Does global warming worsen poverty and inequality? An updated review

We offer an updated and comprehensive review of recent studies on the impact of climate change, particularly global warming, on poverty and inequality, paying special attention to data sources as well as empirical methods. While studies consistently find negative impacts of higher temperature on poverty across different geographical regions, with higher vulnerability especially in poorer Sub-Saharan Africa, there is inclusive evidence on climate change impacts on inequality. Further analyzing a recently constructed global database at the subnational unit level derived from official national household income and consumption surveys, we find that temperature change has larger impacts in the short term and more impacts on chronic poverty than transient poverty. The results are robust to different model specifications and measures of chronic poverty and are more pronounced for poorer countries. Our findings offer relevant inputs into current efforts to fight climate change

Does hotter temperature increase poverty and inequality? Global evidence from subnational data analysis

Despite a vast literature documenting the harmful effects of climate change on various socioeconomic outcomes, little evidence exists on the global impacts of hotter temperature on poverty and inequality. Analysis of a new global panel dataset of subnational poverty in 134 countries finds that a one-degree Celsius increase in temperature leads to a 9.1 percent increase in poverty, using the US$1.90 daily poverty threshold. A similar increase in temperature causes a 1.4 percent increase in the Gini inequality index. The paper also finds negative effects of colder temperature on poverty and inequality. Yet, while poorer countries—particularly those in South Asia and Sub-Saharan Africa—are more affected by climate change, household adaptation could have mitigated some adverse effects in the long run. The findings provide relevant and timely inputs for the global fight against climate change as well as the current policy debate on the responsibilities of richer countries versus poorer countries

Country statistical capacity: a recent assessment tool and further reflections on the way forward

A country's statistical capacity takes an indispensable part in its development. We offer a comprehensive comparison between the World Bank's Statistical Performance Indicators and Index (SPI) and its predecessor, the Statistical Capacity Index (SCI) regarding different conceptual and empirical aspects. We further examine the relationships of the two indexes with some agriculture development indicators such as food security, food sustainability and productivity as well as other key indicators including headcount poverty, GDP per capita, and an SDG progress index. Our analysis employs the latest SPI data update in 2022, which were not available in previous studies. We also propose clear guidelines on how the SPI can be maintained and updated in the future to ensure that this process is transparent, replicable, safeguarded with high quality, and provides comparable data over time

Poverty dynamics for Ghana during 2005/06–2016/17: an investigation using synthetic panels

Ghana has consistently kept its poverty rate lower than the regional average over the past 25 years, but this positive trend has slowed down recently. Without actual panel data, it would be next to impossible to probe into the dynamic patterns beneath this trend. We offer the first study that examines the dynamics of overall, moderate, and extreme poverty in Ghana during 2005/06–2016/17, addressing the lack of actual panel data by constructing synthetic panel data from three nationally representative cross-sectional rounds of the Ghana Living Standards Surveys (GLSSs). We present a well-defined decomposition framework, which allows us to examine a rich profile of the dynamics among different population groups. Beyond poverty analysis, we further investigate the dynamics of the full consumption expenditure distribution. Although we find considerable conditional chronic (extreme) poverty rates hovering around 50–60%, there was more upward mobility than downward mobility during this period. Poor households were also more likely to have stronger consumption expenditure growth. The findings suggest that factors such as educational attainment, female household headship, urban residence, and nonagricultural work are positively correlated with poverty reduction. Compared to all other correlates, educational attainment appears to be the most effective in pushing households out of poverty and keeping them from falling into poverty. These results contribute to the growing literature on poverty dynamics in developing countries in general and provide new and relevant inputs for policy advice in Ghana in particular, especially since policies that address chronic poverty typically differ from those that tackle transient poverty

Life satisfaction, subjective wealth, and adaptation to vulnerability in the Russian Federation during 2002-2019

We offer the first study on vulnerability adaptation to subjective well-being, using rich panel data over the past two decades for Russia. We found no adaption to vulnerability for life satisfaction and subjective wealth, with longer vulnerability spells associated with more negative subjective welfare. Some evidence indicates that despite little differences between urban and rural areas in life satisfaction, rural areas exhibit a more robust lack of adaptation for subjective wealth, particularly for longer durations of vulnerability. More education generally indicates a stronger lack of adaptation for life satisfaction, but similar levels of adaptation for subjective wealth

Does Sorting Matter for Learning Inequality? Evidence from East Africa

Inequalities in children’s learning are widely recognized to arise from variations in both household and school-related factors. While few studies have considered the role of sorting between schools and households, even fewer have quantified how much sorting contributes to educational inequalities in low- and middle-income countries. We fill this gap using data on over 1 million children from three East African countries. Applying a novel variance decomposition procedure, our results indicate that sorting of pupils across schools accounts for at least 8 percent of the total test-score variance, equivalent to half a year of schooling or more. This contribution tends to be largest for children from families at the ends of the socio-economic spectrum. Empirical simulations of steady-state educational inequalities reveal that policies to mitigate the consequences of sorting could substantially reduce inequalities in education

Does the COVID-19 Pandemic Disproportionately Affect the Poor? Evidence from a Six-Country Survey

The COVID-19 pandemic has wrought havocs on economies around the world. Yet, much needs to be learnt on the distributional impacts of the pandemic. We contribute new theoretical and empirical evidence on the distributional impacts of the pandemic on different income groups in a multi-country setting. Analyzing rich individual-level data from a six-country survey, we find that while the outbreak has no impacts on household income losses, it results in a 63-percent reduction in the expected own labor income for the second-poorest income quintile. The impacts of the pandemic are most noticeable in terms of savings, with all the four poorer income quintiles suffering reduced savings ranging between 5 and 7 percent compared to the richest income quintile. The poor are also less likely to change their behaviors, both in terms of immediate prevention measures against COVID-19 and healthy activities. We also find countries to exhibit heterogeneous impacts. The United Kingdom has the least household income loss and expected labor income loss, and the most savings. Japanese are least likely to adapt behavioral changes, but Chinese, Italians, and South Koreans wash their hands and wear a mask more often than Americans

Decomposing Learning Inequalities in East Africa: How Much Does Sorting Matter?

Inequalities in learning opportunities arise from both household- and school-related factors. Although these factors are unlikely to be independent, few studies have considered the extent to which sorting between schools and households might aggravate educational inequalities. To fill this gap, this article presents a novel variance decomposition, which is then applied to data from over one million children from East Africa. Results indicate that sorting accounts for around 8 percent of the test-score variance, similar in magnitude to the contribution of differences in school quality. Empirical simulations of steady-state educational inequalities reveal that policies to mitigate sorting could substantially reduce educational inequalities over the long run

The spatio-temporal distribution of acute encephalitis syndrome and its association with climate and landcover in Vietnam.

BackgroundAcute encephalitis syndrome (AES) differs in its spatio-temporal distribution in Vietnam with the highest incidence seen during the summer months in the northern provinces. AES has multiple aetiologies, and the cause remains unknown in many cases. While vector-borne disease such as Japanese encephalitis and dengue virus and non-vector-borne diseases such as influenza and enterovirus show evidence of seasonality, associations with climate variables and the spatio-temporal distribution in Vietnam differs between these. The aim of this study was therefore to understand the spatio-temporal distribution of, and risk factors for AES in Vietnam to help hypothesise the aetiology.MethodsThe number of monthly cases per province for AES, meningitis and diseases including dengue fever; influenza-like-illness (ILI); hand, foot, and mouth disease (HFMD); and Streptococcus suis were obtained from the General Department for Preventive Medicine (GDPM) from 1998-2016. Covariates including climate, normalized difference vegetation index (NDVI), elevation, the number of pigs, socio-demographics, JEV vaccination coverage and the number of hospitals were also collected. Spatio-temporal multivariable mixed-effects negative binomial Bayesian models with an outcome of the number of cases of AES, a combination of the covariates and harmonic terms to determine the magnitude of seasonality were developed.ResultsThe national monthly incidence of AES declined by 63.3% over the study period. However, incidence increased in some provinces, particularly in the Northwest region. In northern Vietnam, the incidence peaked in the summer months in contrast to the southern provinces where incidence remained relatively constant throughout the year. The incidence of meningitis, ILI and S. suis infection; temperature, relative humidity with no lag, NDVI at a lag of one month, and the number of pigs per 100,000 population were positively associated with the number of cases of AES in all models in which these covariates were included.ConclusionsThe positive correlation of AES with temperature and humidity suggest that a number of cases may be due to vector-borne diseases, suggesting a need to focus on vaccination campaigns. However, further surveillance and research are recommended to investigate other possible aetiologies such as S. suis or Orientia tsutsugamushi

Varied patterns of catch-up in child growth: Evidence from Young Lives

The development of human capabilities for many disadvantaged children around the world depends on growth recovery ('catch-up growth'). Here we develop a novel framework that allows different types of catch-up growth to be classified and estimated. We distinguish between catch-up in the mean of a group toward that of a healthy reference population versus catch-up within the group. We show these different growth types can be tested in a unified setting using a latent growth framework. We apply the results to four developing countries, using longitudinal data on 7641 children collected over the period 2002-2013. The results show catch-up growth rates are generally modest but vary significantly between countries, and that local environmental factors are material to variation in child growth trajectories. The paper discusses the benefits of the new framework versus current methods, shows that the method is feasible, and suggests they call for intervention designs that are sensitive to community and country contexts