A comparative stochastic frontier analysis of irrigated and rain-fed potato farms in Eastern Ethiopia

• Authors: Kumilachew Alamerie Melesse , Musa Hasen Ahmed

Title variants

PL

Porównawcza analiza stochastyczna gospodarstw z uprawą ziemniaków nawadnianych sztucznie i naturalnie we Wschodniej Etiopii

• Languages of publication: EN

Abstracts

EN

Irrigation development has been considered as one of the viable strategies for achieving food security. Accordingly, the government of Ethiopia has been increasing water resource development and utilization. However, to what extent the irrigation users are better off than rainfall dependent counterparts on their technical effi ciency (TE) and variability in productivity among the farmers is not well known. Therefore, this study compared the technical efficiency of farmers who are producing potato under irrigation and through rainfall in Eastern Ethiopia. Propensity Score Matching was applied to select irrigated farms with comparable attributes to rain-fed farms to see the true effi ciency diff erences between the two groups. Cobb-Douglas production function was fi tted using the stochastic production frontier for both irrigated and rain fed farming. The result indicated that irrigated farms have high ineffi ciencies compared with the rain-fed farms. This indicates the existence of considerable potential for increasing output by improving the effi ciency of irrigated farms than rain-fed farms. Among the factors hypothesized to determine the level of TE, landholding, family size and extension contact were found to have a signifi cant eff ect on irrigated farms whereas, landholding, non/off income, farm income, livestock size and extension contact were the determinants in rain-fed farms. This indicates that factors that aff ect technical efficiency in irrigated farms are not necessarily the same as rain fed farms. Therefore, it is important to consider both farms groups in evaluating strategies aimed at improving technical effi ciency of smallholder farmers

PL

Rozwój systemów nawadniania jest powszechnie uważany za jedną z najistotniejszych strategii zapewniających bezpieczeństwo żywnościowe. Zwiększenie zasobów wodnych i odpowiednie ich wykorzystanie to kwestie szczególnie istotne dla rządu Etiopii. Dotychczas nie zbadano jednak dokładnie korzyści stosowania nawadniania sztucznego na tle nawadniania naturalnego pod względem efektywności technologicznej. Niniejsze opracowanie zawiera zatem porównanie efektywności technologicznej tych dwóch grup producentów ziemniaków na obszarze wschodniej Etiopii. Przy wyborze porównywalnych gospodarstw do badania zastosowano metodę PSM (Propensity Score Matching), co umożliwiło określenie rzeczywistych różnic między podmiotami z obu grup. Dopasowano funkcję produkcji Cobba-Douglasa, stosując porównawczą analizę stochastyczną produkcji dla obu przypadków – z nawadnianiem i bez. Wykazano, że gospodarstwa nawadniane są znacznie mniej efektywne w porównaniu z drugą grupą. Wskazuje to na ogromny potencjał zwiększenia ich produkcji dzięki poprawie efektywności. W gospodarstwach nawadnianych za czynniki mające hipotetycznie największy wpływ na poziom efektywności technologicznej uznano: wielkość gospodarstwa, liczebność rodziny i kontakty z ośrodkami doskonalenia, natomiast w gospodarstwach nawadnianych naturalnie były to: wielkość gospodarstwa, dochód z działalności pozarolniczej i rolniczej, liczebność żywego inwentarza i kontakty z ośrodkami doskonalenia. Okazuje się więc, że w każdej z tych dwóch grup gospodarstw zupełnie inne czynniki wpływają na efektywność technologiczną. Przy opracowywaniu strategii mających na celu jej poprawę trzeba zatem uwzględnić specyfi kę obu badanych grup.

Keywords

EN

irrigation; rain-fed; technical efficiency; stochastic frontier; PSM; potato

PL

nawadnianie; nawodnienie naturalne; efektywność technologiczna; porównawcza analiza stochastyczna; PSM; ziemniaki

• Publisher: Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu
• Journal: Journal of Agribusiness and Rural Development
• Year: 2015
• Issue: 4(38)
• Pages: 769-781

Contributors

author

Kumilachew Alamerie Melesse

• Haramaya University

author

Musa Hasen Ahmed

• Haramaya University

References

• Abdoulaye, T., Sanders, J. H. (2005). Stages and determinants of fertilizer use in semiarid African agriculture: the Niger experience. Agric. Econ., 32 (2), 167–179.
• Ahmed, H., Lemma, Z., Endrias, G. (2014). Technical Efficiency of Maize Producing Farmers in Arsi Negelle, Central Rift Valley of Ethiopia: Stochastic Frontier Approach. J. Agric. Forest., 60 (1), 157–167.
• Aigner, D., Lovell, C., Schmidt, P. (1977). Formulation and Estimation of Stochastic Frontier Production Function Models. J. Economet., 6, 21–37.
• Arega, D., Manfrez, Z. (2005). Technology Adoption and Farmer Effi ciency in Multiple Crops Production in Eastern
• Ethiopia: A Comparison of Parametric and Non-Parametric Distance Functions. Agric. Econ. Rev., 6(1), 5–17.
• Awulachew, B., Yilma, A., Loulseged, M., Loiskandl, W., Ayana, M., Alamirew, T. (2007). Water Resources and Irrigation Development in Ethiopia. Working Paper 123. Colombo, Sri Lanka: International Water Management Institute.
• Battese, G. E., Coelli, T. J. (1995). A Model for Technical Inefficiency Eff ects in a Stochastic Frontier Production Function for Panel Data. J. Empiric. Econ., 20 (2), 325–332.
• Bezabih, E., Hadera, G. (2007). Constraints and Opportunities of Horticulture Production and Marketing in Eastern Ethiopia. Dry lands Coordination Group Report No. 46.
• Rosembaum, P. R., Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.
• Bradley, K., Tatjana, H., Ralph, M., Charles, E., Wilson, J., Lance, S. (2014). Measurement of Technical, Allocative and Scale Efficiency of Rice Production in Arkansas Using Data Envelopment Analysis. J. Agric. Appl. Econ., 46(1), 89–106.
• Caliendo, M., Kopeinig, S. (2008). Some Practical Guidance for the Implementation of Propensity Score Matching. IZA Discussion Paper No. 1588, University of Cologne.
• Chakraborty, K., Misra, S., Johnson, P. (2002). Cotton Farmers’Technical Effi ciency Stochastic and Non-Stochastic Production Function Approaches. Agric. Res. Econ. Rev., 31, 211–220.
• Charnes, A., Rhodes, E. (1978). Measuring the Inefficiency of Decision Making Unit. Eur. J. Oper. Res., 2, 429–44.
• CSA (2014). Statistical Report on Area and Crop Production. Addis Ababa, Ethiopia: Central Statistical Agency.
• Coelli, T. J., Prasada, D. S., O’Donnell, C. J, Battese, G. E. (2005). An introduction to efficiency and productivity analysis. Second edition. New York: Springer Science.
• Coelli, T. J., Prasada, D. S., O’Donnell, C. J., Battese, G. E. (1998). An Introduction to Efficiency and Productivity Analysis. Boston: Kluwer Academic Publishers.
• Coelli, T. J. (1995). Estimators and Hypothesis Tests for Stochastic Frontier Function: A Monte Carlo Analysis. J. Prod. Anal., 6, 247 – 268.
• Dehejia, R. H., Wahba, S. (2002). Propensity Score Matching Methods for Non-Experimental Causal Studies. Rev. Econ. Stat., 84 (1), 151–161.
• Del Gatto, M., Di Liberto, A., Petraglia, C. (2011). Measuring Productivity. Econ. Surv., 25 (5), 952–1008.
• Endale, G., Gebremedhin, W., Lemaga, B. (2008). Potato Seed Management. In: W. Gebremedhin, G. Endale, B. Lemaga (Eds.), Root and tuber crops: The untapped resources (p. 53–78). Addis Ababa: Ethiopian Institute of Agricultural Research.
• FAOSTAT (2015). Retrieved from: http://faostat3.fao.org/home/E.
• FAO (2009). How to Feed the World In 2050, Vialedelle Terme di Caracalla. Rome, Italy: Food and Agriculture Organization of the United Nations.
• Farrell, M. J., Fieldhouse, M. (1962). Estimating Efficient Production under Increasing Returns to Scale. J. Royal Stat. Soc., 125, 252–267.
• Farrell, M. J. (1957). The Measurement of Productive Efficiency. J. Royal Stat. Soc., 120, 253–281.
• Gebrehaweria, G., Regassa, N., Stein, H. (2012). Technical Efficiency of Irrigated and Rain-Fed Smallholder Agriculture in Tigray, Ethiopia: A Comparative Stochastic Frontier Production Function Analysis. Q. J. Int. Agric., 51(3), 203–226.
• Gelaw, F. (2013). Ineffi ciency and Incapability Gaps as Causes of Poverty: A Poverty Line-Augmented Effi ciency Analysis Using Stochastic Distance Function. Afr. J. Agric. and Res. Econ., 8 (2), 24–68.
• Getachew, S., Ranjan, R. (2012). Growing Vulnerability: Population Pressure, Food Insecurity and Environmental Degradation, Central Rift Valley, Ethiopia. J. Biodiv. Env. Sci., 2(3), 33–41
• Goshu, D., Kassa, B., Mengistu, K. (2012). Is Food Security Enhanced By Agricultural Technologies In Rural Ethiopia? Afr. J. Agric. Res. Econ., 8 (1), 58–68.
• IWMI (2011). A Comparative Analysis of the Technical Efficiency of Rain-Fed and Smallholder Irrigation in Ethiopia. International Water Management Institute.
• Jondrow, J., Lovell, C. K., Materov, I. S., Schmidt, P. (1982). On Estimation of Technical Ineffi ciency in the Stochastic Frontier Production Function Model. J. Economet., 19, 233–38.
• Mahlet, A., Bezabih, E, Mengistu, K., Jeff reyson, K. M., Jemal, Y. (2105). Gender role in market supply of potato in Eastern Hararghe Zone, Ethiopia. Afr. J. Agric. Mark., 3 (8), 241–251.
• Meeusen, W., Van Den Broeck, J. (1977). Effi ciency Estimation from Cobb–Douglas Production Function with Composed Error. Int. Econ. Rev., 18, 435–444.
• MoA (2000). Agro-ecological zonations of Ethiopia. Addis Ababa, Ethiopia: Ministry of Agriculture.
• Raymond, J. (1981). The Measurement of Technical Efficiency: The Reconsideration. J. Econ., 96(3).
• Sharma, K. R., Leung, P., Zalleski, H. M. (1999). The Technical, Allocative and Economic Efficiencies in Swine Production in Hawaii: A Comparison of Parametric and NonParametric Approaches. Agric. Econ., 20, 23–35.
• UNDP (2009). Terms of Reference for Consultancy to Carry out Assessment of Past and Present Experiences (Success/Challenges) On the Resettlement Program in Tigray Region. United Nation Development Program.
• WFP (2010). The State of Food Insecurity in the World. Rome, Italy: World Food Program.
• Yin, R. (2000). Alternative Measurements of Productive Efficiency in the Global Bleached Softwood Pulp Sector. J. Forest Sci., 46, 558–569.

Identifiers

DOI

10.17306/JARD.2015.80