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Ben Casselman

@bencasselman

Econ/business reporter

. Formerly:

@fivethirtyeight

. Adjunct

@newmarkjschool

. He/him ben.casselman@nytimes.com Photo: Earl Wilson/NY

nytimes.com/by/ben-casselm…Joined September 2008

3,031 Following

72.9K Followers

Ben Casselman’s Tweets

Ben Casselman Retweeted

Making this point in chart form: The non-seasonally adjusted drop in payrolls we got in January was the smallest for a January since 1984.

Quote Tweet

Changes in seasonal patterns may have boosted job gains in Jan. Non-seasonally adjusted payrolls declined by 2,505,000 in Jan, the smallest MoM % decline in Jan since 1984. Employers may have held onto seasonal workers after the holidays bc of difficulty hiring. #jobsreport 3/

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As I said in my thread yesterday, it's always a good idea to view outlier numbers with some skepticism. I wouldn't be at all shocked if today's numbers eventually get revised down. But it doesn't look like the benchmark revisions are the issue.

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(Note: I'm basing the above tweet on the overall nonfarm jobs total. I haven't dug into the individual industry series to explore how composition could have played a role here.)

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Worth noting that BLS updates its seasonal adjustment formula based on the benchmark revisions. This year's revision actually appears to have made the January adjustment slightly less extreme. Using the old seasonal factors, January's job growth could have looked even bigger.

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The seasonal formula "knows" that, and adjusts the figures accordingly. That's not a conspiracy -- it's what seasonal adjustment is meant to do. But when seasonal factors are that large, small shifts in seasonal patterns can result in big swings in the SA data.

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A much more likely culprit for the January surprise, as

@BrettMatsumoto

predicted yesterday, is seasonal adjustment. January is a crazy month for seasonal adjustment, because employment plunges by millions as seasonal workers get laid off.

Quote Tweet

@BrettMatsumoto

Thread on likely complications in interpreting tomorrow's jobs number. I would add a few additional factors. First, seasonality could be a big issue. Jan is the month with the largest seasonal adjustment as NFP tends to decline on an NSA basis by several million each Jan. Any twitter.com/bencasselman/s…

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But that affect isn't nearly large enough to account for the big surprise in January. To give a sense of magnitude: The benchmark revisions added 34,000 jobs to the November gain, and 37,000 to December.

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They are indirectly affected in that the BLS uses the information gleaned from the benchmarking process to update its models. These revisions suggest the monthly survey was underestimating job growth through Q1 2022, so BLS will revise its models accordingly.

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The annual benchmarking process only affects data up through the prior year. So the January 2023 figures released today are not directly affected by the revisions.

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There were three revision-related issues in today's report: 1. Pop. adjustments 2. Benchmark revisions 3. Updated industry definitions #1 is about the household survey and doesn't affect the payroll numbers. #3 doesn't change the topline figures. So #2 is all that matters here.

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Given the surprising (to put it mildly) jobs report this morning, I'm getting lots of questions about whether the issues I flagged in this thread from yesterday could be messing with the January numbers. Short answer: not really. Slightly longer answer in thread.

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Tomorrow is #JobsDay, my favorite day of the month! Except that tomorrow's report is going to be so, so, SO annoying. Quick, nerdy thread on why:

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Jay Powell to markets right now: youtube.com/watch?v=SWmQbk

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WOW: U.S. employers added a whopping 517,000 jobs in January. The unemployment rate fell to 3.4%, the lowest since 1969. Data: bls.gov/news.release/e Full coverage: nytimes.com/live/2023/02/0

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No.

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Worth noting that there was a big gain in state and local government jobs because of University of California workers returning from a strike. (Although private sector gain of 443k is nothing to sneeze at!)

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On the other hand, big gains in both jobs and hours worked means that total labor income jumped back up. That's what matters for aggregate spending.

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Sort of a mixed picture on inflation in this report. On the one hand, hourly earnings continued to cool a bit on both a month-over-month and year-over-year basis (though the January slowdown is partly because December was revised up).

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Looking over the full pandemic period, leisure and hospitality are still down, but by roughly half previous estimate. Retail flips from small positive to small negative. Warehousing even stronger than believed.

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Interesting to look at the benchmark revisions by sector. Large upward revisions to leisure, professional services and transportation/warehousing. Retail and government revised down.

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The unemployment rate fell to 3.4 percent in January. That's the lowest it's been since 1969.

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The benchmark revisions make the recovery look *even stronger* than it already did. Although note this does not incorporate QCEW data from last spring that suggests some weakness.

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Still, even (or maybe especially) when we get big surprises like this, it's important to keep the bigger picture in mind. This has been an exceptionally strong rebound from the pandemic losses, but employment is still below where we'd have been had job growth continued unabated.

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The story in the job market had been "gradual cooldown but surprising resilience." This report, taken on its own, paints a very different picture: all the resilience, none of the slowdown.

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BLS web site being a real jerk today.

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Average earnings up 10 cents/hour. Up 4.4% over the past year. Unlike everything else in the report, that's consistent with a continued gradual cooldown.

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November/December both revised up, by combined 71k. That's separate from the benchmark revisions throughout 2022.

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WOW: U.S. employers added a whopping 517,000 jobs in January. The unemployment rate fell to 3.4%, the lowest since 1969. Data: bls.gov/news.release/e Full coverage: nytimes.com/live/2023/02/0

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Ben Casselman Retweeted

@BrettMatsumoto

Thread on likely complications in interpreting tomorrow's jobs number. I would add a few additional factors. First, seasonality could be a big issue. Jan is the month with the largest seasonal adjustment as NFP tends to decline on an NSA basis by several million each Jan. Any

Quote Tweet

Tomorrow is #JobsDay, my favorite day of the month! Except that tomorrow's report is going to be so, so, SO annoying. Quick, nerdy thread on why:

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Ben Casselman Retweeted

@BrettMatsumoto

I've been on the productivity puzzle thing for a while saying the decline was likely normalization and not something to worry about. The data releases and revisions since (including today's Q4 data) supports this, and we seem to be moving back to more or less trend growth.

Quote Tweet

@BrettMatsumoto

After the updated data from today, this productivity decline is even less of a puzzle. Both historical output and hours were revised, the net effect is productivity grew more in 2020 and 2021 than prior estimates and declined less this year. If you look at the plot of twitter.com/BrettMatsumoto…

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Big picture: Be *extra* skeptical tomorrow if you see any big monthly changes that don't seem consistent with other evidence. That's always a good practice anyway given how volatile these numbers an be.

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There are big changes in Retail and Information. BLS is killing off the "nonstore retailer" category to reflect the fact that nearly ALL retail now has an e-commerce component. Similar move with media, where they'll no longer have a separate category for online publishing.

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The impact here is BROAD. BLS says that "Approximately 10 percent of CES employment was reclassified into different industries as a result of the revision." A lot of that will happen at very detailed industry levels that most people won't notice. But... bls.gov/web/empsit/ces

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But wait, there's more! Tomorrow's report will *also* incorporate updated industry definitions. This won't affect the topline numbers, but it means essentially all the industry data will be revised going back more than 30 years.

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(As an aside,

@BrettMatsumoto

has done some good threads on why we should be cautious about how we interpret the quarterly QCEW data, so I wouldn't take that Philly Fed estimate as gospel.)

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@BrettMatsumoto

On Q2 2022 QCEW vs CES, I would exercise a little caution in interpreting the divergence. The first thing to keep in mind is that QCEW tends to be lumpier. This means that the 2 can track over longer periods while diverging over shorter periods. If you look at y/y changes at

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In other words, that big debate that's been bubbling up on #EconTwitter lately about which set of jobs numbers to believe? It won't be resolved for another year (at the earliest).

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But crucially, tomorrow's revisions only incorporate the more detailed data up through Q1 2022. An analysis of more recent data from the Philly Fed suggests the BLS overestimated job growth in Q2 -- but that won't show up until NEXT YEAR's revisions.

philadelphiafed.org

Early Benchmark Revisions of State Payroll Employment

Quarterly release of early benchmark estimates of monthly state employment for all 50 states and the District of Columbia

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Thankfully, BLS *does* revise the establishment survey going back, so we'll be able to make historical comparisons with the payroll figures (as long as you download all the data fresh on Friday).

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BLS released preliminary revision estimates back in August, and they suggest we'll see a fairly large net revision (+462,000 jobs), plus some big shifts at the industry level (more jobs in warehouses, fewer in retail). bls.gov/web/empsit/ces

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Second, we *also* get the annual benchmark revisions tomorrow. This is when BLS reconciles survey-based payroll figures with more accurate (but less timely) data from state unemployment insurance systems.

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Fortunately, BLS does publish estimates of the impact of the pop. adjustments on some of the most important data series. And as I'm sure

will remind us, we really shouldn't be focused on month-to-month changes in the CPS anyway. But still a pain.

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That means that the household survey estimates are NOT directly comparable between December and January. And sometimes, it can make a really big difference -- as it did last year, when if you missed the adjustments, you'd get the whole interpretation of the report wrong.

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