Trends in Yield, Area, and Production of Foodgrains in India

An attempt is made in this paper to examine the patterns in the area, production, and productivity, of India's major food grain crops. Statistical methods such as trend analysis as average annual growth rate, and Auto-Regressive Distributed Lag model are used. The ARDL Model is used to determine the short-run and long-run relationship between the independent variables area, production on the dependent variable yield of foodgrain from 1965 to 2022. The study found that in the short-run there is a significant positive impact of area and second lag of yield on the dependent variable yield of food grains in India and the production is not significantly influencing the yield of foodgrains. On the other hand, in the long-run cointegrating relationship among the variables based on the bound test results shows that the production is having a significant positive impact on the yield of foodgrains and the area under cultivation is showing an insignificant impact on the yield of foodgrains. The corresponding Error Correction Mechanism indicates the high speed of adjustment towards the equilibrium relationship among the variables.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-05-09
DOI
https://doi.org/10.36948/ijfmr.2025.v07i03.44350
Primary Topic
GABA and Rice Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Trends in Yield, Area, and Production of Foodgrains in India

Khalid Muhammad, K. Manikandan, M. Priyadharshini, C T Shaharshad
International Journal For Multidisciplinary Research
GABA and Rice Research
article

Trends in Yield, Area, and Production of Foodgrains in India

Khalid Muhammad, K. Manikandan, M. Priyadharshini, C T Shaharshad
article en

Abstract

An attempt is made in this paper to examine the patterns in the area, production, and productivity, of India's major food grain crops. Statistical methods such as trend analysis as average annual growth rate, and Auto-Regressive Distributed Lag model are used. The ARDL Model is used to determine the short-run and long-run relationship between the independent variables area, production on the dependent variable yield of foodgrain from 1965 to 2022. The study found that in the short-run there is a significant positive impact of area and second lag of yield on the dependent variable yield of food grains in India and the production is not significantly influencing the yield of foodgrains. On the other hand, in the long-run cointegrating relationship among the variables based on the bound test results shows that the production is having a significant positive impact on the yield of foodgrains and the area under cultivation is showing an insignificant impact on the yield of foodgrains. The corresponding Error Correction Mechanism indicates the high speed of adjustment towards the equilibrium relationship among the variables.

International Journal For Multidisciplinary ResearchVol. 7(3)
Openalex Percentile: Top 92%
GABA and Rice Research
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