WASHINGTON, May 4, 2012 – Measuring poverty in the developing world is no easy task, as the perennial debate over the World Bank’s release of poverty statistics can attest.
One challenge is the lag in household data. The most recent and comprehensive global poverty statistics end in 2008, which was four years ago and before the financial crisis shook the world economy.
There is a reason for such delays: Many countries lack the resources or capacity to conduct and publish results of surveys – the collection of data the World Bank depends on to compile poverty statistics.
This, in turn, means that governments and their partners may not be able to target responses to food or economic crises where the help is most needed.
Enter high-frequency surveys, a new and emerging breed of income and consumption surveys that use economic modeling or wireless technology to capture the poverty picture in real time.
“High-frequency data is doing to economics what genetics did to medicine,” said Marcelo Guigale, the World Bank’s director of economic policy and policy reduction programs in Africa. “We always had economics before which allowed us to do policy and try to solve people’s problems, but with high-frequency data we’re able to do things we couldn't do before.”
Mobile Phone Surveys Give Instant Answers
In 2009, as the global financial crisis took hold, phones started ringing at the World Bank in Washington. Government officials were calling to ask how the economic downturn was affecting the poor in their countries, and how they could best respond.
Amparo Ballivian, a lead economist focusing on the Latin American and Caribbean region, and her team were asked by their director to come up with some answers.
“We had to tell him the truth: We didn’t have any data,” Ballivian recalled.
A discussion began in her group about how to get data more frequently, Ballivian said, so they would “be able to answer similar requests in the future when we have similar crises.”