Pover-T Tests: Predicting Poverty

Measuring poverty is hard. Thanks to the efforts of thousands of competitors, The World Bank can now build on open source machine learning tools to help predict poverty, optimize uses of survey data, and support work to end extreme poverty … #development

$15,000 in prizes
feb 2018
2,308 joined

The data for this competition comes from The World Bank Development Data Group:

The mission of the World Bank’s Development Data Group is to provide high-quality national and international statistics to clients within and outside the Bank and to improve the capacity of member countries to produce and use statistical information. As part of the international statistical system, the Data Group works with other organizations on new statistical methods, data collection activities and statistical capacity-building programs.

With funding from the World Bank's Knowledge for Change Program, this competition aims to engage data scientists from developing countries and apply a cost-effective solution to testing a diverse set of approaches to poverty prediction.

The surveys used come from three developing countries. Each country offers a different demographic makeup, so successful poverty prediction across these countries will help identify robust set of predictors that can be used in future poverty measurement efforts.

Ultimately, we only can improve what we measure, therefore measuring poverty is critical. Right now, collecting data for poverty measurement is hard, time consuming, and expensive. For that reason, consumption surveys are implemented infrequently. To support the targeting of poverty reduction policies and programs, rapid surveys are often implemented to complement these detailed datasets. To determine the poverty status of beneficiaries, rapid surveys rely on poverty predictors (proxies) derived from the consumption surveys. The more accurate the predictions, the more efficient the targeting will be. This competition aims to harness the power of existing data and data science to maximize the impact and cost-effectiveness of poverty reduction interventions.

You can learn more here: