Myanmar

Myanmar: Analysis of the economic fallout & food insecurity in wake of the takeover

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Key takeaways

  • Prior to 1 February 2021, 2.8 million people were considered food insecure in Myanmar. WFP estimates that 1.5 to 3.4 million additional people could be at risk of food insecurity and in need of assistance due to the economic slowdown provoked by the political crisis in the coming three to six months. This is largely because poor people have lost jobs and income, making it harder to afford food.

  • Vulnerable people in urban areas affected by the economic standstill are at greatest risk, while longer term impact on food systems will also add pressure on rural populations’ food security.

  • In addition to job and income loss, increasing food and fuel prices, disruptions in trade, slumping economic growth, and internal displacement of ethnic minority groups bode ill for Myanmar’s poor. The latest forecast from the World Bank indicates a GDP contraction of 10% in 2021.

  • Market prices of rice and cooking oil have increased across all monitored markets since the start of February 2021 by 5% and 18%, respectively; however even higher increases were registered in border states including Rakhine, Kachin and Chin. Given the importance of rice and cooking oil in diets and the expenditure of poorest households on rice, continued price increases will likely further impact household food security.

  • Myanmar’s economy was already severely impacted by the COVID-19 pandemic in2020; a quarter of the country’s population were poor and a further third were vulnerable to poverty.

  • The current situation is extremely precarious and there may be additional short- and longterm impacts on Myanmar’s food security and poverty levels.

This brief provides an analysis of the short-term, immediate food security impacts of the current events and perspectives for the longer term to inform WFP operations. Considering the fluidity of the current situation and the lack of fresh primary data on affected populations, the analysis builds on secondary data and employs a broad set of assumptions.