Friday’s whopper of a jobs number was double expectations, and December’s data was one of several months to get heavily revised. Why are economists’ forecasts frequently so wrong?
It’s nearly impossible to say with certainty how much prices rose or how many people were hired at a given point in time across an entire country’s economy. Finding out how many new hires there were in a given month would involve asking every employer how many people were on their payrolls. That’s why the government and other economic data providers often rely on surveys to make sophisticated estimates.
The BLS, Census Bureau and other government agencies that conduct surveys that inform economic reports do rigorous work to make the best possible estimates with the information they gather. And more often than not they do a tremendous job at it.
But surveys, by nature, are imperfect.
In the same way that election polls don’t always predict the candidate who ends up winning, surveys don’t capture the exact true picture. However, they can get pretty close to the truth.
In election polls and government surveys, there’s a sample size of respondents designed to be representative of the overarching group studied. The larger and more diverse a sample, the closer an estimate will be to the true value.
Getting a large and diverse sample requires a lot of outreach to recruit people to be part of a group that BLS and other agencies enlist to regularly respond to a given survey. The rate at which people are getting recruited for surveys that are used in many of BLS’ monthly reports including employment, Consumer Price Index and Job Openings and Labor Turnover are down sharply from before the pandemic.
But Laura Kelter, national estimates branch chief within the division of Current Employment Statistics at the BLS, told CNN the declines can be attributed to a variety of challenges including the voluntary nature of participating in the surveys as well as survey fatigue — that is, people getting bombarded with too many surveys.
Changes in technology like caller ID and spam filtering, and heightened concerns about confidentiality and data security are also at play.