Faculty Publications

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    Classifying behavioural traits of small-scale farmers: Use of a novel artificial neural network (ANN) classifier
    (Institute of Electrical and Electronics Engineers Inc., 2016) Jena, P.R.; Majhi, R.
    This paper develops and employs a novel artificial neural network (ANN) model to study farmers' behaviour towards decision making on maize production in Kenya. The paper has compared the accuracy level of ANN based model and the statistical model and found out that the ANN model has achieved higher accuracy and efficiency. The findings from the study reveal that the farmers are mostly influenced by their demographic and food security for decision making. Further to examine the relative importance of different demographic and food security characteristics, an ANOVA test is undertaken. The results found that education and food security indices are instrumental in influencing farmers' decision making. © 2016 IEEE.
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    Analyzing vulnerability to poverty and assessing the role of universal public works and food security programs to reduce it: Evidence from an eastern Indian state
    (John Wiley and Sons Inc, 2022) Khosla, S.; Jena, P.R.
    Social protection (SP) programs have become a widespread intervention to strengthen coping strategies in developing countries to improve the well-being of vulnerable households. Past studies have identified the positive impact of SP on ex-post poverty reduction. However, there is relatively scant evidence of the role of SP in reducing vulnerability to poverty (VtP). This study estimates the role of SP, in particular, the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) and public distribution system (PDS) in reducing household VtP in the eastern Indian state of Odisha. Firstly, the household VtP was estimated using the feasible generalized least squares (FGLS) method. Secondly, the role of SP in reducing household VtP was analyzed using the quantile regression (QR) approach. This study utilizes cross-sectional data of 1506 rural households from the State of Odisha. The FGLS estimates show that the household VtP rate is 42.43% as opposed to the current poverty rate of 32.87% in the state. The QR results demonstrate that the households that participated in the MGNREGA program are less likely to fall into poverty than those without it. However, household access to the PDS is observed to have no significant association with vulnerability. © 2022 John Wiley & Sons Ltd.
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    Effect of farm machinery adoption on household income and food security: evidence from a nationwide household survey in India
    (Frontiers Media S.A., 2023) Jena, P.R.; Tanti, P.C.
    An increase in farm productivity and income is crucially linked to farm mechanization. Labour shortage in rural areas and frequent extreme weather events have made a resounding pitch for the deepening of farm mechanization in India. Our study examines the effect of agricultural machinery adoption on net agricultural income, household income, and household consumption in India; the latter is considered as an indicator of food security. A nationwide household survey of 10253 households drawn from the majority of states of India has been used. To assess the impact of machinery adoption on the outcome variables, the endogenous switching regression (ESR) model is used. Of the three types of machineries investigated, such as tractors, electric pumps, and diesel pumps, the average adoption rates are found to be low in the country, i.e., 8% for tractors, 24% for electric pumps, and 14% for diesel pumps. The wide heterogeneity in terms of adoption is mostly rooted in the large geographical differences among the states of India, as machinery adoption is concentrated in the north and north-central plains of the country. The first stage of ESR, which is a probit model, reveals the determinants of mechanization as access to credit, climatic shocks, access to irrigation, and farmer cooperative membership. The average treatment effect estimates from the second stage outcome regression reveal that the adoption of machineries has increased net agricultural income by 31%, household income by 19%, and food consumption by 5%. Given these demonstrable positive effects of mechanization in agriculture, there is a need for deepening of low-cost scale appropriate farm machines suitable for small holders. Government support would play a pivotal role in this direction by making farm credits accessible to smallholders, providing timely subsidies on machinery purchase, and providing required extension services. © © 2023 Jena and Tanti.
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    Enhancing crop yields and farm income through climate-smart agricultural practices in Eastern India
    (Springer Science and Business Media B.V., 2024) Tanti, P.C.; Jena, P.R.; Timilsina, R.R.; Rahut, D.B.
    Climate-induced increase in temperature and rainfall variability severely threaten the agricultural sector and food security in the Indian state of Odisha. Climate-smart agricultural (CSA) practices, such as crop rotation and integrated soil management, help farmers adapt to climate risk and contribute to a reduction in greenhouse gas (GHG) emissions. Therefore, this paper examines the impact of CSA practices on yield and income in vulnerable semi-arid districts of Odisha—Balangir, Kendrapara, and Mayurbhanj. We use primary survey data from 494 households collected in 2019–2020, using a multi-stage stratified sampling approach and structured questionnaire. Propensity score matching (PSM) and the two-stage least square method (2SLS) have been used to analyze the impact of CSA on income and productivity. Two instrument variables, namely distance to the extension office and percentage of adopters in a village, are used to control self-selection bias and endogeneity in our model. Both models show a positive and significant impact of the adoption of CSA on farmers’ productivity and income. The study sheds light on the significant contribution of CSA practices in fostering sustainable income growth amid environmental challenges. Overall, our results suggest that small and marginal farmers of Eastern India, a highly environmentally vulnerable area, can significantly improve their income and productivity by adopting CSA technology. Hence, policymakers should scale the adoption of CSA technology through effective extension programs. © The Author(s) 2024.