The economist’s research touches on many different aspects of consumption
Angus Deaton who advocates policy measures based on consumption rather than income has been awarded this year’s Nobel in Economic Sciences. The Scottish-born economist’s work is largely based on understanding of necessary individual consumption choices are to design an economic policy that promotes welfare and reduces poverty.
Born in 1945 in United Kingdom, Angus Deaton is affiliated with Princeton University, USA. By linking detailed individual choices and aggregate outcomes, his research has helped transform the fields of microeconomics, macroeconomics, and development economics, says the Nobel committee.
How do consumers distribute their spending among different goods? Answering this question, according to the Nobel Committee, is not only necessary for explaining and forecasting actual consumption patterns, but also crucial in evaluating how policy reforms, like changes in consumption taxes, affect welfare of different groups.
The economist has done major work in India too. In 1996, Deaton, along with others, had highlighted that cost of calories increases when one’s income rises. He used the detailed household survey data from India to prove this. It is because households substitute products like cereals with dairy and meat products.
While his main line of inquiry takes nutrition to be determined by income, Deaton also provided indirect evidence on the strength of the reverse link from malnutrition to poverty. Specifically, they document that the calories necessary for a day’s activity cost less than five per cent of the daily wage. This makes it quite unlikely that malnutrition explains poverty.
Deaton’s name has been appearing as possible laureates even in past too. Angus Deaton’s research spans a very broad field, touching on many different aspects of consumption. It also shows an impressive breadth in its approaches: basic theory; statistical methods for testing theories; in-depth knowledge of the quality of existing data; and extensive work on producing new kinds of data. One common denominator in his research is the desire to build bridges between theory and data.
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