Environmental Management

, Volume 54, Issue 2, pp 288–300 | Cite as

Technical- and Environmental-Efficiency Analysis of Irrigated Cotton-Cropping Systems in Punjab, Pakistan Using Data Envelopment Analysis

  • Asmat Ullah
  • Sylvain R. Perret


Cotton cropping in Pakistan uses substantial quantities of resources and adversely affects the environment with pollutants from the inputs, particularly pesticides. A question remains regarding to what extent the reduction of such environmental impact is possible without compromising the farmers’ income. This paper investigates the environmental, technical, and economic performances of selected irrigated cotton-cropping systems in Punjab to quantify the sustainability of cotton farming and reveal options for improvement. Using mostly primary data, our study quantifies the technical, cost, and environmental efficiencies of different farm sizes. A set of indicators has been computed to reflect these three domains of efficiency using the data envelopment analysis technique. The results indicate that farmers are broadly environmentally inefficient; which primarily results from poor technical inefficiency. Based on an improved input mix, the average potential environmental impact reduction for small, medium, and large farms is 9, 13, and 11 %, respectively, without compromising the economic return. Moreover, the differences in technical, cost, and environmental efficiencies between small and medium and small and large farm sizes were statistically significant. The second-stage regression analysis identifies that the entire farm size significantly affects the efficiencies, whereas exposure to extension and training has positive effects, and the sowing methods significantly affect the technical and environmental efficiencies. Paradoxically, the formal education level is determined to affect the efficiencies negatively. This paper discusses policy interventions that can improve the technical efficiency to ultimately increase the environmental efficiency and reduce the farmers’ operating costs.


Cotton farming Data envelopment analysis Technical efficiency Environmental efficiency Production costs 



This authors wish to express their gratitude to the Higher Education Commission of Pakistan (HEC) and the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD) for their financial support to the doctoral research and field work that generated the paper. The authors also thank the three anonymous reviewers, whose valuable comments helped in making substantial improvements in this paper.


  1. Afonso A, St. Auby M (2006) Cross-country efficiency of secondary education provision: A semi-parametric analysis with non-discretionary inputs. Econ Model 23:476–491CrossRefGoogle Scholar
  2. Azizullah A, Khattak MNK, Richter P, Hader D (2011) Water pollution in Pakistan and its impact on public health-a review. Environ Int 37:479–497CrossRefGoogle Scholar
  3. Banker RD (1984) Estimating most productive scale size using data envelopment analysis. Eur J of Oper Res 17:35–44CrossRefGoogle Scholar
  4. Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078–1092CrossRefGoogle Scholar
  5. Barros CP, Assaf A (2009) Bootstrapped efficiency measures of oil blocks in Angola. Energy Policy 37:4098–4103CrossRefGoogle Scholar
  6. Barros CP, Garcia-del-Barrio P (2011) Productivity drivers and market dynamics in the Spanish first division football league. J Prod Anal 35:5–13CrossRefGoogle Scholar
  7. Callens I, Tyteca D (1999) Towards indicators of sustainable development of firms. A productive efficiency perspective. Ecol Econ 28:41–53CrossRefGoogle Scholar
  8. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J of Oper Res 2:429–444CrossRefGoogle Scholar
  9. Choudhury ATMA, Kennedy IR (2005) Nitrogen fertiliser losses from rice soils and control of environmental pollution problems. Commun Soil Sci Plant Anal 36:1625–1639CrossRefGoogle Scholar
  10. Coelli T, Rao DSP, Battese GE (1998) An introduction to efficiency and productivity analysis. Kluwer Academic Publishers, BostonCrossRefGoogle Scholar
  11. Cooper WW, Seiford LM, Tone K (2007) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-Solver software, 2nd edn. Springer Science + Business Media, LLC, New YorkGoogle Scholar
  12. Dagistan E, Akcaoz H, Demirtas B, Yilmaz Y (2009) Energy usage and benefit-cost analysis of cotton production in Turkey. Afr J of Agric Res 4:599–604Google Scholar
  13. De Koeijer TJ, Wossink GAA, Struik PC, Renkema JA (2002) Measuring agricultural sustainability in terms of efficiency: the case of Dutch sugar beet growers. J of Environ Manag 66:9–17CrossRefGoogle Scholar
  14. Economic Survey of Pakistan (2011–12) Government of Pakistan, Finance Division Economic Adviser’s Wing, Islamabad, pp. 19Google Scholar
  15. Ellis F (1998) Household strategies and rural livelihood diversification. J of Dev Stud 35:1–38CrossRefGoogle Scholar
  16. Fan S, Chan-Kang C (2005) Is small beautiful? Farm size, productivity, and poverty in Asian agriculture. Agric Econ 32(l):135–146CrossRefGoogle Scholar
  17. FAO (1992) CROPWAT model. Food and Agricultural Organisation, RomeGoogle Scholar
  18. Gang C, Zhenhua Q (2013) MaxDEA Pro 6 for data envelopment analysis. available at
  19. Gómez-Limón JA, Picazo-Tadeo AJ, Reig-Martínez E (2012) Eco-efficiency assessment of olive farms in Andalusia. Land Use Policy 29:395–406CrossRefGoogle Scholar
  20. Hussain I, Hussain Z, Sial MH, Akram W, Farhan MF (2011) Water balance, supply and demand and irrigation efficiency of Indus basin. Pak Econ and Soc Rev 29(1):13–38Google Scholar
  21. IPCC (2006) NO2 emission from managed soil and CO2 emission from lime and urea application. In: guidelines for national greenhouse gas inventories, volume 4: Agriculture, Forestry and Other Land Use. GenevaGoogle Scholar
  22. Keating BA, Carberry PS, Bindraban PS, Asseng S, Meinke H, Dixon J (2010) Eco-efficient agriculture: concepts, challenges and opportunities. Crop Sci 50:109–119CrossRefGoogle Scholar
  23. Kumar A, Kandpal TC (2007) Renewable energy technologies for irrigation water pumping in India: a preliminary attempt towards potential estimation. Energy 32:861–870CrossRefGoogle Scholar
  24. Kuosmanen T (2005) Weak disposability in nonparametric production analysis with undesirable outputs. Am Agric Econ Assos 87:1077–1082CrossRefGoogle Scholar
  25. Kuosmanen T, Kortelainen M (2004) Data envelopment analysis in environmental valuation: environmental performance, eco-efficiency and cost-benefit analysis. Discussion Paper, 21. Department of business and economics, University of JoensuuGoogle Scholar
  26. Mohapatra R, Sen B (2013) Technical, allocative and economic efficiency in sugarcane production: a non-parametric approach. Int J of Adv Res 1:366–374Google Scholar
  27. Nguyen TT, Hoang VN, Seo B (2012) Cost and environmental efficiency of rice farms in South Korea. Agric Econ 43:369–378CrossRefGoogle Scholar
  28. Picazo-Tadeo AJ, Reig-Martínez E, Hernández-Sancho F (2005) Directional distance functions and environmental regulations. Resour Energy Econ 27(2):131–142CrossRefGoogle Scholar
  29. Picazo-Tadeo AJ, Gómez-Limón JA, Reig-Martínez E (2011) Assessing farming eco-efficiency: a Data Envelopment Analysis approach. J of Environ Manag 92:1154–1164CrossRefGoogle Scholar
  30. Picazo-Tadeo AJ, Beltrán-Esteve M, Gómez-Limón JA (2012) Assessing eco-efficiency with directional distance functions. Eur J of Oper Res 220:798–809CrossRefGoogle Scholar
  31. Pimentel D (1980) Handbook of energy utilisation in agriculture. CRC Press, Inc., Boca RatonGoogle Scholar
  32. Proto M, Supino S, Malandrino O (2000) Cotton: a flow cycle to exploit. Ind Crops Prod 11:173–178CrossRefGoogle Scholar
  33. Reig-Martínez R, Picazo-Tadeo AJ (2004) Analysing farming systems with data envelopment analysis: citrus farming in Spain. Agric Syst 82:17–30CrossRefGoogle Scholar
  34. Simar L, Wilson PW (2000) A general methodology for bootstrapping in nonparametric frontier models. J of Appl Stat 27:779–802CrossRefGoogle Scholar
  35. Simar L, Wilson PW (2007) Estimation and inference in two-stage, semi-parametric models of production processes. J of Econom 136:31–64CrossRefGoogle Scholar
  36. Tariq MI, Afzal S, Hussain I, Sultana N (2007) Pesticides exposure in Pakistan: a review. Environ Int 33:1107–1122CrossRefGoogle Scholar
  37. Torgersen AM, Førsund FR, Kittelsen SAC (1996) Slack-adjusted efficiency measures and ranking of efficient units. J of Prod Anal 7:379–398CrossRefGoogle Scholar
  38. Wossink A, Denaux ZS (2006) Environmental and cost efficiency of pesticide use in transgenic and conventional cotton production. Agric Syst 90:312–328CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of Environment, Resources and Development, Asian Institute of TechnologyPathumthaniThailand
  2. 2.Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementMontpellierFrance

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