Opening paper at #BPEA, is @LHSummers and @LukaszRachel who begin by juxtaposing two strikings:
Ten-year projections for debt-to-GDP for the US rose from 6% of GDP in 2000, to 105% today. Yet the ten-year real interest rate declined from 4.3% to 0.8%. brookings.edu/bpea-articles/…
Implication is that if not for fiscal policy, r* — the neutral real interest rate — would be substantially negative. Secular stagnation might turn out to be a bigger deal than we ever imagined. #BPEA
This likely terrifies central banks for whom the zero lower bound might become an everyday problem. It suggests that policymakers needs to become comfortable at using fiscal policy as a counter-cyclical tool. And with r<g, we need to rethink what fiscal responsibility means #BPEA
Concludes that full employment is basically incompatible with following both the sorts of monetary policies that the BIS would approve of, and the sorts of fiscal policies that the (pre-Blanchard) IMF would approve of. Something’s gotta give (and in the US, both have).
A methodological aside for the youngs: This paper is based on juxtaposing a market price and a forecast today, with levels 18 years ago. Taken together, the 4 numbers point to some major policy challenges. Yes, the authors churn through some models, but it’s really about 4 facts.
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Payrolls grew a relatively uninteresting (and positive!) +177k in April, and unemployment was unchanged at 4.2%.
This economy is still humming along.
NOTE: This is a reading largely from the pre-tariff period. Still very foggy about what lies ahead.
Revisions were somewhat worrying: March was revised down -43k to +185k. Feb down -15k to +102k.
Three month average payrolls growth -- a useful indicator of the underlying pace of job growth -- is a healthy +155k. That's a pretty great place to be at this point in the cycle.
Nominal wage growth was 0.2% this month, and are up 3.8% over the year. That's probably enough to keep inflation above the Fed's target (and that's before factoring in the effect of tariffs).
Ugh. It's happening. The economy shrank in the first quarter, at an annual rate of -0.3%.
The good news: Consumption and investment remained strong. Think of this as a hard-to-interpret report due to -- **all of this**. Remember, this is the average of Q1, and the real concern is about Q2.
Look into the details, and the GDP report really isn't that bad. (We already know from the jobs data that the economy did okay in Q1.)
@jasonfurman suggested focusing on Real final sales to private domestic purchasers (basically C+I, the reliable parts of GDP) which grew +3.0%
The sharp rise in investment appears to be almost all due to pre-tariff front-running. Investment contributed 3.6%-pts to Q1 GDP growth.
Of that, inventory accumulation was 2.2%-pts.
And an additional 1.1% came from equipment investment (which is what the China tariffs hit).
1. Tariffmageddon isn't over: Lotsa tariffs to account for, but the average tariff rate is only down around one quarter.
2. He's not going to get big wins: Tariffs were low before this mess, and if Trump negotiates competently, they'll be low again. Basically no gain.
You've seen this movie before: It was NAFTA which got relabeled by Trump in 2020, but really barely changed.
3. The rationale for this policy keeps changing. Remember when it was all about bringing manufacturing home? (That was yesterday.) Now it's negotiating deals. Those are fundamentally in tension.
(I'm only going to build a factory in the US if tariffs are likely to persist.)
One thing I've learned to do when I have questions about social security number holders who are age 100 or older is to look up the SSA Inspector General audit report, "Numberholders Age 100 or Older Who Did Not Have Death Information on the Numident."
After all: Is there a principled difference between weighting on age (to ensure that your sample includes youngs and olds) and weighting on past vote (to ensure you get folks from across the political spectrum)?
Both age and past vote are:
- Predetermined (before this poll)
- Non-manipulable
- Though self-reported
- And we have good population estimates to weight them to.
What principle would make one of these a legitimate survey design weight and the other "herding"?