Analysis of Socio-economic Factors Influencing the Adoption of Breeding Technologies among Dairy Farmers in the North Rift Region of Kenya

Author(s)

Ernest Kipkemei ,

Download Full PDF Pages: 143-168 | Views: 1487 | Downloads: 402 | DOI: 10.5281/zenodo.3473905

Volume 6 - December 2017 (12)

Abstract

In many third world countries today, Kenya included, adoption of agricultural technologies plays a big role in agricultural production especially due to the need to increase production for food security and income. North Rift is one of the regions in Kenya where the dairy sub-sector is the second largest income contributor. This sector employs 50% of agricultural labour force and provides substantial amount of raw materials for local meat and milk processing industries. Though the region is one of the high potential agricultural areas in Kenya, the total annual milk output lately does not match the region’s potential. North Rift region is endowed with a lot of livestock and thus is expected that dairy output in the region should be high yet this is not so. Despite the government’s plans to develop the livestock sector through the introduction of various technologies such as breeding   the local farmers hardly implement this technology. This has resulted in low milk production in the region. This study therefore, sought to determine and analyze the socio-economic factors that affect the adoption of breeding technologies among the dairy farmers in the region. The study was undertaken in Nandi, Uasin-Gishu and Trans-Nzoia counties of the North Rift region. A survey research design was used. The target population was all dairy farmers in the three counties of the region. Purposive, multistage, simple random and systematic sampling techniques were used to get 360 respondents for the study. Data was collected by use of structured questionnaires and analyzed using descriptive and inferential statistics.  Dairy farming households were used as units for analysis.  Descriptive analysis and the Logit model were used to analyze data in order to answer the study objectives. The results showed that the age, gender and education level of the farmer, size of dairy land, cost of AI and frequency of visits by the extension personnel significantly influenced the adoption of breeding technologies by the farmers. There is need for the government to revive and expand adult literacy classes to enhance level of education of farmers and hence adoption of technology. The results also showed that the cost of the selected technology was the biggest predictor of changes in odds ratios and also had high marginal effects. The government should therefore introduce cost sharing programmes on AI services; employ more extension personnel and improve their mobility through provision of means of transport so as to enhance access to information by farmers. It is also recommended that land fragmentation be discouraged. Policies geared at improving education system, empowering women, strengthening extension services, appropriate land policy reforms and providing financial support to farmers will help a lot in promoting adoption of breeding dairy technologies in the North Rift region.

Keywords

North Rift region, Dairy Farmers, breeding technology, Innovations, Household, Adoption, Food security, livestock productivity. 

References

i.            Abadi Ghadim, K. A., and D. J. Pannell (1999). “A Conceptual Framework of Adoption of an Agricultural Technology.” Agricultural Economics 21 (1999): 145-154.

ii.            Abara, I. O. C. and S. Singh (1993). “Ethics and Biases in Technology Adoption: The Small Farm Argument.” Technological Forecasting and Social Change. 43 (1993): 289-300.

iii.            Adesina, A. A., Zinnah, M. M. (1993): Technology Characteristics, Farmers Perceptions and Adoption Decisions: A Tobit Model Application in Sierra Leone, Agricultural Economics 9: 297-311.

iv.            Adesina, A.A. and J. Baidu-Forson (1995). “Farmers’ Perceptions and Adoption of New Agricultural Technology: Evidence From Analysis in Burkina Faso and Guinea, West Africa.” Journal of Agricultural Economics. 13 (1995):1-9.

v.            Allison, Paul D. (1991). Logistic Regression using the SAS System: Theory and Application. Cary,   NC: SAS Institute.

vi.            Alston, J.M., G.W. Norton and P.G. Pardey (1995). Science under Scarcity: Principles and Practice of Agricultural Research Evaluation and Priority Setting. Ithaca: Cornell University

vii.            Amusala G (2012): Awareness and Adoption of Stress Tolerant Maize and Sorghum Cultivars in Western Kenya, MSc. Thesis: Moi University.

viii.            Baidu-Forson, J. (1999): “ Factors Influencing Adoption of Land-enhancing Technology in the Sahel: Lessons From a Case Study in Niger.” Journal of Agricultural Economics. 231-239.

ix.            Benin S, Pender J and Ehui S (2003). Policies for sustainable land management in the East African highlands. Socioeconomics and Policy Research Working Paper 50. International Livestock Research Institute (ILRI), Nairobi, Kenya: 90-95.

x.            Bonabana-Wabbi Jackline (2002) “Assessing Factors affecting Adoption of Agricultural: The Case of Integrated Pest Management (IPM) in Kumi District, Eastern Uganda”.      Unpublished Thesis Presented to Virginia State University; USA.

xi.            Cameron, A. Colin, and Pravin Trivedi K. (2005) Microeconometrics: Methods and Applications. New York: Cambridge University Press.

 xii.    Cameron, A. Colin, and Trivedi, K. Pravin (2009) Microeconometrics Using Stata. TX Stata   Press.

xiii.            Cameron, L.A. (1999): “The Importance of Learning in the adoption of High-Yielding Variety Seeds.” American Journal of Agricultural Economics. 83-94.

xiv.            Caswell, M., K.S. Jans and C. Kascak (2001). Adoption of Agricultural production practices: Lessons learned from the US. Department of Agriculture area studies project. Washington DC. US Department of Agriculture. Resource

xv.            Conelly W.T. (1998): Colonial Era Livestock Development Policy: Introduction to Improved

    i.            Dairy Cattle in High Potential Farming Areas of Kenya. World Development 26(9): 1733-1748.

xvi.            Cortina, J. M. (1993): “What is Coefficient Alpha? An Examination of Theory and Applications,” Journal of Applied Psychology, 78(1), 98–104.

xvii.            Cronbach, L. J. (1951): Coefficient alpha and the internal structure of tests. Psychometrika 16:      297 - 334.Dairy Cattle in Western Kenya; USAID.

xviii.            Dey J. (1981): Gambian Women: Unequal Partners in Rice Development projects. Journal of Development studies, 17; 109-122.

xix.            DFID Kenya, (2001): The Kenya Dairy Sub-sector. A study for DFID Kenya Ebony Consulting International. September, 2001. Draft Report for DFID Kenya.

xx.            DLPO, (2009); Region Livestock Production Office Annual Reports (2005-2008). MOA, Uasin Gishu  District.

xxi.            Dorfman, J. H. (1996): “Modeling Multiple Adoption Decisions in a Joint Framework.” American Journal of Agricultural Economics 78, 3 (1996): 547-557.

xxii.            Doss, C.R and M.L Morris (2001): “How Does Gender Affect the Adoption of Agricultural Innovation? The Case of Improved Maize Technologies in Ghana.” Journal of Agricultural Economics. 2527-39.

xxiii.            El-Osta, H.S and M.J. Morehart (1999): “Technology Adoption Decisions in Dairy Production and the Role of Herd Expansion.” Agricultural and Resource Economics Review. 28 84-95.

xxiv.            Enos, J.L and W.H Park. (1988): The Adoption of Imported Technology: The Case of Korea. New York: Croom Ltd,.

xxv.            FAO (1996): World Food Summit: Food Security situation and issues in the Africa region. Ouagadougou, Burkina Faso, 16-20. (Print)

xxvi.            FAO, (2008): Dairy Development in Kenya; Nairobi; ILRI/FAO.

xxvii.            FAO, (2010): Dairy Development in Kenya; Nairobi; ILRI/FAO.

 xxviii.            FAO, (2011): Dairy Development in Kenya; Nairobi; ILRI/FAO.

xxix.            Feder GR, Just RE and Zilberman D (1985): Adoption of agricultural innovation in developing     countries: A survey. Econ Dev. and Cult. Change 33: 255-298.

xxx.            Feder, G. and R. Slade(1984): “The acquisition of information and the adoption of new Technology.” American Journal of Agricultural Economics. American Agricultural Economics Association.

xxxi.            Feder, G., E. R. Just and D. Zilberman. (2001): “Adoption of Agricultural Innovations in Developing Countries: A Survey.” Economic Development and Cultural Change. 33 (1985):255-298. Gabre-Madhin, E.Z. and S. Haggblade. Success in African Agriculture: Results of an Expert Survey. International Food Policy Research Institute. Washington DC.

xxxii.            Fernandez-Cornejo, J. (1998): “Environmental and Economic Consequences of Technology Adoption: IPM in Viticulture.” Agricultural Economics, 18 (1998): 145-155.

xxxiii.            Franzel, S. and Wambugu (2007): The Uptake of Fodder Shrubs among Smallholders in East Africa: Key Elements that Facilitate Wide Spread Adoption. Hare, MD and Wong Pichet, K(eds): 203-222.

xxxiv.            Gabre-Madhin, E.Z. and S. Haggblade June (2001): Success in African Agriculture: Results of an Expert Survey. International Food Policy Research Institute. Washington DC.

xxxv.            GOK (1994): Assessing economic impacts of East Coast Fever Immunization: A case study in Coast Province, Kenya. Veterinary Records (in press).

xxxvi.            GOK (2001): National Development Plan 1999-2004, Nairobi: Government Printers. Nairobi, Kenya

xxxvii.            GOK (2002): Official Journal of the Agricultural Society of Kenya Constrains and Possible Solutions to Dairy Industry in Kenya.

xxxviii.            GOK (2005): National Development Plan 2005-2007, Nairobi: Government Printers.

xxxix.            GOK (2006-2009): Office of the Vice President and Ministry of Planning and National Development. Nairobi: government Printers. -(2002-2005) Uasin Gishu District Development Plan. Nairobi: Government Printers.

xl.            GOK (2010): District Annual Report; Uasin Gishu, Nairobi; Government Printers.

xli.            GOK (2012): Kenya National Dairy Master Plan; Nairobi; Government Printers.

xlii.            Green, D.A.G., and D.H. Ng’onyala (1993): “Factors Affecting Fertilizer Adoption in Less Developed Countries: An Application of Multivariate Logistic Analysis in Malawi.” Journal of Agricultural Economics.

xliii.  Greene, William H. (1996): Marginal Effects in the Bivariate Probit Model Stern School of  Business, New York University.

xliv.  Greene, William H. (2003) Econometric Analysis, Fifth Edition Upper Saddle River, NJ:    Prentice Hall.

xlv.  Greene, William H. (2007): LIMDEP Version 9.0 Econometric Modeling Guide. Plainview, New York: Econometric Software.

xlvi.            Greene, W. H. (2008): Econometrics Analysis Sixth Edition Pearson Prentice Hall Upper Saddle  River New Jersey New York USA: Chapter 21 P 663-756.

xlvii.            Gujarati, D. N. (2007): Basic Econometrics. Tata McGraw-Hill Edition New Delhi, India: Chapter 18, 21 and 22.

xlviii.            Harper, J. K., M. E. Rister, J. W. Mjelde, B. M. Drees, and M. O. Way. (1990): “Factors influencing the adoption of insect management technology.” American Journal of Agricultural Economics. 72(4) 997-1005.

xlix.            Henson, R. (2001): “Understanding Internal Consistency Reliability Estimates: A Conceptual        Primer on Coefficient Alpha,” Measurement and Evaluation in Counseling and            Development, 34(1), 177–189.

l.            Homewood, K., P. Trench, S. Randall, G. Lynen and B. Bishop (2006). Livestock Health and Socio-economic Impacts of Veterinary Intervention in Maasailand: Infection-and-Treatment Vaccine against East Coast Fever. Agricultural Systems 89(2-3): 248-271.

li.            IFPRI & ILRI (2007): Dairy Cattle in Western Kenya; USAID.

lii.            IFPRI, (1998): International Food Policy Research Institute. Pest Management and Food Production: Looking into the future, Vol. 20, no. 52.

liii.            ILRAD, (1991). Annual Scientific Report 1991. International Laboratory for Research on Animal Diseases. Nairobi, Kenya.

liv.            ILRAD, (1997). Immunization against ECF Report on a workshop on collection, handling and analysis of performance and productivity held in Nairobi, Kenya. 23-25th Sept. 1996 (ed) Irvin A.D.

lv.            Irungu, P, Mbogoh, SG, Staal, SG and Njubi, D (1998). Factors influencing the adoption of Napier  grass in smallholder dairying in the highlands of Kenya. Proceedings of a   BSAS/KARI/APSK/ILRI international conference held at KARI conference centre,      Nairobi, Kenya, 27-30 January 1998.

lvi.            Jera, R and Ajayi, OC (2008). Logistic modeling of smallholder livestock farmers’ adoption of tree-based fodder technology. Agrekon, 47: 379-382.

lvii.            Kaiser, H. (1974): “An Index of Factor Simplicity. Psychometrika” 39: 31 – 36.

lviii.            Kathuri, Nephat J. & Pals, Douglas A. (1993): Introduction to Educational Research Egerton Education Book Series, Njoro, Kenya; Egerton University.

lix.            Kebede, Y., K. Gunjal, (1990): “Adoption of New Technologies in Ethiopian Agriculture: The case of Tegulet-Bulga District, Shoa Province.” Journal of Agricultural Economics.

lx.            Khanna, M. (2001): “Sequential Adoption of Site-Specific Technologies and its Implications for Nitrogen Productivity: A Double Selectivity Model.” American Journal of Agricultural Economics. 83(1)

lxi.            Kipkemei, E (2001): The contribution of Secondary School Agricultural Knowledge on Crop &

    i.            Livestock Production: The case of small scale farmers in Uasin Gishu District.

  ii.            MSc. Thesis: Egerton University.

lxii.            Kodhek, A.G. (1999): Report on revitalizing the dairy industry in Kenya. Nairobi: Tegemeo Institute.

lxiii.            Kothari, C. R. (1990): Research Methodology: Methods in Technique, Second, New Delhi: Wisely Eastern.

lxiv.            Koutsoyiannis, A. (1993): Theory of Econometrics Second Edition ELBS with Macmillan UK.

lxv.            Leisinger, K.M. (1996): Sociopolitical Effects of new Biotechnologies in Developing countries. IFPRI.2020 Vision Brief

lxvi.            Lionberger, H.F. (1960.): Adoption of New Ideas and Practices. Iowa State: University Press.

lxvii.    Long, J. Scott (1997) Regression Models for Categorical and Limited Dependent Variables: Advanced Quantitative Techniques in the Social Sciences Sage Publications.

lxviii.     Long, J. Scott, and Jeremy Freese (2003): Regression Models for Categorical Dependent   Variables Using Stata, 2nd ed. College Station, TX: Stata Press.

lxix.            Long, J. S., and J. Freese (2006): Regression Models for Categorical Dependent Variables Using Stata. 2nd ed. College Station, TX: Stata Press.

lxx.            Lowenberg-DeBoer, J. (2000): “Comments on Site-Specific Crop Management: Adoption Patterns and Incentives.” Review of Agricultural Economics. 22(1).

lxxi.            Lwayo (2000): Factors Influencing Adoption of Farm Forestry in Busia District of Kenya; Msc. Thesis.

lxxii.            Maddala G. S. (2002): Introduction to Econometrics Third Edition John Willey and Sons    New     York: USA Chapter 8 P 318, 322-9 and 331-2.

lxxiii.            Maddala, G. S. (1983). Limited Dependent and Qualitative Variables in Econometrics New           York:             Cambridge University Press.

lxxiv.            McCalla, A.F. (1999): “Prospects for Food Security in the 21st Century: with special Emphasis on Africa.” Journal of Agricultural Economics. 20(1)

lxxv.            Mekonnen H, Dehninet G and Kelay B (2009). Dairy technology adoption in smallholder farm in Dejen district, Ethiopia. Tropical Animal Health and Production.

 lxxvi.    Metz T, Kiptarus J and Muma M (1995). Diffusion of dairy technologies in six districts of    Kenya: A survey of smallholder dairy farmers in Kakamega, Uasin Gishu, Nandi,          Kiambu, Nakura, and Nyeri districts. Monitoring and Evaluation Unit, National Dairy       Development Project, Ministry of Agriculture, Livestock Development and Marketing, Nairobi, Kenya.

lxxvii.    Misra, D.C. (1990): “Defining Agricultural Extension for 1990’s”. Directorate of Extension

a.      Occasional Paper. Dinesh Chandra Misra Ministry of Agriculture, New Delhi.

lxxviii.  Mohamed A. M, Ahmed S E and Yemesrach A (2004). Dairy development in Ethiopia. EPTD.

lxxix.  Mohi A K and Bhatti J S (2006). Constrained encountered by dairy farmers in adoption of improved dairy farming practices. J Dairying and H.S. 25: 47-50.

lxxx.            Mose J. (2013): An Economic Analysis of Trypanosomiasis Control Methods in Smallholder Cattle Farms in Busia County; Ph.D Thesis; Moi University.

lxxxi.            Mugisa-Mutetikka, M. (2000): “Logistic Regression Analysis of Adoption of New Bean Varieties in Uganda.” Unpublished.

lxxxii.            Mukhebi, A. and B. Perry (1993): “Economic Implications of the Control of East Coast Fever in Eastern, Central and Southern Africa, ILRI (aka ILCA and ILRAD).

lxxxiii.            Muriuki H. (1993): “Kenya National Dairy Development Project, ILRI (aka ILCA and ILRAD).

lxxxiv.            Muriuki, H, A. Omore, N. Hooton, M. Waitaka, R, Ouma, S. Staal and P. Odhiambo (2003): The Policy Environment in the Kenya Dairy Sub-sector. A Review, SDP Research and Development Report.

lxxxv.            Mwangi, John Gowland (1999): Policy Milestones in Kenya that have Supported or Constrained Sustainable Agriculture and Poverty Alleviation 1890 – 1999. A Research Report Prepared for the Director, Tegemeo Institute, Nairobi, Kenya.

lxxxvi.            Nicholson CF, Thornton PK, Mohammed L, Muinga RW, Mwamachi DM, Elbasha EH, Staal SJ and Thorpe W (1999). Smallholder dairy technology in coastal Kenya: An adoption and            impact study. ILRI Impact Assessment Series 5, International Livestock Research           Institute, P.O. Box 30709, Nairobi, Kenya.

lxxxvii.            Nkonya, E., T. Schroeder, and D. Norman. (1997): “Factors Affecting Adoption of Improved Maize Seed and Fertilizer in Northern Tanzania.” Journal of Agricultural Economics. 48 No. 1 (1997):1-12

lxxxviii.            Nowak, P. (1987). The Adoption of Agricultural Conservation Technologies: Economic and Diffusion Explanations.” Rural Sociology. 52(2) (1987): 208-220.

lxxxix.            Nowak, P. (1996): “Practical Considerations in Assessing Barriers to IPM Adoption.” Proceedings of the Third National IPM Symposium/Workshop. (Eds.) S.

xc.            Odulaja, A. and F.G Kiros (1996):  “Modeling Agricultural Production on Small-scale Farmers in Sub-Saharan Africa: A Case Study in Western Kenya.” Journal of Agricultural economics.

xci.            Oerke, E. C., H.W Dehne., F. Schoenbeck and A. Weber. (1994): Crop Production and Crop Protection: Estimated Losses in Major Food and Cash Crops. Amsterdam, The Netherlands: Elsevier.

xcii.            Ouma, R., L.Njoroge, D, Romney, P. Ochungo, S. Staal and I Baltenweck (2007). Targeting Dairy Interventions in kenya. A Guide for Development Planners, Researchers and Extension Workers.

xciii.            Overfield, D. and E. Fleming (2001): “A Note on the Influence of Gender Relations on the Technical Efficiency of Smallholder Coffee Production in Papua New Guinea.” Manuscript. Journal of Agricultural Economics.

xciv.            Park, Hun Myoung. (2004): "Presenting the Binary Logit/Probit Models Using the SAS/IML." Proceedings of the 15th Midwest SAS Users Group Conference in Chicago, IL        (September 26-28, 2004).

xcv.            Peterson, B., and F. E. Harrell, Jr. (1990): Partial proportional odds models for ordinal response   variables Applied Statistics 39: 205–217.

xcvi.            Pindyck, R. S. and D. L. Rubinfeld (1998): Econometrics Models and Economic     Forecasts,        Fourth Edition McGraw-Hill International Editions New York,         USA P Chapter 11 P   307-317 and P 319-323.

xcvii.            Quddus MA (2010): Constraints of native cattle genetic resource conservation and features of breeding system in representative areas of Bangladesh. J. Bang. Agric. Univ.             8: 113-120.

xcviii.            Quddus M. A. (2012) “Adoption of Dairy Technologies by Small Farm Holders: Practices and Constraints”, Bangladesh Journal of Animal Science.

xcix.            Rege, (1998); Utilization of exotic ger-plasm for milk production in the tropics. Proc. 6th World Congr. Genet. Appl. Livest.prod.25:193-2000.

c.            Rege J. (2001): Zebu Cattle of Kenya. Uses, Performance, Farmer Preference Measures of Genetic Diversity and Options for Improved use: ILRI Caka ILCA and ILRAD.

ci.            Reynolds L, Metz T and Kipatarus J (1996): Smallholder dairy production in Kenya. World  Animal Review 87-1996/2, http:/www.fao.org/docrop/W2650T/w2650t00.

cii.            Rogers, E.M. (1983): Diffusion of Innovations. 3rd  Edition. New York: The Free Press.

ciii.            Rogers, E.M. (1995): Diffusion of Innovations. 4th Edition. New York: The Free Press.

civ.            Saunders M, Lewis P & Thornhill, A (2007): Research Methods for Business Students

cv.            Schultz T.P (1981): Economics of Population Reading, MA: Addison – Wesley.

cvi.            Shakya, P. B. and J. C. Flinn (1985): “Adoption of Modern Varieties and Fertilizer Use on Rice in the Eastern Tarai of Nepal.” Journal of Agricultural Economics.

cvii.            Staal S.C. Degaldo and C. Nicholson (1997): Smallholder Dairying under Transaction Costs in

    i.            East Africa, World Development 25(5): 779-794.

 cviii.            Staal SJ, Baltenweck I, Waithaka MN, deWolff T and Njoroge L (2002). Location and uptake:  integrated household and GIS analysis of technology adoption and land use, with         application to smallholder dairy farmers in Kenya. J. Agric. Econ. 27: 295-315.

cix.            Staal, S. (1998);Dairy Systems Characterization of the Nairobi Milk Shed: Application of Spatial and Household analysis. MOA/KARI/ILRI Collaborative Research Report, Small holder Dairy (R&D) Project, Nairobi, Kenya.

cx.            Staal, S. (1999); The Kenya Dairy Sub-sector. A Rapid Appraisal. Smallholder Dairy (Research and Devt). Project Report. 51p.

cxi.            Stata Press (2007). Stata Base Reference Manual, Release 10. College Station, Texas         Corporation TX: Stata Press.

cxii.            Stata Corp, (2013) Stata Release 13. Statistical Software.  College Station, TX: StataCorp Stata             Multivariate Statistics Reference Manual TX: Stata Press.

cxiii.            Tegemeo (2002): The Dairy Industry in Kenya: The Post-Liberalization Agenda. Paper Presented at the Dairy stakeholders’ workshop Norfolk Hotel, Nairobi 27th August 2002. Ed. By A. M. Karanja.

cxiv.            Thorpe, W. (1998): Dairy Cooperatives and policy Reforms in Kenya: Effects of Livestock Service and milk market liberalization. Food Policy. 23:173-185. Uasin Gishu District. Msc.Thesis: Egerton University

cxv.            Tjornhom, J.D. (1995): “Assessment of Policies and Socio-Economic Factors Affecting Pesticide

a.      Use in the Philippines”. MS. Thesis, Virginia Polytechnic Institute and State University.

 cxvi.            Uddin MM, Sultana MN, Ndambi OA, Hemme T and Peters KJ (2010). A farm economic analysis in different dairy production systems in Bangladesh. Livestock Research for       Rural Development. 22: 122.

a.      USA.

cxvii.            United Nations, Food and Agriculture Organization, Rome (1997). The State of Food and

a.      Agriculture.

 cxviii.            Waitaka, M.A. Wokabi J. Nyanyaga E. Ouma, J. Biwott, S Staal, M. Ojowi, R. Ogidi I, Njarro and PMudavadi (2000): A Participatory Rapid Appraisal (Pra) of Farming Systems in Western Kenya. Report of a PRA on dairy and crop activities in Western Kenya January to February 5th.

cxix.            Waller, B.E. (1998): “Matching Innovations with Potential Users: A Case Study of Potato IPM practices.” Agriculture, Ecosystems and Environment.

cxx.            Wolfe, R., and Gould W. (1998): SAGE 76: An approximate likelihood-ratio test for ordinal           response models. Stata Technical Bulletin 42: 24–27. In Stata Technical Bulletin        Reprints, vol. 7, 199–204 College Station, Texas TX: Stata Press.

cxxi.            Wu, J., and B.A. Babcock. (1998): “The Choice of Tillage, Rotation and Soil Testing Practices: Economic and Environmental Implications.” American Journal of Agricultural Economics.

cxxii.            Yamano Takeshi (2009): Lecture Notes on Advanced Econometrics, PhD Second Year Notes         University of Indiana, USA.

cxxiii.            Yaron, D., Dinar and H. Voet (1992): “Innovations on Family Farms: The Nazareth Region in     Israel.” American Journal of Agricultural Economics. American Agricultural Economics    Association. (1992): 361-370.

Cite this Article: