Assessing the economic impact of sand and dust storms provides critical insights to policy development and reforms; a subject that is gaining more attention as risk management becomes the dominant approach for hazard mitigation policies. To assess the causal impact of sand and dust storms on agriculture, specifically on crop and livestock revenue and physical production, random year-to-year variations in dust exposure were analyzed using a fixed effect regression. To complete this analysis, weather and climate data from the on-ground meteorological stations was combined with the household level socioeconomic surveys conducted by Mongolia’s National Statistics Office (NSO) over a decade. The descriptive statistics of the meteorological data collected over the eight years period show that, on average, 29 dust events have occurred every year across the country, with greater variation among provinces (Aimags) and regions, reaching up to 108 events in a year in some provinces. The overall trend reveals a slight decrease in the dust events from 2009 to 2019. The econometric results show that value of crop and livestock production (gross income) and physical yields significantly decline in response to higher frequencies of sand and dust storms events. During this period, Mongolia experienced a 2.7% decline in crop revenue as a result of additional sand and dust storms. Assuming 2.7% constant decline in revenues across all agricultural sub-sectors and regions or Aimags, this could lead to about $37.8 million in losses to the economy, which is equivalent to about 0.27% of the national GDP of Mongolia. Increases in the frequency of sand and dust storms could reduce agricultural productivity by between 1.5% to 24%, depending on the crop. Estimates from the modelling exercise are robust to potential endogeneity bias in the measure of sand and dust storms; different specification and identification approaches accounting for the endogeneity bias consistently reveal negative and qualitatively similar impacts of sand and dust storms on crop and livestock productivity.
