WASHINGTON — A ski instructor gets hired in November and laid off in May. A lifeguard is hired in June and let go in September.
What does that say about the U.S. economy? Nothing. It is all radio static.
To get rid of that static, the government’s number crunchers often provide economic data that has been “seasonally adjusted.”
It’s a process that seeks to estimate and then remove seasonal “noise” from the numbers. That happens when ski instructors are hired every fall and lifeguards every summer, potentially affecting job statistics. Or when increases in heating oil production are reported each September as producers prepare for the winter heating season.
Here are some questions and answers about seasonal adjustments.
Question: Why is data seasonally adjusted?
Answer: It’s geared to getting a better grasp of the real underlying trends in economic activity, which can be masked by seasonal movements. If each month has a different seasonal tendency toward big increases or big decreases, it can be difficult to detect the underlying patterns in the economy.
“It is mundane in some ways, but also critically important in others,” said Sean Snaith, economics professor at the University of Central Florida. “It is really helpful for us to see the big picture of what is going on in the economy. It is a way to see the forest for the trees.”
Q: What are some of the government reports where data is seasonally adjusted?
A: Monthly reports on national and state employment are seasonally adjusted. So are quarterly reports on gross domestic product, or GDP, which is the tally of all goods and services produced in the United States.
Monthly inflation barometers such as the Consumer Price Index are adjusted, as are reports on retail sales.
Some reports, such as the Labor Department’s monthly report on employment in metropolitan areas, aren’t seasonally adjusted. In that case, there isn’t enough data to come up with a seasonal pattern to make the statistical adjustments.
In general, the smaller the slice being measured, the more difficult it is to come up with statistically sound adjustments.
When data is adjusted to remove the seasonal effects, month-to-month comparisons are easier to make. When it isn’t adjusted, month-to-month comparisons can be more volatile, so they should be viewed with caution.
“Should we celebrate because there was an increase in employment from month to month due to a seasonal effect, like more amusement park workers were hired because of the summer tourist season? No. It doesn’t really tell us the labor market is better,” Snaith said.
In cases where data isn’t seasonally adjusted, it is best to look over a longer period — say, compare one month of activity to the same month a year ago to try to detect broader trends, economists said.
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