This report’s aim is to raise awareness on El Niño–Southern Oscillation (ENSO) events among Myanmar’s policy makers and stakeholders. Particularly, the aim is to guide them on preparedness and resiliency building measures. It does this by providing information on ENSO’s social, poverty, economic, and agricultural impacts in Myanmar and outlining ways forward. The report finds that ENSO’s impacts vary from region to region but tend to exacerbate current climatic trends. Myanmar’s government attempted to prepare for, and respond to, the 2016 El Niño, but capacity and organizational constraints limited its effectiveness. Preparing for ENSO is important because of Myanmar’s low resilience to climate shocks, the importance of agriculture for the national economy, the rural and poor populations’ climate vulnerability, and the lack of research on ENSO in Myanmar. This report is timely given the high likelihood of Myanmar facing another El Niño in winter 2018/2019.
ENSO has important impacts on Myanmar’s climate, agriculture, economy, and society
Myanmar is highly vulnerable to ENSO-related climate shocks. ENSO describes naturally occurring ocean and atmospheric temperature fluctuations that can have major implications on global weather patterns. Historical data show the two phases of ENSO, El Niño and La Niña, tend to depress and increase average rainfall, respectively. Between 1980 and 2015, there were eight El Niño events in Myanmar. Historical rainfall patterns show average annual rainfall was about 10 percent lower during El Niño years in the summer months and 4 percent higher during La Niña, years compared to non-ENSO years (see the left side of Figure A). ENSO has been linked to extensive drought and flooding. For example, during the 2016 El Niño, 1,700 villages experienced water shortages. Also, ENSO impacts tend to be highly localized, with certain areas more affected than others during the same event. For example, 15 million people, mainly farmers, suffered from the effects of El Niño in just three regions in 2016: Sagaing, Magaway, and Ayeyarwady. This uncertainty makes planning for ENSO events a challenge. This is further exacerbated by Myanmar’s low coping and absorptive capacity, which is the capacity to respond to disasters and implement development preparedness measures.
ENSO’s impacts on agriculture affect Myanmar’s entire economy. Myanmar’s agricultural sector contributes 30 percent to the country’s gross domestic product (GDP) and accounts for 60 percent of employment. As such, many people are reliant on agriculture for their livelihoods and are vulnerable to ENSO-related climate shocks. Agriculture is even more important when considering its linkages with downstream sectors and consumers in domestic and foreign markets. As such, any shocks to agriculture cause reverberations across the entire economy, with serious implications on welfare, food security, and national poverty levels.
Analysis conducted in this report shows that crop yields tend to decline during El Niño and increase during La Niña. In fact, yield gains during La Niña are slightly larger than yield declines during El Niño, in percentage terms. This was not common in other countries where similar crop analyses were conducted. In those countries, El Niño was found to be more damaging to crop yields than La Niña was helpful. In line with historic data, the model shows ENSO affects bean yields, which tend to be grown in the North, more than other crops in Myanmar. Rice, which is Myanmar’s most important crop and cultivated mostly in the South, sees yields decrease by six percent during El Niño, and increase by about the same amount during La Niña. The Central part of the country, which sees frequent droughts during El Niño, grows some maize but very little rice or beans, so crops are minimally impacted. Myanmar’s vegetable growing areas are more evenly spread across the country, and simulations show yields decrease by 3 percent during El Niño and increase by 4 percent during La Niña.
ENSO events may adversely affect Myanmar’s livestock and fishery sectors, but evidence is inconclusive. There are more high temperature-humidity days during La Niña years, which can cause heat stress for livestock. From 1951 to 2010, La Niña years have four more hot days than neutral and El Niño years, which have about 25 such days per year. Poultry are sensitive to heat, with strong declines in feed intake, egg size, and egg quality. Swine and cattle are also sensitive to heat, with negative outcomes evident at high temperatures. Reports show drought led to fodder shortages and weak and unhealthy cows and goats, which forced herders to sell meat at lower prices, and high temperatures led to increased pest populations and disease outbreaks among livestock populations. Fisheries, which contribute to about 10 percent of national GDP,11 saw declines in fishing stocks during El Niño but is unclear if this was because of higher water temperatures or overfishing. Generally, temperatures in Myanmar are mild, and ENSO is not expected to change these dramatically enough to cause major concerns.
Simulations indicate El Niño causes significant economic losses, but La Niña generates nearly as much in economic gains. National GDP is 0.8 percent lower during El Niño years compared to non-ENSO years. But, even small percentage reductions in national GDP can imply substantial monetary losses. For example, a 0.8 percent drop in national GDP equals $421 million in lost value-added. El Nino impacts an even larger portion of the agricultural sector, which sees GDP fall by 2.7 percent. By contrast, La Niña’s impacts on the agricultural sector expand the economy. Simulations show national GDP gains during La Niña ($400 million) almost offset GDP losses during El Niño ($421 million), with the agricultural sector gaining the most ($444 million). In fact, GDP gains in the agriculture sector during La Niña are higher than losses in the agriculture sector during EL Niño: a 3.0 percent gain compared to a 2.7 percent loss. This positive net effect is strongest in the North and South regions where agriculture is most prominent (see right side of Figure A).
ENSO has greater negative impacts on poor and rural households than on affluent and urban households. Simulations show all households experience a decline in consumption, or welfare, during a strong El Niño event. However, rural households suffer over twice as much in consumption losses (0.74 percent loss) than urban households (0.34 percent loss). Rural households are more likely to be farmers, and they spend a larger share of their incomes on food, which sees higher prices during El Niño. Urban households, as net consumers of food products, are also hurt by higher food prices but not to the level of rural households. Simulations also show lower income households are affected slightly worse by El Niño, experiencing a 0.72 percent consumption loss, compared to a 0.61 percent consumption loss, on average, for all households. This is partly because poor households are more dependent on incomes from low-skilled farming. Also, the regions with the most rainfall variability during ENSO tend to be poorer and less able to cope. Rising food prices during El Niño–related shocks more negatively impact the poor, who spend a larger share of their income on food. El Niño is also predicted to exacerbate poverty. Simulations show a typical El Niño raises the national poverty rate by 0.6 percentage points during the event period, which is equivalent to an additional 300,000 people living below the poverty line.
Female-headed households are slightly less affected than male-headed households by strong El Niño events, but women are less able to recover. Women play an important role in agriculture in Myanmar: about 48 percent of women are employed in agriculture compared to 51 percent of men. Simulations show female-headed households are slightly less affected by strong El Niño events, both in rural areas and nationally, than male headed households. This outcome may reflect differences in male and female land ownership, with women less likely to own farmland, and thus less likely to have incomes directly affected by ENSO shocks. This does not mean that male-headed households become poorer than female-headed households after an ENSO event; women remain poorer. Moreover, women and girls have lower recovery capacity than men. This is because of limited geographic and occupational mobility; lower access to employment and financial resources; and higher food insecurity and malnutrition.
Myanmar has taken actions to support ENSO preparedness, but there is room for improvement
The government of Myanmar has recently taken steps toward addressing longer term weather-related risks, like ENSO. In 2016, a new government came to power in Myanmar. Since then, the country began a transformation toward a more open economy, where foreign and private sector investments are encouraged. It was also in 2016 that the government enacted several measures to directly prepare for ENSO events. The government approved an El Niño risk mitigation plan and conducted an El Niño Outlook Forum, which brought together relevant stakeholders and representatives from the media, government agencies, and international organizations to discuss El Niño’s potential impacts and preparedness measures. However, in the end, much of the El Niño funding support was diverted to provide important aid and drinking water, not to improve preparedness. Prior to 2016, the government began developing institutional and policy reforms to address climate change and related disasters. Since then, these efforts have quickened.
The government’s important steps to prepare for ENSO in 2016 also revealed areas to strengthen. These include the following:
Government-specific areas to strengthen
Myanmar would benefit from policies and action plans for slow onset, ENSOrelated shocks. There are several relevant strategies addressing climate change and natural disasters, but few specifically for ENSO events.
There are opportunities to strengthen Myanmar’s Early Warning Systems (EWS).
The Department of Meteorology and Hydrology (DMH) could improve its EWS infrastructure and capacity to implement a fully effective EWS.
Myanmar’s budgeting system could become more efficient and effective in responding to ENSO events. Contingency funds are often underutilized, and ministry budget allocations could have broader focuses.
There are opportunities to improve coordination and human capacity on ENSOrelated themes. Since ENSO has not yet been mainstreamed into government strategies, there remains institutional overlap and areas to raise awareness and human capacity.
General areas to strengthen
The country’s agricultural stakeholders have yet to apply, at sufficient scale, appropriate water and agricultural management practices. Also, the country has not been effective in locating and harvesting water resources, particularly groundwater.
Myanmar suffers from resource and capacity constraints. Myanmar is in the lowest quintile of countries in coping capacity and absorptive capacity.
There is insufficient research and knowledge on ENSO in Myanmar. Limited information makes it difficult to forecast and assess ENSO-related calamities.
Gender issues could be mainstreamed into agricultural planning in Myanmar, including into climate change or disaster risk planning. Policy makers, extension workers, development planners, and other local government agencies need greater female participation in local and national economic activities.
Policy interventions can offset ENSO-related losses
Introducing drought tolerant seed varieties and investing in irrigation infrastructure are the most effective interventions for mitigating GDP losses during El Nino. In-depth modeling carried out under this study simulated six policy interventions— including introducing drought-tolerant crop varieties, expanding irrigation, restricting rice exports, storing and distributing grains, expanding social protection coverage (or social transfers), and applying all of these policy interventions simultaneously—to understand how they would mitigate El Niño’s impacts on GDP, household welfare, and poverty. Simulations show that introducing drought-tolerant varieties reduces national GDP losses from $421 million without interventions to $169 million. Expanding irrigation also offsets El Niño–related GDP losses by making overall crop production more resilient to climate shocks and raising yields during normal years. Cash transfers and rice export bans, by contrast, are largely ineffective at mitigating El Niño–related GDP losses. Distributing stored grains would actually have a negative impact on agricultural GDP because it increases competition with current farm outputs. Overall, when all interventions are combined and implemented concurrently, there is a GDP gain of $16 million during El Niño events.
Investing in on-farm risk mitigating measures is effective in reducing household welfare losses during El Niño events. Simulations show, as with GDP, that on-farm investments, like expanding irrigation use and providing drought-tolerant seed varieties, reduces consumption losses across the income distribution. Restricting exports and extending social transfers are less effective because they have fiscal implications that may outweigh their benefits. When all policy scenarios are implemented at once, total consumption losses during El Niño are reversed, with all households benefitting from the policy package. Urban households stand to benefit more than rural households from policy interventions, despite being less affected by El Niño: a 1.91 percentage swing from no interventions to all interventions for urban households, compared to a 1.61 percentage swing for rural households. This is because urban consumers benefit from lower food prices, whereas rural household benefits are partially offset by lower food prices paid to farmers. Simulations show both male-headed and female-headed households benefit from on-farm investments, but female-headed households benefit more from introducing drought-tolerant seeds than any intervention for any gender. This is because female households grow more cereal and food crops, and because, by virtue of being poorer, they spend a larger share of their incomes on cereals. Female-headed households also benefit more from cash transfers, in part because they are poorer and more likely to be targeted in a progressive transfer scenario. Male-headed households benefit the most from policy interventions in general, enjoying a 1.57 percentage gain in consumption levels from a no-intervention to an all-intervention scenario.
On-farm risk mitigating measures are again the most effective at preventing people from slipping into poverty during El Niño. Simulations show introducing drought-tolerant seed varieties can decrease the number of people living in poverty by 123,500, despite El Niño. Additional irrigation would negate about two-thirds of the negative poverty outcomes from a strong El Niño, while the other options would negate poverty declines by less than a third each. Interestingly, cash transfers are not particularly effective at mitigating poverty impacts. Again, implementing all intervention scenarios concurrently would reduce poverty significantly. In fact, there would be about 830,000 fewer people living below the poverty line if all interventions were applied compared to if no interventions were applied. There are definite synergies among building resilience to ENSO, poverty reduction, and greater food security.
The government can take additional actions to improve ENSO preparedness
There are many opportunities to improve ENSO preparedness and resilience. In Table A, recommendations are divided into two groups: preparedness and resilience. Preparedness are measures specifically geared toward ENSO and should, ideally, be in place before the next ENSO event occurs. These actions will significantly empower people to cope, respond, and recover from damaging ENSO events. Resilience, by contrast, are measures that are not specifically tailored to ENSO, but that will build individuals’ and organizations’ ability to adapt to multiple forms of risks and shocks without compromising long-term development. Recommendations in red are a high priority, recommendations in tan are a moderate priority. The final two columns denote short-term (S) actions that could be completed within a year, and medium- to long-term (M/L) actions that require more than a year to achieve.