Surveys

While many data watchers eagerly anticipate the monthly jobs report coming out this Friday, today the Bureau of Labor Statistics released another set of jobs data, and arguably a much better and more complete set of jobs data for 2023. It’s called the Quarterly Census of Employment and Wages, and I have written about this data before.

The QCEW data is better because, as the name implies, it is a census of employment, rather than just a survey, meaning it is an attempt to measure the universe of employment (or at least, the universe of employment covered by unemployment insurance, which is something like 95% of the workforce). Surveys are nice, because they can provide us more timely information — notice that the QCEW is 5-6 months out of date. It is also useful to have this complete data to check on the monthly data and see if it was mostly accurate — indeed, the data is updated through a process called “benchmarking” on a regular basis.

What do the latest QCEW show us? The headline number is that total employment grew by 2.3 million jobs from December 2022 to December 2023, which is 1.5% job growth (if we use annual averages, growth is a little stronger at 2%). That’s a healthy rate of job growth, but it’s less than the familiar Nonfarm Payroll series (CES) shows from December to December: about 3 million jobs added, or a growth rate of 1.8% If we focus just on private-sector employment, we see again that the monthly series is running faster than the more comprehensive QCEW: 2.3 million jobs in the monthly report added versus 1.7 million.

Does all this mean that the monthly jobs numbers are “fake”? Of course not. Surveys will always be imperfect, but they are still useful. But it does mean that you might want to discount them by about 25 percent.

Axios just surveyed over 2,000 U.S. adults to find that “Americans rank the importance of regulating AI below government shutdowns, health care, gun reform…” Without pressure from the public to pass new legislation, Congress might do nothing for now, which will lead to the rapid advance of LLM chatbots into life and work.

The participants seem more worried about AI taking jobs than they are excited about AI making life better. There is some concern about misinformation.** So, they don’t think AI will have no impact on society, but they also don’t see enacting regulation as a top priority for government.

At my university, the policy realm I know best, we will probably not be “regulating” AI. We have had task forces talking about it, so it’s not because no one has considered it.

The Axios poll revealed gender gaps in attitudes toward AI. Women said they would be less permissive about kids using AI than men. Also, “Parents in urban areas were far more open to their children using AI than parents in the suburbs or rural areas.” Despite those gaps in what people say, I expect that the gaps in what their children are currently doing with technology are smaller. Experimental economists are suspicious of self-reported data.

**Our results did not change much when we ran the exact same prompts through GPT-4. A version of my paper on AI errors that I blogged about before is up on SSRN, but a new manuscript incorporating GPT-4 is under review: Buchanan, Joy, Stephen Hill, and Olga Shapoval (2023). “ChatGPT Hallucinates Nonexistent Citations: Evidence from Economics”. Working Paper.