Agric. Econ. - Czech, 2023, 69(11):436-445 | DOI: 10.17221/279/2023-AGRICECON

Profit efficiency and its determinants in the agricultural sector: A Bayesian approachOriginal Paper

Marta Arbelo-Pérez1, Pilar Pérez-Gómez1, Antonio Arbelo1
1 Department of Management, Instituto Universitario de la Empresa, University of La Laguna, La Laguna, Tenerife, Spain

Most empirical studies evaluating efficiency in the agricultural sector estimate cost efficiency, assuming homogeneity across firms. However, achieving the goal of profit maximisation requires both minimising costs and maximising revenue. Unlike cost efficiency, the concept of profit efficiency considers the errors on both the input side and the output side, and thus, it is more appropriate for evaluating the overall performance of firms. This paper estimates profit efficiency and its determinants in the agricultural sector in Spain using a Bayesian stochastic frontier model with random coefficients. This methodology adequately captures the heterogeneity across firms in the industry. The results reveal, firstly, that agricultural firms in Spain are operating with an average profit inefficiency of 35.78% and, secondly, that this inefficiency is affected, albeit unevenly, by the size and age of the farm. Finally, the implications of these results for managers and public policies are discussed.

Keywords: Bayesian estimation; heterogeneity; overall performance; stochastic frontier approach

Received: August 23, 2023; Revised: October 18, 2023; Accepted: October 31, 2023; Prepublished online: November 15, 2023; Published: November 22, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Arbelo-Pérez M, Pérez-Gómez P, Arbelo A. Profit efficiency and its determinants in the agricultural sector: A Bayesian approach. Agric. Econ. - Czech. 2023;69(11):436-445. doi: 10.17221/279/2023-AGRICECON.
Download citation

References

  1. Agrell P.J., Brea-Solís H. (2017): Capturing heterogeneity in electricity distribution operations: A critical review of latent class modelling. Energy Policy, 104: 361-372. Go to original source...
  2. Ali M., Chaudhry M.A. (1990): Inter-regional farm efficiency in Pakistan's Punjab: A frontier production function study. Journal of Agricultural Economics, 41: 62-74. Go to original source...
  3. Álvarez A., del Corral J., Tauer L.W. (2012): Modelling unobserved heterogeneity in New York dairy farms: One-stage versus two-stage models. Agricultural and Resource Economics Review, 41: 275-285. Go to original source...
  4. Arbelo A., Pérez-Gómez P., González-Dávila E., Rosa-González F.M. (2017): Cost and profit efficiencies in the Spanish hotel industry. Journal of Hospitality and Tourism Research, 41: 985-1006. Go to original source...
  5. Arbelo-Pérez M., Arbelo A., Pérez-Gómez P. (2020): Technological heterogeneity and hotel efficiency: A Bayesian approach. Cornell Hospitality Quarterly, 61: 170-182. Go to original source...
  6. Assaf A. (2009): Are US airlines really in crisis? Tourism Management, 30: 916-921. Go to original source...
  7. Assaf A. (2011): Accounting for technological differences in modelling the efficiency of airports: A Bayesian approach. Applied Economics, 43: 2267-2275. Go to original source...
  8. Barney J. (1991): Firm resources and sustained competitive advantage. Journal of Management, 17: 99-120. Go to original source...
  9. 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. Go to original source...
  10. Bauman A., Thilmany D., Jablonski B.B. (2019): Evaluating scale and technical efficiency among farms and ranches with a local market orientation. Renewable Agriculture and Food Systems, 34: 198-206. Go to original source...
  11. Berger A.N., Mester L.J. (1997): Inside the black box: What explains differences in the efficiencies of financial institutions? Journal of Banking and Finance, 21: 895-947. Go to original source...
  12. Bokusheva R., Hockmann H., Kumbhakar S.C. (2012): Dynamics of productivity and technical efficiency in Russian agriculture. European Review of Agricultural Economics, 39: 611-637. Go to original source...
  13. Bos J.W., Koetter M. (2011): Handling losses in translog profit models. Applied Economics, 43: 307-312 Go to original source...
  14. Bravo-Ureta B.E., Evenson R.E. (1994): Efficiency in agricultural production: The case of peasant farmers in eastern Paraguay. Agricultural Economics, 10: 27-37. Go to original source...
  15. Čechura L. (2010): Estimation of technical efficiency in Czech agriculture with respect to firm heterogeneity. Agricultural Economics - Czech, 56: 183-191 Go to original source...
  16. Chivu L., Andrei J.V., Zaharia M., Gogonea R.M. (2020): A regional agricultural efficiency convergence assessment in Romania - Appraising differences and understanding potentials. Land Use Policy, 99: 104838. Go to original source...
  17. Coelli T.J., Battese G.E. (1996): Identification of factors which influence the technical inefficiency of Indian farmers. Australian Journal of Agricultural Economics, 40: 103-128. Go to original source...
  18. Coelli T.J., Rao D.S.P., O'Donnell C.J., Battese G.E. (2005): An Introduction to Efficiency and Productivity Analysis. New York, Springer: 349.
  19. De Freitas C.O., Teixeira E.C., Braga M.J., de Souza Schuntzemberger A.M. (2019): Technical efficiency and farm size: An analysis based on the Brazilian agriculture and livestock census. Italian Review of Agricultural Economics, 74: 33-48.
  20. De Freitas C.O., De Figueiredo Silva F., Braga M.J., De Carvalho Reis Neves M. (2021): Rural extension and technical efficiency in the Brazilian agricultural sector. International Food and Agribusiness Management Review, 24: 215-232. Go to original source...
  21. FAO (2022): The Future of Food and Agriculture: Drivers and Triggers for Transformation. Rome, FAO: 415.
  22. Griffin J.E., Steel M.F. (2007): Bayesian stochastic frontier analysis using WinBUGS. Journal of Productivity Analysis, 27: 163-176. Go to original source...
  23. Hansen M.H., Perry L.T., Reese C.S. (2004): A Bayesian operationalization of the resource-based view. Strategic Management Journal, 25: 1279-1295. Go to original source...
  24. Helfand S.M., Levine E.S. (2004): Farm size and the determinants of productive efficiency in the Brazilian Center-West. Agricultural Economics, 31: 241-249. Go to original source...
  25. Huang H.C. (2004): Estimation of technical inefficiencies with heterogeneous technologies. Journal of Productivity Analysis, 21: 277-296 Go to original source...
  26. Karimov A.A. (2014): Factors affecting efficiency of cotton producers in rural Khorezm, Uzbekistan: Re-examining the role of knowledge indicators in technical efficiency improvement. Agricultural and Food Economics, 2: 7. Go to original source...
  27. Kočišová K. (2015): Application of the DEA on the measurement of efficiency in the EU countries. Agricultural Economics - Czech, 61: 51-62. Go to original source...
  28. Koop G. (1994): Recent progress in applied Bayesian econometrics. Journal of Economic Surveys, 8: 1-34. Go to original source...
  29. Koop G., Steel M.F., Osiewalski J. (1995): Posterior analysis of stochastic frontier models using Gibbs sampling. Computational Statistics, 10: 353-373.
  30. Koop G., Osiewalski J., Steel M.F. (1997): Bayesian efficiency analysis through individual effects: Hospital cost frontiers. Journal of Econometrics, 76: 77-105. Go to original source...
  31. Kumbhakar S.C., Tsionas E.G. (2005): Measuring technical and allocative inefficiency in the translog cost system: A Bayesian approach. Journal of Econometrics, 126: 355-384. Go to original source...
  32. Lakner S., Brenes-Muñoz T., Brümmer B. (2017): Technical efficiency in Chilean agribusiness industry: A metafrontier approach. Agribusiness, 33: 302-323. Go to original source...
  33. Lambarraa F. (2011): Dynamic efficiency analysis of Spanish outdoor and Greenhouse Horticulture sector. In: EAAE 2011 Congress Change and Uncertainty, Zurich, Aug 30- Sept 2, 2011: 1-12
  34. Lambarraa F. (2012): The Spanish horticulture sector: a dynamic efficiency analysis of outdoor and greenhouse farms. In: International Association of Agricultural Economists (IAAE) Triennial Conference, Foz do Iguaçu, Aug 18-24, 2012: 1-16.
  35. Lambarraa F., Stefanou S., Gil J.M. (2016): The analysis of irreversibility, uncertainty and dynamic technical inefficiency on the investment decision in the Spanish olive sector. European Review of Agricultural Economics, 43: 59-77. Go to original source...
  36. Mackey T.B., Barney J.B., Dotson J.P. (2017): Corporate diversification and the value of individual firms: A Bayesian approach. Strategic Management Journal, 38: 322-341. Go to original source...
  37. Marzec J., Pisulewski A. (2021): Measurement of technical efficiency in the case of heterogeneity of technologies used between firms - Based on evidence from Polish crop farms. Agricultural Economics, 67: 152-161. Go to original source...
  38. Maudos J., Pastor J.M., Pérez F., Quesada J. (2002): Cost and profit efficiency in European banks. Journal of International Financial Markets, Institutions and Money, 12: 33-58. Go to original source...
  39. Njuki E., Bravo-Ureta B.E., O'Donnell C.J. (2019): Decomposing agricultural productivity growth using a random-parameters stochastic production frontier. Empirical Economics, 57: 839-860. Go to original source...
  40. O'Donnell C.J., Coelli T.J. (2005): A Bayesian approach to imposing curvature on distance functions. Journal of Econometrics, 126: 493-523. Go to original source...
  41. Rezitis A.N., Tsiboukas K., Tsoukalas S. (2002): Measuring technical efficiency in the Greek agricultural sector. Applied Economics, 34: 1345-1357. Go to original source...
  42. Skevas I. (2019): A hierarchical stochastic frontier model for efficiency measurement under technology heterogeneity. Journal of Quantitative Economics, 17: 513-524. Go to original source...
  43. Skevas T., Grashuis J. (2019): Technical efficiency and spatial spillovers: Evidence from grain marketing cooperatives in the US Midwest. Agribusiness, 36: 111-126. Go to original source...
  44. Spiegelhalter D.J., Best N.G., Carlin B.P., Van Der Linde A. (2002): Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society Series B: Statistical Methodology, 64: 583-639. Go to original source...
  45. Theriault V., Serra R. (2014): Institutional environment and technical efficiency: A stochastic frontier analysis of cotton producers in West Africa. Journal of Agricultural Economics, 65: 383-405. Go to original source...
  46. Tsionas E.G. (2002): Stochastic frontier models with random coefficients. Journal of Applied Econometrics, 17: 127-147. Go to original source...
  47. Van den Broeck J., Koop G., Osiewalski J., Steel M.F. (1994): Stochastic frontier models: A Bayesian perspective. Journal of Econometrics, 61: 273-303 Go to original source...
  48. Zyphur M.J., Oswald F.L. (2015): Bayesian estimation and inference: A user's guide. Journal of Management, 41: 390-420. Go to original source...

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.