petersuber

New from Oxford economist #OlivierSterck: "Measuring poverty on a spectrum instead of an arbitrary line conveys a more accurate picture of inequality."
https://theconversation.com/measuring-poverty-on-a-spectrum-instead-of-an-arbitrary-line-conveys-a-more-accurate-picture-of-inequality-271912

PS: I find this take on poverty very illuminating. Instead of measuring poverty by incomes (dollars per year), we should measure it by the time it takes to earn $1 (years per dollar). The classical measure allows a small number of very rich people to pull up the average income, and makes widespread poverty seem to be a minor problem. Sterck's new measure allows a large number of struggling people to pull up the average time needed to earn money, and makes a necessary correction to our understanding. The classical measure gives more voice or weight to the rich, when they're very rich, while Sterck's gives more to the poor, when they're very numerous. This helps us see two things otherwise invisible: widespread poverty hidden by average wealth, and the role of income inequality in hiding that poverty.

While the average income is higher or better in the US than in Europe, the average time needed to earn $1 is significantly longer or worse in the US. This kind of poverty exists alongside that high average income. We need to bring in severe income inequality to explain this, and of course income inequality is significantly higher in the US than Europe.

#Economics #Income #IncomeInequality #Poverty

Measuring poverty on a spectrum instead of an arbitrary line conveys a more accurate picture of inequality

An economist proposes a new method of estimating the scope of poverty in different countries.

The Conversation
Mar 7 at 5:46pmWeb
Show threadKatrina Katrinka Mar 7
@petersuber
It also shows the disparity in racial and gender demographics.
Show threadBrokarMar 7

@petersuber I would simplify that a little and just ask:
How much have you left at the end of the month to put into a savings account?

If the answer is 0 then you can assume this person is in the area of the target group.

Show threadDan Neuman 🇨🇦Mar 7
@Brokar @petersuber While savings is an important measure, I think there is a buffer zone where people are flexible on the quality of food and quality of housing depending on their income.
Show threadBrokarMar 8

@dan613 @petersuber

Do you rather live in an expensive house and have nothing left at the end of the month of would you move to a cheaper housing and have something left?
I don't think anyone would choose the expensive housing.
The same goes for food. You only spend it on quality if you can afford it.

And everyone wants a financial buffer in case something unforeseen happens, like the washing machine breaks down etc.

So no, i don't think that's an issue.

Show threadDan Neuman 🇨🇦Mar 8
@Brokar @petersuber You've never heard the term "house poor"? It's common, even if it isn't entirely rational in the short term.
Show threadJanne MorenMar 7

@petersuber
The problem is using averages. When it's not gaussian (a bell curve) it will give you the wrong answers.

We should use the median (and related measures like percentiles). It removes the distortion from a few outliers. It's also easier to understand, and we already use it when we refer to the top 1% earners and the like.

Show threadDan Neuman 🇨🇦Mar 7
@jannem @petersuber Using an inverse causes the few rich outliers to have very little impact on the average. 1/$Billion = almost zero. I'm not sure using a median would have a significant impact here.
Show threadJanne MorenMar 7

@dan613 @petersuber
With medians you don't need to use an inverse in the first place.

Also, the average still gives you the wrong results; the distribution is still not gaussian. The median is the better measure just about always (with gaussian distributions the median and average converges).

Show threadNaga (he/him)Mar 8

@jannem @dan613 @petersuber I'm not trying to contradict the broad point here by the article or Peter, but just weighing in on median:

As a quantitative social scientist, income and wealth are precisely the standard examples of when you should use median and never mean/average. The point is general about non-Gaussian distributions, but in the cases of income and wealth, it's especially about outliers. The moment you add Musk's wealth into an otherwise Gaussian distribution, the mean breaks down badly.

Show threadNaga (he/him)Mar 8
@jannem @dan613 @petersuber Non-linear transformations like inverse are patches on the problem. Helpful for some situations, depending on the next steps, but don't necessarily get you where you want, and have other implications.
Show threadDan Neuman 🇨🇦Mar 7
@petersuber This was very interesting. I note that the article uses minutes per dollar rather than the years per dollar in your comment. I assume that was an unintended difference.
Show threadpetersuberMar 8
@dan613
Right. I wanted the parallelism of dollars per year v. years per dollar, and knew that most people would understand the second to mean time-units per dollar. But you really could measure in years per dollar, if you were willing to use very small fractions (like 0.0000019...), just as you could measure your body weight in solar masses.
Show threadDan Neuman 🇨🇦Mar 8
@petersuber Haha! I suppose that's true.
Show threadGeofCoxMar 8

@petersuber

The point that conventional methods for measuring comparative incomes and poverty overstate US prosperity and understate European reminds me of a similar point made recently by Thomas Piketty here in France: GDP comparisons, even GDP per capita, suggest higher productivity in the US - but this advantage disappears if you measure productivity per hour worked. The US economy is not more efficient than France's - it's just that Americans work a lot more hours.

These points are crucial in societies like the UK, where US 'efficiency' is used by conservatives to suggest that lower tax, less employment protection, lower welfare standards and weaker trade unions lead to a more dynamic and prosperous society - but the reality is that they just make most people worse off.