The Unequal Recovery: Measuring Financial Distress by Zip Code | Hacker News Reader

The Unequal Recovery: Measuring Financial Distress by Zip Code

stlouisfed.org

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The upshot is that aggregate measures obscure what's really happening when there's a wide range of observations.

On average, wealth has increased since the Great Recession, but dis-aggregate the data and you'll find that many communities aren't very healthy.

This study dis-aggregates by zip code, and if you could further decomp into neighborhoods I'm sure you'd see much greater disparities.

But what does this ultimately say that we didn't already know? That the US is an extraordinarily unequal society? That the "recovery" was captured by some and left others behind?

Taking this to the next logical analytical step would be really powerful. How does this economic recovery compare with prior recoveries? When the next recession hits, who will bear the heaviest burden? Do the communities hurt most also show other signs of distress like lower life expectancy, higher crime rates, etc.? Is there a causal relationship we can detect?

If so, what are the implications for fiscal and monetary policy?

> Taking this to the next logical analytical step would be really powerful. How does this economic recovery compare with prior recoveries? When the next recession hits, who will bear the heaviest burden?

Do you know of anyone who is doing this specific analysis?

> the "recovery" was captured by some

As if there's a finite amount of wealth that just gets divided unequally. No. Some people made the world better than they found it.

This is a little strong of a statement for me. Sure, the economy isn't a zero sum game, but that doesn't mean that it automatically benefits everyone equally

True. But I said "some people".

It's not everyone, but the typical millionaire in the US became a millionaire by producing a lot of value for somebody else.

I guess the socialists are out in force today.

The next logical step would be to look inside the groups.

Say, we found that Chinese, on average, got better off, Mexicans, on average, got worse. Excellent. But surely some Chinese got worse and some Mexicans got better. That's where the answer may be. What did these people do that might explain the difference?

I expected the differences to fall along rural/urban zip codes, but that's not true - there are significant differences in financial health in rural areas as well as urban areas (going by their chart). It's got to be cultural in some fashion.

Or statistical noise. This is exactly what you would expect to see if the data were sliced up and compared using a loose significance threshold like 'p<0.05' instead of a tight one like 'p<(0.05/numberOfZipcodes)'. They don't seem to specify this?

See also "Justify your alpha" https://www.nature.com/articles/s41562-018-0311-x

Indian lenders have been doing this for a long time. They deny loans to borrowers from certain pincodes, provide loans with lower limits or higher interest rates etc.

Happens in Germany too. It is illegal if that's the only criteria, but hard to enforce cause most banks will tell you that they used their "judgement" to decide.

I have a couple of questions about their methodology.

How are they accounting for multiple comparisons in their tests for statistical significance? The answer had better be really good because they are making a /lot/ of significance tests at once.

How come it is reasonable to estimate the average household wealth as the median multiplied by the total number of households? This is novel to me and intuitively it seems dubious.

On using zip codes, and nearly masking the Flint water crisis:

http://theconversation.com/how-zip-codes-nearly-masked-the-l...

given that red and blue are used to color states and counties by political party it would have been better if they used a gray scale to show % of households in economic distress. Also, geographically larger counties tend to be more sparsely populated so the graphic could be further improved by showing raw counts of households in distress instead of percentages.

So they should fit their data to your bias? There are no red/blue states, just people. Party political pidgenholing is vile and needs to leave HN.

average millennials net worth is only $8K (group aged 18-35 today) so this is not surprising to me.

in 20-25 years, when millennials approach retirement age - its not going to look pretty for the economy.

It’s only not going to be pretty if you don’t take into account 30-40 years of technological advances. Healthcare advances and food science advances will both usher in higher quality that is more accessible at lower prices. Advances in energy show make energy cheaper. Eventually the boomers will die, putting lots of housing on the market making it available to millennials.

Between that you’ve got most major costs addressed, housing, healthcare, food and utilities.

Retirement may not be achievable at 65 anymore but they are going to be hitting 65 much healthier than any prior generation so working past 65 won’t be the same burden as it was for someone who did hard physical labor their entire lives.

They are literally going to be the generation that has had it easiest, but they are going to feel like they’ve had it hardest.

The biggest problem isn’t savings but the fact that so many eschew the type of labor necessary to maintain the infrastructure they are inheriting. Without plumbers, electricians and other technical trades, much of the infrastructure they inherit may have greatly deteriorated due to long overdue deferred maintenance.

Healthcare advances in the _past_ few decades have gone hand-in-hand with healthcare _costs_ rising much faster than inflation, at least in the US. Better medicine you can't afford doesn't help much.

Its hard to start families with 8K in savings.

This is a major blow for the economy that is consumption based.

If people have very little saved and have little assetts by the time they retire - im afraid this is bad news for years 2040-2065. Not that far away...

What’s the source on that? Every now and then there are headlines like this https://www.cnbc.com/2018/02/05/1-in-6-millennials-have-1000... so it’s hard to get a good idea of the big picture.

Is it one of those scenarios where there’s decent income, but wealth transfers to university administration in the form of the student loans offsets any of the gains?

It’s likely this story from a few days ago.

https://www.washingtonpost.com/business/2019/05/31/millennia...

Im so freaking mad that the .gov isnt even doing such data analysis as a matter of course.

This just illustrates how fucking stupid the government is

The government is, by definition, big data.

Such morons. Ajit pai should be drawn and quartered.

And shame on SV for being complicit.

Look at the following: palantir went hiding in its sleazy shell, YC defends them; yet we have a completely new industry vertical coming on line (cannabis) and we are all letting the same tropes fall in to place ... and the dialog on HN is crickets.

Here we have the biggest emerging market and YC acts like it doesnt exist....

The reason this is pertinent is that look at the consumption of flower/pens by demo? (I have done so... ) - look at financial distress cs medicating on that via dispensaries etc... i have the data to determine but not the time (building out our footprint is huge)

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