Rangeland cattle production in Uruguay: Single-output versus multi-output efficiency measures


  • Federico García-Suárez University of the Republic https://orcid.org/0000-0002-5079-0798
  • Gabriela Pérez-Quesada University of the Republic ; Kansas State University
  • Carlos Molina Riccetto University of the Republic ; Instituto Plan Agropecuario




beef, production, rangeland cattle, stochastic production frontier, stochastic ray frontier


Rangeland cattle production is the largest agricultural sector of Uruguay. Ranches produce up to three products (beef, sheep-meat, and wool) usually combined into an equivalent meat (EM) index. The objective is to compare the empirical results from the estimation of a single output stochastic production frontier (SPF) and a multi-output stochastic ray frontier (SRF) to provide insights on the use
of the EM index to evaluate ranches performance. Results show similar efficiency scores. The average level of TE is 0.769 for the SPF and 0.779 for the SRF. We cannot discard EM index as a simple measure of combined production.


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Author Biographies

Federico García-Suárez, University of the Republic

School of Agronomy

Gabriela Pérez-Quesada, University of the Republic ; Kansas State University

School of Agronomy, University of the Republic ; PhD Candidate at Kansas State University

Carlos Molina Riccetto, University of the Republic ; Instituto Plan Agropecuario

School of Agronomy, University of the Republic ; Instituto Plan Agropecuario


Aguirre, E. (2018). "Evolución reciente de la productividad ganadera en Uruguay (2010-2017). Metodología y primeros resultados". Anuario OPYPA 2018, 457-470. Montevideo, Uruguay: Ministerio de Ganadería Agricultura y Pesca. Retrieved from: https://www.gub.uy/ministerio-ganaderia-agricultura-pesca/sites/ministerio-ganaderia-agricultura-pesca/files/documentos/publicaciones/ProductividadGanadera.pdf

Aigner, D., Knox Lovell, C.A. & Schmidt, P. (1977). "Formulation and estimation of stochastic frontier production function models". Journal of Econometrics, 6(1), 21-37. https://doi.org/10.1016/0304-4076(77)90052-5

Álvarez, J.E. (2013). "Ventajas y limitaciones del uso de indicadores sintéticos de productividad física de la ganadería en la comparación del desempeño productivo de los sistemas agrarios de Nueva Zelanda y Uruguay". Communication presented to IX Jornadas de Investigación en Historia Económica, AUDHE, Montevideo. Retrieved from: https://www.audhe.org.uy/images/stories/upload/Jornadas_nacionales/novenas2013/jorge%20alvarez_audhe_%202013_1.pdf

Battese, G.E. & Coelli, T.J. (1988). "Prediction of firm-level technical efficiencies with generalized frontier production function and panel data". Journal of Economics, 38(3), 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". Journal of Productivity Analysis, 3, 153-169. https://doi.org/10.1007/BF00158774

Battese, G.E. & Coelli, T.J. (1995). "A model for technical inefficiency effects in a stochastic frontier production function for panel data". Empirical Economics, 20, 325-332. https://doi.org/10.1007/BF01205442

Battese, G.E. & Corra, G.S. (1977). "Estimation of a production frontier model: with application to the pastoral zone of eastern Australia". Australian Journal of Agricultural Economics, 21(3), 169-179. https://doi.org/10.1111/j.1467-8489.1977.tb00204.x

Bervejillo, J.E. (2019). Indicadores de la productividad ganadera. Estadísticas de OPYPA: Ministerio de Ganadería, Agricultura y Pesca. Not published. In person communication.

Bervejillo, J.E., Mila, F. & Bertamini, F. (2011). "El crecimiento de la productividad agropecuaria 1980-2010". Anuario OPYPA. Montevideo, Uruguay: Ministerio de Ganadería Agricultura y Pesca. Retrieved from: http://www2.mgap.gub.uy/OpypaPublicaciones/ANUARIOS/Anuario2014/pdf/estudios/E%20-%20Bervejillo%20Bertamini%20-%20Cambio%20tecnico%20y%20crecimiento%20dela%20productividad%20total%20del%20sector%20agrop.pdf

Bravo-Ureta, B.E. & Pinheiro, E. (1993). "Efficiency analysis of developing country agriculture: A review of the frontier function literature". Agricultural and Resource Economics Review, 22(1), 88-101. https://doi.org/10.1017/S1068280500000320

Bravo-Ureta, B.E., Solís, D. & Moreira, V.H. (2007). "Technical efficiency in farming: a meta-regression analysis". Journal of Productivity Analysis, 27, 57-72. https://doi.org/10.1007/s11123-006-0025-3

Coelli, T. & Perelman, S. (1996). Efficiency Measurement, Multiple-Output Technologies and Distance Functions: With Application to European Railways. Working paper CREPP 96/05, University of Liege. Retrieved from: https://www.researchgate.net/publication/24125205_Efficiency_measurement_multipleoutput_technologiess_and_distance_functions_with_application_to_European_Railways

Coelli, T.J. (1995). "Estimators and hypothesis tests for a stochastic frontier function: A montecarlo analysis". Journal of Productivity Analysis, 6, 247-268. https://doi.org/10.1007/BF01076978

Coelli, T.J. & Battese, G.E. (1996, August). "Identification of factors which influence the technical inefficiency of Indian farmers". Australian Journal of Agricultural Economics, 40(2), 103-128. https://doi.org/10.1111/j.1467-8489.1996.tb00558.x

Fousekis, P. (2002). "Distance vs. ray functions: An application to the inshore fishery of Greece". Marine Resource Economics, 17(4), 251-267. https://doi.org/10.1086/mre.17.4.42629369

Gatti, N., Lema, D. & Brescia, V. (2015). "A meta-frontier approach to measuring technical efficiency and technology gaps in beef cattle production in Argentina". Communication presented to International Conference of Agricultural Economists. Milan, Italy.

Green, W. (2005a). "Fixed and random effects in stochastic frontier models". Journal of Productivity Analysis, 23, 7-32. https://doi.org/10.1007/s11123-004-8545-1

Green, W. (2005b). "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model". Journal of Econometrics, 126(2), 269-303. https://doi.org/10.1016/j.jeconom.2004.05.003

Henningsen, A., Belín, M. & Henningsen, G. (2017). New insights into the stochasticray production frontier. Technical Report 01, University of Copenhagen: Department of Food and Resource Economics (IFRO). Retrieved from: https://www.econstor.eu/handle/10419/204405

Henningsen, G., Henningsen, A. & Jensen, U. (2015). "A Monte Carlo study on multiple output stochastic frontiers: A comparison of two approaches". Journal of Productivity Analysis, 44, 309-320. https://doi.org/10.1007/s11123-014-0416-9

INIA. (2018). Indicadores de productividad. Ficha técnica, 43. Retrieved from: http://www.ainfo.inia.uy/digital/bitstream/item/12103/1/Ficha-tecnica-43-Indicadoresde-productividad.pdf

Jondrow, J., Konx Lovell, C.A., Materov, I.S. & Schmidt, P. (1982). "On the estimation of technical inefficiency in the stochastic frontier production function model". Journal of Econometrics, 19(2-3), 233-238. https://doi.org/10.1016/0304-4076(82)90004-5

Kodde, D.A. & Palm, F.C. (1986). "Wald criteria for jointly testing equality and inequality restrictions". Econometrica, 54(5), 1243-1248. Retrieved from: https://www.jstor.org/stable/1912331?seq=1#metadata_info_tab_contents https://doi.org/10.2307/1912331

Kumbhakar, S.C. & Knox Lovell, C.A. (2000). Stochastic frontier analysis. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139174411

Kumbhakar, S.C., Line, G. & Hardker, J.B. (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

Löthgren, M. (1997). "Generalized stochastic frontier production models". Economic Letters, 57(3), 255-259. https://doi.org/10.1016/S0165-1765(97)00246-2

Löthgren, M. (2000). "Specification and estimation of stochastic multiple-output production and technical inefficiency". Applied Economics, 32(12), 1533-1540. https://doi.org/10.1080/000368400418943

Managi, S., Opaluch, J.J., Jin, D. & Grigalunas, T.A. (2006). "Stochastic frontier analysis of total factor productivity in the offshore oil and gas industry". Ecological Economics, 60(1), 204-215. https://doi.org/10.1016/j.ecolecon.2005.11.028

Meeusen, W. & van den Broeck, J. (1977). "Efficiency estimation from Cobb- Douglas production functions with composed error". International Economic Review, 18(2), 435-444. Retrieved from: https://www.jstor.org/stable2525757?seq=1#metadata_info_tab_contents https://doi.org/10.2307/2525757

Niquidet, K. & Nelson, H. (2010). "Sawmill production in the interior of British Columbia: A stochastic ray frontier approach". Journal of Forest Economics, 16(4), 257-267. https://doi.org/10.1016/j.jfe.2010.04.001

Oficialdegui, R. (1984). "Carne equivalente: los riesgos de la simplificación". SUL Boletín Técnico, 13, 53-62. Retrieved from: http://www.ainfo.inia.uy/consulta/busca?b=ad&id=28874&biblioteca=vazio&busca=autoria:%22Oficialdegui,%20R.%22&qFacets=autoria:%22Oficialdegui,%20R.%22&sort=&paginacao=t&paginaAtual=1

Qushim, B., Gillespie, J. & Nehring, R. (2013). "Scale economies and economic performance in southeastern U.S. cow-calf production". Communication presented to Southern Agricultural Economic Association (SAEA) Annual Meeting, Orlando, Florida. https://dx.doi.org/10.22004/ag.econ.143009

Trestini, S. (2006). "Technical efficiency of Italian beef cattle production under a heteroscedastic non-neutral production frontier approach". Communication presented to 10th Joint Conference on Food, Agriculture and the Environment, Duluth, Minnesota. https://dx.doi.org/10.22004/ag.econ.6683

Yin, X., Zhu, X., Zhou, H., Li, Z., Wang, A. & Liao, X. (2017) "Technical efficiency of carp polyculture production in Jiangsu, China: A ray stochastic frontier production approach". Aquaculture Research, 48(4), 1629-1637. https://doi.org/10.1111/are.12998