Estimation of the impact of CAP subsidies as environmental variables on Romanian farms

Titolo Rivista Economia agro-alimentare
Autori/Curatori Nicola Galluzzo
Anno di pubblicazione 2022 Fascicolo 2021/3
Lingua Inglese Numero pagine 0 P. 1-24 Dimensione file 0 KB
DOI 10.3280/ecag2021oa12772
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Romanian agriculture is characterised by the presence of small farm enterprises, with an average value of land capital of less than 5 hectares in more than 95% of cases. The aim of this research was to assess the level of technical efficiency in farming through a non-parametric approach such as the Data Envelopment Analysis (DEA), and also to estimate the impact that financial subsidies allocated under the first and second pillars of the Common Agricultural Policy (CAP) have had on the technical efficiency. In the application of this analysis, these two inputs have been considered as environmental variables in order to evaluate their effect in fostering the technical efficiency using a two-stage dea method. The results have revealed the pivotal impact of financial subsidies disbursed through the first and second pillars of cap in enhancing technical efficiency in the Romanian farms included in the fadn dataset. In contrast, the subsidies disbursed under only the second pillar of the CAP in the framework of rural development have not been found to have had any discernible effect on the technical efficiency of Romanian farms. The novelty of this quantitative approach in the estimation of technical efficiency lies in its focus on the role of environmental variables as drivers in affecting the technical efficiency of farms, defining, in addition, how important they are in addressing efficiency and in shifting enhancing the function of technical efficiency on farms as well.Some conclusions were drawn: it is important to increase the endowment of subsidies for rural development and as well as decoupled payments in order to raise the level of technical efficiency in Romanian farms. At the same time, the findings suggest the need for Romanian farmers to reduce the level of certain inputs, such as labour, on the one hand, while on the other, increasing the dimension size of farms in terms of land capital and encouraging greater investment in labor-saving technology, even if significant imbalances remain between different Romanian regions, both in terms of the level of technical efficiency achieved and also in terms of output yield, and in the endowment of land capital and other assets.

Keywords: Data Envelopment Analysis; Technical efficiency; Separability test; Rural Development Programme; FADN

  1. Baráth, L., Fertő, I. & Bojnec, Š. (2018). Are farms in less favored areas less efficient? Agricultural Economics, 49(1), 3-12, DOI: 10.1111/agec.12391
  2. Farrell M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281, DOI: 10.2307/2343100
  3. Aigner, D., Lovell, C.K. & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of econometrics, 6(1), 21-37, DOI: 10.1016/0304-4076(77)90052-5
  4. Ayouba, K., Boussemart, J.P. & Vigeant, S. (2017). The impact of single farm payments on technical inefficiency of French crop farms. Review of Agricultural, Food and Environmental Studies, 98(1), 1-23, DOI: 10.1007/s41130-017-0049-2
  5. Bădin, L., Daraio, C. & Simar, L. (2010). Optimal bandwidth selection for conditional efficiency measures: A data-driven approach. European journal of operational research, 201(2), 633-640, DOI: 10.1016/j.ejor.2009.03.038
  6. Bădin, L., Daraio, C. & Simar, L. (2012). How to measure the impact of environmental factors in a nonparametric production model. European Journal of Operational Research, 223(3), 818-833, DOI: 10.1016/j.ejor.2012.06.028
  7. Banker, R.D., Charnes, A. & Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092, DOI: 10.1287/mnsc.30.9.1078
  8. Baráth, L., Fertő, I. & Bojnec, Š. (2020). The effect of investment, LFA and agrienvironmental subsidies on the components of total factor productivity: the case of Slovenian farms. Journal of Agricultural Economics, 71(3), 853-876, DOI: 10.1111/1477-9552.12374
  9. Bartolini, F. & Viaggi, D. (2013). The common agricultural policy and the determinants of changes in EU farm size. Land use policy, 31, 126-135, DOI: 10.1016/j.landusepol.2011.10.007
  10. 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(1-2), 153-169, DOI: 10.1007/978-94-017-1923-0_10
  11. 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(2), 325-332, DOI: 10.1007/BF01205442
  12. Beluhova-Uzunova, R., Atanasov, D. & Hristov, K. (2017). Analysis of direct payments distribution in Bulgarian agriculture. Trakia Journal of Sciences, 15(1), 282-287.
  13. Bielik, P. & Rajčániová, M. (2004). Competitiveness analysis of agricultural enterprises in Slovakia. Agricultural Economics, 50(12), 556-560, DOI: 10.17221/5248-AGRICECON
  14. Bravo-Ureta, B.E. & Pinheiro, A.E. (1993). Efficiency analysis of developing country agriculture: a review of the frontier function literature. Agricultural and resource economics Review, 22(1), 88-101, DOI: 10.1017/S1068280500000320
  15. Charnes, A., Cooper, W.W. & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444, DOI: 10.1016/0377-2217(79)90229-7
  16. Ciaian, P. & Swinnen, J.F. (2006). Land market imperfections and agricultural policy impacts in the new EU member states: a partial equilibrium analysis. American Journal of Agricultural Economics, 88(4), 799-815, DOI: 10.1111/j.1467-8276.2006.00899.x
  17. Ciaian, P., Kancs, D.A. & Swinnen, J. (2014). The impact of the 2013 reform of the common agricultural policy on land capitalization in the European Union. Applied Economic Perspectives and Policy, 36(4), 643-673, DOI: 10.1093/aepp/ppu016
  18. Coelli, T.J., Rao, D.S.P., O’Donnell, C.J. & Battese, G.E. (2005). An introduction to efficiency and productivity analysis. Berlin, DE: Springer Verlag, DOI: 10.1007/978-1-4615-5493-6
  19. Cooper, W.W., Seiford, L.M., Tone, K. & Zhu, J. (2007). Some models and measures for evaluating performances with DEA: past accomplishments and future prospects. Journal of Productivity Analysis, 28(3), 151-163, DOI: 10.1007/s11123-007-0056-4
  20. Crescenzi, R. & Rodríguez-Pose, A. (2011). Reconciling top-down and bottom-up development policies. Environment and planning A, 43(4), 773-780, DOI: 10.1068/a43492
  21. Czyzewski, A., Majchrzak, A. & Smedzik-Ambrozy, K. (2017). Land Productivity and Its Prices in the Countries of EU-15 and EU-12. Economic Science for Rural Development, 46, 228-228.
  22. Daraio, C. & Simar, L. (2005). Introducing environmental variables in nonparametric frontier models: a probabilistic approach. Journal of productivity analysis, 24(1), 93-121, DOI: 10.1007/s11123-005-3042-8
  23. Daraio, C., Simar, L. & Wilson, P.W. (2015). Testing the “separability” condition in two-stage nonparametric models of production (No. 2015/21). LEM working paper series.
  24. Daraio, C., Simar, L. & Wilson, P.W. (2018). Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non-parametric, two-stage models of production. The Econometrics Journal, 21(2), 170-191, DOI: 10.1111/ectj.12103
  25. Forleo, M.B., Giaccio, V., Mastronardi, L. & Romagnoli, L. (2021). Analysing the efficiency of diversified farms: Evidences from Italian FADN data. Journal of Rural Studies, 82, 262-270, DOI: 10.1016/j.jrurstud.2021.01.009
  26. Galluzzo, N. (2013). Farm dimension and efficiency in Italian agriculture: a quantitative approach. American Journal of Rural development, 1(2), 26-32.
  27. Galluzzo, N. (2016). An analysis of the efficiency in a sample of small Italian farms part of the fadn dataset. Agricultural Economics, 62(2), 62-70, DOI: 10.17221/37/2015-AGRICECON
  28. Galluzzo, N. (2018). A quantitative assessment of the rurality and an efficiency analysis of emigration in Romania. Applied Studies in Agribusiness and Commerce, 12(3-4), 39-46, DOI: 10.19041/APSTRA CT/2018/3-4/5
  29. Galluzzo, N. (2019a). A long-term analysis of the Common Agricultural Policy financial subsidies towards Italian farms. Ukranian Journal on Veterinary and Agricultural Science, 2(1), 12-17, DOI: 10.32718/ujvas2-1.03
  30. Galluzzo, N. (2019b). An analysis of technical efficiency in Icelandic dairy and sheep farms. Studies in Agricultural Economics, 121(3), 144-150, DOI: 10.7896/j.1916
  31. Galluzzo, N. (2020a). A technical efficiency analysis of financial subsidies allocated by the CAP in Romanian farms using Stochastic Frontier Analysis. European Countryside, 12(4), 494-505, DOI: 10.2478/euco-2020-0026
  32. Galluzzo, N. (2020b). Analysis of resilience in Romanian rural farm areas by a quantitative approach. Bulgarian Journal of Agricultural Science, 26(1), 16-22.
  33. Galluzzo, N. (2020c). Effects of farms specialization, environmental subsidies and agri-districts on technical efficiency in Italian farms. Ikonomika I upravlenie na selskoto stopanstvo, 65(4), 13-22.
  34. Galluzzo, N. (2021). A quantitative analysis on Romanian rural areas, agritourism and the impacts of European Union’s financial subsidies. Journal of Rural Studies, 82, 458-467, DOI: 10.1016/j.jrurstud.2021.01.025
  35. Garrone, M., Emmers, D., Lee, H., Olper, A. & Swinnen, J. (2019). Subsidies and agricultural productivity in the EU. Agricultural Economics, 50(6), 803-817, DOI: 10.1111/agec.12526
  36. Gorton, M. & Davidova, S. (2004). Farm productivity and efficiency in the CEE applicant countries: a synthesis of results. Agricultural economics, 30(1), 1-16, DOI: 10.1111/j.1574-0862.2004.tb00172.x
  37. Gutiérrez, E. & Lozano, S. (2020). Cross-country comparison of the efficiency of the European forest sector and second stage DEA approach. Annals of Operations Research, 1-26, DOI: 10.1007/s10479-020-03756-9
  38. Gutiérrez, E., Aguilera, E., Lozano, S. & Guzmán, G.I. (2017). A two-stage DEA approach for quantifying and analysing the inefficiency of conventional and organic rain-fed cereals in Spain. Journal of cleaner production, 149, 335-348, DOI: 10.1016/j.jclepro.2017.02.104
  39. Horvat, A.M., Radovanov, B., Popescu, G.H. & Panaitescu, C. (2019). A twostage DEA model to evaluate agricultural efficiency in case of Serbian districts. Економика пољопривреде, 66(4), 965-973, DOI: 10.5937/ekoPolj1904965M
  40. Kourtesi, S., Fousekis, P. & Polymeros, A. (2012). Conditional efficiency estimation with environmental variables: evidence from Greek cereal farms. Scientific Bulletin-Economic Sciences, 11(1), 43-52.
  41. Kumbhakar, S.C. & Lien, G. (2010). Impact of Subsidies on Farm Productivity and Efficiency. In Ball, V., Fanfani, R. & Gutierrez, L. (Eds.). The Economic Impact of Public Support to Agriculture. Studies in Productivity and Efficiency, 7. New York, NY: Springer, DOI: 10.1007/978-1-4419-6385-7_6
  42. Kumbhakar, S.C., Wang, H.J. & Horncastle, A.P. (2015). A practitioner’s guide to stochastic frontier analysis using Stata. Cambridge, UK: Cambridge University Press, DOI: 10.1017/CBO9781139342070
  43. Latruffe, L. & Desjeux, Y. (2016). Common Agricultural Policy support, technical efficiency and productivity change in French agriculture. Review of Agricultural, Food and Environmental Studies, 97(1), 15-28, DOI: 10.1007/s41130-016-0007-4
  44. Latruffe, L., Bravo-Ureta, B.E., Carpentier, A., Desjeux, Y. & Moreira, V.H. (2017). Subsidies and technical efficiency in agriculture: Evidence from European dairy farms. American Journal of Agricultural Economics, 99(3), 783-799, DOI: 10.1093/ajae/aaw077
  45. Latruffe, L., Diazabakana, A., Bockstaller, C., Desjeux, Y., Finn, J., Kelly, E., Ryan, M. & Uthes, S. (2016). Measurement of sustainability in agriculture: a review of indicators. Studies in Agricultural Economics, 118(3), 123-130, DOI: 10.7896/j.1624
  46. Laurinavičius, E. & Rimkuvienė, D. (2017). The comparative efficiency analysis of EU members agriculture sectors. Rural Sustainability Research, 37(332), 10-19, DOI: 10.1515/plua-2017-0002
  47. Lovell, C.K. (1993). Production frontiers and productive efficiency. The measurement of productive efficiency: Techniques and applications, 3, 67.
  48. Manevska-Tasevska, G., Rabinowicz, E. & Surry, Y. (2016). Pure and compensated efficiency of Swedish dairy farms. Agricultural and Food Science, 25(2), 111-123, DOI: 10.23986/afsci.53182
  49. Mennig, P. & Sauer, J. (2019). The impact of agri-environment schemes on farm productivity: a DID-matching approach. European Review of Agricultural Economics, 1-49, DOI: 10.1093/erae/jbz006
  50. Minviel, J.J. & Latruffe, L. (2017). Effect of public subsidies on farm technical efficiency: a meta-analysis of empirical results. Applied Economics, 49(2), 213-226, DOI: 10.1080/00036846.2016.1194963
  51. Nowak, A., Kijek, T. & Domańska, K. (2015). Technical efficiency and its determinants in the European Union. Agricultural Economics, 61(6), 275-283, DOI: 10.17221/200/2014-AGRICECON
  52. Osman, I.H. & Anouze, A.L. (2014). A cognitive analytics management framework (CAM-Part 3): Critical skills shortage, higher education trends, education value chain framework, government strategy. In Osman, I.H., Anouze, A.L. & Emrouznejad, A. (Eds.). Handbook of research on strategic performance management and measurement using data envelopment analysis (pp. 190-234). Hershey, US: igi Global.
  53. Petrick, M. & Zier, P. (2011). Regional employment impacts of Common Agricultural Policy measures in Eastern Germany: a difference‐in‐differences approach. Agricultural Economics, 42(2), 183-193, DOI: 10.1111/j.1574-0862.2010.00509.x
  54. Rizov, M., Pokrivcak, J. & Ciaian, P. (2013). CAP subsidies and productivity of the EU farms. Journal of Agricultural Economics, 64(3), 537-557, DOI: 10.1111/1477-9552.12030
  55. Rude, J. (2008). Production effects of the European Union’s single farm payment. Canadian. Journal of Agricultural Economics/Revue Canadienne d’Agroeconomie, 56(4), 457-471, DOI: 10.1111/j.1744-7976.2008.00141.x
  56. Rudinskaya, T., Hlavsa, T. & Hruska, M. (2019). Estimation of technical efficiency of Czech farms operating in less favoured areas. Agricultural Economics, 65(10), 445-453, DOI: 10.17221/52/2019-AGRICECON
  57. Shucksmith, M., Thomson, K.J. & Roberts, D. (2005). The CAP and the regions: the territorial impact of the Common Agricultural Policy. Wallingford: CAB Int. Publishing, DOI: 10.1079/9780851990552.0000
  58. Simar, L. & Wilson, P.W. (2007). Estimation and inference in two-stage, semiparametric models of production processes. Journal of econometrics, 136(1), 31-64, DOI: 10.1016/j.jeconom.2005.07.009
  59. Simar, L. & Wilson, P.W. (2011). Two-stage DEA: caveat emptor. Journal of Productivity Analysis, 36(2), 205-218, DOI: 10.1007/s11123-011-0230-6
  60. Simar, L. & Wilson, P.W. (2015). Statistical approaches for non‐parametric frontier models: a guided tour. International Statistical Review, 83(1), 77-110, DOI: 10.1111/insr.12056
  61. Stanciu, S. (2017). A comparative study regarding the European agricultural allocation of funds for rural development during 2007-2013 and 2014-2020. SEA–Practical Application of Science, 13, 49-55.
  62. Swinbank, A. (2008). Potential wto Challenges to the CAP. Canadian Journal of Agricultural Economics/Revue Canadienne d’Agroeconomie, 56(4), 445-456, DOI: 10.1111/j.1744-7976.2008.00140.x
  63. Todorović, S., Papić, R., Ciaian, P. & Bogdanov, N. (2020). Technical efficiency of arable farms in Serbia: do subsidies matter? New Medit: Mediterranean Journal of Economics, Agriculture and Environmen, 19(4), 81-97, DOI: 10.30682/nm2004f
  64. Von Witzke, H. & Noleppa, S. (2007). Agricultural and trade policy reform and inequality: the distribution effects of the direct payments to German farmers under the EU’s new common agricultural policy. Working paper no. 79/2007.
  65. Wang, H.J. & Schmidt, P. (2002). One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels. Journal of Productivity Analysis, 18(2), 129-144, DOI: 10.1023/A:1016565719882
  66. Zhu, X. & Lansink, A.O. (2010). Impact of CAP subsidies on technical efficiency of crop farms in Germany, the Netherlands and Sweden. Journal of Agricultural Economics, 61(3), 545-564, DOI: 10.1111/j.1477-9552.2010.00254.x

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Nicola Galluzzo, Estimation of the impact of CAP subsidies as environmental variables on Romanian farms in "Economia agro-alimentare" 3/2021, pp 1-24, DOI: 10.3280/ecag2021oa12772