Price controls have traditionally been a policy that economists love to use as an example of unintended consequences, but new survey data suggests voters across the political spectrum increasingly support them. We dig into why both Republicans and Democrats are warming to the idea after years of frustration with higher prices. We also walk through what economic theory and history tell us about shortages, production incentives, and the longer-run effects of price ceilings. Finally, we wrestle with a harder question for economics teachers: if students understand the model but still support the policy, what exactly should we be trying to teach?

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In this episode, we talk about:

• Why support for price controls now crosses party lines

• How years of higher grocery, housing, and energy prices may be creating “inflation fatigue”

• Why price ceilings can create shortages and change producers’ behavior over time

• Why understanding the economics of price controls doesn’t necessarily mean opposing them

• What economics teachers can do when students understand the model but reach a different policy conclusion

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This Week’s Drinks 🍻

Jadrian typically joins with a beer, but this time he’s gone with a Cuba Libre Zero. He’s finally taking advantage of the bar cart he was inspired to assemble by friend-of-the-show Brian O’Rourke. Matt went with a Trash Talk IPA from Yards Brewing, served in some appropriately celebratory business-school glassware.

Name That Stat 📊

In what may be a first for the show, we somehow both managed to get our stats this week! Matt shared the stat that drove our episode: the share of Republicans who now say they support government price controls. Jadrian went with a back-to-school theme and shared the percentage of college students who say they have changed their major or concentration because of job market worries.

Show Notes

Price controls are one of those topics that can feel almost automatic in an introductory economics class. Draw supply and demand, put a binding price ceiling below equilibrium, show the shortage, and move on to price floors. New polling data might make this topic a lot more interesting. A CBS News/YouGov poll found a majority support for price controls among Republicans, independents, and Democrats. That caught our attention because the partisan differences are still there, but opposition to price controls is no longer something you can neatly map onto the usual limited-government versus government-intervention divide.

So what changed? Our best guess was fatigue. Consumers have spent years watching grocery bills, housing costs, gasoline, and plenty of everyday purchases get more expensive. Even when inflation slows, that doesn’t mean the price level goes back to where it was before. We talked about the disconnect that creates when economists can say inflation has come down, but consumers continue to see their grocery bill is still much higher than it used to be. After enough years of that, “the government should do something about prices” starts sounding pretty appealing.

From there, we went back to the basic economics of a price ceiling. If the government caps a price below the market equilibrium, consumers want to buy more while producers have less incentive to supply the product. In the short run, that creates a shortage. But the longer-run response may be even more important. Farmers plant less next year. Landlords invest less in maintaining apartments. Developers decide not to build. These aren’t just predictions. The U.S. has a history of wage and price controls in the 1970s and rent control in modern days.

That brought us to the part of the conversation we found most interesting: what if people understand all of that and still support the policy? Jadrian admits to seeing this in his class. Students can predict the shortage and explain how producers will respond, but then continue to support price controls on tuition or rent. It’s possible people aren’t thinking about the market-wide outcome, or they may be thinking probabilistically about themselves: “I can’t afford it now, so if the government lowers the price, maybe I’ll be one of the people who gets it.” A shortage is a cost, but it can feel like a chance at an affordable product that otherwise seems completely out of reach.

That creates an important challenge for economics teachers. Hearing an economic argument once isn’t necessarily enough to overturn years of prior beliefs or personal experience. Maybe our goal shouldn’t simply be getting students to repeat that “price controls are bad.” The more interesting teaching opportunity is helping them recognize the tradeoffs, think about who actually gets the lower-priced good, and compare price controls with policies that attack the supply side of the problem.

We’d love to hear how you think about this one, especially if you teach economics: if students understand why a price control creates shortages but still support the policy, what should we want them to take away from the lesson? Leave a comment and keep the conversation going.

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Pop Culture Corner 🍿

Jadrian’s entry comes with a Not Safe for the Classroom warning. Chris Rock has a stand-up bit that offers his own version of gun control: instead of focusing on guns, make bullets wildly expensive. If ammunition costs enough, people are going to think a lot harder about using it. It may not be the example you want to lead with in your 8 a.m. principles class, but it’s certainly a memorable way to think about how prices change behavior.

Matt brought two clips this week. The first comes from the final episode of Friends, when the group is saying goodbye to Monica and Chandler’s apartment. Chandler reflects on what a beautiful place it was and all the great memories they made there before adding the economist-friendly punchline: because of rent control, the place was a “frigging steal.”

Matt’s second pick shifts from price controls specifically to the broader affordability problem. In the opening number from his favorite movie musical, everyone is dealing with the frustrations of trying to make it in Southern California. But, hey, at least there’s another day of sun. Of course, there’s an economics angle to that sunshine: lots of people want to live in Southern California, and all that demand shows up in housing prices.

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Artificial intelligence is quickly becoming part of the college classroom, whether instructors are ready for it or not. We talk about how we’re using AI to save time as teachers, from writing better quiz questions to helping us prepare course materials, and how we’ve experimented with bringing it directly into class. But the bigger question is what happens when students use these tools to replace the struggle that’s supposed to lead to learning. We dig into where AI can make students stronger, where it might create shortcuts that hurt them, and how all of this is changing the way we think about teaching.

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In this episode, we talk about:

• How LLMs can save instructors time on quiz questions, distractors, announcements, and other teaching prep

• Bringing AI into class to work through game theory and other economics problems alongside students

• The growing divide between students who use AI to build skills and those who use it to avoid building them

• Why struggling with a problem is often part of learning, not an obstacle to it

• How AI is forcing us to rethink assignments, assessments, and what we actually want students to get out of college

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This Week’s Drinks 🍻

We recorded this one in the morning, so the drinks looked a little different than usual. Jadrian had coffee with a splash of Buffalo Trace Bourbon Cream, but only because he wasn’t heading straight to work after recording. Matt kept things technically non-alcoholic with Diet American Dew, served in a Michelob Ultra FIFA World Cup cup for a little extra flair.

Name That Stat 📊

Since we’re talking AI in the classroom, Jadrian shared a stat that looked at how common artificial intelligence use was among college instructors. We know the students are using it to help in the classroom, but what about the professors? Matt went in an entirely different direction, with a focus on Broadway revenue. Despite concerns about ticket prices and struggling shows, Broadway is still generating a pretty remarkable amount of money.

Show Notes

AI is already in the classroom, but “using AI in the classroom” can mean a lot of different things. We’re both using LLMs as part of our jobs, especially for the repetitive work surrounding teaching. They’re great for cleaning up clicker questions, generating new versions of questions, suggesting plausible wrong answers for multiple-choice questions, and helping draft announcements. Anyone who has spent too much time trying to invent a fourth believable distractor knows how useful that can be. The important distinction is that much of this happens outside the classroom.

But Matt has actually experimented with putting LLMs in front of students. One example came from his game theory course, when he introduced the classic beauty contest game. Everyone chooses a number, and the winner is the person closest to a fraction of the group’s average. After playing the game with students, he asks the LLM to play along, too. What makes the response interesting isn’t simply whether it lands on the “right” answer. It can explain the equilibrium, recognize that choosing the equilibrium probably won’t actually win against a room full of humans, and reason through how many steps ahead the other players are likely to think. Matt has also done a similar in-class experiment with a coordination game, showing how an LLM could distinguish between the factually correct answer and the answer most likely to be chosen by everyone else.

The harder part of this conversation is what we’re seeing from students. There’s a potentially huge difference between using AI to help you learn and using AI to avoid learning. Strong students can use these tools to go further than they could before. They are asking more questions, exploring new ideas, improving projects, and getting feedback almost instantly. But we’re also seeing students turn to an LLM the second they encounter friction. Give them an ungraded practice problem, and some will immediately ask AI for the answer. Ask them to recall an elasticity formula and, instead of thinking through which version applies, the first instinct can be to ask a chatbot. The answer might be correct, but the thinking that was supposed to happen along the way disappears.

That’s what makes the idea of productive struggle so important. We’ve always had technology that can do things students are supposed to learn to do. Calculators didn’t eliminate the value of knowing multiplication tables. The fact that a tool can produce an answer doesn’t necessarily mean there’s no value in learning how to reach that answer yourself. With LLMs, though, that substitution can happen across a much wider range of tasks. Jadrian has already adjusted some in his small class by only allowing handwritten notes and assigning in-person quizzes. But if students can hand a reading to an LLM and ask for a summary, then we have to think much more carefully about what the reading assignment was supposed to accomplish in the first place.

The part we’re still wrestling with is what this means five or ten years from now. We may end up with students who become dramatically more capable because AI lets them build on an already strong foundation, while others become increasingly dependent on a tool because they never built that foundation at all. That makes this more than a conversation about cheating or whether ChatGPT should be allowed on an assignment. It’s really a question about what learning looks like when getting an answer has become incredibly cheap.

So we’re curious how this is playing out for you. Where have you found AI genuinely helps someone learn, and where have you seen it become a substitute for learning? Leave a comment and tell us what you’re seeing in your own classroom, workplace, or experience with these tools.

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Pop Culture Corner 🍿

Matt went back to Fiddler on the Roof and the song “Dear Sweet Sewing Machine,” which celebrates a piece of technology that seems pretty ordinary today. But for a tailor in early-20th-century Russia, a sewing machine represented a major productivity boost: suddenly, you could produce substantially more in the same amount of time.

Jadrian has been rewatching Superstore and highlighted an episode where the fictional retailer rolls out an app that lets customers find products, scan their items, and pay without ever interacting with an employee. Naturally, the workers start wondering: if customers can do all of that themselves, why are we here?

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The 2000s were so important, we needed a Part 2 to tackle the Great Recession. We unpack how easy credit, soaring housing prices, risky lending, and the financial system combined to create the biggest economic crisis since the Great Depression. Along the way, we debate whether the government bailouts were the right call and talk about the long-term effects that still shape housing, lending, higher education, and personal finance today.

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In this episode, we talk about:

• What caused the Great Recession and why there wasn’t one single culprit

• The housing bubble, subprime mortgages, and why banks kept lending

• Whether TARP and the bank bailouts were unpopular necessities or policy mistakes

• How the recession permanently changed lending, mortgages, and borrowing

• Why the effects of 2008 still show up today through demographics, higher education, and attitudes toward debt

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Check out the first part of this conversation when we unpacked the rest of the 2000s:

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This Week’s Drinks 🍻

We may be recording on the same day, but that doesn’t mean the drinks need to stay the same. Brian stuck with his cocktail tour of the decade by switching from a mojito to a Cosmopolitan. In contrast, Jadrian switched from his Pickle PBR to something a little more local: Richmond Lager from Hardywood Brewery. Matt stuck with his Summer Shred Hazy IPA from Ever Grain Brewing.

Name That Stat 📊

We stuck with the 2000s themes for our stats this week with data on the amount of value that was destroyed when Enron collapsed, the number of votes that decided the 2000 presidential election in Florida, and the number of banks that failed during 2008. The stats for this week’s episode help frame just how unusual the decade really was.

Show Notes

The aughts were such an important decade that we had to tackle it in two parts. We previously looked at the economy right before it arrived at the edge of the cliff. This episode is about what happened after it went over. The Great Recession reshaped the economy for a long time: unemployment stayed elevated for years, the financial system nearly collapsed, and the recovery became a defining economic experience for an entire generation. If you haven’t listened to Part 1 yet, that’s the perfect place to start before jumping into this episode.

We started our conversation by trying to figure out what actually caused the crisis. There’s no single bad decision. Instead, there were several forces that reinforced one another: historically low interest rates, rapidly rising home prices, increasingly risky mortgages, political pressure to expand homeownership, banks making loans they should have questioned more carefully, and the widespread belief that housing prices simply wouldn’t fall. With all of that we eventually saw falling home values, mortgage defaults, and failing financial institutions.

But with all that happening, we can’t ignore the government’s response. One question we kept coming back to was whether programs like TARP were bad policy or simply the least bad option available. On one hand, bailing out banks that made poor decisions created a clear moral hazard problem and left many people wondering why financial institutions received help while ordinary homeowners struggled. On the other hand, the government could have allowed the financial system to collapse. With the benefit of hindsight, TARP may have been one of the most effective emergency economic policies despite being so unpopular at the time.

We finished by thinking less about what happened in 2008 and more about the repercussions we are seeing today. Buying a home today involves far more documentation and scrutiny than it once did, reflecting the lessons lenders learned after the crash. The recession also caused a sharp decline in birth rates, creating today’s demographic cliff that many colleges are beginning to experience. Today’s younger generations also seem much more cautious about taking on debt, whether that’s mortgages, credit cards, or student loans. Some of those changes are clearly the result of new regulations, while others may simply reflect a generation shaped by watching what happened during the financial crisis.

The Great Recession may have ended years ago, but many of the decisions made during that period still shape the economy we live in today. Looking back, do you think the government made the right choices, or would you have handled the crisis differently? We’d love to hear your perspective in the comments.

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Pop Culture Corner 🍿

Jadrian recommended The Year That Broke America, a book that argues many of today’s political, economic, and cultural challenges can be traced back to the pivotal events of 2000. After spending two episodes unpacking the decade, it’s a fitting reminder that the forces shaping today’s economy had been building for years before the Great Recession.

Jadrian also chipped in one of the more unexpected pop culture picks: footage from the 2008 Rock Paper Scissors National Championship in Las Vegas. Beyond the novelty, it’s a fun illustration of game theory in action. Even in a seemingly random game, players try to anticipate one another’s strategies, making it a surprisingly useful way to think about incentives, expectations, and decision-making under pressure.

Brian highlighted a memorable scene from Despicable Me in which Gru visits the Bank of Evil to ask for a loan. Eagle-eyed viewers will notice the sign underneath the bank’s name: “Formerly Lehman Brothers.” It’s a blink-and-you’ll-miss-it joke, but one that perfectly captures how synonymous Lehman Brothers became with the financial crisis.

Brian also gave a shout-out to his book, Potternomics: Why Wizards Still Live in the Dark Ages. Since the first Harry Potter film premiered in 2001, it also serves as a nostalgic nod to one of the defining cultural phenomena of the decade we just spent exploring.

Matt’s first recommendation comes from The Big Short, specifically the scene that introduces mortgage bonds and explains how home loans were bundled together and sold throughout the financial system. It’s one of the clearest and most entertaining explanations of the financial plumbing behind the housing crisis and pairs perfectly with this week’s discussion.

Matt wrapped things up with a clip from The Office where Warren Buffett unexpectedly appears as a job applicant. Even one of the world’s most successful investors wasn’t immune from becoming part of the cultural conversation surrounding the Great Recession.

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The 2000s began with a strong economy, low unemployment, growing globalization, and plenty of optimism left over from the 1990s. Then came the dot-com crash, 9/11, China’s entry into the World Trade Organization, major manufacturing job losses, and a sharp increase in federal debt. We look at how those events reshaped markets, jobs, government spending, and household finances. We decided to stop just before the Great Recession, which is big enough to get an episode of its own.

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In this episode, we talk about:

• What the 2000s inherited from the booming economy of the late 1990s

• The economic fallout from 9/11 and the wars that followed

• China’s WTO entry, globalization, and the decline of manufacturing employment

• How interest rates, household debt, and easy borrowing set the stage for what came next

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This Week’s Drinks 🍻

Jadrian finally got the chance to bring out his Pabst Blue Ribbon mixed with Grillo’s pickle juice, timed nicely with the approach of Picklesburgh. Matt went with a Summer Shred Hazy IPA from Ever Grain Brewing Company, which has no connection to the 2000s but was apparently overdue for an appearance. Brian leaned into the decade with a mojito, inspired by the super-sweet, fruit-heavy cocktails that were everywhere in the 2000s.

Name That Stat 📊

This week's numbers covered several different corners of the 2000s economy. We looked at the explosive growth of the World Series of Poker's Main Event, the dramatic collapse of the NASDAQ after the dot-com bubble burst, and the millions of manufacturing jobs lost during the decade.

Along the way, we also explored how unemployment, federal debt, and financial markets changed over one of the most turbulent economic periods in recent history.

Show Notes

We have a packed episode, but thankfully we have Brian O’Roark back to help us make sense of the 2000s. It was a decade packed with an incredible amount of economic history, but we start by asking what the decade inherited from the 1990s. The answer was a lot of economic optimism, despite initial fears of bank failures, grounded airplanes, and collapsing computer systems thanks to the Y2K scare.

Unemployment was at levels that once seemed unusually low, the federal government had recently run budget surpluses, globalization was accelerating, and the stock market had spent years climbing. Europe was moving toward physical euro notes, China was approaching entry into the World Trade Organization, and economists had plenty of reasons to believe freer trade and deeper international connections would create broad gains. That optimism did not last long.

The dot-com bubble burst, and the ensuing Nasdaq crash forced some people to remain in the workforce much longer than expected. The broader stock market offered very little progress for anyone who invested in the beginning and was hoping to cash out at the end. This is part of the reason the decade is sometimes described as a lost decade for investors and households.

Even though 9/11 was not primarily an economic event, its economic consequences spread quickly and lasted for years. Airlines stopped flying, travel and commerce were disrupted, and businesses faced an entirely new security environment. The longer-term effects included the wars in Afghanistan and Iraq, the expansion of the security state, and a major increase in military and federal spending. That helped push the national debt much higher during the decade and marked a dramatic break from the budget surpluses inherited from the late 1990s.

The decade also provided an opportunity to look at globalization and the labor market. China’s entry into the WTO accelerated a shift that was already underway in communities built around manufacturing. American manufacturing continues to produce an enormous amount of stuff, but it increasingly does so with fewer workers. Those losses were concentrated in particular towns and regions and led to wider consequences, including effects on health, crime, educational opportunities, political attitudes, and the opioid crisis.

We closed with a look at the numbers that defined the decade: unemployment rising after two separate recessions, household debt payments taking up a larger share of disposable income, median household income struggling to make sustained progress, and federal interest rates moving sharply up and down. The Federal Reserve cut rates aggressively after the early recession, kept borrowing unusually cheap, and later raised rates again before dropping them toward zero during the crisis. We had to stop before covering the Great Recession because it was too important (and too complicated) to squeeze into the end of this conversation.

When you think back on the 2000s, which economic change feels most important to you: the dot-com crash, globalization, 9/11, the changing job market, or something else entirely? Leave a comment and tell us what stands out from your own experience of the decade.

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Pop Culture Corner 🍿

Matt raised a glass to longtime Federal Reserve Chair Alan Greenspan and recommended his book The Age of Turbulence. Greenspan’s decisions, and the wider debate over whether interest rates stayed too low for too long, fit directly into the decade’s story. The book offers a natural companion to the episode’s discussion of monetary policy, recessions, and the buildup to the housing crisis.

Brian revisited the classic Simpsons episode in which Homer’s car ends up immobilized between the Twin Towers. While the rest of the family enjoys New York, Homer is forced to wait all day for a parking official who may arrive at any time. It works as a lesson in opportunity cost and government inefficiency, but it also preserves an image of pre-9/11 New York that now carries much more emotional weight.

Jadrian chose HGTV’s House Hunters, which debuted in 1999 and became a perfect symbol of the housing culture that grew during the 2000s. Cheap mortgages, ambitious renovations, house flipping, and buyers casually discussing budgets that look almost unbelievable today all captured the mood of the pre-recession housing boom. Old clips now feel like little time capsules from an era when rising home values seemed almost automatic.

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America turns 250 this year, so we take a step back to ask how the United States became one of the world’s richest economies. We explored the institutions, policies, and cultural factors that fueled economic growth, from entrepreneurship and corporations to highways and property rights. Along the way, we debated which overlooked policies deserve more credit and which challenges could shape America’s future. Finally, we looked ahead to what America might look like by its 300th birthday.

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In this episode, we talk about:

• Why the United States became one of the world’s economic powerhouses.

• The role of entrepreneurship, immigration, and risk-taking in the American economy.

• Which historical policies quietly transformed economic growth.

• The biggest economic challenges facing America today.

• What innovations and industries could define America over the next 50 years.

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This Week’s Drinks 🍻

This week, we kept things refreshing. Jadrian switched things up with a Bold Rock Blueberry Lemon Hard Cider, a perfect summer drink for the Fourth of July. Matt continued working through his Nova Scotia collection with Tatamagouche Brewing Company’s Hippie Dippie Pale Ale, another souvenir from his trip north. Before diving into economics, we also swapped stories from attending FIFA World Cup matches and compared the very different atmospheres created by fans from around the world.

Name That Stat 📊

This week's numbers all tied into America's 250th birthday celebration. We guessed how much Americans are expected to spend on fireworks this Fourth of July, how many people lived in the United States around the time of Independence, and even how many towns across the country are named "Liberty." A few patriotic statistics made for a fun way to kick off a conversation about America's economic history.

Show Notes

America’s 250th birthday gave us the perfect excuse to ask one of our favorite kinds of economics questions: why did the United States become so economically successful? We start by thinking through some of the country’s earliest advantages. Was it abundant natural resources? Strong property rights? The legal structure behind corporations? Or was it something less tangible, like a culture that rewarded entrepreneurship and encouraged people to take risks? Generations of people were willing to leave everything behind to create a country where trying something new became part of the national identity.

From there, we shifted to the policies that quietly changed the American economy. The Interstate Highway System became one of our favorite examples because it connected markets, expanded labor opportunities, and fundamentally changed how people and businesses interacted across the country. We also talked about the Homestead Act, the Federal Reserve, property rights, the GI Bill, and Social Security, along with the challenge of identifying which policies deserve far more credit than they usually receive.

Looking at today’s economy, we each picked an area where we think the United States still has room to improve. Housing affordability stood out as one of the biggest challenges, especially as restrictive building policies make homeownership increasingly difficult in many cities. Healthcare was another major topic, but not because the quality of care has failed to improve, but because paying for it has become increasingly confusing and expensive. We also discussed education costs and how expanding opportunity remains central to long-term economic growth.

Finally, we looked ahead to America 300. Will artificial intelligence eliminate jobs the same way earlier technologies replaced occupations that once seemed permanent? Could new industries emerge that we can’t even imagine today? We also wondered whether encouraging more entrepreneurship and making it easier for smaller businesses to compete could become one of the defining economic challenges of the next generation.

America’s economy has changed dramatically over the past 250 years, and chances are it’ll look just as different 50 years from now. If you had to pick one policy, innovation, or cultural change that mattered most in building today’s economy, what would it be? We’d love to hear your thoughts in the comments.

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Pop Culture Corner 🍿

Jadrian recommended the new Planet Money book because it felt like all the best episodes of Planet Money merged into a single book. If you enjoy the way the Planet Money team explains complicated economic ideas through fascinating stories, this is an easy addition to your library.

Matt’s America 250 recommendation was Molasses to Rum from the classic musical 1776. He wouldn’t name names, but he’s aware that some people watch the musical every Fourth of July as part of their annual tradition. The song describes the 18th-century Transatlantic economy, which was based on the economic cycle that fueled the “Triangle Trade” between the American colonies, West Africa, and the Caribbean.

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The World Cup has brought millions of international fans to North America, and many are discovering aspects of American life that locals take for granted. Matt and Jadrian explore why visitors are fascinated by things like massive convenience stores, endless product variety, and regional chains. They also dig into the economics behind World Cup ticket prices, player compensation, and the surprising value of hosting global sporting events. Along the way, they discuss how soccer itself is changing as leagues seek new revenue streams.

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In this episode, we talk about:

• Why World Cup visitors are going viral while discovering everyday American experiences.

• How economies of scale help explain Buc-ee’s, giant convenience stores, and product variety.

• Whether hosting major sporting events creates meaningful economic benefits.

• The economics of ticket prices and why they may not be as outrageous as they seem.

• How hydration breaks, advertising revenue, and changing soccer rules could reshape the sport’s future.

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This Week’s Drinks 🍻

With a morning recording session on a workday, the drinks menu leaned heavily toward breakfast beverages. Jadrian enjoyed a “non-alcoholic mimosa” (also known as orange juice), while Matt powered through with a Diet Mountain Dew that was specifically rebranded as “American Dew 250.”

Name That Stat 📊

This week featured a pair of World Cup-themed statistics. The first number focused on the cheapest resale ticket price available for one of today’s matches. The other looked at the number of World Cup players who were born in a different country than the one they were representing on the field.

Show Notes

With the World Cup underway, one of the most interesting stories hasn’t been happening on the field. Instead, it’s been unfolding across social media as international visitors document their experiences traveling through the United States. Fans have gone viral for their reactions to Waffle House, Taco Bell, giant soda fountains, and especially Buc-ee’s. What seems ordinary to Americans often looks extraordinary to visitors encountering it for the first time.

That observation led to a broader discussion about variety, competition, and economies of scale. Jadrian wrote about this in his Monday Morning Economist newsletter, connecting their experience back to the famous stories about Soviet leader Boris Yeltsin visiting American grocery stores decades ago. While the historical circumstances were very different, both stories revolve around the same reaction: amazement at the sheer number of choices available to consumers.

From there, we shifted toward the economic impact of hosting events like the World Cup. Economists are often skeptical of exaggerated claims about sports-driven economic growth, but one potential benefit is much harder to measure: positive publicity. The flood of videos showing visitors enjoying American culture may improve perceptions of the United States as a travel destination long after the tournament ends.

We also took some time to explore how ticket prices fit into the broader sports marketplace. While some World Cup matches are commanding hundreds or even thousands of dollars on secondary markets, those prices still look modest when compared to recent NBA Finals tickets. The comparison raises an interesting question about scarcity, prestige, and what people are willing to pay for a once-in-a-lifetime experience.

Finally, one of the most intriguing economic storylines of this summer’s games is the introduction of hydration breaks. Officially designed to give players time to cool down, these stoppages also create opportunities for additional advertising revenue. Will soccer leagues around the world eventually adopt similar breaks now that it’s happening on the game’s biggest stage? The “rules of the game” are always evolving, and the best way to see that is looking back at some of Major League Soccer’s famously strange early attempts to “Americanize” soccer, including countdown clocks, shootouts, and eliminating ties.

We covered a lot of the economics behind the World Cup in this episode, but we’re curious about something a little different, and we’d love your help. If a World Cup visitor came to your hometown or country, what’s the one place, meal, or experience you’d recommend to help them understand what makes it special? Drop your answer in the comments. If we’re ever in your neck of the woods, we just might add it to our itinerary.

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Pop Culture Corner 🍿

This week’s recommendation stayed firmly on theme. Jadrian’s recommendation was The Longest Penalty Shot in the World (El penalti más largo del mundo), a Spanish comedy built around an economist’s dream scenario. A backup goalkeeper suddenly finds himself responsible for stopping a championship-deciding penalty kick. Thanks to an unusual twist, the kick won’t happen until the next day. That delay creates endless opportunities for strategy, second-guessing, and game theory. The scene is a fun exploration of interdependence as everyone tries to predict what everyone else will do.

Similarly, there is also a great scene from Ted Lasso involving Nate and AFC Richmond’s coaching staff. The coaches spiral into a chain of “he knows that we know that he knows” logic while trying to anticipate their opponent’s strategy. It’s a perfect pop culture example of common knowledge, strategic thinking, and the recursive decision-making that sits at the heart of game theory.

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The 2010s were an unusual economic decade as there was a long recovery from the Great Recession without a major economic shock in the United States. We look at the trends that defined the era, including falling unemployment, the rise of smartphones, the growth of the gig economy, and the emergence of Bitcoin. Along the way, we debate whether Obamacare was the decade’s most important policy and whether low interest rates set the stage for some of today’s economic challenges. The result was a fascinating look at how many of today’s economic realities were built during the 2010s.

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In this episode, we talk about:

• Why the 2010s may be remembered as the “recovery decade.”

• The economic impact of smartphones, apps, and Bitcoin.

• Which trends from the 2010s still shape the economy today.

• The rise of gig work and changing labor markets.

• Obamacare and the decade’s biggest policy battles.

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This Week’s Drinks 🍻

Jadrian is still working through a Sam Adams variety pack, with this week’s contribution being a Breakaway Blonde. Matt just got back from a cruise up to Halifax, and he’s cracking open a Tiny Angus from Breton Brewing Co. The beer itself wasn’t the entire story, though. The real adventure involved hauling a giant box of Canadian beer off the cruise ship after discovering that local liquor stores sold individual cans from regional breweries.

Name That Stat 📊

Our numbers this week ranged from timely to topical. Matt shared the annual compensation of FIFA President Gianni Infantino, sparking a conversation about whether that figure is too high, too low, or about right compared to leaders of other major sports organizations.

We initially skipped Jadrian’s number entirely, but remembered it midway through the episode. Fortunately, his statistic fit perfectly with our discussion of the 2010s, focusing on the amount of Bitcoin involved in the first-ever commercial purchase of two pizzas.

Show Notes

When people think back on economic history, they usually remember dramatic moments: crashes, recessions, bubbles, or breakthroughs. That’s what makes the 2010s such an interesting decade. One of the defining features of the period may have been the lack of a single major disruptive economic event in the United States. Instead, the decade was largely shaped by a long recovery from the Great Recession and a steady return to economic normalcy.

While events like the European debt crisis, concerns over government debt, and political movements such as Occupy Wall Street and the Tea Party captured headlines, much of the economic story centered on slowly improving labor markets, rising household incomes, and a return to economic stability.

Unemployment fell from nearly 10% at the start of 2010 to just 3.6% by the end of 2019. At the same time, labor force participation drifted lower as Baby Boomers retired and some workers left the labor market altogether. The result was an economy that slowly but consistently tightened, eventually producing stronger income growth in the latter half of the decade.

With the benefit of hindsight, there are several candidates for the decade’s most important economic development. One contender was the rise of the gig economy. Companies like Uber and Lyft normalized flexible work arrangements and created entirely new ways for people to earn income. What felt revolutionary at the time now feels so commonplace that it’s easy to forget how quickly these platforms transformed labor markets.

Several other developments quietly reshaped the economy. Fracking dramatically increased domestic energy production and helped keep energy prices lower than they otherwise would have been. Meanwhile, Bitcoin and cryptocurrency emerged from niche internet experiments into assets that would eventually become part of mainstream financial conversations.

But if there was one innovation that connected nearly every major trend of the decade, it was the smartphone, which fundamentally changed how Americans navigate, shop, pay for goods, consume media, communicate, and even work. Ride-sharing apps, mobile banking, streaming services, social media, GPS navigation, and countless other conveniences all became possible because powerful computers migrated into our pockets. Looking back, it’s hard to imagine any other technology having a larger effect on daily life during the 2010s.

Finally, no discussion of the decade would be complete without policy. The Affordable Care Act dominated political and economic debates throughout the 2010s, generating intense disagreement that continues today. Of course, this decade also saw regulatory reform, rising federal debt, and the broader political backdrop of the Tea Party movement and Occupy Wall Street. Whether you view these developments as successes, failures, or something in between, they helped define the economic and political landscape that carried into the 2020s.

Economists love making lists, and we’re willing to admit ours might be incomplete. What did we miss? If there’s a defining economic moment from the 2010s that deserves more attention, tell us in the comments and make your case.

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Pop Culture Corner 🍿

Jadrian kept things topical with a look back at Shark Tank, one of the defining television hits of the 2010s. Beyond the memorable pitches and dramatic negotiations, the show offers a surprisingly useful way to teach economics. In the middle of the decade, a group of economists developed lesson plans and classroom activities built around selected clips from the show, using them to explore entrepreneurship, costs of production, and business decision-making.

Matt’s selection was Hadestown, the acclaimed musical inspired by the myth of Orpheus and Eurydice. While the story is set in a post-apocalyptic world with strong Great Depression-era influences, it raises questions about migration, opportunity, labor, and economic hardship that connect surprisingly well to many of the issues discussed throughout the episode.

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The 2020s have already delivered one of the strangest economic decades in modern history. We unpack how the pandemic reshaped work, inflation, housing, consumer behavior, and even the way economists think about recessions. We debate whether the pandemic or AI will ultimately define the decade, revisit the policy decisions that still shape the economy today, and talk through why everything from used cars to mortgage rates suddenly felt upside down. Along the way, we explore why the economy has seemed surprisingly resilient despite nonstop shocks, disruptions, and uncertainty.

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In this episode, we talk about:

• Whether the pandemic or AI will be remembered as the defining economic event of the 2020s

• Inflation, stimulus policies, tariffs, and the strange post-pandemic economy

• How housing, work-from-home, and consumer habits permanently changed

• Why the 2020s economy has felt unusually weird and unpredictable

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This Week’s Drinks 🍻

Jadrian cracked open a Hardywood Pils, leftover from an end-of-semester cookout with his TAs. He almost grabbed the PBR x Grillo’s Pickle Beer, but decided to save that adventure for a future episode. Matt went with a Hammerhead IPA from Big Oyster Brewery, a West Coast-style IPA brewed with six hop varietals for an intense citrus and grapefruit character with notes of pine.

Name That Stat 📊

We originally planned to talk about the economics of higher education, so Jadrian brought in a stat on the number of graduate programs in the U.S., which has grown by roughly 69% since the early 2000s. But once we decided to launch our “economics by the decade” series, Matt pivoted to one of the defining economic indicators of the 2020s: the inflation rate that peaked in June 2022 at its highest level since the early 1980s.

Show Notes

We’re kicking off a new series that looks back at the biggest economic stories of every decade, starting with the 2020s and working backward through history. We’re taking a shot at making sense of the economic chaos of the 2020s. Honestly, “chaos” might undersell it a little. It should be no surprise that we start with the pandemic, which instantly disrupted employment, supply chains, education, consumer habits, and everyday life. But twenty years from now, will we remember the pandemic as the biggest story, or will the introduction of generative AI ultimately eclipse it?

Perhaps the most common theme of the episode is how weird the economy has behaved this decade. Historically, recessions, unemployment, inflation, and growth tended to move together in more predictable ways. The 2020s constantly break those expectations. One easy example: the NBER determined that the pandemic recession officially lasted only two months, even though the traditional shorthand definition of a recession involves two quarters, or six months, of decline. Of course, the disruption lasted much longer than two months, which allowed educators the chance to explain the ways economists define and measure different indicators.

The 2020s also included large spikes in inflation without the kind of sustained unemployment that economists might typically expect. The decade saw regional bank collapses, sweeping tariffs, and repeated uncertainty, but markets often just kept chugging along. Even the stock market wasn’t immune to the weirdness.

There were also some pretty big policy decisions this decade, not all of which have been consensus picks. A lot of people would argue that the earliest rounds of pandemic relief were necessary to prevent economic collapse, while later stimulus packages may have contributed to inflation once the economy had already stabilized.

But did policymakers really know the economy was in a good place at the time? Maybe not. There was no serious economic justification for imposing widespread tariffs on our trading partners, notwithstanding that tariffs are almost universally disliked by economists. One takeaway for listeners is that nearly every major decision of the decade came with enormous trade-offs and very little certainty.

Not to be left out, but housing and consumer trends were also contenders for the defining stories of the decade. Ultra-low pandemic-era mortgage rates locked many homeowners into staying put, while newer buyers suddenly faced dramatically higher borrowing costs. Meanwhile, consumers saw a massive uptick in online ordering, curbside pickup, delivery apps, and mobile-first shopping experiences that never really disappeared afterward.

In many ways, the 2020s feel like a decade where the economy keeps absorbing shocks that would have seemed unimaginable only a few years earlier. And somehow, despite all of it, things keep moving forward, even if nobody is entirely sure what “normal” is supposed to look like anymore.

So tell us: what did we miss? What do you think will define the 2020s economically? And which decade are you most excited for us to cover next?

Leave a comment and let us know how wrong we were.

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Pop Culture Corner 🍿

While it’s not a traditional pop culture contribution, Jadrian shared a book recommendation: Financial Diaries by Jonathan Morduch and Rachel Schneider. The authors draw on the lives of 235 low- and middle-income families over the course of a year, using those diaries to challenge popular assumptions about how Americans earn, spend, borrow, and save. The book highlights how income volatility, not just low income, creates financial stress for many working families.

Matt has recently been working on expanding his pop culture reach across new disciplines, including political science and accounting. His contribution this week included a classic scene from Office Space, where “The Bobs” are brought in to audit Initech.

The second clip comes from a project on helping accounting professors teach their courses. In the following scene from The Office, Michael Scott puts discount tickets randomly into boxes. The accounting question: how does that liability factor onto the balance sheet?

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Teenagers today are far less likely to work than previous generations. This episode explores the long decline in teen labor force participation and tries to identify some possible causes. The conversation also turns personal, with reflections on the skills we gained from working early. Along the way, we debate whether teenage jobs still provide important lessons in responsibility, communication, and independence.

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In this episode, we talk about:

• Why teen labor force participation has fallen so dramatically since the 1970s

• Whether modern teenagers value independence differently than previous generations

• How working as a teenager builds confidence, responsibility, and communication skills

• The role of extracurriculars and college competition in shaping teen time use

• Whether colleges undervalue work experience compared to other activities

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This Week’s Drinks 🍻

Jadrian cracked open a Hardywood Fighting Hokie Hefeweizen, although the real story was that he found the unopened can under the seat of his car and has absolutely no idea how it got there. Matt kept things classic with a Dogfish Head 60 Minute IPA. It’s not quite as mysterious, but a reliable go-to.

Name That Stat 📊

This week’s statistics covered two very different topics. Jadrian shared an estimate on the share of websites created since 2022 that may have been generated with artificial intelligence. Matt brought data on the share of teenagers participating in the labor force back in 1978, which set up the broader conversation for today’s episode.

Show Notes

This week’s episode centered on a deceptively simple question: why aren’t teenagers working as much anymore? The decline in teen labor force participation seems to happen in waves, but the long-term trend is unmistakable. One possible explanation is surprisingly simple: fewer teenagers are getting driver’s licenses, which means fewer have the independence or transportation needed to get to work. If there’s no rush to get out of the house and get a car, perhaps teenagers aren’t finding that same rush to get out and go to work.

Another possible explanation is financial. With higher household incomes and smaller family sizes, parents may be more able to support their children without requiring them to earn their own spending money. That removes one of the biggest traditional incentives for teenagers to work in the first place.

We also discussed how teenagers spend their time differently today. There’s growing pressure to focus on extracurricular activities, sports, leadership positions, and resume-building experiences, especially as college admissions have become more competitive. But that raises an interesting question: why are unpaid extracurriculars often viewed as more valuable than paid work experience?

Finally, we explored the idea that some teenagers may avoid work because they don’t see a direct connection between a part-time job and their future career goals. If the payoff is not immediate or obvious, working may feel less worthwhile. In that sense, the decision not to work can become a strategic one rather than simply a matter of laziness or lack of opportunity.

We want to hear from the parents out there: do your teenagers want part-time jobs? If not, what do you think changed compared to when you were growing up?

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Pop Culture Corner 🍿

Jadrian’s contribution had absolutely nothing to do with teen employment. Instead, he used the opportunity to recommend a new book from friend-of-the-show Brian O’Roark. His new book, Potternomics, explores economics through the world of Harry Potter. Hopefully, we can get Brian to join a future episode and talk Hogwarts economics with us.

Turns out Matt also didn’t have a teen employment pop culture reference ready to go, so he pivoted to a guest lyric from Jay-Z on a Diamonds from Sierra Leone (Remix) track: “I’m not a businessman, I’m a business, man.” It’s a surprisingly useful way to think about personal finance and self-investment.

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This episode breaks down what non-compete agreements are and why they’ve become such a hot topic in labor economics. Matt and Jadrian explore when these contracts make sense and when they might go too far. They weigh the trade-offs between protecting company investments and limiting worker mobility, while also digging into recent policy debates and what non-competes mean for innovation and entrepreneurship.

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In this episode, we talk about:

• What non-compete agreements are and why companies use them

• Whether it’s reasonable to restrict employees from working for competitors

• The fairness (or unfairness) of non-competes after leaving a job

• The role of non-competes in limiting job mobility and career growth

• State-level bans and the brief FTC attempt to outlaw non-competes nationally

• Whether non-competes function similarly to patents in protecting investments

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This Week’s Drinks 🍻

This week featured a couple of solid, no-nonsense beer picks. Jadrian went with a Sam Adams Cold Snap White Ale, a citrusy, spiced brew with clementine and orange peel that paired perfectly with chips and homemade salsa. Matt opted for a Founders Centennial IPA, a go-to choice that balances quality with value. Nothing says economist like getting a 15-pack for the price of a 12. Classic Matt.

Name That Stat 📊

This week’s stats covered two very different corners of the economy. Matt brought in the surprisingly large number of Bitcoin ATMs in the U.S. after spotting one at a gas station. Jadrian followed up with a stat tied to last week’s conversation, showing that households spend about 5% more on groceries when men do the shopping compared to women.

Show Notes

Non-compete agreements sound simple at first: you work for a company, and in return, you agree not to work for their competitors. But the reality is much more nuanced. There are two main types: those that apply while you’re employed and those that extend after you leave. The first type makes a lot of intuitive sense. If you’re working for a company, it’s reasonable they don’t want you splitting time or sharing insights with competitors.

Things get trickier with post-employment non-competes. On one hand, companies invest real resources into training employees and developing proprietary knowledge. From that perspective, it makes sense to protect that investment. It’s similar to how patents give firms time to profit from innovation before competitors can copy their ideas. But on the other hand, restricting workers after they leave can limit career opportunities and slow down the natural movement of talent in the economy.

There can be some vagueness to these agreements that make the situation even stickier. Saying “you can’t work for a competitor” sounds straightforward, but defining a competitor isn’t always obvious. Is LinkedIn a competitor to a job board? Is Google? Without clear boundaries, these agreements can create uncertainty and risk for workers trying to make career moves.

Non-competes may reduce job mobility, which is generally seen as healthy for both workers and firms. There’s also the argument that they suppress entrepreneurship. If people can’t leave to start competing businesses, fewer new ideas make it to market. While some claims (like thousands of startups being lost each year) may be overstated, the underlying concern is real.

So, do the benefits of non-competes outweigh the economic costs? We’re in another familiar space for economists: it depends. Non-competes can be reasonable in some contexts, but they can also be overused or abused. The challenge is likely in balancing incentives for firms with freedom for workers.

Have you ever been subject to a non-compete agreement? If so, did it actually change how you approached your next job search or the opportunities you considered?

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Pop Culture Corner 🍿

This week’s topic stumped us at first. We couldn’t quickly name a pop culture tie-in for non-competes. After a quick search, we found a great example from Hacks, where Deborah’s non-compete agreement becomes a major plot point. You can see what led up to that moment here:

We usually stick to movies, TV, and music, but this time we’re also throwing in a real-world pop culture moment. A quick search reminded us of the famous story of Conan O’Brien navigating a non-compete agreement with NBC in 2010. It’s a good example of how these contracts can play out on a very public stage.

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Explore the current state of financial literacy as we celebrate Financial Literacy Month. We walk through the “Big 3” financial literacy questions and discuss how surprisingly few people answer them correctly. For many people, financial knowledge is learned through experience rather than formal education, but that’s starting to change as more states push for personal finance requirements.

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In this episode, we talk about:

• What Financial Literacy Month highlights and why it matters

• The “Big 3” financial literacy questions and how people perform on them

• Gaps in financial knowledge across education levels

• How personal experiences shape financial understanding

• Simple, practical advice for managing money more effectively

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This Week’s Drinks 🍻

Jadrian is working through a spring variety pack from Samuel Adams, featuring the Breakaway Blonde. Matt has cracked open an Edelmeister IPA from Poland, even though he’s never been to Poland and isn’t entirely sure where this one came from. It’s the middle of April, which means the end of the academic year is approaching. Things are getting busy, but it’s also a time filled with celebrations, ceremonies, and opportunities to recognize students’ accomplishments.

Name That Stat 📊

April is Financial Literacy Month, which sets the stage for a conversation about how well people actually understand basic financial concepts, and the answer is: not as well as you might expect. Matt shares a statistic on the average retirement balance for people in their early forties, while Jadrian highlights how people perform on the Big 3 financial literacy questions across different education levels.

Show Notes

This week’s conversation focuses on how little formal financial education many people receive growing up, and how most people end up learning about money in practice. Even with advanced degrees in economics, it’s easy to feel unprepared when making real financial decisions for the first time. Much of our own understanding came through trial and error: credit card mistakes, missed payments, and learning how interest works in real life. These experiences can be costly, but they often become important turning points in building financial awareness.

The “Big 3” questions cover topics on compound interest, inflation, and diversification, and can serve as a simple benchmark for financial literacy. Many people struggle with them, even though these concepts appear in economics courses. That raises a bigger question: are we teaching these ideas in a way that connects to people’s everyday financial decisions? There may be room to better bridge the gap between economic theory and personal finance.

Finally, we share some practical advice based on both experience and common guidance. The most consistent recommendations tend to be: (1) build an emergency fund, (2) understand how interest works, especially on debt, (3) avoid carrying credit card balances, and (4) take advantage of employer retirement matches. More than anything, financial success comes down to building consistent habits rather than chasing perfect strategies. Small, steady decisions matter more than people often realize.

Do you think we missed something that should be on that list? Let us know in the comments!

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Pop Culture Corner 🍿

Jadrian went with the song $ave Dat Money by Lil Dicky, which humorously focuses on cutting costs and avoiding unnecessary spending. He’s trying to do something that other rappers just can’t seem to understand. (Warning - NSFW.)

Matt brings up an episode of Cheers where Rebecca, facing financial struggles at the bar, thinks the best plan is to use petty cash to buy lottery tickets. It’s definitely an example of questionable financial decision-making.

Matt also recommends two books for those interested in personal finance: To Die with Zero and The Simple Path to Wealth. Both offer thoughtful perspectives on money, though they approach the topic from very different angles.

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How early is too early to get to the airport? This episode looks at that question through an economic lens. We explore the tradeoffs between time, risk, and the cost of missing a flight, using data and real travel experiences. What seems like a simple decision turns out to reflect how we think about uncertainty, incentives, and risk.

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In this episode, we talk about:

• The tradeoff between arriving early and risking missed flights

• How opportunity cost shapes airport arrival decisions

• Real-world data on how early people actually arrive at airports

• Why small airports vs. major hubs change optimal timing

• Risk aversion in travel decisions and flight planning

• Airline incentives, overbooking, and voluntary bumping decisions

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This Week’s Drinks 🍻

Spring break might be over, but the drinks still feel like spring. Jadrian is trying a Sam Adams Blackberry Wheat Beer from a new variety pack, and Matt is pouring a Kalik from his recent cruise to the Bahamas. It’s a fitting way to celebrate some big news: Susquehanna has been ranked third in the country for undergraduate business experience by Poets & Quants.

Name That Stat 📊

Matt kicked off our new segment with a number that highlights the recent jump in fuel prices from late February to mid-March. Jadrian kept things going with another price increase: how much fresh fruit and vegetables have risen over the past year.

Show Notes

Today’s episode was motivated by an article Matt read about a family who spent $30,000 on a cruise but lost it all at the gate. The issue? They were scheduled to fly into the cruise port the morning of departure, but their flight was delayed just enough that they missed the cruise entirely.

We’re not diving into the economics of delays or cancellations, but the story got us thinking about a different question: how early should you get to the airport? It’s a simple setup that highlights a classic tradeoff. Arrive too early and you’re wasting time at the airport. Arrive too late and you risk missing your flight. The “right” choice depends on how you balance time versus risk.

Survey data suggests many travelers aim to arrive one to two hours early, though actual behavior varies widely depending on experience and preferences. We share some of our own strategies, but it turns out that has been thinking about this too.

Drawing on data from 800 flights, he offers a framework for when travelers should arrive at the airport. His approach considers many of the same factors we talked about, including things like drive time, airport size, and whether you’re flying through a regional airport or a major hub.

Silver Bulletin

I've tracked my last 800 flights. Here's when you really need to get to the airport.

Dec. 24, 2025: Amidst the holiday travel season, we’ve updated this article with some additional charts. But the spreadsheet version at the end still reflects our most comprehensive approach. The text of the article is unchanged from August…

Read more

8 months ago · 394 likes · 98 comments · Nate Silver

George Stigler famously observed, “If you never miss a plane, you’re spending too much time at the airport.” It’s a common experience that is also a useful way to think about everyday decision-making. People differ in their tolerance for risk, how they value time, and how flexible they can be if something goes wrong. Whether it’s arriving early, cutting it close, or accepting compensation to take a later flight, each choice reflects a personal optimization problem shaped by constraints and incentives.

Would you rather arrive early and wait, or risk missing your flight to save time?

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Pop Culture Corner 🍿

In a podcast first (we think), Matt ceded his pop culture segment so Jadrian could share two clips. The first comes from Brooklyn Nine-Nine, where a risk-averse character plans to arrive at the airport five hours early for a domestic flight. His coworkers convince him to go even earlier (seven hours ahead of departure). Despite all that, he still ends up missing the flight, though he had (of course) booked a backup flight just in case.

In Jadrian’s second clip, he turns to the question of whether to accept airline vouchers to take a later flight. In Life in Pieces, one family repeatedly volunteers to get bumped in exchange for vouchers, only to end up stuck overnight when the last flight is canceled. They take it in stride, though, because the airline covers the hotel.

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Prediction markets allow people to bet on future events, from elections to economic data releases, with prices reflecting the crowd’s expectations. Economists often view them as powerful forecasting tools because participants have money at stake, which can lead to more accurate predictions than traditional polling. But these markets also raise concerns about manipulation, insider information, and ethical questions about what events should be traded. Together, we explore both the promise and the risks of prediction markets.

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In this episode, we talk about:

• What prediction markets are and how event contracts work

• Why prediction markets often outperform traditional polling

• The role of incentives and “skin in the game” in improving forecasts

• The potential for insider information or manipulation in these markets

• Whether prediction markets should be regulated like gambling or financial markets

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This Week’s Drinks 🍻

We’re checking in together a little earlier than normal since we each have Spring Break trips coming up soon. Matt brings a Ring the Bell American Lager from Conshohocken Brewing Company. In a rare day when he has an IPA and Matt does not, Jadrian opens Liftoff, a West Coast IPA from Daredevil Brewing Company in Indiana, courtesy of a colleague who brought beers to JETSet.

Name That Stat 📊

Jadrian shared the number of companies that have filed lawsuits against the federal government seeking tariff reimbursements after a recent Supreme Court ruling. Matt followed with a second number that sparked today’s conversation: the amount a tax economist bet on a prediction market that last year’s DOGE push wouldn’t meaningfully reduce federal spending.

Show Notes

Matt’s contribution helped us set up a broader discussion of prediction markets. These platforms allow participants to buy and sell contracts based on the outcomes of future events. Contracts usually trade between zero and one dollar, paying out one dollar if the event occurs and nothing if it doesn’t. In practice, the price reflects the market’s estimate of the probability of an event happening. These markets cover everything from elections and economic indicators to corporate decisions and sports outcomes.

The tax economist in the story reportedly wagered his life savings that federal spending would remain high despite political pressure to reduce it. His reasoning was grounded in a simple economic insight: entitlement programs make up such a large share of federal spending that short-term policy pushes are unlikely to meaningfully reduce overall expenditures. The bet paid off and illustrates how people with specialized knowledge can profit when they believe markets are mispricing an outcome.

We also discuss why economists have long been fascinated by prediction markets. Unlike opinion polls, participants have money on the line, which encourages them to reveal their true beliefs. This “skin in the game” helps prediction markets aggregate information across many individuals and often makes them surprisingly accurate. Some companies have even experimented with internal prediction markets to forecast sales or project outcomes, sometimes outperforming traditional forecasting methods.

Of course, prediction markets also raise difficult questions. If someone has inside knowledge or the ability to influence an outcome, they could potentially manipulate the market. Examples range from bets about public speeches to speculation about political behavior. These situations blur the line between information discovery and market manipulation.

That leads to the broader policy question: how should prediction markets be regulated? They sit somewhere between gambling and financial markets, and it’s not always clear which rules should apply. Some regulation may be necessary to prevent manipulation or insider trading, but too much could eliminate a tool economists believe provides valuable information about future events.

If you could create a prediction market about anything, what event would you want people betting on?

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Pop Culture Corner 🍿

Jadrian contributed a clip from an Anderson Cooper segment highlighting a man who spent hundreds of dollars trying to win an Xbox at carnival games, but eventually drained his life savings in the process. It should be seen as a cautionary tale about gambling and risk-taking.

Matt shares a short clip from a YouTube creator who bets $100 per day on different events in prediction markets. In the clip, the bettor wagers that a State of the Union speech will last longer than 115 minutes and nervously watches the speech unfold as applause and interruptions stretch the clock. The bet ultimately loses when the speech ends just short of the target time.

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A recent headline claimed that Canada’s GDP per capita has fallen below Alabama’s. That sparked a broader conversation about what GDP per capita actually measures and why it can change in surprising ways. We explored possible explanations, including immigration patterns, post-pandemic growth differences, and policy environments. Along the way, we asked a bigger question: what really drives long-run economic growth?

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In this episode, we talk about:

• Why GDP per capita in Canada now trails Alabama’s

• The difference between GDP per capita and median income

• How immigration can lower averages even if individuals are better off

• Why U.S. GDP per capita has grown steadily since 2020 while Canada, Germany, and the U.K. have stalled

• Whether pro-growth business climates actually explain the recent divergence

• How stereotypes about “poor” regions can lag behind economic reality

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Show notes & references

We’re nearing the halfway point of the semester, which is a great time to check in with each other. Matt has been working on international initiatives, and Jadrian has been deep in the redesign of his sports economics course. For drinks this week, Matt just returned from a trip to Cyprus and brought back a Shockwave Pale Ale from a small bottle shop. Unfortunately, the pint glass didn’t survive the trip home. Jadrian opted for a Blackberry Lemon Shandy from Rusty Rail, courtesy of a friend in State College.

Our data point challenge this episode started with how long it’s been since the U.S. men’s hockey team last won gold at the Winter Olympics. Matt followed that up with two numbers that sparked today’s main topic: Canada’s GDP per capita compared to Alabama’s.

From there, we unpacked what GDP per capita actually measures. It’s an average, and averages can move in ways that don’t always reflect individual well-being. We compared this to U.S. median household income data from FRED, which can tell a very different story than GDP per capita. The distinction between median and average matters, especially when population changes are involved.

We also looked at recent trends across other developed economies. While U.S. GDP per capita has steadily increased since the pandemic dip, Germany and Canada both saw initial rebounds followed by declines in the past few years. The United Kingdom experienced a similar bounce but has been largely flat more recently. That raises a broader question: what explains the divergence?

So what can (and can’t) GDP per capita tell us about well-being? There’s a straightforward “math story” here. Even if everyone in a country is better off than they were before, averages can fall if the population grows quickly and new workers enter at lower wages. True statistics can still be interpreted in misleading ways.

We also spent time discussing two popular measures of economic freedom: one from the Heritage Foundation and another from the Fraser Institute. According to the Heritage Foundation’s index, Canada has ranked higher than the U.S. in recent years. That gap may be influenced in part by trade policy uncertainty in the United States, though the full story is more nuanced.

While much of our focus was on what might be happening in Canada, we also asked whether Alabama deserves more credit. Cities like Huntsville have worked hard to attract business investment and lower unemployment. The authors of the original article traveled to Alabama expecting one story and came away with another. Stereotypes about regions can linger long after the underlying data changes.

If you’re in Canada or Alabama (or Germany, or the U.K.), we’d love to hear your perspective. What are we missing?

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Pop Culture Corner 🍿

Matt brought up an example of creative destruction, one of the key forces behind long-run income growth. In a classic Friends episode, Joey flips through the Yellow Pages to find a guitar instructor. At the time, those thick books were a household staple. Today, they’re mostly obsolete, replaced by web searches, Yelp, and online directories.

Jadrian chose a classic South Park episode that a graduate student recently shared with him. In the scene, immigrants from the future arrive in town and begin undercutting local wages. Residents storm a city council meeting to complain that the newcomers are “taking their jobs” and demand action. It’s exaggerated, but it highlights a real economic tension around immigration, wage competition, and public perception.

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We’re joined by Doug McKee to talk about how economists can use assessments and experiments to improve teaching and learning. Doug explains how learning assessments can reveal what students actually understand, not just how they feel about a course. We also discuss the Economic Education Network for Experiments (EENE) and why large, multi-institution studies matter for credibility. Our conversation highlights how economics classrooms can double as powerful research labs for understanding learning itself.

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In this episode, we talk about:

• Doug’s path into economics teaching and education research

• Why student learning assessments matter more than course evaluations

• How Cornell built a culture around prerequisite and skills-based assessments

• The origins and goals of the Economic Education Network for Experiments (ENEE)

• Using large, multi-school experiments to test what really works in the classroom

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Show notes & references

We’re joined this week by Doug McKee, a senior lecturer in economics at Cornell University and one of the leaders behind the Economic Education Network for Experiments. He’s keeping it simple with high-pulp orange juice, while Jadrian braces for another impending snowstorm with a Dark Starr Dry Irish Stout. Matt has logged in with a flight of beers from the back booth at East End Brewing Company in Pittsburgh.

Our data point challenge this episode focused on the age of Trump’s most recent announcement regarding the next potential Chair of the Federal Reserve, the number of undergraduate students enrolled at Cornell University, and the number of people who have been killed by ICE agents in Minneapolis so far this year.

Doug kicked off the show by sharing his fairly unconventional path into economics education research. After becoming frustrated with the traditional publication process, he realized that he couldn’t stop thinking about teaching. That shift eventually led him to Cornell, where institutional support made it possible to treat teaching as a serious research agenda.

A big part of his research agenda involves measuring what students actually learn. Doug has helped Cornell faculty work together to clearly define learning goals and then build assessments around them. Instead of relying only on student evaluations, these tools provide concrete evidence about which skills students gain before and after course redesigns. The assessments started as internal tools and eventually became the foundation for larger studies across institutions.

By pooling data from many courses and universities, researchers can separate what works in one classroom from what works more generally, across different student populations and institutional types. This motivation led to the creation of ENEE, a collaborative network that allows instructors to run coordinated experiments in real classrooms. Doug walks through current projects, including studies on team contracts in group work and earlier work on AI and classroom practices.

If you could run one large-scale classroom experiment across many universities, what question would you want it to answer?

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Pop Culture Corner 🍿

Jadrian shared a clip that was sent his way earlier in the week by Charlie Ben-Nathan, an economics educator in London. The clip comes from Yes, Prime Minister and highlights the economic logic behind cigarette taxes, healthcare costs, and unintended consequences. It’s a great illustration of the tradeoffs policymakers face, especially when dealing with goods that generate externalities.

With award season underway and the Oscars approaching, Matt took the opportunity to revisit La La Land. A decade after its release, the film still holds up for its music and storytelling, and it turns out to be surprisingly useful for economics examples as well, including ideas like search costs.

Doug recommended Ninth House, an adult dark fantasy novel set at Yale and centered on the university’s secret societies. The book blends dark magic, murder, and elite privilege, and it’s written by an author with deep familiarity with Yale’s campus and lore. It makes the setting feel especially vivid for those with New Haven connections.

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This episode looks at a JPMorgan survey of billionaires and what it reveals about how the ultra-wealthy think. We talk about their biggest fears, especially the fear of losing wealth, even when they have more money than they could ever spend. The conversation connects those fears to ideas from behavioral economics like loss aversion and risk tolerance. Along the way, we ask whether having more money actually makes people more cautious rather than more daring.

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In this episode, we talk about:

• How many billionaires exist, and what their combined wealth adds up to

• What a JPMorgan focus group reveals about billionaire fears and priorities

• Loss aversion and why losing money feels worse than gaining the same amount

• Whether extreme wealth makes people more risk-averse in investing decisions

• The habits billionaires credit most for their success, and what actually matters

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Show notes & references

The semester is back underway, so we start with a quick check-in after the first week of classes and all the energy associated with students back on campus. Jadrian is recording from his campus office with a Coke Zero in hand, while Matt is sipping a classic Moscow mule.

This episode’s data point analysis begins with the cost of a 30-second Super Bowl commercial this year: a staggering $8 million. For context, the average ad spot first crossed the $1 million mark back in 1994. We also briefly talk about how Netflix pulled in $1.5 billion in advertising revenue last year before landing on the number that drives the main conversation: there are currently 3,028 billionaires worldwide with a combined net worth of about $16.1 trillion.

Have you ever wondered what billionaires think about the economy, the future, or life more broadly? Wonder no longer. JPMorgan Bank surveyed billionaires on exactly these questions, drawing insights from 111 billionaire principals across 28 countries and more than 15 industries. () helpfully summarized the findings on his Substack. One result stood out in particular: some of these billionaires (especially those who inherited their wealth) say they’re genuinely afraid of losing it all.

That fear opens the door to a broader behavioral economics discussion. How does loss aversion work when “1%” translates into tens of millions of dollars? Is there a meaningful difference between thinking about losses in percentage terms versus absolute dollars? And if someone suddenly became a billionaire, would they take more risks or actually become more cautious? It’s a useful reminder that risk tolerance can change with both income and life experience.

We wrap up the episode by walking through the list of “success habits” identified in the billionaire survey: reading, exercise, consistency, waking up early, prioritizing tasks, goal setting, and deep thinking time. The big takeaway is that consistency may be the hidden engine behind all the rest. None of these habits matters much if they’re tried once and quickly abandoned.

If you had to pick one habit from the list that’s helped you the most, which would it be? We’d love to hear in the comments.

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Pop Culture Corner 🍿

Matt shares a clip from Hard Knocks where NFL player Carl Nassib passionately tries to teach his teammates about the glory of compound interest. Matt also quickly recommended The Simple Path to Wealth as a straightforward, low-stress introduction to personal finance and investing.

Jadrian shares a scene from Brooklyn Nine-Nine in which Gina returns from maternity leave and jokes about juggling work and a newborn. Her punchline: juggling must be easy because if it were hard, there would be rich jugglers.

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Ticket prices are in the spotlight as the NCAA football championship and the upcoming World Cup push demand to extremes. We dig into why resale markets exist, why prices can explode, and why face value often has little to do with what fans actually pay. Using real examples from college football, the World Cup, and concerts, we talk through supply, demand, and who really benefits from ticket resale. Along the way, we wrestle with whether there’s a “better” system or if frustration is just part of the market.

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In this episode, we talk about:

• Why national championship tickets can cost $3,000 before teams are even announced

• How World Cup ticketing systems create confusion, scarcity, and frustration

• The role of resale platforms like Ticketmaster and StubHub in shaping prices

• Why events often underprice tickets initially and let secondary markets take over

• Whether there’s a better way to price tickets without banning resale or rewarding bots

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Show notes & references

Jadrian checked in from Pittsburgh, where a hotel stay unexpectedly came with complimentary nightly drinks. He enjoyed The Oaklander, a hazy IPA brewed by Two Frays Brewery. Matt stuck with a Bud Zero as part of “healthy January,” and shared some updates on cutting snacks, eating better lunches, and trying to keep habits sustainable during the semester.

This week’s data point analysis featured a look at how large language models like ChatGPT have changed the way programmers use Stack Overflow. The number of questions posted on the site has collapsed from hundreds of thousands per month to just a few thousand last month. Matt’s contribution helped form the basis of this week’s post by offering up a headline claiming that the 2026 World Cup would generate $47 billion in economic impact. We’re skeptical.

With several major sporting events approaching, ticket prices have become a natural case study in supply and demand. The upcoming NCAA football championship tickets are pushing past $3,000 on verified resale sites, even though we don’t know which teams will be in the game. Tickets for the semifinal games can still be found for under $200. Same sport, same stakes, wildly different prices.

Even with really high prices, sometimes the sellers require buyers to jump through several hoops to secure tickets. Matt shared a firsthand account of navigating FIFA’s multi-step ticketing process. Buying the “right to buy” tickets, long before matchups are known, highlights how firms profit from scarcity. While the experience may be memorable, the system itself feels opaque and, at times, deliberately confusing.

So, why don’t leagues and artists just charge the market-clearing price up front? Drawing on research by Eric Budish, we explore explanations ranging from public relations concerns to atmosphere effects. Teams may want “true fans” in the seats, not just the highest bidders. There’s also the uncomfortable possibility that venues and platforms benefit from resale fees changing hands multiple times.

The episode wraps with a broader question: is there a fix? Verified fan systems, limits on resale, airline-style non-transferable tickets, and even UK-style resale bans all come with tradeoffs. In the end, the market mostly works, but not without frustration, high fees, and the lingering sense that the wrong people are capturing too much of the value.

What’s the worst ticket-buying experience you’ve had, and why?

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Pop Culture Corner

Jadrian went with a classic episode from The Simpsons centered on ticket scalping. Homer waits in line for several days to buy tickets, but gets shut out by a buyer who grabs all remaining tickets. He’s left to purchase much higher-priced resale tickets later.

Matt highlights a student-led project analyzing game theory in Bridgerton. The video breaks down strategic decision-making in how Daphne and Simon’s relationship can be modeled with multiple possible Nash equilibria.

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Economics Happy Hour is a podcast where two economics educators talk through current events, teaching, and research the same way we would at a bar after work. It’s informal, unscripted, and grounded in how economists actually think.

Episodes are about 45 minutes, with roughly 30 minutes focused on a single topic. Some episodes are just the two of us; others include guests. We record ahead of time, but try to release with intention around what’s happening in the world.

Not sure where to start? Try one of these:

• The Economics of Beer (with Trey Malone)
  A look at how beer reflects supply chains, regulation, local identity, and what “buying local” really means.

• Which Economists Should You Follow?
  A discussion of economists doing interesting, accessible work across podcasts, social media, and traditional academic spaces.

• The Economics of Abolishing the Penny
  Weighing the costs and benefits of eliminating the penny, including rounding, consumer behavior, and lessons from other countries.

• Is “Big Econ” Problematic?
  A conversation about concentration and power in elite economics departments, publishing, and prize distribution.

New episodes are (usually) released every other Thursday afternoon. You can listen directly on Substack or in your podcast app of choice.

If you ever have a question, topic idea, or something you think we should talk through, reply to any post or email. We read them.

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In this episode, we discuss:

• What prediction markets say about the probability of a recession, and why those forecasts matter.

• How our goals from 2025 held up and what changes are coming in 2026

• What academic publishing really looks like (and why it’s so frustrating)

• Reflections on teaching wins and evolving classroom strategies

• Making professional trade-offs between teaching and research

• And a whole lot more!

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Some show notes:

Season 4 kicks off with a reflection on 2025, both personally and professionally. Jadrian is celebrating the New Year with a Shiner Premium lager while Matt is getting an early start on Dry January with a Diet Coke. We’ll revisit our goals from the previous year throughout the episode, but let’s state upfront that we didn’t move the needle much on weight loss. Perhaps we’ll enter 2026 with renewed motivation and a more intentional focus on fitness, finances, and structure.

We kicked off our data point analysis with a look at how prediction markets are showing a 27% chance of a U.S. recession before 2027 and how that number has changed throughout the year. Unlike surveys, prediction markets are different because they impose real costs for being wrong. From there, we turn to New Year’s resolutions. Americans under the age of 45 are twice as likely as older Americans to say they’ll make one, which naturally leads us into a broader reflection on goals, incentives, and realism.

Academically, Jadrian is happy with his newsletter's growth (nearing 10,000 subscribers), media interviews (including Marketplace, NPR, and the New York Times), and record-setting course evaluations. Meanwhile, Matt was on sabbatical last Spring and was able to wrap up several research projects, including a policy-relevant experimental economics study and a Broadway-focused data paper.

We close the episode by looking forward. For Jadrian, that means being open to new opportunities with teaching and writing. For Matt, it means focusing on the things only a dean can do, especially expanding international internship opportunities for students and continuing to think carefully about teaching and learning in an AI-heavy environment.

As with most economic decisions, the theme of the episode is familiar: maximize what matters, subject to limited time, imperfect information, and a lot of uncertainty.

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This week’s pop culture references:

One of the best parts of teaching is when students start spotting economics outside of the classroom. Jadrian often brings pop culture into his classroom, but it had been a few semesters since a student brought something back to him. That changed this past semester when a student told him she was binge-watching Psych and caught a reference to game theory.

Matt taught game theory for the first time in a while and assigned a project where students applied the concepts to something they’re passionate about. With permission, he’s turned a few of those projects into presentations for a broader audience. In this episode, he shared one where a student analyzed the popular game Clash Royale and explained how mixed strategies can help in high-pressure scenarios.

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In this episode, we discuss:

• The surprising stat that 1 in 5 Americans have jobs that didn’t exist in 2000

• What kinds of new jobs have emerged in the past 25 years

• The decline of older job types and industries, like video rental

• How institutions and firms adapt to new tech by creating new roles

• Teaching strategies to help students understand labor market changes

• And a whole lot more!

Catch up on some old episodes:

You can also subscribe to us on Spotify, TuneIn Radio, Amazon Music, and Apple Podcasts. If one of these is your go-to podcast service, be sure to rate us and subscribe!

Some show notes:

We’re sitting down in the middle of December, which means our classes are nearly over. By the time you’re reading this, grades have been posted, and we likely have auto replies on our emails. Jadrian celebrates the end of the term with a Shiner Bock (Texas pride intact), while Matt braved a Mad Elf, with a water on standby.

Our mystery stat game included estimates of holiday spending across the U.S. and Canada, and the motivation for today’s conversation: roughly 20% of Americans now work in jobs that didn’t exist 25 years ago. That stat, based on LinkedIn data cited by The Wall Street Journal, set the stage for our discussion on how the economy has evolved over the past 25 years.

It’s easy to spot the jobs that have emerged in recent years: prompt engineers, social media managers, app developers. Even long-standing institutions like universities now rely on roles in IT, marketing, and cybersecurity that simply didn’t exist 25 years ago. And beyond traditional workplaces, the gig economy has exploded, with Uber drivers, Instacart shoppers, and Grubhub couriers becoming a visible part of daily life.

But there’s a flip side: jobs that fade away. One of the clearest examples is video rental, where employment dropped from over 120,000 in 2000 to fewer than 13,000 by 2017. It’s a reminder that as technology and habits shift, entire industries can disappear.

Students often struggle with this dual reality. New tech can destroy some jobs while creating others we couldn’t have predicted. The fear that automation will leave everyone unemployed reflects a common economic mistake: the lump-of-labor fallacy, or the idea that there’s a fixed number of jobs to go around.

Labor market change can feel uncertain, even threatening. If 20% of today’s jobs didn’t exist a generation ago, what does that mean for the value of a college degree? For us, it reinforces the point: teaching students how to think, adapt, and collaborate may be the most reliable form of job security. Majors and tools will change, but curiosity, communication, and decision-making won’t be outdated anytime soon.

Cheers, and happy holidays!

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This week’s pop culture references:

Jadrian brought a fun throwback clip from a 1994 episode of The Today Show, where the hosts puzzle over what the internet is and how email addresses work. It’s a great reminder of just how recent (and confusing) the digital age once felt.

Matt shared a scene from Sunset Boulevard’s “With One Look,” where a former silent film star (Norma Desmond) reflects on losing her place in Hollywood. It’s a striking example of creative destruction. New technology (talking pictures) can erase entire careers, even for once-iconic stars.

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