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Global Findex 2017 microdata available for download

Leora Klapper's picture
We're thrilled to release the 2017 Global Findex microdata, featuring individual survey responses from roughly 150,000 adults globally. Get it here, along with documentation including a variable list, questionnaire, and information on sampling procedures and data weighting.
 
Downloading the data is easy. At the microdata library, you'll see a screen that looks like this:
 

 

The Economic Case for Early Learning

Harry A. Patrinos's picture
Also available in: Español | العربية 

 

Photo credit World Bank

We are living in a learning crisis.  According to the World Bank’s 2018 World Development Report, millions of students in developing countries are in schools that are failing to educate them to succeed in life. According to the UNESCO Institute of Statistics, there are 617 million children and youth of primary and secondary school age who are not learning the basics in reading, two-thirds of whom are attending school. The urgency to invest in learning is clear.

Reducing data collection bias in education research

Kabira Namit's picture
Training for data collectors in Kambia, Sierra Leone. (Photo: Kabira Namit / World Bank)


Collecting data in education can be a tricky business. After spending considerable resources to design a representative study, enlist and train data collectors, and organize the logistics of data collection, we want to ensure that we capture as true a picture of the situation on the ground as possible. This can be particularly challenging when we attempt to measure complex concepts, such as child development, learning outcomes, or the quality of an educational environment.
 
Data can be biased by many factors. For example, the very act of observation by itself can influence behavior. How can we expect a teacher to behave “normally” when outsiders sit in her or his classroom taking detailed notes about everything they do? Social desirability bias, where subjects seek to represent themselves in the most positive light, is another common challenge. Asking a teacher, “Do you hit children in your classroom?” may elicit an intense denial, even if the teacher still has a cane in one hand and the ear of a misbehaving child in another.

Official Statistics in a Post-Truth World

Haishan Fu's picture
Photo Credit:  2018 Edelman Trust Barometer Report

I've been thinking about the role of data and digital technology in today's information landscape. New platforms and technologies have democratized access to much of the world’s knowledge, but they’ve also amplified disinformation that affects public discourse. In this context, the official statistics community plays a critical role in bringing credible, evidence-based information to the public.
 
A “post-truth” society is not an inevitable state of affairs that we must accept; it's an unacceptable state of affairs that we must address. To do so, we need reliable data that are trusted by the public. Institutions like national statistical offices must go beyond their traditional data production remit to become a trusted, visible force for reason in people’s lives by building trust, embracing relevance, and communicating better.

Privacy law and services trade: Resolving the conflict

Aaditya Mattoo's picture

The EU’s new General Data Protection Regulation (GDPR) recently went into effect. You have probably received emails regarding your data resident on email servers and applications. And while the media focus has also remained on data concerns with Facebook and other personal data, the impact of the GDPR on developing countries has received little attention.  Their exports of data-based services rely on the free flow of data across borders. Strengthened regulation can make international data transfers more difficult. And traditional trade rules and regulatory cooperation cannot resolve this conflict.

Event: 50 Years of Measuring World Economies – Wednesday May 23, 2018 at 4pm EST

Nada Hamadeh's picture
Join us live online or in-person on Wednesday at 4pm for "50 Years of Measuring World Economies" event held at the World Bank James D. Wolfensohn Atrium in Washington, DC.
 
The International Comparison Program (ICP) – the world’s largest global data initiative led by the World Bank under the auspices of the United Nations Statistical Commission – is celebrating its 50th anniversary this year. Since the initiation of the ICP as a modest research project at the University of Pennsylvania by Irving Kravis, Alan Heston and Robert Summers in 1968, the Program has grown to cover about 200 countries and 20 global, regional and sub-regional agencies.
 

To commemorate this milestone, World Bank Group Chief Executive Officer Kristalina Georgieva, 2015 Nobel Laureate in economics Sir Angus Deaton, and Georgetown University Provost Robert M. Groves will come together at an event to discuss the challenges and opportunities for investing in evidence for sustainable development. In addition, Lawrence H. Summers, the 71st Secretary of the US Treasury and son of ICP co-founder Robert Summers, will share a recorded tribute. A video produced by the World Bank for the occasion will showcase the history and impact of the ICP.

Survey specialists and data scientists meet: machine learning to measure a person’s height from a picture.

Michael M. Lokshin's picture
A test subject holding a reference image and a silhouette derived from the photo by Tensorflow/DeepLab semantic image segmentation model.

Human body measurements are used to evaluate health trends in various populations. We wanted a simple way to reliably measure someone’s height as part a field interview, using a photo of them holding a reference object. We’ve developed an approach and would highlight two things we learned during the process:

  • With an iteratively refined method, it’s possible to get a measure of someone’s height accurate to 1% from a well-composed image of them holding a calibrated paper printout. We plan to integrate this functionality in to the free World Bank Survey Solutions CAPI tool.

  • We found working with an in-house team of survey specialists and data scientists the best way to tackle this problem. It’s only when we combined our domain knowledge and field experience with our data science skills and a healthy dose of creative problem solving, were we able to develop a working prototype.

It’s time to improve the ‘Value for Money’ toolkit, and not junk it

Suvojit Chattopadhyay's picture

 Julio Pantoja / World BankThe ‘results agenda’ of donor agencies have inspired several heated debates. Value for money is one of the main tools that helps further this agenda. There is significant pressure on donor development agencies to ‘demonstrate’ what they have achieved (results), and further, examine whether these results have been achieved in a cost-effective manner (‘value for money’). This pressure to demonstrate ‘value for money’ often leads to plenty of frustration, as those designing and implementing aid programmes struggle to strike a balance between what is easy to prove versus the complex nature of an intervention designed to tackle a real-world problem.

There are several problems with the results agenda – development interventions take place in a wide range of contexts, that lend themselves to comparisons on some counts and not, on others. These contexts change every day, and certainly over the lifetime of a development project, and attempting a grand theory or mathematical formulae to capture the entire process is nearly impossible.

Besides technical problems, there are valid fears that focusing too closely on ‘value for money’ will lead development workers to focus on ‘bean-counting’ and preferring interventions that can be easily measured and whose costs and benefits are easy to estimate. Some researchers have gone further and argued that an obsession with such metrics essentially forces development workers into lying about how their projects actually work.

Toward a linked and inclusive economy

Jim Yong Kim's picture
The arrival of broadband internet is set to significantly improve medical services in Tonga. © Tom Perry/World Bank.
The arrival of broadband internet is set to significantly improve medical services in Tonga. © Tom Perry/World Bank.

While some studies predict automation to eliminate jobs at a dizzying rate, disruptive technologies can also create new lines of work. Our working draft of the forthcoming 2019 World Development Report, The Changing Nature of Work, notes that in the past century robots have created more jobs than they have displaced. The capacity of technology to exponentially change how we live, work, and organize leaves us at the World Bank Group constantly asking: How can we adapt the skills and knowledge of today to match the jobs of tomorrow?
 
One answer is to harness the data revolution to support new pathways to development. Some 2.5 quintillion bytes of data are generated every day from cell phones, sensors, online platforms, and other sources. When data is used to help individuals adapt to the technology-led economy, it can make a huge contribution toward ending extreme poverty and inequality. Technology companies, however well intended, cannot do this alone.

To close the gap in women’s land rights, we need to do a better job of measuring it

M. Mercedes Stickler's picture
A woman holding her land certificate in rural Zambia. © Jeremy Green
A woman holding her land certificate in rural Zambia. © Jeremy Green

There is broad global agreement that secure property rights help eradicate poverty and that securing women’s land rights reduces gender inequality. But our understanding remains strikingly limited when it comes to the extent to which women’s land rights are – or are not – secure and the impact of women’s tenure security (or lack thereof) on women’s empowerment.

This is true even in Africa, where the most studies have been published, due to shortcomings in both the quality and quantity of research on these questions.


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