Nate Silver's forecasting model gives Democrats a better than 70% chance of capturing the Senate and an over 90% chance to flip the House, propelled by an estimated 11-point national midterm swing against the incumbent Republican administration. (3:18)
Democrats are polling competitively across deep-red territory Trump won by double digits in 2024—including Texas, Ohio, Kansas, and Alaska—bolstered by moderate candidate recruitment and economic pain points like diesel fuel prices in the Midwest. (9:52)
Unlike presidential elections where polls repeatedly underestimated Donald Trump, midterms in the Trump era (2018 and 2022) were historically accurate, while off-year gubernatorial races significantly undercounted Democratic support. (19:28)
Trump's approval rating has reached historic lows following military confrontation with Iran, gas prices climbing past $4.50, and persistent tariff and market volatility, leaving down-ballot Republicans highly exposed without Trump on the ballot. (41:19)
Detailed notes
## Background
Published on YouTube by The Ezra Klein Show on October 27, 2026, this episode features election forecaster Nate Silver one week before the 2026 midterm elections. The show notes outline Silver's assessment that an anticipated Democratic wave could flip both the House and Senate, potentially signaling the end of the Trump era while scrutinizing the reliability of modern polling and emerging narrative trends in the data.
## TL;DR
Nate Silver joins Ezra Klein to break down model projections giving Democrats an unexpectedly strong path to winning both the House and Senate, fueled by an estimated 11-point national midterm swing against the second Trump administration. They examine whether polling can be trusted after past presidential misses, contrasting durable midterm polling accuracy with the mechanics of likely-voter modeling and candidate quality in red bastions like Texas, Ohio, and Kansas. The conversation broadens into macroeconomic and structural vulnerabilities dragging down Republicans—including war with Iran, surging fuel prices, and backlash to AI data centers—alongside the rise of an 'elder millennial' bench of Democratic talent. Finally, they weigh the systemic tail risks of an aging Donald Trump governing as an isolated lame duck facing potential economic, technological, and geopolitical shocks.
## Atmosphere & style
The discussion carries an analytical, engrossed, and quietly foreboding atmosphere, pairing Klein’s narrative inquiries with Silver’s coolly probabilistic, poker-informed skepticism. Rather than partisan cheerleading, the exchange feels like an exhaustive diagnostic post-mortem conducted in advance, marked by deep-in-the-weeds polling methodology and candid assessments of candidate flaws. An underlying sense of sobriety emerges toward the end as both men look past horse-race math to contemplate the fragile, volatile reality of a fractured lame-duck presidency navigating cascading global crises.
## Bulletin
- [03:18](https://www.youtube.com/watch?v=uDqR4t5N84o&t=198s) Nate Silver's forecasting model gives Democrats a better than 70% chance of capturing the Senate and an over 90% chance to flip the House, propelled by an estimated 11-point national midterm swing against the incumbent Republican administration.
- [09:52](https://www.youtube.com/watch?v=uDqR4t5N84o&t=592s) Democrats are polling competitively across deep-red territory Trump won by double digits in 2024—including Texas, Ohio, Kansas, and Alaska—bolstered by moderate candidate recruitment and economic pain points like diesel fuel prices in the Midwest.
- [19:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1168s) Unlike presidential elections where polls repeatedly underestimated Donald Trump, midterms in the Trump era (2018 and 2022) were historically accurate, while off-year gubernatorial races significantly undercounted Democratic support.
- [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) Trump's approval rating has reached historic lows following military confrontation with Iran, gas prices climbing past $4.50, and persistent tariff and market volatility, leaving down-ballot Republicans highly exposed without Trump on the ballot.
## Key takeaways
- [03:18](https://www.youtube.com/watch?v=uDqR4t5N84o&t=198s) A standard midterm backlash against the president's party is currently running at an 11-point national swing, instantly converting states Trump won by double digits into active toss-ups.
- [06:43](https://www.youtube.com/watch?v=uDqR4t5N84o&t=403s) Maine and Michigan represent essential defensive firewalls; losing both states would effectively extinguish Democratic hopes of flipping the Senate majority.
- [09:52](https://www.youtube.com/watch?v=uDqR4t5N84o&t=592s) Midwestern and heartland polling strength for Democrats is driven by high diesel and heating fuel costs, recent working-class and young male coalition defectors dropping out, and local reactions near newly built AI data centers.
- [11:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=688s) Voter fatigue with progressive governance has weakened Democratic margins in deep-blue trifecta states like Oregon and Minnesota, whereas disciplined moderates are excelling in red states.
- [17:56](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1076s) Because polling errors are correlated across states, a uniform 3-to-4-point pro-Republican error would erase narrow Democratic leads in tight races like Texas and Ohio.
- [19:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1168s) Trump-era midterm polling has proven remarkably accurate compared to presidential cycles, contradicting the popular assumption that polls inherently understate Republican strength in every election.
- [22:20](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1340s) Modern polling operates as predictive modeling; self-reported voter enthusiasm yields heavily Democratic samples, while algorithmic past-turnout screens produce significantly tighter margins.
- [31:33](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1893s) An 'elder millennial' cohort of media-fluent Democratic politicians forged in the Obama and first Trump eras is breaking through across both moderate and left-wing factions after years of generational backlog.
- [34:30](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2070s) Aggressive gerrymandering and geographic sorting have severely compressed the competitive House landscape, holding projected Democratic net gains to around 22 seats despite a large national wave.
- [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) Trump's personalized political approach damages down-ballot Republicans, as his disengaged, low-propensity base routinely fails to turn out when Trump is not personally on the ballot.
- [44:34](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2674s) The White House's embrace of energy-intensive AI data centers aligns with major tech donors like Elon Musk, but conflicts with broader public sentiment favoring a slowdown in AI development.
- [47:12](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2832s) A second-term lame-duck Trump facing an economic downturn or escalating foreign conflicts poses extreme systemic risk due to age, erratic decision-making, and an absence of experienced establishment advisors.
- [51:48](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3108s) Campaign fundraising hits steep diminishing returns in saturated top-of-the-ticket races, but late money remains highly influential down-ballot in low-information state legislative and obscure House contests.
## Detailed walkthrough
### [00:00](https://www.youtube.com/watch?v=uDqR4t5N84o&t=0s) The Looming 2026 Midterm Shock
Ezra Klein opens by noting that just one week remains before the midterm elections, and an outcome that appeared almost unthinkable twelve months prior has materialized: Democrats hold a clear path to winning not only the House of Representatives, but also the Senate. To secure that upper-chamber majority, Democrats must hold all of their existing competitive seats while flipping at least four Republican-held states. A couple of targets had appeared plausible from the outset, but Democratic candidates are now running competitively—and in some instances leading comfortably—in deep-red states that Donald Trump carried by double digits in 2024, including Kansas, Texas, Ohio, and Alaska. With Democrats burnt by polling misfires in previous cycles, Klein asks whether voters and analysts can actually trust the current data.
Klein introduces Nate Silver, editor of *The Silver Bulletin* on Substack, co-host of the podcast *Still Counting*, and author of *On the Edge: The Art of Risking Everything*. In a preview snippet, Silver notes that Trump’s approval rating has sunk below its post-January 6 nadir, describing it as being as low as it has ever been. Klein then observes that Silver had an uncharacteristically distant look in his eye before going on air, remarking that the upcoming election feels "momentous." Silver explains the stakes plainly: “If the election goes roughly as the polls say it will go, then in some ways it would mark the end of the Trump era, I think.” While Trump would remain president for two more years, Silver argues that the moment votes are tallied—even if counting stretches out in states like Alaska and California—the 2028 presidential campaign begins instantly, rendering Trump an ultra-lame duck reminiscent of George W. Bush after the 2006 midterms.
Beyond generational turnover and Trump nearing the final quarter of his constitutional limit, Silver highlights shifting structural currents. He suggests that artificial intelligence is playing an underappreciated role in this cycle and could emerge alongside the economy as one of the defining issues of 2028.
[03:18](https://www.youtube.com/watch?v=uDqR4t5N84o&t=198s) The Anatomy of an 11-Point Midterm Swing
Klein recalls that a year earlier, conventional political wisdom dictated that Democrats would likely take the House, but reclaiming the Senate was viewed as near-impossible. Doing so required winning in states Trump carried by more than ten percentage points—a feat modern partisan sorting seemed to rule out. Yet with roughly two weeks until Election Day at the time of recording, Silver’s forecasting model gives Democrats a better than 70 percent chance of capturing the Senate majority.
```mermaid
flowchart TD
accTitle: Senate Swing Math
accDescr: Flowchart illustrating how a generic midterm wave shifts a deep-red state into a competitive tossup.
Silver explains that the post-2024 narrative regarding a permanent conservative realignment was overstated: “And but if you look at the history of American elections, then the most regular trend in American elections, one of the few things that survives for decades is there is a backlash against the president's party at the midterm.” While an average midterm sees an environment shift of roughly 7.5 points against the incumbent party, the current environment exhibits an 11-point swing. Because Trump won states like Ohio by roughly 11 points in 2024, a uniform national wave instantly converts former red bastions into tossups.
- In historical midterms, the only notable exceptions to the midterm penalty against the president's party are 1998 (following the Lewinsky scandal) and 2002 (post-September 11), with Joe Biden suffering a relatively muted blow in 2022.
- Intangible candidate quality differences typically shift race outcomes by at most 4 to 5 points.
- In Texas, an 11-point national swing pulls Trump's 13-point margin down to R+2; James Talarico's challenge against an ethically vulnerable Ken Paxton provides the remaining differential to create a D+2 margin.
- Democrats have also benefited from disciplined recruitments, such as former governor Roy Cooper in North Carolina and running independent-in-name-only candidates in places like Nebraska.
[06:43](https://www.youtube.com/watch?v=uDqR4t5N84o&t=403s) Candidate Quality, Recruitment Battles, and State-Level Risks
Klein points to the Democratic Senatorial Campaign Committee (DSCC)—led by Kirsten Gillibrand—which faced sharp criticism months earlier after a botched recruitment effort in Maine. National party leaders fought to install Governor Janet Mills as the nominee, but were rebuffed; activist Graham Platner subsequently stepped forward and imploded, leaving Troy Jackson as the nominee against incumbent Susan Collins. While Jackson leads in the polling, observers remain anxious because Collins famously outran her polling by roughly nine points in 2020. In Alaska, however, Representative Mary Peltola is outperforming expectations and running as a slight favorite.
Silver warns that if Democrats drop both Maine and Michigan, their prospects for taking the Senate majority evaporate: “Michigan and Maine, if Democrats were to lose one of them they'd still have a chance. If they were to lose both then probably game over for a Democratic Senate flip.” Analyzing Michigan's Senate contest, Silver distinguishes between the statewide performances: while Democratic gubernatorial nominee Jocelyn Benson leads by eight points, Senate candidate Abdul El-Sayed holds a narrower edge of about 3 to 3.5 points. Silver notes this matches the predicted four-point gap between progressives and moderates in purple states, though he remarks that El-Sayed's blue-collar "bro" persona, fundraising prowess, and distinct style help keep him ahead despite that ideological drag.
Klein closes the segment by querying a curious trend in the numbers: Democrats appear to be dramatically overperforming in deep-red states like Texas, Kansas, and Iowa, while posting more modest numbers in standard battlegrounds and blue states such as Michigan and Minnesota. Silver acknowledges the phenomenon, observing that this geographic distribution is precisely what leaves Democrats uneasy, as rural and heartland states have historically yielded the largest polling misses.
[09:52](https://www.youtube.com/watch?v=uDqR4t5N84o&t=592s) Explaining the Midterm Map: Fuel Prices, Reversion, and Data Centers
Nate Silver points out that Democratic polling overperformance has clustered in specific regions, and several concrete factors explain why. First, economics: diesel fuel is consumed not primarily by passenger cars, but by trucking, agriculture, petroleum operations, and home heating oil—industries heavily concentrated in the colder Midwestern battleground states. Second, Silver raises a "last in, first out" coalition thesis. In 2024, the electorate showed signs of mild depolarization; Democrats experienced some of their worst relative drop-offs in deep-blue states like California and New York, largely driven by younger men and younger voters of color shifting rightward. Conversely, the partisan voting index gap tightened slightly in places like Kansas. If recent entrants to the Trump coalition—such as working-class white voters and Hispanic voters—are drifting back toward the middle or simply staying home, it disproportionately harms Republicans. As Silver notes, “The one group you do not want to rely on to turn out in a midterm is usually young men.”
```mermaid
flowchart TD
accTitle: Drivers of Midwestern Shift
accDescr: Three structural factors driving polling shifts toward Democrats in heartland battlegrounds.
subgraph Drivers["Heartland & Western Shifts"]
A["High Diesel & Heating Fuel Costs<br/>(Agriculture, trucking, home heat)"]
B["'Last In, First Out' Reversion<br/>(Young men & working-class voters drop out)"]
C["Proximity to Data Centers<br/>(Exurban tech infrastructure growth)"]
end
Drivers --> D["Midwestern & Western Polling Overperformance"]
```
A third, less obvious structural driver comes from reporting in *The Economist*: data indicates that the closer Trump voters live to newly built data centers, the more likely they are to flip Democratic. Because tech companies place these massive facilities across the American West and Midwest—seeking ample space without being completely disconnected from the grid—this geographic infrastructure footprint may be exerting a quiet suburbanizing pull on local electorates.
[11:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=688s) Candidate Quality vs. Democratic Governance Fatigue
Ezra Klein proposes an alternative candidate-quality explanation: Democrats have deliberately calibrated their candidates based on state geography. In redder territory, the party ran moderate, populist, or fiercely independent-seeming figures who match the local electorate:
- **Kansas:** Adam Hamilton running as an independent-minded moderate
- **Ohio:** Sherrod Brown, a longtime, deeply rooted economic populist
- **North Carolina:** Roy Cooper, an incumbent governor with broad brand appeal
- **Georgia:** Jon Ossoff, a relentlessly disciplined campaigner
- **Nebraska:** Dan Osborn, an independent candidate whom Democrats backed by declining to field a nominee against him
By contrast, Klein observes that in bluer and traditionally purple states where Democrats felt more comfortable taking ideological risks, they nominated candidates further to the left, often leading to underperformance. In Maine, Graham Platner was replaced by an even more left-leaning candidate; Abdul El-Sayed won in Michigan; and in Minnesota, the leftist nominee is running tighter than past Democrats. In Florida, Democrats nominated a DSA-aligned candidate who is completely absent from national pickup conversations while trailing by six to eight points—illustrating what Silver characterizes as a failure to recognize that "you need a pretty conservative Democrat probably to win in Florida at this point."
Silver agrees, adding that in deep-blue states with Democratic trifectas, voters are expressing real fatigue with progressive governance. In Oregon, Governor Tina Kotek is leading her poll matchups by only one or two points amid sharp public backlash over state policy. In New York, Governor Kathy Hochul is on track to win by a comparatively tepid margin. Conversely, well-governed blue states with a history of pragmatic governance, like Massachusetts under former Republican Governor Charlie Baker, do not share this vulnerability.
The most dramatic casualty of this governance backlash is Minnesota. Klein points out that Jon Ossoff in Georgia and Roy Cooper in North Carolina are cruising to reelection, demonstrating that not all incumbents face blowback. However, Minnesota has turned into "ground zero" because outgoing Governor Tim Walz's approval ratings collapsed to roughly 17 points underwater, forcing him to abandon a planned reelection run. As Silver quips regarding Walz's fast trajectory, “The trajectory of losing vice presidential nominees, you know, John Edwards had a rough fall from Grace, for example.”
[15:30](https://www.youtube.com/watch?v=uDqR4t5N84o&t=930s) Attention vs. Polling: The Social Media Disconnect
Ezra Klein notes a striking disconnect between online attention and actual electoral strength. Digital-first figures like Abdul El-Sayed and James Talarico, or politicians whose viral debate clips flood social feeds like Jon Ossoff, attract enormous national attention and podcast appearances. Meanwhile, candidates who are quietly outperforming expectations in challenging terrain—such as Sherrod Brown in Ohio, Mary Peltola in Alaska, or Roy Cooper in North Carolina—run disciplined, low-profile, insular campaigns with almost no national media footprint.
Silver points out that these choices stem from differing political incentives: candidates harboring potential 2028 presidential ambitions want maximum national exposure, whereas candidates in conservative states understand that nationalizing their races is lethal. Midterms fundamentally boil down to three mechanisms:
1. Turnout among your own base
2. Turnout among the opposing base
3. Persuasion within the roughly 15% of the electorate consisting of genuine swing voters
By the final week of a campaign, the persuasion phase is essentially over. Silver predicts Democratic base turnout will be exceptionally high by historical midterm standards; the crucial unknown is whether Republican voters show up. That single turnout differential will dictate whether the GOP merely keeps Democratic House gains to roughly 10 seats while clinging to the Senate, or suffers a sweeping, 1994-style catastrophe.
[17:56](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1076s) The Nature and Direction of Polling Error
Turning to how polling error could reshape election night, Klein asks how resilient Democratic leads are to systematic bias, particularly given past cycles where Donald Trump or Susan Collins were significantly underestimated.
Silver cautions that polling misses are correlated rather than isolated events: “Look, the first thing I always tell people is that whenever you're looking at a series of polls in a Senate race or in Senate races plural, right, always ask yourself, what if they're off by three or four points in the same direction in every race?”
- **Senate Exposure:** Many Democratic leads in key battlegrounds like Ohio and Texas sit right around three points. A uniform three-point polling error in favor of Republicans would immediately wipe out those margins, turning election night into a grueling, drawn-out affair where control of the Senate might hinge on the ranked-choice tabulation in Alaska.
- **The House Firewall:** A failure to flip the House would represent a catastrophic polling failure that would raise profound questions about polling methodologies and the political landscape at large.
- **Democratic Anxiety:** Democrats carry deep psychological trauma from past cycles (such as 2016 with Hillary Clinton), leaving them convinced that whenever a polling error occurs, it inevitably cuts against their side.
[19:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1168s) Polling Accuracy in Midterms and the Ann Selzer Shock
Ezra Klein challenges the popular impression that polls systematically underestimate Donald Trump and disadvantage Democrats, asking whether that pattern holds true during midterm cycles. Nate Silver points out that polling during the midterms of the Trump era tells a very different story: 2018 was one of the most accurate polling cycles in history, and 2022 was similarly reliable. Even in high-profile races like the 2022 Pennsylvania Senate contest—where surveys showed Mehmet Oz closing the gap against John Fetterman after Fetterman suffered a stroke—Fetterman still won handily by four or five percentage points. Moreover, in recent off-year gubernatorial races in Virginia and New Jersey, polls actually underestimated Democratic performance by five to ten points, marking some of the largest errors seen in heavily polled general elections.
The persistent narrative that pollsters undersample Republicans due to differential response rates and Democratic enthusiasm is something every professional in the industry already tracks. However, the successive undercounts of Donald Trump in the 2016, 2020, and 2024 presidential elections proved to be the death knell for the historical "gold standard" of polling—the pure philosophy of surveying voters, weighting simply to census demographics, and trusting raw outputs without aggressive modeling.
```mermaid
flowchart TD
accTitle: Historical Polling Accuracy vs Midterm Reality
accDescr: Diagram contrasting presidential polling undercounts of Trump with accurate midterm cycles and off-year Democratic surges.
subgraph PresidentialCycles["Presidential Cycles (Underestimating Trump)"]
P1["2016, 2020, 2024"] --> P2["Underestimated Trump support"]
P2 --> P3["Death of raw demographic weighting"]
end
subgraph MidtermAndOffYear["Midterms & Off-Years (Robust/High Dem Performance)"]
M1["2018 & 2022 Midterms"] --> M2["High overall accuracy (e.g., Fetterman win)"]
M3["Virginia & New Jersey Off-Years"] --> M4["Polls missed low on Dems by 5-10 points"]
end
```
The breakdown of traditional raw-data polling was dramatized by the famous Ann Selzer poll in Iowa immediately prior to the 2024 presidential election. Selzer, widely regarded as the gold standard who correctly anticipated Barack Obama’s 2008 Iowa caucus victory, shocked the political world on the Saturday before the vote by releasing a poll showing Kamala Harris leading Iowa by three points, despite all other data showing Trump ahead by around nine. Silver recalls receiving a frantic text about the rumor right before a Saturday dinner; his model remained deeply skeptical of such a massive shift. The result was an off-the-mark miss by 13 to 15 points, prompting an absurd defamation lawsuit from Donald Trump against *The Des Moines Register*.
- “It has not been true in the two midterms under in the Trump era.” — Nate Silver
- In Virginia and New Jersey off-year elections, polls underestimated Democratic candidates by 5 to 10 points.
- The 2024 Ann Selzer Iowa poll missed the final outcome by roughly 13 to 15 points after projecting a three-point lead for Harris.
---
[22:20](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1340s) How Pollsters Build Likely Voter Models
Klein expresses disorientation with modern polling methodologies, observing that between demographic weighting, online panels, and non-response adjustments, polling often feels indistinguishable from forecasting. Silver agrees that the boundary has blurred, noting that every modern poll acts as a miniature predictive model built with poll-flavored inputs. He rejects the simplistic idea that polling is a broken dashboard fuel gauge with a fixed bias. Instead, he compares it to running a restaurant where the chef iteratively tweaks spice levels based on alternating customer complaints. Pollsters face immense reputational pressure in the final weeks of a campaign, creating powerful incentives to correct known blind spots, even as they publicly claim to offer mere snapshots in time.
```mermaid
flowchart LR
accTitle: Polling Methodologies and Turnout Modeling
accDescr: Flowchart illustrating the iterative adjustments pollsters make to screen likely voters and the turnout risks involved.
When unexpected wave elections occur, polling averages can still fail to capture differential turnout. Silver highlights historical precedents:
- In 1994, an ostensibly bad cycle for Bill Clinton snowballed into a catastrophic wave election.
- In 2014, Barack Obama's younger, multiracial coalition failed to turn out at midterm rates, leading to a devastating nine-seat Senate loss for Democrats.
Screening techniques heavily influence headline numbers: asking respondents directly whether they intend to vote produces heavily Democratic-leaning samples, whereas algorithmic models that predict turnout based on past voter history yield more conservative results. Interestingly, early voting figures reveal high participation among low-propensity voters—those who voted in no more than one of the past three elections—and this segment currently leans Democratic. If Republicans fail to close that turnout gap on Election Day, the polls could once again end up understating Democratic strength.
- “I think the upshot of the Ann Selzer thing is that everyone knows that a poll is kind of almost like a mini model with polling flavored inputs.” — Nate Silver
---
[26:24](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1584s) Plausible Republican Overperformance and High-Stakes Narrative Races
When Klein asks what an unexpected Republican victory would look like, Silver describes two distinct possibilities. The most realistic scenario sits comfortably within the regular distribution of polling error: Democrats simply lose every tight toss-up. In that scenario, candidates like James Talarico in Texas or Jeff Jackson fall short by a single percentage point, Abdul El-Sayed gets pushed into a recount, and Sherrod Brown wins while other Democrats drop close contests by a few points. In that world, observers would conclude that baseline partisanship remained too rigid for Democrats to scale the steep "oxygen-deprived" climb up an R+12 state.
The alternate scenario—where the House remains close and Democrats pick up only a single Senate seat like North Carolina—would represent a massive, five-to-seven-point polling error that defies standard midterm dynamics under an unpopular administration.
Beyond the raw totals, Klein points to candidates who hold symbolic narrative weight for the future of the Democratic Party:
- **James Talarico:** A test of whether Democrats can flip Texas by leaning into the rhetoric of the religious left.
- **Abdul El-Sayed:** A test of whether an unapologetic, sharp-witted left-populist candidate can win in Michigan, exemplified by viral clips of him dismantling bad-faith town hall questions about the Muslim Brotherhood and leaving his detractors as a "smoking crater on the floor."
- “Like that’s very feasible in the kind of thick part of the probability distribution.” — Nate Silver
- A major Republican sweep where Democrats only gain North Carolina would require fat-tail polling errors of five to seven points across multiple races.
[28:40](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1720s) Democratic Party Factions and Primary Narrative Dynamics
Ezra Klein begins by revisiting Nate Silver’s taxonomy of the internal factions shaping the Democratic Party: the "capital-L Left," the "abundance libs" (a camp Klein jokingly identifies with himself), and "Richardsonism" (named after Substack historian Heather Cox Richardson, representing the institutionalist "resistance libs" and anti-authoritarian "no kings" constituency). Looking ahead to the midterms, Klein asks how the election results might shape party strategy, pointing to two key underlying storylines beyond the raw battle for control: how progressives perform relative to moderates, and whether there is measurable evidence of an anti-AI backlash in state-by-state data centers where local construction might cause Republicans to underperform. Silver notes that high-stakes candidate losses heavily dictate post-election narratives; if high-profile progressive candidates like Abdul El-Sayed lose, it creates a punishing narrative for the left regardless of who wins the Senate, whereas more subtle statistical nuances (such as Jocelyn Benson winning by nine points while El-Sayed wins by four) would only be dissected by data analysts calculating "wins above replacement." Silver stresses that perception hinges on speed and clarity: “I think for any race, an important threshold question is, was the race called on election night?”
Silver pushes back against the media's oversimplified narrative that progressives dominated the primary cycle. Voters made nuanced distinctions, rejecting Francesca Hong in Wisconsin and turning away from Representative Jasmine Crockett in Texas in favor of James Talarico. Crockett, Silver argues, was not necessarily to the ideological left of Talarico or aligned with the Democratic Socialists of America (DSA), but rather functioned as a partisan bomb-thrower. Klein agrees, pointing out that Democratic primary voters were making calculating decisions rather than purely maximizing ideological purity or electability. Silver observes that voters operate on an expected-value calculation—balancing the odds of a candidate winning against how effectively they will advance the issues voters care about—and notes that intense Democratic infighting noticeably cooled after decisive primaries in Maine, Michigan, and Wisconsin, though it is bound to explode again as the 2028 presidential race ramps up.
- **Primary testing grounds**: Competitive contests in Wisconsin (where Francesca Hong lost) and Texas (where James Talarico defeated Jasmine Crockett) illustrated voter selectivity.
- **Narrative drivers**: The clarity of election-night calls and high-profile candidate wins or losses dominate party self-reflection far more than nuanced margin-of-victory calculations.
---
[31:33](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1893s) The Rise of the Elder Millennial Generation of Democratic Talent
Taking a step back, Klein articulates an emerging narrative about generational transition within the Democratic Party: the rise of an "elder millennial" cohort of political talent. Klein apologizes to his Gen X Democratic friends in office, arguing that late Baby Boomers and Gen X politicians found themselves trapped between radically different political and media eras. By contrast, a new wave of figures who entered politics during the presidency of Barack Obama and were forged during Donald Trump's first administration appear instinctively native to modern communication. Klein cites figures across diverse ideological spectrums, from left-wing figures like Zohran Mamdani, Abdul El-Sayed, and Alexandria Ocasio-Cortez to figures like Iowa gubernatorial contender Rob Sand (polling toward an easy victory), Texas star James Talarico, Georgia Senator Jon Ossoff, and Pete Buttigieg. Across all Democratic factions, high-wattage talent is finally surfacing simultaneously.
```mermaid
flowchart TD
accTitle: Generational Evolution of Democratic Political Talent
accDescr: Diagram illustrating the generational transition in Democratic political leadership from Obama to the elder millennial cohort.
subgraph Past ["Prior Generations"]
LateBoomerGenX["Late Boomers & Gen X<br/>'Caught between eras'"]
Interruption["Post-2012 Disruption<br/>(Clinton 'turn' & Biden flight to safety)"]
end
subgraph Influence ["The Catalyst"]
Obama["Barack Obama<br/>'Steph Curry effect'"]
end
Silver compares Obama’s transformational impact on this cohort to the way basketball superstar Stephen Curry reshaped the NBA by pulling up from deep range: “I think some kind of like a Steph Curry effect with Obama as an analog where like he starts shooting three-pointers from where no one has before and now kids are practicing that in in high school and they graduate and grow to college in the NBA.” Silver reflects on how the natural trajectory of the Obama realignment was momentarily derailed after 2012. Rather than passing the baton forward, the party reverted in 2016 to Hillary Clinton under a sense of "it's Hillary's turn," representing the 1990s Clintonian coalition. Later, in 2020, Democrats turned to Joe Biden—a running mate Obama had deliberately chosen because his age made him an unthreatening elder statesman—in a panicked flight to safety. That decades-long detour, Silver suggests, is finally ending as the party's modern talent pipeline reasserts itself.
- **Generational contrast**: Late Boomer and Gen X politicians struggled to adapt to modern fragmented media, whereas elder millennials were forged in online, direct communication environments.
- **The institutional delay**: The post-2012 succession was interrupted by Hillary Clinton’s 2016 nomination and Joe Biden’s 2020 candidacy before resuming with this emerging bench.
---
[34:30](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2070s) House Modeling, Redistricting, and the Florida Outlier
Turning from the Senate to the House of Representatives, Klein highlights that the House is not an all-or-nothing proposition; whether Democrats land at 228, 235, 240, or 250 seats dramatically changes governing leverage. Silver explains that even though the Silver Bulletin model gives Democrats over a 90% chance to flip the House, the projected average seat gain is only around 22 seats. This modest margin stands in sharp contrast to historic midterm sweeps—such as the 63-seat Republican landslide in 2010 or Democrats' 41-seat gain in 2018. Silver attributes this compression to extreme voter sorting and ruthless gerrymandering, which have radically reduced the number of genuinely competitive swing districts. Furthermore, Democrats had already performed relatively well in the House in 2024 despite Kamala Harris losing the presidency, leaving fewer easy Republican seats to flip.
Silver details how redistricting reshuffled the congressional landscape across key states:
- **Southern GOP pickups**: Republicans cleanly extracted three seats by dismantling majority-minority districts in Louisiana, Alabama, and Tennessee, although the remade Alabama district remains surprisingly competitive in recent polling.
- **Texas miscalculations**: Texas Republicans drew aggressive maps under the assumption that 2024's sharp rightward shifts among lower-income Hispanic voters were permanent; however, recent polls show those demographics shifting aggressively back toward Democrats, leaving those districts vulnerable.
- **Florida gerrymandering**: Governor Ron DeSantis pushed through an aggressive, high-risk congressional map optimized for high-turnout presidential years, leaving numerous seats in "toss-up" or "lean Republican" territory in an unfavorable midterm climate.
When Klein asks why Florida transformed so completely from a bellwether swing state into a fortress more conservative than Texas—recalling that DeSantis barely won his first gubernatorial election in 2018—Silver estimates the shift is driven roughly 75% by migration patterns and 25% by an internal Democratic "death spiral." Describing Florida's appeal to conservatives, Silver quips, “Florida is a unique place in offering blue state amenities, but without without as many libs, you know what I mean?” While Democrats are regaining ground in voter registration figures across the industrial Midwest and Pennsylvania after years of decline, Florida continues to register net gains for Republicans, cementing its status as an outlier. Klein wraps up by asking whether a standard 3- to 4-point polling error in Democrats' favor could crack these heavily engineered maps wide open, potentially transforming a modest House majority into an explosive 40-seat blowout.
[38:44](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2324s) Vulnerable Republican Candidates and Trump's Midterm Strategy
When an electoral wave swells, it inevitably floods candidates who were never built to withstand severe political storms. Nate Silver points directly to Kansas senator Roger Marshall as a prime example of an exposed and flawed candidate whose seat would normally be secure in deep-red territory. Silver, noting that he has family in Overland Park, Kansas, who follow Kansas and Missouri politics closely, reflects on how easily low candidate quality gets exposed during high-tide midterm cycles. Ezra Klein reminds Silver of Donald Trump’s clumsy defense of Marshall, in which Trump tried to excuse Marshall’s controversial history of aggressively pursuing debts from medical patients by using an antisemitic trope:
> “And they made it like, oh, he was some kind of a Shylock-type guy.”
This dynamic leads Silver to wonder whether Trump genuinely cares if the Republican Party holds the Senate at all, particularly since he governs almost exclusively through executive power rather than legislative action. Klein points out that Texas offers another obvious example: Trump could easily have intervened in the Texas primary to hand the nomination to John Cornyn, putting Republicans in a vastly safer position to defend their majority. Instead, Trump’s entire midterm approach has revolved around his own ego. He organized a bizarre "midterm convention" under the assumption that Republicans will only struggle because he is not personally on the ballot, while floating plans to issue a $5,000 check to every American if Republicans win. Klein observes that Trump is only interested in winning the midterm if the victory flatters him personally; if winning requires distancing candidates from him or endorsing figures he dislikes, he simply refuses.
```mermaid
flowchart TD
accTitle: Trump Midterm Paradox
accDescr: Diagram showing how Trump's personalized strategy creates vulnerabilities for down-ballot Republicans.
subgraph EgoStrategy["Trump-Centric Strategy"]
A["Focus on Personal Credit"] --> B["Bribes & Spectacle<br>($5,000 check pledge, Midterm Convention)"]
A --> C["Interference in Primaries<br>(Refusing to consolidate Cornyn, defending Marshall)"]
end
subgraph MidtermReality["Midterm Electoral Dynamics"]
D["Trump Not on the Ballot"]
E["Vulnerable Candidates Inundated<br>(Kansas, Texas)"]
end
B --> D
C --> E
D --> F["Turnout Deficit Among Low-Propensity Base"]
E --> G["Risk of Senate Majority Loss"]
```
[41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) Trump's Missing Base and the High-Turnout Disconnect
Republicans repeatedly find themselves trapped whenever Trump looms as the dominant figure in the party but is not physically on the ballot. Silver traces this structural problem across the entire modern electoral ledger: the 2018 midterms, the 2022 cycle where Joe Biden avoided the historic wipeout normally associated with a 40 percent approval rating, the two Georgia Senate runoffs, special elections, state Supreme Court contests, and citizen ballot initiatives.
> “Look, Republicans are kind of caught between a rock and a hard place in elections where Trump himself is the dominant figure but not himself on the ballot.”
Silver explains that Trump’s singular political gift is motivating a specific cohort of otherwise disengaged, low-propensity voters to "crawl on glass" to cast a ballot for him—voters who are frequently screened out of polling models as unlikely voters. But those same disaffected voters will not crawl over broken glass to vote for candidates like Roger Marshall or Ken Paxton. At the same time, Silver cautions against over-indexing on candidate mechanics while ignoring the colossal macroeconomic elephant in the room: Democrats would not be favored to take the Senate if Trump had not dragged the country into a war with Iran, driving nationwide gasoline prices well into the mid-$4 range per gallon.
- The disengaged Trump base disproportionately abstains in off-year, runoff, and special elections.
- Republican losses in off-cycle contests span Georgia Senate runoffs, Wisconsin Supreme Court races, and reproductive-rights ballot initiatives.
- Nationwide gas prices shot into the mid-$4.00s per gallon following the outbreak of hostilities with Iran, climbing even higher in states like California.
When Klein asks whether Trump’s approval rating drop during his second administration has been a smooth attrition or a series of discrete shocks, Silver indicates that it has been a largely steady slide punctuated by distinct inflection points. Statistically, Trump’s approval remains closely linked to gas prices and broader economic strain. A noticeable plunge occurred around "Liberation Day" in April 2025 amid widespread consumer and market alarm over proposed tariffs.
Silver argues that observers drew flawed conclusions from Trump's first presidency. In the first three years of that administration, a healthy economy acted as a Teflon shield:
> “When voters felt like the economy was good, and objectively it was pretty good in the first three years of Trump, that just kind of serves as like a a halo that allows you to say, 'Oh, Democrats are complaining about democracy this and democracy that and and race and xenophobia and whatever else, right? But you got more money in your paycheck.'”
Now that voters are questioning their paycheck security, their home equity, and the stock market, the administration's relentless culture wars register as desperate and grating. Compounding this is sheer voter exhaustion. Trump has dominated headlines since mid-2015, and at 80 years old, he faces many of the same age-related vulnerabilities that began eroding Joe Biden’s standing at a comparable stage of his term. Silver highlights how baffling Trump's policy positions have become, pointing out that his vocal defense of energy-hungry AI data centers pits him against an 80–20 issue where the public overwhelmingly wants artificial intelligence deployment slowed down rather than accelerated (roughly 60% favoring a slowdown versus only 3% advocating acceleration).
[44:34](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2674s) Trump's Bet on AI, Data Centers, and Big Tech Donors
Klein offers two primary explanations for why Trump has embraced the deeply unpopular proliferation of AI data centers instead of demagoguing against them as a populist. First, Trump appears genuinely persuaded that the United States is locked in a zero-sum geopolitical and technological arms race with China, adopting the mindset that whoever wins AI wins the future. Second, the administration is backed into an economic corner where equities are the last remaining pillar standing:
> “If the AI boom, if something shifts sentiment, then the one economic indicator Trump has that is looking good for him, which is the stock market, collapses.”
If tech enthusiasm breaks, Trump faces an ugly cocktail of high interest rates, ballooning federal debt, sluggish GDP growth, and a plunging stock market. Beyond macroeconomics, Klein notes the naked financial influence at work: leading Silicon Valley executives have poured massive sums into Trump's orbit, with Elon Musk alone funneling an estimated $400-plus million directly into bankrolling the Republican midterm effort.
Silver agrees that Trump’s paramount daily obsession has always been avoiding "red arrows on the stock market ticker." Yet investor unease is steadily building around whether the AI infrastructure trade resembles a fragile bubble trying to execute a high-speed landing without proven flight instruments. With oil prices spiking again amid Middle Eastern escalation, Silver observes that an eleventh-hour financial market drop remains the most plausible wildcard capable of sinking Republican prospects right before the polls open.
[47:12](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2832s) Bush 2006 Parallels and Lame-Duck Risks
Klein turns to the historical precedent of George W. Bush’s second term. While commentators frequently reference Bush in 2006 as the cautionary tale of an immobilized, super-lame-duck executive, Klein underscores that the final two years of Bush's tenure were violently consequential, culminating in the 2008 global financial meltdown. Looking ahead at Trump's trajectory, Klein sees severe, systemic tail risk across every theater:
> “I look at Trump and I look at the economy and I look at the geopolitical situation and what I see is risk everywhere.”
Klein and Silver review the sheer volume of potential crises that could engulf the back half of Trump’s term:
- A severe domestic recession, an abrupt stock market unwinding, or an interconnected banking crisis.
- Uncontrollable military escalations spanning Russia-Ukraine, Israel-Iran, or the broader Persian Gulf.
- Novel threats from rogue autonomous systems or cyberwarfare escalations, such as an American or Chinese AI swarm strike.
Silver adds that Trump will turn 82 before leaving the Oval Office. When a lame-duck president faces compound systemic shocks with zero public trust, depleted congressional leverage, and advancing age, the administration lacks the institutional credibility required to steer through the blast radius.
[48:53](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2933s) Foreign Policy Blunders and the Threat of a Lame-Duck Tilt
Ezra Klein and Nate Silver discuss the political fallout of recent foreign policy decisions, contrasting Joe Biden’s administration with Donald Trump’s second term. While crises in Ukraine and Gaza emerged under Biden's watch, the recent confrontation with Iran was an active choice driven by Trump and Benjamin Netanyahu. Silver argues that if Republicans lose the Senate, Defense Secretary Pete Hegseth deserves a significant share of the blame, observing that few conventional defense officials would have agreed to an ambiguous war plan with undefined strategic goals.
Klein notes that Hegseth, a former *Fox & Friends* host, was installed precisely because Trump demanded uncritical loyalty: “Donald Trump had named Pete Hegseth a Fox & Friends correspondent to be defense secretary because he wanted somebody in that position who would never under any circumstance say no to him.” Klein doubts Hegseth will be replaced by a seasoned, authoritative figure like Jim Mattis if he is dismissed after the midterms. He draws an analogy to economic policy, pointing out that Gary Cohn—the former Goldman Sachs executive who led the National Economic Council during Trump's first term—would have resisted the current tariff regime.
Looking ahead, Klein raises alarm over potential cascading crises during Trump's final two years, including an AI market collapse, confrontation with China, or an economic meltdown, warning that an isolated Trump could resort to erratic, high-risk gambles. Silver confesses that the compounding uncertainty makes him anxious, noting that an aging Trump is particularly ill-equipped to steer the nation through an unprecedented technological transformation: “I'm not sure that's the person that you'd want to have in charge as an 82-year-old Donald Trump.”
```mermaid
flowchart TD
accTitle: Systemic Risks in Trump Lame-Duck Administration
accDescr: Diagram illustrating how loyalty-first appointments feed into policy escalation and heighten broader geopolitical and technological risks.
subgraph Administration["Personnel Selection"]
A["Loyalty Over Experience<br>(e.g., Pete Hegseth, Fox & Friends)"]
B["Absence of Internal Checks<br>(No Jim Mattis or Gary Cohn)"]
end
subgraph Shocks["Immediate Shocks"]
C["Confrontation with Iran<br>(Ambiguous war objectives)"]
D["Aggressive Tariffs Regime"]
end
subgraph Volatility["Compounding Risks"]
E["Economic Downturn / AI Disruption"]
F["Lame-Duck 'High-Tilt' Behavior<br>Under 82-Year-Old Trump"]
end
A --> B
B --> C
B --> D
C --> E
D --> E
E --> F
```
[51:48](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3108s) Money in Politics and 2026 Midterm Predictions
When Klein asks whether late-stage campaign expenditures—including massive cash infusions from Elon Musk—can alter the midterms, Silver responds that money is generally overrated in high-profile Senate, gubernatorial, and presidential races due to diminishing returns. However, funding remains critical down-ballot in state legislative races and marginal House districts where name recognition is thin, especially given frequent redistricting fights. Silver adds that raw Republican financial advantages are misleading: grassroots donor money yields lower statutory advertising rates, whereas last-minute corporate and party PAC money pays high premiums, equalizing actual ad impressions.
Reflecting on past elections, Klein recalls how Silver's model favored Kamala Harris in 2024 while his gut warned of a Trump win. Silver explains the psychological difficulty of hedging against poll misses:
> “The fundamental conditions feel terrible for Republicans, right? You have the second-term 80-year-old president who had a bad midterm when he was younger and more popular and the economy was perceived as better in 2018. And now you have Iran, you have 4.50 gas, you have Jeffrey Epstein, right? You have corruption in the White House, you have the strong batch of Democratic candidates.”
Silver observes that in 2024 he easily compiled 21 environmental indicators favoring Trump, whereas in 2026 the macro environment overwhelmingly favors Democrats. If the backlash matches or exceeds the 2018 cycle, Democrats could carry the national House popular vote by 10 to 11 percentage points. While Silver remains skeptical of dramatic polling leads in deep-red states like Iowa or Kansas, he concludes that his gut worries more about idiosyncratic state polling errors than an error in the national environment.
- **High-profile race diminishing returns:** Campaign cash has limited marginal impact in saturated Senate and gubernatorial contests, but remains influential in state legislative and obscure House races.
- **Ad rate disparity:** Early small-dollar candidate fundraising secures protected, cheaper television ad rates, balancing out large, late corporate and PAC expenditures that buy ads at peak pricing.
- **2026 Republican headwinds:** Key negative drivers include high fuel prices ($4.50/gallon), renewed fallout from the Jeffrey Epstein files, the ongoing war with Iran, and broad voter fatigue.
[54:50](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3290s) Nate Silver’s Book Recommendations
Wrapping up the interview, Klein invites Silver to share three book recommendations for the audience. Silver selects three unconventional titles spanning macroeconomics, personal agency, and gambling lore:
1. ***The Rise and Fall of American Growth* by Robert J. Gordon (2016)**
Silver read Gordon’s economic history while playing in a poker tournament in Paris, amid news of the war with Iran and disputes between the Department of Defense and Anthropic. The book argues that humanity's most dramatic improvements in living standards occurred between 1870 and 1970 through innovations like indoor plumbing and electricity, rather than recent digital advances. Silver notes that early phases of the Industrial Revolution produced Dickensian squalor, child labor, and manure-filled streets long before translating into broad prosperity—a cautionary parallel for modern AI optimists.
2. ***You Can Just Do Things* by Cate Hall**
Written by former top-ranked poker professional Cate Hall, this volume functions as a practical manual on agency and communication for analytically minded people. Hall, who overcame addiction before transitioning to the Bay Area tech and rationality scene, emphasizes having transparent conversations about intentions, needs, and feedback rather than allowing social awkwardness to distort relationships.
3. ***The Biggest Game in Town* by A. Alvarez (1983)**
Silver calls Alvarez's account the greatest poker book ever written. The British poet and literary critic traveled into the Nevada desert during the formative years of the World Series of Poker, capturing vivid portraits of classic Texas roadhouse gamblers. Silver praises its literary craftsmanship, sharp prose, and portrait of high-stakes American subculture.
[58:20](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3500s) Concluding Book Recommendations and Wrap-Up
Nate Silver concludes his final book recommendation by reflecting on why it resonates so deeply with him personally. He acknowledges that while some writing on the subject can feel superficial or overly journalistic, this work genuinely connects with a subculture he cares about. As Silver emphasizes, “And it’s one of the few books about gambling that doesn’t fall into cliches and captures this part of the world that I’m fascinated by very well.”
Ezra Klein responds warmly, noting, “That that book sounds great,” before wrapping up the conversation and thanking Silver for coming on the program. Silver offers a brief thank you in return as the closing theme music plays out the episode.
## Notable quotes
> [09:52](https://www.youtube.com/watch?v=uDqR4t5N84o&t=592s) The one group you do not want to rely on to turn out in a midterm is usually young men. — Nate Silver
> [00:00](https://www.youtube.com/watch?v=uDqR4t5N84o&t=0s) If the election goes roughly as the polls say it will go, then in some ways it would mark the end of the Trump era, I think. — Nate Silver
> [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) Republicans are kind of caught between a rock and a hard place in elections where Trump himself is the dominant figure but not himself on the ballot. — Nate Silver
> [47:12](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2832s) I look at Trump and I look at the economy and I look at the geopolitical situation and what I see is risk everywhere. — Ezra Klein
## Mentioned
Nate Silver, Ezra Klein, Donald Trump, George W. Bush, Barack Obama, Joe Biden, Kamala Harris, Hillary Clinton, Kirsten Gillibrand, Janet Mills, Graham Platner, Troy Jackson, Susan Collins, Mary Peltola, Jocelyn Benson, Abdul El-Sayed, James Talarico, Ken Paxton, Roy Cooper, Sherrod Brown, Jon Ossoff, Dan Osborn, Adam Hamilton, Tina Kotek, Kathy Hochul, Charlie Baker, Tim Walz, John Edwards, John Fetterman, Mehmet Oz, Ann Selzer, Jeff Jackson, Francesca Hong, Jasmine Crockett, Heather Cox Richardson, Alexandria Ocasio-Cortez, Zohran Mamdani, Rob Sand, Pete Buttigieg, Stephen Curry, Ron DeSantis, Roger Marshall, John Cornyn, Elon Musk, Benjamin Netanyahu, Pete Hegseth, Jim Mattis, Gary Cohn, Robert J. Gordon, Cate Hall, A. Alvarez, Jeffrey Epstein, The Silver Bulletin, Still Counting, On the Edge: The Art of Risking Everything, The Rise and Fall of American Growth, You Can Just Do Things, The Biggest Game in Town, Democratic Senatorial Campaign Committee, The Des Moines Register, The Economist, Anthropic, Fox & Friends
## Video description
“If the election goes roughly as the polls say it will go, then in some ways it would mark the end of the Trump era,” Nate Silver told me.
The midterms are a week away, and it looks entirely possible that Democrats will win not just the House, but also the Senate. Democrats are polling competitively deep into red territory – Texas, Ohio, Alaska, Iowa, Kansas – states that Trump won in 2024 by double digits.
But Democrats have been burned by big polling misses before. So can we really trust what the polls are telling us? And what stories have emerged in the data that we might see play out on election night?
Silver is an internationally famous elections nerd, one of the people who made election forecasting a core part of American political discourse. He edits The Silver Bulletin on Substack, co-hosts the podcast “Still Counting” and is the author, most recently, of “On the Edge: The Art of Risking Everything.”
[00:00:00] Intro
[00:09:40] Are Democrats overperforming in red states?
[00:13:07] Does moderation win elections?
[00:26:32] What if Republicans have a better night?
[00:30:05] The Democratic Party's new talent
[00:42:26] Trump's declining approval rating
[00:48:48] Risks in Trump's lame duck term
[00:51:48] Money's impact & election predictions
[00:54:50] Book recommendations
Read the full transcript here: https://www.nytimes.com/2026/10/27/opinion/ezra-klein-podcast-nate-silver.html
Watch more on @EzraKleinShow
Thoughts? Guest suggestions? Email us at ezrakleinshow@nytimes.com.
You can find transcripts (posted midday) and more episodes of “The Ezra Klein Show” at nytimes.com/ezra-klein-podcast. Book recommendations from all our guests are listed at https://www.nytimes.com/article/ezra-klein-show-book-recs.html
Analyzing the upcoming midterm elections, forecaster Nate Silver and Ezra Klein argue that an 11-point national swing against Donald Trump's Republican Party has placed Democrats on a plausible path to sweep both chambers of Congress. Silver contends that a decisive Democratic victory would effectively end the Trump era by inaugurating an immediate, lame-duck status and launching the 2028 presidential campaign.
Structural Mechanics of the 11-Point Swing (3:18)
While historical midterms typically feature an average backlash of 7.5 percentage points against the incumbent party, Silver's model tracks an 11-point environment shift in favor of Democrats. Because Donald Trump carried states like Ohio by roughly 11 points in 2024, a uniform swing instantly pushes previously solid Republican territory into competitive tossup range. Silver's model gives Democrats better than a 70 percent chance of capturing the Senate and over a 90 percent chance of flipping the House, though ruthless gerrymandering caps projected House gains at an average of roughly 22 seats.
Silver attributes the clustering of Democratic overperformance in heartland and Midwestern states to several concrete economic and demographic drivers. Spiking diesel and heating oil prices have severely pressured agricultural and trucking sectors concentrated in colder battlegrounds. Furthermore, Silver observes a "last in, first out" dynamic: low-propensity young men and working-class voters who swung toward Trump in 2024 tend to drop out during midterms, compounding Republican turnout vulnerabilities.
Candidate Quality and the Millennial Bench (11:28)
Electoral outcomes continue to depend heavily on candidate recruitment and regional calibration. Democrats have excelled where they nominated moderate, populist figures tailored to local electorates—such as James Talarico in Texas, Roy Cooper in North Carolina, and Sherrod Brown in Ohio. By contrast, where progressives won primaries in purple or conservative states, such as a DSA-backed nominee in Florida trailing by six to eight points, the party has struggled. In Michigan, progressive Abdul El-Sayed's narrower lead reflects the ideological drag progressive candidates face compared to moderates like gubernatorial nominee Jocelyn Benson.
Klein and Silver highlight a broader generational transformation: the rise of an "elder millennial" cohort across Democratic factions, including figures like Talarico, Jon Ossoff, Rob Sand, and Alexandria Ocasio-Cortez. Silver compares Barack Obama's stylistic influence on this cohort to Stephen Curry transforming basketball, noting that the succession was delayed for years by the nominations of Hillary Clinton in 2016 and Joe Biden in 2020. Conversely, Republicans face severe exposure from flawed candidates such as Roger Marshall in Kansas and Ken Paxton in Texas, whom Trump has defended while largely ignoring legislative defensive strategy.
Polling Realities and Systematic Error Scenarios (19:28)
Addressing Democratic anxieties over past polling errors, Silver emphasizes that midterms in the Trump era have been historically accurate. The 2018 and 2022 cycles saw reliable survey averages, and recent off-year elections in Virginia and New Jersey actually underestimated Democratic margins by five to ten points. While raw demographic weighting broke down in presidential contests—exemplified by Ann Selzer's 2024 Iowa poll missing the final margin by 13 to 15 points—pollsters now utilize aggressive likely-voter screening models to avoid underestimating the conservative base.
Silver cautions that polling errors are correlated across states. If surveys systematically understate Republican support by three to four points, close Democratic leads in Texas and Ohio would evaporate, potentially preserving the Republican Senate majority. However, Silver argues that preserving the House would require an extraordinary five-to-seven-point polling error that defies standard midterm backlash patterns under an unpopular executive.
Lame-Duck Escalation and Macroeconomic Headwinds (47:12)
Silver links Trump's declining approval ratings to severe economic shocks and unforced policy missteps, notably military escalation with Iran that drove nationwide gasoline prices into the mid-$4 range. Unlike Trump's first administration, where strong economic growth insulated him from criticism, public anxiety over home equity, inflation, and interest rates has rendered constant culture-war controversies grating to voters. Klein notes that Trump has placed a high-stakes bet on artificial intelligence infrastructure, relying on tech optimism to sustain equity markets despite broad public skepticism toward rapid AI deployment.
Drawing parallels to George W. Bush's post-2006 term, Klein warns that the back half of Trump's presidency faces systemic tail risks spanning geopolitical conflicts, recession, and cyber warfare. Because Trump prioritized loyalty over administrative experience by appointing figures like Defense Secretary Pete Hegseth, the administration lacks institutional checks such as Jim Mattis or Gary Cohn. Silver adds that an 82-year-old lame-duck president facing cascading crises with negligible public trust poses grave governance risks.
Silver concludes that while idiosyncratic state polling errors could still cause Democrats to fall short in narrow Senate pickup opportunities, national fundamentals heavily favor an anti-incumbent wave. The unresolved question is whether Republican base turnout collapses entirely without Trump on the ballot, converting a modest Democratic takeover into a sweeping, historical rout.
## Background
本内容由《The Ezra Klein Show》于 2026 年 10 月 27 日发布在 YouTube 平台。节目简介指出，距中期选举仅剩一周，民调显示民主党不仅有望拿下众议院，甚至深入得克萨斯、俄亥俄、堪萨斯等深红州角逐参议院控制权，埃兹拉·克莱恩（Ezra Klein）特邀知名民调专家内特·西尔弗（Nate Silver）共同探讨民调可信度及特朗普时代是否正走向终结。
## TL;DR
节目深入剖析了本届中期选举民主党在全国范围内掀起的大幅反弹动能，及其在传统深红州意外展现竞争力的底层逻辑。西尔弗拆解了全国性选情漂移、候选人特质差距与柴油通胀、地缘冲突等宏观基本面如何共同挤压共和党，并推演了民调系统性误差可能带来的不同结局。两人还探讨了民主党“年长千禧一代”政治新星的代际崛起，并对特朗普第二任期沦为“超级跛脚鸭”后，受制于顺从型内阁而可能引发的经济、地缘与技术失控风险发出了严厉预警。
## Atmosphere & style
整场对话洋溢着极客式的智识交锋与严谨的数据推演氛围，克莱因敏锐的宏观叙事框架与西尔弗冷静客观的概率模型形成了极具张力的互补。对谈从对民调历史偏差的冷峻审视，逐步推进至对白宫决策机制、地缘冲突与市场脆弱性的深层担忧，语调在专业理性中隐隐透出对系统性未知的焦虑感。终局关于牌手心智与经济史的书单分享，则为这场高密度的政治推演增添了一抹从容的人文与哲学底色。
## Bulletin
- [01:46](https://www.youtube.com/watch?v=uDqR4t5N84o&t=106s) 内特·西尔弗的模型预测显示民主党夺回参议院的概率已突破70%，全国性民调反弹幅度达11个百分点，不仅能守住脆弱选区，更有望在堪萨斯、得州等传统深红州完成翻盘。
- [11:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=688s) 民主党在深红州依靠温和派及独立人选（如汉密尔顿、布朗、奥斯本）实现民调超常发挥，而在紫州或安全州因提名偏左甚至DSA激进候选人导致领先优势大幅缩水。
- [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) 特朗普第二任期支持率跌入历史低谷，油价飙升、关税焦虑与介入伊朗战事使其宏观基本面远差于2018年，且无法在自己不参选的中期选举中有效动员低投票倾向选民。
- [51:48](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3108s) 埃隆·马斯克虽注资超4亿美元为共和党中期选举托底，但政治竞选资金在高级别选举中边际效用递减，叠加高昂广告费率，未能形成实质传播压制。
## Key takeaways
- [01:46](https://www.youtube.com/watch?v=uDqR4t5N84o&t=106s) 若选举结果如民调所示，特朗普将瞬间变为类似2006年中期后小布什式的“超级跛脚鸭”，从政治上实质标志特朗普时代的终结。
- [04:13](https://www.youtube.com/watch?v=uDqR4t5N84o&t=253s) 美国中期选举规律中反对党平均反弹约7.5个百分点，而本届偏向民主党的全国性反弹幅度达11个百分点，足以直接抹平得克萨斯和俄亥俄等深红州的基本盘优势。
- [09:52](https://www.youtube.com/watch?v=uDqR4t5N84o&t=592s) 柴油价格高企沉重打击了中西部农业、物流与供暖选民，加上2024年加入特朗普联盟的年轻男性与拉美裔选民呈现“后进先出”特征，共同驱动了深红州的民调松动。
- [11:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=688s) “温和派胜选假说”在选战中得到印证：深红州严格推举温和派或独立人选表现亮眼，而部分州推举偏左乃至美国民主社会主义者（DSA）候选人则直接导致优势萎缩或跌出竞争圈。
- [15:03](https://www.youtube.com/watch?v=uDqR4t5N84o&t=903s) 社交媒体声量与实际选票表现严重脱节，红紫州高胜率候选人大多选择极少接受全国媒体采访的低调防御策略。
- [19:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1168s) 民调在2018和2022年中期选举中其实表现出高度准确性甚至低估过民主党，当前民调本质上已演化为带有民调输入的“微型预测模型”。
- [31:29](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1889s) 民主党“年长千禧一代”明星班底跨越派系边界全面接班，其表达风格深受巴拉克·奥巴马影响，终结了2012年后党内代际交替的停滞期。
- [34:30](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2070s) 佛罗里达州彻底翻红并形成共和党坚固堡垒，75%归因于寻求非自由派生活方式的人口迁徙，25%归因于佛州民主党的组织性衰退。
- [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) 特朗普唯一的动员“魔术”是让自己在选票上激发边缘铁杆，当其本人未参选时，选民绝不会为罗杰·马歇尔或肯·帕克斯顿等弱质候选人去“爬玻璃渣”。
- [44:36](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2676s) 为保住股市这一最后遮羞布并维系科技金主，特朗普不惜在民意反对率高达80%的AI数据中心议题上站台。
- [48:53](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2933s) 特朗普第二任期彻底清除了建制派制衡者，由绝对服从的“唯唯诺诺者”（如防长海格塞斯）组阁，一旦遭遇地缘与经济风暴极易陷入扑克式“狂躁失控（Tilt）”。
- [51:48](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3108s) 政治资金在高关注度选举中边际递减，民主党凭借小额捐款在早期锁定的低价广告点位，有效抵消了马斯克等超级金主的巨额注资。
- [54:50](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3290s) 西尔弗推荐罗伯特·戈登的《美国增长的起落》等书，强调美国核心生产力飞跃发生在1870至1970年，提醒人们客观看待当前AI乐观派的技术承诺与早期转型代价。
## Detailed walkthrough
### [00:00](https://www.youtube.com/watch?v=uDqR4t5N84o&t=0s) 中期选举前夕：民主党意外迎来的参议院翻盘契机
距离中期选举仅剩一周时间，一年前看似完全不可能发生的情景如今却成为了现实：民主党不仅拥有拿下众议院的明确路径，甚至有可能一举夺回参议院的控制权。从选战算术来看，民主党若想重掌参议院多数席位，前提是必须守住目前所有处于竞争状态的现有席位，同时还必须在目前由共和党把持的州中至少翻转四个席位。在这些目标州中，有一两个席位此前一直被认为存在微弱机会，但剩下的则是硬骨头——那些唐纳德·特朗普（Donald Trump）在2024年以两位数优势大胜的深红州。此前几乎没有人认真讨论过堪萨斯州，然而现在堪萨斯州却赫然在列。更令人瞩目的是，民调显示民主党在所有这些深红州都展现出了强劲的竞争力，在个别选战中甚至处于大幅领先状态。
面对这一选情，核心疑问随之而来：民调真的可信吗？在投票日前仅剩一周的关头，数据究竟揭示了什么？为了厘清局势，埃兹拉·克莱恩（Ezra Klein）邀请了国际知名的民调与选举预测专家内特·西尔弗（Nate Silver）展开对话。西尔弗目前在Substack平台主笔《Silver Bulletin》，并联合主持播客《Still Counting》，其最新著作是《On the Edge: The Art of Risking Everything》。埃兹拉特别提及，特朗普目前的支持率甚至已经跌破了“1月6日国会山骚乱”之后的历史低点。
- **参议院翻盘路径**：民主党不仅需要全守自身脆弱席位，还必须从共和党手中翻转至少4个席位。
- **竞争范围扩大**：除常规战场外，特朗普曾以两位数优势胜出的深红州（如堪萨斯州、得克萨斯州、俄亥俄州）均进入实质竞争状态。
- **总统民调风向**：特朗普当前的支持率已跌至其执政生涯以来的最低水平之一。
---
### [01:46](https://www.youtube.com/watch?v=uDqR4t5N84o&t=106s) 为何这届选举至关重要：特朗普及特朗普时代的终结？
在节目正式录制前，西尔弗曾向埃兹拉透露，他隐约觉得这次中期选举带有某种“重大历史转折”（momentous）的气息。埃兹拉指出，相识多年来西尔弗极少使用这种宏大叙事的词汇。西尔弗对此解释称，如果最终投票结果与当前民调大致吻合，这在很大程度上将宣示特朗普时代的终结。内特·西尔弗强调说：“如果选举结果大致如民调所示，那么我认为在某种程度上，这将标志着特朗普时代的终结。”
西尔弗进一步剖析，尽管特朗普在宪法层面上还将继续担任两年总统，但一旦计票结束（考虑到阿拉斯加和加利福尼亚等州计票较慢可能需要一些时日），2028年大选的战幕便会立即拉开。如果共和党如民调所示遭遇惨败，特朗普将瞬间变成一个“超级跛脚鸭”，其处境堪比2006年中期选举惨败后的小布什（George W. Bush）。选民目前难以置信的原因在于，眼前的数据仿佛呈现出了一个全新的政治格局：得克萨斯和堪萨斯居然变得充满悬念，民主党正在向共和党腹地大举反攻。西尔弗认为，伴随代际更替、特朗普进入任期尾声，以及人工智能（AI）和经济议题对选民心理的深层重塑，美国政治正处于范式转变的临界点。
埃兹拉回忆道，就在一年前，华盛顿的共识还是参议院翻盘绝无可能，埃兹拉·克莱恩回忆说：“一年前大家的议论还是：民主党或许能拿下众议院，但至于参议院，虽然绝不能说‘绝不可能’，但基本没戏。”当时的逻辑是，深陷高度两极化极化党派政治的美国选民，不可能跨越特朗普10个百分点以上的基本盘鸿沟。然而在西尔弗的模型预测中，民主党赢得参议院的概率已经突破了70%，不仅有望胜选，甚至可能赢得相当充裕的多数席位。
```mermaid
flowchart TD
accTitle: Midterm Shift and Seat Flipping Logic
accDescr: Diagram illustrating how an 11-point national swing combined with candidate quality converts red states into tossups or flips.
subgraph Baseline ["2024年选情基准"]
A["特朗普在深红州领先\n(例如：俄亥俄+11%, 得州+13%)"]
end
subgraph Dynamics ["本届中期选举动力"]
B["历史性中期反弹\n(选情整体向民主党偏移约 11 个百分点)"]
C["候选人特质差距\n(共和党弱候选人 vs 民主党强竞选人，影响幅度约 2-5 个百分点)"]
end
subgraph Outcome ["参议院席位转变"]
D["俄亥俄州成为五五开摇摆选区\n(Trump +11% - 11% 摆动 = 平局)"]
E["得克萨斯州发生翻盘\n(Trump +13% - 11% 摆动 - 候选人惩罚 = D+2%)"]
end
A --> B
B --> D
B --> E
C --> E
```
---
### [04:13](https://www.youtube.com/watch?v=uDqR4t5N84o&t=253s) 历史钟摆与11个百分点的选情漂移
谈及局势反转的原因，西尔弗认为首先在于2024年后外界预期的严重失准。2024年大选后，坊间充斥着关于“保守派氛围永久性转向”的论调，认为拜登执政失败、进步主义（wokeness）受挫，民主党将长期一蹶不振。埃兹拉直接插话吐槽这种“永久性转向”的论调十分愚蠢。西尔弗对此表示赞同，并指出美国选举史上最恒定、历经数十年检验的规律，就是选民对白宫执政党的中期选举大反弹。内特·西尔弗指出：“但如果你回顾美国选举的历史，就会发现美国选举中最规律的趋势——也是几十年来极少数依然成立的规律之一——就是执政党必定会在中期选举中遭遇选民的反弹。”纵观历史，除1998年克林顿因莱温斯基弹劾事件获同情票、2002年小布什借九一一事件声势之外，几乎概莫能外。
通常情况下，中期选举的大环境平均会向反对党倾斜约7.5个百分点，而本届选举的数据显示，这一偏向民主党的全国性反弹幅度达到了惊人的11个百分点左右。西尔弗拆解了这11个百分点的数学逻辑：
- 像俄亥俄州这样特朗普当年赢下11个百分点的州，在均匀遭遇11个百分点摇摆冲击后，瞬间变成了五五开的均势对决。
- 得克萨斯州原本是特朗普领先13个百分点的红州，在抵消11个百分点的系统性转向后，基础差距仅剩共和党领先2个百分点（R+2）。
- 此时，候选人个人特质（candidate intangibles）所能左右的2到5个百分点差距就成了胜负手。深陷丑闻与争议的得州总检察长肯·帕克斯顿（Ken Paxton）作为共和党候选人严重失分，面对詹姆斯·塔拉里科（James Talarico）这样的民主党挑战者，完全足以抹平R+2并倒向民主党领先2个百分点（D+2）。
此外，民主党在多数重要选区完成了高质量的候选人招募，例如查克·舒默（Chuck Schumer）团队成功说服北卡罗来纳州前州长罗伊·库珀（Roy Cooper）出山参战，同时在内布拉斯加州等传统红区推举事实上的独立派人士参选。
---
### [06:44](https://www.youtube.com/watch?v=uDqR4t5N84o&t=404s) 民主党选战操盘与关键战场：缅因、密歇根与候选人特质
埃兹拉顺势提到了参议院民主党竞选委员会（DSCC）及其掌舵人瑟斯顿·吉利布兰德（Kirsten Gillibrand）。数月前，该团队曾因缅因州的初选失误而备受指责：建制派试图力推珍妮特·米尔斯（Janet Mills）参选未果，随后被寄予厚望的格雷厄姆·普拉特纳（Graham Platner）选情崩溃，最终由州参议院议长特洛伊·杰克逊（Troy Jackson）出线对阵资深共和党温和派参议员苏珊·柯林斯（Susan Collins）。尽管杰克逊目前民调微弱领先，但柯林斯有着多次大幅超越民调预期的历史（上届大选其实际得票比民调高出整整9个百分点），且缅因州的高质量民调样本较少，这让民主党人依然非常焦虑。
西尔弗分析指出，候选人特质在关键州的胜负中扮演着分水岭角色：
- **阿拉斯加州**：玛丽·佩尔托拉（Mary Peltola）表现极其亮眼，甚至以微弱优势领跑，如果是换作普通民主党人绝不可能在此类红州形成均势。
- **密歇根州与意识形态鸿沟**：西尔弗坚持认为温和派在摇摆州具备天然优势。内特·西尔弗直言：“我始终属于这种观点的人：在其他条件相同的情况下，至少在像密歇根这样的摇摆州，温和派候选人会比进步派表现得更好。”以密歇根州为例，走温和务实路线的州务卿乔斯林·本森（Jocelyn Benson）在州长竞选中领先对手8个百分点，而偏向进步派的参议员候选人仅领先对手3到3.5个百分点。这4.5个百分点的差距，恰恰印证了候选人特质在当下的实际影响力上限。不过，得益于民主党整体的顺风环境，加上其浓厚的密歇根本土工人阶级风格以及充沛的竞选筹款，候选人仍保持领先。
- **参议院底线预警**：西尔弗明确指出，密歇根和缅因是民主党的生命线，如果民主党丢失其中一个，仍有夺取参议院的希望；但如果两州尽失，民主党翻盘参议院的大门将被彻底关死。
---
### [09:15](https://www.youtube.com/watch?v=uDqR4t5N84o&t=555s) 红州超常发挥与蓝州温吞：令人不安的反常现象
对话切入了一个贯穿本轮民调的奇特现象：埃兹拉提出，民主党人似乎在越红的州超常发挥越明显。在得克萨斯、堪萨斯、爱荷华这类深红州，民主党的民调势头出人意料地迅猛；反而在密歇根、明尼苏达等传统蓝州或铁锈带紫色州，其优势幅度却显得较为收敛与温和。
埃兹拉询问西尔弗这背后究竟反映了什么实质机制。西尔弗坦言，这恰恰是让许多民主党内部人士深感不安的核心原因——因为在历史经验中，民调在深红腹地（尤其是美国内陆农业心脏地带）发生系统性偏差的概率往往最高。这种反直觉的分布究竟是代表了深红州反特朗普情绪的彻底爆发，还是民调抽样在红州再次漏掉了潜在保守派选民，成为了大选揭晓前最具悬念的谜题。
### [09:52](https://www.youtube.com/watch?v=uDqR4t5N84o&t=592s) 红州民调异动的经济与选民重组逻辑
内特·西尔弗（Nate Silver）指出，民主党近期在部分红州民调中的超水平发挥在多个层面上是合乎逻辑的。首要因素是汽油与柴油价格。柴油主要不用于乘用车，而是广泛消耗于农业、货运卡运、石油工业和家庭取暖油——这些领域高度集中在气候偏冷的中西部各州，而这也恰好是当前诸多核心战场的所在地。
第二个关键视角是“后进先出”（last in, first out）效应，即美国政治是否正在一定程度上脱离特朗普时代（Trump era）并发生温和的“去极化”（depolarization）。在2024年大选中，民主党相对2020年表现最差的反而往往是纽约和加利福尼亚等深蓝州；年轻有色人种选民及年轻男性整体转向了共和党。相反，在堪萨斯等传统红州，卡玛拉·哈里斯（Kamala Harris）与全国差距（PVI）的劣势实际上略微缩小。这一逻辑意味着，最晚加入特朗普联盟的群体——如部分拉美裔和白人工人阶级——可能正在轻微回调，或者干脆选择不投票。西尔弗特别强调了投票率特征：
> “The one group you do not want to rely on to turn out in a midterm is usually young men.”（中期选举中，你最不应该指望去投票的群体通常就是年轻男性。）
- **柴油经济受损区**：农业、物流与供暖重度依赖柴油，中西部选民对能源成本的敏感度直接冲击执政联盟。
- **选民重组的回摆**：2024年支撑特朗普民调爆发的年轻男性群体在非大选年中缺乏稳定的投票意愿。
---
### [11:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=688s) “温和派获胜”假说与候选人资质分歧
埃兹拉·克莱因（Ezra Klein）提出了另一种替代性假说：民调差异的根源可能在于两党在不同类型州的候选人资质（candidate quality）。在深红州，民主党内部更严格地贯彻了“提名温和派”的战略。例如：
- 堪萨斯州的亚当·汉密尔顿（Adam Hamilton）；
- 俄亥俄州深耕多年的民粹主义老将谢罗德·布朗（Sherrod Brown）；
- 北卡罗来纳州的罗伊·库珀（Roy Cooper）；
- 佐治亚州表现极其克制自律的乔恩·奥索夫（Jon Ossoff）；
- 内布拉斯加州以独立候选人身份参选、但获得民主党背书且未遭遇党内分流的丹·奥斯本（Dan Osborn）。
相反，克莱因指出，随着版图延伸到传统紫州或更蓝的州，民主党往往倾向于提名更激进的左翼候选人。例如缅因州由更偏左的候选人接替；密歇根州由阿卜杜勒·埃尔-萨耶德（Abdul El-Sayed）出战；明尼苏达州提名的偏左候选人佩吉·弗拉纳根（Peggy Flanagan）虽然有望胜出，但民调领先优势远低于安全线。在佛罗里达州，由于提名了一名美国民主社会主义者（DSA）候选人，目前落后6至8个百分点，甚至直接掉出了国家级竞争版图。克莱因借此推论，在红州，民主党严谨地选择了更具独立形象的温和人选；而在安全地带，他们因冒险偏左而吞下了选举优势缩水的结果。
```mermaid
flowchart TD
accTitle: Candidate Moderation vs State Partisanship
accDescr: Diagram contrasting Democratic candidate strategies in red states versus purple and blue states.
subgraph RedStates["深红州战略 (Red States)"]
RS_Action["严格推举温和派 / 独立候选人<br/>(Hamilton, Brown, Cooper, Osborn)"]
RS_Result["民调超预期<br/>表现强劲或紧咬"]
end
subgraph BluePurpleStates["紫州与蓝州战略 (Purple / Blue States)"]
BP_Action["推举偏左 / DSA 激进候选人<br/>(El-Sayed, Flanagan, DSA in FL)"]
BP_Result["优势缩水或错失良机<br/>(领先仅 1-4 点或直接落后)"]
end
RS_Action --> RS_Result
BP_Action --> BP_Result
```
西尔弗对此表示认同，并补充道，这也是选民对民主党“全面执政”（trifecta）州治理不满的体现：
- **明尼苏达州**：弗拉纳根仅领先3.5至4个百分点，而非传统的9到10个百分点；
- **俄勒冈州**：选民对自由派治理饱含批评，现任州长蒂娜·科特克（Tina Kotek）在民调中仅领先1至2个百分点；
- **纽约州**：凯西·霍楚尔（Kathy Hochul）预计能连任，但赢面幅度显得相对疲软。
西尔弗认为整体选民中存在着反现任情绪，大众在潜意识中权衡“究竟是谁在掌控我的现实生活”。不过克莱因提醒，这种反现任并非无差别爆发——佐治亚州的奥索夫与北卡罗来纳州的库珀等表现出色的现任者依然选情稳固。而明尼苏达州陷入苦战的直接原因，是蒂姆·沃尔兹（Tim Walz）净支持率暴跌至负17个百分点且放弃连任，重演了落选副总统候选人政治生涯断崖式下跌的经典宿命（如约翰·爱德华兹、保罗·瑞安）。
---
### [15:03](https://www.youtube.com/watch?v=uDqR4t5N84o&t=903s) 数据中心假说与社交媒体声量脱节
西尔弗进一步引述了《经济学人》（The Economist）的一项数据假设：特朗普选民居住地距离“数据中心”（data centers）越近，在本届选举中倒戈投向民主党的概率就越高。中西部与西部拥有广袤土地，既能容纳占地庞大的数据中心，又没有彻底脱离电网和主要基建，这可能构成了影响局部经济心态的隐性变量。
随后，克莱因指出当下竞选环境中的一个巨大割裂：社交媒体的声量/注意力与选票表现之间几乎没有任何正相关性。
- **高曝光群体**：阿卜杜勒·埃尔-萨耶德、詹姆斯·塔拉里科（James Talarico）频繁现身顶级播客并在社交信息流中无处不在，奥索夫的切片视频随处可见；
- **低曝光群体**：谢罗德·布朗、玛丽·佩尔托拉（Mary Peltola）、罗伊·库珀极少接受全国性媒体采访，行事低调，但在各自基本盘民调中表现优异。
西尔弗解释称，政客的媒体策略取决于未来诉求：如果放眼2028年总统大选，自然需要维持全国曝光度；但对于面临艰苦战役的红州/紫州政客，保持低调是极其明智的自我保护。中期选举本质上仅由三大问题决定：
1. 己方选民是否出门投票；
2. 对方选民是否出门投票；
3. 约占选民总数15%的摇摆选民说服工作完成得如何。
西尔弗评估，选民说服阶段已基本结束，民主党在中期选举标准的投票率必然高涨，真正的唯一变数是共和党选民是否会放弃投票。西尔弗对此评价道：
> “We don't know if Republicans are going to turn out, and that will determine the range between Republicans hold the Senate and keep Democrats to 10 seats in the House and complete 1994 style disaster.”（我们不知道共和党人是否会出来投票，而这决定了结局是共和党守住参议院并把民主党在众议院的优势压缩至10席，还是迎来一场1994年式的彻底灾难。）
---
### [17:47](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1067s) 民调误差风险：参议院与众议院的容错差异
克莱因将话题引向风险控制：民主党过去曾反复被特朗普或苏珊·柯林斯（Susan Collins）的民调低估所灼伤，民主党当前的乐观预期究竟能承受多大程度的民调系统性误差？
西尔弗给出了评估模型的第一法则：审视一系列参议院选战时，必须推演“如果所有州的民调同时朝同一方向偏离3到4个百分点会发生什么”。目前，民主党在俄亥俄州和得克萨斯州等红州的领先优势普遍只有3个百分点左右：
> “Look, the first thing I always tell people is that whenever you're looking at a series of polls in a Senate race or in Senate races plural, right, always ask yourself, what if they're off by three or four points in the same direction in every race?”（听着，我总是对人们说的第一件事就是，无论何时你在观察一场或多场参议院选举的系列民调时，永远要问自己：如果每场选举中的民调都朝着同一个方向偏离了三到四个百分点，结果会怎样？）
西尔弗分析，如果发生3个百分点的逆向误差，参议院选举将陷入漫长的焦灼之夜，甚至需要苦等阿拉斯加州的排序复选制计票结果。但众议院的容错度截然不同：目前的数据缓冲足够深厚，如果民主党最终连众议院都没有拿下，那不仅意味着民调体系出现了深不见底的系统性溃败，更意味着整个国家的底层政治逻辑发生了难以理解的剧变。然而在心理层面上，受希拉里·克林顿选举挫败的影响，民主党选民始终挥之不去“民调误差永远只对自己不利”的情感创伤。
### [19:28](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1168s) 特朗普时代中期选举的民调表现与“金牌民调”神话的破灭
Ezra Klein 提出疑问：既然民调在过去反复低估了唐纳德·特朗普，那么在接下来的中期选举中，民调偏差是否同样会系统性地对民主党不利？Nate Silver 澄清指出，这一规律在特朗普时期的两次中期选举中并不成立。2018 年中期选举是民调史上最准确的年份之一；2022 年也十分相近，例如宾夕法尼亚州参议员选举中，约翰·费特曼（John Fetterman）中风后民调显示穆罕默德·奥兹（Mehmet Oz）正在迅速追赶，但最终费特曼仍以稳健的 4 到 5 个百分点胜出。此外，在新泽西和弗吉尼亚等奇数年选举中，民调反而曾大幅低估民主党达 5 到 10 个百分点。
```mermaid
flowchart TD
accTitle: 民调在不同选举周期的偏差倾向
accDescr: 对比总统大选与中期选举及地方选举中民调误差的不同方向
subgraph Presidential ["总统大选年 (2016 / 2020 / 2024)"]
P1["传统人口加权抽样"] --> P2["严重低估特朗普/共和党支持率"]
P2 --> P3["Ann Selzer 爱荷华民调严重失准 (相差13-15个百分点)"]
end
subgraph Midterms ["中期选举与奇数年选举 (2018 / 2022 / 地方)"]
M1["2018 & 2022 整体民调高度准确"]
M2["新泽西/弗吉尼亚奇数年选举低估民主党 5-10 个百分点"]
M3["费特曼胜选验证了民调未被系统性拉偏"]
end
```
Silver 认为，外界批评民调“低估共和党样本、民主党人更有热情接电话”这一现象，业内其实人尽皆知。民调机构清醒地意识到，2016、2020 和 2024 年三次总统大选的接连失手，彻底粉碎了以往“仅靠人口普查特征加权并盲目相信原始数据”的所谓“金牌标准”。其中最具象征意义的事件就是爱荷华州传奇民调专家 Ann Selzer：
- Ann Selzer 曾准确预测 2008 年奥巴马在爱荷华州初选的胜利，长期被誉为顶级独立民调专家。
- 在 2024 年大选前夕，其他民调均显示特朗普在爱荷华州领先约 9 个百分点，而 Selzer 发布的民调却显示卡玛拉·哈里斯（Kamala Harris）领先 3 个百分点。
- 最终结果该民调出现了 13 到 15 个百分点的惊人误差。
- Nate Silver 谈及此事的戏剧性时回忆道：“What was it was the weekend before the election right and I had like some dinner plans on Saturday and then I got like a text from a friend saying have you heard about this Iowa poll?”
- 随后特朗普甚至荒唐地起诉了刊登该民调的报纸，认为发布其落后的民调构成了诽谤。
### [22:20](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1340s) 民调的“小模型化”与选民筛选机制的博弈
Ezra Klein 探讨了民调机构背后的具体操作：如今电话接听率极低、依赖线上抽样且无法预知选民投票率，民调机构究竟在做什么？Silver 直言，如今民调专家与预测师（Forecaster）的界限已经高度模糊，每一份民调在本质上都像是一个“带有民调输入特征的微型预测模型”。Silver 将民调行业的调整比作开餐馆调试菜品辣度：客人抱怨太辣就调淡，又有客人抗议不够辣就再加辣，民调专家在巨大的声誉压力下不断进行迭代修正。
在如何定义和筛选中期选举选民（Likely Voters）的问题上，业内做法产生了分化：
- **自我陈述法**：仅通过询问“你是否打算投票？热情有多高？”来筛选，往往会产生极度偏向民主党的样本。
- **行为预测模型**：利用往届投票记录等多维数据来建模预测选民到场率，得出的数据对民主党而言则显得更为温和。
- **低投票倾向选民（Low-propensity voters）**：在提前投票数据中，在过去三次选举中投票不超过一次的低倾向选民目前展现出相当明显的民主党倾向。若共和党在投票日当天无法靠传统选民补足这一差距，本次中期选举民调便可能再次出现“低估民主党”的偏差。
正如 Nate Silver 所言：“I think the upshot of the Ann Selzer thing is that everyone knows that a poll is kind of almost like a mini model with polling flavored inputs.”
### [26:26](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1586s) 共和党选情超预期的两种情景与焦点战役
谈到如果选举夜共和党表现优于预期可能会发生什么，Silver 划分了两种不同层面的可能性：
第一种是处于“常规概率分布区间”的普通波动：民主党在所有摇摆席位中以微弱劣势落败。例如詹姆斯·塔莱里科（James Talarico）落后 1 个点，约翰·埃尔齐（John Elsayed / Abdul El-Sayed）因重新计票险胜或落败，夏罗德·布朗（Sherrod Brown）保住席位但其他选区落败。这种情况下，说明红州的党派基本盘依然根深蒂固，民主党只是“在攀爬那座陡峭的红州大山时耗尽了氧气”。
第二种则是“肥尾效应（Fat tails）”驱动的系统性崩盘：若众议院极其焦灼，而民主党在参议院仅勉强拿下北卡罗来纳州一个席位，这种民调偏差达 5 到 7 个百分点的情景将颠覆目前对中期选举机制的所有认知。正如 Nate Silver 所断言：“Like you know we have these in our model these like fat tails that say sometimes polls can be off by five or six or seven points or something crazy right, but that would kind of like defy everything that we think we know about how midterms work.”
在叙事层面，两人重点指出了几场承载极高政治风向标意义的焦点竞选：
- **詹姆斯·塔莱里科（James Talarico）的德州竞选**：不仅检验民主党在传统深红得州的竞争力，更象征着“宗教左翼（Religious Left）”话语体系的回归可能。
- **阿卜杜勒·埃尔-萨耶德（Abdul El-Sayed）**：被视作左翼民粹主义与直面交锋型候选人的关键测试。Klein 提及他在市政厅面对提问者要求其谴责穆斯林兄弟会时，凭借极其出色的辩才将对方驳得体无完肤。这些选区的结果将深刻塑造大选后两党的叙事走向。
### [28:40](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1720s) 民主党党内派系博弈与中期选举叙事
埃兹拉·克莱因（Ezra Klein）首先谈及内特·西尔弗（Nate Silver）近期对民主党内部派系划分的梳理。西尔弗曾将党内力量大致切分为大写左翼（capital L left）、充裕自由主义（abundance libs，克莱因打趣称自己大概属于这一类），以及以知名 Substack 政治历史学者命名、代表“抵制派且反君主集权”倾向的理查森主义（Richardsonism，源自 Heather Cox Richardson）。克莱因好奇除了单纯的胜负之外，大选结果将如何塑造党内的叙事与发展方向。西尔弗指出，11 月 3 日大选有两条极其关键的次级叙事：第一是进步派相对于温和派的表现；第二则是各州选举结果中是否存在“反人工智能浪潮”（AI backlash）的痕迹——比如通过后续的生态回归分析（ecological analysis），若发现在建有大量数据中心的州里共和党得票率普遍落后了 3 个百分点，这将成为重大的政治信号。
谈及进步派的选举叙事时，西尔弗强调，一旦阿卜杜勒·赛义德（Abdul El-Sayed）败选，无论参议院控制权最终花落谁家，“那对进步派而言都将是一个极为糟糕的叙事（that's a very bad narrative for progressives）”。若出现乔斯林·本森（Jocelyn Benson）大赢 9 个百分点而赛义德仅赢 4 个百分点的情况，即便民调极客们能算出赛义德的胜幅低于基准替代水平（wins above replacement），这种精细计算也不会成为公众舆论的主导。西尔弗特别提醒，任何选战中塑造叙事的决定性门槛在于选举夜当晚能否立刻宣告结果：“非专业极客的人通常不会去细究具体的微小分差，只要结果看起来清晰无歧义即可。”
外界此前过度鼓吹的“进步派在初选中横扫一切”的论调与事实脱节。威斯康星州的弗兰切斯卡·洪（Francesca Hong）最终失利；而在得克萨斯州，贾斯敏·克罗克特（Jasmine Crockett）与其说是坚定的进步派，不如说是党派言辞激烈的“重炮手”（partisan bombthrower），她同样输给了詹姆斯·塔拉里科（James Talarico）。克莱因补充指出，克罗克特并非美国民主社会主义者（DSA）成员，政治底色大不相同。西尔弗对此总结道，民主党选民展现出了高度的“理性权衡（rational discretion）”能力——选民并非机械地以胜选几率最大化为唯一准则，而是在进行某种期望值计算：将候选人的胜选概率与其一旦上任后推进核心议题所能带来的边际效益综合考量。在缅因州、密歇根州和威斯康星州的激烈初选尘埃落定后，党内内耗曾短暂回落，但西尔弗警告，随着 2028 年大选初选临近，党派纷争势必再度卷土重来。
- **初选事实检验**：弗兰切斯卡·洪（Francesca Hong）在威斯康星州初选中被否决，贾斯敏·克罗克特（Jasmine Crockett）在得克萨斯州败给詹姆斯·塔拉里科（James Talarico）。
- **选民决策逻辑**：选民在权衡“胜选率（electability）”与“政策推进期望值（expected value score）”之间寻求平衡。
---
### [31:29](https://www.youtube.com/watch?v=uDqR4t5N84o&t=1889s) 民主党“年长千禧一代”明星班底的崛起
跳出具体的战术算计，克莱因提出了一个更为宏观的观察：民主党正迎来一批“年长千禧一代（elder millennial）”的顶尖政治人才。相比之下，晚期婴儿潮（late boomer）以及 X 世代（Gen X）的民主党公职人员，往往尴尬地被卡在新旧政治时代与传播媒介转型的夹缝之中。然而放眼当下的民主党，左翼阵营有扎赫兰·马姆达尼（Zohran Mamdani）、阿卜杜勒·赛义德以及亚历山德里娅·奥卡西奥-科尔特斯（Alexandria Ocasio-Cortez, AOC）；温和派与建制阵营中，罗布·桑德（Rob Sand）在艾奥瓦州州长竞选中遥遥领先，詹姆斯·塔拉里科展现出极强星味，而乔恩·奥索夫（Jon Ossoff）则已成长为耀眼的政治巨星。克莱因认为，这批深谙当今传播逻辑、在奥巴马时期步入政坛、经历特朗普时代洗礼的年轻干部正在跨越派系边界全面接班。
西尔弗借用体育界著名的“斯蒂芬·库里效应（Steph Curry effect）”来打比方：当年库里在没人敢出手的超远距离投三分球，后来全美的高中生都在练超远三分，长大后这批新人把整个大学和 NBA 赛场彻底改变。在当今政坛，这个库里式的原型人物正是巴拉克·奥巴马（Barack Obama）。无论是赛义德、奥索夫，还是被克莱因提名为年长千禧代人才的皮特·布蒂吉格（Pete Buttigieg），都深受奥巴马语言风格与公众表达体系的熏陶。
西尔弗随后剖析了民主党在 2012 年之后的历史性曲折。比尔·克林顿于 1992 年入主白宫，而希拉里·克林顿在 2008 年初选败给奥巴马后，党内到 2016 年却形成了一种“现在该轮到希拉里了”的思维定势。尽管希拉里在与伯尼·桑德斯（Bernie Sanders）的恶战中脱颖而出，但这在某种程度上是将民主党拉回了旧时代，偏离了奥巴马当年试图打造的新型政党轨道。及至 2020 年，当年正是因为年迈且被认为不会构成总统竞争威胁才被奥巴马挑中为副手的乔·拜登（Joe Biden），在全党“避险情绪（flight to safety）”主导下赢得了提名。这一连串的代际更替停滞，使得民主党自身的发展轨迹被硬生生打断；而如今各大派系星光璀璨的局面，则标志着这种代际演进终于重新回到了正轨。
```mermaid
flowchart TD
accTitle: 民主党代际传承与奥巴马效应演进图
accDescr: 展现从克林顿时代到奥巴马新范式，经历2016-2020停滞期，最终迎来千禧一代新星接班的演变历程。
subgraph Origin["政治模版奠基"]
BO["巴拉克·奥巴马 (Barack Obama)<br/>'斯蒂芬·库里'式破局者"]
end
subgraph Interruption["代际轨道中断期 (2016-2024)"]
HRC["2016年: 希拉里·克林顿<br/>回归传统政治框架"]
JB["2020年: 乔·拜登<br/>避险情绪下的过渡选择"]
end
subgraph NewTalent["年长千禧一代新星班底崛起"]
Left["左翼代表:<br/>AOC / 阿卜杜勒·赛义德 / 扎赫兰·马姆达尼"]
Mod["中温和代表:<br/>乔恩·奥索夫 / 詹姆斯·塔拉里科 / 皮特·布蒂吉格"]
Gov["地方执政代表:<br/>罗布·桑德 (艾奥瓦州)"]
end
BO -->|"打断自然进化"| Interruption
Interruption -->|"代际恢复 / 新生代成型"| NewTalent
```
---
### [34:30](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2070s) 众议院席位分布、选区重划与佛罗里达的彻底翻红
两人的对话随即从参议院转向众议院。克莱因指出，参议院选举因席位稀少、明星候选人特色鲜明，犹如中期选举中引人瞩目的“魅力旗舰（charismatic megafauna）”；但众议院并非非黑即白的二元胜负，民主党最终拿下 228 席、235 席还是 250 席，对后续实际执政有着根本性的差别。西尔弗解释称，选区重划（redistricting）与选民自我聚居隔离（voter self-sorting）的最直接后果，就是当今政坛的摇摆选区（swing districts）数量大幅萎缩。尽管其模型测算出民主党有超过 90% 的概率夺回众议院，但在平均预测值下，这仅仅对应净增约 22 个席位，远不及 2010 年共和党狂揽 63 席或 2018 年民主党拿下 41 席的传统“选民海啸（wave election）”。
针对选区版图的变化，西尔弗进行了细致解构：
- **南部重划**：共和党在路易斯安那、阿拉巴马及田纳西等州直接抹除了少数族裔占多数的选区，直接剥夺了民主党约 3 个稳固席位（尽管阿拉巴马的个别选区在民调中依旧紧咬）。
- **得克萨斯州**：共和党曾自信地认为低收入拉美裔选民已大幅右倾，因而画出了更激进的地图；但最新民调显示，这部分选民正急速回流民主党，使共和党原本的如意算盘落空。
- **佛罗里达州**：州长罗恩·德桑蒂斯（Ron DeSantis）主导绘制了极其进取的版图，专为总统大选年设计。西尔弗特别分析了这片政治版图的风险：“在德桑蒂斯画出的这幅图景中，很多选区属于‘摇摆至微偏共和党’，在如今这样的中期选举大环境下其实脆弱不堪。”
谈及佛罗里达从全美标杆性摇摆州彻底沦为“比得州更坚固的共和党堡垒”，克莱因追问这背后的根本动因。西尔弗将此归结为“75% 归因于人口迁徙，25% 归因于佛州民主党自我强化的死亡螺旋”：
> “从人口迁徙来看，佛罗里达是一个独一无二的地方，它能提供蓝州的优质生活设施，但没有那么多自由派（Florida is a unique place in offering blue state amenities, but without as many libs）。”
这种环境不仅持续吸引退休养老群体，还促成了强烈的政治自我筛选。在全美大多数州（尤其是宾夕法尼亚等中西部铁锈带），选民重新出现民主党注册人数反超共和党的势头，打破了过去四五年的颓势；唯独佛罗里达在选民注册层面上继续深红化。最后，克莱因提出核心疑问：在当前极度紧绷的选区结构下，历史常见的 2 至 4 个百分点的民调系统性误差是否会引发连锁反应？一旦民主党选情实际表现超额 3 个百分点，那些原本精心重划的选区是否会全盘崩盘，从而将一场微弱的胜利直接催化为净胜 40 席以上的超级选举海啸？西尔弗与克莱因的推演由此拉开帷幕。
### [38:44](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2324s) 席卷红州的蓝色浪潮与特朗普及弱质候选人的困境
内特·西尔弗（Nate Silver）指出，一旦中期选举掀起巨大的“蓝色浪潮”，其海洋海啸般的冲击力就会彻底淹没那些毫无防备的候选人。以堪萨斯州参议员罗杰·马歇尔（Roger Marshall）为例，西尔弗提到自己在堪萨斯州欧弗兰帕克（Overland Park）有家人深入参与当地政治，直言“马歇尔是个非常糟糕的候选人”。尽管堪萨斯州传统上是深红州，但一旦遭遇风潮（该州此前就曾选出民主党籍众议员莎丽斯·戴维斯（Sharice Davids）），马歇尔这类候选人就岌岌可危。埃兹拉·克莱因（Ezra Klein）随即补充了唐纳德·特朗普（Donald Trump）在公开场合为其辩护的荒诞一幕：特朗普为马歇尔强行向患者追讨欠款辩护，声称法律强制他必须严厉讨债，甚至在辩解中不自觉地使用了带有反犹色彩的词汇，称外界把他描绘成了“夏洛克（Shylock）式的人物”。
```mermaid
flowchart TD
accTitle: Midterm Dynamics Under Trump
accDescr: Flowchart illustrating the interplay between Donald Trump's presence, candidate quality, and the broader macro risks impacting the GOP midterm chances.
subgraph TrumpDilemma["特朗普的选票效应悖论"]
T1["特朗普亲自在选票上"] -->|"激发低投票倾向/不理会民调的铁杆选民"| TWin["大幅提振选情"]
T2["特朗普未在选票上（中期/补选）"] -->|"普通候选人无法动员其铁杆"| TLoss["共和党连遭惨败（2018/2022/特别选举）"]
end
subgraph MacroPressures["宏观与政策压力"]
M1["伊朗冲突引发油价飙升"]
M2["重度押注AI数据中心与科技金主"]
M1 --> Approval["支持率持续走低（跌破40%区间）"]
M2 --> Risk["金融与地缘政治脆弱性加剧"]
end
TrumpDilemma --> Result["深红州脆弱候选人（马歇尔/帕克斯顿）面临灭顶之灾"]
MacroPressures --> Result
```
克莱因进一步质疑特朗普是否真的在乎共和党能否守住国会，因为他主要依赖行政权力施政，在立法层面并无太多大动作。在得克萨斯州，如果特朗普在初选期间介入支持约翰·科宁（John Cornyn），共和党保住参议院的把握会大得多；但他不仅没有这么做，反而让肯·帕克斯顿（Ken Paxton）这种极具争议的人物上位。特朗普的中期选举理论极其自我中心：他办了一场古怪的中期选举大会，认定共和党会输完全是因为“他本人没有出现在选票上”，甚至开出“若共和党获胜将向每位美国人发放5000美元支票”的荒诞空头支票来公开贿赂选民。克莱因尖锐地指出，特朗普只愿意在一种情况下赢下中期选举——那就是胜利必须归功于他个人；如果赢球的前提是给共和党人腾出空间、与他保持距离并支持他不喜欢的建制派候选人，他宁可不赢。
- 特朗普公开为罗杰·马歇尔向患者追债辩护，称其为遵纪守法的好人，并反驳外界将其打成“夏洛克（Shylock）”式贪婪放贷者的指控。
- 埃兹拉·克莱因断言：“特朗普的中期选举理论似乎就是：共和党可能会输，完全是因为他自己没在选票上；只要大家表现得好像他在选票上，共和党就会没事。”
- 特朗普曾提出激进的中期选举口号，承诺若共和党获胜，将给每位美国人直接发放5000美元支票。
### [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) 特朗普支持率滑坡与选民动员的“魔术把戏”失效
西尔弗分析认为，共和党在特朗普作为主导政治人物却未亲自出现在选票上的选举中（如2018年中期选举、2022年部分选举、佐治亚州两次决选以及多场特别选举与最高法院竞选），往往处于极其尴尬的进退维谷之境，其战绩几乎全线溃败。特朗普唯一的政治绝技，就是动员那些平时政治冷漠、不愿回应民调或被民调归类为“不太可能投票”的边缘选民，让他们在自己参选时“爬过玻璃渣也要去投票”。然而，当特朗普本人不在选票上时，这批选民绝不会为了罗杰·马歇尔或肯·帕克斯顿去爬玻璃渣。
更关键的宏观背景在于，如果特朗普没有主动卷入与伊朗的战争并将汽油价格推高至每加仑4.5美元以上（在加州等地甚至更高），民主党根本不可能在参议院处于如此有利的争夺态势。谈到特朗普第二任期内民调支持率的急剧走低，西尔弗指出，虽然其支持率在2025年4月围绕关税担忧的“解放日（Liberation Day）”期间曾出现断崖式下跌，但总体而言，这一走势与油价和经济焦虑呈现出高度的相关性与持续衰退轨迹。
在第一任期的前三年，相对强劲的客观经济表现像一层神圣光环掩盖了特朗普的种种行径，让选民对民主党关于民主、种族与排外的攻击不屑一顾（“你的工资涨了，有体面工作，股市上涨，房子升值”）；但一旦这些基本经济支撑动摇，文化战争的口水仗就显得极度歇斯底里且苍白无力。加之特朗普自2015年年中以来统治美国政治已逾十年，如今已年满80岁，公众已产生强烈的疲劳感。
- 内特·西尔弗直言：“特朗普唯一的魔术把戏，就是能让某种平时对政治冷漠的选民在他亲自在选票上时，哪怕‘爬过玻璃渣’也要跑去给他投票；但那些人绝不会为了罗杰·马歇尔或肯·帕克斯顿去爬玻璃渣。”
- 特朗普第二任期支持率的持续下滑与汽油价格飙升及关税通胀焦虑高度吻合。
- 政治疲劳与高龄问题显现：特朗普自2015年起主导美国政治舆论，至本届任期步入80岁高龄，重演了拜登此前遭遇的衰老舆论危机。
### [44:36](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2676s) AI狂潮、埃隆·马斯克注资与“跛脚鸭”末期的全局性风险
针对西尔弗提出的疑问——为何特朗普会在数据中心这种高达80%对20%遭遇公众反感的民粹逆风议题上坚定站台，克莱因给出了两层深层解读：其一，特朗普深信美中之间正在进行一场决定地缘霸权的AI军备竞赛（“谁赢了AI，谁就赢了一切”）；其二，AI热潮推高了股市，而股市是特朗普目前手中唯一拿得出手的经济遮羞布。一旦AI泡沫破裂或资本情绪逆转，高利率、巨额国债、乏力的经济增长将全面暴露，他将彻底一无所有。此外，AI科技高管和埃隆·马斯克（Elon Musk）为特朗普投入了海量政治资金，马斯克一人就砸下了4亿多美元，几乎是以一己之力在为共和党的中期选举买单。
西尔弗赞同这一判断，指出唯一能真正刺痛特朗普神经的就是看到股市大盘飘红下跌。然而，市场对AI泡沫的焦虑正日益加深，投资者都在苦思如何在没有成熟安全参照系且跑道极其狭窄的情况下实现软着陆。叠加中东油价持续震荡，大选最后阶段若出现市场暴跌，将直接摧毁特朗普的最后防线。
克莱因回顾了小布什（George W. Bush）在2006年中期选举后的“超级跛脚鸭”执政期，指出其最后两年极其动荡并最终以全球金融海啸收尾。审视当前特朗普执政中期的局势，克莱因直言地缘政治、宏观经济与前沿技术充斥着巨大系统性风险：
“我看着特朗普，看着眼下的经济与地缘政治局势，我看到的是无处不在的风险。”
无论是乌克兰战事失控、美伊或以伊冲突全面外溢、突发的金融危机，抑或是AI集群引发的技术失控与地缘打击，一旦在一名即将年满82岁、缺乏民意信任与施政合法性的“跛脚鸭”总统任期末尾集中引爆，政府将完全丧失应对危机的公信力与调控筹码。
- 埃隆·马斯克（Elon Musk）个人向共和党中期选举投入了超过4亿美元的巨额政治资金，成为实质上的单一最大金主。
- 数据中心在民意中属于典型的极度不受欢迎议题（约80%反对、仅3%支持加速AI发展，约60%希望放缓），但特朗普为守住股市和科技金主利益全力背书。
- 埃兹拉·克莱因警示：“如果这几年发生大规模经济衰退、股市回调或是系统性金融危机，完全在情理之中；世界充满了风险，而跛脚鸭总统一旦遇到事情在眼前彻底引爆，他们将几乎没有任何权力或公众公信力去力挽狂澜。”
### [48:53](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2933s) “唯唯诺诺者”内阁与跛脚鸭任期的失控风险
Ezra Klein 与 Nate Silver 谈及特朗普第二任期的执政危机，指出当前局势与拜登政府时期截然不同——在拜登任内，乌克兰危机与加沙冲突是在其任期内爆发的外部事件，而当下的危机则完全是白宫自身主动决策的结果。Silver 尖锐地指出，如果共和党在中期选举中丢掉参议院，国防部长皮特·海格塞斯（Pete Hegseth）应当是首当其冲被问责的人之一，因为几乎没有哪个称职的国防部长会认为在战争计划与战略目标极其模糊的情况下与伊朗开战是个好主意。Klein 则进一步点破了这层权力关系的本质：其实是特朗普与内塔尼亚胡铁了心要对伊朗开战，而特朗普挑选前《Fox & Friends》主持人海格塞斯执掌五角大楼，本质上就是想要一个“在任何情况下都绝不对他说‘不’”的传声筒。
```mermaid
flowchart TD
accTitle: 特朗普第二任期决策闭环与风险放大机制
accDescr: 展示特朗普清除建制派制衡后，周围充斥听话官员导致的地缘与经济连锁风险。
subgraph Personnel["决策人事结构"]
A["唐纳德·特朗普"] -->|"任命绝对服从者"| B["唯唯诺诺者内阁<br/>（如防长皮特·海格塞斯）"]
C["首任期制衡力量<br/>（吉姆·马蒂斯 / 加里·科恩）"] -.->|"彻底出局 / 无法回归"| A
end
subgraph Shocks["连锁危机爆发"]
B --> D["鲁莽地缘决策<br/>（对伊开战 / 模糊战争目标）"]
B --> E["激进经贸与科技政策<br/>（全面关税 / 对华摩擦）"]
end
subgraph Outflow["系统性崩溃隐患"]
D --> F["油价暴涨与经济重创"]
E --> F
F --> G["特朗普被逼入绝境<br/>进入扑克式'高倾斜（Tilt）'狂躁状态"]
end
```
Klein 强调，尽管海格塞斯在中期选举后极有可能被撤职，但他绝不可能被吉姆·马蒂斯（Jim Mattis）那样有威望、敢抗命的沉稳将领所取代；正如首任国家经济委员会主任、前高盛总裁加里·科恩（Gary Cohn）在世也绝不会容许当下的极端关税体系落地一样，特朗普如今只允许身边留下顺从者。如果股市因 AI 尚未成熟或过于危险而陷入自由落体，抑或中美爆发直接对抗，地缘政治灾难将以摧枯拉朽之势传导至宏观经济。Klein 担忧，当一位年过八旬、身边全是一群海格塞斯式弄臣的总统在任期最后两年被彻底逼入政治绝境时，极可能陷入扑克术语中所说的“高倾斜（Tilt）”狂躁状态，采取极其非理性的险招。Silver 对此深感焦虑，坦言一想到科技正迎来几十年未有的剧烈变革、整个社会可能在三五年内天翻地覆，而掌舵的却是一位八十二岁高龄的特朗普，就让人不寒而栗。
- “Like I think it's very likely he pretty quickly gets the axe after the midterms or at some point. But he's very unlikely to be replaced by a like a thoughtful commanding general who has the personal stature to say no to Donald Trump.” —— Ezra Klein 谈及防长海格塞斯即便被炒，也绝不会换上敢于制衡特朗普的将领。
### [51:48](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3108s) 竞选资金的边际递减与 2026 预测模型对撞直觉
随着大选进入收官阶段，针对埃隆·马斯克（Elon Musk）的资金注入及大选末期金钱效应的讨论，Silver 提出了审慎的反共识观点：在政治竞选中，金钱的作用通常被严重夸大了。在高关注度的选举（如参议员、州长乃至总统竞选）中，资金迅速遭遇边际收益递减法则；唯有在众议院边缘选区或知名度严重匮乏的州议会选举中，资金才能产生决定性效用。尤其是如今各州选区划分近乎每两年就要重画一次，州议会控制权变得尤为关键。此外，资金的来源属性极为关键：选民小额捐款购买广告不仅单价更低，而且能在竞争尚不激烈的早期锁定低费率；反观共和党眼下依赖企业与党派资金堆积出的账面优势，由于购买费率畸高，在实际触达选民的广告曝光量上，双方其实仅仅打成了五五开。
回顾 2024 年大选前夕，Silver 曾发表过一篇备受争议的文章，公开声明“我的模型预测卡玛拉·哈里斯获胜，但我的直觉告诉我唐纳德·特朗普会赢”。当 Klein 追问今年其直觉与模型是否存在背离时，Silver 坦承，行业（民调机构与预测专家）若是再次在铁锈带中西部低估共和党，将会蒙受巨大的声誉耻辱，这种心理防御机制让他直觉上对堪萨斯州或爱荷华州等深红州的民主党领先优势抱有一丝怀疑。然而，与 2024 年他能列出二十一条特朗普利好、却只能凑出四五条哈里斯优势的局面截然相反，如今的宏观基本面对共和党而言堪称灾难。
| 宏观维度 | 2018 年中期选举（共和党惨败） | 2026 年当前中期选举环境 |
|:--- |:--- |:--- |
| **执政者状态** | 处于首任期，相对年轻，民调支持率尚可 | 80 岁高龄的第二任期总统，支持率全面垮塌 |
| **宏观经济感知** | 选民对整体经济基本面感知较为优良 | 4.5 美元高油价、关税重创市场与衰退恐慌 |
| **地缘与突发丑闻** | 尚无直接陷入大规模局部战争 | 陷入伊朗战火、白宫腐败争议与爱泼斯坦案余波 |
| **在野党候选人质量** | 呈现传统中期选举的反弹动能 | 民主党推选出一大批极具竞争力的新生代温和派人才 |
Silver 指出，如果说特朗普在年轻、更受欢迎且经济更强劲的 2018 年尚且遭遇了惨烈的中期选举溃败，那么在眼下内外交困的死局中，共和党的选情理应比当年更加恶劣。若这一逻辑完全兑现，民主党在全国众议院普选票上的领先优势可能达到惊人的 10 到 11 个百分点。因此，他目前的内心是矛盾的：他并不担心全国大盘的民调校准失真，反而更担心那些深红州的个别民调是否存在偏差。
- “The fundamental conditions feel terrible for Republicans, right? You have the second-term 80-year-old president who had a bad midterm when he was younger and more popular and the economy was perceived as better in 2018.” —— Nate Silver 论证 2026 年共和党所面临的政治基本面远比 2018 年更为恶劣。
### [54:50](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3290s) 嘉宾终极书单推荐：从经济史到牌手心智
节目尾声，依照《The Ezra Klein Show》的传统惯例，Klein 邀请 Silver 为听众推荐三本著作。Silver 打趣称自己是节目的忠实听众，原本挑好的许多书已经被其他嘉宾捷足先登，因此他特意遴选了三本风格略显清奇、但影响深远的冷门经典：
第一部是经济史学家罗伯特·戈登（Robert J. Gordon）于 2016 年出版的巨著《美国增长的起落》（*The Rise and Fall of American Growth*）。Silver 回忆自己不久前在巴黎参加扑克锦标赛时翻读此书，彼时恰逢美伊爆发战争、美国国防部与 Anthropic 人工智能实验室激烈交火，巴黎那种超越时间的古典静谧感与外部世界疯狂加速的技术狂飙形成了魔幻的对照。戈登的核心论点表明，美国最具颠覆性的经济与生产力飞跃其实集中在 1870 年至 1970 年之间；当前鼓吹 AI 的乐观派往往以“工业革命最终提升了人类寿命与财富”为由进行辩护，却遗忘了工业革命在最初的数十年间曾带来极度野蛮恶劣的生存环境——狄更斯笔下的贫民窟童工，以及满街堆积、缺乏室内排污系统的马粪海。该书深刻揭示了许多无法被 GDP 简单度量的社会质变，也印证了欧洲放弃部分 GDP 增速以换取更高生活品质的发展路径。
第二部是凯特·霍尔（Cate Hall）所著的个人成长心智类书籍《你可以直接去做》（*You Can Just Do Things*）。作者曾是全球顶尖的女性职业扑克玩家，也是 Silver 在牌圈的同行旧友。她在巅峰期曾深陷毒瘾沉沦数年，随后戒毒重返湾区工作。Silver 评价这是一本为特定“书呆子（Nerd）”群体量身打造的极客版认知指南，通篇贯穿对“主体性（Agency）”的极致强调。全书核心探讨了人们在人际交往中因过度担忧场面尴尬而无法直率表达诉求的通病，主张只要敢于进行坦诚透彻的沟通并接受真实反馈，人生境遇就会迎来巨大改观。
第三部则是被 Silver 誉为有史以来最优秀的扑克文学经典——英国文学评论家兼诗人阿尔·阿尔瓦雷斯（Al Alvarez）在 1983 年撰写的《城中最大牌局》（*The Biggest Game in Town*）。作者带着纯正的英式文学笔触深入拉斯维加斯荒漠，记录了世界扑克大赛（WSOP）初创时期的风云变幻，以极富质感的笔触勾勒出得克萨斯路边赌场老派赌徒群像，是一部篇幅精悍但文学造诣极高的传世之作。
- “Gordon's book talks about a couple of things. One the thesis which is implied by the title is that actually the huge gains that the United States made came between like roughly 1870 and 1970.” —— Nate Silver 阐述推荐罗伯特·戈登著作的核心论点。
### [58:20](https://www.youtube.com/watch?v=uDqR4t5N84o&t=3500s) 赌博文学的真实质感与对谈尾声
内特·希尔弗（Nate Silver）在为本期节目推荐图书时，特别分享了一本关于博彩世界的作品。他坦言，这本书虽然带着某种“杂志专稿式的风格”（magaziney way），但描写的那个世界对他而言具有极其重要的意义。在他看来，市面上绝大多数描写赌博的读物往往都会落入陈词滥调，充斥着老套的戏剧冲突与刻板印象，而这本书却是极少数能真正跳出俗套、精准捕捉到那个令他深感着迷的圈子与真实质感的作品。正如希尔弗所评价的那样：“And it's one of the few books about gambling that doesn't fall into cliches and captures this part of the world that I'm fascinated by very well.”
埃兹拉·克莱恩（Ezra Klein）随即称赞这本书听起来非常精彩，并对希尔弗的做客与深度剖析表达了诚挚的感谢，说道：“Nate Silver, thank you very much.” 希尔弗也回应致谢，整期围绕中期选举预测、民调机制、两党前景以及政治风险的深度对话在片尾音乐中圆满落幕。
## Notable quotes
> [04:13](https://www.youtube.com/watch?v=uDqR4t5N84o&t=253s) 如果你回顾美国选举的历史，就会发现美国选举中最规律的趋势——也是几十年来极少数依然成立的规律之一——就是执政党必定会在中期选举中遭遇选民的反弹。 — 内特·西尔弗
> [41:19](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2479s) 特朗普唯一的魔术把戏，就是能让某种平时对政治冷漠的选民在他亲自在选票上时，哪怕‘爬过玻璃渣’也要跑去给他投票；但那些人绝不会为了罗杰·马歇尔或肯·帕克斯顿去爬玻璃渣。 — 内特·西尔弗
> [01:46](https://www.youtube.com/watch?v=uDqR4t5N84o&t=106s) 如果选举结果大致如民调所示，那么我认为在某种程度上，这将标志着特朗普时代的终结。 — 内特·西尔弗
> [06:44](https://www.youtube.com/watch?v=uDqR4t5N84o&t=404s) 在其他条件相同的情况下，至少在像密歇根这样的摇摆州，温和派候选人会比进步派表现得更好。 — 内特·西尔弗
> [44:36](https://www.youtube.com/watch?v=uDqR4t5N84o&t=2676s) 我看着特朗普，看着眼下的经济与地缘政治局势，我看到的是无处不在的风险。 — 埃兹拉·克莱因
## Mentioned
唐纳德·特朗普, 内特·西尔弗, 埃兹拉·克莱因, 乔·拜登, 卡玛拉·哈里斯, 苏珊·柯林斯, 罗伊·库珀, 肯·帕克斯顿, 詹姆斯·塔拉里科, 玛丽·佩尔托拉, 乔斯林·本森, 阿卜杜勒·埃尔-萨耶德, 特洛伊·杰克逊, 查克·舒默, 基尔斯滕·吉利布兰德, 谢罗德·布朗, 乔恩·奥索夫, 丹·奥斯本, 佩吉·弗拉纳根, 蒂娜·科特克, 凯西·霍楚尔, 蒂姆·沃尔兹, 约翰·费特曼, 穆罕默德·奥兹, Ann Selzer, 扎赫兰·马姆达尼, 亚历山德里娅·奥卡西奥-科尔特斯, 罗布·桑德, 皮特·布蒂吉格, 巴拉克·奥巴马, 希拉里·克林顿, 比尔·克林顿, 伯尼·桑德斯, 罗恩·德桑蒂斯, 贾斯敏·克罗克特, 弗兰切斯卡·洪, 罗杰·马歇尔, 埃隆·马斯克, 皮特·海格塞斯, 本雅明·内塔尼亚胡, 吉姆·马蒂斯, 加里·科恩, 罗伯特·戈登, 凯特·霍尔, 阿尔·阿尔瓦雷斯, Silver Bulletin, Still Counting, On the Edge: The Art of Risking Everything, The Rise and Fall of American Growth, You Can Just Do Things, The Biggest Game in Town, 民主党全国委员会, 参议院民主党竞选委员会, Anthropic, 美国民主社会主义者
## Video description
“If the election goes roughly as the polls say it will go, then in some ways it would mark the end of the Trump era,” Nate Silver told me.
The midterms are a week away, and it looks entirely possible that Democrats will win not just the House, but also the Senate. Democrats are polling competitively deep into red territory – Texas, Ohio, Alaska, Iowa, Kansas – states that Trump won in 2024 by double digits.
But Democrats have been burned by big polling misses before. So can we really trust what the polls are telling us? And what stories have emerged in the data that we might see play out on election night?
Silver is an internationally famous elections nerd, one of the people who made election forecasting a core part of American political discourse. He edits The Silver Bulletin on Substack, co-hosts the podcast “Still Counting” and is the author, most recently, of “On the Edge: The Art of Risking Everything.”
[00:00:00] Intro
[00:09:40] Are Democrats overperforming in red states?
[00:13:07] Does moderation win elections?
[00:26:32] What if Republicans have a better night?
[00:30:05] The Democratic Party's new talent
[00:42:26] Trump's declining approval rating
[00:48:48] Risks in Trump's lame duck term
[00:51:48] Money's impact & election predictions
[00:54:50] Book recommendations
Read the full transcript here: https://www.nytimes.com/2026/10/27/opinion/ezra-klein-podcast-nate-silver.html
Watch more on @EzraKleinShow
Thoughts? Guest suggestions? Email us at ezrakleinshow@nytimes.com.
You can find transcripts (posted midday) and more episodes of “The Ezra Klein Show” at nytimes.com/ezra-klein-podcast. Book recommendations from all our guests are listed at https://www.nytimes.com/article/ezra-klein-show-book-recs.html
[Source](https://www.youtube.com/watch?v=uDqR4t5N84o)
[9:52] Nate Silver: The one group you do not want to rely on to turn out in a midterm is usually young men.
[0:00] Nate Silver: If the election goes roughly as the polls say it will go, then in some ways it would mark the end of the Trump era, I think.
[41:19] Nate Silver: Republicans are kind of caught between a rock and a hard place in elections where Trump himself is the dominant figure but not himself on the ballot.
[47:12] Ezra Klein: I look at Trump and I look at the economy and I look at the geopolitical situation and what I see is risk everywhere.
Original transcript
[0:00] We are a week out from the midterm
[0:01] elections and something that looked
[0:03] almost impossible a year ago has
[0:06] happened. There is a path for Democrats
[0:08] to win not just the House but the
[0:10] Senate. So a Senate majority for
[0:12] Democrats to to sort of recap this. They
[0:15] need to defend the competitive Senate
[0:16] seats they currently hold. And then they
[0:19] need to flip at least four seats in
[0:22] states currently held by Republicans. A
[0:24] couple of those states had always looked
[0:26] possible, but then came the hard ones
[0:28] states where Trump had won by double
[0:30] digits. People weren't really talking
[0:32] about Kansas, but now [music] Kansas.
[0:35] And the remarkable thing about this
[0:37] cycle is that Democrats are polling
[0:39] competitively in all of them. In a
[0:42] handful of those races, they're actually
[0:43] far ahead.
[0:45] And so, I think the question is, can we
[0:48] trust these polls?
[0:50] What can we really say about where the
[0:53] election stands just a week before the
[0:56] vote? To talk about all this, I want to
[0:59] have Nate Silver on the show. Nate, of
[1:01] course, is, you know, internationally
[1:02] famous elections nerd.
[1:04] >> The polling guru Nate Silver,
[1:06] >> he predicted [music] every state in the
[1:08] last presidential election.
[1:10] >> Heavy is the head that wears the crown.
[1:12] Silver.
[1:13] >> Absolutely.
[1:14] These days he edits a silver bulletin on
[1:16] Substack which puts out a ton of great
[1:19] analysis, polling, and election
[1:21] forecasts. He co the podcast still
[1:23] counting. Trump's approval rating is now
[1:25] lower than it was uh after January 6th
[1:29] when he was
[1:30] >> I didn't realize that.
[1:31] >> No, it's it's you know it's as low as
[1:32] it's ever been.
[1:33] >> And he's the author of most recently on
[1:35] [music] the Edge: The Art of Risking
[1:37] Everything. Nate joins me now.
[1:43] >> [music]
[1:46] >> Nate Silver, welcome back to the show.
[1:47] >> Hey, Ezra. How are you, man?
[1:49] >> I'm good. I I wanted to ask I didn't
[1:51] follow up when you said this to me a
[1:52] second ago cuz I want to do it on air.
[1:53] [laughter]
[1:54] You said to me, looking a little far
[1:57] away in your eyes, that this election
[1:59] feels momentous to you. I've known you a
[2:01] long time. You don't usually say things
[2:02] like that. So, what feels momentous? If
[2:05] the election goes roughly as the polls
[2:08] say it will go, then in some ways it
[2:10] would mark the end of the Trump era, I
[2:14] think. [laughter]
[2:15] Um, he'll still be president for two
[2:17] more years. Um, but the minute the
[2:20] election, the votes are counted might
[2:22] take a while because of Alaska and
[2:24] California and states like that, the
[2:26] 2028 election campaign begins and if
[2:27] Trump has a bad night, as polls show,
[2:29] then he's a super lame duck, right? You
[2:33] might draw an analogy to um to Bush
[2:35] after 2006.
[2:37] Um and like part of what people
[2:41] understandably are having trouble
[2:42] believing in the polls. It kind of looks
[2:44] like a different regime, right? Where
[2:46] Kansas is competitive, Texas is
[2:48] competitive, potentially gains for
[2:50] Democrats deep into Republican
[2:52] territory. But maybe we're on the verge
[2:53] of something different between
[2:55] generational turnover,
[2:57] between Trump being threequarters of the
[2:59] way through his two constitutionally
[3:01] provided for terms and um and with AI
[3:05] looming too. It's not quite clear to me
[3:07] how big an issue AI is in this election.
[3:09] I think maybe more than people assume,
[3:11] but um but it could be the biggest issue
[3:13] of 2028. I think I think you might
[3:15] expect it to be along with the economy
[3:16] the biggest issues of 2028. I was
[3:18] thinking as you said some of that about
[3:21] the conversations I had about the
[3:22] election a year ago.
[3:23] >> Yeah.
[3:23] >> And a year ago the conversation was
[3:26] Democrats will probably win the House
[3:30] and the Senate. I mean never say never.
[3:33] >> Yeah.
[3:33] >> But no. And the the the reason was that
[3:38] to win back the Senate, Democrats were
[3:39] going to need to win in a number of
[3:43] places where Trump had won by more than
[3:45] 10 points. And given everything we know
[3:47] about partisanship in modern America,
[3:50] that wasn't going to happen. So, you
[3:53] know, when we're talking, it's about 2
[3:55] weeks before the election right now,
[3:56] it'll be less by the time this airs,
[3:59] Democrats are at a 70 plus% chance of
[4:02] winning the Senate in your model. And
[4:04] not just winning the Senate, but
[4:05] possibly winning like beyond that
[4:08] despair.
[4:11] >> Why? What happened?
[4:13] So, I think a couple of things happened
[4:15] and some of them have to do with
[4:17] expectations maybe being miscalibrated.
[4:19] Um, you know, after 2024, there was talk
[4:22] of a I guess permanent conservative vibe
[4:26] shift. Um, that Democrats were on their
[4:28] back heels and Biden had failed and
[4:31] wokeness.
[4:32] >> That was dumb. The idea they'd be
[4:33] permanent.
[4:34] >> Yeah. [laughter] And but if you look at
[4:35] the history of American elections, then
[4:36] the most regular trend in American
[4:38] elections, one of the few things that
[4:39] survives for decades is there is a
[4:42] backlash against the president's party
[4:43] at the midterm. Maybe a little bit
[4:45] bigger if a president is in his second
[4:47] kind of lame duck term, but you know, we
[4:50] can recite the exceptions on one hand.
[4:51] 1998 um after Monica Lewinsky, 2002
[4:55] after September 11th, that's about it.
[4:56] 2022, Biden had a relatively gentle
[4:59] thumping in the midterm compared to what
[5:01] you might expect based on his approval
[5:02] rating. Um so you know look in the
[5:06] average midterm the environment shifts
[5:08] by seven and a half points against the
[5:09] president's party versus the previous
[5:11] presidential year. Um this year it looks
[5:14] more like 11 points. But why is 11
[5:18] points important? Well um there are all
[5:20] these states like you said that Trump
[5:21] won by 10 11 12 13 points right? Ohio I
[5:26] think he won by 11 points. Um, so if you
[5:29] have an 11-point swing and it's fairly
[5:30] uniform, all of a sudden Ohio becomes a
[5:33] tossup. Um, what I think wasn't so clear
[5:36] is that Democrats have actually
[5:37] nominated in most important races pretty
[5:40] good candidates and or lucky enough to
[5:42] face weaker Republican candidates,
[5:44] right? Um, I'm not sure if James Talico
[5:47] is everybody's cup of tea, but like um,
[5:50] you know, he is able to take advantage
[5:51] of Ken Paxton's many sins so forth,
[5:54] right? Um, in North Carolina, Roy Cooper
[5:57] was a strong recruit from Schumer and
[5:59] Company. Um, you know, Democrats have
[6:02] the strategy now of trying to nominate
[6:04] independents and kind of name only in
[6:07] states like Nebraska. I think both the
[6:08] candidates, Republican and the Democrat,
[6:09] are strong in Iowa, for example. Um,
[6:12] but, you know, I would say that probably
[6:14] the candidate intangibles. um you know
[6:17] they might move things by five points at
[6:20] most but you kind of do the math and
[6:22] you're like okay well Texas is a Trump
[6:24] plus 13 state the parson climate moves
[6:26] 11 points toward Democrats so now it's R
[6:28] plus two and then is Ken Paxton below
[6:31] average enough to turn R plus2 into D
[6:33] plus2 well that's the math right and
[6:35] that's kind of that's a logical enough
[6:38] story so one question that raises for me
[6:43] is
[6:44] Schumer and his team, [snorts] the
[6:46] Democratic Senatoral Campaign Committee.
[6:48] It's under Christian Gillibrand right
[6:50] now. They looked pretty bad a couple
[6:53] months ago and they looked pretty bad
[6:54] primarily because a focus was on the
[6:57] fight that they waged and lost in Maine
[7:00] to make Janet Mills the nominee and
[7:02] instead it was going to be Graham
[7:03] Planner. Graham Platner imploded.
[7:05] >> Yeah.
[7:06] >> Uh Troy Jackson, who's the Democratic
[7:09] nominee now, you know, is ahead of Susan
[7:12] Collins by a bit. I think people are
[7:13] nervous about that race because Collins
[7:14] tends to outperform her polling and it's
[7:16] not that, you know, wide of a gap.
[7:20] But if you're looking over the the range
[7:23] of states, do they look pretty good? I
[7:25] mean, Turk in Iowa, you know, Pollah and
[7:28] in Alaska, Roy Cooper, right? It seems
[7:31] like
[7:31] >> Pela is a big one. I'm not sure that an
[7:33] average Democrat would be in a toss up.
[7:35] She's, you know, a slight favorite in
[7:36] that race, actually. Um,
[7:38] >> look, yeah, you have these big fights in
[7:40] Maine and Michigan. I I would share
[7:42] Democrats concern about Maine a little
[7:45] bit. I mean, that's based on
[7:47] nothing but just the fact that Susan
[7:49] Collins beat her polls by like literally
[7:50] like nine points in the last election.
[7:51] There's a whole argument about how
[7:52] persistent polling error is. We tend to
[7:55] assume that it's not, but um that's one
[7:58] race where the polls have gotten maybe
[7:59] closer by a point or two. There hasn't
[8:01] been a lot of polling in Maine. Um,
[8:03] Michigan. Look, I'm one of those people
[8:05] who says that other things held equal
[8:07] that a moderate can't able do better
[8:09] than a progressive, at least in a purple
[8:11] state like like Michigan, right? Um, and
[8:14] if you compare the governor's race there
[8:16] where Jocelyn Benson is ahead by eight
[8:18] points, Eliad's ahead by three or three
[8:20] and a half or something, right? Again,
[8:22] that, you know, there is a four or four
[8:24] and a half point candidate quality gap.
[8:26] that is again within that range of what
[8:28] we think candidates how much they can
[8:30] matter in an environment like this one
[8:32] right um but um if you have enough wind
[8:36] at your back then you can overcome some
[8:37] of those problems and by the way in in
[8:39] other ways Elsa is a is a good candidate
[8:42] right he's very Michigan in certain ways
[8:44] right he in kind of a zoranesque way um
[8:49] doesn't present I mean he kind of is a
[8:52] bro right it's an interesting contrast
[8:53] to like Franchesco Hong or somebody and
[8:56] there are gendered parts of that
[8:57] comparison too potentially. Um he's also
[8:59] raised a lot of money and money is money
[9:01] is helpful. Um so but yeah I mean
[9:04] Michigan and Maine if Democrats were to
[9:06] lose one of them they'd still have a
[9:09] chance. If they were to lose both then
[9:11] probably game over for a Democratic
[9:13] Senate flip.
[9:15] >> One of the things that has been
[9:16] interesting to me looking at at the
[9:18] polls and and people have comment on
[9:20] this. This is not my original
[9:21] observation. Is it that Democrats seem
[9:23] to be overperforming more in redder
[9:25] states?
[9:26] >> Yes.
[9:27] >> So they look better than you would think
[9:29] in a Texas, a Kansas, an Iowa, maybe
[9:34] like a little bit less good in like a
[9:36] Michigan, a Minnesota, you know, it kind
[9:39] of goes on like in the blue states,
[9:40] right? Is there something to this? And
[9:42] and if so, what do you make of it? Well,
[9:44] that's what I think makes Democrats
[9:47] nervous because it's the red states,
[9:49] especially in the heartland where um the
[9:52] polling over performance has been
[9:53] concentrated in in some of these recent
[9:55] elections. At the same time, the story
[9:59] does make sense on a couple of levels,
[10:01] right? Um number one, gas and diesel
[10:04] prices. Um, if you look at where diesel
[10:07] fuels are consumed, not usually by
[10:09] passenger vehicles, but by agriculture,
[10:11] trucking, petroleum, home heating oils,
[10:14] right, it's all kind of the colder
[10:16] Midwestern states where a lot of the
[10:17] battlegrounds are concentrated as it
[10:18] happens this year. Um, if you believe in
[10:21] kind of a last in first out argument,
[10:24] like what if we are reverting somewhat
[10:28] out of the Trump era? Actually, in 2024,
[10:31] um, for the first time in a while, you
[10:33] had very mild depolarization. Some of
[10:37] the worst states that Democrats had
[10:39] relative to 2020 were like New York and
[10:43] and California. Um, you know, younger
[10:45] voters of color, for example, and
[10:48] younger men in general kind of moved
[10:50] against Democrats. Um whereas you know
[10:53] like relatively speaking if you're
[10:55] really looking in the weeds like Kansas
[10:57] is a state where Harris I think the PVI
[11:00] we call it the gap between that and the
[11:02] national spread declined in Kansas a
[11:04] little bit. Um, so maybe you're having
[11:06] some last in first out where the people
[11:08] that join the Trump coalition like
[11:10] Hispanics, working-class whites, maybe
[11:13] just moving a little bit back in the
[11:16] other direction or maybe just not
[11:17] voting, right? You know, one reason why
[11:19] Trump polls in 24 was overperformance
[11:22] among like young men. The one group you
[11:25] do not want to rely on to turn out in a
[11:26] midterm is usually young men.
[11:28] >> [snorts]
[11:28] >> So I I feel like there's another story
[11:30] you could tell and I'd be curious how
[11:31] this rates for you which is that it
[11:34] actually has to do potentially with
[11:37] candid quality on both sides. So in
[11:40] redder states Democrats have been I
[11:43] would say more rigorously following a
[11:48] view that they need more moderate
[11:50] candidates. So you think of like Adam
[11:52] Hamilton in in in Kansas. Um shared
[11:54] brown is like a longtime populist and
[11:56] you know very well but Roy Cooper in
[11:58] North Carolina. Um John Ov is this like
[12:01] I mean I wouldn't say George is a red
[12:02] state anymore but John Ov is this like
[12:04] relentlessly disciplined figure.
[12:06] Nebraska with Osborne who's actually
[12:08] running as an independent. I wouldn't
[12:09] say Democrats chose him but obviously
[12:11] Democrats are uh aligned I think and
[12:14] excited about his candidacy and didn't
[12:16] run a Democrat um against him. Um, and
[12:18] as you get more into the more
[12:20] traditionally purple or bluer states,
[12:22] uh, you know, Maine, they have nominated
[12:25] like a more left candidate, you know,
[12:26] Jackson replacing Platner, who is also a
[12:28] more left candidate. Obviously, Abdul
[12:30] sayed in Michigan, the more left
[12:32] candidate won in Minnesota, the more
[12:34] kind of left candidate, one for the
[12:36] Democrats, and it seems like she's going
[12:38] to win, but is performing a little bit
[12:40] worse than people are comfortable with.
[12:42] So, I feel like one way you could squint
[12:44] at this is to say
[12:46] in redder states, Democrats have been,
[12:49] you know, very purposefully choosing
[12:52] candidates who just seem more
[12:54] independent, right? [snorts] You know,
[12:56] and that as you go down to where
[12:57] Democrats felt more comfortable and
[12:58] could take more risk, they're taking
[12:59] more risk and trading away some of the
[13:01] possible gains. Like that would be the
[13:04] moderation wins thesis of like what
[13:06] we're seeing. Well, in and Florida is a
[13:08] state where you had a DSA candidate that
[13:11] isn't on anyone's map because, you know,
[13:13] um she's now trailing by six or seven or
[13:15] eight points, which isn't that bad for
[13:17] Florida, but like but there you see the
[13:19] failure to select a uh a you know, you
[13:23] need a pretty conservative Democrat
[13:24] probably to win in Florida at this
[13:26] point. No, I think that's a lot of it. I
[13:27] think a lot of it also if you look at a
[13:29] state like Minnesota where Peggy
[13:30] Flanigan is ahead, but by three and a
[13:32] half or four points,
[13:34] >> not by nine or 10, which
[13:35] >> Yeah. um you know the states where you
[13:37] have these democratic trifectas and you
[13:39] have critiques of democratic governance
[13:40] is where you tend to see more more
[13:43] problems potentially in Oregon where
[13:46] you've had a lot of critiques of liberal
[13:47] governance right um Tina Cotch the
[13:49] incumbent I think is only ahead by like
[13:50] one or two points in the polls um you
[13:52] know Kathy Hokll certainly looks like
[13:54] she'll win re-election but maybe by a
[13:56] relatively tepid margin you haven't seen
[13:58] that as much in like Massachusetts which
[14:00] is a classically well-governed state
[14:02] that's often had a Republican governor
[14:04] in the form of Charlie Baker Right. Um,
[14:06] but you know, I think people are there's
[14:07] an anti-inccumbent mood. [laughter]
[14:10] People, I think, are making this
[14:11] implicit calculation about who has kind
[14:13] of power over my life, right?
[14:15] >> But not against all incumbents, right?
[14:16] Like Austin is incumbent in Georgia is
[14:18] going to stomp. I mean, from what we can
[14:20] tell in the polls, his challenger, um,
[14:23] Roy Cooper is the incumbent governor in
[14:25] North Carolina. Yeah. Um, or, you know,
[14:27] obviously was like he's going to like
[14:29] win in a walk. So, like there are
[14:31] Democratic incumbents who are doing just
[14:32] fine here. I think Minnesota is the
[14:35] clearest example of this because Tim
[14:37] Walls's approval rating is 17 points
[14:39] underwater or something to the point
[14:40] where he was going to run for another
[14:42] term and and didn't. So, it's kind of
[14:44] like ground zero.
[14:45] >> He's had a real fast fall in rise and
[14:47] fall in politics.
[14:48] >> The trajectory of losing vice
[14:50] presidential nominees, you know, John
[14:53] Edwards had a rough fall from Grace, for
[14:55] example. Um,
[14:56] >> you know, Paul Ryan uh no longer in
[15:00] Congress, right? It's pretty, you know,
[15:01] pretty rough. That's a fair point.
[15:03] >> One one more thing for these hypotheses
[15:06] about the heartland and the Midwest. Um
[15:08] the economists had some data showing
[15:10] that like the closer that Trump voters
[15:13] live to data centers, the more likely
[15:15] are to flip and vote Democratic in this
[15:17] election. Um and in the West in general,
[15:20] you have a a lot of data centers, right?
[15:22] Because you want some space, but you
[15:25] don't want to be too far off the grid
[15:27] and too rural. And so and so that could
[15:29] be a hidden factor, too. There's
[15:31] something I was thinking about while I
[15:32] was like going through and trying to
[15:33] decide which of the candidates seem to
[15:35] me to be overperforming the most. I was
[15:38] thinking about how uncorrelated
[15:41] attention and performance is right now.
[15:43] So it's like if I go through the
[15:44] candidates who are all over my feeds and
[15:47] who are on big podcasts and and I mean
[15:50] obviously some of this is also their
[15:51] choice of of of how to run but it's like
[15:55] uh like Abdul said like omnipresent
[15:58] right James Taro omnipresent John Of
[16:00] he's not going on many national podcasts
[16:01] at the moment but his clips are
[16:02] absolutely everywhere you're not seeing
[16:04] sher brown right you're not seeing um
[16:07] you know very much of Mary Pollola right
[16:08] she does not do a lot of national press
[16:10] you're not seeing a lot of Roy Cooper
[16:12] but It's really like you look at it and
[16:15] there is almost no connection between
[16:17] who are the candidates who are
[16:19] everywhere,
[16:20] you know, on social media and my feeds
[16:22] and who are the candidates who are doing
[16:24] practically well or poorly um at least
[16:26] in polls.
[16:27] >> Yeah, look, some candidates have
[16:28] different incentives. If you want to run
[16:30] for president in 2028, then you probably
[16:32] want a somewhat somewhat higher profile
[16:34] potentially. I think in a case like
[16:36] Taler Rico um or Elsa, they kind of
[16:40] inescapably feel that um they're going
[16:43] to get the maximum amount of attention
[16:44] anyway. But look, there's something to
[16:46] be said for kind of keeping a a a lower
[16:49] profile, too. You know, maybe Ohio is a
[16:51] good example of that. Maybe Iowa a bit.
[16:54] I mean, look, in midterms, um there are
[16:57] basically three big questions, right?
[16:59] Will your voters turn out? Will the
[17:01] other side's voters turn out? And then
[17:02] how much persuasion is taking place
[17:03] among, you know, the 15% of the elector
[17:06] that's possibly swing voters. Um, and
[17:08] you know, if Democrats were to come up
[17:10] short in a couple of races like Iowa or
[17:13] Kansas, they might say, you know what,
[17:14] this race just got like a little bit too
[17:16] much on everybody's on everybody's radar
[17:19] and Republicans managed to drag some
[17:21] voters off the finish line. I mean, the
[17:22] persuasion part of this is done. I'd be
[17:26] shocked if Democratic turnout wasn't
[17:28] high by midterm standards. We don't know
[17:30] if Republicans are going to turn out and
[17:32] and
[17:34] that will determine the range between
[17:36] Republicans hold the Senate and keep
[17:39] Democrats to 10 seats in the House and
[17:41] complete 1994 style disaster.
[17:47] [music]
[17:56] So the right now I mean we're talking a
[17:59] little bit as if the thing Democrats are
[18:02] hoping will happen will happen.
[18:03] >> Yeah.
[18:04] >> But we often see polling error in
[18:06] midterms and maybe we see polling error
[18:07] in general elections too. So, how
[18:11] resilient
[18:13] are Democratic hopes to polling error
[18:16] and and how are you thinking about
[18:19] where the polling error might be? Like
[18:21] when you're building things into the
[18:22] model and thinking about like what
[18:24] you're trying to correct for, you know,
[18:26] you've seen Trump underestimated many a
[18:28] time, seen Susan Collins underestimated
[18:30] many a time. On the other hand, the
[18:31] pollsters know that has happened, right?
[18:32] How do you think about the polling error
[18:34] dimension of this? Look, the first thing
[18:36] I always tell people is that whenever
[18:37] you're looking at a series of polls in a
[18:39] Senate race or in Senate races plural,
[18:42] right, always ask yourself, what if
[18:44] they're off by three or four points in
[18:45] the same direction in every race? Um,
[18:49] you know, Democrats have a lot of
[18:51] threepoint leads in races like Ohio and
[18:54] Texas, more or less, right? Um, if you
[18:57] had a three-point polling error, you
[18:58] would have a a very long night where we
[19:02] might be waiting for rank choice voting
[19:03] in Alaska. But it's, you know, the House
[19:06] is different. If Democrats were not to
[19:08] win the House, then
[19:11] there would be profound questions about
[19:13] what's going on with the polling and in
[19:15] some ways what's going on with the with
[19:16] the country, too. I I think Democrats
[19:18] have the emotional feeling that when
[19:22] there's a polling error, it is, you
[19:25] know, against them, right? Because it,
[19:27] you know, Hillary Clinton and and and
[19:28] and Joe Biden and just in general, polls
[19:31] actually have repeatedly underestimated
[19:33] Donald Trump. But but is that true? And
[19:36] is it particularly true in in midterms?
[19:38] Have polling errors been consistently
[19:40] against Democrats?
[19:41] >> It has not been true in the two midterms
[19:43] under in the Trump era. I guess 2018 was
[19:46] under Trump and their polls were, you
[19:48] know, one of the most accurate years for
[19:49] polling ever. 2022 similar. In fact,
[19:52] there were a couple of races that were
[19:53] high-profile like the Federman race in
[19:55] Pennsylvania where polls showed Oz
[19:58] closing the gap after Federman's stroke,
[20:01] right? And then Federman won by a pretty
[20:02] solid I think four or five points or
[20:04] something like that, right? But overall
[20:05] polls were quite accurate. There are
[20:07] also elections that are held in
[20:09] oddnumbered years, runoffs, things like
[20:11] that. In New Jersey and Virginia last
[20:13] year, the polls were five to 10 points
[20:16] low on on Democrats, which is a one of
[20:19] the biggest polling errors we've seen in
[20:21] a well-pled, you know, general election.
[20:24] Um, so yeah, the critique I have of some
[20:28] of the people say, they'll say, well,
[20:29] you know, you're under sampling
[20:30] Republicans in these polls and Democrats
[20:32] are much more enthusiastic and much more
[20:33] likely to respond and trust the
[20:34] pollsters more. Every single person in
[20:37] the industry is is aware of that. Look,
[20:40] I think every pollster is aware that
[20:42] polls missed uh low on Donald Trump in
[20:45] 2016, 2020, and 2024. Um, you know, the
[20:49] three presidential years was kind of the
[20:51] death nail for the gold standard of
[20:54] polling, which is like we're just going
[20:55] to go and survey people and and we'll
[20:57] wait to well-known census demographics
[20:59] and we'll just we'll just trust the
[21:00] data. The an Seltzer poll in Iowa,
[21:04] [laughter]
[21:05] which and bless I mean, she was
[21:06] literally the highest rated pollster.
[21:07] She and then your times were like I
[21:09] think tied for number one or something,
[21:10] right? Um but now
[21:12] >> now we stand alone.
[21:13] >> Yeah. [laughter]
[21:15] >> So say what happened with Nelzer because
[21:16] maybe some people are emotionally
[21:18] scarred and some people have no idea
[21:19] what we're talking about.
[21:20] >> Yeah. What was it was the weekend before
[21:21] the election right and I had like some
[21:23] dinner plans on Saturday and then I got
[21:24] like a text from a friend saying have
[21:25] you heard about this Iowa poll? There's
[21:27] a rumor that like Anseltzer, the um kind
[21:30] of, you know, Dame or Don of Iowa
[21:32] polling, right? Um who had predicted
[21:34] Barack Obama's big win, the Iowa caucus
[21:36] in in 2008, would have a poll coming out
[21:39] showing Kla Harris winning, I think, by
[21:40] three points in Iowa. Every other poll
[21:43] of Iowa had been Trump plus nine or
[21:44] something like that, right? Um and
[21:48] our model was pretty skeptical. you
[21:51] don't usually want to bet against an
[21:52] Seltzer, but like it kind of opened up
[21:54] this whole world like what if everyone's
[21:55] just kind of way overcompensating for
[21:57] past elections and and it didn't make a
[21:59] lot of sense, but she had gotten very
[22:02] far before just saying I'm just going to
[22:03] trust my data. I'm not going to overly
[22:04] massage it, not make too many
[22:05] assumptions about it. And the poll was
[22:07] off by what was it like 13 or 14 or 15
[22:09] points.
[22:11] >> Trump insanely sued the paper as if like
[22:14] publishing a poll where he um was losing
[22:17] was defamation.
[22:18] >> Yeah. Yeah, it's never clear what the
[22:19] incentives are supposed to be.
[22:20] >> Can I stop on this polling thing for a
[22:21] minute though to let's let's get in the
[22:24] weeds methodologically for a minute
[22:27] because I find whenever we start
[22:28] discussing or I start thinking about how
[22:31] what is happening in polls
[22:34] to massage demographics
[22:37] to kind of answer all these problems of
[22:40] people don't pick up the phone or you
[22:41] know we're using online sampling and we
[22:43] don't know who will turn out.
[22:46] I I feel very disoriented. What do you
[22:48] do? Like what what are the pollsters
[22:50] doing?
[22:51] >> And I should say I am I'm not a
[22:53] pollster. I'm a forecaster, right? But I
[22:55] that distinction in some ways is
[22:56] becoming blurriier, right? Yeah,
[22:58] >> that's what I mean. They feel like
[22:59] they're forecasting. [laughter]
[23:00] >> I think the upshot of the ancelter thing
[23:02] is that um everyone knows that a poll is
[23:05] kind of almost like a a mini model with
[23:07] polling flavored inputs.
[23:10] And I'm not sure what the right metaphor
[23:12] is. But people wanted to make it like
[23:13] it's some broken gauge that like you're
[23:15] um that you know on your beat up old car
[23:17] that when it says 25% of fuel left
[23:20] actually have to refill because the
[23:21] gauge is broken. Right? Instead this is
[23:24] a more of an iterative process. Right?
[23:26] You open a restaurant, the customers
[23:28] complain the food is too spicy. You tamp
[23:32] it down a little bit. Now some of your
[23:33] customers say no I wanted the spice back
[23:35] in my food. Right? And so but it's more
[23:37] of an innovative process. And I think um
[23:39] pollsters are now aware they'll be
[23:41] judged on their results in the final few
[23:43] weeks at least. And as much as they
[23:45] might say, well, it's just a snapshot of
[23:47] public opinion, there are huge
[23:50] reputational stakes on the line for for
[23:53] being right. So I mean the pers and for
[23:55] being wrong.
[23:56] >> So the pollsters have pretty good
[23:58] incentives to correct for these problems
[24:01] potentially. Um but you know, but
[24:04] sometimes when
[24:06] it I know it sounds kind of toological,
[24:07] right? when there are these big wave
[24:09] change elections or elections that are
[24:12] kind of unexpected and sometimes
[24:14] pollsters lowball them. In 1994, for
[24:16] example, it looked like a relatively bad
[24:20] year for Clinton that turned into a
[24:21] terrible year, right? You can also look
[24:24] at a year like 2014 is a parallel that
[24:27] I'd be worried about if I were
[24:28] Republicans because that's a year when
[24:29] the polls were never great for Obama,
[24:32] but you had a really, really big
[24:33] differential turnout where Democrats
[24:36] just weren't that enthusiastic. At the
[24:37] time, Obama was relying on more of a
[24:39] multi-thnic younger coalition that
[24:41] traditionally does not turn out at the
[24:43] same rates in midterms. And that turned
[24:45] into a 9 seat loss, a total route for
[24:47] Democrats in in the Senate.
[24:49] >> Yeah. I mean, this is, I think, what I'm
[24:50] asking you, that we know the midterm
[24:52] electorate is going to be different than
[24:53] the presidential electorate, that some
[24:56] people are going to be more motivated to
[24:57] vote than others. I mean, are they just
[24:59] pulling people and saying, "Do you think
[25:00] you're going to vote?" And and and
[25:02] that's like the big screen just for
[25:04] somebody who does not like I have read
[25:06] analysis of these the upshot a while
[25:08] back and and Nick Cohen did a cool thing
[25:09] where they let you see like how
[25:11] different ways of moving the data around
[25:13] would give you a very different result
[25:14] on the same like underlying poll data.
[25:17] But is there like a a kind of
[25:19] conventional thing they're doing to
[25:21] compose a midterm electorate that is
[25:24] going to be really different in 2026
[25:25] than it was in 2022?
[25:26] >> Yeah. So, one difference if you ask
[25:28] people, are you going to vote? How
[25:30] enthusiastic are you about voting? That
[25:33] produces a very democratic sample. Um,
[25:37] other pollsters try to predict whether
[25:40] people will vote based on other types of
[25:42] data, right? um and and those techniques
[25:47] tend to produce more modest results for
[25:49] Democrats. One thing you can watch in
[25:51] the early voting data, which generally I
[25:52] advise people not to do, but who was
[25:54] winning among like lower propensity
[25:56] voters, right? People of who have voted
[25:58] in no more than one out of the past
[26:00] three elections counting counting
[26:01] midterms. Um those low propensity voters
[26:05] appear to be quite Democratic so far. It
[26:09] [clears throat] maybe probably will to
[26:11] some extent. Republicans will cast their
[26:12] vote by election day anyway and they'll
[26:14] and they'll catch up, right? But but if
[26:16] not, if Democrats low propensity voters
[26:18] turn out and the GOP doesn't, then
[26:21] that's where you might see a polling
[26:22] error that underestimates Democrats.
[26:24] >> So if Republicans end up having a better
[26:27] thanex expected night, what do you think
[26:29] will have ended up being the explanation
[26:31] for it?
[26:32] >> I mean, look, I think there are two
[26:35] versions of this. Like one is just
[26:37] Democrats lose all the toss-ups, right?
[26:39] Talerico loses by a point. Jackson loses
[26:41] by a point. Maybe Elsa wins by a
[26:44] recount. Shared Brown wins, but Turk
[26:47] loses by three points. Like that's very
[26:49] feasible in the kind of thick part of
[26:51] the probability distribution. And then
[26:54] and then I think you know with some
[26:56] questions about the polls, but that's
[26:58] kind of that's kind of in line. We'll
[26:59] say, okay, partisanship is still really
[27:01] strong. Maybe pollsters and Democrats
[27:02] had their hopes up a little bit too high
[27:04] to think you could win on these, you
[27:06] know, R +12 states, it would have been R
[27:08] plus 8, then yeah, but we just kind of
[27:11] reached the point where we ran out of
[27:12] like oxygen climbing up that that big
[27:14] red hill, right? If there's a if there's
[27:17] like a like let's say the House is kind
[27:19] of close, right? And Democrats only pick
[27:21] up North Carolina in the Senate, right?
[27:24] I mean then
[27:26] that's kind of hard to contemplate
[27:30] almost right not just not because it's
[27:32] not theoretically possible based on the
[27:34] polls right like you know we have these
[27:36] in our model these like fat tails that
[27:38] say sometimes polls can by five or six
[27:40] or seven points or something crazy right
[27:42] um but that would kind of like defy
[27:46] everything that we think we know about
[27:47] how how midterms work there are I think
[27:50] a couple of races that feel to me like
[27:52] they have like a a lot of outsized
[27:54] narrative importance. Telerico feels to
[27:57] me like it's got a lot of narrative
[27:59] importance to people. You know, the
[28:01] possibility of Democrats being
[28:02] competitive in Texas, a sort of return
[28:04] of a religious left. Abdul sayed is
[28:06] going to be seen as a very important
[28:08] test of, you know, he's actually not a
[28:10] DSA guy, but sort of a more left
[28:12] populist, you know, unsparing candidate.
[28:15] Like I was watching this video where he
[28:17] just like absolutely annihilates this
[28:21] guy who comes to one of his town halls
[28:24] and is like will you denounce to the
[28:25] Muslim Brotherhood and I mean Elsiad
[28:28] who's a very very very smart guy leaves
[28:30] this guy like a smoking like crater on
[28:33] the floor.
[28:34] >> So it feels like there's going to be a
[28:35] lot of attention on how he specifically
[28:37] does
[28:38] >> um
[28:40] >> you know you've been very attentive to
[28:42] like the factional divisions of the
[28:43] Democratic party recently. I think
[28:44] you've you've cut Democrats into what is
[28:47] it the capital L left the abundance libs
[28:49] which I guess is me
[28:50] >> and then Richardsonism which you've
[28:52] named for Heather Cox Richardson who's
[28:54] you know the substacker and that's sort
[28:56] of the big like resistance libs no kings
[28:59] kind of thing but I I'm curious how you
[29:01] think different forms of the election
[29:04] might end up being interpreted and
[29:05] shaping the the Democratic party and its
[29:07] strategies. So the two big apart from
[29:09] who wins, right? The two big sub story
[29:11] lines of November 3rd are one, how do
[29:13] progressives do relative to moderates?
[29:15] But then is there evidence of like an AI
[29:18] backlash um from the state-by-state
[29:21] results, right? If people do these
[29:23] ecological analyses afterward, they
[29:24] find, hey, yeah, in states where there
[29:26] was a data center construction and
[29:27] Republicans underperformed by by three
[29:29] points, I mean, that might be important
[29:30] as well. Yeah. If if [snorts] I I'll say
[29:33] I were to lose,
[29:36] then win or lose the Senate, and that's
[29:38] a very bad narrative for progressives. I
[29:40] don't know what happens if like um you
[29:43] know, let's say that um Benson wins by
[29:46] nine points and Elsa wins by four,
[29:47] right? Maybe nerds like me are like,
[29:49] well, he had a below average wins of a
[29:51] replacement. That proves my thesis, but
[29:52] like I think that wouldn't really carry
[29:54] the day in the Democratic debate as
[29:55] much. Um, I I think for any race, an
[29:59] important threshold question is, was the
[30:00] race called on election night? Right?
[30:04] That shapes narratives quite a bit.
[30:06] People who aren't nerds tend not to pay
[30:08] much attention to the margin as long as
[30:09] it seems unambiguous and clear. Um,
[30:14] I mean, look, people wanted to tell this
[30:16] oversupplied narrative of like the
[30:17] progressives like winning everywhere in
[30:20] the primary, and that wasn't entirely
[30:23] true. You know, Franchesca Hong was
[30:25] ultimately rejected in Wisconsin. Um, I
[30:28] don't know that Jasmine Crockett
[30:30] actually is more progressive than Taller
[30:33] Rico. She's more of a partisan
[30:34] bombthrower and and she lost that that
[30:37] race. Um, yeah,
[30:39] >> she wasn't a DSA person. That was not
[30:42] her her profile in politics.
[30:44] >> But like I think I think Democratic
[30:45] voters have exercised
[30:48] a fair amount of kind of rational
[30:52] discretion, right? I mean, there's
[30:53] nothing that says that voters have to or
[30:56] necessarily should maximize everything
[30:59] based on electability, right? You're
[31:02] allowed to say, well, I'm trying to
[31:03] calculate some like expected value score
[31:07] of what is the chance that this
[31:08] candidate wins times how much good will
[31:09] they do for the issues that I that I
[31:11] care about, right? Although, I will tell
[31:12] you one thing. Um
[31:15] the amount of Democratic infighting
[31:17] really dropped off after these races in
[31:20] Maine, Michigan,
[31:21] >> Wisconsin.
[31:22] >> Primaries just create a lot of I mean
[31:23] and it's going to go up again when the
[31:25] 2028 primary
[31:26] >> it's going to be the only thing
[31:26] everyone's talking about for a year and
[31:27] a half or something. I would say and and
[31:29] this is like a step back I have.
[31:33] One narrative that I think is going to
[31:35] be true particularly if you have you
[31:37] know a bunch of these players win is the
[31:40] Democrats are coming into an an era of
[31:42] like elder millennial talent
[31:44] that I apologize to my Democratic office
[31:47] holder Gen X friends. I think like the
[31:50] like the late boomer and then um like
[31:53] the Gen X class and Democratic party
[31:54] ended up like pretty caught between
[31:56] political eras and communication eras.
[31:59] But when I look at the Democratic talent
[32:02] right now and I think about you know on
[32:04] the left people like Zan Mani and Abdul
[32:06] Seed and AOC who are hugely talented
[32:10] like I think El say'll be like a pretty
[32:12] superstar US senator if he wins. Um, you
[32:15] know, and then I look at, you know,
[32:17] people like Rob Sand who's, you know,
[32:19] looks like he's going to win the Iowa
[32:20] governor's race in a walk, but you think
[32:21] about Telerico who like is like really a
[32:24] star. John Of who has become an absolute
[32:27] superstar. Like I think you're just sort
[32:29] of seeing like the arrival of like a
[32:32] Democratic class that is just more
[32:34] native to this era. Like came in during
[32:37] Obama, then was shaped by Trump,
[32:39] understands communication now. just
[32:42] something to me seems to be changing
[32:44] that is actually across a different
[32:46] faction like they all now have stars in
[32:48] a way that I wouldn't have said was true
[32:50] a few years ago. I think some kind of
[32:52] like a Steph Curry effect with Obama as
[32:55] an analog where like he starts shooting
[32:57] three-pointers from where no one has
[32:58] before and now kids are practicing that
[33:00] in in high school and they graduate and
[33:02] grow to college in the NBA.
[33:03] >> And who is Steph Curry in this analogy?
[33:05] >> Obama.
[33:06] >> Yeah. like in some ways
[33:09] >> I mean yeah Elsiad and Assa for instance
[33:11] are very both influenced by Obama in
[33:13] different ways you know Mayor Pete's got
[33:15] a little
[33:15] >> Mayor Pete yeah Pete Buddha Judge is
[33:17] another kind of elder millennial talent
[33:18] I would add to this
[33:20] >> um but like I think like in some ways
[33:22] what happened to Democrats after
[33:25] 2012 was kind of weird right where
[33:27] Hillary lost to Obama and Bill Clinton
[33:30] became president in 1992 right and for
[33:33] some reason it's like well it's it's
[33:35] Hillary's turn now, right? And she had a
[33:38] very competitive primary against Bernie
[33:40] Bernie Sanders and prevail, but like
[33:42] that in some ways felt like um a return
[33:46] to a different Democratic party than the
[33:47] party that Obama was trying to craft,
[33:49] right? And then and then Biden who was
[33:51] kind of expressly chosen by Obama
[33:55] because he was old and not seen as a
[33:57] threat to run for president himself kind
[33:59] of won amid this like flight to safety
[34:03] and then but like um
[34:06] I don't know obviously some of these
[34:07] were competitive nomination processes
[34:08] right but it feels like some trajectory
[34:10] [music] got interrupted in the
[34:13] Democratic party and and maybe now it's
[34:16] being restored I suppose a little
[34:18] >> [music]
[34:30] >> So, we've been talking a lot about the
[34:31] Senate, and the Senate is like the
[34:33] charismatic megapon of midterms because
[34:35] there are only a couple races you have
[34:36] to pay attention to, and you can keep
[34:37] the characters of them in mind.
[34:39] >> Obviously, the House is not a binary
[34:41] outcome. it really matters if Democrats
[34:44] end up with 228
[34:47] members of the House, 235, 240, 250.
[34:51] So tell me about what the modeling and
[34:54] the polling seems to suggest about where
[34:56] Democrats might end up and you know like
[34:59] the kind of sensitivity of that in both
[35:01] directions.
[35:02] >> Yeah. So, one of the big consequences of
[35:04] all this redistricting as well as voter
[35:07] self- sorting is that you have far fewer
[35:11] swing districts than than you once did,
[35:13] right? Also, Democrats had a relatively
[35:15] good 2024 in the House. I mean, there
[35:19] was still some doubt on election night
[35:20] whether Democrats might actually win the
[35:21] House in 24 despite Harris having lost.
[35:24] Um, so, you know, even the models, even
[35:26] our model that has them with a 90% plus
[35:29] chance of winning the House, that only
[35:30] translates quote unquote into I think 22
[35:33] seats or something on average. Um and
[35:36] >> which like we've seen, you know, wave
[35:38] elections that are like 40 50 seats,
[35:40] >> right? I mean, was it 63 in in 2010, for
[35:44] example,
[35:44] >> which was like the big the very big one
[35:46] >> or 41 or something in 2018? Um
[35:50] >> you know, Republicans did gain a few
[35:53] seats from the redistricting process,
[35:55] mostly in the mostly one where they just
[35:56] cut out a majority minority district,
[35:58] right? So, Louisiana, Alabama,
[36:01] Tennessee, and some of those states, the
[36:03] Alabama district is actually kind of
[36:05] close in the polling. Um, but that's
[36:07] like a clean three seats wiped out from
[36:10] Democrats, right? Um, in Texas and
[36:13] Florida, you were not seeing many
[36:15] Republican gains because in Texas, the
[36:17] theory was that like, oh, we can now we
[36:18] can now take more risks because we now
[36:21] have a much firmer hold with lower
[36:23] income Hispanic voters. Well, if you
[36:24] believe the polls, those are the groups
[36:26] that are shifting most aggressively back
[36:28] toward Democrats. And in Florida,
[36:31] Dantis kind of drew a riskier map that
[36:34] was optimized more for presidential
[36:37] years and would have a lot of toss up to
[36:41] lean our districts in an environment
[36:44] like this one. Now, in Florida,
[36:46] Republicans have, you know, I we talked
[36:49] before about like, well, what if
[36:50] Democrats win in Kansas or Texas? At
[36:53] this point, it would almost feel as
[36:54] remarkable if a Democrat won a statewide
[36:56] race. And
[36:57] >> you have I Florida I have never
[37:02] read what was to me a fully satisfying
[37:04] explanation of how Florida became so
[37:07] red. But Florida has gone, as you say,
[37:09] from being a canonical swing state
[37:13] >> to more of a Republican readout than
[37:16] Texas. I mean, Ronda Sanders barely won
[37:20] um his first race for governor. How did
[37:22] Florida become so red?
[37:24] >> I think it's 75% migration and 25% kind
[37:29] of a death spiral for the Democratic
[37:30] party that might be self-reinforcing. I
[37:31] mean, with the migration, um, Florida is
[37:36] a unique place in offering blue state
[37:40] amenities, but without [laughter]
[37:42] without as many libs, you know what I
[37:43] mean? Um, and that attracts, you know, a
[37:47] has always attracted older people. Um
[37:49] but yeah, I think you have a lot of like
[37:51] political self- selection in most
[37:52] states. If you look at like voter
[37:53] registration data,
[37:55] um people have begun to again register
[37:58] more as Democrats than Republicans,
[38:00] which which was not true for like four
[38:01] or five years in a row. Um this year you
[38:06] seeing those comebacks for Democrats in
[38:07] the Midwest in particular in
[38:08] Pennsylvania, but not in Florida.
[38:10] Florida just keeps getting redder at the
[38:11] registration level.
[38:12] >> Okay. So, so that's like the center of
[38:15] house polling, but but we've talked
[38:17] about a two to three or four point
[38:19] polling error like not being unusual
[38:23] given incumbency advantages in the
[38:25] House, given redistricting.
[38:26] >> Yeah. Is this the kind of thing where if
[38:29] you get a three-point error and it turns
[38:31] out Democrats did better than expected
[38:33] by three points? Yeah. Where all of a
[38:35] sudden a bunch of the redistricting
[38:36] falls apart and Democrats like have this
[38:38] huge wave election and actually they are
[38:40] winning, you know, 40 seats in the house
[38:42] and they have this like huge majority
[38:44] under speaker Hakee Jeff.
[38:48] Yeah. No, it is a little bit asymmetric,
[38:50] right? And people love the flood and
[38:52] maritime metaphors, but but um if the
[38:56] wave gets really big, then one thing
[38:59] that happens is it inundates candidates
[39:01] who have not been prepared for that type
[39:03] of disaster potentially. I mean, I think
[39:05] the best example is like actually in in
[39:07] the Senate with Roger Marshall where I
[39:10] have um
[39:10] >> in Kansas
[39:11] >> in Kansas, right? I have a family that
[39:13] lives in Overland Park, Kansas, big in
[39:16] Kansas and Missouri politics and like
[39:17] boy, Roger Marshall's a really bad
[39:19] candidate, right? I'm like, you know,
[39:20] it's Kansas. It's I'm sorry. Doesn't
[39:22] matter. Doesn't matter. Um but um but if
[39:25] you're caught up in this tide and like
[39:27] Kansas, you know, it's elected Theres
[39:28] Davis to Congress.
[39:29] >> Sorry. You saw the thing where Trump
[39:30] then went to defend Roger Marshall.
[39:33] >> Oh, no. Yeah.
[39:33] >> And was like, Yeah. I mean, the reason
[39:36] he had to go after his candidates, his
[39:39] his patience for payment in that way,
[39:41] people trying to paint him. He used like
[39:42] an anti-semitic slur.
[39:44] >> Roger was given a real I know the guy.
[39:48] He's one of the He's a tough guy and
[39:50] all, but he's also high quality and he's
[39:52] a fine person. And he was given a bum
[39:55] wrap because he was mandated by law to
[39:58] request strongly money owed from
[40:00] patients. You're not allowed not to do
[40:02] it. You have to by law go after those
[40:05] people and they made it like, oh, he was
[40:07] some kind of a shillock type guy.
[40:09] >> There are times when I wonder whether
[40:10] Trump really cares whether GOP holds the
[40:13] center or not, right? I mean, he hasn't
[40:15] done a whole lot through Congress. It's
[40:16] mostly been through executive power,
[40:18] right?
[40:19] >> And I think Cornin would win Texas.
[40:23] Trump easily could have just ended that
[40:25] primary and made Cornin the the winner,
[40:27] right? That that was completely within
[40:28] Trump's power and Republicans would be
[40:31] in a stronger position in Texas and less
[40:33] likely to lose the Senate if that had
[40:34] happened. You know, Trump has on the
[40:38] margin not wanted to lose the midterm
[40:41] election. He did this weird midterm
[40:43] convention, but his whole theory of why
[40:46] Republicans might lose a midterm
[40:48] convention appears to be that he himself
[40:50] is not on the ballot and that if only
[40:53] people would act like he is on the
[40:54] ballot, Republicans would be fine. Then
[40:56] his other theory was to promise every
[40:57] American a $5,000 check if Republicans
[41:00] win. So like to bribe people. It's like
[41:02] he's willing to win the midterm if he
[41:06] can win it in a way that is personally
[41:09] congratulatory of him. But if winning
[41:11] the midterm means giving Republicans
[41:13] space from him and you know backing
[41:16] people he doesn't really like
[41:17] >> then no.
[41:19] >> Look, Republicans
[41:21] are kind of caught between a rock and a
[41:23] hard place in elections where Trump
[41:26] himself is the dominant figure but not
[41:28] himself on the ballot. Right? that
[41:30] entire trench of elections. So 2018, if
[41:33] you kind of want to count 2022 as well,
[41:35] where something prevented Biden from
[41:36] having the wipeout you might get with a
[41:39] 40% approval rating, typically all the
[41:42] runoffs, including the two in Georgia,
[41:44] all the special elections, Supreme Court
[41:47] races, ballot initiatives, all that kind
[41:49] of stuff. It's all gone really badly for
[41:51] for Republicans. Um because the one
[41:55] magic
[41:57] trick that Trump has is to get a certain
[41:59] type of usually disengaged voter to kind
[42:02] of like crawl on glass to vote for him
[42:04] when he himself is on on the ballot. And
[42:07] furthermore, these are the exact voters
[42:09] that aren't answering polls or that are
[42:11] incorrectly deemed to be unlikely voters
[42:14] or anything like that, right? Um, those
[42:17] people are not gonna crawl over glass to
[42:19] vote for Roger Marshall or Ken Paxton, I
[42:24] don't think. But I I don't want to lose
[42:25] the side of the big picture here, right?
[42:27] The I don't think we'd be talking about
[42:29] Democrats being favored in the Senate if
[42:32] Trump hadn't decided to go to war with
[42:34] Iran and spike gas prices into the mid4
[42:37] per gallon. More here in California and
[42:39] places like that, less in some other
[42:40] places.
[42:41] >> You know, you obviously keep a close
[42:43] track of Trump's approval rating. Yeah.
[42:47] >> What is the story of its decline? It's
[42:49] dropped quite a bit since he took office
[42:51] a second time. Has that dropped been
[42:54] steady or has it been like discontinuous
[42:57] around certain events?
[42:59] >> If you want to like model it
[43:00] statistically, then
[43:03] you know it's quite correlated with gas
[43:05] prices. Frankly, there's al also a time
[43:07] trend, right? In general, you see it jut
[43:09] up and down a little bit based on gas
[43:12] prices and kind of economic anxiety. It
[43:14] dropped a lot during Liberation Day. Was
[43:16] that April 2025 concern about tariffs?
[43:19] Um,
[43:20] >> but it's been a pretty steady decline
[43:23] and I think people kind of learned some
[43:25] incorrect lessons from the first Trump
[43:28] term, right? um when voters felt like
[43:31] the economy was good and objectively it
[43:33] was pretty good in the first three years
[43:34] of Trump. That just kind of serves as
[43:36] like a a halo that allows you to say,
[43:39] "Oh, Democrats are complaining about
[43:41] democracy this and democracy that and
[43:42] and race and xenophobia and whatever
[43:45] else, right? But you got more money in
[43:46] your paycheck. You have a good job. The
[43:47] stock market's up. Your house is
[43:49] appreciating in value, right?" And now
[43:51] that people question all those things,
[43:53] it makes the culture war stuff seem kind
[43:55] of desperate and silly. also just kind
[43:57] of fatigue. Um, you know, Trump likes to
[44:02] say it's his third term, but it kind of
[44:04] feels that way. He's been the dominant
[44:05] figure in American politics since
[44:07] whatever mid 2015. That's a that's a
[44:10] really long time. He's also um 80 years
[44:13] old, you know, like you, Ezra, you and I
[44:15] were both kind of early on that Biden is
[44:16] too old. I don't know if you
[44:18] have to censor that bandwagon. Um, but
[44:20] Biden began to develop more problems at
[44:23] roughly this point in his presidency,
[44:25] you know, and it's like, okay, you we've
[44:27] already mentioned the two things that
[44:28] are maybe not hard to explain, but like
[44:30] why the war with Iran and then why is
[44:34] Trump taking this very unpopular stance
[44:36] on data centers, which feels like kind
[44:40] of the perfect issue for a populist to
[44:42] do some mild demagoguing in the other
[44:45] direction, right? like data centers are
[44:46] like a a 8020 issue against data centers
[44:50] now roughly. And when you ask people do
[44:51] you want to have LA AI accelerate or
[44:54] slow down. It's like 3% for accelerate
[44:56] and like 60% for slow down and 30% are
[44:59] not sure or whatever. Well, I I could
[45:01] give two, you know, I give a substantive
[45:03] and a less substantive reason for Trump.
[45:05] I mean, one is that I think he actually
[45:07] is persuaded
[45:09] we're in a
[45:12] military and geopolitical and economic
[45:14] race with China. I mean, as he likes to
[45:16] say, whoever wins AI wins. And the other
[45:19] is that
[45:21] if the AI boom, if something
[45:25] shifts sentiment, then the one economic
[45:29] indicator Trump has that is looking good
[45:31] for him, which is uh the stock market.
[45:34] >> Yeah.
[45:35] >> Collapses.
[45:37] And then he's got nothing, right? Then
[45:39] you've got high interest rates, you've
[45:40] got terrible debt, you've got, you know,
[45:41] anemic growth, you've got a weak stock
[45:43] market. And like the thing where all the
[45:45] investment was going is no longer maybe
[45:46] working out. And also, and I think it's
[45:48] not nothing here, a bunch of AI execs
[45:52] have donated a ton of money to Donald
[45:54] Trump and Elon Musk personally, and I
[45:56] want to talk about this too, is like
[45:59] individually financing at this point the
[46:01] Republican midterm campaign, right? Like
[46:05] I mean, what's he put in? It's hundreds
[46:06] of millions of dollars
[46:07] >> for like 400 some million.
[46:09] >> Yeah. And it's hard even to know if we
[46:10] know everything that's gone in. And so,
[46:13] you know, he may also not want to like
[46:15] alienate his tech, right? Um, you know,
[46:18] even tech center constituency.
[46:20] >> I think that's a lot of it. I think I
[46:22] think, you know, I'm not a I'm not a
[46:24] Trump whisperer, right? It does seem
[46:26] like the one thing that consistently
[46:27] motivates him is that he doesn't like
[46:29] seeing red arrows on the stock market
[46:31] ticker. Um, and you know, you've seen
[46:35] increasing amounts of investor anxiety
[46:38] about about maybe not I think the AI
[46:41] bubble argument is getting more
[46:42] sophisticated, right? It's like [sighs]
[46:45] how can we land this plane without
[46:49] instrumentation we've tested before and
[46:51] this kind of narrow strip of runway,
[46:53] right? You know, you've also had just in
[46:56] the past week or two, you've had oil
[46:57] prices increase sharply again in the
[47:00] Middle East. I don't know. I mean, if
[47:01] there were to be a last week surprise,
[47:05] [laughter]
[47:06] the most obvious surprise would be some
[47:07] kind of market downturn that would kind
[47:09] of further hurt Trump potentially.
[47:11] Things can break a lot more.
[47:12] >> I mean, this is you were using the Bush
[47:14] 06 analogy a few minutes ago. You know,
[47:16] you talked about sort of Bush as a super
[47:18] lame duck and one and I was thinking as
[47:20] you said that though that the final two
[47:22] years of Bush's term were tremendously
[47:25] eventful um leading up to a global
[47:28] financial meltdown at the end of it. And
[47:32] yeah, I look at Trump and I look at the
[47:36] economy and I look at the geopolitical
[47:39] situation and what I see is risk
[47:43] everywhere. Right? If you told me we
[47:45] were going to have like a massive
[47:48] recession or stock market correction or
[47:51] correlated financial crisis, you know,
[47:53] next few years, I'd say, "Yeah, that
[47:55] totally tracks to me."
[47:56] >> If you were to tell me some like Russia
[47:58] Ukraine or Iran America or Israel, Iran
[48:03] or some combination of things like Gulf
[48:05] State like that it like flies even more
[48:08] out of control than it already is. Like
[48:09] that would seem totally plausible to me.
[48:12] some kind of rogue AI behavior. Yeah.
[48:15] That attacks like, you know, an American
[48:18] AI swarm attacks China or a Chinese AI
[48:21] swarm attacks America. Like the world
[48:24] feels full of risk to me. And like we've
[48:28] seen, you know, lame duck presidents
[48:30] like that. Like really things begin to
[48:32] like blow up in their face and they have
[48:34] very little power or public credibility
[48:36] to then handle it.
[48:38] >> And he'll be 82 years old by by the end
[48:40] of the term, too. Um, look, in some
[48:43] ways, Trump was pretty
[48:47] lucky in the first three years of his
[48:49] first term in the White House that kind
[48:50] of
[48:52] not nothing kind of literally or
[48:53] figuratively blew up, right? It wasn't
[48:56] like Biden where Ukraine happened under
[48:58] Biden's watch and Gaza happened under
[49:00] Biden's watch, right? You know, if
[49:03] Republicans lose the Senate, probably
[49:05] one of the first people that should be
[49:06] blamed is Pete Pegsith, I think. Right.
[49:08] Um, I don't think there are very many
[49:10] people who would serve a secretary of
[49:11] defense that would have thought that
[49:14] going to war with Iran with this very
[49:16] ambiguous war plan and very ambiguous
[49:18] goals was a was a smart idea. But but
[49:21] it's the other way around. I'm not
[49:22] saying you're saying anything different
[49:24] here, but Donald Trump and Benjamin
[49:26] Netanyahu wanted to go to war in Iran.
[49:27] And Donald Trump had named Pete Hegsth a
[49:30] Fox and Friends correspondent to be
[49:33] defense secretary because he wanted
[49:35] somebody in that position who would
[49:37] never under any circumstance say no to
[49:39] him. Like I think it's very likely he
[49:41] pretty quickly gets the axe after the
[49:43] midterms or at some point. But he's very
[49:47] unlikely to be replaced by a like a
[49:51] thoughtful commanding general who has
[49:53] the personal stature to say no to Donald
[49:55] Trump. Right? It's not going to be
[49:57] they're not going to bring back Jim
[49:59] Mattis and that has I mean you've seen
[50:02] this on tariffs right Gary Conn the um
[50:06] Goldman Sachs head who is the NEC
[50:08] director national economics council in
[50:09] Trump's first term would not have
[50:11] presided over this tariffs regime he
[50:13] just would not have Trump and his team
[50:16] wanted to come in and make sure Trump
[50:18] would be surrounded by people who always
[50:19] said yes. um what does this all look
[50:22] like if the stock market goes into freef
[50:24] fall because it turns out AI isn't not
[50:26] ready for prime time because it's
[50:28] actually too dangerous or you know what
[50:30] if we do end up in confrontation with
[50:32] China
[50:33] like the number of things that could go
[50:35] wrong and not just go wrong
[50:36] geopolitically but in a way that would
[50:38] then correlate into the economy in like
[50:40] a catastrophic fashion potentiating some
[50:44] crazy meltdown to say nothing of like
[50:46] the way Trump might act if he's really
[50:48] cornered in the last two years and begin
[50:50] like going into like high tilt
[50:52] strategies to use one of your poker
[50:54] turns and Trump older and surrounded by
[50:57] Pete Hegaths.
[51:00] Yeah. Um it makes me anxious to to be
[51:05] honest, right? I mean I the AI thing
[51:07] alone,
[51:08] >> this is a different episode, right?
[51:10] Probably makes me anxious. We're just
[51:11] like, okay, the future could look very
[51:12] different um
[51:15] 5 years from now, 3 years from now,
[51:17] right? Um, if you're in middle age,
[51:19] right, you want to kind of think, oh, I
[51:20] can keep doing what I'm doing, do it for
[51:22] another 20 or 30 years, and then
[51:24] whatever, retire. And now it's like, oh,
[51:25] who the knows what's gonna, you
[51:26] know? But like, but Trump is not the
[51:28] ideal president to have [laughter] at
[51:30] the helm when you're on the verge of I
[51:33] don't think we're necessarily on the
[51:35] verge of a singularity, right? But like
[51:37] with perhaps the most important
[51:40] technological advancement in in decades,
[51:42] to put it modestly, right? I'm not sure
[51:43] that's the person that you'd want to
[51:44] have in charge as an 82-y old Donald
[51:46] Trump. Does the Musk money dump matter?
[51:48] Does money in general matter this late
[51:50] in the election?
[51:52] >> I think money is generally overrated in
[51:56] politics. I qualify that by saying for
[51:58] any high-profile race, so Senate,
[52:01] governor, um certainly president, where
[52:04] you encounter diminishing returns, if
[52:06] you were to look at the frontier of like
[52:08] the House map where maybe name
[52:11] recognition, and visibility is an issue.
[52:13] If you were to look at like state
[52:15] legislatores, those are really
[52:17] important, especially now that state
[52:18] legislators and governors play into the
[52:20] now apparently every two years
[52:22] redistricting that we have. The other
[52:24] thing too is that like when you are um
[52:27] buying ads with voter donated money, you
[52:29] get better rates and also you get better
[52:31] rates if you have that money raised
[52:32] earlier and and lock that in when it's
[52:34] less competitive, right? So you hear
[52:36] about the Republican financial
[52:37] advantage. Um because that's primarily
[52:42] corporate money and party money. Um it's
[52:44] probably translating to more like 50/50
[52:46] in terms of actual ad impressions that
[52:48] voters are seeing. Right before the 2024
[52:50] election, you published a piece, you can
[52:53] correct me if I'm wrong about some part
[52:54] of this where you basically said, "My
[52:56] model says Kla Harris is going to win."
[52:58] >> Yeah.
[52:58] >> And my gut says Donald Trump is going to
[53:01] win.
[53:01] >> Right. I think you did this
[53:02] pre-election. Yeah. This a
[53:03] pre-registered take. Yeah. Do you is
[53:06] your gut in any way different than your
[53:07] model this year?
[53:10] >> Well, what I talked about in that piece
[53:11] is that like
[53:14] it would be more embarrassing for the
[53:18] industry, meaning pollsters,
[53:20] forecasters, pundits, whatever, etc., if
[53:23] once again, Republicans beat their polls
[53:25] in the Midwest, right? So, like
[53:27] emotionally, I feel some need to hedge
[53:30] against that. And yeah, I'm a little
[53:31] skeptical of of
[53:34] Kansas maybe and Iowa and that tier of
[53:37] states. What's different though is that
[53:38] like so in 24 um I had an exercise where
[53:42] I'm like here are I think it became like
[53:44] a list of like 21 reasons why the
[53:47] political environment favored Donald
[53:49] Trump. And I'm like I'm going to do one
[53:51] to be fair for why it favors Harris. But
[53:54] I could like only come up with like four
[53:55] or five things. Right? This here that's
[53:58] the reverse. The fundamental conditions
[54:00] feel terrible for Republicans, right?
[54:03] You have the secondterm 80-year-old
[54:05] president who had a bad midterm when he
[54:07] was younger and more popular and the
[54:10] economy was perceived as better in 2018.
[54:13] Um, and now you have Iran, you have 450
[54:16] gas, you have Jeffrey Epstein, right?
[54:20] Um, you have corruption in in the White
[54:22] House, you have the strong batch of
[54:23] Democratic candidates. You know, in some
[54:25] ways it's um
[54:27] you'd imagine that it would be a worse
[54:29] year for Republicans in 2018, right? And
[54:31] if that's true, that means like
[54:32] Democrats win the popular vote by the
[54:34] House by for by for by by like 10 or 11
[54:37] points or something. And so my my my
[54:40] guts really contradictory, right? I
[54:41] worry more about the state polls being
[54:45] wrong than the national race being being
[54:48] miscalibrated.
[54:49] >> I think that's a good place to end.
[54:50] Always a final question. What are three
[54:52] books you recommend to the audience?
[54:54] >> Okay. Esther, this is tough because I'm
[54:55] a frequent listener of the show and some
[54:56] of my recommendations have been taken by
[54:58] other
[54:58] >> No, that's good. I feel like the
[55:00] audience takes it more seriously when
[55:02] there are uh repeat recommendations.
[55:03] >> Well, I picked three slightly weird
[55:05] ones. So, um the first one is um The
[55:08] Rise and Fall of American Growth by the
[55:10] economic historian Robert Gordon. It was
[55:12] written in 2016. Um I remember kind of
[55:16] reading this book when I was um in Paris
[55:18] at a poker tournament in Paris as one
[55:20] does, right? Um, and like Paris is so
[55:24] timeless. And meanwhile, this was like
[55:26] the week when the US went to war with
[55:27] Iran. It was the week when the
[55:28] Department of Defense and Anthropic got
[55:29] in a big fight. Things just felt like
[55:30] they were excited.
[55:31] >> You read this book recently.
[55:32] >> I read it recently. Yeah. Yeah. Um, and
[55:35] the kind of justosition between like the
[55:37] timelessness of Paris and um this
[55:40] acceleration to AI and other things got
[55:42] me kind of like thinking a little bit
[55:43] about like economic history and like and
[55:46] but anyway, Gordon's book talks about a
[55:48] couple of things. one the thesis which
[55:50] is implied by the title is that actually
[55:52] the huge gains that the United States
[55:54] made came between like roughly 1870 and
[55:58] 1970 it's also a reminder that like the
[56:00] um the industrial revolution because
[56:03] this is kind of what the AI optimistic
[56:04] case is right well the industrial
[56:05] revolution worked out okay and wound up
[56:07] making people live longer and wealthier
[56:09] right for many years the industrial
[56:12] revolution produced terrible living
[56:14] conditions for for people right where
[56:16] you had like you know dickens and you
[56:18] had like child labor. You know, the most
[56:20] vivid image I have is he talks about
[56:22] like how much like horse manure there
[56:23] was on American streets, right? And you
[56:26] didn't have like indoor plumbing. And
[56:27] so, um, so it's a fascinating book. It's
[56:29] very detailed. It's not like a beach
[56:31] read. Um, but, um, but very compelling
[56:35] about all these massive changes that
[56:36] aren't well measured by GDP. And then I
[56:38] tie that to my France thing because it's
[56:40] like Europe has kind of opted for lower
[56:41] GDP growth, but arguably um, higher
[56:44] quality of life. Maybe in the best time
[56:45] talking about France this week, but
[56:47] still. Um,
[56:50] book number two is called You Can Just
[56:53] Do Things by Kate Hall. Kate is a former
[56:56] poker player and kind of a fellow
[56:58] traveler. Um, she was at one point the
[57:00] highest ranked um, uh, women poker
[57:02] player, female player in the world. She
[57:04] developed um, a a drug addiction and
[57:07] kind of dropped off the map for a couple
[57:09] of years. um but is now back to working
[57:11] in in the Bay Area scene. And it's kind
[57:14] of a self-help book for a certain type
[57:16] of of nerd that emphasizes the
[57:18] importance of of agency, but a lot of it
[57:21] really is about like how to handle
[57:24] personal relationships better and how
[57:27] poor people are at at communicating
[57:30] sometimes basic goals and needs and
[57:32] wants and relationships because they
[57:34] think it might feel weird or whatever
[57:35] else. But like she's like, "Look, just
[57:37] have honest conversations with people,
[57:38] get honest feedback, and that will that
[57:40] will go a long way in life." So, I
[57:42] recommend that book, too. Um, last one
[57:45] is another oldie but goodie. Um, there
[57:48] is not. So, I read a lot of like poker
[57:50] strategy books, like probably not
[57:51] appropriate for the Esper Klein show for
[57:52] recommendations. Probably the best poker
[57:55] related book of all time is called The
[57:57] Biggest Game in Town. It was written by
[57:59] a guy named Al Alvarez in 1983. It's a
[58:02] it's a short, compact read. So he was
[58:04] like a British literary critic and poet
[58:07] who did this thing where he kind of like
[58:09] went into the desert in Las Vegas when
[58:11] the World Series of Poker is coming into
[58:13] being and talks to like all these
[58:14] oldtime like Texas Roadhouse gamblers.
[58:17] It's very well written, a very maybe
[58:19] slightly overwritten, like kind of
[58:20] magaziney way, but like this part of the
[58:22] world's important to me, right? And it's
[58:26] one of the few books about gambling that
[58:29] doesn't fall into cliches and captures
[58:31] this part of the world that I'm
[58:32] fascinated by very well.
[58:33] >> That that book sounds great. Uh Nate
[58:34] Silver, thank you very Thank you.
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[58:56] Hey, hey, hey.
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