“A New Distribution Sensitive Index for Measuring Welfare, Poverty, and Inequality.” World Bank Policy Research working paper; no. WPS 10470; RRR Washington, D.C.: World Bank Group. June 2023. (with Kraay, Lakner, Ozler, Decerf, Jolliffe, Sterck). -- under review --
Abstract: Simple welfare indices such as mean income are ubiquitous but not distribution sensitive. In contrast, existing distribution sensitive welfare indices are rarely used, often because they are difficult to explain and/or lack intuitive units. This paper proposes a simple new distribution sensitive welfare index with intuitive units: the average factor by which individual incomes must be multiplied to attain a given reference level of income. This new index is subgroup decomposable with population weights and satisfies the three main definitions of distribution sensitivity in the literature. Variants on this index can be used as distribution sensitive poverty measures and as inequality measures, with the same simple intuitive units. The properties of the new index are illustrated using the global distribution of income across individuals between 1990 and 2019, as well as with selected country comparisons. Finally, the index can be used to define the “prosperity gap” as a proposed new measure of “shared prosperity,” one of the twin goals of the World Bank.
Technical blog: Can we have a welfare index that is easy to understand but also distribution sensitive? June 2023. World Bank Development Impact Blog. [Link]
Blog on shared prosperity: The prosperity gap: A proposed new indicator to monitor shared prosperity. June 2023. Let’s Talk Development Blog. [Link]
“The Impact of COVID-19 on Global Inequality and Poverty.” World Bank Policy Research working paper; no. WPS 10198; RRR Washington, D.C.: World Bank Group. October 2022. (with Daniel Mahler, Christoph Lakner).
Abstract: 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.
Blog: End of an Era of Global Income Convergence. October 2022. World Bank Data Blog. [Link]
"Covid-19 and Economic Inequality: Short-term impacts with Long-term Consequences" World Bank Policy Research Working Paper WPS9902. January 2022. (with A. Narayan et al.)
Abstract: This paper examines the short-term implications of the COVID-19 pandemic for inequality in developing countries. The analysis takes advantage of high-frequency phone survey data collected by the World Bank to assess the distributional impacts of the pandemic through the channels of job and income losses, food insecurity, and children’s education in the early days of the pandemic and subsequent period of economic recovery leading up to early 2021. It also introduces a methodology for estimating changes in income inequality due to the pandemic by combining data from phone surveys, pre-pandemic household surveys, and macroeconomic projections of sectoral growth rates. The paper finds that the pandemic had dis-equalizing impacts both across and within countries. Even under the assumption of distribution-neutral impacts within countries, the projected income losses are estimated to be higher in the bottom half of the global income distribution. Within countries, disadvantaged groups were more likely to have experienced work and income losses initially and are recovering more slowly. Inequality simulations suggest an increase in the Gini index for 29 of 34 countries in the sample, with an average increase of about 1 percent. Although these short-term impacts on inequality appear to be small, they suggest that projections of global poverty and inequality impacts of COVID-19 under the assumption of distribution-neutral changes within countries are likely to underestimate actual impacts. Finally, the paper argues that the overall inequality impacts of COVID-19 could be larger over the medium-to-long term on account of a slow and uneven recovery in many developing countries, and disparities in learning losses during pandemic-related school closures, which will likely have long-lasting effects on inequality of opportunity and social mobility.
"What do we know about poverty in India 2017/18?" World Bank Policy Research Working Paper WPS9931. February 2022. (with I. N. Edochie, S. Frejie-Rodriguez, C. Lakner, L. L. M. Herrera, D. Newhouse, S. Roy) -- under review --
Abstract: This paper nowcasts poverty in India, one of the countries with the largest population below the international poverty line of $1.90. because the latest official household survey dates back to 2011/12, there is considerable uncertainty over the recent poverty trends in the country. Applying a pass-through and survey-to-survey methodology, extreme poverty (at the $1.90-a-day poverty line) for India in 2017 is estimated at 10.4 percent with a confidence interval of [8.1, 11.3]. The urban and rural poverty rates are estimated at 7.2 and 12.0 percent, respectively. The paper finds no evidence of an increase in poverty between 2011/12 and 2017/18, which is corroborated by a wide range of indicators.
"State Capacity and Civil Conflict: Evidence from the Decade-long Civil War in Nepal."
[link to the paper (version October 2020)]
Abstract: Utilizing the Civil War in Nepal which lasted from 1996 to 2006, this paper addresses two issues: First, civil conflicts predominantly occur in weak states, which are states that lack state capacity, however, it is unclear why not all weak states experience civil conflict. Second, political stability and unequal distribution of resources are opposing forces that are unlikely to coexist together. Nevertheless, cross-country literature on civil conflict finds little relationship between conflict and the unequal distribution of resources. I use an exogenous shock---the massacre of the King and ten other members of the royal family in 2001---to identify the variation in conflict before and after 2001. Whereas the conflict in Nepal was isolated and sparse in the pre-2001 period, it immediately escalated and became more pervasive in the aftermath of the massacre. Employing a difference-in-differences framework, by comparing the Maoist insurgency in Nepal with that in India, I find a six-fold increase in conflict outcomes in the period after the massacre relative to the period before. While the massacre provided the opportunity for conflict, mass armed conflict would have been unlikely without a motive. In the post-massacre period, I find that conflict outcomes doubled in districts with unequal distribution of land relative to more equal districts.
"Assortative Mating and Labor Income Inequality: Evidence from Fifty Years of Coupling in the U.S." SocArXiv. June 2020.
Abstract: Labor income inequality among couples has increased by 33 percent in the U.S. over the past half-century. Over the same period, the correlation of labor income within couples has also increased sharply. Is this increase in sorting over labor income a cause for the rise of labor income inequality among couples? Using the March supplement of the CPS, first, I find that there has been a sharp increase in positive sorting over labor income in the U.S. in the 1970-2018 period. The top decile of men’s earners married to the top decile of women’s earners has doubled from 10.6 percent in 1970 to 23.3 percent in 2018. Second, I use a bounded copula framework as a reference distribution to track the relative changes in labor income inequality among couples. Using this framework, I find that positive sorting over labor income did play a role in increasing labor income inequality among couples in the 1970-1990 period; however, I find little evidence to suggest that this relationship existed in the 1990-2018 period.
Stone Center working paper: https://stonecenter.gc.cuny.edu/research/assortative-mating-and-labor-income-inequality-evidence-from-fifty-years-of-coupling-in-the-u-s/