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Measuring India’s economy using PPPs shows it surpassed France 25 years ago

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].

Earlier this summer, new data published by the World Bank showed that the Gross Domestic Product (GDP) of India had recently surpassed that of France, and that it was on track to overtake the UK economy too. Many news outlets jumped upon this new ranking of India’s economy, now sixth from top. But most media articles did not mention that the World Bank’s other measure, which compares GDP across countries using purchasing power parities (PPPs), has placed India ahead of both France and the UK for the last 25 years.

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.

Why are people dying following surgery in Africa?

Bruce Biccard's picture

Surgery is a core component of health. It is a cost-effective intervention1 which is important for global health.2 However, to fully realize the health benefits of surgery, it needs to be safe. In the African continent—with a population of 1.2 billion people—it is estimated that approximately 95% do not have access to safe and affordable surgery. The Lancet Commission on Global Surgery has established six indicators to indicate the success of providing access to safe and affordable surgery.3 Four of them are included in the World Bank’s World Development Indicators (WDI) database. The perioperative mortality rate (POMR)—the number of in-hospital deaths from any cause in patients who have undergone a procedure done in an operating theatre, divided by the total number of procedures—is one of the indicators the success in achieving safe surgery, yet it is not included in the WDI as the data is sparse, including the one from Africa. The recent publication of the African Surgical Outcomes Study (ASOS) has cast an important light on the POMR in Africa.4

ASOS has shown that for patients in Africa fortunate enough to access surgical care, the patient outcomes following surgery are relatively poor. ASOS demonstrated that African surgical patients were twice as likely to die following surgery when compared to the global average, despite a similar complication rate to the global average (Table 1). This is despite the fact that surgical patients in Africa are relatively healthy when compared with similar international surgical patient cohorts,5 and one would thus expect them to do well postoperatively. Therefore, if the data from ASOS had been risk-adjusted for patient comorbidities, it is likely that the mortality following surgery in Africa is more than twice the global average. The results from ASOS are compelling as they provide comprehensive data on surgical outcomes in Africa, from 25 countries, 247 hospitals, and over 11,000 patients.

Table 1. Mortality, complications and ‘failure to rescue’ following surgery

Source: ISOS International Surgical Outcomes Study ASOS African Surgical Outcomes Study4
  ISOS
(elective surgery)
ASOS
(elective surgery)
ASOS
(elective and emergency surgery)
Mortality 207/44 814 (0.5%) 48/4792 (1.0%) 239/11193 (2.1%)
Complications 7508/44814 (16.8%) 624/4658 (13.4%) 1977/10885 (18.2%)
Death following complication
(failure to rescue)
207/7508 (2.8%) 30/620 (4.8%) 188/1970 (9.5%)

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.

New country classifications by income level: 2018-2019

World Bank Data Team's picture
Also available in: 中文 | Français | العربية | Español

Updated country income classifications for the World Bank’s 2019 fiscal year are available here.

The World Bank assigns the world's economies into four income groups — high, upper-middle, lower-middle, and low. We base this assignment on GNI per capita calculated using the Atlas method. The units for this measure and for the thresholds is current US Dollars.

At the Bank, these classifications are used to aggregate data for groups of similar countries. The income-category of a country is not one of the factors used that influence lending decisions.

Each year on July 1st, we update the classifications. They change for two reasons:

1. In each country, factors such as income growth, inflation, exchange rates, and population change, influence GNI per capita.

2. To keep the dollar thresholds which separate the classifications fixed in real terms, we adjust them for inflation.

The data for the first adjustment come from estimates of 2017 GNI per capita which are now available. This year, the thresholds have moved down slightly because of low price inflation and the strengthening of the US dollar. Click here for information about how the World Bank classifies countries.

Updated Thresholds

New thresholds are determined at the start of the Bank’s fiscal year in July and remain fixed for 12 months regardless of subsequent revisions to estimates. As of July 1 2018, the new thresholds for classification by income are:

Threshold GNI/Capita (current US$)
Low-income < 995
Lower-middle income 996 - 3,895
Upper-middle income 3,896 - 12,055
High-income > 12,055

Changes in Classification

The following countries have new income groups:

Country Old group New group
Argentina Upper-middle High-income
Armenia Lower-middle Upper-middle
Croatia Upper-middle High-income
Guatemala Lower-middle Upper-middle
Jordan Lower-middle Upper-middle
Panama Upper-middle High-income
Syrian Arab Rep. Lower-middle Low-income
Tajikistan Lower-middle Low-income
Yemen Rep. Lower-middle Low-income

The country and lending groups page provides a complete list of economies classified by income, region, and lending status and links to previous years’ classifications. The classification tables include all World Bank members, plus all other economies with populations of more than 30,000. The term country, used interchangeably with economy, does not imply political independence but refers to any territory for which authorities report separate social or economic statistics.

Tables showing 2017 GNI, GNI per capita, GDP, GDP PPP, and Population data are also available as part of the World Bank's Open Data Catalog. Note that these are preliminary estimates and may be revised. For more information, please contact us at [email protected]

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