Skip to main navigation menu Skip to main content Skip to site footer
FrancoAngeli Journals

Regular Articles

Vol. 22 No. 2 (2020)

The technical efficiency of the Apulian winegrowing farms with different irrigation water supply systems

DOI
https://doi.org/10.3280/ecag2-2020oa10410
Submitted
settembre 17, 2020
Published
2020-09-17

Abstract

Apulia has a considerable demand of irrigation water, however high inefficiency levels of the collective water networks force most of the regional farms to use groundwater, with a consequent worsening of its quality, as well as of soil and crops characteristics. Therefore, the use of sustainable supply methods
for irrigation water is desirable both through improvements of the collective networks and by appropriate economic tools.
However, making the correct choices in these matters requires knowledge concerning the effects of the present water supply systems on the economic performance of farms.
The objective of this study is to measure and compare the technical efficiency of winegrowing farms in northern Apulia that use different supply systems for irrigation water: groundwater from private wells, irrigation water from collective networks, and irrigation water from both private wells and collective networks. The results enable to understand if and how different supply systems of irrigation water affect the management of productive factors and inputs. These findings also provide useful information for appropriate policies aimed at preserving groundwater and its externalities, as well as at improving the economic performance of Apulian farms.

References

  1. Acciani, C. & Sardaro, R. (2014). Percezione del rischio da campi elettromagnetici in presenza di servitù di elettrodotto: incidenza sul valore dei fondi agricoli. Aestimum, 64, 39-55, doi: 10.13128/Aestimum-14708.
  2. Aigner, D.J., Lovell, C.A.K. & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21-37, doi: 10.1016/0304-4076(77)90052-5.
  3. Ali, M. & Flinn, J.C. (1989). Profit efficiency among Basmati rice producers in Pakistan Punjab. American Journal of Agricultural Economics, 71, 303-310, doi: 10.2307/1241587.
  4. anbi (2009), Relazione annuale. www.adb.basilicata.it/adb/Pstralcio/pianoacque/ basilicata/Allegato%205%20-%20Uso%20irriguo%20nel%20distretto%20-%20 Regione%20BASILICATA.pdf.
  5. Arborea, S., Giannoccaro, G., de Gennaro, B.C., Iacobellis, V. & Piccinni, A.F. (2017). Cost–Benefit Analysis of Wastewater Reuse in Puglia, Southern Italy. Water, 9, 175, doi: 10.3390/w9030175.
  6. Battese, G.E. & Coelli, T.J. (1993). A stochastic frontier production function incorporating a model for technical inefficiency effects. Working Paper 93/05. Department of Econometrics, University of New England, Armidale, Australia.
  7. 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, doi: 10.1007/BF01205442.
  8. Benedetti, I., Branca, G., Zucaro, R. (2019). Evaluating input use efficiency in agriculture through a stochastic frontier production: An application on a case study in Apulia (Italy). Journal of Cleaner Production, 236, 117609, doi: 10.1016/j.jclepro.2019.117609.
  9. Berbel, J., Borrego, M.M., Expósito, A., Giannoccaro, G., Montilla-López, N.M. & Roseta-Palma, C. (2019). Analysis of irrigation water tariffs and taxes in Europe. Water Policy, 21, 806-825, doi: 10.2166/wp.2019.197.
  10. Bozoğlu, M. & Ceyhan, V. (2007). Measuring the technical efficiency and exploring the inefficiency determinants of vegetable farms in Samsun province, Turkey. Agricultural Systems, 94, 649-656, doi: 10.1016/j.agsy.2007.01.007.
  11. Coelli, T.J. (1996). A guide to frontier Version 4.1: a computer program for stochastic frontier production and cost function estimation. Working Paper. Centre for Efficiency and Productivity Analysis, University of New England, Armidale.
  12. Coelli, T.J., Rao, D.S.P. & Battese, G.E. (1998). An introduction to efficiency and productivity analysis. Boston: Kluwer Academic Publishers, doi: 10.1007/978-1-4615-5493-6.
  13. Christensen, L., Jorgensen, D. & Lau, L. (1973). Transcendental Logarithmic Production Frontier. Review of Economics and Statistics, 55, 28-45, doi: 10.2307/1927992.
  14. De Benedictis, M. & Cosentino, V. (1979). Economia dell’azienda agraria. Bologna: il Mulino.
  15. Distretto Idrografico dell’Appennino Meridionale (2010). Piano di Gestione Acque (Direttiva Comunitaria 2000/60/CE, D.Lvo. 152/06, L. 13/09).
  16. Fabiani, S. (a cura di) (2009). Aspetti economici dell’agricoltura irrigua in Puglia. Roma: Istituto Nazionale di Economia Agraria.
  17. Farrell, M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120, 253-281, doi: 10.2307/2343100.
  18. Giannoccaro, G., Casieri, A., de Vito, R., Zingaro, D. & Portoghese, I. (2019). Impatti economici dell’interruzione del servizio irriguo consortile nell’area della Capitanata (Puglia). Stima empirica per il pomodoro da industria nel periodo 2001-2016. Aestimum, 74, 101-114, doi: 10.13128/aestim-7382.
  19. Greene, W. (2004). Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization’s panel data on national health care systems. Health Economics, 13, 959-980, doi: 10.1002/hec.938.
  20. Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126, 269-303, doi: 10.1016/j.jeconom.2004.05.003.
  21. Hansson, H. & Öhlmér, B. (2008). The effect of operational managerial practices on economic, technical and allocative efficiency at Swedish dairy farms. Livestock Science, 118, 34-43, doi: 10.1016/j.livsci.2008.01.013.
  22. Idda, L., Furesi, R. & Pulina, P. (2010). Economia dell’allevamento ovino da latte. Produzione, trasformazione, mercato. Milano: FrancoAngeli.
  23. Istat (2010), 6° Censimento Generale dell’Agricoltura, http://dati-censimentoagricoltura.istat.it/Index.aspx.
  24. Jondrow, J., Lovell, K., Materov, L. & Schmidt, P. (1982). On the estimation of technical inefficiency in the stochastic frontier production function model. Journal of Econometrics, 19, 233-238, doi: 10.1016/0304-4076(82)90004-5.
  25. Kumbhakar, S.C., Biswas, B. & Bailey, D.V. (1989). A study of economic efficiency of Utah dairy farmers: a systems approach. Review of Economics and Statistics, 71, 595-604, doi: 10.2307/1928101.
  26. Lawson, G.L., Agger, J.F., Lund, M. & Coelli, T. (2004). Lameness, metabolic and digestive disorders, and technical efficiency in Danish dairy herds: a stochastic frontier production function approach. Livestock Production Science, 91, 157-172, doi: 10.1016/j.livprodsci.2004.07.016.
  27. Meeusen, W. & van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18, 435-444, doi: 10.2307/2525757.
  28. Nino, P. & Vanino, S. (a cura di) (2009). Uso del suolo e stima dei fabbisogni irrigui nelle aree non servite da reti collettive dei consorzi di bonifica nelle regioni meridionali. Roma: Istituto Nazionale di Economia Agraria.
  29. Rahman, S. (2003). Profit efficiency among Bangladeshi rice farmers. Food Policy, 28, 487-503, doi: 10.1016/j.foodpol.2003.10.001.
  30. Petrillo, F. & Sardaro, R. (2014). Urbanizzazione in chiave neoliberale e progetti di sviluppo a grande scala. Scienze Regionali, 13, 125-134, doi: 10.3280/SCRE2014-002010.
  31. Sardaro, R., Bozzo, F. & Fucilli, V. (2018). High-voltage overhead transmission lines and farmland value: evidences from the real estate market in Apulia, southern Italy. Energy Policy, 119, 449-457, doi: 10.1016/j.enpol.2018.05.005.
  32. Sardaro, R., Grittani, R., Scrascia, M., Pazzani, C., Russo, V., Garganese, F., Porfido, C., Diana, L. & Porcelli, F. (2018). The Red Palm Weevil in the City of Bari: A First Damage Assessment. Forests, 9, 452, doi: 10.3390/f9080452.
  33. Sardaro, R., Faccilongo, N. & Roselli, L. (2019). Wind farms, farmland occupation and compensation: Evidences from landowners’ preferences through a stated choice survey in Italy. Energy Policy, 133, 110885, doi: 10.1016/j.enpol.2019.110885.
  34. Serpieri, A. (1929). Guida a ricerche di Economia Agraria. Ristampa del 1960. Bologna: Edagricole.
  35. Tan, S., Heerink, N., Kuyvenhoven, A. & Qu F. (2010). Impact of land fragmentation on rice producers’ technical efficiency in South-East China. NJAS-Wageningen Journal of Life Sciences, 57, 117-123, doi: 10.1016/j.njas.2010.02.001.
  36. Tzouvelekas, V., Pantzios, C.J. & Fotopoulos C. (2001). Technical efficiency of alternative farming systems: the case of Greek organic and conventional olivegrowing farms. Food Policy, 26, 549-569, doi: 10.1016/S0306-9192(01)00007-0.
  37. Wilson, P., Hadley, D., Ramsden, S. & Kaltsas, L. (1998). Measuring and explaining technical efficiency in UK potato production. Journal of Agricultural Economics, 48, 294-305, doi: 10.1111/j.1477-9552.1998.tb01273.x.
  38. Zucaro, R., Pontrandolfi, A., Dodaro, G.M., Gallinoni, C., Pacicco, C.L. & Vollaro, M. (2011). Atlante nazionale dell’irrigazione. INEA.
  39. Zucaro, R. (a cura di) 2014. Condizionalità ex-ante per le risorse idriche: opportunità e vincoli per il mondo agricolo. Rapporto INEA.

Metrics

Metrics Loading ...

Most read articles by the same author(s)