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July 2018

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.

What do private companies look for in a performance-based non-revenue water project?

Jemima Sy's picture



Recent estimates
place global annual non-revenue water (NRW), i.e. water produced but not billed because of commercial or physical losses, at 126 billion cubic meters. This translates to nearly $40 billion in annual losses on waste and foregone revenues—a sum, that even if a fraction could be recovered, would underpin a compelling market opportunity for private service companies and a boost to public water utilities’ sustainability.

A new joint initiative is aiming to drive declines in NRW faster, cheaper, and more sustainably by assisting water utilities to engage private companies in performance-based contracts (PBCs). The World Bank’s Public-Private Infrastructure Advisory Facility (PPIAF) and the Bank’s Water Global Practice, in partnership with the International Water Association, analyzed 43 projects and determined that NRW initiatives supported by PBCs are 68 percent more effective compared to those undertaken by utilities alone, (see for example, Using Performance Based Contracts to Reduce NRW) and are systematically faster at reducing the rate of loss.

Delivering quality health services: A patient’s perspective

Cecilia Rodríguez's picture

The vignette below was originally published in a new joint report from the World Bank, WHO and OECD, Delivering quality health services: A global imperative for universal health coverage.  

Eight years ago, when she was diagnosed with rheumatoid arthritis, an autoimmune disease that causes inflammation, swelling and acute pain in the joints, Cecilia Rodriguez was Director of a primary health care facility. “I had very bad rheumatoid arthritis and spent a lot of time in bed,” says Rodriguez, who was in her thirties when she first experienced the painful symptoms. “I realized that what I had been promoting as a health administrator was very different from what I needed as a patient.” 

Water flows from the spring of Kyrgyzstan’s snowy mountains

Bolormaa Amgaabazar's picture
Togotoi is a small mountainous village in the south of the Kyrgyz Republic. Last month, some colleagues and I traveled there to participate in a ceremony to mark the opening of a newly-built water supply system. Mr. Askarov, Vice-Prime Minister of the Kyrgyz Republic and Mr. Sarybashov, Governor of Osh Oblast, opened the celebrations, signifying the high importance of this event for the local population.

The new water supply system at Togotoi is the first project to become operational under the Government’s National Rural Drinking Water Supply Program, which was launched last year and was called “Ala-Too Bulagy” – meaning “spring of snowy mountains.”
Togotoi villagers and school children celebrate the opening of their new water system.

Face to face with William Maloney, Chief Economist, Equitable Finance and Institutions

Nandita Roy's picture

Returns on technological adoption are thought to be extremely high, yet developing countries appear to invest little, implying that this critical channel of productivity growth is underexploited. A recent World Bank study – The Innovation Paradox: Developing-Country Capabilities and the Unrealized Promise of Technological Catch-Up – sheds light on how to address this paradox. In this interview, William Maloney Chief Economist, Equitable Finance and Institutions Practice Group, World Bank Group, calls upon developing country public and private-sector leaders to pursue a more focused approach to innovation policy.



What is the new study Innovation Paradox all about?

The potential gains from bringing existing technologies to developing countries are vast, much higher for poor countries than for rich countries. Yet developing-country firms and governments invest relatively little to realize this potential. That’s the origin of what we are calling ‘The Innovation Paradox’.

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Why do firms in developing countries lag behind when it comes to innovation?

The Innovation Paradox, argues that developing country firms choose not to invest heavily in adopting technology, even if they are keen to do so, because they face a range of constraints that prevent them from benefitting from the transfer.

Developing country firms are often constrained by low managerial capability, find it difficult to import the necessary technology, to contract or hire trained workers and engineers, or draw on the new organizational techniques needed to maximize the potential of innovation. Moreover, they are often inhibited by a weak business climate. For example, small and medium enterprises (SMEs) are constantly in a situation where they are putting out fires, they don’t have a five-year plan, they don’t have somebody keeping track of what new technology has come out of some place that they could bring to the firm.

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How can developing economies catch up with the developed world on innovation?

The rates of return to investments and innovation of various kinds appear to be extremely high, yet we see a much smaller effort in these areas.  In the developing countries, we need to think not only about barriers to accumulating knowledge capital, we have to think about all the barriers to accumulating all of the complementary factors—the physical capital. So, if I have a lousy education system, it doesn’t matter if I get a high-tech firm because there won’t be any workers to staff it.

Innovation requires competitive and undistorted economies, adequate levels of human capital, functioning capital markets, a dynamic and capable business sector, reliable regulation and property rights. Richer countries tend to have more of these conditions. This is at the root of Paradox. Even though follower countries have much to gain from adopting existing technologies from the advanced countries, in practice, missing and distorted markets, weak management capabilities and human capital prevent them from taking advantage of these opportunities.

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Dominica’s path to resilient recovery after Hurricane Maria

Keren Charles's picture


Located in the warm waters of the Eastern Caribbean, Dominica is no stranger to tropical storms and hurricanes.  Yet Hurricane Maria, which battered Dominica last September, was unlike anything the island nation had ever seen. Packing winds of over 160 miles per hour, the Category 5 hurricane claimed the lives of 30 people and caused total damages and losses exceeding US$1.3 billion.

Socio-Emotional Skills Wanted! – New Big Data Evidence from India

Saori Imaizumi's picture


We all hear about the importance of “socio-emotional skills” when looking for a job. Employers are said to be looking for individuals who are hardworking, meet deadlines, are reliable, creative, collaborative … the list goes on depending on the occupation. In recent years, it seems, these skills have become equally important as technical skills. But do employers really care about these soft skills when hiring? If so, what type of personality do they favor?

New country classifications by income level: 2018-2019

World Bank Data Team's picture

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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