Technical efficiency in beef cattle farming in Uruguay

Insights from census data

Authors

DOI:

https://doi.org/10.31285/AGRO.28.1237

Keywords:

stochastic frontiers, production function

Abstract

Livestock farming is the agricultural activity with the greatest individual land-use, but it faces competition from other sectors for land, and is criticized for its environmental footprint. In this global context, Uruguay emerges as an important case study, boasting a long tradition and significance in the beef export sector. Enhancing livestock productivity is imperative to mitigate environmental impacts, and bolster farm competitiveness and food production. This study delves into the technical efficiency of cattle ranches focused on cow-calf production in Uruguay during the 2011 agricultural year, with nationwide and mandatory data coverage. Using data from the 2011 General Agriculture Census we estimate a translog stochastic production frontier model encompassing key inputs (livestock units, grazing area, and labor), along with control variables such as soil suitability and infrastructure improvements. Our findings underscore the potential to augment Uruguay's beef production by an average of 26.4%, harnessing existing resources and technology while improving ranch management. Moreover, variables like the extent of reliance on livestock farming as the primary source of income of the ranch, the use of outsourced services, foreign cattle ownership ratios, and agronomic and veterinary consultation exert noteworthy significant impacts on TE.

Downloads

Download data is not yet available.

References

Aguirre E. Evolución de la productividad ganadera en Uruguay (2005-2021) [Internet]. 2022 [cited 2023 Dec 07]. Available from: https://www.researchgate.net/publication/368839939_Evolucion_de_la_productividad_ganadera_pastoril_en_Uruguay_2005-2021

Aguirre E. Evolución reciente de la productividad ganadera en Uruguay (2010-17): metodología y primeros resultados. In: Anuario OPYPA 2018. Montevideo: MGAP; 2018. p. 457-70.

Aguirre E. La asociación entre adopción de tecnologías y productividad en la ganadería de carne vacuna en Uruguay. In: Anuario OPYPA 2022. Montevideo: MGAP; 2022. p. 559-70.

Aguirre E. La variabilidad de la producción ganadera pastoril en Uruguay entre 2005 y 2021. In: Anuario OPYPA 2022. Montevideo: MGAP; 2022. p. 549-58.

Aguirre E. Productividad ganadera de los establecimientos de carne bovina del Censo General Agropecuario.In: Anuario OPYPA 2019. Montevideo: MGAP; 2019. p. 497-510.

Aguirre E. Productividad y adopción de tecnologías en la ganadería de carne vacuna en Uruguay [Internet]. 2022 [cited 2023 Dec 07]. Available from: https://bit.ly/3uOfpvw

Aigner D, Lovell CAK, Schmidt P. Formulation and estimation of stochastic frontier production function models. J Econom. 1977;6(1):21-37. DOI: https://doi.org/10.1016/0304-4076(77)90052-5

Athey S, Imbens G. Recursive partitioning for heterogeneous causal effects. Proc Natl Acad Sci U S A. 2016;113(27):7353-60. DOI: https://doi.org/10.1073/pnas.1510489113

Belotti F, Daidone S, Ilardi G, Atella V. Stochastic Frontier Analysis using Stata. Stata J. 2013;13(4):719-58. DOI: https://doi.org/10.1177/1536867X1301300404

Bervejillo JE, Bertamini F. Cambio técnico y crecimiento de la productividad total del sector agropecuario. In: Anuario OPYPA 2014. Montevideo: MGAP; 2014. p. 425-36.

Bervejillo JE. Uruguay’s beef industry: an assessment of WTO disciplines on market access in agriculture [Internet]. Oslo: Norwegian Institute of International Affairs; 2015 [cited 2023 Dec 07]. 69p. Available from: http://hdl.handle.net/11250/283631

Bonferroni C. Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R. Istituto superiore di scienze economiche e commerciali di Firenze. 1936;8:3-62.

Caudill SB, Ford JM. Biases in frontier estimation due to heteroscedasticity. Econ Lett. 1993;41(1):17-20. DOI: https://doi.org/10.1016/0165-1765(93)90104-K

Durán V, Jones C, Alegrette MJ, Boragno L, Arriaga ME. Emisión de un bono soberano indexado a indicadores de sostenibilidad y cambio climático. In: Anuario OPYPA 2022. Montevideo: MGAP; 2022. p. 375-9.

Esteve M, Aparicio J, Rabasa A, Rodriguez-Sala JJ. Efficiency analysis trees: a new methodology for estimating production frontiers through decision trees. Expert Syst Appl. 2020;162:113783. Doi: 10.1016/j.eswa.2020.113783. DOI: https://doi.org/10.1016/j.eswa.2020.113783

Farrell MJ. The measurement of productive efficiency. J R Stat Soc Ser A Stat Soc. 1957;120(3):253-81. DOI: https://doi.org/10.2307/2343100

García Suárez F, Lanfranco B. Eficiencia técnica y aspectos tecnológicos de productores seleccionados: uso sostenible del campo natural. Rev INIA. 2019;(73):135-47.

García-Suárez F, Pérez-Quesada G, Molina Riccetto C. Rangeland cattle production in Uruguay: single-output versus multi-output efficiency measures. Econ Agrar Recur Nat. 2022;22(1):69-88. DOI: https://doi.org/10.7201/earn.2022.01.04

Gatti N, Lema D, Brescia V. A meta-frontier approach to measuring technical efficiency and technology gaps in beef cattle production in Argentina. 2015. 21p. Doi: 10.22004/ag.econ.211647.

Hothorn T, Hornik K, Zeileis A. Unbiased recursive partitioning: a conditional inference framework. J Comput Graph Stat. 2006;15(3):651-74. DOI: https://doi.org/10.1198/106186006X133933

Kumbhakar SC, Ghosh S, McGuckin JT. A generalized production frontier approach for estimating determinants of inefficiency in U.S. dairy farms. J Bus Econ Stat. 1991;9(3):279-86. DOI: https://doi.org/10.1080/07350015.1991.10509853

Kumbhakar SC, Parmeter CF, Zelenyuk V. Stochastic frontier analysis: foundations and advances I. In: Ray S, Chambers R, Kumbhakar S. Handbook of Production Economics. Singapore: Springer; 2020. p. 1-40. DOI: https://doi.org/10.1007/978-981-10-3450-3_9-2

Kumbhakar SC, Parmeter CF, Zelenyuk V. Stochastic Frontier Analysis: Foundations and Advances II. In: Ray S, Chambers R, Kumbhakar S. Handbook of Production Economics. Singapore: Springer; 2020. p. 1-38. DOI: https://doi.org/10.1007/978-981-10-3450-3_11-1

Kumbhakar SC, Wang H, Horncastle AP. A practitioner’s guide to stochastic frontier analysis using Stata. Cambridge: Cambridge University Press; 2015. 374p. DOI: https://doi.org/10.1017/CBO9781139342070

Lanfranco B, Buffa I. Eficiencia técnica de la invernada en Uruguay: un análisis de fronteras de producción. In: Montossi F, editor. Invernada de precisión: pasturas, calidad de carne, genética, gestión empresarial e impacto ambiental. Montevideo: INIA; 2013. p. 109-28.

Martinez Cillero M, Thorne F, Wallace M, Bree J. Technology heterogeneity and policy change in farm-level efficiency analysis: an application to the Irish beef sector. Eur Rev Agric Econ. 2019;46(2):193-214. Doi: 10.1093/erae/jby028. DOI: https://doi.org/10.1093/erae/jby028

Ministerio de Ganadería, Agricultura y Pesca, DIEA (UY). Censo general agropecuario 2011: resultados definitivos. Montevideo: MGAP; 2013. 142p.

Nin A, Ehui S, Benin S. Chapter 47 livestock productivity in developing countries: an assessment. In: Evenson R, Pingali P, editors. Handbook of agricultural economics. Vol. 3, Agricultural Development: Farmers, Farm Production and Farm Markets. North-Holland: Elsevier; 2007. p. 2461-532. Doi: 10.1016/S1574-0072(06)03047-7. DOI: https://doi.org/10.1016/S1574-0072(06)03047-7

Nin A, Freiría H, Muñoz G. Productivity and efficiency in grassland-based livestock production in Latin America: the cases of Uruguay and Paraguay [Internet]. Washington: IDB; 2019 [cited 2023 Dec 07]. 69p. Report No.: IDB-WP-1024. Available from: https://www.econstor.eu/handle/10419/208186

Nwigwe C, Okoruwa V, Adenegan K, Olajide A. Technical efficiency of beef cattle production technologies in Nigeria: a stochastic frontier analysis. Afr J Agric Res. 2016;11:5152-61. DOI: https://doi.org/10.5897/AJAR2016.11744

OECD; FAO. OECD-FAO Agricultural Outlook 2019-2028. Paris: OECD; 2019. 326p. Doi: 10.1787/agr_outlook-2019-en. DOI: https://doi.org/10.1787/agr_outlook-2019-en

Otieno DJ, Hyubbard L, Ruto E. Assessment of technical efficiency and its determinants in beef cattle production in Kenya. J Dev Agric Econ. 2014;6:267-78. DOI: https://doi.org/10.5897/JDAE2013.0525

Peyrou J. La cadena de la carne vacuna. Montevideo: Universidad Católica del Uruguay; 2016. 180p.

Qushim B, Gillespie JM, Bhandari BD, Scaglia G. Technical and scale efficiencies of US grass-fed beef production: whole-farm and enterprise analyses. J Agric Appl Econ. 2018;50(3):408-28. DOI: https://doi.org/10.1017/aae.2018.7

Qushim B, Gillespie JM, Nehring RF. Scale economies and economic performance in southeastern U.S. cow-calf production. 2013. 12p. Doi: 10.22004/ag.econ.143009.

Sickles RC, Zelenyuk V. Measurement of productivity and efficiency: theory. Cambridge: Cambridge University Press; 2019. 626p. DOI: https://doi.org/10.1017/9781139565981

Steinfeld H. Livestock’s long shadow: environmental issues and options. Rome: FAO; 2006. 390p.

Stevenson RE. Likelihood functions for generalized stochastic frontier estimation. J Econom. 1980;13(1):57-66. DOI: https://doi.org/10.1016/0304-4076(80)90042-1

Trestini S. Technical efficiency of italian beef cattle production under a heteroscedastic non-neutral production frontier approach. St. Paul: Center for International Food and Agricultural Policy; 2006. 18p. Doi: 10.22004/ag.econ.6683.

Wang H-J. Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model. J Product Anal. 2002;18:241-53. DOI: https://doi.org/10.1023/A:1020638827640

Downloads

Published

2024-02-21

How to Cite

1.
Aguirre E, García Suárez F, Sicilia G. Technical efficiency in beef cattle farming in Uruguay: Insights from census data. Agrocienc Urug [Internet]. 2024 Feb. 21 [cited 2024 Jul. 13];28:e1237. Available from: https://agrocienciauruguay.uy/index.php/agrociencia/article/view/1237

Issue

Section

Social Sciences, Rural Sociology and Agricultural Economics
QR Code

Altmetric

Article metrics
Abstract views
Galley vies
PDF Views
HTML views
Other views

Most read articles by the same author(s)