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Aaron C Brown's avatar

This is a strong piece, and the core thesis is clearly true: the Michigan survey has become a partisan thermometer, and the post-2024 readings can't be taken at face value. I argued something similar about the survey's inflation-expectations component in a Bloomberg column, so I'm sympathetic. But I have three objections.

First, the adjustments explain the wrong thing. The mode shift and the partisan reweighting both land after mid-2024. The vibecession is older than that. Kyla Scanlon coined the term in 2022, under Biden, when — by your own partisanship chart — the sample wasn't yet Democrat-skewed and the survey was still on the phone. The puzzle that launched four years of commentary was sentiment running below what 3.5% unemployment "should" produce. The corrections pull the recent readings up toward 2013 levels; they don't touch the 2022 divergence. They explain the depth, not the phenomenon.

Second, subtracting nine points to match the old phone series assumes phone was unbiased and web is contaminated. But self-administered modes are well documented to reduce social-desirability bias — people are franker to a screen than to a live interviewer. If web respondents are simply more honest, the level shift is signal, and it was the phone series that ran high. As the piece argues, a 0.97 correlation between modes can't adjudicate this. The same goes for anchoring to a fixed NPORS partisan split: it partly defines away the partisan-driven sentiment you're trying to measure.

Third the piece addresses Hsu's claim that the national number tracks independents. But her main argument, in the May 22 note, is that partisan gaps are "economically important and meaningful," showing up in actual spending, entrepreneurship, and portfolio choice. If partisanship moves behavior, then partisan-skewed sentiment isn't expressive noise to weight away — it's a forecast of consumption. You can't treat the partisan signal as meaningless for the index and meaningful for the economy at once.

Which gets at what the vibecession actually is. These instruments measure central tendency, not perceived variance. "Continuous good times, or periods of widespread unemployment, over the next five years" asks about the mean, not the felt second moment. Someone can rationally say things are fine now but the ground feels less stable than before 2020 — pandemic, Silicon Valley Bank, Iran War, an oil shock, tariffs, AI displacement, DSA making a bid to take over the Democratic party while MAGA is showing signs of life after Trump — and that depresses sentiment without being partisan or irrational.

The vibecession reads more like a fragility premium than a happiness deficit. The clearest evidence is the present-versus-expectations gap: okay now, worried ahead. The Conference Board's split between its Present Situation and Expectations indexes captures that directly.

None of this rescues the headline. 49.5 is not a true Great Recession reading. But "partly an artifact of bad data" is too clean — part of it is a real signal the instruments aren't built to measure.

Gwic's avatar

The inconsistency of date ranges on the charts makes the analysis raise my eyebrows a bit. Looking at the charts, they go back to:

* 2006

* 2016

* "G.W. Bush", so 2001-2008?

* N/A - not your chart

* 2022

* N/A - point in time

* N/A - not your chart

* 2017

* 2007 - not your chart, but the data is publicly available to make it shorter/longer

* 2009

Some of these may be benign in intent (e.g. you want to highlight a more recent trend, or not all data series are available for the full time window) but shifting the window of analysis on every single chart smells a lot like cherry picking to make the data fit your conclusion.

Take the chart "Consumer sentiment looks less negative after adjusting for mode and partisanship". It goes back to 2017, but the leading text references earlier dates in Obama's term ("depths-of-the-Great-Recession", "when he was re-elected"), so reader's can't even see that in the data.

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