Why heat, not rain, matters more for Inflation and Rural Demand

This article covers the Temperatures, more than rainfall or reservoir levels, have become the dominant factor in predicting food production and inflation in India.

Table of Contents

Context: Temperatures, more than rainfall or reservoir levels, have become the dominant factor in predicting food production and inflation in India.

Trends of Temperature Rise and Crop Yields

Temperature Rise:
- Data since the 1950s shows average temperatures have steadily increased.
- The correlation between temperatures and food inflation has grown over time.
Impact on Crop Yields:
- A projected temperature increase of 2.5-4.9°C could reduce wheat yields by 41-52% and rice yields by 32-40%.
- Specific examples:
  - March 2022 Heatwave: Reduced sugarcane yield by 30%, affected vegetables and oilseeds.
  - March 2024 Heatwave: Reached temperatures of 50.5°C, causing a spike in vegetable prices due to crop damage.

Crop Sensitivity to Heat

Perishable Crops (vegetables and fruits): Short-cycle crops, highly sensitive to temperature fluctuations.
- Over the past decade, the correlation between temperatures and perishable crop prices has risen from 20% to 60%.
Durable Crops (cereals, pulses, oilseeds, sugar): Traditionally less sensitive to heat, but this is changing.
- The correlation between temperatures and durable crops has risen from 10% to 45% in the last decade.
Animal Products (dairy, poultry, fish): Rising temperatures have increased animal mortality, impacting prices of animal proteins.

Comparison with Rainfall and Reservoir Levels

Better Irrigation Mitigates Low Rains: Irrigation improvements, especially in North-West India, have lessened the impact of low rainfall on agriculture.
Temperature vs. Reservoir Levels: Temperatures correlate with reservoir levels (~50%), meaning much of the relevant information about water availability is already embedded in temperature data.

Model Findings

Food Inflation Model: Incorporating temperature into food inflation models improves forecasting accuracy. This raises the robust model (R-squared) from 80% to 90%.
- Temperatures are better predictors of food inflation than rainfall and reservoir levels.
Supply-Side Management: Government actions (e.g., managing granary stocks, quick transport, clamping down on hoarders) have played a role in controlling inflation over the past decade.

Outlook for Food Inflation

La Niña Effect (2024): The shift from El Niño to La Niña has brought cooler temperatures and increased precipitation.
- This is expected to lower food inflation and bring overall inflation closer to the RBI’s 4% target by March 2025.
Long-term Challenge: While improved irrigation can mitigate weak rainfall, there is no quick solution to the impact of rising temperatures on agriculture and inflation management.