Modelling climate variabilities and global rice production: A panel regression and time series analysis

Area of Science:

• Agricultural Science
• Climate Science
• Environmental Science

Background:

• Climate change poses a significant threat to global agriculture and food security.
• Rice production is crucial for food security and Sustainable Development Goals, making it vulnerable to climate variations.
• Existing literature highlights the impact of temperature and rainfall fluctuations on rice supply.

Purpose of the Study:

• To analyze and model the impact of temperature changes and rainfall variations on rice production in major rice-producing countries.
• To assess the relationship between climate variables and rice productivity globally.

Main Methods:

• Collected time series data on national rice production, yield, average annual temperature, and rainfall for 15 major rice-producing countries.
• Compared trends between rice productivity variables and climate data.
• Developed a panel regression model to assess the relationship between rice production and climate variables.

Main Results:

• Time series analysis indicated increasing trends in rice production and yield for most analyzed countries.
• Panel regression model revealed that increased temperatures can decrease rice production.
• Rainfall volume was found to directly impact rice output, highlighting susceptibility to extreme weather events.

Conclusions:

• Rice production is highly susceptible to climate variability, particularly temperature increases and extreme rainfall events (flooding and drought).
• Interventions are needed to mitigate the negative impacts of climate change on rice supply and ensure food security.