Faculty Publications
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Item Role of institutional factors in climate‐smart technology adoption in agriculture: Evidence from an Eastern Indian state(Elsevier B.V., 2022) Tanti, P.C.; Jena, P.R.; Aryal, J.P.; Rahut, D.B.Climate change threatens rural livelihoods by adversely affecting agricultural production through reduced crop yields, harvest loss, and increased cost of production. Climate-smart agriculture (CSA) practices have emerged as a possible solution to ensure food security by adapting to climate risks on the one hand, and mitigating GHG emissions from agriculture, on the other hand. However, resource-poor farmers often face both financial and knowledge constraints to adopt CSA practices, and thus, institutional support plays a crucial role in overcoming those barriers. Therefore, this study uses primary data collected from 248 farm households in the Eastern Indian state of Odisha to examine the role of institutional factors in CSA adoption. Almost 95% of the sample farmers experienced the effects of climate change, and many have adopted CSA practices such as rescheduling planting (78%), crop rotation (56%), crop diversification (35%), micro-irrigation (17%), and drought-resistant seeds (16%). Probit models are estimated to explore the key determinants of the adoption of these five major practices. Results show that factors such as government extension service, farmer field school participation, subsidies, access to energy, and perception of climate shocks are the major determinants. Further, the coefficient of interaction between landholding and credit availability on the decision to adopt CSA is positive. Thus, agricultural policies to improve institutional support, such as subsidies on farm machinery, extension support, credit facility, and field demonstration of technologies, are crucial to upscale CSA adoption in the region. © 2022Item Can rural livelihood programs enhance capabilities and reduce vulnerability to poverty? Evidence from a tribal region of eastern India(Elsevier B.V., 2023) Khosla, S.; Jena, P.R.; Rahut, D.B.Quantitative evidence on the impact of social protection such as livelihood programs (LPs) on reducing vulnerability to poverty (VtP) is scant. Therefore, this paper aims to estimate VtP and the ability of LPs to reduce it. The analysis is based on the primary data collected in 2018–19 from 479 households in a tribal region of eastern India. First, household VtP was estimated using the feasible generalized least squares (FGLS) method. Households were categorized into four groups based on their current and predicted future poverty status: chronic poor, transient poor, escaped poverty, and non-poor. Second, factors influencing this movement of households from current to future poverty states were determined using multinomial logistic regression. Third, the impact of the LP on VtP was investigated using the endogenous switching regression (ESR) approach. The FGLS estimates show that 34.7% of households are vulnerable to future poverty, which exceeds the actual poverty rate of 28.6%. The major factors responsible for exacerbating chronic poverty and causing transient poverty are chronic illness, climate shocks, and the sale of assets. The ESR results indicate that a household's VtP is reduced by 3% for those that participate in LPs. Although the LP evaluated in this study has an average positive impact in reducing vulnerability, there is wide heterogeneity among the beneficiaries as the geographically disadvantaged communities lag behind the others. Therefore, the study suggests strengthening such LPs with a particular focus on disadvantaged and vulnerable communities. © 2022 Economic Society of Australia, QueenslandItem Can farmers with higher capabilities fend off falling into future Poverty? Empirical evidence from a tribal region in eastern India(Elsevier Ltd, 2024) Jena, P.R.; Khosla, S.; Rahut, D.B.The United Nations Sustainable Development Goals (SDGs) 1 (no poverty), targets those individuals who are below the poverty line and those who are vulnerable to falling below the poverty line (VtP). Farmers are more VtP due to limited resilience capacity against the covariate and idiosyncratic shocks. However, literature on farmers’ VtP and their capabilities to mitigate the adverse effects of shocks is relatively scant. Thus, this study aims to examine if higher capabilities lead to less VtP. Using a survey dataset from 222 farm households in rural eastern India, this study first estimated VtP by employing the Feasible Generalized Least Squares (FGLS) approach. Secondly, it used a counting approach and Propensity Score Matching (PSM) method to examine the relationship between the capabilities of households and their VtP. The FGLS results show that about 50% of households are VtP, which exceeds the actual poverty rate of about 36%. The counting approach results show that households with higher capabilities are less VtP. The PSM results indicate that a household's VtP is reduced by 27–37% for those with higher capabilities. Thus, the policy targeting the household below poverty line and also VtP would significantly reduce poverty and contribute to achieving SDG1. This would involve identifying and targeting households most in need of assistance such as households with low income, lack of education, and limited access to resources. This study also suggests increasing the resilience capabilities of households by providing job skill training, diversifying income portfolios, insurance coverage, and social safety nets. © 2023 Elsevier LtdItem 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.