Department Of Economic Studies

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    Farm size and productivity relationship among the farming communities in India
    (SAGE Publications Inc., 2023-05-25T00:00:00) Kumar, Karnati Kiran; Moharaj, Prasanta
    The relationship between farm size and productivity has been a topic of interest in agricultural research for decades due to the significance of agriculture in rural economies and its potential to reduce poverty and promote inclusive growth. The relationship between farm size and productivity is influenced by factors such as the type of crop being produced, costs of cultivation, farm management practices, access to inputs and markets and socio-economic conditions. This paper aims to investigate the relationship between farm size and productivity in the context of farming households, their cost of cultivation and the types of crops they produce. Using the Cobb�Douglas production function, the present study estimates the regression function for principal crops such as cotton and paddy in the study area. The findings reveal strong evidence of an inverse relationship between farm size and productivity, indicating that small and marginal farmers are more productive in wetland cultivation (paddy). In contrast, medium and large farmers are more productive in dry land cultivation (cotton). The paper also investigates the availability and accessibility of credit facilities for different farm sizes. It concludes that small and marginal farmers depend mainly on non-institutional credit agencies compared to medium and large farmers. � The Author(s) 2023.
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    Role of land reforms in eradicating land inequalities in rural india
    (Society of Economics and Development, 2016) Singla, Naresh; Kaur, Pavneet; Ahmed, Mumtaz
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    Socio-economic implications of pesticide use in bathinda district of the punjab state
    (Central University of Punjab, 2014) Kaur, Harvinder; Bhatia, Sandeep Kaur
    The excessive use of the pesticides in agriculture has not only increased production cost but also led to negative externalities. The present study is an attempt to analyse the socio-economic implications of pesticide use in Bathinda district known as cotton belt as it has maximum area under cotton cultivation. Among eight blocks, two blocks namely Talwandi Sabo having maximum area under cotton cultivation and Phul block having maximum area under paddy cultivation had been selected for the study. Therefore, in the present study entitled "Socio-Economic Implications of Pesticide use in Bathinda District of the Punjab State", an attempt has been are made to access efficiency of two farms growing cotton and paddy and also to find out the impact of pesticides on gross returns of the crops and also on health of farmers and agricultural labourers. The farmers and agricultural labourers engaged in growing cotton and paddy were randomly selected across two villages i.e. Laleana and Rayia respectively. The primary data was collected from 120 farmers and 80 agricultural labourers through structure schedules . The data was analysed using Data Envelopment Analysis programme, Simple regression analysis, Multiple (Step-up) regression analysis and Probit model. The rate of return from pesticides for cotton crop for large farmers (Rs. 13.40) was less than medium farmers (Rs. 14.31) and small farmers (Rs. 15.44). It was the highest for small farmers (Rs. 15.44) showing that it decreases with the increase in the expenditure on pesticides. Likewise for paddy, rate of return was less for large farmers (Rs. 18.56) as they incurred more on pesticides while the highest for small farmers (Rs. 22.67). Regarding the impact of different inputs iv used for returns of cotton, pesticides were significant and positive input while for paddy; labour was significant and positive variable. The result of technical efficiency reveals that cotton farms were less efficient than paddy farms. Usage of pesticides had harmful effect upon the health of farmers and agricultural labourers indicating that those were using manual backup sprayer face many problems. The farmers should be educated to identify the threshold level of pest infestation and take measures only after that instead of blindly following the neighbouring farmers while applying pesticides.