Research
Working Papers
The COVID-19 pandemic has had catastrophic economic and human consequences worldwide. This paper tries to quantify the consequences of the pandemic on global inequality and poverty in 2020. Since face-to-face household survey data collection largely came to a halt during the pandemic, a combination of data sources is used to estimate the impacts on poverty and inequality. This includes actual household survey data, where available, high-frequency phone surveys, and country-level estimates from the literature on the impact of the pandemic on poverty and inequality. The results suggest that the world in 2020 witnessed the largest increase to global inequality and poverty since at least 1990. This paper estimates that COVID-19 increased the global Gini index by 0.7 point and global extreme poverty (using a poverty line of $2.15 per day) by 90 million people compared to counterfactual without the pandemic. These findings are primarily driven by country-level shocks to average incomes and an increase in inequality between countries. Changes to inequality within countries were mixed and relatively modest.
Publications
Assessing the Impact of the 2017 PPPs on the International Poverty Line and Global Poverty, with Dean Jolliffe, Christoph Lakner, Aziz Atamanov, and Samuel Kofi Tetteh Baah. World Bank Economic Review, forthcoming.
Purchasing power parity exchange rates (PPPs) are used to estimate the international poverty line (IPL) in a common currency and account for relative price differences across countries when measuring global poverty. This paper assesses the impact of the 2017 PPPs on the nominal value of the IPL and global poverty. The analysis indicates that updating the $1.90 IPL in 2011 PPP dollars to 2017 PPP dollars results in an IPL of approximately $2.15—a finding that is robust to various methods and assumptions. Based on an updated IPL of $2.15, the global extreme poverty rate in 2017 falls from the previously estimated 9.3 to 9.1 percent, reducing the count of people who are poor by 15 million. This is a modest change compared with previous updates of PPP data. The paper also assesses the methodological stability between the 2011 and 2017 PPPs, scrutinizes large changes at the country level, and analyzes higher poverty lines with the 2017 PPPs.
Ending extreme poverty has a negligible impact on global greenhouse gas emissions, with Philip Wollburg and Stephane Hallegatte, Nature, 2023.
Growing consumption is both necessary to end extreme poverty and one of the main drivers of greenhouse gas emissions, creating a potential tension between alleviating poverty and limiting global warming. Most poverty reduction has historically occurred because of economic growth, which means that reducing poverty entails increasing not only the consumption of people living in poverty but also the consumption of people with a higher income. Here we estimate the emissions associated with the economic growth needed to alleviate extreme poverty using the international poverty line of US $2.15 per day. Even with historical energy- and carbon-intensity patterns, the global emissions increase associated with alleviating extreme poverty is modest, at 2.37 gigatonnes of carbon dioxide equivalent per year or 4.9% of 2019 global emissions. Lower inequality, higher energy efficiency and decarbonization of energy can ease this tension further: assuming the best historical performance, the emissions for poverty alleviation in 2050 will be reduced by 90%. More ambitious poverty lines require more economic growth in more countries, which leads to notably higher emissions. The challenge to align the development and climate objectives of the world is not in reconciling extreme poverty alleviation with climate objectives but in providing sustainable middle-income standards of living.
Intergenerational Mobility around the World: A New Database, with Roy van der Weide, Christoph Lakner, Ambar Narayan, and Rakesh Ramasubbaiah, Journal of Development Economics, 2023.
Using individual data from over 400 surveys, this paper compiles a global database of intergenerational mobility in education for 153 countries covering 97 percent of the world’s population. For 87 percent of the world’s population, it provides trends in intergenerational mobility for individuals born between 1950 to 1989. The findings show that absolute mobility in education—the share of respondents that obtains higher levels of education than their parents—is higher in the developed world despite the higher levels of parental educational attainment. Relative mobility—measuring the degree of independence between parent and child years of schooling—is also found to be greater in the developed world. Together, these findings point to severe challenges in intergenerational mobility in the poorest parts of the world. Beyond national income levels, the paper explores the correlation between intergenerational mobility and a variety of country characteristics. Countries with higher rates of mobility have (i) higher tax revenues and rates of government expenditures, especially on education; (ii) better child health indicators (less stunting and lower infant mortality); (iii) higher school quality (more teachers per pupil and fewer school dropouts); and (iv) less residential segregation.
What Makes Public Sector Data Valuable for Development? with Dean Jolliffe, Malar Veerappan, Talip Kilic, and Philip Wollburg, World Bank Research Observer, 2023.
Data produced by the public sector can have transformational impacts on development outcomes through better targeting of resources, improved service delivery, cost savings in policy implementation, increased accountability, and more. Around the world, the amount of data produced by the public sector is increasing at a rapid pace, yet their transformational impacts have not been realized fully. Why has the full value of these data not been realized yet? This paper outlines 12 conditions needed for the production and use of public sector data to generate value for development and presents case studies substantiating these conditions. The conditions are that data need to have adequate spatial and temporal coverage (are complete, frequent, and timely), are of high quality (are accurate, comparable, and granular), are easy to use (are accessible, understandable, and interoperable), and are safe to use (are impartial, confidential, and appropriate).
The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees and Forests, with Paolo Brunori and Paul Hufe, Scandinavian Journal of Economics, 2023.
We propose a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. In particular, we illustrate how these methods represent a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, they minimize the risk of arbitrary and ad-hoc model selection. Second, they provide a standardized way of trading off upward and downward biases in inequality of opportunity estimations. Finally, regression trees can be graphically represented; their structure is immediate to read and easy to understand. This will make the measurement of inequality of opportunity more easily comprehensible to a large audience. These advantages are illustrated by an empirical application based on the 2011 wave of the European Union Statistics on Income and Living Conditions.
Free to Choose or Free to Lose? Understanding Individual Attitudes towards Paternalism? With David Dreyer Lassen, Behavioral Public Policy, 2022.
In the past decades, behavioral economics has credibly identified numerous decision-making biases leading people to make choices they would not have made if better informed about the long-term consequences of their actions. This has given rise to a new reason for government interventions: internalities. In contrast to traditional reasons for government intervention, such as redistribution and externalities, overcoming internalities often involves the use of paternalistic policies. We investigate theoretically and empirically the formation of attitudes towards paternalistic policies. Theoretically, we focus on the role of self-interest and distinguish between self-interest as construed for the rational decision-maker, self-interest when self-control problems are present, and self-interest when procedural or expressive elements, such as autonomy, matter. Empirically, we employ two novel data sets: a Danish survey on political opinion combined with administrative data on actual behavior and a large-scale cross-country survey to analyze attitudes towards paternalistic policies in the health and financial domains. We show that targets of paternalism are more opposed to paternalism than non-targets both in Denmark and across nine Western democracies, and rely on our theoretical priors to explore mechanisms that can explain these attitudes.
Nowcasting Global Poverty, with Andres Castaneda and David Newhouse, World Bank Economic Review, 2022.
Timely and comparable poverty estimates are vital to assess countries’ development progress and track the first Sustainable Development Goal, to end extreme poverty by 2030. Yet timely and comparable estimates of poverty are lacking. For these reasons, initiatives that reliably and cost-effectively predict what the poverty rate is today (i.e., nowcasting) are crucial for informed high-level decision-making. In this paper, we discuss how to leverage large-scale datasets, such as the World Development Indicators, and statistical learning techniques to improve the accuracy of the World Bank’s current poverty nowcasts. We apply these techniques and dataset to predict growth in mean welfare, and back out poverty rates by applying the predicted growth rates equally to all households in the last observed distribution. This is in line with how the World Bank’s current nowcasts work. We find only minor gains in prediction accuracy but that progress in reducing global poverty is slower than current estimates indicate. Predicting headcount rates directly, rather than through growth in mean welfare, considerably reduces prediction accuracy. Prediction accuracy would be greatly improved if it were possible to accurately predict both growth in mean welfare and growth in the Gini coefficient
How Much Does Reducing Inequality Matter for Global Poverty? With Christoph Lakner, Mario Negre & Espen Prydz, Journal of Economic Inequality, 2022.
The goals of ending extreme poverty by 2030 and working towards a more equal distribution of incomes are part of the United Nations’ Sustainable Development Goals. Using data from 166 countries comprising 97.5% of the world’s population, we simulate scenarios for global poverty from 2019 to 2030 under various assumptions about growth and inequality. We use different assumptions about growth incidence curves to model changes in inequality, and rely on a machine-learning algorithm called model-based recursive partitioning to model how growth in GDP is passed through to growth as observed in household surveys. When holding within-country inequality unchanged and letting GDP per capita grow according to World Bank forecasts and historically observed growth rates, our simulations suggest that the number of extreme poor (living on less than $1.90/day) will remain above 600 million in 2030, resulting in a global extreme poverty rate of 7.4%. If the Gini index in each country decreases by 1% per year, the global poverty rate could reduce to around 6.3% in 2030, equivalent to 89 million fewer people living in extreme poverty. Reducing each country’s Gini index by 1% per year has a larger impact on global poverty than increasing each country’s annual growth 1 percentage points above forecasts. We also study the impact of COVID-19 on poverty and find that the pandemic may have driven around 60 million people into extreme poverty in 2020. If the virus increased the Gini by 2% in all countries, then more than 90 million may have been driven into extreme poverty in 2020.
Lives and Livelihoods: Estimates of the Global Mortality and Poverty Effects of the Covid-19 Pandemic, with Benoit Decerf, Francisco Ferreira, and Olivier Sterck, World Development, 2021.
This paper evaluates the global welfare consequences of increases in mortality and poverty generated by the Covid-19 pandemic. Increases in mortality are measured in terms of the number of years of life lost (LY) to the pandemic. Additional years spent in poverty (PY) are conservatively estimated using growth estimates for 2020 and two different scenarios for its distributional characteristics. Using years of life as a welfare metric yields a single parameter that captures the underlying trade-off between lives and livelihoods: how many PYs have the same welfare cost as one LY. Taking an agnostic view of this parameter, estimates of LYs and PYs are compared across countries for different scenarios. Three main findings arise. First, as of early June 2020, the pandemic (and the observed private and policy responses) has generated at least 68 million additional poverty years and 4.3 million years of life lost across 150 countries. The ratio of PYs to LYs is very large in most countries, suggesting that the poverty consequences of the crisis are of paramount importance. Second, this ratio declines systematically with GDP per capita: poverty accounts for a much greater share of the welfare costs in poorer countries. Finally, the dominance of poverty over mortality is reversed in a counterfactual “herd immunity” scenario: without any policy intervention, LYs tend to be greater than PYs, and the overall welfare losses are greater.
Death and Destitution: The Global Distribution of Welfare Losses from the COVID-19 Pandemic, with Benoit Decerf, Francisco Ferreira, and Olivier Sterck, LSE Public Policy Review, 2021.
The Covid-19 pandemic has brought about massive declines in wellbeing around the world. This paper seeks to quantify and compare two important components of those losses – increased mortality and higher poverty – using years of human life as a common metric. We estimate that almost 20 million life-years were lost to Covid-19 by December 2020. Over the same period and by the most conservative definition, over 120 million additional years were spent in poverty because of the pandemic. The mortality burden, whether estimated in lives or in years of life lost, increases sharply with GDP per capita. The poverty burden, on the contrary, declines with per capita national incomes when a constant absolute poverty line is used, or is uncorrelated with national incomes when a more relative approach is taken to poverty lines. In both cases the poverty burden of the pandemic, relative to the mortality burden, is much higher for poor countries. The distribution of aggregate welfare losses – combining mortality and poverty and expressed in terms of life-years – depends both on the choice of poverty line(s) and on the relative weights placed on mortality and poverty. With a constant absolute poverty line and a relatively low welfare weight on mortality, poorer countries are found to bear a greater welfare loss from the pandemic. When poverty lines are set differently for poor, middle and high-income countries and/or a greater welfare weight is placed on mortality, upper-middle and rich countries suffer the most.
Equality of Opportunity in Four Measures of Well-Being, with Xavi Ramos, Review of Income and Wealth, 2019.
A growing literature has tried to measure the extent to which individuals have equal opportunities to acquire income. At the same time, policymakers have doubled down on efforts to go beyond income when designing policies to enhance well‐being. We attempt to bridge these two areas by measuring the extent to which individuals have equal opportunities to achieve a high level of well‐being. We use the German Socio‐Economic Panel to measure well‐being in four different ways, including incomes. This makes it possible to determine if the way in which well‐being is measured matters for identifying who the opportunity‐deprived are and for tracking inequality of opportunity over time. We find that, regardless of how well‐being is measured, the same people are opportunity‐deprived and equality of opportunity has improved over the past 10 years. This suggests that going beyond income has little relevance if the objective is to provide equal opportunities.