Screen Shot 2015-10-14 at 10.33.17 AM

On Monday, Princeton professor Angus Deaton won the Nobel prize for Economics*.
*Yes, I know it’s not one of the real Nobel prizes. But semantics.

According to the official press release, it was “for his analysis of consumption, poverty and welfare.”

The Summary of That Analysis

How do consumers distribute their spending among different goods? Answering this question 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 the welfare of different groups. In his early work around 1980, Deaton developed the Almost Ideal Demand System – a flexible, yet simple, way of estimating how the demand for each good depends on the prices of all goods and on individual incomes. His approach and its later modifications are now standard tools, both in academia and in practical policy evaluation.

That is: before Deaton’s “Almost Ideal Demand System” (AIDS), economists tended to talk about the “representative consumer”. Deaton pointed out that aggregating data like that is a bit foolish, because society is made up of many groups of people. So, for example, when there is a change in general income levels, young adults will respond differently to pensioners, and the wealthy will respond differently to the middle class, and so on. Meaning that when you reduce those different reactions down to one average reaction, then you’re vastly oversimplifying. Tsk.

How much of society’s income is spent and how much is saved? To explain capital formation and the magnitudes of business cycles, it is necessary to understand the interplay between income and consumption over time. In a few papers around 1990, Deaton showed that the prevailing consumption theory could not explain the actual relationships if the starting point was aggregate income and consumption. Instead, one should sum up how individuals adapt their own consumption to their individual income, which fluctuates in a very different way to aggregate income. This research clearly demonstrated why the analysis of individual data is key to untangling the patterns we see in aggregate data, an approach that has since become widely adopted in modern macroeconomics.

It’s the same thing as I said earlier – you can’t just “aggregate” everyone in an economy. What you have are small mini-economies of more homogenous groupings, all interacting with each other to cause a general outcome.

Screen Shot 2015-10-14 at 10.33.33 AM

How do we best measure and analyze welfare and poverty? In his more recent research, Deaton highlights how reliable measures of individual household consumption levels can be used to discern mechanisms behind economic development. His research has uncovered important pitfalls when comparing the extent of poverty across time and place. It has also exemplified how the clever use of household data may shed light on such issues as the relationships between income and calorie intake, and the extent of gender discrimination within the family. Deaton’s focus on household surveys has helped transform development economics from a theoretical field based on aggregate data to an empirical field based on detailed individual data.

This is where Deaton’s work has been kind of cool (although I’m a nerd, so my judgement on this is questionable).

Two findings that I think are interesting:

  • Poverty statistics tend to overstate the extent of poverty. This is because poverty data is collected at a household level, and then the household income is divided by the number of people in that household, giving an “income per capita”. But Deaton has shown that expenditure on children in a poor household is between 30% and 40% of expenditure on an adult, so the statistics on homes with children significantly overstate the problem.
  • Deaton also found a way to test gender discrimination in poor households – where the theory is that daughters in poor households are given systematically less resources than sons. He did it by indirectly testing household consumption data on adult clothing, tobacco and alcohol, to see whether the reduction in that type of consumption changed differently after a family had a daughter or a son. And while he couldn’t find any evidence of this kind of discrimination under normal circumstances, subsequent researchers have found significant evidence of gender discrimination when the household is suffering under adverse circumstances.

For more on his work, the Royal Academy of Swedish Sciences (who award the Nobel) have published a “popular science background” to his work.

Which I think is well progressive.

Happy Wednesday.

Rolling Alpha posts about finance, economics, and sometimes stuff that is only quite loosely related. Follow me on Twitter @RollingAlpha, or like my page on Facebook at www.facebook.com/rollingalpha. Or both.