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Impact of Government facilitieson technical efficiency of rice farmers in the Senegal River Valley

Year 2017, Volume: 1 Issue: 1, 36 - 46, 30.01.2017
https://doi.org/10.29023/alanyaakademik.290280

Abstract

This paper aims at assessing the impact of the government hydro-agricultural
facilities on the rice farmers’ technical efficiency in the Senegal River
valley. Results estimations showed that farming in thesefacilities increaseson
average the technical efficiency by 5.17 %. The technical efficiency
determinants analysis from an exponential function estimation, using a
nonlinear least squares method, reveals that, besides the treatment, the
combined effects between this one and the distance from the house to the plot,
the educations’ level, the household sizeand the householder gender are
statistically significant on efficiency. The major policy implications are:(i)
the Government should keep on providing these kinds of agricultural
infrastructure to farmers; (ii) the establishment of a sustainable Fund for
Supporting Agricultural Research and Scaling out Agricultural Research
Achievements would strengthen capacities of Research and Extension Services to
address many issues in the rural areas.

References

  • Agence Nationale de la Statistique et de la Démographie, 2014. Note d’Analyse du Commerce Extérieur.Ministryof Economyand Finances of Senegal.
  • Alene, AD& Hassan,RM, 2003.Measuring the Impact of Ethiopia’s New Extension Programme on the Productive Efficiency of Farmers.Contributed paper selected for presentation at the 25th International Conference of Agricultural Economists, August, Durban, South Africa.
  • Alvarez – Ayuso, IC, Becerril – Torres,OU&del Moral – Barrera, LE,2011.The Effect of Infrastructures on Total Factor Productivity and its Determinants: A Study on Mexico. Economic Studies: Vol. 26, No. 1, January – June, pp 97 – 122.
  • Ashok, KR&Balasubramanian, R,2006. Role of Infrastructure in Productivity and Diversification of Agriculture, Draft Final Report,South Asia Network of Economic Institutes (SANEI).
  • Bassole, L,2004.Programme d’infrastructures rurales et bien-être des ménages : Analyse en termes d’indicateurs anthropométriques des enfants. Unpublished paper, CERDI – CNRS, Universitéd’Auvergne.
  • Becker, SO&Ichino,A,2002. Estimation of average treatment effects based on propensity scores.The Stata Journal 2, No. 4, pp 358 – 377.
  • Chabé – Ferret, S,2008.L’évaluation de l’impact des politiques publiques : caractérisation des enjeux et exemples de politiques agricoles et forestières. Unpublished doctoral dissertation,Universitéd’Auvergne Clermont-Ferrand I, France.
  • Cox, DR,1970. The Analysis of Binary Data. London: Methuen & Co Ltd.
  • Debreu, G,1951.The Coefficient of Resource Utilization. Econometrica: Vol. 19, No. 3, July, pp. 273-292.
  • Diagne, A,2014. Impact Assessment Methodology. Presentation made at the Africa Rice Center Headquarters, Cotonou, Benin.
  • Dontsop-Nguezet, PM, Diagne, A,Okoruwa, VO. &Ojehomon,V, 2011.Impact of Improved Rice Technology on Income and Poverty Among Rice Farming Household in Nigeria: A Local Average Treatment Effect (LATE) Approach.Contributed paper prepared for the 25th conference of the Centre for the Studies of African Economies (CSAE),March, St Catherine College, University of Oxford, UK.
  • Fall, AA, 2008.Impact du crédit sur le revenu des riziculteurs de la Vallée du Fleuve Sénégal. Unpublished doctoral dissertation, Universityof Montpellier I, France.
  • Farrel, MJ,1957.The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), Vol. 120, No. 3, pp. 253 - 290.
  • Heckman, JJ, Ichimura, H&Todd, P, 1998.Matching As An Econometric Evaluation Estimator. Review of Economic Studies: 65, pp 261 – 294.
  • Holland, PW, 1986. Statistics and Causal Inference. Journal of the American Statistical Association: 81, 945–970.
  • Jha, RK, Gyawali, LN, Regmi, AP, Ghimire,A&Paudyal, KR,2007. Impacts of participatory extension programme on technical efficiency of farmers in Nepal. Unpublished paper, South Asia Network of Economic Institutes (SANEI).
  • Koopmans, TC,1951. Analysis of production as an efficient combination of activities.In Cowles Commission for Research in Economics (Ed.),Activity Analysis of Production and Allocation. John Wiley & Sons, Inc., New York.
  • Mastromarco, C&Woitek,U,2006.Public infrastructure investment and efficiency in Italian regions.Journal of ProductivityAnalysis 25:57–65.
  • Ministère de l’Agriculture et de l’Equipement Rural du Sénégal, 2014.Programme d’Accélération de la Cadence de l’Agriculture Sénégalaise (PRACAS) : Les Priorités à l’horizon 2017. Unpublishedpaper.
  • Ngom, CAB, Sarr,F&Fall,AA, 2016.Mesure de l’efficacité technique des riziculteurs du bassin du fleuve Sénégal. EconomieRurale :numéro 355, septembre - octobre, pp 91 - 108.
  • Opara, UN,2010. Personal and Socio-Economic Determinants of Agricultural Information Use by Farmers in the Agricultural Development Programme (ADP) Zones of Imo State, Nigeria. Library Philosophy and Practice: pp 1 – 8.
  • Percoco, M, 2004. Infrastructure and Economic Efficiency in Italian Regions. Networks and Spatial Economics: No. 4, pp 361–378.
  • Puig-Junoy, J& Pinilla, J,2008. Why Are Some Spanish Regions So Much More Efficient Than Others?Unpublishedpaper.
  • Quatrida, D,2009. La SAED face aux privés : problèmes et perspectives de l’agriculture irriguée dans le Delta du fleuve Sénégal.InDansero, E, Luzzati, E&Seck, SM(Ed.),Organisation paysanne et développement local, leçon à partir du cas du Delta du fleuve Sénégal.L’Harmattan, Italia.
  • Rosenbaum, PR& Rubin,DB,1983. The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika: Vol. 70, No. 1, April, pp 41 – 55.
  • Rubin, DB, 1974. Estimating Causal Effects of the Treatments in Randomized and Nonrandomized Studies. Journal of Educational Psychology. Vol. 66, No 5, pp 688 – 701.
  • Rubin,DB, 1977. Assignment to Treatment Group on the Basis of a Covariate.Journal of Educational Statistics.Vol. 2, pp. 1-26.
  • Taylor, TG, Drummond, HE& Gomes,AT,1986. Agricultural credit programmes and production efficiency: an analysis of traditional farming in southeastern Minas Gerais, Brazil. Am. J. Agric. Econ.: 68:110-119.
  • Xie Y, Brand J & Jann, B, 2011. Estimating Heterogeneous Treatment Effects With Observational Data. Report 11 – 729, Population Studies Center, University of Michigan Institute for Social Research, USA.

Impact of Government facilitieson technical efficiency of rice farmers in the Senegal River Valley

Year 2017, Volume: 1 Issue: 1, 36 - 46, 30.01.2017
https://doi.org/10.29023/alanyaakademik.290280

Abstract

Bu makale, devlet hidro-tarım tesislerinin,
Senegal Nehri vadisinde pirinç çiftçilerinin teknik verimi üzerindeki etkisini
değerlendirmeyi amaçlamaktadır. Sonuçlara göre, bu tesislerde gerçekleştirilen zirai
faaliyetler ortalama % 5,17 oranında teknik verimliliği arttırmaktadır. Lineer
olmayan en küçük kareler yöntemini kullanarak üstel fonksiyon tahmininden
teknik verimlilik belirleyicileri analizi, işleyişin yanı sıra, ev ile arsa
arasındaki mesafenin birleşik etkisi, eğitim seviyesi, hanehalkı büyüklüğü ve
aile içi cinsiyet, verimlilik açısından istatistiksel olarak önemlidir.
Uygulanabilecek başlıca politikalar ise şunlardır:  (i) Hükümet bu tür tarım altyapısını
çiftçilere sunmaya devam etmelidir, (ii) Tarımsal Araştırma Destekleme ve
Tarımsal Araştırma Başarılarını Ölçeklendirme için sürdürülebilir bir fon
kurulması, Araştırma ve Genişletme Hizmetlerinin kırsal alanlardaki birçok
konuyu ele alacak kapasitelerini güçlendirecektir.

References

  • Agence Nationale de la Statistique et de la Démographie, 2014. Note d’Analyse du Commerce Extérieur.Ministryof Economyand Finances of Senegal.
  • Alene, AD& Hassan,RM, 2003.Measuring the Impact of Ethiopia’s New Extension Programme on the Productive Efficiency of Farmers.Contributed paper selected for presentation at the 25th International Conference of Agricultural Economists, August, Durban, South Africa.
  • Alvarez – Ayuso, IC, Becerril – Torres,OU&del Moral – Barrera, LE,2011.The Effect of Infrastructures on Total Factor Productivity and its Determinants: A Study on Mexico. Economic Studies: Vol. 26, No. 1, January – June, pp 97 – 122.
  • Ashok, KR&Balasubramanian, R,2006. Role of Infrastructure in Productivity and Diversification of Agriculture, Draft Final Report,South Asia Network of Economic Institutes (SANEI).
  • Bassole, L,2004.Programme d’infrastructures rurales et bien-être des ménages : Analyse en termes d’indicateurs anthropométriques des enfants. Unpublished paper, CERDI – CNRS, Universitéd’Auvergne.
  • Becker, SO&Ichino,A,2002. Estimation of average treatment effects based on propensity scores.The Stata Journal 2, No. 4, pp 358 – 377.
  • Chabé – Ferret, S,2008.L’évaluation de l’impact des politiques publiques : caractérisation des enjeux et exemples de politiques agricoles et forestières. Unpublished doctoral dissertation,Universitéd’Auvergne Clermont-Ferrand I, France.
  • Cox, DR,1970. The Analysis of Binary Data. London: Methuen & Co Ltd.
  • Debreu, G,1951.The Coefficient of Resource Utilization. Econometrica: Vol. 19, No. 3, July, pp. 273-292.
  • Diagne, A,2014. Impact Assessment Methodology. Presentation made at the Africa Rice Center Headquarters, Cotonou, Benin.
  • Dontsop-Nguezet, PM, Diagne, A,Okoruwa, VO. &Ojehomon,V, 2011.Impact of Improved Rice Technology on Income and Poverty Among Rice Farming Household in Nigeria: A Local Average Treatment Effect (LATE) Approach.Contributed paper prepared for the 25th conference of the Centre for the Studies of African Economies (CSAE),March, St Catherine College, University of Oxford, UK.
  • Fall, AA, 2008.Impact du crédit sur le revenu des riziculteurs de la Vallée du Fleuve Sénégal. Unpublished doctoral dissertation, Universityof Montpellier I, France.
  • Farrel, MJ,1957.The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), Vol. 120, No. 3, pp. 253 - 290.
  • Heckman, JJ, Ichimura, H&Todd, P, 1998.Matching As An Econometric Evaluation Estimator. Review of Economic Studies: 65, pp 261 – 294.
  • Holland, PW, 1986. Statistics and Causal Inference. Journal of the American Statistical Association: 81, 945–970.
  • Jha, RK, Gyawali, LN, Regmi, AP, Ghimire,A&Paudyal, KR,2007. Impacts of participatory extension programme on technical efficiency of farmers in Nepal. Unpublished paper, South Asia Network of Economic Institutes (SANEI).
  • Koopmans, TC,1951. Analysis of production as an efficient combination of activities.In Cowles Commission for Research in Economics (Ed.),Activity Analysis of Production and Allocation. John Wiley & Sons, Inc., New York.
  • Mastromarco, C&Woitek,U,2006.Public infrastructure investment and efficiency in Italian regions.Journal of ProductivityAnalysis 25:57–65.
  • Ministère de l’Agriculture et de l’Equipement Rural du Sénégal, 2014.Programme d’Accélération de la Cadence de l’Agriculture Sénégalaise (PRACAS) : Les Priorités à l’horizon 2017. Unpublishedpaper.
  • Ngom, CAB, Sarr,F&Fall,AA, 2016.Mesure de l’efficacité technique des riziculteurs du bassin du fleuve Sénégal. EconomieRurale :numéro 355, septembre - octobre, pp 91 - 108.
  • Opara, UN,2010. Personal and Socio-Economic Determinants of Agricultural Information Use by Farmers in the Agricultural Development Programme (ADP) Zones of Imo State, Nigeria. Library Philosophy and Practice: pp 1 – 8.
  • Percoco, M, 2004. Infrastructure and Economic Efficiency in Italian Regions. Networks and Spatial Economics: No. 4, pp 361–378.
  • Puig-Junoy, J& Pinilla, J,2008. Why Are Some Spanish Regions So Much More Efficient Than Others?Unpublishedpaper.
  • Quatrida, D,2009. La SAED face aux privés : problèmes et perspectives de l’agriculture irriguée dans le Delta du fleuve Sénégal.InDansero, E, Luzzati, E&Seck, SM(Ed.),Organisation paysanne et développement local, leçon à partir du cas du Delta du fleuve Sénégal.L’Harmattan, Italia.
  • Rosenbaum, PR& Rubin,DB,1983. The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika: Vol. 70, No. 1, April, pp 41 – 55.
  • Rubin, DB, 1974. Estimating Causal Effects of the Treatments in Randomized and Nonrandomized Studies. Journal of Educational Psychology. Vol. 66, No 5, pp 688 – 701.
  • Rubin,DB, 1977. Assignment to Treatment Group on the Basis of a Covariate.Journal of Educational Statistics.Vol. 2, pp. 1-26.
  • Taylor, TG, Drummond, HE& Gomes,AT,1986. Agricultural credit programmes and production efficiency: an analysis of traditional farming in southeastern Minas Gerais, Brazil. Am. J. Agric. Econ.: 68:110-119.
  • Xie Y, Brand J & Jann, B, 2011. Estimating Heterogeneous Treatment Effects With Observational Data. Report 11 – 729, Population Studies Center, University of Michigan Institute for Social Research, USA.
There are 29 citations in total.

Details

Subjects Economics
Journal Section Makaleler
Authors

Cheikh Ahmadou Bamba Ngom This is me

Publication Date January 30, 2017
Published in Issue Year 2017 Volume: 1 Issue: 1

Cite

APA Ngom, C. A. B. (2017). Impact of Government facilitieson technical efficiency of rice farmers in the Senegal River Valley. Alanya Akademik Bakış, 1(1), 36-46. https://doi.org/10.29023/alanyaakademik.290280