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The World Region

Behind Closed Doors: how traditional measures of poverty mask inequality inside the household and a new look at possible solutions

Caren Grown's picture

During the days coming up to, and after October 17, when many stories, numbers, and calls for action will mark the International Day for the Eradication of Poverty, we want to invite you to think for a second on what you imagine a poor household to be like. Is this a husband, wife, and children, or maybe an elderly couple? Are the children girls or boys? And more importantly, do all experience the same deprivations and challenges from the situation they live in?  In a recent blog post and paper, we showed that looking at who lives in poor homes—from gender differences to household composition more broadly—matters  to better understand and tackle poverty.

Globally, female and male poverty rates—defined as the share of women and men who live in poor households—are very similar (12.8 and 12.3 percent, respectively, based on 2013 data). Even in the two regions with the largest number of poor people (and highest poverty rates)—South Asia and Sub-Saharan Africa—gender differences in poverty rates are quite small. This is true for the regions, but also for individual countries, irrespective of their share of poor people. Why is that the case? As Chapter 5 of the 2018 Poverty and Shared Prosperity Report explains, our standard monetary poverty indicator is measured by household, not by individual. So, a person is classified as either poor or nonpoor according to the poverty status of the household in which she or he lives. This approach critically assumes everyone in the household shares equally in household consumption—be they a father, a young child, or a daughter-in-law.  By design, it thus masks differences in individual poverty within a household.

Notwithstanding this shortcoming, when we look a bit deeper the information we have today still shows visible gender differences in poverty rates. Take age, for example. We know that there are more poor children than poor adults, and while we do not find that poverty rates differ much between girls and boys at the early stages of life, stark differences appear between men and women during the peak productive and reproductive years.

Incomes of the poorest are growing in 3 of every 4 economies

Maria Ana Lugo's picture

In much of the world today, the incomes of the poor are growing. The World Bank calls this concept shared prosperity, defined as the average annual growth in income or consumption of the poorest 40 percent (the bottom 40) within each country. So, if shared prosperity in a country is positive, the poor are getting richer.

In addition, the shared prosperity premium is defined as the difference between the annual income or consumption growth rate of the bottom 40 and the annual growth rate of the mean in the economy. A positive premium indicates that the bottom 40 are getting a larger share of overall income in the economy.

Global poverty in 2015: PovcalNet’s new estimates and improved documentation

Christoph Lakner's picture

PovcalNet released new poverty estimates last week, indicating that in 2015, 10 percent of the global population were living on less than the international poverty line (IPL), currently set at US$1.90 per person per day in 2011 purchasing power parity (PPP). This estimate is based on a series of new data and revisions, including more than 1,600 household surveys from 164 countries, national accounts, population estimates, inflation data, and purchasing power parity data. The new poverty numbers were released on September 19 and will be part of “Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle,” a report to be published on October 17, End Poverty Day.

We’re also launching a Global Poverty Monitoring Technical Note Series which describes the data, methods and assumptions underpinning the World Bank’s global poverty estimates published in PovcalNet. With this update, we’re releasing four new notes in this series, including the “What’s New” note that will accompany each of the semi-annual updates to PovcalNet. The other notes cover different aspects of the price adjustments embedded in the global poverty estimates, such as adjustments for inflation and price differences across countries

Begun as a research project by Martin Ravallion, Shaohua Chen and others, PovcalNet has become the official source for monitoring the World Bank’s Twin Goals, the Millennium Development Goals (MDG), and now Sustainable Development Goal 1.1. PovcalNet is managed jointly by the Data and Research Groups within the World Bank’s Development Economics Division. It draws heavily upon a strong collaboration with the Poverty and Equity Global Practice, which is responsible for gathering and harmonizing the underlying survey data.

PovcalNet does much more than simply providing the most recent global poverty estimates. It’s a computational tool that allows users to estimate poverty rates for regions, sets of countries or individual countries, over time and at any poverty line. It also provides several distributional measures, such as the Gini index and income shares for the various decile groups.

The most recent PovcalNet data show us that over the last few decades, remarkable progress has been made in reducing extreme poverty. The world attained the first MDG target—cutting the 1990 poverty rate in half by 2015—six years ahead of schedule. With continued reductions, the global poverty rate, defined as the share of world’s population living below the IPL, has dropped from 35.9 percent in 1990 to 10 percent in 2015 – more than a 70 percent reduction.

In the last quarter century, global poverty dropped by more than 70 percent

 

The number of extremely poor people continues to rise in Sub-Saharan Africa

Divyanshi Wadhwa's picture
Also available in: Español | Français | العربية | 中文

Globally, extreme poverty has rapidly declined. New poverty estimates by the World Bank suggest that the number of extremely poor people—those who live on $1.90 a day or less—has fallen from 1.9 billion in 1990 to about 736 million in 2015.

However, the number of people living in extreme poverty is on the rise in Sub-Saharan Africa, comprising more than half of the extreme poor in 2015. Forecasts also indicate that by 2030, nearly 9 in 10 extremely poor people will live in Sub-Saharan Africa. Find more information and the latest poverty estimates at World Bank PovcalNet and Poverty & Equity Data portal.

 

New child and adolescent mortality estimates show remarkable progress, but 17,000 children under 15 still died every day in 2017

Emi Suzuki's picture

This blog is based on new mortality estimates released today by the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME)

There has been remarkable progress in reducing mortality among children and young adolescents in the past several decades. Between 1990 and 2017, the global under-five mortality rate dropped by 58 percent from 93 deaths per 1,000 live births to 39 deaths per 1,000 live births. During the last 17 years, the reduction in under-five mortality rates accelerated to an average 4% annual reduction, compared to an average 1.9% annual reduction between 1990 and 2000. For children aged 5-14, mortality dropped by 53 percent, from 15 deaths to 7 deaths per 1,000 children.

True Demand for Data

Michael M. Lokshin's picture
Headquarters of the United Nations
Photo: Yutaka Nagata (CC BY 2.0)

A snow storm was barreling toward New York City and the roster of attendees at the UN Statistical Committee meeting—myself included—fully expected that all flights would be canceled. Fifty statisticians made the same calculation—to find the closest bar. I headed to the Vienna Café in the UN headquarters building, a place which affords one the rarified opportunity to socialize with high-level government officials from around the world. On my way in, I recognized the Director-General of a statistics office from an African country and we spoke. I mentioned several statistical programs that donors were planning to finance in his country. He expressed enthusiasm about these projects but voiced an increasingly familiar note of concern about long term sustainability of his agency in general. He fretted that his entire statistical office would collapse without donor support. He admitted that most of the demand for data was coming from the donors themselves, as indicators for their own reporting and planning; the country’s own government had much less interest in data or statistics.

Celebrating 50 years of measuring world economies

Edie Purdie's picture

The ICP blog series explores ideas and issues under the International Comparison Program umbrella – including innovations in price and data collection, discussions on purpose and methodology, as well the use of purchasing power parities in the growing world of development data. Authors from across the globe, whether ICP practitioners or researchers making use of ICP data, are encouraged to submit relevant blogs for consideration to [email protected].

A visitor to the World Bank’s atrium on May 23, 2018 would have seen a who’s who of eminent economists and statisticians congregating to celebrate the 50th anniversary of the International Comparison Program. Organized by the Global ICP Unit based in the World Bank in Washington, D.C, a large local, and virtual, audience gathered to hear the thoughts and reflections of major ICP players at the “50 Years of Measuring World Economies” event.

Cured Into Destitution: the risk of financial catastrophe after surgery

Kathryn Wall's picture
Also available in: العربية | Español

Low-income countries face the highest risk of financial catastrophe due to surgery and have made the slowest progress

Five billion people—two thirds of the world’s population—lack access to safe, timely, and affordable surgical, anesthesia, and obstetric (SAO) care, as World Bank Group President Dr. Jim Yong Kim stated. Of the myriad barriers to accessing SAO care—safety, for example, or the lack of a well-trained workforce—one of the largest is financial. For patients, surgery can be very expensive. Not only can the financial burden of seeking surgical care be a formidable obstacle to those who need surgery, it can also have a devastating impact on those who are able to receive it. Over two billion people cannot afford surgery if they needed it today, and, of those who get surgery every year, an estimated 33 million of them will undergo financial hardship from its direct costs—81 million when the ancillary costs of care like transportation and food are included.

Introducing two new dashboards in the Health, Nutrition and Population data portal

Haruna Kashiwase's picture

We’re pleased to launch new dashboards in the Health, Nutrition and Population Portal, following the portal’s revamp last year. The renewed HNP portal has two main dashboards covering Population and Health. Both dashboards are designed to be interactive data visualization tools where users can see various population and health indicators. Users can access various charts and maps by selecting specific time, country or region and indicators. We have added new indicators, charts and new health topics such as Universal Health Coverage and Surgery and Anesthesia. Below are some examples of stories gleaned from our dashboards.

India’s population is projected to surpass that of China around 2022

China, with 1.4 billion people, is the most populous country in the world in 2017. However, India, the second most populous country with 1.3 billion people, is projected to surpass China’s population by 2022. China’s total fertility rate (the number of children per woman) has also declined sharply since the 1970s.

Data quality in research: what if we’re watering the garden while the house is on fire?

Michael M. Lokshin's picture

A colleague stopped me by the elevators while I was leaving the office.

“Do you know of any paper on (some complicated adjustment) of standard errors?”

I tried to remember, but nothing came to mind – “No, why do you need it?”

“A reviewer is asking for a correction.”

I mechanically took off my glasses and started to rub my eyes – “But it will make no difference. And even if it does, wouldn’t it be trivial compared to the other errors in your data?”

“Yes, I know. But I can’t control those other errors, so I’m doing my best I can, where I can.”

This happens again and again — how many times have I been in his shoes? In my previous life as an applied micro-economist, I was happily delegating control of data quality to “survey professionals” — national statistical offices or international organizations involved in data collection, without much interest in looking at the nitty-gritty details of how those data were collected. It was only after I got directly involved in survey work that I realized the extent to which data quality is affected by myriad extrinsic factors, from the technical (survey standards, protocols, methodology) to the practical (a surprise rainstorm, buggy software, broken equipment) to the contextual (the credentials and incentives of the interviewers, proper training and piloting), and a universe of other factors which are obvious to data producers but usually obscure and typically hidden from data users.

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