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Does commercial farming protect the environment? Evidence from chemical input use in Haryana, India

Verma, Saroj and Paltasingh, Kirtti Ranjan and Mohapatra, Souryabrata (2025): Does commercial farming protect the environment? Evidence from chemical input use in Haryana, India. Published in: Journal of Agribusiness in Developing and Emerging Economies

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Abstract

Purpose: This study investigates the impact of contract farming (CF) on chemical input usage (fertilisers, pesticides and herbicides) in wheat farming in Haryana, India, weighing on environmental risks from unsustainable chemical input usage under CF. Design/methodology/approach: The research employs an endogenous switching regression (ESR) model using data from 754 farm households, enabling a comparative analysis between contract and non-contract farmers. Findings: The results show that farmers who adopted CF would have reduced chemical input usage by 26.8% if they did not adopt it. Conversely, non-adopters would have increased chemical input usage by 54% if they adopted CF. While CF enhances farm productivity and income, it also increases chemical input usage, posing risks such as soil fertility loss and water contamination. Originality: This study addresses the overlooked topic of chemical input usage in CF research. Leveraging household data and using an endogenous switching regression model provides unique comparative analysis and counterfactual scenarios. The findings contribute to understanding the environmental implications of CF and propose actionable recommendations for sustainable agricultural practices. Managerial or Policy implications: The study recommends promoting organic farming and minimal chemical usage in CF agreements. Government intervention is needed to reduce the environmental impact of CF. Policies should promote environment-friendly fertilisers and provide guidelines on chemical usage based on crop variety, seed quality and soil fertility. Research limitations/implications: The geographic focus on Haryana may limit generalisability. Reliance on cross-sectional data from a single season might not capture variability across different seasons. Future research could expand to other regions, use longitudinal data and investigate a broader range of crops.

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