One Quick Question: When reading economic news, can you trust the numbers?

When it comes to economics news, the headlines are full of precise numbers — growth rates, job gains, wage increases — but many people don’t feel like they match their lived experience. They can be hard to understand and harder to trust. To help decipher the numbers game, we reached out to James McCafferty, co-director of Western Washington University’s Center for Economic and Business Research (CEBR), for some answers.

Q: How should people understand the economic data behind the numbers we see in economics news headlines?

A: There’s a famous phrase — lies, damned lies, and statistics — often attributed to Mark Twain, who credited British Prime Minister Benjamin Disraeli, though fittingly, it’s not clear Disraeli ever said it. As economists, we get a front-row seat to how that phrase gets used. In most cases, the problem isn’t that the numbers are lies. It’s that very few people understand how the data are actually produced.

To understand today’s economic statistics, you have to look back to before the pandemic. Even then, many government datasets — the ones people rely on to assess unemployment, wages, job growth, business formation and other reference points — were experiencing a rise in survey nonresponse, which increases what statisticians call “sample error.”  

Then when the pandemic hit, those traditional datasets couldn’t be assembled quickly enough, so economists turned to available high-frequency data — credit card transactions, mobility data, tolling records, and health data. These datasets weren’t perfect, but they were timely. During that period of rapid economic change, speed mattered.

As we transitioned back to traditional surveys and sources after the pandemic, a new problem emerged: people had stopped responding. Some employment surveys that once had response rates near 80 percent fell to below 30 percent. When response rates fall that sharply, the margin of error can mean that a reported increase is just as likely a decrease.

At the same time, Federal government cost-cutting efforts have reduced sample sizes and changed collection methods. Smaller samples mean higher uncertainty.  

Combined, these trends have made portions of today’s federal economic data less reliable.

Economists have grown increasingly cautious about newly released Federal data, especially when the initial estimates differ dramatically from non-government forecasts. Historically, large differences were unusual and often suggested that substantial revisions were forthcoming. Revisions have always been necessary, but the magnitude has increased in recent years, making the revisions themselves newsworthy.

For example, when initial estimates of employment or inflation are strikingly high or low, they make the news. But then so do the subsequent revisions ... and people start questioning the validity of the data or whether the whole process could be politically motivated.  

It's not politics. It’s statistics. Economists approach initial estimates based on small samples or non-random samples with care. They probably should not be published as true and accurate since they are so likely to be revised.

What should an informed reader do? You shouldn’t ignore federal statistics, but you also shouldn’t take a single number at face value. Pay attention to revisions. Look at the footnotes. Compare multiple data sources. This is easier than it sounds. At our center, we review and share insights from international, national, and regional sources every day to understand the range of what the data are telling us. Our daily social media posts may become your new best friend for water-cooler discussions.

Economic data are still essential for understanding the economy. But they work best when paired with context, transparency, and a recognition of their limits. The goal isn’t blind trust or outright skepticism — it’s informed interpretation.

James McCafferty is the co-director of Western Washington University’s Center for Economic and Business Research (CEBR). Housed in Western’s College of Business and Economics, CEBR employs students, staff and faculty from across WWU as well as outside resources to assist businesses, government entities and nonprofits by developing reports based on academic approaches and rigor with a neutral analysis perspective. CEBR’s projects and initiatives include primary research, data analysis, producing economic profiles, economic impact reports, a quarterly Puget Sound Economic Forecaster report, the After Hours with the Puget Sound Economic Forecaster podcast in between quarterly reports, and daily updates on LinkedIn, Facebook, and Instagram.

Read part one of this series where we untangled the difference between inflation, Consumer Price Index, and cost of living.

Jennifer Nerad covers Western's College of Business and Economics and College of the Environment for the Office of University Communications. Have a great story idea? Reach out to her at neradj@wwu.edu.