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A new home for the World Bank’s global poverty and inequality data

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Gif of home page of the Poverty and Inequality Platform

Today sees the beta-launch of the World Bank’s new Poverty and Inequality Platform (PIP), an online analysis tool that provides global, regional, and country-level poverty estimates. PIP combines the information that can be currently accessed through PovcalNet and the Poverty & Equity Data Portal. After the beta-testing phase, we anticipate that PIP will replace the existing websites in March 2022.

PIP was developed by a team drawn from across the World Bank. We hope the new website and features are useful to a wide range of users, including students, journalists, policymakers, and researchers from around the world. As we are now in the beta-testing phase, we are also seeking your help in testing the site. Please send any feedback to

PIP provides several new features which we hope will improve the useability of the World Bank’s poverty and inequality estimates:

First, the website has been completely redesigned to be more user-friendly and intuitive for both researchers and casual data consumers. PIP allows users to visualize data in many ways. This includes line charts for trends over time, bar charts for comparing across countries in the most recent year, and maps of global poverty and inequality. Indicators are easily accessible through clickable options, and users can download the data. By clicking on the “SHARE” button, they are able to share charts via Facebook, Twitter, or Linkedin.

Second, the World Bank’s commitment to open data, transparency, and reproducibility are core elements of PIP. Computations are made available as open-source code written in the R language. The code for all statistical calculations and methodological decisions is available on Github. Anyone around the world can now look at the underlying code, check how global poverty estimates are calculated, and propose improvements.  

Third, we have expanded the documentation of PIP. Users will find definitions for every indicator and documentation about methodological decisions, input data, and survey metadata. A comprehensive methodology manual that compiles all the key methodological aspects of poverty and inequality estimations is also available directly from PIP. The manual answers many of the questions that we have received in the past.

Fourth, PIP includes a first public version of the Statistics Online platform, allowing users to perform their own computations directly on the microdata that underpins the global poverty estimates. This innovative platform blends household survey data, computing engines (powered by statistical software such as Stata/Numerics), and Jupiter Notebook into one environment. It allows users to analyze the World Bank’s publicly available harmonized household survey data, replicate the estimates available in PIP, and conduct their own analysis. The publicly available harmonized data in Statistics Online—which will be made available in spring 2022—currently includes vetted variables such as welfare aggregates, age, gender, education, urban/rural, location, and access to infrastructure services. This is another way of making our data more accessible and providing transparency, open code, and open data.

All PIP data can be accessed via the PIP website or directly through the PIP data API. In addition to these API endpoints, we will also release two API wrappers (clients) for statistical software such as R and Stata to end-users so they can efficiently work with our poverty and inequality data. Users can test a first beta version of the Stata package by following the installation instructions in this Github repository (the R wrapper will be released in March). However, users must keep in mind that this is not a stable version yet, will change constantly before the official launch in spring 2022, and that it requires Stata 16 or higher.

PIP aims to achieve improved useability through data visualization and greater transparency and replicability through open code, open data, documentation, remote execution, and version control. We look forward to your feedback!


We gratefully acknowledge financial support from the United Kingdom government through the Data and Evidence for Tackling Extreme Poverty Research Programme and from the Foreign, Commonwealth and Development Office.


R. Andres Castaneda Aguilar

Economist, Development Data Group, World Bank

Ifeanyi Edochie

Data Scientist, Poverty and Equity GP, World Bank

Aleksander Eilertsen

Junior Professional Officer, Development Data Group (DECDG), World Bank

Minh Cong Nguyen

Senior Data Scientist, Poverty and Equity Global Practice, World Bank

Haoyu Wu

Economist in the World Bank’s Poverty and Equity Global Practice

Christoph Lakner

Program Manager, Development Data Group, World Bank

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