- DI: You have spent almost 25 years at the World Bank– including many as a manager or director. Now you’re in academia: how does it compare? What do you enjoy the most in being a professor compared with a researcher at the WB? What, if anything, do you miss about being at the Bank?
MR: Roughly half the job of being an academic is pretty similar to being a researcher at the Bank. The other half is very different. The common half is research, of course. The Bank has a very good research department, which I miss, though I stay in contact, and today’s development research community is global. Poverty and inequality remain the dominant focus in my own work, and the broad direction of that research has not changed since the Bank, and even before.
The other half is teaching, which replaces the support I gave (like other Bank researchers) to the Bank’s lending and policy advice in countries. I like teaching, at both undergraduate and PhD levels; developing new courses at Georgetown on poverty and inequality has been personally satisfying. Some great, socially aware and committed, students at Georgetown. But I also enjoyed and learnt from my operational engagement at the Bank—especially when it involved working with counterparts in government. I miss that. The Bank is a truly great opportunity for an applied economist to work on real-world problems—opportunities that are less plentiful when based in academia. However, having moved into management at the Bank over the latter half of my time there, I was already missing the operational work when I left.
- DI: Movement is afoot on issues facing women and minorities in economics. What, to you, are the most pertinent issues? Are you hopeful of substantial improvements soon? If so, what will it take?
MR: Yes, we are seeing some welcome progress in how women and minorities are treated in the economics profession. I am optimistic that this will continue as there is a self-reinforcing cycle. Alongside the greater diversity we are seeing in course enrolments, recruitment and promotions, there have been equally welcome changes in the topics that economists study. As economists go more deeply into issues of poverty, inequality and human development this will make the subject more appealing to women and hopefully minorities, which will further strengthen work in those areas. I find this very promising for the social relevance of economics as a field.
- DI: . Is there anything you’d like to say here that might clarify some misconceptions or has been hard for you to get across in papers or on social media? Also, the field has been changing rapidly since the early criticisms of RCTs. Have your views changed about any of this since, say, you published 10 years ago?
MR: I have always thought an RCT is an important tool on the menu of options for evaluation, and I have used this tool myself at times, going back to the 1990s. The difference I have with advocates of RCTs is that I don’t put this one tool on a pedestal as the “gold standard.” To justify a confident ranking of two evaluation designs, we need to know a lot more than the fact that only one of them uses randomization. Advocating RCTs as the best, or even only, rigorous method for impact evaluation is more a matter of faith than science.
However, my biggest worry is that this view risks distorting our knowledge base for fighting poverty, given that this tool is only feasible for a non-random subset of the topics that matter. Ten years ago, that risk was one of my main concerns in “Should the Randomistas Rule?”, and the experience since then has only reinforced that concern. The biases have been documented. I have recently written a substantial update, “Should the Randomistas (Continue to) Rule?” (coming out in an edited OUP volume on this topic; the early WP version is ). The update elaborates on the biases in development knowledge that the RCT push has generated. A re-balancing is needed to assure that our research addresses the most pressing knowledge gaps for development policy making.
- DI: You recently have been more vocal about poverty in the US. Your makes use of on consumption/income floors to examine what happened to the poorest here at home and the role of SNAP (commonly known as food stamps) trying to counter the sinking of the floor. For readers who have not read your papers on this, can you please explain the idea of the income floor and the issues that come up in trying to measure it using household surveys?
MR: I have always thought that what economists and statisticians do in measuring social progress must be in tune with the concerns that one finds in the broader arena of social policy thinking and debates. One of the ways in which the two are out of tune today relates to the “floor,” which I define as the lower bound to permanent consumption or income. If the poorest are being reached in a sustained way, then the floor rises above the biological minimum. The idea that we care about the poorest has deep roots in moral philosophy, social policy and thinking about development goals.
However, our standard poverty measures tell us nothing about our progress in lifting the floor. Granted this is hard to measure with cross-sectional data, but I have a proposal, using a weighted mean of observed consumptions below a poverty line, with highest weight on the poorest. (You can read more about the idea .) Implementing this for the developing world I find that there has been only modest progress in lifting the floor, despite the progress made in reducing the numbers of poor as judged by (say) the World Bank’s international line. There are fewer poor people in the developing world, but the poorest are not much better off.
There are differences between countries, with some doing better than others. Social protection policy has helped, but (sadly) very little so far. For the US, my latest research with Dean Jolliffe and Juan Margitic (the WP is ) indicates that the floor has actually been falling over the last 30 years, which is alarming. Antipoverty policies such as food stamps have helped prevent America’s floor from falling even further, but the coverage of the poorest needs to improve.
- DI: You were behind the Bank’s “dollar-a-day” poverty line and oversaw it for a long time. You have now passed this torch on but must still be following its course and offering advice. How do you see the evolution of this work? Does it still play a role or is it time for something else? How does it, or should it, interact with the literature on multidimensional poverty measurement?
MR: As I said, it is important to make sure that our measures are socially relevant. One of the many things we have learnt from research in economics and the social sciences more generally is the importance of relative deprivation and social inclusion to personal wellbeing. This perspective is missing from our standard “absolute” measures. So too is the idea of the “floor” that I have discussed already.
I have always thought poverty is not just about low consumption or income, but also involves things that are missing in standard (even comprehensive) measures, notably access to non-market goods, as is often reflected in attainments in basic health and education. So, there is a case for multidimensional poverty measurement—a dashboard of relevant indicators.
However, I don’t find it helpful to try to collapse these multiple dimensions back into one dimension, as is done by some composite indices of so-called “multidimensional poverty” or inequality. The policy relevance is found in the components, not the composite mashup index with weak foundations for aggregation. Governments doing badly in one dimension, such as maternal and child health, may well be happy to have this hidden from view in some composite index. But that is not a good basis for antipoverty policy making.
After a long period of neglect, economists are now giving more attention to the gender and ethnic dimensions of poverty and inequality. We are learning a lot about the limitations of our standard household-level measures of welfare in properly reflecting the circumstances of women and children. For example, my work with Cait Brown and Dominique van de Walle found that the majority of undernourished women and children in Sub-Saharan Africa are not found in the households that are identified as poor by standard measures. (The paper is found .) This struck us, and pointed to some difficult measurement challenges ahead, with important implications for social policy. I am increasingly skeptical about efforts at fine targeting based on the data we routinely use.
There is more scope for studying past policy efforts in a range of country and sub-national contexts. The late Tony Atkinson encouraged us to study the economic history of redistributive spells. I have done that in the past for China and India, in various papers (with ex-Bank colleagues Shaohua Chen, for China, and Gaurav Datt, for India). This calls for a combination of micro-data work with archival work, using pre-computerized tabulations. The work can be analytically challenging, but messy, and causality is often illusive. However, it provides useful “thick descriptions” that deepen our understanding of development.
More recently I have returned to this type of work for Malaysia, where ethnic inequality has been a huge issue over 60 plus years. Malaysia provides a good example of relatively successful “market-friendly affirmative action,” that has greatly reduced the ethnic inequality and polarization inherited from colonial times. In turn, this has contributed to growth and poverty reduction (further details ). How one does such policies is key, and there will (of course) be losers as well as gainers, and beyond some point the policies should no longer be needed and fade away. But the issues of ethnic disparities are widespread and cannot be ignored.
- DI: What do you like to do for fun? You are not allowed to answer, “referee reports.”
MR: Definitely not referee reports, mostly. I like discovering new places, new cultures, new foods. Along with almost everyone I guess, I enjoy entertaining for family and close friends. Cooking too. I have to say my own research is often (not always!) fun too, as is teaching, at times. People who enjoy their work are very fortunate.