Relative importance of agricultural factors on India’s GDP growth

The relative importance of factors in Indian agriculture from 1960-61 to 2019-20 has been assessed using the True Relative Importance methodology. This approach combines statistical logic, axioms, and theorems from various correlation measures, including squared orthopartial, semi-orthopartial, and simple correlations. Five factors were selected for analysis: Non-irrigated area, irrigated area, fertilizer, rainfall, and temperature, to demonstrate how they contribute to agricultural growth. In the presence of multicollinearity, factors can exhibit positive or negative overlapping, depending on the absence or presence of enhancement synergism. Irrigated area emerged as the most significant factor, explaining 29.15 percent, followed by fertilizer at 27.16%, while rainfall held the lowest relative importance at 0.25%. Despite significant annual rainfall, India relies heavily on irrigation due to spatial and temporal distribution issues. Marginal explanatory power tends to overestimate the true importance of irrigated area while underestimating that of temperature. This pattern holds for other factors as well, where marginal analysis either overestimates or underestimates true importance. Effective policy implementation requires an accurate analysis of true importance, which marginal analysis fails to provide.

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Publication Details

Journal
Farming and Management
Published
2025-06-06
DOI
https://doi.org/10.31830/2456-8724.2025.fm-158
Primary Topic
Agricultural Economics and Practices
Type
article
Field-Weighted Citation Impact
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article

Relative importance of agricultural factors on India’s GDP growth

Debasish Mondal, Rajib Kumar Dolai
Farming and Management
Agricultural Economics and Practices
article

Relative importance of agricultural factors on India’s GDP growth

Debasish Mondal, Rajib Kumar Dolai
article en

Abstract

The relative importance of factors in Indian agriculture from 1960-61 to 2019-20 has been assessed using the True Relative Importance methodology. This approach combines statistical logic, axioms, and theorems from various correlation measures, including squared orthopartial, semi-orthopartial, and simple correlations. Five factors were selected for analysis: Non-irrigated area, irrigated area, fertilizer, rainfall, and temperature, to demonstrate how they contribute to agricultural growth. In the presence of multicollinearity, factors can exhibit positive or negative overlapping, depending on the absence or presence of enhancement synergism. Irrigated area emerged as the most significant factor, explaining 29.15 percent, followed by fertilizer at 27.16%, while rainfall held the lowest relative importance at 0.25%. Despite significant annual rainfall, India relies heavily on irrigation due to spatial and temporal distribution issues. Marginal explanatory power tends to overestimate the true importance of irrigated area while underestimating that of temperature. This pattern holds for other factors as well, where marginal analysis either overestimates or underestimates true importance. Effective policy implementation requires an accurate analysis of true importance, which marginal analysis fails to provide.

Farming and ManagementVol. VOLUME 10(ISSUE 1 (JUNE) 2025)
Kanya Maha Vidyalaya (IN)
Openalex Percentile: Top 81%
Agricultural Economics and Practices
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