Christopher Blattman is an associate professor of public affairs and political science at Columbia University.
He writes:
<< For me, at least, this year is different than most, since the winner, Angus Deaton of Princeton University, is such a towering figure in my field of international development. This is a prize for advances in our understanding of poverty and inequality. It couldn't be better deserved. .. .>>
He writes:
<< For me, at least, this year is different than most, since the winner, Angus Deaton of Princeton University, is such a towering figure in my field of international development. This is a prize for advances in our understanding of poverty and inequality. It couldn't be better deserved. .. .>>
For development economists like me, Deaton was a revolutionary and a visionary.
foreignpolicy.com
Deaton's books contained the models for every measure of economic well-being the profession possessed. At the time, I took for granted they existed, and it never once occurred how hard they were to invent and get people to use.
As we walked to the office today, my colleague Suresh Naidu put it nicely. Before there were evaluations of anti-poverty programs, or analysis of inequality trends, or really most of empirical development economics, there had to be something more fundamental: measurement. We had to know how to assess poverty, and we needed to have large-scale data to do so, to challenge our assumptions, and provide new answers. And Deaton as much or more than anyone else made this happen.
Deaton helped bring about this data and measurement revolution in several ways. One was to help establish expenditures and consumption as the best of a bunch of bad measures of poverty. Annual income works fine in a country like the United States where most people earn a regular salary from one source, but it's meaningless when a household has dozens of small activities, varying day to day, most of which produce things the family consumes themselves. The other contributions were to show just how much we could pull out of these simple data, and (as impressively) to actually measure it in huge household surveys — in countries that had never had that kind of data before. [ . . . ]
Deaton's books contained the models for every measure of economic well-being the profession possessed. At the time, I took for granted they existed, and it never once occurred how hard they were to invent and get people to use.
As we walked to the office today, my colleague Suresh Naidu put it nicely. Before there were evaluations of anti-poverty programs, or analysis of inequality trends, or really most of empirical development economics, there had to be something more fundamental: measurement. We had to know how to assess poverty, and we needed to have large-scale data to do so, to challenge our assumptions, and provide new answers. And Deaton as much or more than anyone else made this happen.
Deaton helped bring about this data and measurement revolution in several ways. One was to help establish expenditures and consumption as the best of a bunch of bad measures of poverty. Annual income works fine in a country like the United States where most people earn a regular salary from one source, but it's meaningless when a household has dozens of small activities, varying day to day, most of which produce things the family consumes themselves. The other contributions were to show just how much we could pull out of these simple data, and (as impressively) to actually measure it in huge household surveys — in countries that had never had that kind of data before. [ . . . ]
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