Impact of direct seeded rice technology adoption on farm income in Punjab
472 / 350
Keywords:
Adoption, Direct seeded rice, Impact, Propensity score matchingAbstract
The study isolates the impact of DSR technology on farm household well-beings in the state of Punjab using PSM technique on data pertaining to 2017-18. The results conclude that adopters of DSR technology have reduced their labor cost, and irrigation cost significantly, besides a marginal improvement in yield of paddy. The cost cutting on inputs and a slight improvement in yield due to this technology yielded a higher net income of about Rs. 8100/ ha compared to non adopters.Downloads
References
Baser O. 2006. Too much ado about propensity score models? Comparing methods of propensity score matching, Value in Health. 9(6): 377–85. DOI: https://doi.org/10.1111/j.1524-4733.2006.00130.x
Becerril J and Abdulai A. 2010. The impact of improved maize varieties on poverty in Mexico: A propensity score-matching approach, World Development 38(7): 1024–35. DOI: https://doi.org/10.1016/j.worlddev.2009.11.017
Caliendo M and Kopeinig S. 2008. Some practical guidance for the implementation of propensity score matching, Journal of Economic Surveys 22(1): 31–72. DOI: https://doi.org/10.1111/j.1467-6419.2007.00527.x
Dehejia R H and Wahba S. 2002. Propensity scorematching methods for nonexperimental causal studies, Review of Economics and Statistics, 84(1): 151–61. DOI: https://doi.org/10.1162/003465302317331982
Farooq M, Siddique K H M, Rehman H, Aziz T, Lee D and Wahid A. 2011. Rice direct Sseeding: Experiences, challenges and opportunities, Soil and Tillage Research 111(2): 87–98. DOI: https://doi.org/10.1016/j.still.2010.10.008
Imbens G. 2004. Nonparametric estimation of average treatment effects under exogeneity: A review, The Review of Economics and Statistics 86: 4–29. DOI: https://doi.org/10.1162/003465304323023651
Kamboj B R, Kumar A, Bishnoi D K, Singla K, Kumar V, Jat M L, Chaudhary N, Jat H S, Gosain D K, Khippal A, Garg R, Lathwal O P, Goyal S P, Goyal N K, Yadav A, Malik D S, Mishra A and Bhatia R. 2012. Direct seeded rice technology in Western Indo-Gangetic Plains of India: CSISA Experiences. CSISA, IRRI and CIMMYT. 16 p.
Kaur S and Vatta K. 2015. Groundwater depletion in central Punjab: Pattern, access and adaptations, Current Science 108(4): 485–90.
Kumar V and Ladha J K. 2011. Direct seeding of rice: Recent developments and future research needs (Chapter 6). Advances in Agronomy, 111: 297–413. DOI: https://doi.org/10.1016/B978-0-12-387689-8.00001-1
Malabayabas A J, Templeton D and Singh P. 2012. Ex-ante impact of direct seeding of rice as an alternative to transplanting rice in the Indo-Gangetic Plain, Asian Journal of Agriculture and Development 9(2): 13–29.
Mendola M. 2007. Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh, Food Policy 32(3): 372–93. DOI: https://doi.org/10.1016/j.foodpol.2006.07.003
Mishra A K, Khanal A R and Pede V O. 2017. Is direct seeded rice a boon for economic performance? Empirical evidence from India, Food Policy 73: 10–8. DOI: https://doi.org/10.1016/j.foodpol.2017.08.021
MoAFW. 2019. Agricultural statistics at a glance 2018, Directorate of Economics and Statistics, Ministry of Agriculture and Farmers Welfare, Government of India.
Rosenbaum P R and Rubin D B. 1983. The central role of the propensity score in observational studies for causal effects, Biometrica 701: 41–55. DOI: https://doi.org/10.1093/biomet/70.1.41
Rosenbaum P R and Rubin D B. 1985. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician 39: 33–8. DOI: https://doi.org/10.1080/00031305.1985.10479383
Sahu S K and Das S. 2016. Impact of agricultural related technology adoption on poverty: A study of select households in rural India. (In) Siddharthan N and Narayanan K (Eds). Technology, India Studies in Business and Economics. Springer, Singapore. DOI: https://doi.org/10.1007/978-981-10-1684-4_8
Sha W, Chen F and Mishra A K. 2019. Adoption of direct seeded rice, land use and enterprise income: Evidence from Chinese Rice Producers, Land Use Policy 83: 564–70. DOI: https://doi.org/10.1016/j.landusepol.2019.01.039
Sharma B R, Gulati A, Mohan G, Manchanda S, Ray I and Amarasinghe U. 2018. Water Productivity Mapping of Major Indian Crops, NABARD-ICRIER Report.
Wu H, Ding S, Pandey S and Tao D. 2010. Assessing the impact of agricultural technology adoption on farmers' well-being using propensity-score matching Analysis in Rural China, Asian Economic Journal 24(2): 141–60. DOI: https://doi.org/10.1111/j.1467-8381.2010.02033.x
Downloads
Submitted
Published
Issue
Section
License
Copyright (c) 2020 The Indian Journal of Agricultural Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright of the articles published in The Indian Journal of Agricultural Sciences is vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR.