australian Journal of Agricultural Economics, 21, 169-179  https://doi.org/10.1111/j.1467-8489.1977.tb00204.x
Chen Yi-Yi, Schmidt Peter, Wang Hung-Jen (2014): Consistent estimation of the fixed effects stochastic frontier model. Journal of Econometrics, 181, 65-76  https://doi.org/10.1016/j.jeconom.2013.05.009
Coelli T.J., Rao D.S.P., O’Donnell C.J., Battese G.E. (2005): An Introduction to Efficiency and Productivity Analysis. Springer Science & Business Media.
Colombi Roberto, Kumbhakar Subal C., Martini Gianmaria, Vittadini Giorgio (2014): Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency. Journal of Productivity Analysis, 42, 123-136  https://doi.org/10.1007/s11123-014-0386-y
Cornwell Christopher, Schmidt Peter, Sickles Robin C. (1990): Production frontiers with cross-sectional and time-series variation in efficiency levels. Journal of Econometrics, 46, 185-200  https://doi.org/10.1016/0304-4076(90)90054-W
Farrell M. J. (1957): The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120, 253-  https://doi.org/10.2307/2343100
Farsi Mehdi, Filippini Massimo (2009): An analysis of cost efficiency in Swiss multi-utilities. Energy Economics, 31, 306-315  https://doi.org/10.1016/j.eneco.2008.11.009
Filippini Massimo, Greene William (2016): Persistent and transient productive inefficiency: a maximum simulated likelihood approach. Journal of Productivity Analysis, 45, 187-196  https://doi.org/10.1007/s11123-015-0446-y
Greene W. (2005): Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis,
23: 7–32.
Jondrow James, Knox Lovell C.A., Materov Ivan S., Schmidt Peter (1982): On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics, 19, 233-238  https://doi.org/10.1016/0304-4076(82)90004-5
Karagiannis Giannis, Tzouvelekas Vangelis (2007): A flexible time-varying specification of the technical inefficiency effects model. Empirical Economics, 33, 531-540  https://doi.org/10.1007/s00181-006-0116-z
Karagiannis G., Tzouvelekas V. (2009): Parametric measurement of time-varying technical inefficiency: Results from competing models. Agricultural Economics Review, 10: 50–79.
Kumbhakar Subal C. (1990): Production frontiers, panel data, and time-varying technical inefficiency. Journal of Econometrics, 46, 201-211  https://doi.org/10.1016/0304-4076(90)90055-X
Kumbhakar S.C., Lovell C.K. (2000): Stochastic Frontier Analysis. Cambridge University Press.
Kumbhakar S.C., Lien G., Flaten O., Tveterås R. (2008): Impacts of Norwegian milk quotas on output growth: a modified distance function approach. Journal of agricultural
Economics, 59: 350-369.
Kumbhakar Subal C., Lien Gudbrand, Hardaker J. Brian (2014): Technical efficiency in competing panel data models: a study of Norwegian grain farming. Journal of Productivity Analysis, 41, 321-337  https://doi.org/10.1007/s11123-012-0303-1
Kumbhakar Subal C., Tsionas Efthymios G. (2011): Some Recent Developments in Efficiency Measurement in Stochastic Frontier Models. Journal of Probability and Statistics, 2011, 1-25  https://doi.org/10.1155/2011/603512
Kumbhakar S.C., Wang H.-J., Horncastle A. (2015): A Practitioner‘s Guide to Stochastic Frontier Analysis Using Stata. Cambridge University Press, Oxford.
Meeusen Wim, van Den Broeck Julien (1977): Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error. International Economic Review, 18, 435-  https://doi.org/10.2307/2525757
NIBIO report (BFJ) (2016): Totalkalkylen for jordbruket. Budget Committee for Agriculture, Aggregate Accounts for Agriculture. Norwegian Institute of Bioeconomy Research, Norway.
Statistics Norway (2013): Agriculture statistics. Available at https://www.ssb.no/jord-skog-jakt-og-fiskeri?de=Landbrukstellinger (accessed May, 2014).
Pitt Mark M, Lee Lung-Fei (1981): The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9, 43-64  https://doi.org/10.1016/0304-3878(81)90004-3
Schmidt Peter, Lin Tsai-Fen (1984): Simple tests of alternative specifications in stochastic frontier models. Journal of Econometrics, 24, 349-361  https://doi.org/10.1016/0304-4076(84)90058-7
Schmidt P., Sickles R.C. (1984): Production frontiers and panel data. Journal of Business & Economic Statistics, 2: 367–374.
download PDF

© 2020 Czech Academy of Agricultural Sciences