Odd Lots - Big Take DC: Economists May Be Using Bad Data to Make Big Decisions

Episode Date: January 30, 2024

Today's episode is a special edition of Bloomberg's Big Take DC podcast, featuring an interview with our own Joe Weisenthal and Tracy Alloway. They spoke to Big Take host Saleha Mohsin of Bloomberg News, about how the US has managed to avoid a recession — and whether the Federal Reserve’s decisions were based on reliable data. It also features an interview with Claudia Sahm, an ex-Fed economist and contributor to Bloomberg Opinion. To hear more from Big Take DC, subscribe to their show.See omnystudio.com/listener for privacy information.

Thanks for listening to OddLOTS. Follow the show on Amazon Music for more future episodes or just ask Alexa, play the podcast, OddLOTS on Amazon Music. Hello, OddLod's listeners. You'll be enjoying an episode of one of our fellow podcasts on the Bloomberg network, Big Take DC. Yep, hosted by Saleh Moeson. This episode features one of our favorite guest, economist Claudia Somm. You might remember that we spoke to her back in November about the outlook for the U.S. economy, and Saleh digs even deeper into what's driving things like sentiment consumer surveys versus the hard data right now. Take a listen. When the government is trying to get a handle on inflation, it's the Federal Reserve that has

the biggest lever to pull. Think of the Fed like a traffic cop. Instead of a whistle and cone, the central bank uses interest rates to try and contain inflation. When rates go up, money becomes expensive and people tend to spend to spend. spend and borrow less, that slows the economy down. When rates go down, people are more willing to spend since everything from credit card fees to mortgage rates are cheaper. Unlike the traffic buildup on a road, which anyone can see, the Fed has to get creative in order to manage the economy, so it uses data to decide when and how to intervene. But last year, when economists everywhere

were expecting a full-blown recession, the Fed was raising interest rates over and over again. They needed to rain in inflation. And the man in charge chaired Jerome Powell, he kept pointing to one category of data that was guiding the Fed's decision. The labor market, the labor market remains very tight. All this talk about the tight labor market made Claudia Somm's ears perk up.

She's an economist and a Bloomberg opinion contributor. She worked in the Obama White House and spent 12 years at the Fed. She'd been looking into the labor market numbers herself and the Fed's decisions left her scratching her head. They are making big decisions about the interest rates, the mortgage rates. We pay the credit card, interest rates, auto loans. So we want them to be data-driven, but they can only do as good a job as the data they have.

And that data they've been focused on? She's had some serious questions about it. This morning, the government released new GDP data that shows the U.S. successfully avoided a recession, even though almost every economist was predicting one. But the data that the Federal Reserve examined as it made policy decisions is complicated. On today's show, have policymakers trusted data that might have been faulty? I talk to Claudia Somm about her findings. And I sit down with Tracy Allaway and Joe Wisenthal from Bloomberg's Odd Lots podcast.

We talk about what's behind the numbers and why it's important in an election year. From Bloomberg's Washington Bureau, this is the Big Take DC podcast. I'm your host, Saleh Amosin. Claudia Somm decided her concerns about the Federal Reserve's data were worth voicing. So in November, she wrote an article for Bloomberg opinion. It had an eye-catching headline. Economists may have been flying blind all along. So the argument I was making when I said economists are flying blind

is the awareness that we need to have in terms of the measures, like how we try and measure quote-unquote reality and then in our giving policy advice. How we measure quote-unquote reality? I know that sounds dense, but her point is that as much as we'd love to think that the Fed is making its decisions based on hard numbers, you know, objective, unbiased data, often it's not.

Data doesn't come down from heaven. For example, let's look at that tight labor market that Fed Chair J. Powell kept mentioning. He said that the labor market was tight, meaning more job openings than workers. He cited numbers from the job openings and labor turnover survey, joltz, for short. Now, that might sound straightforward, right? Measuring the number of open jobs? Not so fast. There was a lot of conversation amongst those of us who have nothing better to do than study data,

that what a job opening is could be changing over time. Because of the pandemic, the way employers list jobs is just different than it was before. Especially from work from home, you can put up multiple ones for different geographies because it doesn't matter. So a company might list the same job in several different cities. It doesn't cost them anything. But it does mean that the numbers are getting inflated. So when economists at the Fed were looking at the number of open jobs and basing their assumptions off of what was typical, they were at risk of ignoring one key factor.

The world wasn't typical. I wanted to understand just what's going on here and whether it was an issue beyond this one job survey. So I sat down with two of my colleagues. I'm Tracy Alloway. I am the co-host of the Allotts podcast. And I'm Joe Wisenthall, also the co-host of the Oddlots podcast. Joe and Tracy read Somm's article, and they agreed with her. They do not trust that Jolt's data. Pre-COVID, Joltz was a bottom-shelf economic indicator. It was the well-drinks of, you know, it's like some nerds like to pour over it because there is information on it, but it was not a market mover.

If Joltz was a bottom-shelf well-drink to them pre-COVID, it was basically a cheap shot of bad tequila once the pandemic hit. You just don't know that the patterns of history related to things like job openings, related to, things like claims and quit really mean the same thing in this environment as they might have in past cycles. If it was a business cycle, it was the weirdest business cycle ever. Companies are behaving differently to how they used to. There's the idea of labor hoarding. People are so scarred from the pandemic period that they just want to make sure they're not caught out again with a labor shortage. So they're just hiring who they can or they're putting out ads to see who responds. I mean, it's pretty easy to place an ad on some digital job site nowadays.

It doesn't really cost that much. So why not try and see who you get? So the pandemic threw all our old markers of normal out the window. That left the jolt survey and pretty and steady ground. But COVID didn't just mess with jolts. It also did another thing that influences all sorts of important data points that Fed economists rely on. Survey responses, we know they have declined in recent.

years. So I think something like the housing survey gets like half of the people. It surveys actually responding nowadays, and that's down from two-thirds. We reached out to the Bureau of Labor Statistics and the Census Bureau for comment for this episode, and they both acknowledged declining response rates as a critical problem that they're trying to address. It's a problem that only got worse during the pandemic. All this matters, because if your survey only captures half a of the people you contact? You're going to have to question whether or not that 50% is reflective of the actual American experience. And, of course, the irony is that most advanced economies are collecting more data than ever.

We're doing more soft surveys than ever, but the response rates are trending down and the quality of that data is questionable. We'll get to why Americans are getting survey shy, what the Fed is doing to fix it, and what it all means for the 2024 election after the break. A lot of short daily news podcasts focus on just one story. But right now, you probably need more. On Up First from NPR, we bring you three of the world's top headlines every day in under 15 minutes. Because no one's story can capture all that's happening in this big, crazy world of ours on any. given morning. Listen now to the Up First podcast from NPR. What separates good leaders from transformational ones? I'm Jessica Chen and in season

two of Leading By Example, we'll sit down with executives like Grace Chen of Bertie Gray to find out. It's important to understand where you spike, but also really acknowledge where you don't and find people who can fill those gaps. Listen to leading by example, executives making an impact on the IHeart radio app, Apple Podcast, or wherever you get your podcasts. We're back. Part of what made Claudia Sam argue that economists may have been flying blind is lower response rates to government surveys. And that decline is actually a symptom of a much bigger problem.

We've seen a growing distrust in government. And, you know, I can understand if you don't trust the government, if they show up and be like, hey, tell us all about your wealth and you're dead and how much income you make. which for a lot of people, these are very sensitive topics. Peer research found that two-thirds of adults think the risk of responding to a survey outweighs the benefits. They're concerned about things like privacy and not so concerned about the consequences of low response rate data. Somme says they should be. You need to rebuild that relationship and help people understand, know what you tell us.

Like, policymakers, this is important. And if we don't know what's going on in your life, then it's, almost guaranteed that the policy just can't address the issues. We're in an election year, one when Americans list the economy as the top issue driving their votes. So flawed assumptions about the economy, based on sketchy data, carry a risk as people decide who they want as president. And so does data that doesn't fully capture voters' lived experiences. I asked Joe and Tracy from Oddlots about all that. It kind of feels like the worst timing to have bad data or questionable data when there's such a consequential election at hand.

So I'm curious what you guys think. How do you think potentially flawed data is going to affect all of this? One of my favorite surveys to read through is the NFIB Small Business Optimism Survey. And there's one chart that really catches my eye in which the NFIB itself disambiguates between what they call the hard data and the, soft data. So the hard data is like, were your sales higher or lower in the last three months? It's not really an opinion question. Either it was or was it, and see your answer. And then there's the soft data. It's like, do you feel confident enough to invest in this environment? What's really interesting is that the hard data and soft data really do converge during

past Republican administrations and really do diverge during Democratic administration. So there's a huge gap right now within the NFIB between their soft and hard data. So I do think that there is a split in sort of how people perceive the economy versus how people perceive their own household finances. That is sort of interesting. How do people vote on this? You know, it's hard to say. To that point, I kind of think about it on a sort of personal versus like absolute basis, which is you do see a lot of self-reporting. So people talking about their own financial circumstances, or to Joe's point about small businesses, their own small business circumstance, they will say it's going relatively well. And you can see some of that borne out in the hard data. But when they talk about the economy in aggregate, that's when you tend to see a lot more negative sentiment. And there is a sort of weird cognitive dissonance there. We can talk about like whether that might be down to partisanship, down to the media, things like that. But I do think the interesting question is, If everyone keeps saying they think the economy is doing terribly, is that actually going to manifest in a slowdown in growth or even a contraction at some point?

We haven't seen that yet. That's significant. A lot of people this time last year were looking at government data and saying we're headed straight for a recession. But it turns out, all this flawed data isn't just affecting the Fed's decisions. It also goes the other way. As in Fed decisions, like raising interest rates, also shame. the narratives that economists construct about the state of the economy. The consensus position going into 2023 was that we were going to see a recession, that it was

impossible to have the extent of the rate hikes that we had seen without having some sort of slowing or negative effect on the economy. The story is you make money more expensive. That decreases the ability to invest and borrow. That causes people to lose their jobs. lost jobs mean less demand. Less demand means lower prices. That is the basic causal chain between how higher rates causes low inflation.

It's sort of the standard popular telling of how economics work. The idea that prices could come down without spiking unemployment was just absolutely outrageous, sort of this time last year. And yet what we've seen is exactly that. Janet Yellen, who serves as President Joe Biden's Treasury Secretary, caught it a soft landing, no pun intended. In other words, if the economy is a plane, it didn't crash. So what does all this mean about Somm's argument?

How can we make sense of the data we have and the stories economists are telling us about it? Maybe one way to think about is if you're going to extend the flying analogy, it's terrible weather and it's cloudy and it's raining, and there's wind from multiple directions and they're landing in an area with a lot of snow and a valley. It's really tough. to know what's going on. And what's striking is the degree of narratives that I could tell you right now about what's happening with the economy. I could tell you a story about how inflation is coming down and the labor market is still robust and we're on pace for a soft landing. I could say there are certain

measures of inflation that aren't coming down as much. And there are signs that the labor market is actually weakening. I can say, look at what's going on with financial market speculation. and say, look, actually, we haven't extinguished the inflationary embers at all in this economy. And so any one of those narratives, someone could convincingly make the case, it is extremely hard for the Fed to really know what's going on. Yeah. If there was no uncertainty, there would be no market, basically. And not to labor the flying analogy. But I think the trick is that, yes, it's stormy outside. But you're flying a plane. You have all these different indicators. You know, you can look out the windscreen and see what the weather actually looks like. You can look at your instruments and measure wind shear or whatever.

You sort of have to figure out which of your instruments to listen to at this moment in time. And it's tricky because it's not the usual flying environment. Gosh, I'm getting sick of this analogy. But it is a weird business cycle going back to what we were saying earlier. Somm was very clear in her article. The Federal Reserve is doing. the best it can. We're trying to get a sense on a $20 trillion-plus economy with, you know, hundreds of millions

of people working and busy. We're like trying to measure a moving target. But she does think the government overall could do more to restore trust so that people are more willing to respond to surveys. And she's also been involved in efforts to bridge the gap between that hard and soft data that Joe mentioned by relying on both. There are ways to use administrative data where you could put together like surveys where we ask people things that would be really hard to go measure somewhere else. But then maybe from the Internal Revenue Service, we know their income.

And it's definitely easier than figuring out how to get people to trust the government more. Somme says there's an urgent need to address these problems before they get worse. Statisticians have looked at this and, you know, people that research in this area, and they still feel comfortable with the degree of quality, accuracy. Like, there are ways to get a sense of the reliability. And they're still in a place where it's like, okay, we feel comfortable with these. And yet survey response rates that continue to go down, right? At some point, you cross a threshold of being reliable.

Thanks for listening to the Big Take DC podcast from Bloomberg News. I'm Saleemosa. This episode was produced by Alex Suggera. Julia Press and Naomi Shaven. It was fact-checked by Stacey Renee. A special thanks to Kate Davidson and Matt Bosler. Blake Maples is our mix engineer, and our story editors are Michael Shepard and Wendy Benjaminson.

Nicole Beamster-Bower is our executive producer. Sage Bauman is our head of podcasts. If you like what you heard, please be sure to subscribe, rate, and review the show. It'll help other listeners find us. Thanks for tuning in. I'll be back next week. Join Bloomberg in New York or via live stream on May 19th for building an AI Future Ready business. This event will examine how organizations are moving beyond experimentation to scale agentic AI across the enterprise.

By joining us, you'll hear from successful executives who are at the forefront of designing human plus agent operating models that are secure and outcome driven. This event is proudly sponsored by Kindrell. Register at Bloomberg Live.com slash FutureReady. What separates good leaders from transformational ones? I'm Jessica Chen and in season two of Leading By Example, we'll sit down with executives like Grace Chen of Bertie Gray to find out. It's important to understand where you spike, but also really acknowledge where you don't

and find people who can fill those gaps. Listen to Leading By Example, executives making an impact on the IHeart Radio app, Apple Podcast, or wherever you get your job. your podcasts.