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Peter Ganong Profile picture
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28 Jul, 6 tweets, 2 min read
Why is UI hard to access?

Most policy discussions (rightly) focus on issues of state capacity.

Amazing paper by Sorkin, Lachowska, and Woodbury focus on *firms* who make it hard to get UI and the seamy underbelly of experience rating.
I think of this as the academic paper which captures @IndivarD's political economy model of a major problem with the UI system
Experience rating is the system where firms that lay off more workers pay more in UI taxes.

Goal: discourage layoffs
But there's a catch: experience rating also encourages firms to appeal. If a firm doesn't pay a UI claim, then it doesn't get taxed on it.

Firms that are shrinking a lot do not have this disincentive and also do not appeal nearly as often.
This strongly suggests that experience rating is driving firms to appeal.

Policy implication (h/t @IndivarD): UI would be a lot easier to access if there was less experience rating
Full paper here: conference.nber.org/conf_papers/f1…

I didn't see the authors on twitter, but plz tag them in the comments

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More from @p_ganong

Peter Ganong Profile picture
29 Jul
New research on Pandemic Unemployment Assistance by JPMC Institute w @FionaGreigDC @Dan_M_Sullivan @pascaljnoel @JoeVavra

PUA is for people not eligible for regular UI

PUA meaningfully insures inc risk, but w/much longer wait for benefits!

jpmorganchase.com/content/dam/jp… Image
The plot above shows that for people who got regular UI in 2019, non-UI income falls at exactly the same time that UI kicks in (green line).

Regular UI in 2020 (orange line) income starts to fall four weeks before UI kicks in

PUA (blue) income starts to fall ten weeks before
There is also a smaller decline in income after UI receipt for the blue line. Two likely interpretations:
--PUA recipients account for smaller share of HH income
--some PUA recipients have already gone back to work by the time they finally get their benefits
Read 4 tweets
Peter Ganong Profile picture
29 Jul
🚨new results on the effect of UI supplements on job-finding 🚨

2 designs x 2 policy changes yield consistent pattern: small, precisely estimated disincentive effects

Disincentive remains small even after job openings up Image
An overarching theme of the pandemic has been to view the supplements as responsible for the biggest problems (slow employment recovery, usually conservatives) and the biggest successes (rising wages at the bottom, usually liberals).

Our results are inconsistent with both views.
Instead, it makes sense to think of the effects of pandemic UI primarily as an ambitious anti-poverty policy. I can’t think of a time before when a country gave *full* insurance to earnings losses (examples welcome in the comments)
Read 22 tweets
Peter Ganong Profile picture
16 Jul
Millions of people have had federal UI benefits cut off

Stated goal: speed the labor market recovery.

Is it working?

Tldr: It’s going to be really hard to use state employment data to do a good job of answering this question.

Looks like a noisy 0
So far, 26 governors have announced plans to cut off at least some federal benefits. 20 are cutting off all benefits by July 5. This is where we might expect to see the biggest effects.
In those states, over 1 million people had their benefits fully cut off and another 1+ million people lost the supplement by July 5.
Read 17 tweets
Peter Ganong Profile picture
15 Apr
“Should you coauthor your JMP?”

Motivated by @RyanReedHill and @carolyn_sms thread, @pascaljnoel and I decided to write our own coauthored JMP thread.

The “Hillstein” thread is excellent, but there are three additional *upsides* to doing this which we want to share!
1) Research is emotionally difficult, at least for me. I *hated* working alone. I was on leave when @pascaljnoel and I started working together in earnest. There’s a good chance I would not have finished my PhD if we hadn’t started working together.
Ask yourself “If you are going to work long hours and push your limits, would you rather do that alone or as part of a team?”
Read 15 tweets
Peter Ganong Profile picture
11 Feb
🚨 new paper on labor market & expanded UI benefits 🚨

Tldr: spending ⬆️ more than expected,
job search ⬇️ order of magnitude less than expected

1) rise of repeat unemployment
2) effect of UI on spending
3) effect of UI on job search
4) connections to current policy debate
“Spending and Job Search Impacts of Expanded Unemployment Benefits: Evidence from Administrative Micro Data”
With @FionaGreigDC @maxliebeskind @pascaljnoel @Dan_M_Sullivan @JoeVavra
bfi.uchicago.edu/working-paper/…
1) we can track workers’ experiences over the course of pandemic

Confirm well-known fact: long-term unemployment is high

New finding: *repeat* unemployment has been rising. (Estimates of long-term unemployment in the CPS miss this since they only ask about most recent spell)
Read 24 tweets
Peter Ganong Profile picture
7 Jan
Newly published paper by @danascoot @finamor_lucas which has I think the best evidence to date on the incentive effects of the $600 weekly supplement (🧵)
(Dana's thread on the paper is here)
The paper uses time clock data from small biz, many of which are restaurants. they compare workers with higher and lower earnings in 2019 & ask "were workers with lower earnings in 2019 (and therefore higher benefit replacement rates) slower to return to work after expiration?"
Read 6 tweets

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