Low-Income Countries

AI will affect almost 40 percent of jobs around the world, replacing some and complementing others. We need a careful balance of policies to tap its potential

The negative impact of ‘de-risking’ strategies by major economies would be felt beyond China, while comprehensive reforms in China could generate significant positive spillovers

The economic gains from $272 billion in pandemic support for 94 countries were strongest in the poorest and more vulnerable recipients of IMF concessional financing

Smart fiscal policy can help restore price stability and lessen the impact of the cost-of-living crisis.

Low-income countries face huge economic challenges and financing needs. They rely on international institutions, including the IMF’s Poverty Reduction and Growth Trust, for vital policy and financial support. Economically stronger countries have a responsibility to contribute to the funding of this support.

Despite decades of rapid growth, regional inequalities in sub-Saharan Africa persist. 

Social protection programs are crucial for stabilizing household income, especially during crises. Brazil's response to the pandemic, the Auxilio Emergencial (AE) program, demonstrated the value of a resilient social safety net and digital tools. This study assesses AE's effectiveness in income stabilization, poverty reduction, and inequality. Results show that the pre-pandemic social protection system would have only buffered about a quarter of income loss, with unemployment insurance more significant for higher-income households, and social safety net transfers crucial for lower-income households, especially those in informal employment. AE successfully supported lower-income households during the pandemic, but its generosity went beyond the stabilization of income, resulting in large fiscal costs.

This paper estimates the impact of external demand shocks on real income. We utilize a first order approximation to a wide class of small open economy models that feature sector-level gravity in trade flows, which allows us to measure foreign shocks and characterize their welfare impact in terms of reducedform elasticities. We use machine learning techniques to group 4-digit manufacturing sectors into a smaller number of clusters, and show that the cluster-level elasticities of income with respect to foreign shocks can be estimated using high-dimensional statistical techniques. Foreign demand shocks in complex intermediate and capital goods have large positive impacts on real income, whereas impacts in other sectors are negligible. We showthat the estimates imply that countries that specialize in these sectors enjoy greater gains from increased openness, and that (small) export subsidies to these sectors are welfare-improving. Finally, a calibrated multisector production and trade model with input-output linkages and external economies of scale can match the empirical estimates.

We explore the role of sectoral debt dynamics in shaping business cycles in a sample of 52 Emerging Market Economies (EMEs) and Frontier Market Economies (FMEs) from 2005 to 2021. Higher household debt levels and growth are associated with significantly slower GDP growth in more developed EMEs but not in less developed EMEs and FMEs. We also examine the relationship between US dollar cycles, sectoral debt levels and growth, and economic activity. Among developed EMEs, higher expected household debt growth magnifies the impact of US dollar fluctuations on economic activity, with significant but less persistent effects on consumption and more persistent effects on investment. Our empirical findings highlight the important role of household debt dynamics in relatively developed EMEs.

The paper explores the drivers of political fragility by focusing on coups d’état as symptomatic of such fragility. It uses event studies to identify factors that exhibit significantly different dynamics in the runup to coups, and machine learning to identify these stressors and more structural determinants of fragility—as well as their nonlinear interactions—that create an environment propitious to coups. The paper finds that the destabilization of a country’s economic, political or security environment—such as low growth, high inflation, weak external positions, political instability and conflict—set the stage for a higher likelihood of coups, with overlapping stressors amplifying each other. These stressors are more likely to lead to breakdowns in political systems when demographic pressures and underlying structural weaknesses (especially poverty, exclusion, and weak governance) are present or when policies are weaker, through complex interactions. Conversely, strengthened fundamentals and macropolicies have higher returns in structurally fragile environments in terms of staving off political breakdowns, suggesting that continued engagement by multilateral institutions and donors in fragile situations is likely to yield particularly high dividends. The model performs well in predicting coups out of sample, having predicted a high probability of most 2020-23 coups, including in the Sahel region.

This paper studies how and why inflation expectations have changed since the emergence of Covid-19. Using micro-level data from the University of Michigan Survey of Consumers, we show that the distribution of consumer expectations at one-year and five-ten year horizons has widened since the surge of inflation during 2021, along with the mean. Persistently high and heterogeneous expectations of consumers with less education and lower income are mainly responsible. A simple model of adaptive learning is able to mimic the change in inflation expectations over time for different demographic groups. The inflation expectations of low income and female consumers are consistent with using less complex forecasting models and are more backward-looking. A medium-scale DSGE model with adaptive learning, estimated during 1965-2022, has a time-varying solution that produces lower forecast errors for inflation than a variant with rational expectations. The estimated model interprets the surge of inflation in 2021 mainly as the result of a price markup shock, which is more persistent and requires a larger and more persistent monetary policy response than under rational expectations.

This paper analyzes the distributional impacts of inflation in Thailand. For that aim, the paper uses rich micro-survey data on 46,000 Thai households to study the effect of the recent elevated inflation on poverty, its distributional effects on different income levels, and the fiscal cost to compensate households from real income losses. To study the multidimensional impact of inflation, the paper also studies how inflation differentially affects households through the consumption, income, and wealth channel. The analysis shows that under a baseline scenario, poverty in Thailand could increase by 1.3 percentage points—about 900,000 people—in the absence of government intervention. Targeted fiscal support to only compensate households that are below the national poverty line from rising inflation amount to 0.05 percent of GDP. However, fiscal support to compensate relatively rich households, defined as those above the median of the income distribution, amount to 1.4 percent of GDP. Moreover, due to high levels of debt, richer households benefit from inflation relative to poorer households. Finally, the paper also delves into policy responses undertaken by the Thai government and Asian and emerging economies to mitigate elevated inflation.