Analyzing PM-KISAN fund utilization in Southern Indian agriculture
DOI:
https://doi.org/10.14719/pst.6068Keywords:
agricultural spending, farmer behaviour, financial assistance, PM KISAN programmeAbstract
This study investigates the factors influencing the spending patterns of farmers receiving financial assistance through the Pradhan Mantri Kisan Samman Nidhi (PM KISAN) program in five southern Indian states. Using a mixed-methods approach, the research collected data from 1900 PM KISAN beneficiaries across Tamil Nadu, Kerala, Andhra Pradesh, Telangana and Karnataka. The study employed factor analysis to identify key determinants of spending behaviour. Results reveal four primary factor groups: agricultural spending, repayment, social spending and household mandatory spending. The timing of fund disbursement coinciding with agricultural operations emerged as the most influential determinant, followed by farmers' interest in agriculture. Regional variations were observed, with Kerala and Tamil Nadu showing higher agricultural spending tendencies, while Andhra Pradesh and Telangana displayed stronger influences from financial pressures and social factors. The study also highlights the significant impact of socio-economic characteristics, such as farm size, education level and credit orientation, on spending decisions. These findings suggest that aligning fund disbursement with agricultural cycles enhances program efficacy. Policy recommendations include financial literacy programs and improved fund allocation strategies. The study contributes to a more nuanced understanding of the PM KISAN program's impact on rural livelihoods and agricultural productivity in southern India.
Downloads
References
Singh RP, Prakash J, Singh AK. A study on structural changes in operational holding in india: an analytical approach. Agro Econ. 2021;8(2):141–51. https://doi.org/10.30954/2394-8159.02.2021.8
Akhtar J. The Impact of Pradhan Mantri Kisan Samman Nidhi Scheme on the Farm Income of Beneficiaries in Uttar Pradesh. Prayagraj:University of Allahabad; 2022.
Gelardi A. Saving the past, making history: film festivals and the dynamics of rediscovery. Cinéma & Cie. Film and Media Studies Journal. 2024;24(42):119–36. https://doi.org/10.54103/2036-461X/19028
Hair Junior JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis. New Jersey. 1998;5(3):207–19.
Apriyana Y, Surmaini E, Estiningtyas W, Pramudia A, Ramadhani F, Suciantini S, et al. The integrated cropping calendar information system: a coping mechanism to climate variability for sustainable agriculture in Indonesia. Sustainability. 2021;13(11):6495. https://doi.org/10.3390/su13116495
Fernando S, Garnevska E, Ramilan T, Shadbolt N. Organisational attributes of cooperatives and farmer companies. J Co-operative Organ Manage. 2021;9(1):100132. https://doi.org/10.1016/j.jcom.2021.100132
Kumar P, Babu BK. A study on farmers awareness towards Pradhan Mantri Kisan Samman Nidhi Yojana in the Guntur district. Int J Res Reg Studies. 2018;3(3):10–4.
Thompson B. Exploratory and confirmatory factor analysis: Understanding concepts and applications. Washington, DC American Psychological Association; 2004. https://doi.org/10.1037/10694-000
Amitha CD, Karthikeyan C. Pradhan Mantri Kisan Samman Nidhi (PM KISAN)–beneficiaries opinion, amid–covid–19 pandemic. J Comm Mob Sustain Develop. 2022:767.
Pulla S, Nisha PR, Subramonian S, Prabhu M, Thilakar P, Kumar N. Comparison of vulnerability faced by farmers in different livestock farming and coping mechanisms. Ind J Ext Edu. 2021;57(4):35–40. https://doi.org/10.5958/2454-552X.2021.00160.2
Kalolo A, Gautier L, De Allegri M. Exploring the role of social representations in micro–health insurance scheme enrolment and retainment in sub–Saharan Africa: a scoping review. Health Pol Plann. 2022;37(7):915–27. https://doi.org/10.1093/heapol/czac036
Skaalsveen K, Ingram J, Urquhart J. The role of farmers' social networks in the implementation of no-till farming practices. Agric Sys. 2020;181:102824. https://doi.org/10.1016/j.agsy.2020.102824
Tabachnick BG, Fidell LS, Ullman JB. Using multivariate statistics. Boston, MA: Pearson; 2013.
Thegaleesan T. A study on Pradhan Mantri Kisan Samman Nidhi (Pm–Kisan) scheme in India. J Xi'an Uni Archi Techno. 2020;12(3):6293–307.
Hartoyo B, Sahara D. Analysis of income and expenditure of farmers' household in the rain–fed area of Boyolali district. IOP Publishing Earth and Environmental Science 2021;653:012007. https://doi.org/10.1088/1755-1315/653/1/012007
Wang S, Tian Y, Liu X, Foley M. How farmers make investment decisions: Evidence from a farmer survey in China. Sustainability. 2019;12(1):247. https://doi.org/10.3390/su12010247
Greiner R, Gregg D. Farmers' intrinsic motivations, barriers to the adoption of conservation practices and effectiveness of policy instruments: Empirical evidence from northern Australia. Land Use Policy. 2011;28(1):257–65. https://doi.org/10.1016/j.landusepol.2010.06.006
Rutten CJ, Steeneveld W, Lansink AO, Hogeveen H. Delaying investments in sensor technology: The rationality of dairy farmers' investment decisions illustrated within the framework of real options theory. J Dairy Sci. 2018;101(8):7650–60. https://doi.org/10.3168/jds.2017-13358
Adimassu Z, Kessler A, Hengsdijk H. Exploring determinants of farmers' investments in land management in the Central Rift Valley of Ethiopia. Applied Geo. 2012;35(1–2):191–8. https://doi.org/10.1016/j.apgeog.2012.07.004
Okello JJ, Lagerkvist CJ, Kakuhenzire R, Parker M, Schulte–Geldermann E. Combining means–end chain analysis and goal–priming to analyze Tanzanian farmers' motivations to invest in quality seed of new potato varieties. British Food J. 2018;120(7):1430–45. https://doi.org/10.1108/BFJ-11-2017-0612
Chellappan S, Sudha R. Investment, adoption, attitude and extent of participation of farmers in soil conservation projects in the Western Ghats of India: Revised topic. Int J Social Econ. 2015;42(3):251–75. https://doi.org/10.1108/IJSE-10-2013-0219
HAIR JUNIOR JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis. New Jersey. 1998;5(3):207–19.
Dziuban CD, Shirkey EC. When is a correlation matrix appropriate for factor analysis? Some decision rules. Psycho Bull. 1974;81(6):358. https://doi.org/10.1037/h0036316
Apriyana Y, Surmaini E, Estiningtyas W, Pramudia A, Ramadhani F, Suciantini S, et al. The integrated cropping calendar information system: a coping mechanism to climate variability for sustainable agriculture in Indonesia. Sustainability. 2021;13(11):6495. https://doi.org/10.3390/su13116495
Vejan P, Khadiran T, Abdullah R, Ahmad N. Controlled release fertilizer: A review on developments, applications and potential in agriculture. J Control Rel. 2021;339:321–34. https://doi.org/10.1016/j.jconrel.2021.10.003
Kambali U, Panakaje N. A Review on access to agriculture finance by farmers and its impact on their income. SSRN. 2022;4104741. https://doi.org/10.47992/IJCSBE.2581.6942.0166
Kirby CK, Specht K, Fox–Kämper R, Hawes JK, Cohen N, Caputo S, et al. Differences in motivations and social impacts across urban agriculture types: Case studies in Europe and the US. Landscape and Urban Planning. 2021;212:104110. https://doi.org/10.1016/j.landurbplan.2021.104110
Kwapong NA, Ankrah DA, Boateng–Gyambiby D, Asenso–Agyemang J, Oteng Fening L. Assessment of agricultural advisory messages from farmer–To–farmer in making a case for scaling up production: A qualitative study. Qualitative Report. 2020;25(8):2011–25. https://doi.org/10.46743/2160-3715/2020.4241
Skaalsveen K, Ingram J, Urquhart J. The role of farmers' social networks in the implementation of no–till farming practices. Agricultural Systems. 2020;181:102824. https://doi.org/10.1016/j.agsy.2020.102824
Olorunfemi TO, Olorunfemi OD, Oladele OI. Determinants of the involvement of extension agents in disseminating climate smart agricultural initiatives: Implication for scaling up. J Saudi Soc Agric Sci. 2020;19(4):285–92. https://doi.org/10.1016/j.jssas.2019.03.003
Antwi–Agyei P, Stringer LC. Improving the effectiveness of agricultural extension services in supporting farmers to adapt to climate change: Insights from northeastern Ghana. Climate Risk Manage. 2021;32:100304. https://doi.org/10.1016/j.crm.2021.100304
Kaiser N, Barstow CK. Rural transportation infrastructure in low–and middle–income countries: a review of impacts, implications, and interventions. Sustainability. 2022;14(4):2149. https://doi.org/10.3390/su14042149
Hemathilake DM, Gunathilake DM. Agricultural productivity and food supply to meet increased demands. In. Bhat R, editor. Future foods. London: Academic Press; 2022. p. 539–53. https://doi.org/10.1016/B978-0-323-91001-9.00016-5
Moahid M, Maharjan KL. The role of credit obtained from input suppliers in farm investment in Afghanistan. J Contemp India Stud Space Soc. 2020;10:1–6.
Green WN. Financing agrarian change: Geographies of credit and debt in the global south. Prog Human Geograp. 2022;46(3):849–69. https://doi.org/10.1177/03091325221083211
Ssewanyana S, Kasirye I. Estimating catastrophic health expenditures from household surveys: evidence from living standard measurement surveys (lsms)–integrated surveys on agriculture (ISA) from sub–Saharan Africa. App Heal Econ Health Pol. 2020;18:781–8. https://doi.org/10.1007/s40258-020-00609-1
Thema J, Vondung F. Expenditure–based indicators of energy poverty - An analysis of income and expenditure elasticities. Energies. 2020;14(1):8. https://doi.org/10.3390/en14010008
Adams DW. Are the arguments for cheap agricultural credit sound? In: Admas DW, editors. Undermining rural development with cheap credit. London: CRC Press; 2021. p. 65–77. https://doi.org/10.4324/9780429270178-9
Grivins M, Thorsøe MH, Maye D. Financial subjectivities in the agricultural sector: A comparative analysis of relations between farmers and banks in Latvia, Denmark and the UK. J Rur Stud. 2021;86:117–26. https://doi.org/10.1016/j.jrurstud.2021.06.006
Key N. Credit constraints and the survival and growth of beginning farms. Agricultural Fin Rev. 2022;82(3):448–63. https://doi.org/10.1108/AFR-04-2021-0050
Kiros S, Meshesha GB. Factors affecting farmers' access to formal financial credit in Basona Worana district, North Showa zone, Amhara regional state, Ethiopia. Cogent Econ Fin. 2022;10(1):2035043. https://doi.org/10.1080/23322039.2022.2035043
Masaood M, Maharjan KL. An exploration of the informal credit practices for agriculture in Afghanistan: reasons for availing informal and not availing formal credit. J Int Dev Coop. 2020;26:95–108.
Behera AR, Behera M. Access and repayment of institutional agricultural credit by farmers in tribal areas of Odisha: trends, determinants and policy measures. J Asian Afr Stud. 2024 ;59(2):623–39. https://doi.org/10.1177/00219096221117075
Haumba EN, Kaddu S. Information seeking behaviour patterns of family farmers and household food security in Kisoga B village, Ntenjeru sub county in Mukono district, Uganda. University of Dar es Salaam Library Journal. 2021;16(1):21–37.
Kalolo A, Gautier L, De Allegri M. Exploring the role of social representations in micro–health insurance scheme enrolment and retainment in sub–Saharan Africa: a scoping review. Health Pol Plan. 2022;37(7):915–27. https://doi.org/10.1093/heapol/czac036
Sorgho R, Mank I, Kagoné M, Souares A, Danquah I, Sauerborn R. We will always ask ourselves the question of how to feed the family: subsistence farmers' perceptions on adaptation to climate change in Burkina Faso. Int J Environ Res Public Health. 2020;17(19):7200. https://doi.org/10.3390/ijerph17197200
Cole DC, Bondy MC. Meeting farmers where they are–rural clinicians' views on farmers' mental health. J Agromed. 2020;25(1):126–34. https://doi.org/10.1080/1059924X.2019.1659201
Mwambi M, Bijman J, Mshenga P. Which type of producer organization is (more) inclusive? Dynamics of farmers' membership and participation in the decision?making process. Ann of Public Cooperative Econ. 2020;91(2):213–36. https://doi.org/10.1111/apce.12269
Fernando S, Garnevska E, Ramilan T, Shadbolt N. Organisational attributes of cooperatives and farmer companies. J Co–operative Organ Manage. 2021;9(1):100132. https://doi.org/10.1016/j.jcom.2021.100132
Abokyi E, Strijker D, Asiedu KF, Daams MN. The impact of output price support on smallholder farmers' income: evidence from maize farmers in Ghana. Heliyon. 2020;6(9):9e05013. https://doi.org/10.1016/j.heliyon.2020.e05013
Viganò L, Castellani D. Financial decisions and risk management of low–income households in disaster–prone areas: Evidence from the portfolios of Ethiopian farmers. Int J dis Risk Red. 2020;45:101475. https://doi.org/10.1016/j.ijdrr.2020.101475
Picone G, Kimou AJ, Kanga D. Medical emergencies and farm productivity in Côte d'Ivoire. Rev Develop Econ. 2023;27(3):1630–48. https://doi.org/10.1111/rode.12987
Chang HH, Meyerhoefer C. Health care expenditure and farm income loss: evidence from natural disasters. Nat Bur Econ Res; 2022;1-46. https://doi.org/10.3386/w29898
Downloads
Published
Versions
- 20-04-2025 (2)
- 29-03-2025 (1)
How to Cite
Issue
Section
License
Copyright (c) 2025 Kaleeswaran Mahendiran, Ramasubramanian Muthuramlingam, Puthira Prathap Duarisamy , Venkatesan Purushothaman, Jegadeesan Muniandi, Subash Somasekaran, Shanmugasundaram Balasubramanium, Ramesh Rajangam
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright and Licence details of published articles
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Open Access Policy
Plant Science Today is an open access journal. There is no registration required to read any article. All published articles are distributed under the terms of the Creative Commons Attribution License (CC Attribution 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/). Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
