

Technical efficiency of the Russian agriculture
https://doi.org/10.32609/0042-8736-2016-4-144-155
Abstract
Keywords
JEL: D24, O13, O47, Q10
About the Author
V. KorotchenyaRussian Federation
References
1. Asmild M., Paradi J. C., Aggarwall V., Schaffnit C. (2004). Combining DEA window analysis with the Malmquist index approach in a study of the Canadian banking industry. Journal of Productivity Analysis, Vol. 21, No. 1, pp. 67-89.
2. Battese G. E., Rao D. S. P., O’Donnell C. J. (2004). A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis, Vol. 21, No. 1, pp. 91-103.
3. Charnes A., Clark C. T., Cooper W. W., Golany B. (1985). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces. Annals of Operations Research, Vol. 2, No. 1, pp. 95-112.
4. Charnes A., Cooper W. W., Rhodes E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, Vol. 2, No. 6, pp. 429-444.
5. Coelli T. J., Rao D. S. P. (2005). Total factor productivity growth in agriculture: A Malmquist index analysis of 93 countries, 1980-2000. Agricultural Economics, Vol. 32, No. s1, pp. 115-134.
6. Cooper W. W., Seiford L. M., Tone K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEAsolver software. 2nd ed. New York: Springer.
7. Cooper W. W., Seiford L. M., Zhu J. (eds.) (2011). Handbook on data envelopment analysis. 2nd ed. New York: Springer.
8. Dyson R. G., Allen R., Camanho A. S., Podinovski V. V., Sarrico C. S., Shale E. A. (2001). Pitfalls and protocols in DEA. European Journal of Operational Research, Vol. 132, No. 2, pp. 245-259.
9. Emrouznejad A., Parker B. R., Tavares G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sciences, Vol. 42, No. 3, pp. 151-157.
10. Farrell M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), Vol. 120, No. 3, pp. 253-281.
11. IMF (2015). World economic outlook, April 2015: Uneven growth: Shortand longterm factors. Washington, DC: International Monetary Fund.
12. O’Donnell C. J., Rao D. S. P., Battese G. E. (2008). Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Economics, Vol. 34, No. 2, pp. 231-255.
13. Ravn M. O., Uhlig H. (2002). On adjusting the Hodrick-Prescott filter for the frequency of observations. The Review of Economics and Statistics, Vol. 84, No. 2, pp. 371-376.
14. Ray S. C. (2004). Data envelopment analysis: Theory and techniques for economics and operations research. Cambridge, UK; New York: Cambridge University Press.
15. Tone K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, Vol. 130, No. 3, pp. 498-509.
16. Tone K. (2011). Slacks-based measure of efficiency. In: W. W. Cooper, L. M. Seiford, J. Zhu (eds.). Handbook on data envelopment analysis. 2nd ed. New York: Springer, pp. 195-209.
17. Vlontzos G., Niavis S. (2014). Assessing the evolution of technical efficiency of agriculture in EU countries: Is there a role for the agenda 2000? In: C. Zopounidis, N. Kalogeras, K. Mattas, G. van Dijk, G. Baourakis (eds.). Agricultural cooperative management and policy: New robust, reliable and coherent modelling tools. Cham, Switzerland: Springer, pp. 339-351.
18. Zhu J. (2014). Quantitative models for performance evaluation and benchmarking: Data envelopment analysis with spreadsheets. 3rd ed. Cham, Switzerland: Springer.
Review
For citations:
Korotchenya V. Technical efficiency of the Russian agriculture. Voprosy Ekonomiki. 2016;(4):144-155. (In Russ.) https://doi.org/10.32609/0042-8736-2016-4-144-155