Journal of Productivity Analysis

, Volume 45, Issue 1, pp 23–33 | Cite as

Multi-directional program efficiency: the case of Lithuanian family farms

  • Mette Asmild
  • Tomas BaležentisEmail author
  • Jens Leth Hougaard


The present paper analyses both managerial and program efficiencies of Lithuanian family farms, in the tradition of Charnes et al. (Manag Sci 27(6):668–697, 1981) but with the important difference that multi-directional efficiency analysis rather than the traditional data envelopment analysis approach is used to estimate efficiency. This enables a consideration of input-specific efficiencies. The study shows clear differences between the efficiency scores on the different inputs as well as between the farm types of crop, livestock and mixed farms respectively. We furthermore find that crop farms have the highest program efficiency, but the lowest managerial efficiency and that the mixed farms have the lowest program efficiency (yet not the highest managerial efficiency).


Multi-directional efficiency analysis (MEA) Managerial efficiency Program efficiency Data envelopment analysis (DEA) Family farms Lithuania 

JEL Classification

C430 C440 C610 Q100 Q120 


  1. Asmild M, Matthews K (2012) Multi-directional efficiency analysis of efficiency patterns in Chinese Banks 1997–2008. Eur J Oper Res 219:434–441CrossRefGoogle Scholar
  2. Asmild M, Hougaard JL, Kronborg D, Kvist HK (2003) Measuring inefficiency via potential improvements. J Prod Anal 19(1):59–76CrossRefGoogle Scholar
  3. Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30(9):1078–1092CrossRefGoogle Scholar
  4. Beltrán-Esteve M, Reig-Martínez E (2014) Comparing conventional and organic citrus grower efficiency in Spain. Agric Syst 129:115–123CrossRefGoogle Scholar
  5. Bogetoft P, Hougaard JL (1999) Efficiency evaluations based on potential (non-proportional) improvements. J Prod Anal 12:233–247CrossRefGoogle Scholar
  6. Bojnec S, Latruffe L (2008) Measures of farm business efficiency. Ind Manag Data Syst 108(2):258–270CrossRefGoogle Scholar
  7. Bojnec S, Latruffe L (2011) Farm size and efficiency during transition: insights from Slovenian Farms. Trans Bus Econ 10(3):104–116Google Scholar
  8. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444CrossRefGoogle Scholar
  9. Charnes A, Cooper WW, Rhodes E (1981) Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through. Manag Sci 27(6):668–697CrossRefGoogle Scholar
  10. Dios-Palomares R, Martínez-Paz JM (2012) Technical, quality and environmental efficiency of the olive oil industry. Food Policy 36(4):526–534CrossRefGoogle Scholar
  11. FADN (2010) Farm accounting data network: an A to Z of methodology.
  12. Farrell MJ (1957) The measurement of technical efficiency. J Roy Stat Soc Series A Gen 120(3):253–281CrossRefGoogle Scholar
  13. Gómez-Limón JA, Picazo-Tadeo AJ, Reig-Martínez E (2012) Eco-efficiency assessment of olive farms in Andalusia. Land Use Policy 29(2):395–406CrossRefGoogle Scholar
  14. Gorton M, Davidova S (2004) Farm productivity and efficiency in the CEE applicant countries: a synthesis of results. Agric Econ 30:1–16CrossRefGoogle Scholar
  15. Holvad T, Hougaard JL, Kronborg D, Kvist HK (2004) Measuring Inefficiency in the Norwegian Bus industry using multi-directional efficiency analysis. Transportation 31(3):349–369CrossRefGoogle Scholar
  16. Hougaard JL, Kronborg D, Overgård C (2004) Improvement potential in Danish elderly care. Health Care Manag Sci 7(3):225–235CrossRefGoogle Scholar
  17. Latruffe L, Balcombe K, Davidova S, Zawalinska K (2005) Technical and scale efficiency of crop and livestock farms in Poland: Does specialization matter? Agric Econ 32(3):281–296CrossRefGoogle Scholar
  18. Li Q (1996) Nonparametric testing of closeness between two unknown distribution functions. Econom Rev 15:261–274CrossRefGoogle Scholar
  19. Li Q (1999) Nonparametric testing of the similarity of two unknown density functions: local power and bootstrap analysis. J Nonparametr Stat 11:189–213CrossRefGoogle Scholar
  20. Lithuanian Institute of Agrarian Economics (2012) Ūkių veiklos rezultatai (ŪADT tyrimo duomenys) 2011 [FADN survey results 2011]. Lietuvos agrarinės ekonomikos institutas, Vilnius. ISSN 2029-1221Google Scholar
  21. Liu JS, Lu LYY, Lu WM, Lin BJY (2013) Data envelopment analysis 1978–2010: a citation-based literature survey. Omega 41:3–15CrossRefGoogle Scholar
  22. Mancebón MJ, Calero J, Choi Á, Ximénez-de-Embún DP (2012) The efficiency of public and publicly subsidized high schools in Spain: evidence from PISA-2006. J Oper Res Soc 63:1516–1533CrossRefGoogle Scholar
  23. Minviel JJ, Latruffe L (2014) Meta-regression analysis of the impact of agricultural subsidies on farm technical efficiency. Paper prepared for presentation at the EAAE 2014 Congress ‘Agri-Food and Rural Innovations for Healthier Societies’, August 26 to 29, 2014, Ljubljana, SloveniaGoogle Scholar
  24. Simar L, Zelenyuk V (2006) On testing equality of distributions of technical efficiency scores. Econom Rev 25(4):497–522CrossRefGoogle Scholar
  25. Statistics Lithuania, 2012. Agriculture in Lithuania 2011. VilniusGoogle Scholar
  26. Wollni M, Brümmer B (2012) Productive efficiency of specialty and conventional coffee farmers in Costa Rica: accounting for technological heterogeneity and self-selection. Food Policy 37(1):67–76CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Mette Asmild
    • 1
  • Tomas Baležentis
    • 2
    Email author
  • Jens Leth Hougaard
    • 1
  1. 1.Department of Food and Resource EconomicsUniversity of CopenhagenFrederiksberg CDenmark
  2. 2.Lithuanian Institute of Agrarian EconomicsVilniusLithuania

Personalised recommendations