I encourage groups to begin collecting data as part of their basic program activities, and I make the claim that it will eventually allow them to connect their data to other, larger databases and maybe begin to take advantage of big data.
Imagine how my mind has been blown by learning about a huge international income database that has microdata on millions of households from more than 50 countries, all harmonized to make the same kinds of analyses possible across any of these countries! This database should be critically important for understanding poverty at a detailed level.
I just had the thrill of spending an hour with Janet Gornick, the Director of LIS, an international data archive that is located in Luxembourg. LIS is the institute that created and manages this giant database, which is called the Luxembourg Income Study (LIS) Database. I met her last year at KentPresents, a brand-new conference organized by the incredible duo of Ben and Donna Rosen.
Janet is also a professor at the Graduate Center of the City University of New York (CUNY), and she runs a satellite office of LIS there. Her group in New York includes Nobel Prize-winning economist Paul Krugman and renowned inequality scholar Branko Milanovic. I asked her what kind of insights could be gleaned by an anti-poverty group, say in Uruguay (to pick one country out of 50), accessing the LIS. She suggested:
- What is the poverty rate among individuals and households (using any of a number of poverty lines – absolute or relative, national or regional)?
- What does the distribution of poverty look like, that is, what share of the population is extremely poor, poor, and/or near-poor?
- Which individuals and households are most at risk – the youngest children, all children, women, the elderly? single-adult households, multi-generational households?
- What “micro” factors raise the poverty risk for persons and households – age? family structure? employment attachment and educational level of adult household members? other?
- Have the answers to these questions changed during recent years (2007, 2010, 2013)?
- How do these outcomes in Uruguay compare with those in 50 other middle- and high-income countries (including several in Latin America)? Which outcomes/patterns are unusual? Which are widespread?
- How do national-level demographic and labor market features shape the Uruguayan outcomes, in comparative perspective?
- Which national-level public institutions (e.g., government anti-poverty programs, income transfers more generally, taxation) help to explain the Uruguayan results?
Wow! Now, it turns out that this database has been made available under careful limitations to a select group of researchers. There are special constraints to ensure that database queries don’t accidentally reveal personal information about individuals, since that is part of convincing all of these different countries to supply this detailed microdata about household in their country.
Janet and her team get asked all the time to answer questions that the database could help answer, especially around income inequality. And, they often have to decline to help because of limited staff resources. Janet named some very well-known international publications that they had to disappoint in the last year.
Luckily, Janet and her team have an idea for how far more people could benefit from this database. For less than a million dollars on top of their existing funding, they could build an online portal so that researchers, journalists, policymakers, students and the general public could run their own queries on the LIS data.
Something tells me that this is definitely fundable. I am happy to help advocate that donors take a serious look at funding Janet and LIS make this happen. And if it does, we’ll have a major new tool for combating income inequality and poverty in much of the world!