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Economics Happy Hour Podcast

Economics Happy Hour Podcast

著者： Matt & Jadrian
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 A podcast & newsletter about two economists who love talking about all things economics.

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  • Controversy at the BLS

    Controversy at the BLS
    2025/08/07
    We dive into the sudden firing of the Bureau of Labor Statistics Commissioner following large downward revisions to the most recent jobs data. Everything is still pretty new, but we get a chance to talk about the scale of the revisions, the normalcy of such adjustments, and the potential implications of politicizing economic data. It's a first reaction to a surprising move with potentially big economic and institutional stakes.In this episode, we discuss:* The scale and context of recent BLS jobs data revisions* Why revisions are a normal and expected part of labor statistics* Concerns raised by firing a data-focused civil servant over routine changes* The institutional risks of undermining trust in economic data* How policymakers and markets rely on accurate, stable data reporting* And a whole lot more!Catch up on some old episodes:You can also listen to us on Google Podcasts, TuneIn Radio, and Apple Podcasts. If one of these is your go-to podcast service, be sure to rate us and subscribe! Watch this episode on YouTube:Some show notes:Our friend Brian O’Roark made the mistake of texting us about the unexpected firing following the jobs report, which meant he got invited to chat with us. Brian kicked things off with a watermelon vodka cocktail called Brave New Swirl, inspired by the Tequila Mockingbird book. Jadrian opted for a non-alcoholic Electro Lime Circa de Cerveza, and Matt cracked open a Lift Off IPA from Daredevil Brewing Co., a gift from superfan Tim Dye.If you’ve missed the news over the past week, the BLS released its July jobs report on Friday, which included a downward revision of more than 250,000 jobs for May and June. It was one of the largest revisions outside of COVID since 1979. Hours later, President Trump dismissed the BLS Commissioner.We took some time to talk about why revisions happen in the first place. The BLS relies on surveys from over 600,000 workplaces, many of which respond late or not at all. As more data comes in, earlier estimates are adjusted, making revisions common and expected. Our surprise wasn’t based on the revision itself, but the political response. Firing someone over a data adjustment has struck many economists as dangerous, as it undermines the statistical integrity of key economic institutions.There is a lot of institutional expertise at agencies like the BLS. Even though the Commissioner was removed, much of the technical staff remains. This will likely limit the immediate risks to data quality. But the move raises concerns about future interference. Would staff feel pressure to avoid “bad news”? Could upcoming data releases be skewed or politicized?Of course, there are some historical parallels to be drawn, mainly from Eastern Europe and China, where statisticians faced pressure to produce politically favorable numbers. While the U.S. isn’t there, it’s worth noting that credibility and trust are slow to build and easy to lose. The firing also reignited longer-standing debates about how we define and report key economic indicators. Measures like unemployment and inflation rely on intentionally rigid definitions so that economists can make comparisons over time. For instance, inflation calculations don’t just track the price of a product; they adjust for changes in size, ingredients, and quality to make fair comparisons across decades. Even when updates to these definitions are made transparently, they often spark confusion or accusations of manipulation. A recent example came during the pandemic when the Fed revised the definitions of M1 and M2 to reflect modern banking habits. Although nothing new was being “printed,” the change caused spikes in the data that fueled misinterpretation online. Our friend Dr. Abdullah Al Bahrani wrote about it for his newsletter when it was happening:All of this also raises big questions about where policy goes from here. The Fed has been under pressure to cut interest rates, and weak labor market data would support that move. But if Trump is dismissing the jobs numbers as wrong while insisting the economy is booming, then the rationale for rate cuts disappears. Brian noted that Trump seems to want both a roaring economy and low interest rates, an inflationary combination if taken too far. And if last week’s events set a precedent, should the BEA Commissioner be worried if GDP slows after recent tariff moves? Let us know if there’s another angle we should have considered. Are we onto something, or way off base?This week’s pop culture references:Brian shared a scene from National Lampoon’s Christmas Vacation where Clark is shocked to learn that Cousin Eddie hasn’t bought any presents. The conversation turns to Eddie’s long-term unemployment. We learn that it isn’t because jobs are unavailable, but because he’s holding out for a management role. Brian likes to use the clip to illustrate frictional unemployment in action.Jadrian brought up one of his favorite classroom examples: ...
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    40 分
  • Economics of Rewards Programs

    Economics of Rewards Programs
    2025/07/24
    This week, we dive into the economics behind rewards programs and credit card perks. We explore how loyalty schemes influence consumer behavior and how companies use them strategically. The episode covers travel points, airline upgrades, hotel loyalty tiers, and their broader economic implications. We also consider who really foots the bill for all those “free” perks.In this episode, we discuss:* Why companies offer points, perks, and loyalty rewards, and how they profit from it* The trade-offs consumers make to stay loyal to specific brands or services* How status tiers shape travel habits* The hidden costs of rewards programs and who ends up paying for them* Whether reward cards truly benefit most people, or just the most organized few* And a whole lot more!Catch up on some old episodes:You can also listen to us on Google Podcasts, TuneIn Radio, and Apple Podcasts. If one of these is your go-to podcast service, be sure to rate us and subscribe! Watch this episode on YouTube:Some show notes:Jadrian is close to cleaning out his beer shelf, but the remnants aren’t lining up with the season. A shelf full of porters is a lot harder to drink in the middle of a hot summer. Jadrian had a Pay It Forward Cocoa Porter from West Sixth Brewing (Lexington, KY), a leftover from a past JET SET. Matt is recovering from a migraine and opted for something close to water: a Bud Zero. This week’s conversation came courtesy of a Bloomberg story about a CEO who used 1.83 million Amex points to pay off an unexpected $11,000 tariff bill. We aren’t talking about tariffs, but rather a wider conversation about the purpose and strategy behind credit card rewards and loyalty programs. We each share our own experiences, whether that involves the way we track multiple reward accounts in a spreadsheet or weighing the value of lounge access, upgrades, and travel perks. Both of us are loyal card-carrying members of popular loyalty programs offered by Delta Airlines and Marriott hotels, which means we must have some good reasons for paying the annual fee.But do the perks (like companion passes, free nights, or waived baggage fees) outweigh the cost? We seem to think so, but then it left us wondering who is really paying for all these benefits we cash in on?In a classic case of “nothing is free,” it’s important to remember that businesses pass along credit card fees in the form of higher prices for everyone, often including those who pay in cash. That creates a subtle redistribution of resources where people who optimize rewards programs are subsidized by those who don’t. It’s worth noting that companies are also incredibly profitable with their rewards programs. For example, Delta received billions from Amex for its co-branded cards last year.One big takeaway: airline and hotel rewards cards might make sense for frequent travelers, but that’s a small slice of the population. After a long stretch focusing on airline perks, we stopped to consider how often people even fly. According to Gallup, only about 15–20% of Americans take more than three flights per year. Most Americans don’t ever fly during the year.We wrap up our conversation discussing how rewards programs have evolved. In recent years, companies like Delta and Carnival Cruises have shifted their loyalty structures to reward spending on co-branded credit cards rather than prioritizing brand loyalty alone. It’s a subtle but important shift, one that favors high-spending customers and raises the bar for earning perks through behavior like repeat flying or cruising. These programs have become so gamified that they often blur the line between savvy planning and status chasing. For some, that chase is part of the appeal. Take JetBlue’s recent 25th anniversary promotion: fly to 25 different cities before the end of the year, and you’ll earn Mosaic status for the next 25 years. It’s a clever marketing strategy, but also a reminder of how far people are willing to go when there’s a shiny perk on the line.This week’s pop culture references:Matt talked about the 2009 movie Up in the Air, where George Clooney's character obsessively pursues airline miles and elite travel status. In one scene with Anna Kendrick, they discuss the perks of frequent travel and how to maximize them. Jadrian took a different angle, highlighting a more common loyalty program. In this Seinfeld episode, Elaine is determined to complete her punch card to earn a free sub even though she doesn’t like the subs she’s eating. When she loses the card, she’s crushed. Jerry offers a valuable economics lesson, reminding her about sunk costs. Those bad subs are already gone, so is the “free” one really worth it? This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit econhappyhour.substack.com
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    48 分
  • Economics and Sports Betting

    Economics and Sports Betting
    2025/07/13
    Dive into the economic concepts that have helped with the recent explosion of sports betting in the United States. Explore how sportsbooks set odds, the role of information in creating an edge, and why betting markets share some similarities with prediction markets. We briefly unpack the effects of the 2018 repeal of PASPA and discuss how technology has transformed gambling behavior. This week’s conversation highlights both the fun and complexity of modern sports betting.In this episode, we discuss:* How sports betting odds are set and why sportsbooks aim to balance bets.* Why some bettors can gain an edge and how information affects outcomes.* The economics behind parlays, money lines, and house margins.* How the 2018 Supreme Court ruling changed the legal landscape.* And a whole lot more!Catch up on some old episodes:You can also listen to us on Google Podcasts, TuneIn Radio, and Apple Podcasts. If one of these is your go-to podcast service, be sure to rate us and subscribe! Watch this episode on YouTube:Some show notes:We recorded this week’s episode right before Game 7 of the NBA Finals and right after recording our episode on Bobby Bonilla Day. We decided to stick with the sports theme, but our drinks have changed. Eric opted for a glass of water to combat the heatwave sweeping across most of the U.S. at the time, while Jadrian went with Best Day Brewing’s Sea Salt and Lime non-alcoholic cerveza. Matt snagged a Gorb Hazy IPA from Oliphant Brewing on his recent trip to Minnesota.Over the past few years, the amount of ad space dedicated to gambling sites has increased dramatically. That’s due in part to the repeal of PASPA in 2018, which made it easier for states to legalize sports gambling. We brought on our friend Eric Dunaway from Wabash College to help provide some insight into how the sports gambling industry ballooned from underground operations and Nevada-only betting to nationwide, app-based access that includes bets as small as a dollar. Sports gambling is different from traditional gambling in a variety of ways, but perhaps the most interesting to economists is that the outcome of the game is not based on probabilities like traditional casino games. Because of how often blackjack hands are played or roulette wheels are spun, it’s a lot easier to estimate the expected win probability for any given bet. That’s not possible with sports games because we only ever see one observation. As a result, sportsbooks are more interested in “setting lines” rather than trying to predict the outcome of a game. Eavesdrop on some sports gamblers, and there’s no doubt you’ll hear them reference a money line: the initial distinction between favorites and underdogs. Even one of the simplest bets is structured in a way that ensures a profit for the casinos by baking in a “vig” regardless of the outcome. While house edges are fixed in games like roulette, sports betting allows for subjective analysis and the potential for informed bettors to gain an edge.The second half of this week’s episode focused on the behavioral economics aspects of sports gambling, including how fans may bet emotionally on their teams and the ways sportsbooks use boosts and promotions to attract money. Sportsbooks rely on more than just math; they also leverage psychology. Many apps use flashy celebration graphics and real-time win tracking to create a sense of excitement, while quietly downplaying losses. These design choices can make betting feel more like a game than a financial risk. Perhaps more concerning, sportsbooks are now partnering with some universities to present gambling as a way to support college athletics. While framed as sponsorship, we’re not entirely sure it’s appropriate to normalize betting among young adults with blurred lines between supporting your school and engaging in risky financial behavior. Perhaps the one plus side of the rapid growth in sports gambling is that we have a lot of young people passionate about statistics. Let’s hope that passion extends to more responsible financial decisions.This week’s pop culture references:In Back to the Future Part II, the antagonist steals the Time Machine and delivers a sports almanac to his younger self in 1955. With decades of future game outcomes in hand, he builds a gambling empire by always betting with perfect information. The scene ties directly into this episode’s theme: if you know more than the market, even slightly, you can win big.In Casino, Robert De Niro plays a handicapper who works for the mob, helping them set accurate betting lines on sports events before eventually taking over a casino. His role shows how valuable expert analysis and insider knowledge can be when money is on the line. Matt highlights Nate Silver’s new book, On the Edge, where Silver reflects on his own attempt to become a professional NBA gambler. Despite his strong background in statistics and data, he admits he struggled to profit consistently. ...
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    46 分
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