Are These Economic Myths Misleading You?

MARK RIEPE: I'm Mark Riepe, I head up the Schwab Center for Financial Research, and this is Financial Decoder, an original podcast from Charles Schwab. It's a show about financial decision making and the cognitive and emotional biases that can cloud our judgment.

Welcome to a new season of Decoder, and we're kicking things off by exploring a topic that's old as humanity: myths. And since this is Financial Decoder, we're looking at economic myths. Before we get to our guests, let's start by looking at myths in general. It's interesting to me that every culture has myths. People have created myths since time immemorial because the world is complex. Myths are a way to explain those complexities and make them understandable. For example, the ancient Greeks saw the sun rise and set every day. Why did it keep doing that? 

Well, the obvious explanation then was that the god Helios drove his chariot across the sky. They happen to have gotten it wrong, but was any damage really done? Well, probably not. After all, we humans love certainty. Even if something is false, if we like the meaning, we'll cling to it because it makes us feel more secure. And that's how myths have served us through the millennia. The fact that they're not exactly true is beside the point. Or is it?

One of my favorite quotes was originated by Will Rogers. He said, "It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so."

By the way, the Will Rogers part of what I just said is a myth. He definitely wasn't the first person to say that. Some people think it was Mark Twain, but there are doubts about him as well. The more important point is that the problem with the myth is that when you act upon it, you can end up doing something dangerous. Take for example bloodletting. Bloodletting was based on the belief that removing blood eliminated impure fluids from the body. That sounds great. What could go wrong? Well, just ask George Washington. December 13, 1799, was a frigid day at Mount Vernon. It rained, hailed and snowed. Washington was outside for most of it, supervising activities on his estate.

That afternoon he developed a cough, a runny nose, and his voice was hoarse. And by the next morning, he had a fever. Doctors were called and they prescribed bloodletting. By 11:00 a.m., between five and nine pints of blood was removed from him. To give you some perspective, a man of Washington's age and size probably only had about twelve pints to begin with. Not surprisingly, he died that night. The point being that acting upon myths can have consequences. Scrutinize a belief before you act. It could be a myth. Today we'll look at some economic myths that can lead us to make potentially bad decisions and will shed light on those half-truths and nuances that can be confusing. My guest Jennifer Babchuk is going to help us separate the myth from reality.

Jennifer Babchuk is the head of economic research here at the Schwab Center for Financial Research. She leads a team that performs macroeconomic research and analysis that helps to shape Schwab's views and strategies. She joined Schwab in 2019, and she has an M.A. in international economics from Johns Hopkins and a B.S. in neuroscience.

Jennifer, first time on the show, welcome.

JENNIFER BABCHUK: Thanks for having me.

MARK: So Jennifer, I was going to ask you or I will be asking you questions about some specific biases, but before we get to that, what really interested me in your background when we first met is that you've got an atypical background, I think, for most people who end up in an economist role. So I wondered if you could just kind of talk a little bit about that and how that background has informed your approach to some of the questions and problems that people face.

JENNIFER: Yeah, absolutely. So as you mentioned, my path to economics was a little bit unconventional. My undergraduate degree was started off in neuroscience and I've really always been fascinated by how people think, how they make decisions and respond under uncertainty. And it's that interest that eventually led me to pursue a graduate degree in economics, but in many ways, I really don't view the two fields as being all that different.

While economics is often associated with models and data, it's ultimately about people and the decisions they make. And that's one reason that I've always been particularly interested in the behavioral side of economics and investing and how expectations, emotions, and psychology can ultimately influence both economic and financial outcomes.

MARK: This is a great topic. Glad you're here. We're going to be talking about economic information and how to be good consumers of economic information and because this is really important for investors because there's so much economic data out there is being released constantly. Financial news is available 24-7. But certainly when we're interacting with clients, we get to sense that there's some myths that seem to be persisting generation after generation. So first of all, do you agree with that? And to the extent that you do, why do you think some of these myths that we're going to be talking about, why are they so resilient?

JENNIFER: Yeah, you know, Mark, that's a great question. I get the same kind of sense that you do as well. The economy is incredibly complex. It's comprised of a lot of data that is constantly changing. And as humans, we really like to identify patterns, and we have a tendency to distill those complexities into a simpler narrative that is a little bit easier to reconcile. And that's not necessarily a bad thing. Where we can run into problems is when we fail to identify the nuances of those patterns or when the underlying data supporting those patterns changes, rendering them no longer valid. And given that the economy is in a constant state of evolution, it's really important to continuously validate those patterns against the current economic backdrop.

MARK: So let's jump right in and talk about certainly something I hear a lot. It's a common assumption people make that the stock market and the economy are essentially the same thing, that when markets are rising, the economy must be strong and if it's falling, the economy must be in bad shape. Is that the complete story or is there something more to your earlier point? Is there a more nuanced understanding here that people need to be aware of?

JENNIFER: Yeah, I think for a lot of these questions, honestly the answer is going to be it's probably a little bit more nuanced. And it's true that the stock market and economy are related, but they're not exactly the same thing. So we know the economy reflects the health of generally consumers and businesses, while the stock market reflects investors and ultimately what they're willing to pay for future earnings of publicly traded companies. And that's an important distinction because many of these companies operate globally. 

The U.S. economy is primarily measuring activity that occurs here at home, but large publicly traded companies often generate some of their meaningful share of income from overseas. So that means a stock's performance can be influenced both by the domestic economy and also the global economy. And a key distinction here is that the two also operate on a little bit of a different timeline, with economic data generally telling us where we are today, or in some cases where we've recently been, since we know that most economic data is published with at least a little bit of a lag. Whereas the stock market is really more forward looking and prices in where investors think that the economy is headed. 

And this is why we can see the market rise during recession if investors believe that conditions may soon improve. But it also explains why we can see the market fall during periods of otherwise solid economic growth if investors anticipate changes to the economic outlook.

MARK: Yeah, I want you to expand on that point a little bit because I'll often hear, maybe it's a different way of expressing this relationship between the economy and the market, that recessions and bear markets always go hand-in-hand, and sometimes one happens without the other. So what does that tell us about sort of the difference between economic conditions, which are a lot of the economic statistics we're measuring, and investor experience, which is, as you mentioned, is it's a little bit different when you're owning a company.

JENNIFER: Yeah, so that's a great follow-up there. Typically, we think of this as like recession versus bear market. And I think it helps first to unpack the definitions a little bit. So strictly speaking, recession is typically defined as a broad and sustained downturn in economic growth. Sometimes we hear this associated with a two-quarter back-to-back decline in GDP, but not always. Whereas a bear market is typically defined as a stock market decline of at least 20%.

And given the related nature of these definitions, it's not totally uncommon that we can see these occur simultaneously and hence why the myth persists. But the nuance here in the definitions means that they don't necessarily need to coincide. And as we've already talked about, the stock market anticipates future developments, whereas the economic data tells us where we've recently been. Thus it's not totally inconceivable and actually not that uncommon that we can see a bear market commence prior to official warning signals flashing in the economy. And we've also seen bear markets occur in the absence of an economic recession. And a great example of this is actually in 2022, where we had both the S&P 500® and NASDAQ fall by more than 20%. But the economy never actually entered a recession. And during this period, we actually saw the labor market remain pretty strong and economic growth proved more resilient than many folks thought. 

But the disconnect here occurred because investors were repricing assets in response to higher-than-expected inflation. And ultimately, the realization that interest rates would likely need to move significantly higher, which we know tends to put downward pressure on stock valuations. So this is a great reminder that the stock market and the economy are related, but they're not exactly the same thing.

MARK: I think another thing that crossed my mind while you were talking is the fact that investors, and even the media to a certain extent, will talk about, GDP, inflation, how many jobs were created, all these economic statistics as if they're precise numbers. Like someone's literally counting every single widget that's been manufactured or every single price change of goods and services. 

But in fact, these things are really estimates. And then sometimes we get revisions as new data comes in. So if I'm an investor, how should I think about that? The fact that I'm getting this data, it's informing how I should be investing, but what I'm getting is really an approximation, not a precise measurement.

JENNIFER: I think this is a great nuance to tease out because it impacts how we both view and interpret the data, as you mentioned. And quite frankly, the confusion here is pretty understandable in part because some of this data has a lot of hype built up around it in its release. It's usually published by an official government agency, and it's situated very nicely within a clean, polished report. But at the end of the day, most of this economic data are not precise measurements, as you mentioned, but rather they're estimates based on the best information that we have available at a given point in time. 

We know the economy is just simply too large and too complex to measure it perfectly in real time. And that's why many statistics are ultimately revised at a later point as more information becomes available. And in addition to revisions, it's also not uncommon to see changes in how a statistic is calculated.

The lesson here is not that economic data are unreliable, but rather that every economic statistic should be viewed as an estimate and not as a precise number that's set in stone. And as such, I would really caution against putting too much emphasis on a single data point and instead stepping back and looking at that broader trend.

MARK: Yeah, I think that's a good point. The unemployment rate is a good example. That gets so much focus every single month, for good reason, certainly the labor market we all know is important. But also, I think it's important for people to think about how… what's the right way to use a particular statistic. And particularly for an investor, we're more concerned about the future rather than the past. But as you mentioned, I think in the first question, most statistics are kind of backward looking in some form or fashion. So how do you use backward-looking statistics when you're trying to think about the future?

JENNIFER: So let's dig a little bit deeper into the unemployment rate and how it's calculated. So it's a pretty simple calculation, actually. It's the number of unemployed people divided by the total labor force, and it's derived based on a monthly survey of households. There's also several different ways to measure the unemployment rate, one of which is the U-3 rate, which is probably the most commonly cited among many economist media. But there's also another measure, the U-6 rate, which includes discouraged workers and folks working part-time who may actually prefer full-time employment. And depending on which metric you use, you can actually sometimes walk away with a different assessment about the health of the labor market. And because these figures come from surveys, they're not immune to issues like sampling error, response issues, or even later revisions.

And beyond some of the measurement challenges here, it's also important to keep in mind that different indicators serve different purposes. So this gets to kind of what you were speaking about, Mark. Some indicators are leading, meaning that they provide clues about where the economy's headed. Others are coincident, meaning that they help describe where the economy's currently at. And some, like the unemployment rate, are generally considered lagging indicators because they often reflect changes that have already occurred within the broader economy. So in the case of the unemployment rate, you know, we typically don't see companies really ramp up layoffs until only after there's been a persistent and measurable weakening in other parts of the economy. So the key takeaway here is that, you know, when you're looking at a given statistic, ask yourself, what is it actually measuring?

Keep in mind its limitations and assess its broader trend as well as adjacent indicators to ensure you're appropriately contextualizing the data and not assigning too much weight to any single indicator.

MARK: I think another thing that people do a lot with data, analysts, economists, investors, they're looking for relationships between two different statistical series. When one goes up, another one goes down, or two are always moving together. And so that may be indicative of something interesting if they start to diverge. But sometimes those relationships, or at least when I look at some of the data, those relationships can change dramatically over time. There may be a relationship over one period, but it's not necessarily sustainable going forward. So what are some of the dangers, then, if people assume a past relationship will continue when in fact it won't?

JENNIFER: Yeah, so that's a great question there. I mean, I think one of the biggest challenges in investing is really figuring out when is history repeating itself because it sometimes does, or figuring out like has the world fundamentally changed here? And relationships and trends that held in one economic cycle don't necessarily have to survive into the next. So a good example of this is inflation. After more than a decade of low and stable inflation.

Many investors came to believe that inflation would remain subdued pretty much indefinitely. And then when inflation did ultimately rise during the pandemic, many initially viewed it as, you know, the fun word transitory, because that was consistent with recent history. When in reality, we actually saw persistent and broadening inflation that ended up rising above 9%, which we know ultimately drove the Fed to raise rates much more aggressively than most had anticipated. 

And I really want to emphasize here, it wasn't just a handful of investors that got this wrong. lots of well-known economists and key policymakers also failed to appreciate the potential for sustained inflationary pressures. And just taking a step back and viewing this more broadly, in the period following the ‘08 financial crisis we saw expectations for low inflation and low interest rates become embedded in things like asset prices, investment strategies, and even bank balance sheets. And then when rates did rise pretty rapidly during the pandemic, bonds that had been purchased during this low-rate era ended up declining in value. And that repricing, ultimately, is what contributed in part to stress in the banking system, particularly for those regional banks that we saw in 2023. 

So the lesson here is that history can be a pretty powerful guide, but it can also become a trap if we become too reliant on it. It's really important to constantly challenge the prevailing assumptions and ask whether the forces driving today's economy are different from those that drove the last one.

MARK: We'll get back to Jennifer in a minute and discuss more economic myths. But how do we decide if something's a myth or reality? There are many ways to do this, but here's a four-step process to try. Step one is to express the myth in a way that is clear and allows it to be tested. Step two is to find reliable evidence. You get that from multiple independent, reputable sources that either support or refute the belief. Step three tells us to identify alternative, more plausible explanations for any evidence that supports the myth. Finally, step four is to make a new prediction using the myth as the basis for the prediction, then decide whether it's accurate. 

Think of one of your beliefs about investing or economics and give this process a try. Or see if any other myths that strike a chord with you crop up in the rest of the show. Let's get back to Jennifer and her myth-busting.

So Jennifer, you mentioned you mentioned inflation and a lot of times when people are looking to control inflation, for example, they will look to the Fed for solutions. And there's a tendency to think that the Fed can kind of steer the economy wherever it wants. And I think you gave some great examples there where sometimes even policymakers can misinterpret data on occasion. So what are some of the limits on what central banks can really accomplish? How all-powerful are they?

JENNIFER: Yeah, you know, I think a great word to use. They're powerful, but they're not all-powerful. So at a basic level, the Fed influences the economy through things like financial conditions, setting borrowing costs, and signaling expectations. And these tools tend to be most effective when inflation is being driven by aggregate demand, meaning that households and businesses are spending too much relative to the economy's production capacity.

But inflation can also come through the supply side of the economy, with a prime example being an oil-price shock, where higher energy prices put upward pressure on inflation. And in this type of situation, raising rates is not going to produce more oil and it might actually weaken economic activity. And that's why economic theory generally tells us that policymakers should accommodate a one-time supply shock rather than aggressively tighten policy in response.

But the real challenge here comes from determining when a shock is isolated and when it's spilled over into the broader economy. And we tend to see policymakers become more concerned when higher energy costs start showing up in things like wages, transportation costs, and a broader range of prices. And when this occurs, inflation expectations can become entrenched, meaning that businesses and workers start behaving as though inflation is here to stay, which is when we do see policymakers get a little bit more concerned and may need to raise rates in response. So one of the key limitations of central banking is that the Fed is much better equipped to handle shocks to demand rather than supply.

MARK: What if I asked that same question with respect to, instead of policymakers in the Fed, but politicians. A lot of voters, not surprisingly, economic issues are top-of-mind when they're going into the into the ballot box. But you know, as you just kind of laid out in the 20 minutes or so we've been talking, economies are shaped by a lot of different forces, some short term, some much longer term. So how would you characterize the level of influence that politicians actually have over economic outcomes, especially over the short term?

JENNIFER: Yeah, I think that's a really timely question with midterm elections coming up. I will say politicians matter, but they're only one of many factors that ultimately shape the economy. And their influence over economic outcomes is often a little bit overstated, particularly in the short run. So one key challenge is that political and economic timelines don't always align.

Politicians operate on election cycles that are measured in years, whereas many economic trends develop over decades. So for example, if the labor force is aging or housing shortages persist over years, those are issues that no elected official can easily address in a single term. But that doesn't mean that policymakers are completely powerless. They can influence the economy through mechanisms like taxation, government spending, and even trade policy, as we've seen. But those effects typically occur with a little bit of a lag and are often smaller than many people expect. 

And it's also important to remember that many economic developments are outside of any politician's control, which economists like to refer to as exogenous shocks. So things like pandemics, global events, or even technological breakthroughs can have a much larger impact on the economy than any single policy decision. So the takeaway here is that politicians can influence the direction of the economy, but they don't always control it. And we typically see that economic outcomes are the result of a combination of structural trends, private-sector decisions, global events, and government policy all interacting together.

MARK: I want to go back to the Fed for a second. A lot of times people assume that the Fed controls interest rates. And in fact, we just had a Fed meeting conclude just a couple days ago prior to us recording this. And people assume, for example, “Hey, if the Fed were to cut rates, then that's going to… all interest rates are going to come down, and the Fed maybe raises rates and all interest rates go up.” That doesn't always happen that way. Talk to me a little bit about what, when it comes to interest rates, what is the Fed really controlling and what is it not really controlling?

JENNIFER: Yeah, so this is a great question. And I get asked this a lot, actually, especially in the context of mortgage rates, because with the housing market how it is right now, home price values where they are, a lot of people are trying to plan buying a house. And in that plan, they're kind of factoring in where will mortgage rates be a year from now, two years from now? Can I refinance? And they sometimes look at Fed decisions to try to inform their house-buying decisions, which isn't always the best thing to do because ultimately, the Fed only controls what we call the short end of the Treasury yield curve vis-a-vis the federal funds rate, which is essentially an overnight rate used within the banking system, whereas mortgage rates are much more closely tied to the long end of the Treasury yield curve, which is ultimately determined by the bond market and reflects investors' views on things like inflation, economic growth, and even government debt. So let me give you an example here.

So if the Fed cuts rates in response to a weakening labor market, we could still see long-term rates in this scenario remain elevated if investors are worried about things like long-term inflationary pressures or a rising government deficit. So the key takeaway being that the Fed controls the short end of the Treasury yield curve, but the bond market largely determines the long end of the Treasury yield curve, which when we think about it, for example, in the context of mortgage rates, mortgage rates tend to be more closely tied to that long end.

MARK: I got a few questions here about some of the assumptions about rational behavior on the part of individuals that underlie a lot of different economic models. I remember kind of hearing that again and again, again, all the econ classes I took, and then I took one class, behavioral decision making, where the guy said, "OK, everything else everyone else is teaching you is an incomplete story." So why is it important for investors, I guess, to recognize that markets are ultimately made up of imperfect human beings?

JENNIFER: It's funny you mentioned that because a lot of, like you said, a lot of economic models, financial models, assume that people behave rationally. And it's really tempting to make that assumption because it is easier to analyze data with that assumption in mind. But in reality, we know that it's not uncommon for investors to make decisions with incomplete information, under uncertainty, or in emotional environments. And because markets are ultimately the collective results of millions of individual decisions, human behavior inevitably shapes market outcomes. Or put differently, markets themselves don't have behaviors and emotions, but the people participating in them do.

And the reason that this does matter is because market prices don't just reflect what investors know. They also reflect how investors feel about what they know. To sum it all up, I would say investing is both economics and psychology. We know economic fundamentals ultimately drive long-term outcomes, but psychology often explains why markets can temporarily deviate from those fundamentals along the way.

MARK: While we were kind of prepping this this episode, you mentioned some of the ones that you thought were the most relevant were things like anchoring, the anchoring bias, herding, where everyone just starts doing things because everyone else is doing it, confirmation bias. And then you were pointing out that this isn't just about individual investors doing unusual things. They influence economists, analysts, sometimes entire markets. So give me some examples of where you've seen that happening in place, either when it comes to shaping economic expectations or just collective investor behavior.

JENNIFER: Yeah, so let's start with anchoring. So anchoring occurs when we rely too heavily on past experiences when evaluating the current conditions that we're in. And a good example of this is inflation expectations during the pandemic. So backing up a little bit, for nearly a decade following the '08 financial crisis, both interest rates and inflation remained relatively low.

And then the pandemic hits, we end up seeing massive fiscal stimulus combined with supply-chain disruptions. And many investors and economists initially expected inflation to remain relatively benign or transitory, as you may remember. And that is because that had been their experience for so long. Or in other words, they were anchored to this post-'08 environment, which made it harder to recognize that the economic regime may have changed.

And then herding is another great example. The recent AI trade clearly has been supported by real earnings growth and real upside for productivity, but those fundamentals alone don't fully explain the speed of capital flowing into AI-related assets. We see as enthusiasm around a given theme grows, confidence tends to build, and that can attract even more capital and reinforce this trend. And the risk here is that, as consensus builds, fewer people may stop to ask what assumptions are already baked into prices.

And then confirmation bias. This affects how we process information. So we tend to seek out evidence that supports our existing beliefs while giving a little bit of less weight to conflicting information. So take the ongoing conflict with Iran. Despite the conflict persisting for over a few months now, the market has often been very quick to embrace signs of de-escalation. And this is in part because investors want to believe that the economic impacts will be limited while at the same time, we see the same investors might pay a little bit less attention to information that suggests a more protracted conflict because that doesn't fit their preferred narrative.

So the common thread here across all these examples is that biases can influence not just how we interpret the world, but also what information we choose to focus on in the first place. And with that in mind, I would suggest spending as much time challenging your assumptions as you do forming them, with the reminder that the goal here isn't to completely eliminate bias, because that's quite frankly impossible, but rather to recognize when biases might be influencing how we interpret information.

MARK: I think that's fantastic advice. One last question, maybe the most important question here. So we've saved the best for last. How would you suggest investors use economic information thoughtfully without being overly confident in any single forecast, indicator, narrative? It's a very kind of messy, uncertain world out there, but we can't ignore the economy just because it's messy and uncertain. So how's an investor… What's the best way for them to kind of take this information and use it thoughtfully.

JENNIFER: Yeah, I think the most important thing that investors can do is approach economic information with a combination of both curiosity and humility. Throughout the discussion, one recurring theme has been that the economy is nuanced. We see data revised, relationships evolve, and even widely held assumptions can ultimately prove incorrect in the next economic cycle. And that's why it's important not to become overly committed to any single metric.

It also means thinking in probabilities rather than in certainties. We sometimes see the best investors and economists aren't necessarily the ones who predict the future perfectly, but they're usually the ones who understand both what they know and what they don't know, and they're willing to update their views as new information becomes available. And in many ways, investing is really less about finding the right answers and more about asking the right questions. So things like “What assumptions am I making?” “What evidence could change my mind and what risks might I be overlooking?” And those kinds of questions can often be more valuable than any individual forecast. 

And if there's one lesson I'd leave listeners with today, it's be willing to challenge your own narrative as new information emerges and use economic data as a tool for improving your decision making rather than trying to perfectly forecast the future.

MARK: Yeah, and I think you and your team within our group are good examples of that. You're doing lots of scenarios, asking yourself, “Well, what if what if this happens, what if this happens, what if this happens?” Changing assumptions about the path of future interest rates. You're sort of living that advice every single day, right?

JENNIFER: Yeah, we try to do our best. I think one of the things that the post-COVID world has taught us is that there's a ton of exogenous shocks out there and you can have the best forecast, but what you can't do is you can't foresee those exogenous shocks. So being able to look at a few different scenarios and have an understanding of how you could respond or what might happen under those different conditions helps you be more prepared for when the unexpected does occur.

MARK: Jennifer Babchuk is the head of our economics team at the Schwab Center for Financial Research. Jennifer, thanks for being here today.

JENNIFER: Thanks for having me.

MARK: Jennifer gave me a lot to think about, like how to avoid believing even the most compelling myths about the economy. In the meantime, if you'd like to read more from Jennifer, check out her article, "America's New Debt Reality," on Schwab.com. We'll link to it in the show notes. For some more information on economic and personal finance topics, Schwab.com/learn is a great resource. We'll link to it in the show notes as well. You'll find market insights and news, including expert insights on trends of the markets. Schwab's comprehensive website can help you arm yourself against economic and financial myths, so you won't believe what just ain't so. 

If you'd like to hear more from me, you can follow me on my LinkedIn page or at X @MarkRiepe, that's M-A-R-K-R-I-E-P-E. As always, we'd appreciate it if you gave us a rating or review on Apple Podcasts, or comment on the show if you listen to it on Spotify. We always like new listeners, so if you have a friend or two who might like the show, please tell them about us and how they can follow us for free in their favorite podcasting app. 

For important disclosures, see the show notes and schwab.com/FinancialDecoder.

1. ^"Quote Origin: It Ain't What You Don't Know That Gets You Into Trouble. It's What You Know for Sure That Just Ain't So," quoteinvestigator.com, November 18, 2018, https://quoteinvestigator.com/2018/11/18/know-trouble/
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3. ^Dr. Howard Markel, "Dec. 14, 1799: The excruciating final hours of President George Washington," PBS News, December 14, 2014, https://www.pbs.org/newshour/health/dec-14-1799-excruciating-final-hours-president-george-washington
4. ^Thomas DP. The demise of bloodletting. J Royal Coll Phys Edinburgh. 2010; 44(1): 72-77.
5. ^U-3 Unemployment Rate: The official U.S. unemployment rate, measuring the percentage of the civilian labor force that is unemployed and actively seeking work.
6. ^U-6 Unemployment Rate: A broader measure of labor underutilization that includes unemployed individuals, people working part time for economic reasons who would prefer full-time work, and individuals marginally attached to the labor force who want a job but are not currently searching.