Adoption and Impact of Modern Rice Varieties on Poverty in Eastern India
Received date: 2018-08-05
Accepted date: 2018-12-09
Online published: 2019-09-30
The factors affecting the adoption of modern varieties (MVs) of rice and impact on poverty in Odisha, India were discussed. A total of 363 households from Cuttack and Sambalpur districts of Odisha via multistage sampling technique participated in the survey. The Cragg’s Double hurdle model was used to model the determinants of adoption and intensity of adoption of MVs of rice, and the propensity score matching was used to analyze the impact of adoption on poverty. The results showed that age, education, risk aversion, land size, yield, perception of MVs as high yielding, resistant to diseases and availability of MVs positively influenced the decision to adopt. However, variables such as household size, experience of a farmer, off-farm job participation, amount of credit received, cost of seeds, insecticides and fertilizers negatively influenced the adoption of MVs. Intensity of adoption of MVs was negatively influenced by experience of a farmer, cost of fertilizer and marketability of MVs, and positively affected by household size, risk aversion, land size, cost of insecticides, perception of MVs as high yielding and availability of MV seeds. Poverty incidence, gap and severity were high among non-adopters to adopters of MVs. After matching adopters and non-adopters of MV groups using four different algorithms of nearest neighbour matching, stratification matching, radius matching and kernel matching, the impact of MV adoption resulted in higher per capita monthly household expenditure by about US$ 52.82 to US$ 63.17.
Key words： rice; adoption; poverty; Cragg’s Double hurdle model; modern variety
Kwasi Bannor Richard, Amarnath Krishna Kumar Gupta, Oppong-Kyeremeh Helena, Abawiera Wongnaa Camillus . Adoption and Impact of Modern Rice Varieties on Poverty in Eastern India[J]. Rice Science, 2020 , 27(1) : 56 -66 . DOI: 10.1016/j.rsci.2019.12.006
| [1] | Abadie A, Drukker D, Herr J L, Imbens G W.2004. Implementing matching estimators for average treatment effects in Stata.Stat J, 4: 290-311. |
| [2] | Abdulai A N.2016. Impact of conservation agriculture technology on household welfare in Zambia.Agric Econ, 47(6): 729-741. |
| [3] | Afolami C A, Obayelu A E, Vaughan I I.2015. Welfare impact of adoption of improved cassava varieties by rural households in south western Nigeria.Agric Food Econ, 3(18): 2-17. |
| [4] | Ainembabazi J H, Mugisha J.2014. The role of farming experience on the adoption of agricultural technologies: Evidence from smallholder farmers in Uganda.J Devel Stud, 50(5): 666-679. |
| [5] | Amankwah A, Quagrainie K K, Preckel P V.2016. Demand for improved fish feed in the presence of a subsidy: A double hurdle application in Kenya.Agric Econ, 47(6): 633-643. |
| [6] | Asante B O, Villano R A, Patrick I W, Battese G E.2018. Determinants of farm diversification in integrated crop-livestock farming systems in Ghana.Renew Agric Food Syst, 33(2): 131-149. |
| [7] | Bannor R K, Oppong-Kyeremeh H.2018. Extent of poverty and inequality among households in the techiman municipality of brong ahafo region, Ghana.J Energy Nat Res Manag, 1: 26-36. |
| [8] | Barrett C B, Carter M R, Timmer C P.2010. A century-long perspective on agricultural development.Am J Agric Econom, 92(2): 447-468. |
| [9] | Becerril J, Abdulai A.2010. The impact of improved maize varieties on poverty in Mexico: A propensity score-matching approach.World Devel, 38(7): 1024-1035. |
| [10] | Bezu S, Kassie G T, Shiferaw B, Ricker-Gilbert J.2014. Impact of improved maize adoption on welfare of farm households in Malawi: A panel data analysis.World Devel, 59: 120-131. |
| [11] | Boucher S R, Carter M R, Guirkinger C.2008. Risk rationing and wealth effects in credit markets: Theory and implications for agricultural development.Am J Agric Econ, 90(2): 409-423. |
| [12] | Carter M R, Cheng L, Sarris A.2016. Where and how index insurance can boost the adoption of improved agricultural technologies.J Devel Econ, 118: 59-71. |
| [13] | Chandio A A, Jiang Y S.2018. Determinants of adoption of improved rice varieties in northern Sindh, Pakistan.Rice Sci, 25(2): 103-110. |
| [14] | Cragg J G.1971. Some statistical models for limited dependent variables with application to the demand for durable goods.Economatrica, 39(5): 829-844. |
| [15] | Dar M H, Chakravorty R, Waza S A, Sharma M, Zaidi N W, Singh A N, Singh U S, Ismail A M.2017. Transforming rice cultivation in flood prone coastal Odisha to ensure food and economic security.Food Secur, 9(4): 711-722. |
| [16] | Davis K, Nkonya E.2008. Developing a methodology for assessing the impact of farmer field schools in East Africa. In: Proceedings of the 24th Annual Meeting of the Association for International Agricultural and Extension Education (AIAEE). Costa Rica: EARTH University: 93-99. |
| [17] | Garcıa B.2013. Implementation of a double-hurdle model.Stat J, 13(4): 776-794. |
| [18] | Ghimire R, Huang W C.2015. Household wealth and adoption of improved maize varieties in Nepal: A double-hurdle approach.Food Secur, 7(6): 1321-1335. |
| [19] | Ghimire S, Mehar M, Mittal S.2012. Influence of sources of seed on varietal adoption behaviour of wheat farmers in Indo-Gangetic Plains of India.Agric Econ Res Rev, 25: 399-408. |
| [20] | Goswami B, Ziauddin G, Datta S N.2016. Adoption behaviour of fish farmers in relation to scientific fish culture practices in West Bengal.Ind Res J Ext Educ, 10(1): 24-28. |
| [21] | Government of Odisha.2014. District Level Poverty Estimation for Odisha by using Small Area Estimation Technique. Bhubaneswar, India: Directorate of Economics and Statistics, Planning and Convergence Department. |
| [22] | Government of Odisha. 2018. Odisha Economic Survey 2017-2018. Cuttack, India: Odisha Government Press. |
| [23] | Greene J C.2007. Mixed Methods in Social Inquiry. New Jersey, USA: John Wiley & Sons. |
| [24] | Greene W H, Hensher D A.2010. Modeling Ordered Choices: A Primer. Cambridge, UK: Cambridge University Press. |
| [25] | Janaiah A, Hossain M, Otsuka K.2006. Productivity impact of the modern varieties of rice in India.Devel Econ, 44(2): 190-207. |
| [26] | Jena P R, Grote U.2012. Impact evaluation of traditional Basmati rice cultivation in Uttarakhand State of Northern India: What implications does it hold for geographical indications?World Develop, 40(9): 1895-1907. |
| [27] | Jimenez-Soto E V, Brown R P C.2012. Assessing the poverty impacts of migrants’ remittances using propensity score matching: The case of Tonga.Econ Record, 88: 425-439. |
| [28] | Kassie M, Shiferaw B, Muricho G.2010. Adoption and impact of improved groundnut varieties on rural poverty: Evidence from rural Uganda. Environment for Development Discussion Paper-Resources for the Future (RFF): 10-11. |
| [29] | Katchova A L, Miranda M J.2004. Two-step econometric estimation of farm characteristics affecting marketing contract decisions.Am J Agric Econ, 86(1): 88-102. |
| [30] | Khandker S R, Koolwal G B, Samad H A.2010. Handbook on Impact Evaluation: Quantitative Methods and Practices. Washington, USA: World Bank. |
| [31] | Khonje M, Manda J, Alene A D, Kassie M.2015. Analysis of adoption and impacts of improved maize varieties in eastern Zambia.World Devel, 66: 695-706. |
| [32] | Luan D X, Bauer S, Anh N T L.2015. Poverty targeting and income impact of subsidised credit on accessed households in the Northern Mountainous Region of Vietnam.J Agric Rural Dev Trop Sub, 116(2): 173-186. |
| [33] | Mada M, Bannor R K.2015. Poverty situation among small-scale apple producers: The case of Chencha District in Ethiopia.J Int Acad Res Multidis, 3(2): 212-220. |
| [34] | Marenya P P, Barrett C B.2007. Household-level determinants of adoption of improved natural resources management practices among smallholder farmers in western Kenya.Food Policy, 32(4): 515-536. |
| [35] | Mariano M J, Villano R, Fleming E.2012. Factors influencing farmers’ adoption of modern rice technologies and good management practices in the Philippines.Agric Syst, 110: 41-53. |
| [36] | Marothia D, Martin W, Janaiah A, Dadhich C L.2016. Front Matter-Re-Visiting Agricultural Policies in the Light of Globalisation Experience: The Indian Context. Indian Society of Agricultural Economics (IAAE). International Association of Agricultural Economists (ISAE) Inter-Conference, Hyderabad, India. October 12-14, 2014. |
| [37] | Martey E, Wiredu A N, Etwire P M, Fosu M, Buah S S J, Bidzakin J, Ahiabor B D K, Kusi F.2014. Fertilizer adoption and use intensity among smallholder farmers in Northern Ghana: A case study of the AGRA Soil Health Project.Sust Agric Res, 3(1): 24-36. |
| [38] | Matuschke I, Mishra R R, Qaim M.2007. Adoption and impact of hybrid wheat in India.World Devel, 35(8): 1422-1435. |
| [39] | Mohapatra T.2014. Technologies to enhance rice productivity and nutritional security in eastern India (Souvenir-Eastern Zone Regional Agriculture Fair 2013-14). Cuttack, Odisha, India: Central Rice Research Institute, ICAR. |
| [40] | Muthini D N, Nyikal R A, Otieno D J.2017. Determinants of small-scale mango farmers market channel choices in Kenya: An application of the two-step Craggs estimation procedure.J Devel Agric Econ, 9(5): 111-120. |
| [41] | Paltasingh K R.2018. Land tenure security and adoption of modern rice technology in Odisha, Eastern India: Revisiting Besley’s hypothesis.Land Use Policy, 78: 236-244. |
| [42] | Paltasingh K R, Goyari P, Tochkov K.2017. Rice ecosystems and adoption of modern rice varieties in Odisha, east India: Intensity, determinants and policy implications. J Devel Areas, 51(3): 197-213. |
| [43] | Rahm M R, Huffman W E.1984. The adoption of reduced tillage: The role of human capital and other variables.Am J Agric Econ, 66(4): 405-413. |
| [44] | Rath N C, Das L, Mishra S K, Lenka S.2007. Adoption of upland rice technologies and its correlates.ORYZA: An Int J Rice, 44(4): 347-350. |
| [45] | Samal P, Pandey S.2005. Climatic risks, rice production losses and risk coping strategies: A case study of a rainfed village in coastal Orissa.Agric Econ Res Rev, 18: 61-72. |
| [46] | Samal P, Barah B C, Pandey S.2006. An analysis of rural livelihood systems in rainfed rice-based farming systems of coastal Orissa.Agric Econ Res Rev, 19(2): 281-292. |
| [47] | Samal P, Pandey S, Kumar G A K, Barah B C.2011. Rice ecosystems and factors affecting varietal adoption in rainfed coastal Orissa: A multivariate probit analysis.Agric Econ Res Rev, 24: 161-167. |
| [48] | Sarangi S K, Maji B, Singh S, Sharma D K, Burman D, Mandal S, Singh U S, Ismail A M, Haefele S M.2016. Using improved variety and management enhances rice productivity in stagnant flood-affected tropical coastal zones.Field Crops Res, 190: 70-81. |
| [49] | Seymour G, Doss C, Marenya P, Meinzen-Dick R, Passarelli S.2016. Women’s empowerment and the adoption of improved maize varieties: Evidence from Ethiopia, Kenya, and Tanzania. In: 2016 Agricultural & Applied Economics Annual Meeting. July 31 to August 2, 2016. Boston, USA. |
| [50] | Singh R P, Kumar A, Pal S K.2016. The prevalence, productivity, and protection of traditional varieties vis-à-vis modern varieties in eastern India: An appraisal.Jharkh J Devel Manag Stud, 14(2): 6955-6970. |
| [51] | Tanellari E, Kostandini G, Bonabana-Wabbi J, Murray A.2014. Gender impacts on adoption of new technologies: The case of improved groundnut varieties in Uganda.Afr J Agric Res Econ, 9(4): 300-308. |
| [52] | Udry C.2010. The economics of agriculture in Africa: Notes toward a research program.Afr J Agric Res Econ, 5(1): 284-299. |
| [53] | Verkaart S, Munyua B G, Mausch K, Michler J D.2017. Welfare impacts of improved chickpea adoption: A pathway for rural development in Ethiopia.Food Policy, 66: 50-61. |
| [54] | Wason M, Padaria R N, Singh B, Kumar A.2009. Farmers perception and propensity for adoption of integrated pest management practices in vegetable cultivation.Ind J Ext Educ, 45(3/4): 21-25. |
| [55] | Wongnaa C A, Awunyo-Vitor D, Bakang J E A.2018. Factors affecting adoption of maize production technologies in Ghana: A study in Ghana.J Agric Sci (Sri Lanka), 13(1): 81-99. |
| [56] | Wozniak G D.1987. Human capital, information, and the early adoption of new technology.J Human Res, 22(1): 101-112. |
/
| 〈 |
|
〉 |