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The ‘it’s inflation, silly’ thesis is powerful. As MainFT highlighted in a large piece days earlier than the vote and once more on election day. Inflation was clearly having a serious impact on Kamala Harris’s probability of being elected.
However an evaluation of geographically granular US inflation and the precise election outcomes means that inflation didn’t have an easy impact on the swing to Trump.
If it did, locations which suffered larger inflation would have been extra prone to see elevated Trump share of the vote over 2020. This isn’t what the info exhibits, nevertheless.
Cumulative CPI inflation since 2020 on the metropolitan space — essentially the most granular measure of inflation launched by the Bureau of Labor Statistics — shouldn’t be related to the 2024 Trump swing.
As an alternative, there’s a slight unfavorable relationship: cities which noticed larger inflation skilled smaller swings to Trump.
The image modifications if you as an alternative plot cumulative CPI in opposition to Trump’s vote share. Right here, there’s a transparent optimistic affiliation — cities that noticed larger inflation additionally noticed a better vote share for Trump in 2024.
However the identical relationship holds for Trump’s 2020 vote share, when he misplaced to Joe Biden.
Granted, the pattern measurement is small. We solely have each CPI knowledge and voting outcomes for 21 metropolitan areas.
A bigger pattern comes from the Bureau of Financial Evaluation, which releases implied inflation charges for over 300 metro areas within the US, albeit with a very long time delay (the most recent knowledge is for 2022, when inflation peaked within the US).
Simply as with CPI, cumulative PCE inflation by metro space exhibits no relationship with the Trump swing, and there’s additionally no relationship with Trump’s vote share in 2024.
That is puzzling. Exit polls and pre-election surveys present inflation was a serious concern, and tutorial proof is evident that folks really hate inflation and have a tendency responsible the federal government for larger worth ranges irrespective of who or what is definitely responsible.
So why didn’t areas that noticed larger inflation swing extra to Trump?
It’s not as if variation in inflation throughout areas is insignificant. Inflation variations are remarkably massive — Tampa Bay noticed near 30 per cent cumulative CPI inflation since 2020, almost double that of San Francisco, for instance.
What then? The reply to this puzzle may be that goal, combination inflation — as measured by CPI or PCE on the metropolis or nation degree — is a really completely different factor to each perceived inflation and skilled inflation.
First, on perceptions. Republican voters consumed much more negativity concerning the US economic system during the last a number of years, and this confirmed up clearly in sentiment.
A survey by Pew forward of the election discovered a 20 share level hole in concern round costs between folks figuring out as Republicans versus Democrats. And analysis exhibits that Republicans are more likely responsible the federal government for inflation.
From this standpoint, the route of causality runs within the reverse route: help for Republicans formed views on how unhealthy inflation was and who was responsible.
However whereas perceptions may be 9/tenth of actuality, inflation was objectively excessive all around the US.
The opposite level is that combination measures of inflation obscure massive variations in inflation experiences by households. All of us have very completely different consumption baskets, and therefore very completely different precise inflation charges.
One notable instance are typical variations in inflation by earnings group. The poorest usually undergo the best inflation ache, and the latest episode was no exception — the bottom earnings quintile noticed two share factors larger inflation on common since 2019.
Maybe that helps clarify why decrease earnings voters have been extra prone to vote for Republicans over Democrats at this election, for the primary time in a long time.
