Steve Randy Waldman
@interfluidity.com
Just a very fundamental point: People use quantitative data in order to debunk qualitative impressions. But when the data we are discussing is putative welfare measures (e.g. real income or wealth, GDP per capita, etc), the *qualitative* measures are foundational, the quantitative mere proxies. 1/
Steve Randy Waldman
@interfluidity.com
GDP per capita is widely used as a welfare measure not because it conceptually maps well to welfare (for all kinds of reasons it does not!), but because from the mid-20th to early 21st Century it mapped pretty well to our qualitative intuitions about relative welfare. 2/
Steve Randy Waldman
@interfluidity.com
The consensus that there is a good correlation between GDP per capita and qualitative welfare has broken down more recently. 3/
Steve Randy Waldman
@interfluidity.com
We can have arguments about why (inequality, differences in how medical and social insurance are accounted in GDP, market power, treatment of leisure). 4/
Steve Randy Waldman
@interfluidity.com
But fundamentally, it was only ever a good measure because there was a widespread consensus that it tracked qualitative outcomes. Once that consensus has broken down, there is no reason to think it *should* be a welfare measure. 5/
Steve Randy Waldman
@interfluidity.com
(The inventor of GDP, Simon Kuznets, explicitly argued that it should not be!) 6/
Steve Randy Waldman
@interfluidity.com
The same is true of "real" wealth or purchasing power measures! They are not inherently welfare measures. (I belabored this in a recent post.) 7/
Steve Randy Waldman
@interfluidity.com
If people are making qualitative claims that some group's welfare is poor, and you debunk them with quantitative data, whether GDP-per-capita or real purchasing power measures, you are engaged in a kind of circular reasoning. 8/
Steve Randy Waldman
@interfluidity.com
The only reason we think these *should* be welfare measures is because they sometimes seem to work well at capturing our qualitative experience and intuition about relative welfare. 9/
Steve Randy Waldman
@interfluidity.com
If qualitatively they seem to cease to work well as welfare measures, then there is no reason to think they are good welfare measures! When you debunk widespread qualitative expressions of welfare with this "data", you are really debunking the quality of your measures! 10/
Steve Randy Waldman
@interfluidity.com
That's not to say all unevidenced claims about qualitative welfare must be taken as gospel, at face value. The claims could still be wrong! 11/
Steve Randy Waldman
@interfluidity.com
Welfare is unobservable, hard to measure. This is economics' foundational demon as a "science". 12/
Steve Randy Waldman
@interfluidity.com
The moments when there is a strong consensus that any quantitative measure maps well to welfare are fleeting and precious. During those exceptional moments, it seems plausible that we might maximize welfare "scientifically". 13/
Steve Randy Waldman
@interfluidity.com
The rest of the time, like now, we have to cop to the fact that human welfare is not a scientific observable, but something we construct normatively and strive to achieve politically. /fin
Steve Randy Waldman
@interfluidity.com
( i've turned this thread into a blog post: drafts.interfluidity.com/2025/11/19/t... )