Keivabu et al. (2026) Monsoon weather and food security in Pakistan

Identification

• Journal: Food Security
• Year: 2026
• Date: 2026-01-06
• Authors: Risto Conte Keivabu, Rumi Chunara
• DOI: 10.1007/s12571-025-01634-5

Research Groups

• Max Planck Institute for Demographic Research, Rostock, Germany
• Department of Biostatistics, School of Global Public Health, NYU, New York, United States
• Department of Computer Science & Engineering, Tandon School of Engineering, NYU, Brooklyn, New York, United States

Short Summary

This paper investigates how dry monsoon conditions in Pakistan affect self-assessed food security, finding that drier monsoon seasons significantly increase mild to severe food insecurity, primarily by reducing food quality and diversity, with a disproportionate impact on less educated individuals.

Objective

• To understand how dry conditions during the monsoon season affect self-assessed food security in Pakistan.
• To provide novel evidence on the impact of monsoon weather conditions on food security in Pakistan, specifically using the Food Insecurity Experience Scale (FIES).
• To estimate the heterogeneous impact of droughts by employment in agriculture, residence in a rural area, and educational attainment.

Study Configuration

• Spatial Scale: Pakistan, at the district level (126 districts).
• Temporal Scale:
  • Survey data: October 2019 to March 2020.
  • Meteorological data for SPEI calculation: January 1980 to December 2020.
  • Primary exposure period: 2019 monsoon season (May-October) for 6-month SPEI.
  • Short-term heat exposure: 7 days and 1 month prior to the interview.

Methodology and Data

• Models used:
  • Standardized Precipitation-Evapotranspiration Index (SPEI) (6-month, 4-month, and 12-month variants).
  • Linear Probability Model (LPM) with Fixed Effects (for month of interview and province).
  • Principal Component Analysis (PCA) for wealth index construction.
• Data sources:
  • Pakistan Social and Living Standards Measurement Survey (PSLM) 2019–2020 (147,063 households).
  • European Re-Analysis-Land (ERA5) meteorological data (from Copernicus Data Store).

Main Results

• Exposure to a dry monsoon season (one standard deviation increase in inverted SPEI) is associated with an 8.5% increase in mild to severe food insecurity.
• The impact of dry conditions is primarily concentrated on the quality and diversity of food available, rather than total caloric intake, as indicated by specific FIES questions.
• Dry conditions lead to a larger decrease in food diversity for individuals with no or low educational attainment.
• Severe droughts (SPEI < -1.49) increase mild to severe food insecurity by 0.073 (a 17.8% change), an effect size approximately twice that of the continuous SPEI measure, though with higher statistical uncertainty.
• Temperature anomalies during the monsoon season also increase mild to severe food insecurity by 0.071 (a 17.3% change) for a one standard deviation increase.
• Short-term exposure to hotter days (>15 °C) in the week or month prior to the survey significantly increases mild to severe food insecurity.
• No substantial impact of moderate or severe flooding events on self-experienced food security was observed.
• While effects were larger for households employed in agriculture and those in rural areas, these differences were not statistically significant for overall food insecurity.

Contributions

• Provides the first evidence on the impact of monsoon weather conditions on self-assessed food security in Pakistan, addressing a significant gap in the literature for this region.
• Utilizes the Food Insecurity Experience Scale (FIES), a standardized global measure, offering a novel approach compared to previous studies that focused on objective measures like malnutrition or stunting.
• Investigates heterogeneous impacts of droughts across different socio-demographic groups (employment in agriculture, rural/urban residence, educational attainment), revealing disparities in vulnerability, particularly for less educated individuals.
• Leverages district-level household location data, providing finer geographical granularity than previous global studies on FIES.

Funding

• Open Access funding enabled and organized by Projekt DEAL.
• Max Planck Sabbatical Award to Risto Conte Keivabu.

Citation

@article{Keivabu2026Monsoon,
  author = {Keivabu, Risto Conte and Chunara, Rumi},
  title = {Monsoon weather and food security in Pakistan},
  journal = {Food Security},
  year = {2026},
  doi = {10.1007/s12571-025-01634-5},
  url = {https://doi.org/10.1007/s12571-025-01634-5}
}