Eco-market dynamics: deciphering India's agricultural pricing in the context of carbon emissions and inflation

Rashmi Supriya et al.

International Journal of Revenue Management2025https://doi.org/10.1504/ijrm.2025.149684article
ABDC C
Weight
0.37

What the paper says

This study explores the intricate relationship between carbon emissions, agricultural commodity prices, and inflation in India. Using monthly data from January 2014 to March 2022 and structural vector auto regression (SVAR) modelling, the analysis reveals diverse dynamics among key commodities. An inverse relationship is found between wheat prices and inflation, suggesting consumer benefits. Turmeric shows a strong negative correlation, indicating unique market behaviour, while refined soybean oil and cotton prices exhibit minimal negative impacts. In contrast, crude palm oil prices positively influence inflation. A noteworthy finding is the negative correlation between carbon emissions and inflation, highlighting the environmental-economic linkage. These insights enhance understanding of how specific agricultural prices interact with inflation, and how environmental variables play a role. The findings can guide evidence-based policies for agricultural stability, environmental sustainability, and economic growth in India. The implications extend globally, offering valuable insights for developing economies facing similar challenges.

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https://doi.org/https://doi.org/10.1504/ijrm.2025.149684

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@article{rashmi2025,
  title        = {{Eco-market dynamics: deciphering India's agricultural pricing in the context of carbon emissions and inflation}},
  author       = {Rashmi Supriya et al.},
  journal      = {International Journal of Revenue Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijrm.2025.149684},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.