Sunday morning, gasoline wholesalers started calling their customers to announce 25-cent-per-gallon price increases, effective immediately. “Clearly, there’s a whiff of panic there,” said Tom Kloza, an oil analyst and adviser to Gulf Oil. GasBuddy’s Patrick De Haan estimated that some stations would raise prices by as much as 85 cents per gallon by week’s end. The national average hit $3.00 for the first time since December. By Monday, European diesel futures had jumped 23 percent to a two-year high. Jet fuel, gasoline, naphtha, and high-sulfur fuel oil followed. European natural gas futures surged more than 50 percent, the sharpest single-day move since 2022, the kind of move that comes from physical supply disappearing, not traders repricing risk.

On Saturday, February 28, the war between the United States, Israel, and Iran began. By Sunday, the Strait of Hormuz, through which roughly 20 percent of the world’s seaborne oil transits daily, had effectively shut down, not because Iran imposed a formal blockade but because the insurance market made transit impossible.

Lloyd’s List tracked just 23 vessel transits through the Strait on March 1, compared to a January daily average of 10.3 million deadweight tons. Traffic was down 81 percent week-over-week. Just one crude oil tanker transited the Strait that day. Zero LNG carriers. At least four vessels had been struck in and around the waterway, including the Palau-flagged tanker Skylight, hit by a missile and set ablaze within Omani territorial waters. One crew member was killed on the Marshall Islands-flagged crude tanker MKD Vyom. At least 150 crude and LNG tankers dropped anchor in open Gulf waters, clustered off the UAE, Saudi Arabia, and Qatar.

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Then the insurers pulled out. Seven of the twelve member clubs of the International Group of P&I Clubs, which provides marine liability coverage for approximately 90 percent of the world’s ocean-going fleet, issued cancellation notices for war risk coverage in the Persian Gulf. Steamship Mutual’s cancellation took effect 72 hours after midnight GMT on March 1. Maersk suspended all Hormuz transits. MSC instructed every vessel in or bound for the Gulf to proceed to designated shelter areas and suspended all worldwide cargo bookings to the Middle East. Hapag-Lloyd and CMA CGM halted transits and imposed emergency surcharges ranging from $2,000 per twenty-foot container to $4,000 for refrigerated units. Japanese lines NYK, Mitsui O.S.K., and Kawasaki Kisen halted all Hormuz operations. Services that could not transit Hormuz began rerouting around the Cape of Good Hope, adding weeks to delivery times.

Without war risk coverage, neither tankers nor LNG carriers can operate, regardless of whether the waterway is technically open. As Lloyd’s List put it, the Strait has been closed not by Iran but by shipping itself. “I don’t think Iran can shut down the Strait of Hormuz, but insurance companies and vessel operators can,” Kloza said. Even if the shooting stopped tomorrow, the insurance markets would take weeks or months to reopen.

The downstream effects compounded within hours. QatarEnergy halted LNG production at Ras Laffan, the world’s largest export facility, after Iranian drones struck the complex, and declared force majeure. Ras Laffan covers roughly a fifth of global LNG supply. Saudi Aramco shut units at Ras Tanura, the kingdom’s largest domestic refinery, after a drone strike. The loss of 4.3 million barrels per day of refined product exports from the Persian Gulf lifted refinery margins everywhere else on the planet. Diesel faces the most acute near-term physical pressure, according to Kpler, because it is the primary fuel for military logistics, regionally concentrated in supply, and the hardest petroleum product to replace quickly. Europe gets 45 percent of its jet fuel from the Middle East.

Brent crude surged as much as 13 percent intraday to above $82 a barrel, its highest level since January 2025. Barclays warned that Brent could reach $100 as the security situation spirals. JPMorgan said a prolonged disruption could push prices to $120. Deutsche Bank modeled a full Strait closure at $200. As recently as mid-February, Brent had traded in the low-to-mid $60s. Goldman Sachs had projected Q4 2026 Brent at $60; the EIA’s February forecast expected a $58 annual average. A Reuters poll had $63.85, with a geopolitical risk premium of $4 to $10 already priced in. None of these forecasts priced in a Hormuz closure, and by Saturday all of them were obsolete.

For American consumers, the arithmetic is already moving. A $10-per-barrel increase in crude translates to about 25 cents per gallon at the pump. Diesel price increases will bleed through to trucking surcharges, rail freight, and farm input costs just as spring planting begins. Seventy percent of consumers say gas prices affect their feelings about the economy, and energy costs feed into virtually every other price, from groceries to airfare to heating.

In every prior crisis when oil reached these prices, Houston responded. The 2008 spike produced 728,000 mining and logging jobs nationally (the BLS category that includes oil extraction) and 457,500 new positions in the Houston metro alone. High prices meant pain at the pump, but they also meant a compensating boom in the communities that produced the oil.

That industry no longer exists. The independents, the chaotic, debt-fueled ecosystem that converted price signals into production and employment, have been replaced by Wall Street’s capital allocators. The wildcatter era was volatile, environmentally damaging, and financially reckless in its debt-fueled form. Norway solved the governance problem with a sovereign wealth fund. Texas built a boom-bust cycle instead. But the underlying capacity to convert high prices into production and employment was sound. What replaced it is financially optimized and structurally unresponsive, an industry that no longer converts price signals into jobs regardless of what any president asks.

What follows starts with what $100 oil used to buy in Houston, and what it buys now, then documents the capital discipline regime that ensures the industry will not respond. It follows the price shock into the policy toolkit, where new Federal Reserve research shows the transmission from oil to interest rates has tripled in speed since 2021. Then it tracks the consequence almost nobody is discussing: oil shocks suppress fertility, the mechanism is now empirically documented at every link from barrel price to first birth, and the gendered structure of the employment shock means young men are hit hardest. It closes with what policymakers are getting wrong.

What did $100 oil used to mean?

Between 2010 and 2014, Houston added 457,500 jobs, with energy as the city’s primary economic engine. Direct oil and gas employment peaked at roughly 350,000 across the metro. But the real mechanism was the independents. In Corpus Christi, a land man could count 10 to 20 independent operators competing for acreage, each bringing in local doctors and lawyers as investors on well deals. The business model was straightforward: borrow to drill, prove reserves, ride the production upward or flip the asset to a larger player.

When prices were high, the model printed jobs and spread the money far beyond the wellhead. Roughnecks in Midland sent remittances to families in Houston’s eastern suburbs. Service company owners in Katy hired welders, dispatchers, equipment operators. For every direct upstream job, nearly three indirect and induced positions were supported across the Texas economy. A drilling boom meant overtime for pipe fitters, which meant down payments on houses, which meant work for roofers and electricians, which meant spending at grocery stores and car dealerships. Local banks lent against proven reserves. Landowners received royalty checks. School districts in the Permian funded new buildings with severance tax revenue. The cycle was volatile and occasionally ruinous in the busts, but during a price spike it converted global commodity prices into local wages, local consumption, and local tax revenue at scale.

Young men without college degrees could earn $80,000 to $120,000 a year on a rig crew. That income supported marriages, mortgages, and children in communities across West Texas, the Gulf Coast, and the Intermountain West. The boom towns had high birth rates not because of cultural attitudes but because stable income, affordable housing relative to wages, and confidence that the work would last a few years all arrived at the same time. When oil was high, Houston boomed, and the boom was labor-intensive enough to create the household conditions under which families form.

What does $100 oil mean now?

Energy and mining now accounts for 9.4 percent of Houston’s metropolitan employment, down from the city’s largest sector to its fifth-largest. Total upstream energy employment has fallen from approximately 350,000 at the 2014 peak to 290,000 by 2024. The Greater Houston Partnership projects that oil and gas extraction will lose positions in 2026, energy-adjacent manufacturing will lose positions, and administrative support will shrink. These were the baseline forecasts before the Strait of Hormuz closed.

Median household earnings in the metro area are $77,182. The energy cluster still pays $141,667 on average, but fewer workers can access that premium each year. South of the city, petrochemical plants in Texas City, Baytown, and Freeport use crude oil and natural gas as feedstock, not merely fuel, so rising crude prices hit them as direct input costs.

Thirty-year fixed mortgage rates remain between 6 and 7 percent, double the 2021 lows of roughly 3 percent. Monthly mortgage payments consume approximately 35 percent of median household income, a level that housing economists generally consider the threshold of unaffordability. The National Association of Realtors had predicted a housing recovery in 2026, driven by anticipated rate declines. An oil-driven inflation re-acceleration makes those rate cuts less likely.

In this industry’s new configuration, $100 oil is a cost with no compensating boom. The price increase flows through to every household. The employment surge that historically offset the pain is not coming.

Won’t the industry just drill more?

How Wall Street replaced the wildcatters

In 2008, when Brent peaked at $133 per barrel, the American energy sector’s response was immediate. Hundreds of independent E&P firms competed for acreage, services, and talent. When prices rose, production followed within months. The model was also debt-fueled and financially unsustainable, with many independents generating negative free cash flow for years.

The price crash of 2014–2015 triggered a wave of bankruptcies. The pandemic collapse of 2020, when West Texas Intermediate briefly traded at negative $37 per barrel, finished what the first crash started. Capital discipline became the industry’s permanent organizing principle, enforced by compensation structures, board mandates, and an investor base that would punish any reversion to the growth-at-all-costs model.

The result is visible in a single comparison (source: IEA/VisualCapitalist):

The pattern has only deepened. Between 2022 and the first half of 2025, nearly 45 percent of U.S. oil and gas companies’ cash flows went to dividends and share buybacks, according to Deloitte. Wood Mackenzie reported in late February 2026 that the 30 largest oil and gas companies now return 30 to 50 percent of operating cash flow to shareholders, cutting reinvestment rates to half of mid-2010s levels. The money no longer cycles through Houston’s economy. It flows to institutional shareholders and pension funds, most of whom are not in Houston and none of whom hire welders in Katy.

The first real test came in 2022. With crude above $100 for much of the year, the five largest publicly traded oil companies earned a combined approximately $199 billion. The global oil and gas industry earned nearly $4 trillion, more than double its recent annual average, according to IEA Executive Director Fatih Birol. The industry generated more cash than at any point in its history and used it not to drill but to buy back its own stock and raise dividends.

By early 2026, European majors including Shell, BP, TotalEnergies, and Equinor were cutting share buybacks as Brent lingered in the $60s, while U.S. supermajors ExxonMobil and Chevron reiterated their buyback pace. The industry’s response to lower prices was to return less cash and drill less. Its response to higher prices will be to return more cash and drill the same.

“Whether it’s $150 oil, $200 oil, or $100 oil, we’re not going to change our growth plans,” said Scott Sheffield, then CEO of Pioneer Natural Resources, now part of ExxonMobil following a $60 billion acquisition. EOG Resources’ Q4 2025 earnings call, held the day before the Iran strikes, committed to returning 90 to 100 percent of annual free cash flow to shareholders in 2026 and keeping oil production flat. Chevron recorded $12.1 billion in share buybacks during 2025, a record, and reiterated the pace through 2026. On Monday, ExxonMobil and Chevron shares surged more than 6 percent in pre-market trading. Investors were not pricing in a production surge. They were pricing in higher margins on the same barrels.

The machines that replaced the roughnecks

The rig count tells the story in one number. U.S. rigs declined from 750 in December 2022 to 550 for the week ending February 27, 2026, a 27 percent drop. Oil-directed rigs stood at 407, down 79 from a year earlier. In any prior era, a decline of that magnitude would have produced a corresponding drop in production. Instead, weekly crude output averaged 13.7 million barrels per day as of mid-February, just under the all-time high. In the Permian Basin, operators hold 239 rigs, down 65 from a year ago, yet production has barely budged, driven by extended-lateral drilling that now reaches 15,000 feet or more per well, up from 5,000 a decade ago.

The industry achieved extraordinary per-rig productivity, and in doing so, systematically eliminated the infrastructure for rapid scaling. The surplus rigs, the idle service crews, the speculative wildcatters who responded to price signals within months have all been deliberately dismantled.

The total upstream workforce is approximately 1 million full-time equivalents today, down from the 1.26 million peak. The industry shed 252,000 core jobs while producing substantially more energy. The labor required per barrel has been cut by more than half. Petroleum engineering graduates at U.S. universities collapsed from a peak of 2,615 in 2017 to roughly 623 bachelor’s degrees annually, a 76 percent decline. Some programs were nearly wiped out: Louisiana State down 89 percent, University of Oklahoma down 90 percent, Colorado School of Mines down 88 percent from their peaks. The mass layoffs of 2014 and 2020 damaged the industry’s reputation among young professionals so severely that high oil prices no longer pull students back. Even if companies reversed their financial strategy tomorrow, the workforce for a 2014-style surge does not exist.

The competitive ecosystem Houston lost

has done a great job of describing paradise lost of Houston’s (well Texas as it’s Midland does the drilling. Houston writes the checks) O&G ecosystem. Since late 2023, the sector has absorbed nearly $200 billion in mergers: ExxonMobil acquiring Pioneer for $60 billion, Chevron acquiring Hess for $53 billion, and Diamondback merging with Endeavor for roughly $26 billion, among others. Half of the Midland sub-basin, the most productive tight-oil formation on Earth, is now controlled by two companies. Exxon cut approximately 2,000 jobs globally following the Pioneer acquisition. Chevron cut approximately 600 from Hess Tower in Houston. In prior oil shocks, hundreds of firms making independent decisions collectively produced a rapid supply response. Two firms do not behave that way.

The EIA’s January 2026 forecast projected U.S. crude output holding near the 2025 record of 13.6 million barrels per day in 2026, then declining 2 percent to 13.3 million in 2027, what would be the first annual drop since 2021. Dallas Fed Energy Survey respondents reported breakeven prices of $61 to $62 per barrel in the Permian, barely above the EIA’s pre-crisis price forecasts. Wood Mackenzie’s analysis, published two days before the strikes, warned that production from current commercial projects across the 30 largest companies will fall nearly 40 percent between 2025 and 2040, a gap equivalent to adding two Permian Basins. The industry was already in decline before the Strait of Hormuz closed, and nothing about the current crisis changes the incentive structure.

Can’t the government do something?

If Houston’s oil industry is structurally configured not to respond, the question becomes what governments can do instead. Every major tool in the kit was designed for an industry that no longer exists.

Strategic Petroleum Reserve

The Strategic Petroleum Reserve holds roughly 415 million barrels as of late February 2026, about 57 percent of capacity. The Biden administration released 180 million barrels in 2022, the largest emergency drawdown in U.S. history, drawing the reserve to a 40-year low of 347 million by July 2023. Treasury estimated this lowered retail pump prices by 17 to 42 cents per gallon. The administration partially refilled it, purchasing or retaining roughly 200 million barrels at an average of $74.75. But DOE must still sell 99.6 million barrels by 2031 under existing congressional mandates, and Trump’s pledge to fill the reserve completely would cost an estimated $20 billion. At current levels with a maximum drawdown rate of 4.4 million barrels per day, the reserve covers roughly 94 days of net imports. A release can shave cents off the gallon for weeks. It cannot substitute for ongoing production if the Hormuz disruption persists for months.

The SPR could have been more than an emergency dump valve. Employ America, the research group that designed much of the framework the Biden administration adopted, proposed using fixed-price forward contracts and put optionsto create a soft price floor for domestic producers, offering insurance against the crashes of 2014, 2016, and 2020 that had conditioned capital discipline in the first place. DOE finalized a rule in October 2022 allowing fixed-price forward purchases, but execution lagged, and Employ America publicly warned that DOE appeared “spooked” by weak initial bids. Used strategically, the SPR could function as a market-stabilization mechanism that addresses one of the root causes of capital discipline. The administration that came closest ran out of time. The current administration has shown no interest.

OPEC+ agreed on March 1 to raise output by 206,000 barrels per day from April, exceeding analyst expectations of 137,000 but still less than 0.2 percent of global demand. The group holds roughly 3.5 million barrels per day of spare capacity, nearly all concentrated in Saudi Arabia and the UAE, the same countries now absorbing Iranian missile strikes. As Rystad’s Jorge Leon noted, if oil cannot move through Hormuz, production targets matter less than logistics and transit risk. The net supply loss, accounting for pipeline bypass capacity, is still 8 to 10 million barrels per day.

Interest rates

Raising interest rates does not put oil in the Strait of Hormuz. Yet the central bank response was immediate. Markets increased bets that the Fed would remain on hold at its March meeting and potentially through the summer. Monday’s ISM manufacturing data showed more than 70 percent of managers reporting higher prices in February, an 11.5 percentage point jump from the prior month, and that was before the oil spike hit. The Globe and Mail’s assessment was blunt: it is increasingly questionable whether the Fed will cut rates at all this year, and it may end up raising them. Ten-year Treasury yields posted their largest single-day advance since October.

The speed of this transmission has itself changed. A December 2025 SF Fed Economic Letter found that two-year Treasury yields now respond more than three times as strongly to oil supply news as they did in the pre-2021 period. The heightened sensitivity dates to the Fed’s 2022 liftoff and reflects markets pricing in a more aggressive central bank response to oil-driven inflation. For households, this means the pass-through from barrel to mortgage rate is faster and steeper than in any prior oil shock.

The pattern replicated globally. In Europe, Reuters reported that the disruption would cloud the outlook for both the ECB and Bank of England, potentially forcing postponement of further rate cuts. Deutsche Bank’s base case before the strikes was already for the ECB to hold through 2026, with the next move a hike in mid-2027. The timing is brutal: the eurozone had just hit its 2 percent inflation target in December for the first time in three years. Germany’s €500 billion fiscal expansion was supposed to provide a tailwind. An energy shock from the Gulf threatens to undo that progress in weeks. In Asia, OCBC economists warned that “monetary policy easing bias will be put to the test” across the region, with net energy importers facing simultaneous inflation, currency depreciation, and deteriorating trade balances. In Africa, nine countries including Nigeria, Kenya, and Egypt had cut rates just last month; Bloomberg reported Monday that the oil shock now threatens to derail that entire easing cycle.

The modeling underscores the scale. Capital Economics calculates that oil sustained at $100 a barrel would add 0.6 to 0.7 percentage points to global inflation. Oxford Economics models a more severe scenario: a Hormuz closure lifting Brent to $130 could push U.S. inflation to 4.5 percent and eurozone inflation close to 4 percent, derailing expectations of monetary easing entirely.

The question is whether tightening in response to a supply shock is the right prescription. Bernanke and Blanchard found that energy price shocks accounted for nearly all of inflation’s rise in late 2021 and early 2022, and nearly all of its decline in the second half of 2022. Tight labor markets contributed negatively to inflation in 2020 and early 2021.The wage-price spiral never materialized. Real wages fell. If central banks hold or cut into an oil-driven inflation spike, they risk unanchoring inflation expectations. If they raise rates, they apply what Bernanke’s own research showed was the wrong tool for the problem. As one macroeconomic analyst noted, the near-term implications are hawkish regardless. But the industry transformation described in Section III makes the dilemma worse on either path. In the old system, high prices triggered a production surge that moderated prices within months, keeping tightening cycles short and shallow. That self-correction no longer happens. Central banks tighten, prices do not moderate through new supply, and the costs, higher mortgage rates, slower hiring, weaker currencies in import-dependent economies, compound on households with no offsetting energy boom to cushion the blow.

Fiscal buffers

The fiscal buffers that governments used to cushion the last oil shock have been substantially depleted. Global public debt reached $102 trillion by 2024. Following the post-COVID expansions, 143 countries implemented fiscal consolidation measures affecting an estimated 85 percent of the global population: 91 governments capped public-sector wages, 80 cut energy and food subsidies, 86 raised consumption taxes, and over 120 restricted social safety net eligibility.

Renewable energy

If energy price shocks drive inflation, expanding energy supply is the direct response. Every gigawatt of renewable capacity installed is a gigawatt of demand permanently removed from the fossil fuel market. Between January and May 2025, China alone added 198 gigawatts of solar and 46 gigawatts of wind. Total installed Chinese solar capacity now exceeds 1,000 gigawatts, roughly half the world’s total.

Current U.S. policy moves in the opposite direction. The administration’s legislative agenda, the One Big Beautiful Bill, would phase out wind and solar production tax credits by 2027 and introduce new excise taxes on renewable energy projects using Chinese-manufactured inputs, reducing renewable energy capacity additions substantially over the next decade. Independent analyses project this could increase average household energy costs by approximately $400 per year within a decade from ending renewable credits alone.

A major oil supply disruption happening at the same time as legislation that reduces alternative energy supply capacity increases household exposure to exactly the kind of price volatility now unfolding. The administration authorized the military action that created the supply shock. It is pursuing legislation that reduces the capacity to build the alternative supply that would buffer against it.

What does an oil shock do to birth rates?

The metric that hides the problem

The Total Fertility Rate, the number every government tracks and every headline cites, loses critical information by collapsing two independent measures into one. A 2025 study in Scientific Reports (a Nature portfolio journal) by Stephen J. Shaw, analyzing data from 314 million mothers across 33 higher-income economies and 1,470 country-years, demonstrates the problem.

The decomposition is straightforward:

TFR = TMR × CPM

The Total Maternal Rate (TMR) measures the proportion of women who become mothers. Children per Mother (CPM) measures the average family size among those who do. TFR is the product.

These two components are statistically independent. Shaw confirmed this through breakpoint co-occurrence testing, wavelet coherence analysis, and Mutual Information testing. When TFR declines, policymakers cannot tell whether fewer women are entering motherhood or whether mothers are having smaller families. The policy implications are different in kind, not just degree. The 2024 UN World Fertility Report mentions childlessness twice across 62 pages.

What oil shocks do to motherhood rates

Japan provides the clearest case. When the Oil Shock struck on October 19, 1973, the TMR fell sharply across all 47 prefectures simultaneously. Shaw subjected this to a binomial test: the probability of all 47 showing declines between 1974 and 1975 by chance is less than one in ten thousand. Monthly birth data pinpoints the onset to October–November 1974, consistent with an approximately 12-month conception-to-birth lag from the shock. CPM barely moved. The pattern replicated across Italy and the United Kingdom in 1974: near-identical TMR collapses, no corresponding shift in family size among mothers.

The oil crisis suppressed entry into motherhood rather than reducing family size among women who were already mothers.

The United States offers the more recent case. TFR in 2016 was identical to TFR in 1980: 1.82. But TMR had fallen from 76.1 percent to 69.4 percent, nearly 7 percentage points, masked by a simultaneous rise in CPM. Mothers were having slightly larger families, offsetting the growing number of women who never became mothers. Anyone relying on TFR alone would have missed it. The structural break coincided with the 2008 financial crisis.

Oil prices climbed toward $147 per barrel by July 2008, and gasoline hit $4 per gallon early that year, well before the Lehman collapse. The housing bubble burst partly because households already strained by energy costs began defaulting on mortgages. Fertility rates that had been rising across advanced economies reversed sharply. In the United States, TFR fell from 2.12 in 2007 to 1.8 by 2016. In Greece and Spain, which suffered a double-dip recession, TFR dropped from 1.5 to about 1.3. Across the five largest developed economies, 350,000 fewer babies were born in 2012 than in 2008.

But TFR again obscures what actually happened. The sustained decline was driven more by falling first births than by higher-order births, consistent with rising childlessness. Kearney and Levine (2022) found that the Great Recession contributed to the initial decline, but that women born after the mid-1980s continued having fewer first births at every age, even as the economy recovered. Comolli and Bernardi (2015) showed the mechanism: the downturn increased childlessness by lowering first-birth rates among women in their late thirties, women for whom delay meant, biologically, permanent childlessness. Demographers at the Carsey School noted the same pattern in the Great Depression, which produced the highest level of childlessness ever recorded in U.S. history. The economic shock was temporary. The TMR decline was not.

In Europe, the strongest fertility declines tracked the worst labor market deterioration: Southern Europe, Ireland, and parts of Central and Eastern Europe. The academic literature is consistent: childless young adults are most affected by economic downturns, and the longer a recession delays first births, the more likely those delays become permanent.

France illustrates the pattern in contemporary form. Between 2013 and 2023, CPM remained virtually stable at 2.3 to 2.4 children per mother. TMR dropped from 85.0 percent to 72.8 percent, over 12 percentage points in a single decade.

Has this already happened?

Before the 2022 energy crisis, something surprising had been happening across much of the developed world: fertility was recovering. The IMF documented that fertility rates had been rising across advanced economies in the decade before 2008. Even then, it is not all doom and gloom. France’s TFR held above 1.8 through 2017 (without immigrants factored in). Bulk of the Nordic countries maintained rates near or above 1.7 for most of the decade. The Czech Republic climbed steadily from 1.28 in 2003 to 1.83 by 2021. The United States saw a mini-baby boom during COVID, which ended in 2023, around the time of rate hikes and oil prices biting. The “Discourse” (or the more serious parts of it) debated whether the recovery was real or fragile. The 2022 energy shock answered that.

Russia’s invasion of Ukraine sent energy prices across Europe to levels not seen in a generation. Natural gas prices on the Dutch TTF benchmark rose more than tenfold from 2021 lows. Consumer price inflation in Central Europe, where dependence on Russian gas was heaviest, hit double digits and stayed there. The countries that had been recovering fastest proved the most vulnerable.

Hungary had been the poster child for pronatalist policy. A decade of aggressive interventions, including zero-interest loans, tax exemptions for mothers, debt forgiveness, and housing grants, had lifted the country’s TFR from 1.23 in 2011 to 1.59 by 2021, from worst in the EU to ninth best. Then the energy crisis hit. Hungary’s inflation surged above 25 percent in early 2023, driven heavily by energy and food costs. TFR fell from 1.59 in 2021 to 1.56 in 2022 to 1.51 in 2023, then collapsed to 1.39 in 2024, Hungary’s lowest rate in more than a decade, erasing most of the gains from a decade of policy effort. Marriages fell from 72,000 in 2021 to 50,200 in 2023 to 46,550 in 2024, with the sharpest declines among young people in their mid-to-late twenties. The Hungarian Conservative acknowledged that “the COVID-19 pandemic, the war in Ukraine, the energy crisis and economic difficulties on a global scale have also shaken families’ sense of security.” The most expensive pronatalist program in Europe could not withstand two years of energy-driven inflation.

Going back to the Czech Republic. Czecha’s collapse was even more dramatic. As recently as 2021, Czechia had one of the highest fertility rates in Europe at 1.83, higher than France. Then consumer prices surged past 15 percent inflation, and real wages fell in every quarter of 2022 and 2023. TFR dropped 10.4 percent in a single year, from 1.83 to 1.64, the largest single-year decline recorded among EU member states. It kept falling, to 1.53 in 2023 and then 1.37 in 2024, the lowest since records began in 1806, with only 84,000 births. The head of demography at Charles University warned that current-year fertility could reach 1.25. The OSW Centre for Eastern Studies linked the decline directly to falling living standards and collapsing security perceptions: the share of Czechs expressing concern about the threat of war rose from 11 percent in 2021 to 43 percent by 2023. Czech demographer Eva Waldaufová found that 89 percent of survey respondents cited a lack of affordable housing and 88 percent cited financial uncertainty as reasons for having fewer children than desired.The majority still wanted two children but were not reaching that number.

Shaw’s framework predicts the TMR component absorbed the blow disproportionately. The marriage collapses in Hungary and the first-birth delays in Czechia point in the same direction: it is entry into parenthood, not family size among parents, that the energy shock disrupted.

Who is going to be hit hardest in 2026?

Young men are going to be hit harder than any other demographic group. Young men are the population whose economic status most directly determines whether first births happen.

Start with the labor market channel. Elder and Payne (2024), writing in Energy Economics, found that oil price uncertainty shocks produce asymmetric effects on U.S. unemployment by gender, with men disproportionately affected. The industries most exposed to oil-driven cost shocks (construction, manufacturing, transportation, logistics) are the same industries that disproportionately employ young men without college degrees. When diesel prices rise 23 percent in a day, as they did on Monday, the trucking companies, freight operators, and construction firms that absorb those costs respond by freezing hiring or cutting hours.

The connection between male employment and first births is not speculative. A 2025 study by Han and Uchikoshi, published in the Chinese Sociological Review, found that the entire Korea-Japan fertility divergence is concentrated in women aged 25 to 29, and that approximately a third of Korea’s decline in this age group traces to a near-tripling of male economic inactivity. Among Korean men aged 25 to 29, the share neither working nor seeking work rose from roughly 10 percent in the mid-1990s to 30 percent by the early 2020s. In Japan it barely moved. Male inactivity suppresses first births specifically: men who are not in the labor force do not marry, and in both countries, marriage remains effectively a prerequisite for childbearing.

The 2026 oil shock arrives into this dynamic through three reinforcing channels. Diesel surcharges and rising input prices will slow hiring in male-dominated blue-collar sectors during what should be the spring ramp-up in construction and agriculture. The SF Fed’s finding that Treasury yields now respond three times more strongly to oil supply news means mortgage rates will rise faster than in any prior shock, pushing homeownership further from reach for young couples. And seventy percent of consumers already say gas prices shape their perception of the economy, so the psychological effect of watching pump prices climb daily compounds the material cost. For women in their mid-to-late thirties already at the edge of the biological window, any postponement of a partner’s proposal or a couple’s timeline risks becoming permanent childlessness.

Each successive shock operates on a lower baseline, which means the same-sized disruption does more damage. A 5-percentage-point TMR decline from 90 percent leaves 85 percent entering motherhood. The same decline from 60 percent leaves 55 percent entering motherhood and 45 percent remaining childless. The same absolute shock produces qualitatively different outcomes depending on where it lands.

The following table presents TMR data from Shaw’s study (please note, I will update these to DataWrapper when I have some spare time)

A TMR of 47.9 percent means that more than half of South Korean women are projected to remain childless.

We can calculate the TMR required to achieve replacement-level fertility (TFR ≈ 2.1) given each country’s current CPM:

For South Korea, replacement TMR would need to exceed 100 percent, meaning replacement fertility is mathematically impossible through motherhood rates alone, regardless of policy. The Han and Uchikoshi data explain why: male economic inactivity has suppressed marriage rates so severely that no achievable increase in family size can compensate.

What are policymakers getting wrong?

Houston’s wildcatter industry converted $100 oil into jobs, wages, and community investment. Houston’s current industry converts the same price into share buybacks and dividends that leave the community. The households experiencing the price shock are the same. What differs is whether any of that money circulates back.

Brent has surged nearly 28 percent year-to-date and analysts are warning of $100 or higher if the Hormuz disruption persists. The starting conditions are worse on every dimension: higher rates, depleted fiscal buffers, weaker labor markets, and a demographic baseline with less margin than any previous shock hit.

Three assumptions underpin the current policy response, and none of them hold. Energy policy assumes the industry responds to prices, but consolidation and capital discipline ensures it will not. Standard monetary policy assumes supply-side self-correction will shorten tightening cycles, but higher interest rates aren’t going to move oil out of a war zone. Demographic policy targets family size among mothers when the evidence shows the binding constraint is the rate of entry into motherhood itself, ie young people’s very ability to get some economic stability in their lives. Each assumption was calibrated to conditions that no longer exist.

To the right: the American oil and gas industry are not coming to save you. The CEOs have said so publicly, on earnings calls, to shareholders, in plain English. $100 oil, $150 oil, $200 oil, and the production plan does not change without external pressure. The rigs are not coming back without a fight. Wall Street is hellbent on making sure roughnecks are not coming back. The wildcatters who would have responded to this price signal were bought out by ExxonMobil and Chevron, and those companies will return the windfall to shareholders, not to the Permian. “Drill, baby, drill” is a slogan for an industry that no longer exists. If you want energy prices down, you need every tool on the table, including the ones you have spent the last decade trying to kill.

To the left: you are fully aware that this war does not mean the economic damage manages itself. The Strait is closed. Prices are rising now. Every week without emergency action on refinery coordination and non-US diplomatic efforts to reopen shipping lanes is a week the damage compounds into the lives of the young workers, renters, and so many innocents. The window to prevent the downstream damage is closing fast.

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Walk into a Best Buy today and the experience is fine-ish. The floors tend to be clean. The displays work. A blue-shirted employee can probably point you toward the right laptop, and if you’re lucky, the one who helps you actually knows the difference between the models. The Geek Squad desk may or may not have a line. The store-within-a-store sections for Samsung and Apple are slick and impersonal, but without the feel you get at a real Apple Store. It is competent, not revelatory. Best Buy became good enough, and in brick-and-mortar retail, good enough is a high bar.

Now try to walk into a Joann Fabrics. You can’t. The last store closed on May 30, 2025. All 800-plus locations were liquidated. Nineteen thousand workers lost their jobs. But in the years before the end, former employees and customers described what it was like to watch the chain disintegrate from the sales floor: bare shelves, skeleton crews, fabric bolts in disarray, nobody at the cutting counter who knew what they were doing. A former district manager told Fortune the problem was self-inflicted: “the business is there.” What was missing was the capacity to run it properly. The stores had been hollowed out underneath the customers.

Best Buy’s customer experience didn’t transform. It stabilized. The company stopped the bleeding, restored basic competence, matched Amazon’s prices, and gave vendors a reason to invest in its stores. That was enough. Joann, meanwhile, didn’t lose to some technological revolution that made fabric stores obsolete. It collapsed because it could no longer afford to stock its shelves, staff its cutting counters, or maintain the store experience that had sustained a loyal customer base for decades. Ninety-six percent of Joann’s stores were cash-flow positive when it first filed for bankruptcy in 2024. The demand was there. The business worked. Something else killed it.

Understanding why businesses actually fail matters regardless of where you sit politically, because it is a matter of short- and long-term governance. When a retailer fails, state and local governments pick up the tab: lost sales tax revenue, unemployment insurance claims, economic development incentives to attract replacement employers. If those failures are driven by demand shifts, that spending is a reasonable cost of economic transition. If they’re driven by capital structure decisions made at acquisition, taxpayers are subsidizing the back end of a private transaction they had no part in. If we misdiagnose Joann as a story about consumer preferences or e-commerce disruption, every downstream decision, from unemployment policy to pension allocation, starts from the wrong premise.

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In 2010, Joann was the nation’s largest specialty fabric and craft retailer, founded in 1943 by two German immigrant families in Cleveland who combined the names of their daughters, Joan and Jacqueline Ann, to name the store. It had roughly 850 stores, carried zero debt, and its stock price hit a record high that year. In 2012, Best Buy’s stock had cratered below $15 per share. Analysts were writing its obituary. The company in crisis survived. The healthy one, beloved by wine moms, Etsy witches, and cosplayers, is gone.

What it looks like is that Joann was targeted precisely because it was healthy. It was loaded with debt to finance its own acquisition, and milked for returns until it could no longer invest in adaptation. Category dynamics and management quality matter, and we’ll address them, but the balance sheet story comes first.

The retail apocalypse in context

The phrase “retail apocalypse” took off around 2017, when more than 12,000 physical stores closed in a single year. According to Coresight Research, U.S. retailers announced more than 7,300 store closures in 2024, a 57 percent increase over 2023. Projections for 2025 suggest closures could reach 15,000.

The popular narrative attributes this to the “Amazon effect.” That’s a small part of the story. E-commerce still accounts for roughly 16 percent of total retail sales, per Census Bureau data. Amazon’s share of total U.S. retail is about 4 percent. Total retail sales have continued to grow. It’s a reshuffling, not an extinction.

The Amazon narrative also flatters Amazon. Take Toys “R” Us: in 2000, the toy chain signed a 10-year exclusive deal to sell on Amazon’s platform, paying $50 million a year and effectively surrendering its own e-commerce development. By 2003, Amazon was letting competitors sell toys on the same platform. Toys “R” Us sued, won, and terminated the deal in 2006, but it had lost six years of e-commerce development during exactly the period when online retail was being built. The company that then got loaded with $5.3 billion in LBO debt in 2005 was already competing with one arm tied behind its back. When Toys “R” Us collapsed, the narrative was “Amazon killed the toy store.” And sure, Amazon helped, but it was the LBO that extracted the cash flow and actually killed the company. Amazon got the credit, which translated into a market narrative about e-commerce invincibility that has bolstered its valuation ever since.

That narrative doesn’t hold up in reverse, either. Since acquiring Whole Foods for $13.7 billion in 2017, Amazon has failed at nearly every brick-and-mortar format it has attempted. In January 2026, it closed all its Amazon Fresh grocery stores and Amazon Go convenience stores, essentially admitting the stores didn’t work. Before that, it shuttered its bookstores, its 4-Star shops, and several other formats. Amazon is very good at bits but has repeatedly failed at atoms. On that note of Whole Foods, I don’t know if would agree with anything I say, but he writes a great substack on broader grocery business.

The Checkout Grocery Update

The Essential Take on the $1 trillion U.S. Grocery Industry.

By Errol Schweizer, Grocery Nerd

The retailers who actually did the hard work of going online get written out of the story. Walmart’s e-commerce share has grown from under 5 percent of its sales in 2018 to roughly 18 percent in 2024, with online sales growing 22 percent globally in fiscal Q4 2025. It leveraged 4,700 physical stores as fulfillment nodes, with 90 percent of Americans living within 10 miles of a Walmart. Home Depot acquired Blinds.com in 2014, an online-only window coverings retailer that was outperforming Home Depot in its own category, then used its e-commerce platform to build out broader online custom-order capabilities. The apocalypse narrative erases them.

The other factors matter at least as much as e-commerce: an oversupply of retail square footage (mall construction between 1970 and 2015 grew at more than twice the rate of population), shifting consumer preferences, the aftershocks of the Great Recession, and the financial engineering of leveraged buyouts that loaded retail companies with debt they could not service, debt that consumed the cash flow they needed to adapt. A retailer that fails because customers no longer want what it sells is fundamentally different from a retailer that fails because its cash flow is consumed by debt service rather than reinvestment. Both are called “bankruptcy,” but the causal mechanisms and the policy implications are entirely different.

Two Companies, Two Ownership Models

Best Buy’s crisis

When Hubert Joly took over as CEO in September 2012, rather than arriving with a grand strategy, he visited stores in a blue polo shirt tagged “CEO in Training.” He learned from a store employee at a pizza dinner that typing “Cinderella” into Best Buy’s search engine returned Nikon cameras.

His operational moves were shrewd. He price-matched Amazon and converted showrooming from a vulnerability into a sales channel. He invited Samsung, Apple, Microsoft, and other vendors to create store-within-a-store experiences, turning Best Buy’s physical footprint into a marketing asset that vendors would pay to support. He made over $1 billion in cost cuts: supply chain optimization, shuttering the venture capital unit, and eventually hundreds of corporate layoffs. The layoffs came last, not first. He exited unprofitable international ventures, including the European joint venture with Carphone Warehouse and the 184-store Five Star chain in China.

Joann’s “rescue”

In 2011, the year before Joly arrived at Best Buy, private equity firm Leonard Green & Partners acquired Joann in an unsolicited bid for $1.6 billion, paying $61 per share, a 34 percent premium over the stock price when analysts were placing targets around $53. That premium itself became part of the debt burden.

The acquisition was structured, as leveraged buyouts typically are, with the debt placed directly on Joann’s balance sheet. The buyout was financed by JPMorgan Chase, Bank of America, and TCW/Crescent Mezzanine. Overnight, a company with zero debt became a company with more than a billion dollars in obligations, plus annual management fees of $5 million payable to Leonard Green.

The standard PE narrative holds that private equity firms acquire underperforming companies, bring operational discipline, and generate returns through genuine improvement. A European study published in the Journal of Corporate Finance, examining buyout targets across 15 EU countries, found the opposite: PE firms typically select companies with lower financial distress risk. Being good at what you do makes you a target for extraction, not a beneficiary of improvement. Joann, debt-free and profitable, was the model LBO candidate.

Parallel trajectories

From 2012, the paths diverged. Joly had the luxury of retaining Best Buy’s cash flow for reinvestment. Non-GAAP return on invested capital rose from 9.2 percent in fiscal 2012 to 13.6 percent by fiscal 2016. Employee turnover was cut in half. Total shareholder return from the end of fiscal 2013 to Joly’s departure in 2019 was 335 percent, compared to 104 percent for the S&P 500.

At Joann, every dollar generated had to be divided between operating the business and servicing debt, including Leonard Green’s management fees, which totaled roughly $50 million over the ownership period. Interest payments in some years topped $100 million on a business with thin retail margins. Debt peaked at $1.3 billion in 2019, according to Crain’s Cleveland Business. Much of it carried variable interest rates, so when rates rose in 2022-2023, Joann’s costs spiked as its revenues declined post-pandemic. The company sold its Ohio corporate headquarters for $34.5 million, converting an owned asset into a lease obligation: immediate cash at the cost of higher long-term expenses.

Joly had seven years of stable leadership to execute his turnaround. Joann cycled through nine CEOs in thirteen years. One of them, Jill Soltau, brought in McKinsey consultants to analyze the workforce, which led to layoffs, continuing a pattern of cutting the knowledgeable in-store labor force that had long been the chain’s competitive advantage. GlobalData analyst Neil Saunders noted that weakening store standards and declining customer service, “partly because of staffing cuts,” made stores less desirable. Customers who needed lower prices drifted to Hobby Lobby. Those who valued convenience went online.

The Structural Precondition

Best Buy was publicly traded with no crushing debt overhang, able to retain cash flow, pursue a multi-year turnaround, and operate without a private equity sponsor claiming a share of every dollar. Joly had time and capital.

Consider the counterfactual. If Best Buy had been taken private in a leveraged buyout in, say, 2011, when its stock was depressed and it looked like a classic distressed target, the acquirer would have loaded it with billions in debt. Renew Blue would have been impossible. Dick Schulze did consider a take-private bid, but never followed through. That non-event may have been the most consequential moment in the company’s recent history.

The Hobby Lobby counterfactual

There’s another comparison worth making, not with Best Buy but with Hobby Lobby, Joann’s direct competitor in the crafts space. According to former Joann executives, Hobby Lobby’s rise as a national rival was the tipping point for Joann’s competitive decline.

Hobby Lobby is family-owned by the Green family (no relation to Leonard Green & Partners, despite the coincidence). As one former Joann executive put it, Hobby Lobby “didn’t have hundreds of millions in debt to worry about, or management fees.” That cost advantage flowed straight to the consumer.

Joann responded by cutting costs, which degraded its customer experience, which drove more customers to Hobby Lobby: a spiral it never escaped. The proximate cause of death was competition and declining sales; the underlying cause was an ownership model that stripped the company of its capacity to compete.

The crafts retail category was facing structural pressures even before Leonard Green arrived: generational shifts in hobby participation and online competition from Amazon and Etsy. A debt-free Joann would not have been immune to them. But there is a vast distance between gradual competitive decline and total liquidation of 800 stores in a matter of months. What bridges that distance is the balance sheet.

Death by Degrees

The pandemic mirage

COVID-19 briefly appeared to save Joann. Revenue surged nearly 25 percent year-over-year in the first nine months of 2020. Net income swung from a $188 million loss to $174 million in profit across the first three quarters. Leonard Green seized the moment to take the company public again. The 2021 IPO raised $131 million, roughly 30 percent below its target, with proceeds going to pay down debt while Leonard Green remained majority shareholder. This was an exit attempt, not a growth strategy.

Sales collapsed soon after, and the stock cratered below a dollar, triggering Nasdaq delisting.

Double bankruptcy

Joann filed for its first bankruptcy in March 2024, emerging 40 days later as a private company after cutting $505 million in debt. But even halving the debt wasn’t enough. Less than a year later, in January 2025, Joann filed again. This time, no buyer materialized. Liquidation followed. The last store closed on May 30, 2025.

Leonard Green had collected management fees throughout, and the fund vehicle that acquired Joann (Green Equity Partners V) earned an 18.5 percent internal rate of return across the fund’s portfolio. Michaels acquired Joann’s intellectual property and brands but none of its stores.

The Great Filter: PE as Predator, Not Doctor

Joann’s story would be troubling enough as an isolated case. It is not.

The bankruptcy rate

Researchers Brian Ayash and Mahdi Rastad at California Polytechnic State University found that approximately 20 percent of large LBOs go bankrupt within 10 years, compared to 2 percent among matched control firms that remained publicly traded. In retail specifically, 41 percent of LBOs executed between 1980 and 1995 led to bankruptcy. Americans for Financial Reform estimated that from 2015 to 2020, more than half of all retail bankruptcies involved PE-owned companies, eliminating nearly 542,000 jobs.

Some researchers have found that PE fund experience mitigates bankruptcy risk, but Joann was backed by one of the most experienced retail PE firms in the country. Experience didn’t save it.

The extraction playbook

Appelbaum and Batt describe a recognizable playbook: acquire a healthy, cash-generating business through an LBO; load it with debt used to finance its own purchase; extract fees; execute dividend recapitalizations and sale-leasebacks; cut labor to free cash for debt service; and attempt an exit through sale or IPO. If the company fails, the PE firm’s losses are capped at its equity stake while the company and its workers bear the downside.

Joann’s trajectory maps almost perfectly onto every step.

The roster

The list of PE-owned retail chains that have filed for bankruptcy or liquidated includes Toys “R” Us, Payless ShoeSource, Sports Authority, Gymboree, rue21, The Limited, Barneys New York, and many others.

Toys “R” Us is the canonical parallel. In 2005, KKR, Bain Capital, and Vornado acquired the company for $6.6 billion, of which only $1.3 billion came from the buyers’ own pockets. Before the buyout, Toys “R” Us had $2.2 billion in cash reserves; by 2017, reserves had been depleted to $301 million while debt had ballooned to $5.2 billion. Interest payments consumed 97 percent of operating income in 2007. The company still held a 20 percent share of all U.S. toy sales. It was operationally profitable absent the debt. The PE consortium collected $470 million in fees and interest over the course of ownership. Employment fell from 60,000 to 33,000 by liquidation.

The Cost-of-Capital Asymmetry: How the Machine Runs

PE firms have access to cheaper capital than their portfolio companies deserve, and that asymmetry powers the entire extraction cycle.

Banks provide the debt, institutional investors (pension funds, sovereign wealth funds, endowments) provide the equity, and the PE firm itself contributes remarkably little. As Appelbaum and Batt calculated, PE partners invest roughly 0.6 percent of the purchase price of acquired companies while claiming 20 percent of any gains.

What LPs actually get

That capital flows to PE not because the underlying investments are demonstrably superior but because the fee structure makes it lucrative for intermediaries. Phalippou’s research at Oxford found that the average LBO fund charges roughly 7 percent per annum in total fees, with gross returns of around 18 percent and net returns to investors of roughly 11 percent, approximately matching public equity indices in recent decades. The wealth creation that does occur accrues disproportionately to the PE partners themselves. The number of PE multibillionaires rose from 3 in 2005 to 22 in 2020.

A 2025 Harvard Law study found that the risk-adjusted performance of PE for pension plans was “approximately zero,” except for buyout funds, which showed modest outperformance partly explained by value-factor exposure rather than genuine alpha. When debt is abundant, PE firms overpay, entry multiples rise without corresponding improvements in outcomes, and more companies go bankrupt. The PE firms themselves, shielded by limited liability and non-recourse debt structures, bear comparatively little of this downside.

The pipeline

Ohio’s State Teachers Retirement System provides a concrete illustration: the pension eliminated cost-of-living increases for retirees while continuing to pay PE management fees on committed-but-undeployed capital, a practice one audit called “money for nothing.” If those fees were eliminated, the pension estimated it could generate $143 million annually; enough to restore the cost-of-living adjustment.

The people who bear the ultimate cost are the same people at both ends: retail workers in Hudson, Ohio, where Joann was headquartered, losing their jobs, and retirees in Columbus losing their cost-of-living adjustment.

If you are interested in this pensions of the puzzle, you might like this

What the Divergence Really Tells Us

The Best Buy-Joann divergence operates on three levels. The primary factor is ownership structure: Best Buy retained the capacity to reinvest its cash flow, pursue a patient turnaround under stable leadership, and respond to competitive pressure. Joann had none of these options after the LBO. The secondary factor is leadership quality, but this is partly a function of ownership. Public companies competing for CEO talent in a transparent market with equity-linked compensation attract different candidates than PE portfolio companies on five-to-seven-year exit timelines. The third factor is category dynamics: consumer electronics had structural features favoring brick-and-mortar adaptation, while craft retail had its own defensible advantages (tactile fabric selection, knowledgeable staff, the inspiration of browsing) that depended on exactly the investments the LBO debt forced Joann to cut.

A brilliant CEO with $1 billion in LBO debt and $100 million in annual interest payments has far fewer options than a brilliant CEO with a clean balance sheet.

A debt-free Joann might still have struggled against Hobby Lobby and online competition, and might have contracted. Leonard Green’s actual profit or loss on Joann is unclear; the PE industry’s opacity makes definitive accounting difficult, and we have been unable to find detailed data on specific dividend recapitalizations at Joann, if any. What is documented (management fees, interest payments, sale-leaseback, the failed IPO) is damning enough.

In the retail sector specifically, characterized by thin margins, high fixed costs, and the need for continuous reinvestment, the LBO model has produced results that demand a structural explanation, not just a case-by-case one.

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Shiseido hit the wall in 2023. UNIQLO hit it in 2024. Toyota is hitting it now.

The sequence isn’t coincidence. In November 2025, Shiseido announced a ¥52 billion loss, the largest in its 153-year history. Activist investors had acquired a 8.30% stake. Innovation centers in Singapore and Korea were shuttering. Some 2,000 employees had been laid off across three rounds. The standard narrative: China exposure bad, domestic markets good.

The reality is just delightfully messier, which makes it more instructive. Shiseido suffered both a structural shock it couldn’t control and execution failures it absolutely could have avoided. Most coverage conflates these. Companies watching should separate them, because only one is avoidable.

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Ever-eroding, yet Still Standing “Made in Japan” Premium

In 2017, when Shiseido committed approximately ¥1,385 billion to new Japanese manufacturing capacity, the China thesis looked solid. By February 2018, the company had crossed ¥1 trillion in revenue three years early. China sales grew 20.1% that year. The stock had quintupled from ¥1,500 in 2014 to over ¥8,000. CEO Masahiko Uotani, brought in from Coca-Cola Japan, declared that “all regions are growing” and “momentum is accelerating.”

China’s middle class was expanding. Japanese cosmetics carried cachet, perceived as safer, higher-quality. The “Made in Japan” premium was real and monetizable. Against this backdrop, aggressive investment was the consensus view. Analysts praised the strategy. Competitors did the same.

Kao Corporation, Japan’s next largest cosmetics company by domestic market share, took the opposite approach: cautious China entry, limited exposure, domestic focus. While Shiseido built China to 25% of revenue, Kao kept exposure modest. Kao avoided the catastrophic collapse and missed the upside of the boom. During the good years, Shiseido dramatically outperformed. On that note, Kao is rapidly becoming more aggressive starting 2024.

Was Shiseido’s strategy wrong in expectation, or merely unlucky in outcome? The Fukushima water release was not foreseeable in 2017, though in 2023, when ALPS processing water was released, Chinese consumers reduced purchases of Japanese cosmetics. The severity of guochao nationalism (the rise of Chinese domestic brands like Florasis and the “new Chinese aesthetic”) was not widely predicted. COVID’s lasting impact on Chinese consumer behavior could not have been anticipated. Shiseido made a reasonable bet that went badly, which is different from making a bad bet.

What's clearer in retrospect: Shiseido's strategy lacked optionality. The company captured upside but had no downside protection. Kao's caution (not typically associated with strategic advantage) preserved flexibility, allowing it to navigate the collapse without catastrophic exposure. Now Kao is attempting what Shiseido failed to do: aggressive growth combined with real hedges (geographic diversification, manufacturing flexibility). Whether they can sustain both or end up overextended like Shiseido remains to be seen.

China Comes For All Industries

The China cycle repeats across industries because it’s policy, it’s clearly not an accident.

Foreign companies enter China seeking growth, build up local competitors through market development and knowledge transfer, then watch their position erode as Chinese brands capture the capabilities they helped create. Harvard researchers studying the auto sector measured this directly: when a joint venture model scored one standard deviation higher on quality, affiliated domestic firms improved by 0.098 standard deviations in those same dimensions. Worker flows and supplier overlaps transmitted roughly 54% of this knowledge transfer. The USTR’s Section 301 investigation documented the explicit strategy: “introduce, digest, absorb, and re-innovate” foreign technologies, a deliberate approach outlined in China’s technology development plans.

What makes China’s approach distinctive is its comprehensiveness. No sector is too small or too consumer-facing to escape strategic cultivation.

Consider cosmetics. Historically regarded as pure marketing, not technology. Lipstick and moisturizer. The kind of industry you’d expect governments to ignore entirely.

Instead, China issued the Cosmetics Supervision and Administration Regulations (CSAR) in June 2020, taking effect January 1, 2021. The regulation introduced mandatory pre-market safety assessment requirements, and cosmetic efficacy claims must be supported by sufficient scientific evidence. This isn’t consumer protection. It’s industrial policy designed to upscale the quality of skincare China can produce. In 2022, China’s State Administration for Market Regulation and 17 other central government departments jointly released the Action Plan for Further Improving the Quality of Products, Engineering and Services (2022-2025), which proposed cultivating high-end brands in cosmetics and other consumer product fields. Eighteen government bodies coordinating on lipstick.

Local governments offer direct subsidies. Guangzhou provides up to 1 million yuan for new cosmetic ingredients that are first-time applications in China’s cosmetics ingredient directory, with individual enterprises capped at 5 million yuan annually. Beijing established a cosmetics new ingredient innovation award program offering subsidies for enterprises registering or filing new cosmetic ingredients. In 2024, 90 new cosmetic ingredients were notified; a significant increase from 69 the prior year. It’s a historic high that dwarfs the 14 ingredients approved between 2004 and 2020. Domestic chemical companies moved from imitation to invention, protected by regulatory architecture favoring local players.

I want to be clear about how strange this is. The Chinese government treats mascara the way other governments treat semiconductors. There are land grants for eyeshadow innovation. Political slogans about “New Quality Productive Forces” applied to face cream. According to H1 2024 financial reports, Huaxi Biology’s R&D expenditure reached 201 million RMB, with the company framing their investment in synthetic biology platforms using party-approved language designed to unlock state support. For a company that makes hyaluronic acid.

PROYA’s trajectory shows what this produces. The company reached ¥10.78 billion yuan in 2024 revenue, aiming to invest ¥2.1 billion in R&D (approximately 21% increase but it’s questionable if they actually did invest), holds 229 patents, and operates a Paris research center. Chinese domestic brands now invest over 3.5% of revenue in R&D compared to 1.5-3.5% for foreign brands operating in China, demonstrating a strategic commitment to catching up through innovation.

The strategic implication is uncomfortable: what China did to solar panels, semiconductors, and electric vehicles, it is doing to cosmetics. The state has decided that Chinese women should buy Chinese moisturizer, and it is building the industrial base to make that happen. Foreign companies in any sector should assume China has or will develop an industrial policy for their industry. The question is not whether displacement pressure will emerge, but when. If they’ll do it for lipstick, they’ll do it for anything.

Ephemeral Dreams Burst like Bubbles

The August 2023 Fukushima water release triggered a consumer backlash unrelated to Shiseido’s products or execution. Japanese cosmetics became politically suspect overnight. Weibo boycott campaigns accumulated hundreds of millions of views. Shiseido’s stock fell in the following week. This was geopolitical risk materialized, a government decision creating commercial consequences no company could prevent.

Simultaneously, China’s macroeconomic deterioration accelerated: property crisis, youth unemployment, consumer confidence collapse. And PROYA’s rise meant competition had fundamentally changed.

Companies can capture substantial value during the boom phase of the China cycle, as Shiseido did from 2015-2019. The error is assuming the boom phase is permanent rather than building exit options while the position remains strong.

UNIQLO and Toyota initially seemed like counterexamples: Japanese firms navigating China successfully while Shiseido collapsed. That interpretation aged poorly.

UNIQLO China sales fell 4% year-over-year in H1 fiscal 2025, operating profit down 11%. Store count contracted for the first time after years of expansion. Founder Yanai Tadashi acknowledged in April 2025 that the fundamental issue with UNIQLO China is that all stores operate identically and the company hasn't been able to develop products tailored to local customer needs.

Toyota’s China sales fell 13.7% in H1 2024, then 6.9% for the full year. By late 2025, November sales dropped 12.1% year-over-year, three consecutive months of contraction. A parts supplier told Nikkei that China operations had become “a fight for survival.” Japanese automakers’ combined share of the Chinese passenger vehicle market fell from roughly 23% in 2020 to under 15% by 2025.

UNIQLO’s “success” and Toyota’s “resilience” bought time. It’s not an exemption, as you quick to find out. The 1,000+ Japanese companies that have left China since the 2012 peak, the decline in foreign direct investment from $344.1 billion in 2021 to just $45 billion in 2024: these form a pattern Shiseido previewed, not an anomaly it alone suffered.

The self-inflicted collapse

Here’s what the China narrative obscures: a substantial portion of Shiseido’s ¥52 billion loss had nothing to do with geopolitics.

The Drunk Elephant disaster, a ¥46.8 billion goodwill impairment, accounts for roughly 90% of the record loss. This was a 2019 American acquisition ($845 million) meant to provide geographic diversification through a “clean beauty” brand targeting millennials and Gen Z. By 2025, sales had dropped over 40% year-over-year. Shiseido exited the Japanese market entirely for the brand.

The pattern isn’t new. Shiseido acquired Bare Escentuals (bareMinerals and BUXOM) in 2010 for $1.9 billion, added Laura Mercier in 2016, then sold all three brands in 2021 for just $700 million. The M&A graveyard predates the China shock.

Strip out the Drunk Elephant writedown, and the story changes considerably. The structural China pressures are real and would have damaged earnings regardless. But the “largest loss in 153-year history” framing reflects acquisition failure as much as geopolitical exposure.

The lesson isn’t just “international markets are risky.” It’s also “Shiseido is bad at acquisitions.” Companies watching should separate these failure modes. The China cycle is largely unavoidable for firms that entered during the boom. The acquisition disasters were entirely avoidable.

UNIQLO offers an instructive contrast. The company spent two decades building American operations store by store, learning from failures, including the 2005 New Jersey disaster when three suburban mall stores opened to empty parking lots and closed within a year. When China weakened, UNIQLO had genuine alternative markets built through organic capabilities that acquisitions cannot replicate.

What this means

The China cycle isn’t a grim reaper and can be managed. Rising domestic competitors, nationalist consumer preference, industrial policy favoring local champions, macroeconomic deterioration: these forces affect all foreign companies in China. The question is not whether to enter (for most companies during the 2010s, entry was correct) but how to structure presence so eventual de-risking remains possible. Exit timing matters more than entry timing. The companies suffering worst expanded most aggressively during the boom and lack clear exit paths.

If I am forced to boil it down into a set of lessons, it would be:

Domestic markets are strategic assets just like the business rhetoric says it is, not legacy burdens like most business act like it is. Shiseido’s Japanese operations kept the company viable through the collapse. Kao’s historic caution preserved fallback positions. But “stable” is not “attractive.” Japan’s market is mature, the population shrinking. Retreating to domestic markets carries its own risks, and again it is important to note that Kao is becoming more aggressive with expansion.

National branding is a type of infrastructure. A 2019 study in the Journal of Innovation and Entrepreneurship found that a one-unit increase in national brand strength correlated with a 0.23% increase in high-tech export share. The “Made in Japan” premium that protected Shiseido eroded precisely because Chinese industrial policy built alternatives while nationalist sentiment shifted preference. Countries that want their companies to compete globally need comparable support systems. Switzerland’s watches and Germany’s automobiles benefited from decades of deliberate national brand building.

Organic expansion builds what acquisition cannot. Shiseido’s acquisition track record is poor across geographies and decades. UNIQLO’s patient expansion built institutional knowledge. For most firms, the acquisition shortcut destroys more value than it captures.

Assume China has an industrial policy for your industry. The cosmetics case proves that no sector is too consumer-facing, too marketing-driven, too apparently trivial. If five ministries will coordinate on moisturizer, nothing is safe. Plan accordingly.

Shiseido will likely survive. The company has real strengths: genuine R&D capabilities, brands that still mean something, a domestic customer base that hasn’t abandoned it. Restructuring can rebuild around these.

The case is instructive because it was early, not because it was unique. The China boom that defined global corporate strategy for two decades is ending. What remains is the harder work of building durable competitive positions in a world where the easy growth is gone and a Chinese government has opinions about who should make your lipstick.

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In 1961, Japan’s Ministry of International Trade and Industry summoned the country’s automakers to deliver unwelcome news. The industry had too many players: ten manufacturers competing in a market that MITI believed could support two. Toyota and Nissan would absorb the rest. Honda, Mazda, Subaru, and the others would be folded into national champions capable of competing with General Motors and Ford.

Soichiro Honda refused. In a confrontation with MITI officials that became famous in Japanese business history, he declared that he had the right to manufacture automobiles, that the government couldn’t prevent new entrants while protecting incumbents, and that free competition would motivate the industry’s growth.

I had the right to manufacture automobiles, and they couldn’t enforce a law that would allow only the existing manufacturers to build them while preventing us from doing the same. We were free to do exactly what we wanted... If MITI wanted us to merge, then they should buy our shares and propose it at our shareholders’ meeting. After all, we were a public company. The government couldn’t tell me what to do.

He rushed two vehicles into production (the T360 mini-truck and S500 sports car) to establish a manufacturing record before MITI’s consolidation bill could pass. The bill was eventually abandoned.

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Three decades later, China’s central government faced the same problem and reached the same conclusion. In 1989, Beijing announced its “three large, three small, two mini” policy, calling for consolidation of the auto industry around designated national champions. The country had too many manufacturers; they needed to merge into firms with the scale to compete globally.

The policy failed. Provincial governments, whose career incentives and tax revenues depended on local industry, resisted consolidation at every turn. Beijing tried again in the 2000s, and again in the 2010s. As recently as 2024-2025, an attempted merger of state-owned Changan and Dongfeng collapsed. Today China has 169 active automobile manufacturers and 129 EV brands.

The results confounded the planners. The companies MITI sought to eliminate went on to become globally competitive manufacturers. When the United States began imposing emissions standards in the 1970s, Honda and Mazda broke ranks with major carmakers and declared they could meet the new pollution standards. Their innovation, driven by their need to differentiate and compete, became the foundation of Japanese success in the American market. In China, the fragmentation that Beijing tried to prevent produced BYD, which overtook Tesla as the world’s largest EV manufacturer by revenue in 2024. Six of the world’s top ten EV sellers are now Chinese. Product development cycles have compressed to 18-24 months, compared to four or five years for Western automakers.

Honda bet that competitive pressure would strengthen Japan’s auto industry more than government-directed consolidation. Provincial officials in Guangdong and Zhejiang, protecting their local champions from Beijing’s merger plans, made the same bet without meaning to. Both were right. But why?

Conventional, maybe Clichéd, Wisdom

We are living through a revival of industrial policy. Governments worldwide are deploying subsidies, tariffs, tax credits, and direct investments to reshape their economies. In the United States, the CHIPS and Science Act, the Inflation Reduction Act, and a new wave of trade protection signal a decisive break from the laissez-faire consensus of the past four decades.

Yet alongside this revival runs a persistent assumption: that antitrust enforcement and industrial policy are opposing strategies. The logic seems obvious. Industrial policy aims to strengthen domestic firms; antitrust enforcement attacks them. Industrial policy seeks national champions; antitrust breaks them up. As Daniel Sokol put it in his 2015 paper “Tensions between Antitrust and Industrial Policy”, “sound antitrust law and policy is in tension with industrial policy.”

This framing treats the relationship as zero-sum. When American tech firms face antitrust scrutiny, defenders argue that breaking them up would gift advantages to Chinese competitors. When Boeing seeks to acquire rivals, supporters invoke the need to compete with Airbus. The assumption is always the same: competition and competitiveness are in tension.

We think this framing isn’t exact the right fit.

A Different Framework

Tim Wu, in a recent working paper titled “Antitrust and Industrial Policy: A Misunderstood Relationship”, argues that promoting competition through antitrust can be an important means of enhancing national competitiveness. Antitrust and industrial policy are complementary, not opposing.

Wu proposes a typology of government interventions that shape industry. Aid consists of direct assistance: subsidies, grants, tariffs, protective regulations. Support consists of indirect assistance: infrastructure, research funding, education systems. Suppression consists of interventions that deliberately weaken an industry, whether for environmental, health, or strategic reasons.

The fourth category is Discipline: interventions meant to improve an industry by forcing firms to improve performance or face losing market share. Antitrust enforcement is the primary mechanism of discipline. By preventing collusion, blocking anticompetitive mergers, and restraining exclusionary conduct, antitrust forces companies to compete. That competition, Wu argues, strengthens rather than weakens industries.

Wu draws an analogy to athletic training. An Olympic athlete needs both care and challenge, both resources like nutrition and coaching and worthy opponents. Athletes routinely relocate to train against more elite competition; Lionel Messi moved to Barcelona at age thirteen to face better players. “Like boxing champions who lack suitable opponents,” Wu quotes auto executive George Romney, “companies will become soft and flabby” without competitive pressure.

What does discipline mean operationally? It means feedback. Firms facing competition receive clear, fast signals about performance: lose customers, lose revenue, watch competitors demonstrate what’s possible. Protected firms don’t receive these signals, or receive them too late and too weakly. That’s why consolidated industries grow complacent while competitive industries adapt.

Wu identifies several distinct mechanisms, and they work differently. Banning collusion prevents firms from agreeing not to compete; the discipline is immediate. Merger control prevents consolidation that would reduce rivalry; the discipline is structural. Restraining exclusionary conduct (a dominant firm using its position to foreclose rivals) protects adjacent markets; the discipline operates at industry boundaries. Compulsory licensing of intellectual property reduces barriers to entry; the discipline creates room for new firms. These are different legal tools with different effects, but they share a common logic: they force firms to earn profits through performance rather than through suppressing competition.

The two broadest effects are worth emphasizing. First, firms that cannot collude or merge their way to profits must earn them through efficiency and innovation. Second, antitrust can reduce the exclusionary effects of dominant firms that control platforms or bottlenecks. Market power in one part of an industry can slow growth in adjacent industries. Antitrust deters efforts by monopolists to suppress competition, creating room for new firms and new industries to emerge.

This framework is a better fit for Honda’s little bet. MITI believed consolidation would produce strength through scale. Honda believed competition would produce strength through discipline, through the feedback that forces continuous improvement. The subsequent history of the Japanese auto industry suggests Honda had the better of the argument.

What’s the Theory?

Wu’s framework draws on a substantial academic literature, particularly the work of Philippe Aghion and colleagues on competition and innovation.

The Escape-Competition Effect

The foundational work is Aghion’s 2005 study, “Competition and Innovation: An Inverted-U Relationship”. Using panel data on UK firms, Aghion and colleagues found that innovation increases with competition up to a point, then decreases as markets become very fragmented. Wu cites this research; it provides theoretical grounding for why discipline works.

The key mechanism is what they call the “escape competition effect,” and it deserves careful attention because it explains why competitive discipline produces innovation. In industries where firms operate at similar capability levels (”neck-and-neck” competitors), increased competition reduces the profits available to firms that merely maintain the status quo. If you and your rival both make decent cars, neither of you earns much. But if you can pull ahead, through better quality, lower costs, or new features, you can capture market share and earn returns on your investment.

This creates powerful incentives to innovate. Firms invest in R&D not because they love technology but because they need to escape competitive pressure. The discipline of competition makes standing still untenable; the only way out is forward. In neck-and-neck industries, more competition means more innovation because more firms are running to escape.

The relationship reverses when firms are far apart in capability. A laggard competing against a dominant leader has little chance of catching up; innovation won’t help, so why bother? This explains the inverted-U: competition drives innovation up to a point, but too much disparity (or too much fragmentation) undermines the incentive. The sweet spot is industries with multiple capable competitors, each with a realistic shot at pulling ahead.

Aghion extended this work to industrial policy in a 2015 study using Chinese firm-level data. Industrial policy has larger positive effects on productivity in more competitive industries. When subsidies are spread across many firms rather than concentrated in national champions, the disciplinary effect of competition is preserved. The escape-competition logic holds: even subsidized firms innovate more when they face rivals.

Michael Porter’s (the professor that created the five forces framework and other tools) work on national competitive advantage reaches similar conclusions. Porter identifies domestic rivalry as one of four determinants of national competitiveness in his seminal article “The Competitive Advantage of Nations”. He identifies Japan’s auto industry, with its multiple major competitors, as exemplifying how intense competition in the domestic market produces firms that can compete globally. His policy prescription aligns with Wu’s framework: governments should stimulate local rivalry by limiting direct cooperation and enforcing antitrust regulations.

Dani Rodrik puts the point sharply: “Successful industrial policy is not about picking winners. It’s about letting the losers go.” Industrial policy fails when it protects incumbents from competitive pressure, allowing inefficient firms to survive on subsidies. It succeeds when competitive discipline provides feedback about which firms deserve continued support and which should exit.

Why Antitrust Works Differently

Traditional industrial policy faces well-documented political economy problems that antitrust enforcement largely avoids.

The Loser’s Paradox. Economists have documented that declining industries are systematically better at lobbying for government support than rising industries. Loss aversion leads policymakers to place greater weight on preventing job losses than enabling job gains. Established firms with organized workforces lobby more effectively than nascent industries with fragmented interests. The result is a tendency for subsidies to flow to yesterday’s industries rather than tomorrow’s.

Antitrust has different dynamics. Becoming an enforcement target is unwelcome; no industry collectively lobbies for investigation. Section 2 cases often involve large firms targeting small ones (AT&T attacking MCI, Microsoft attacking Netscape), creating adversarial processes that give smaller players a voice. Antitrust attention tends to focus on profitable, growing industries where there are monopoly rents worth protecting, not on declining industries seeking life support.

Information-Forcing Mechanisms. Blocking a merger or proving a Sherman Act violation requires presenting significant evidence of anticompetitive effects. This requirement limits arbitrary or corrupted decisions in ways that subsidy allocation does not.

Lobbying Dynamics. Unlike subsidies, antitrust enforcement does not fit George Stigler’s model of regulation that industries effectively purchase. The process is adversarial, differing from collective industry lobbying for tariffs or subsidies that benefit all incumbents.

It is important to not that Wu does not claim antitrust is immune to political influence (I mean look at the Second Trump Administration or China’s breakdown of Jack Ma’s Ant Group). But the dynamics differ from traditional industrial policy in ways that reduce public choice pathologies, though they do not eliminate them.

The Evidence

Does the theoretical case hold up empirically? We have evidence from automobiles, technology industries, and contemporary semiconductor policy.

Automobiles: A Natural Experiment

The global automobile industry offers something close to a natural experiment. Three major auto-producing nations took dramatically different approaches to industry structure.

China’s Failed Consolidation. The Chinese case, introduced above, rewards closer examination. Economists Hanming Fang, Ming Li, and Guangli Lu analyzed three million Chinese government documents to decode the country’s industrial policy system in their study “Decoding China’s Industrial Policies”. They found that Beijing’s consolidation efforts were not halfhearted; they were sustained, repeated, and backed by central authority. The policy failed anyway.

The mechanism of failure matters. Provincial officials didn’t oppose consolidation on principle; they opposed losing their auto plants. Career advancement in the Chinese system depends heavily on regional GDP growth. Local business taxes fund provincial budgets. When Beijing said “merge,” provincial governments heard “sacrifice your tax base and your promotion prospects for someone else’s national champion.” They resisted through bureaucratic delay, selective enforcement, and quiet support for local manufacturers.

The result was an unplanned experiment in competitive discipline. Chinese brands accounted for 76 percent of global electric vehicle sales through October 2024. The fragmentation that Beijing tried to eliminate produced the industry that now leads the world.

Japan’s Preserved Competition. Honda’s defiance preserved competitive pressure in the Japanese market. The industry maintained at least ten significant manufacturers for decades. Even today, under pressure from Chinese EVs, consolidation has been resisted; Honda-Nissan merger talks collapsed in February 2025.

When emissions standards created a new competitive dimension in the 1970s, the smaller players moved fastest. Their need to differentiate drove innovation that the larger, more comfortable Toyota and Nissan had less incentive to pursue.

America’s Consolidation. The United States took a different path, the path MITI had envisioned for Japan and Beijing has repeatedly sought for China.

By the 1930s, the American industry had consolidated to three major manufacturers. In 1962, General Motors alone held over 50 percent of the market. The Big Three’s combined share topped 90 percent.

George Romney had warned Congress in 1958 what unchecked concentration would mean: “There has not been enough competition in the automobile business in the United States to compel the Big Three to keep their products as modern.” He predicted they had grown too invested in large cars and were neglecting smaller, efficient vehicles, precisely the segment Japanese manufacturers would exploit.

The Case That Was Never Filed. Wu documents that the Justice Department did not simply decline to investigate GM. It prepared a case, drafted a complaint, and chose not to file.

During the Eisenhower and Kennedy administrations, Justice Department lawyers worked on a monopolization complaint against General Motors. According to the Wall Street Journal’s reporting at the time, the complaint reached 104 pages. It was a serial monopolization case that addressed more than 40 of GM’s mergers over the preceding decades. The main remedy would have been the divestiture of Chevrolet from the rest of GM.

Robert Kennedy, as Attorney General, was widely expected to file the suit. But it was still pending when Kennedy left office. The decision passed to the Johnson Administration, and according to the Wall Street Journal, President Johnson reserved for himself the final decision on whether to proceed.

The complaint was never filed. Donald Turner, then head of the Antitrust Division, told the New York Times that the decision never reached the White House; the case may have foundered on legal uncertainty about untested theories of shared monopoly or serial acquisition. Or politics may have played a role. The same period saw passage of the National Traffic and Motor Vehicle Safety Act, championed by Ralph Nader; the Johnson Administration may have decided that if it was going to confront the auto industry, safety regulation was the priority.

Whatever the reasons, the outcome is documented: enforcers prepared to break up GM and chose not to. This is not correlation. It is a policy choice whose consequences can be traced. The 104-page complaint sat in Justice Department files while the American auto industry continued on its consolidated path.

The Consequences. When Japanese small cars entered the American market in the 1970s, the Big Three’s responses were plagued by quality problems. The Chevrolet Vega suffered from oil leaks, warped cylinder heads, and engine fires. The Ford Pinto’s dangerous fuel tank design, chosen to save eleven dollars per car, led to widely-reported fires after low-speed collisions. By 2008, the Big Three’s combined market share had fallen to 44 percent, and GM and Chrysler required government bailouts.

What if the Justice Department had filed? The divested firms would have been in a position similar to Japanese competitors: smaller players with strong incentives to escape competition through innovation. The escape-competition effect would have applied. We cannot know for certain what would have followed. But the comparison with computing and telecommunications, where antitrust pressure produced innovation and industrial succession, suggests the counterfactual is plausible.

The decision not to file against GM may have been one of the most consequential non-decisions in American industrial history.

Technology Industries: Computing and Telecommunications

Back to Wu’s paper, he examines four American technology industries from the mid-twentieth century onward: aerospace, automotive, computing, and telecommunications. All were new industries dependent on evolving technologies. All became concentrated. All received government support through research funding and defense contracts.

The critical difference was antitrust treatment. Computing and telecommunications faced intense enforcement. Aerospace and automotive were granted de facto immunity.

Telecommunications: Seventy Years of Containing AT&T. The federal government, from the 1920s onward, accepted AT&T as a regulated monopoly. But antitrust enforcers repeatedly intervened to prevent AT&T’s monopoly from spreading to adjacent industries. This was not a single intervention or even a single policy. It was a multi-generational institutional commitment spanning seven decades and multiple administrations of both parties.

The pattern begins in 1913, when AT&T sold Western Union to settle an antitrust action, keeping the telephone monopolist out of telegraphs.

In the 1920s, AT&T operated the nation’s dominant radio network, refusing to transmit content from rivals. Following FTC pressure, AT&T sold what became NBC to RCA.

In the 1930s, FTC lawsuits forced AT&T out of the film industry, where it had expanded using its patents over film sound technology.

In 1956, a consent decree kept AT&T out of computing and semiconductors, leaving room for IBM, Fairchild, and Intel. The decree required AT&T to license 7,820 patents royalty-free. This compulsory licensing has been studied carefully: Martin Watzinger and colleagues found it increased follow-on innovation by 17 percent, with the gains concentrated in young and small companies. The mechanism is clear: reducing the exclusionary effects of AT&T’s patent portfolio created room for entrants who would otherwise have been blocked or taxed. Fairchild Semiconductor, founded in 1957, benefited directly; Intel, founded by Fairchild alumni in 1968, benefited indirectly. The semiconductor industry that now anchors American technology grew in space that antitrust enforcement created.

In the 1970s, the FCC’s Computer Inquiries kept AT&T at a distance from online services and data processing, maintaining separation between the telephone network and the computing applications that would eventually run on top of it.

The 1984 breakup extended this logic, dividing AT&T into eight firms. The breakup aided long-distance providers, online services, equipment manufacturers, and eventually the internet industry itself. Those industries developed “on top” of the telecommunications platform once AT&T could no longer foreclose them.

The cumulative effect was to maintain the telephone network as neutral infrastructure upon which other industries could develop. Each intervention created room for industries that later became significant. A small example illustrates the stakes: AT&T had a working prototype of an answering machine by the 1930s. It refused to deploy or allow connection of such devices to its network until federal intervention in the 1970s, a four-decade delay. The suppression wasn’t technological; it was structural. The monopolist had no incentive to enable devices that might reduce calls or create competition.

This is not to say the telecommunications interventions were costless or that American telecom is an unambiguous success story. The breakup imposed transition costs. Some argue that subsequent reconsolidation (SBC acquiring AT&T, the name surviving as a brand on a different company) suggests the interventions didn’t permanently restructure the industry. American broadband today is less competitive and more expensive than in many peer countries. Wu’s argument is not that antitrust produced optimal outcomes, but that it created room for adjacent industries that would not otherwise have developed. The internet industry grew in space that the telecommunications interventions created, whatever one thinks of the current state of telephone and broadband service.

What made the telecommunications pattern work was its persistence. One intervention might have been evaded or eroded. Seventy years of sustained pressure, across administrations, created an institutional expectation: AT&T would be kept in its lane. That expectation shaped behavior even when no case was pending.

Computing: Discipline Through Threat. In 1969, the Justice Department filed a monopolization case against IBM that would last fifteen years. The case was eventually dropped in 1982 as “without merit.” Yet its effects on industry structure were profound.

The mechanism is stranger than it first appears. IBM’s most consequential change came before the complaint was filed, not after. In 1969, anticipating the lawsuit, IBM unbundled software from hardware. The company’s general counsel had identified bundling as “a glaring violation of antitrust law” and advised preemptive action. IBM’s leadership agreed: better to unbundle voluntarily than be forced to do so by a court.

This decision created space for the independent software industry. Within a decade, software had become among the fastest-growing industries in the United States. The change was driven not by a court order but by corporate counsel’s fear of what a court might order.

The pattern continued through the 1970s. IBM’s behavior reflected ongoing antitrust caution. The company declined to acquire Apple, Microsoft, and Seagate when all were small businesses; its attorneys feared renewed scrutiny. When IBM entered the personal computer market, it used a modular design with non-exclusive supplier relationships. The IBM-PC had a hard drive from Seagate, a printer from Epson, a processor from Intel, and (most fatefully) an operating system from a startup called Microsoft. The non-exclusivity was crucial: it enabled Compaq, Dell, and others to build compatible machines.

Wu describes the result as “divided technological leadership,” an era in which no single monopoly controlled computing, but interoperating firms at different levels competed and innovated. The antitrust pressure didn’t just affect IBM’s structure; it changed how IBM made decisions in ways that created room for the entire PC ecosystem.

Then, in 1982, the Reagan Administration dropped the case as “without merit.” Fifteen years of litigation, no verdict, no remedy. By the standard metrics of antitrust enforcement, the IBM case was a failure.

But the discipline had already worked. The threat of enforcement produced preemptive behavioral change. IBM unbundled software, declined acquisitions, chose non-exclusive contracts, all because its lawyers feared what might happen if it didn’t. The case was dropped, but the ecosystem it created remained.

Wu presents these facts without drawing a strong conclusion about policy design. But the implication is worth noting: the threat of enforcement may matter as much as enforcement itself. The IBM case worked because it was credible, because the telecommunications pattern had established that the government would actually pursue monopolists, because AT&T had been broken up and Standard Oil before that. Maintaining that credibility may require actual enforcement over time, even if individual cases don’t always succeed.

The International Comparison. The United States, Japan, and Britain all started with national champion computing firms: IBM, Fujitsu and NEC, ICL. They made different policy choices.

Japan and Britain protected their champions from domestic competition, hoping to strengthen them against international rivals. The United States subjected IBM to intense antitrust pressure. The results diverged sharply.

Japan and Britain failed to develop significant adjacent industries, particularly software. Their national champions survived but their computing ecosystems did not flourish. The United States was the only country to actively force competition in computing through significant and ongoing antitrust interventions. It was also the only country that developed a dynamic computing industry.

Aerospace: The Counter-Example. Aerospace represents what happens when enforcement is actively discouraged.

In 1997, Boeing proposed to acquire its main domestic rival, McDonnell Douglas. Under prevailing merger standards, the combination was presumptively illegal. But the Clinton administration signaled support for the merger as a means of strengthening Boeing against Airbus. The divided Federal Trade Commission declined to act.

The result has been a single American firm in commercial aviation. Wu argues the national champion approach has not succeeded. Boeing’s stock has grown more slowly than the S&P 500 despite decades of government support. The company has shown dis-efficiencies of scale, including the manufacturing defects that led to the 737 MAX grounding.

Most striking is the absence of industrial succession. Boeing was the dominant firm in the 1920s, and it remains the dominant firm in the 2020s. In computing and telecommunications, multiple paradigm shifts occurred; technological leadership changed hands repeatedly. In aerospace, nothing comparable has happened.

Wu poses the comparison vividly: “A time traveler from the 1960s would be shocked and amazed by the advances in today’s computers and communications technologies. Boarding a passenger airliner, however, would be a familiar experience.”

The Growth Numbers

The differential outcomes can be quantified. A study of economic growth from 1960 to 2007 by Dale W. Jorgenson and colleagues shows some, well a lot, differences across industries. The total economy grew at an annual rate of 3.45 percent. Computing and software, industries subjected to intense antitrust pressure, grew at 20 to 35 percent annually, while telecommunications and IT services expanded at 6 to 8 percent per year. The industries granted de facto immunity from antitrust enforcement fared far worse: automotive grew at just 2.4 percent annually, below the economy-wide average, and aerospace managed only 1.2 percent, roughly one-third the overall rate.

The industries subjected to aggressive antitrust enforcement grew far faster than those granted de facto immunity. Automotive grew below the economy-wide average. Aerospace grew at roughly one-third the overall rate.

On that little note, Wu is careful about causation: “Historical causation is complex, and it certainly cannot be claimed that differential government attention was the single factor that made the difference.” But the pattern is consistent. “If nothing else,” Wu concludes, “there is a clear argument that lack of antitrust attention can yield industrial stagnation.”

CHIPS: A Contemporary Test

The CHIPS and Science Act, enacted in 2022, provides a contemporary test.

The CHIPS Program Office had $39 billion to allocate. It could have followed the national champion model, picking a single firm to back. The Department of Defense’s recent MP Materials agreement took essentially that approach: price floors, demand guarantees, loan financing, and equity investment for a single rare earth producer.

CHIPS took a different path, one that echoes the computing and telecommunications models. Sara O'Rourke, the former COO, describes the process in an article for . The pre-application phase created discipline through iterative feedback: “Another applicant submitted a project for a new technology that seemed to be a minor improvement on an enterprise technology use case, which we indicated would be low priority for us; they returned with a proposal that would represent a total breakthrough in AI datacenter chip technology.”

The process maintained discipline through iterative engagement, preserving the feedback loops that make competition work. In the pre-application phase, CHIPS teams met regularly with applicants to provide feedback and push for more ambitious commitments. Leading-edge applicants initially requested over $70 billion in collective funding. CHIPS got them to accept approximately $26 billion for multiple clusters while extracting commitments to build faster, add more capacity, and push to more cutting-edge technology.

The result was a portfolio, not a champion. CHIPS funded all five companies at the leading edge (TSMC, Samsung, Intel, Micron, and SK Hynix) plus suppliers and advanced packaging facilities. Mike Schmidt, the former program director, contrasts this with the MP Materials approach: CHIPS built “a diversified portfolio,” not “a massive brute-force subsidy to a single player.”

Implementation Requirements

Competition does not operate in a vacuum. Effective discipline requires institutional infrastructure.

Institutional Capacity

The Fang study found that high-capacity regions achieved 2.3 times greater productivity effects from identical policies compared to low-capacity regions. Administrative sophistication (the ability to evaluate projects, negotiate with sophisticated companies, structure accountability) determines whether industrial policy succeeds or fails.

The CHIPS program invested heavily in this capacity, hiring what O’Rourke called “top Wall Street and industry talent who understood commercial diligence and deal negotiations.” The telecommunications interventions similarly required sophisticated regulatory capacity at the FCC to design and enforce the Computer Inquiries.

Countries without strong enforcement institutions may not replicate results simply by adopting policies.

Policy Bundles

The Fang study also found that policies employing three or more complementary tools boosted firm productivity 2.3 times more than single-tool approaches.

The successful American technology industries received exactly this: research funding through DARPA and defense contracts, infrastructure investment, education pipelines from universities, all combined with antitrust discipline that maintained competitive pressure. Aid and discipline operated together, not as substitutes.

CHIPS exemplified this bundling. The program deployed pre-application feedback, milestone-based payments, continuous engagement with applicants and their customers, and tailored commitments for each firm. This was aid structured to maintain competitive pressure and accountability.

Maintaining Commercial Ecosystems

On the topic of tech commercialization, we have a cautionary tale in the form of Extreme Ultraviolet (EUV) lithography . EUV, the technology enabling the most advanced semiconductor manufacturing, was largely developed in the United States. DARPA, Bell Labs, the US National Laboratories, IBM Research, and Intel all contributed decades of research and billions of dollars.

Yet today, EUV lithography machines are built by a single firm: ASML, in the Netherlands.

By the time EUV was ready for commercialization, American lithography equipment firms had been almost entirely forced out of the global market. The US did the research but lacked domestic firms positioned to commercialize it.

Antitrust enforcement that preserves competitive entry protects the ecosystem in which commercialization occurs. Research funding alone is not enough if the commercial ecosystem dies. The telecommunications pattern, sustained intervention to keep adjacent markets open, matters precisely because it maintains the firms that can turn research into products.

The Limits

We should be clear about what economists view as genuine constraints.

The Inverted-U’s Downward Slope

Aghion’s model shows that too much competition can reduce innovation. In very fragmented markets, firms may underinvest in R&D because they cannot appropriate returns. The escape-competition effect depends on firms being close enough in capability that pulling ahead seems achievable; when markets are too fragmented, no one can pull ahead far enough to matter.

China’s solar panel industry illustrates the danger. When multiple provinces simultaneously targeted solar with similar subsidies, the resulting overcapacity undermined the industry. Firms proliferated, margins collapsed, and the sector required painful consolidation. China’s 169 automakers may be past the optimal point; current EV production capacity of 54 million vehicles exceeds domestic demand of roughly 30 million.

The feedback that competition provides can itself signal when markets have become too fragmented: collapsing margins, unsustainable losses, inability to fund R&D. The discipline cuts both ways.

Path Dependence

Early choices lock in patterns that persist for decades. The Fang study found that “pioneer” cities, the first to target a sector, achieved 31 percent higher productivity gains than followers.

Path dependence (using the phrase again) cuts both ways. Decisions to maintain competition can produce lasting benefits: the telecommunications interventions that kept AT&T in its lane created conditions that enabled entire industries to develop. But decisions to permit consolidation may be very difficult to reverse. The window for effective intervention may be narrower than policymakers assume.

The non-filing against GM illustrates the point. By the time Japanese competition forced adaptation in the 1970s, decades of limited domestic competition had shaped the industry’s capabilities, culture, and cost structures. The Big Three’s attempts to build competitive small cars failed partly because the organizations had optimized for something else entirely.

Industry-Specific Characteristics

The automobile and aerospace industries have distinctive features (high capital intensity, long product cycles, significant scale economies) that may limit how much competition they can sustain. The relevant question is not whether all industries should be maximally fragmented but whether competitive pressure within each industry’s constraints produces better outcomes than protection.

The evidence suggests it does. Even in capital-intensive automobiles, the fragmented Chinese EV market outperformed the consolidated American industry. Even in scale-dependent aerospace, the absence of domestic competition correlates with stagnation or even decay rather than strength.

The Policy Implication

What follows for policymakers?

First, antitrust enforcement should be understood as one tool in a broader industrial policy toolkit, a form of discipline that differs from subsidies and tariffs but shares the goal of strengthening industry.

Second, a country can simultaneously strengthen an industry through subsidies and research funding while maintaining competitive discipline through antitrust enforcement. The federal government did exactly this in telecommunications and computing. CHIPS did it in semiconductors. The apparent inconsistency is no inconsistency at all. Like an Olympic athlete, an industry can be both supported and challenged.

Third, the failure to enforce is itself a policy choice with consequences. The decision not to file against GM, the decision to permit the Boeing-McDonnell Douglas merger, the broader pattern of treating consolidated industries as national champions: these were choices. They had effects. Non-enforcement should be evaluated with the same rigor as enforcement.

Fourth, credibility may matter as much as cases filed. The IBM experience suggests that the threat of enforcement can produce behavioral change even when cases are never won or are ultimately dropped. But the threat must be credible, which requires a history of actual enforcement. The telecommunications pattern, seventy years of sustained pressure, created expectations that shaped corporate behavior even in the absence of active litigation. Wu doesn’t draw strong conclusions about how to design for this effect, but the implication is that institutional commitment across administrations matters.

Fifth, (and you know I love my dead horses) implementation matters as much as policy design. Competition requires institutional capacity, policy bundles that combine complementary tools, and sustained commitment over decades. The telecommunications pattern produced results that a single intervention could not have achieved.

Sixth, maintaining commercial ecosystems matters as much as funding research. Antitrust enforcement that preserves competitive entry protects the firms that can turn innovations into products. Without that ecosystem, research investments may benefit other nations’ industries.

Back to the Beginning

We return to Honda, and to the provincial officials in Guangdong who never meant to prove him right.

Honda’s bet was that competitive pressure would produce better outcomes than centralized coordination. He wasn’t making an ideological argument about markets versus government. He was making a claim about feedback: that the discipline of competition, the constant signal that you must improve or lose, would drive innovation more reliably than protected consolidation. The Chinese provincial officials who blocked Beijing’s merger plans weren’t making any argument at all; they were protecting their tax bases and their careers. But the effect was the same. By preventing consolidation, they preserved the competitive pressure that forced Chinese automakers to innovate.

The subsequent sixty years have rendered a verdict. The fragmented Japanese auto industry, which Honda helped preserve, produced globally competitive manufacturers. The fragmented Chinese EV industry, which provincial resistance preserved despite Beijing’s plans, has produced the world’s leading electric vehicle companies. The American auto industry, which achieved the consolidation that MITI sought for Japan and Beijing sought for China, required government bailouts.

In computing and telecommunications, sustained antitrust pressure produced industrial succession, the renewal that Schumpeter identified as central to capitalist dynamism. The leading firms of 2025 are unrecognizable from those of 1965. In aerospace and automotive, where antitrust attention faded, the same firms that dominated in the 1950s dominate today.

Within governments, separate teams typically work on “competition” and “competitiveness.” The evidence suggests these should be the same conversation. Competition creates competitiveness. Forcing an industry to compete internally, maintaining the feedback loops that discipline performance, makes it more competitive in the world.

We do not claim fragmentation is always preferable to consolidation, or that antitrust enforcement always promotes innovation. Never been a fan of the “one weird trick” theory of anything. At the end of the day, the relationships are contingent and context-dependent. But the evidence is sufficient to reject the conventional wisdom that antitrust and industrial policy are opposing strategies.

Competition is not the enemy of industrial strength. It is, properly understood, itself a form of industrial policy.

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Organizations with extraordinary reach (hundreds of millions of followers, billions in revenue, democratic mandates to govern) fail systematically at basic operational tasks. Mr. Beast mobilizes 323 million YouTube subscribers, more viewers than the entire U.S. population. His Lunchly meal kits, launched September 2024, faced FDA complaints and widespread reports of moldy cheese within one month. YouTuber Rosanna Pansino documented finding mold in products two months from expiration. When pressed, Mr. Beast blamed retailers and consumers, ignoring supply chain, packaging, and storage failures entirely.

Consider Elon Musk’s Department of Government Efficiency (DOGE), launched on Trump’s first day of his second term in January 2025. The promise: $2 trillion in federal budget savings.

Why should we care? The confusion between reach and execution has consequences. When institutions optimize for visibility rather than capability, when dramatic gestures substitute for systematic improvement, people die. Not metaphorically: literally, as the DOGE catastrophe demonstrates. We think the problem runs deeper than individual failures. The pattern reveals a systematic confusion about what operational competence, also know as operational alpha in finance, actually requires.

Private Equity’s Uncomfortable Discovery: Operations Are Hard

Private equity offers a useful frame of reference here. For decades, PE firms claimed to create value through superior management. This is operational capability or excellence is called “operational alpha”. PE firms love talking about operational alpha, but was actually riding leverage and financial arbitrage. Analysis of deal-level returns tells the story: before 2000, operational improvements subtracted 6% from total value creation. In the 2000-2007 period, they contributed just 12%. Post-2008, only 3%. Leverage contributed 70% of value creation pre-2000, falling to 25% post-2008. The rhetoric claimed operations; the returns came from finance.

That said, circumstances changed. Rising interest rates after 2022 eliminated cheap leverage. Suddenly, PE firms actually needed the operational capabilities they’d been claiming to have all along. The industry responded by hiring hundreds of “operational specialists,” hosting conferences on operational alpha, developing sophisticated value-creation playbooks. The shift was genuine, not merely rhetorical.

But building genuine operational alpha proved harder than talking about it. A Harvard study tracking 1,580 deals found that 84% now include operational improvement actions in their plans, and these improvements do persist after successful exits. The operational value creation is real. Yet when initiatives fail, 67% of failures stem from controllable reasons: 53% from poor implementation, 37% from unrealistic business cases. The industry invested in operational capabilities, but execution quality remains highly uneven because operational alpha requires capabilities most financially-oriented operators simply lack.

This demonstrates the central point: when cheap capital that easy financial engineering needs disappeared, the industry discovered that operational improvement is hard.

The Influencer Illusion: Distribution Without Operations

KSI and Logan Paul’s Prime shows the same dynamics as Mr. Beast’s Lunchly. Class-action lawsuits allege caffeine content 15 to 25mg higher than advertised, allegations of PFAS contamination, and a $67.7 million lawsuit from bottler Refresco for backing out of production agreements. After explosive initial success generating $250 million in first-year sales, UK sales fell 50% year-over-year by April 2024.

NielsenIQ tracked 37 celebrity beauty brands and found only 23% failing, versus 90% failure rates for traditional CPG launches. Influencer brands actually outperform because of built-in audiences (at first).

The advantage proves temporary. Only 18% of influencer brand buyers could identify the celebrity who started the brand. Consumers prove “less likely to recommend influencer brands than mainstream brands.” Celebrity preference dropped from 17-22% in 2020 to just 11% in 2023.

Influencer brands excel at generating initial demand but collapse in execution. They mobilize millions to buy products but cannot ensure those products are safe, consistent, or properly manufactured. The asymmetry reveals a fundamental error: assuming distribution reach substitutes for supply chains, quality control, and other things that make up operational alpha.

Barnes & Noble: What Genuine Operational Improvement Actually Requires

Now consider the counterexample. When Elliott Management acquired Barnes & Noble in August 2019 for $683 million, the retailer was approaching Borders-style liquidation. The numbers at acquisition: $3.6 billion in revenue, $111 million EBITDA, a 6.15x multiple. 627 stores, down from 726 in 2008. More than $1 billion in lost market value over five years. CEO James Daunt said the company was “not quite there but pretty darn close” to following Borders into liquidation.

This was classic distressed retail, the type where private equity typically slashes costs, extracts value, and flips or liquidates. Elliott did something different.

Domain Expertise Proved Non-Negotiable

James Daunt had already turned around Waterstones using unconventional methods. Crucially, Daunt was a 30-year career bookseller who opened his first independent bookstore in 1990. He eschewed investment banking for books. This is operational credibility, not financial credentials.

Genuine Decentralization, Not Rhetoric

The core change: Give local store managers full autonomy over book selection, merchandising, and layout. As Daunt put it: “It’s ironic for somebody who runs chains, but I don’t think chain bookselling works. All I’ve done is bring the principles of independent bookselling to a chain.”

The measurable result: Book return rates dropped from roughly 15% industry standard to 9%, targeting 5%. Returns directly measure whether you’re putting the right books in front of customers. They don’t lie.

Counter-Cyclical Investment

During COVID shutdowns, B&N used downtime to refurbish stores, reorganize layouts, and reassess stock. This is the opposite of typical private equity extraction. They spent money improving assets when revenue was zero.

The Verifiable Results

Store expansion after 15 years of contraction. 16 new stores in 2022. 30 stores in 2023. 50 stores targeted for 2024.

Sales growth: “A good year on top of a prior good year” per Daunt in January 2024. Sales returned to pre-pandemic levels in 2021, then exceeded them. Profitability: Daunt in 2023: “We’ve now got both the profitability and the confidence to start opening up stores again.”

Daunt cut corporate staff in half, removing management layers. He eliminated “extraneous products that had turned B&N stores into indoor flea markets”: toys, electronics, random merchandise. Stores were “boring,” “a bit ugly,” and full of “irrelevant” products, in his words.

What Made This Work

Timeline shows patience. Elliott acquired B&N in August 2019. As of late 2024, they still own it, five years and counting. Store expansion accelerated in years 3-5, not months 1-2.

The improvements are operational, not financial. Elliott didn’t rely on leverage, tax optimization, or multiple arbitrage. Value came from fixing operations: better inventory curation, decentralized decisions, improved aesthetics, refocused product mix.

The changes are heterogeneous and specific. Not generic playbooks like “optimize procurement” or “implement ERP system,” but domain-specific improvements. Empower booksellers to curate. Eliminate publisher co-op payments promoting bad books. Reduce returns through better selection. You can’t copy-paste this.

The Private Equity Industry’s Operational Alpha Gap

Barnes & Noble is exceptional precisely because it achieved what most of private equity merely claims to achieve. McKinsey research indicates that PE funds focused on operational value creation achieved returns two to three percentage points higher than peers. PE firms now employ dozens or hundreds of “operational specialists” with sophisticated value-creation playbooks. Industry conferences feature panels on operational excellence. The rhetoric is pervasive.

But the gap between plans and execution reveals itself in operational details. AlixPartners’ survey found that 41% of PE executives identify senior leadership quality as a challenge in portfolio companies, compared to just 13% of portfolio leaders themselves, a massive perception gap. EY research shows that 81% of PE executives report holding periods extended by up to three years beyond historical averages, precisely because firms can’t execute operational improvements needed for clean exits.

The industry has genuinely invested in operational capabilities. We acknowledge that. But capability distribution remains highly skewed. Most firms can now articulate operational improvement plans. Far fewer can execute them. Barnes & Noble succeeded because Elliott hired a 30-year career bookseller, gave him genuine authority, maintained patient capital, and accepted that real improvements take years. These conditions almost never align in an industry where most partners have financial rather than operational backgrounds.

Toyota Versus Detroit: When Sophisticated Evaluators Confuse Metrics with Capability

DOGE demonstrates how ignorance destroys operational alpha (we’ll get there). But the problem runs deeper than incompetent reformers wielding chainsaws. Even sophisticated analysts confuse metrics with actual operational competence. The pattern appears not just in viral failures and government catastrophes, but in how markets themselves evaluate what “operational alpha” means.

Consider how credit rating agencies evaluated the auto industry during the 2008-2009 financial crisis.

On February 6, 2009, Moody’s downgraded Toyota from AAA (the highest possible rating) to AA1, citing the “significantly impaired state of profitability” due to severe global auto industry conditions. Just hours before the downgrade, Toyota announced it expected an operating loss of ¥150 billion ($1.66 billion) for fiscal year ending March 2009. This was Toyota’s first operating loss since it began publishing results in 1941 (though internal calculations showed a small loss in 1937-38, its first year of operation). Japanese media called it the “Toyota shock.”

The downgrade was remarkable because Toyota faced the crisis from a position of extraordinary financial strength. The company held $115 billion in retained earnings, savings accumulated, as NPR put it, like “a thrifty family.” Toyota required no government assistance. It did not declare bankruptcy. It returned to profitability by October 2009. The practical effect of the downgrade was to increase Toyota’s borrowing costs at the moment when the company’s operational resilience and financial resources positioned it for rapid recovery.

Contrast this with General Motors and Chrysler. Both filed for Chapter 11 bankruptcy in 2009 (Chrysler on April 30, GM on June 1). The U.S. and Canadian governments provided $85 billion in bailout funds. Employment at the Detroit Three plunged from 250,639 in 2007 to under 170,000 in 2009. GM’s North American hourly labor costs fell from $16 billion in 2005 to $5 billion in 2010 through massive layoffs and wage reductions. GM shed approximately one-third of its American workforce. Both companies terminated agreements with hundreds of dealerships and GM discontinued several brands (Pontiac, Saturn, Hummer).

Ford avoided bankruptcy by securing an $8 billion line of credit and $7 billion loan in 2006-2007, before the crisis hit. The bankruptcy/bailout process in 2009 allowed GM, Chrysler, and Ford to impose concessions on the UAW: two-tier wages, suspended COLA, frozen wages, reduced benefits, giving up the right to strike until 2015. Workers were told these were temporary sacrifices to save the companies. The automakers then enjoyed massive profitability for over a decade while maintaining these concessions, two-tier wages lasted 14+ years, COLA stayed suspended for 14 years, legacy workers got no raises for 9 years. It took a major strike in 2023 to finally reverse the 2009 concessions and restore what workers had given up to “save” the companies.

Meanwhile, Toyota preserved its workforce and never imposed similar permanent concessions.

The Operational Philosophy Divide

The divergence in responses revealed fundamentally different views of labor and operational alpha.

Toyota’s approach: The company did not lay off any permanent employees, though it cut around 9,000 temporary workers. Toyota instituted company holidays with pay of 80% of employees’ base salaries and adopted work-sharing systems to preserve employment. The company used production cutbacks as opportunities for training and improvement projects, including reducing plant breakeven points from 80% to nearly 70% of capacity. Toyota advocated for the view that trained workers as appreciating assets, not variable costs.

This reflected Toyota’s commitment, at the time of the Great Recession, to what is commonly called “lifetime employment,” though research shows this actually covered only 20-30% of Japan’s workforce, primarily at large established companies. By 2009, roughly 34% of Japanese workers were “irregular” (temporary) workers, up from 15% in 1984. Toyota maintained its commitment to permanent employees while shedding temporary workers, preserving the operational knowledge and capability embodied in its core workforce to the point the credit agencies felt like they need to explicitly punish Toyota for dare doing so.

Detroit’s approach: Mass permanent layoffs, forced restructuring, treating labor costs as the primary problem. GM CEO Rick Wagoner was forced to resign as a condition of receiving government assistance. The bankruptcies allowed the companies to jettison pension obligations, reduce healthcare commitments, and implement lower wages for new hires. The restructuring prioritized immediate cost reduction over preserving operational capabilities.

What the Credit Downgrade Revealed

The Toyota downgrade exposes a fundamental problem in how institutions evaluate operational competence. Credit agencies assess short-term profitability metrics. Moody’s cited Toyota’s “significantly impaired state of profitability” and warned the company was “unlikely to meaningfully improve its operating performance” in the following fiscal year, despite acknowledging that Toyota will make it through the Great Recession.

That said, profitability and operational competence are not identical. Toyota’s operational capabilities (manufacturing processes, quality systems, supplier relationships, workforce knowledge) remained intact. The company’s $115 billion in retained earnings provided enormous financial flexibility. Its decision to preserve its workforce maintained the organizational knowledge required for rapid recovery.

The American automakers, by contrast, faced bankruptcy precisely because decades of poor operational decisions had left them with unsustainable cost structures and product quality problems. GM had lost market share for 30 consecutive years. The crisis exposed operational failures that had accumulated over decades.

Yet the credit downgrade happened to Toyota, not to GM or Chrysler (which were already rated junk by the time they sought bailouts). The paradox illuminates our central point: legible metrics (quarterly profitability) dominate institutional evaluation, while actual operational competence (the capability to execute consistently over time) goes unmeasured until failure becomes unavoidable.

Toyota’s sales dropped 33.9% during the recession, but the company maintained profitability by pivoting to fuel-efficient models like the Prius and Corolla. By preserving its workforce and operational capabilities, Toyota positioned itself to capture market share as the economy recovered. American automakers achieved cost reduction through mass layoffs but lost the organizational knowledge required for sustained operational excellence.

The credit agency evaluation had a point: Toyota’s short-term profitability had deteriorated, but credit agencies aren’t about the short term but long term expectations. But it missed what mattered: the company’s operational resilience and financial resources would enable rapid recovery, compared to the rest of the industry. This same confusion between legible metrics and actual capability appears repeatedly when institutions evaluate operational competence.

DOGE: When Ignorance Masquerades as Boldness

Now we arrive at the most spectacular recent failure, one that perfectly demonstrates what happens when you mistake speed for competence, cruelty for efficiency, and viral attention for operational alpha.

The Department of Government Efficiency (DOGE), led by Elon Musk and launched on Trump’s first day of his second term in January 2025, promised to save $2 trillion from the federal budget. It disbanded quietly in November 2025, eight months before its scheduled expiration, having achieved a fraction of its goals while causing catastrophic damage.

The Numbers Tell the Story

Musk initially promised $2 trillion in savings, then walked it back to $1 trillion, then $150 billion. DOGE ultimately claimed $214 billion, but multiple analyses showed these figures were grossly inflated. DOGE claimed to have cut an $8 billion ICE contract that was actually worth $8 million, adding two zeros.

The actual cost? The Partnership for Public Service estimated DOGE’s actions cost $135 billion in fiscal year 2025 alone, through lost productivity, paid leave for fired-then-rehired workers, and administrative chaos. This excludes estimated $323 billion in foregone tax revenue over the next decade from cutting 40% of IRS staff.

DOGE claimed $214 billion in questionable savings while generating $135 billion in immediate, documented costs. That’s the scoreboard.

Fire First, Discover Critical Functions Later

DOGE staffers were described as young coders without government experience, making decisions about complex agencies they knew nothing about. The pattern repeated: fire first, discover critical functions later, scramble to rehire.

Approximately 350 employees at the National Nuclear Security Administration, overseeing America’s 5,000 nuclear warheads, were fired Thursday and frantically rehired Friday after Congress warned of “dire national security implications.” The Department of Agriculture fired employees working on H5N1 avian influenza response, then scrambled to rehire them days later. Republican Representative Don Bacon summarized: “There’s an old saying, ‘Measure twice, cut once.’ Well, they are measuring once and having to cut twice.”

The FAA fired approximately 400 employees in February 2025, just three weeks after 67 people died when a passenger plane collided with an Army helicopter near Washington, D.C. DOGE cut 7,000 SSA employees, more than 12% of the workforce, while the acting commissioner admitted DOGE officials were “outsiders who are unfamiliar with nuances of SSA programs.”

And on and on.

The Human Cost: 600,000+ Deaths

The most catastrophic failure came with USAID’s effective shutdown in July 2025. Musk celebrated that he “spent the weekend feeding USAID into the wood chipper” and later wielded a chainsaw at a conservative gathering.

USAID, representing just 0.5% of government spending, had prevented more than 91 million deaths between 2001 and 2021 through programs targeting HIV/AIDS, malaria, tuberculosis, maternal health, and nutrition. A peer-reviewed study in The Lancet projected USAID’s shutdown could result in more than 14 million additional deaths by 2030, including more than 4.5 million children under age five.

As of November 2025, estimates exceeded 600,000 deaths, mostly children, from halted HIV treatment, malaria prevention, tuberculosis control, and nutrition programs. Internal USAID memos obtained by ProPublica warned of these consequences. USAID staff repeatedly shared these projections with political appointees, who “wholly prevented” staff from implementing promised exemptions for lifesaving aid.

When DOGE quietly disbanded in November 2025 after Musk and Trump had a “stunning public feud,” the entity that promised $2 trillion in savings, delivered $214 billion in inflated claims, cost $135 billion in documented waste, and contributed to countless deaths had simply disappeared. No accountability. No reckoning. Just gone.

The Common Thread

Both Mr. Beast and Musk can mobilize enormous attention instantly. Both failed catastrophically at basic operations. The similarity extends beyond reach. Both optimized for what’s visible, visceral, and dramatic: viral launches, mass firings, big numbers, bold claims. Both systematically underinvested in the messy back-office work of actual operations: manufacturing processes, quality control, systems understanding, domain expertise.

When Mr. Beast ships moldy cheese, he blames retailers. When DOGE fires nuclear weapons experts by accident, it claims the people were redundant. The playbook is identical: generate dramatic visible action, ignore operational reality, deflect responsibility when systems collapse.

What Differentiates Success: The Rare Conditions

Barnes & Noble and Toyota succeeded because conditions aligned in ways that are exceptional.

Toyota preserved its workforce precisely because it viewed operational knowledge as an appreciating asset. Daunt already executed successfully at Waterstones. Toyota had decades of refining its production system and treating systematic improvement as core capability. Both approaches empowered workers to identify and solve problems rather than imposing solutions from above.

Both absorbed short-term losses rather than destroying capabilities to preserve quarterly metrics. Both prioritized long-term viability over immediate cost reduction. The improvements are domain-specific. You can’t copy-paste them to other industries. Not generic cost-cutting but careful operational enhancements requiring deep knowledge.

These conditions almost never align. Most private equity firms hire financial operators. Most influencers prioritize reach over manufacturing capability. Most politicians prioritize visible action over operational understanding. Credit agencies evaluate quarterly metrics over operational resilience.

Why Operational Execution Is Hard

Viral marketing scales through network effects. A large following becomes self-reinforcing. Mr. Beast’s 323 million subscribers amplify every launch. Dramatic action is immediately legible. Firing thousands of people, wielding a chainsaw, launching a product to millions: these generate instant metrics, news coverage, apparent results.

Operational execution doesn’t scale the same way. Each product requires specific manufacturing processes, supply chain management, quality control protocols. Each government agency serves different functions with different constraints. The heterogeneity is irreducible.

More specifically, operational execution requires capabilities that influencers and ideologically-motivated reformers typically lack. Deep knowledge of manufacturing processes, supply chain logistics, organizational design, quality systems. Patience, because operational improvements take quarters or years, not weeks. Accepting accountability for outcomes rather than deflecting to external factors. Actually caring about operational details rather than treating them as instrumental to building an audience or demonstrating ideological purity.

Why the Myth of “Efficiency Through Cruelty” Persists

Why do we put up with it? Several dynamics reinforce the pattern.

Cruelty is visible and visceral. Firing 10,000 people generates immediate, measurable results: lower payroll, higher margins, news coverage. Building better systems, improving quality control, reorganizing workflows: these are harder to measure, take longer to show results, don’t make dramatic headlines.

Speed substitutes for understanding. Moving fast and breaking things works when you’re building a consumer app with rapid feedback loops. It catastrophically fails when managing nuclear weapons, disease surveillance, or air traffic control, systems where “breaking things” means dead people and where you often can’t undo the damage. But speed looks like competence.

Ignorance masquerades as boldness. When you don’t know how a system works, radical simplification seems obvious: just cut 80%, obviously there’s waste. When you do know how it works, you understand the consequences: fire the en route charting specialists and controllers (who are also have been cut and short staffed) literally cannot do their jobs because only a handful of trained workers in the country can update navigation charts.

Short-term metrics mislead (assuming they are accurately reported). DOGE claimed $214 billion in “savings” while the $135 billion in immediate costs and 600,000+ deaths wouldn’t show up in the same ledger. Moody’s downgraded Toyota for short-term profitability concerns while ignoring the operational capabilities and financial resources that enabled rapid recovery. GM and Chrysler optimized quarterly metrics for decades while operational competence eroded until bankruptcy became inevitable. When the metrics you’re optimizing diverge from actual value creation, you can look successful while failing catastrophically.

The Lost Capabilities and the Hard Truth

America once built extraordinary operational capabilities. The Bureau of the Budget’s systematic training programs during WWII and the post-war era. The quality management systems that helped achieve 80% public trust in government by the 1950s. These weren’t just policies but complex organizational capabilities built over decades through systematic training, detailed workflow analysis, genuine worker engagement.

President Clinton’s National Performance Review in the 1990s marked the moment when American institutions chose dramatic transformation over systematic improvement. The NPR prioritized politically expedient cost-cutting and workforce reductions over the proven systematic improvement methods that had delivered results in the past. While it achieved some successes (electronic tax filing, FirstGov.gov, new institutional structures), these gains proved fragile precisely because the initiative failed to build sustainable improvement capability within agencies.

The hard truth is that we don’t know how to fully rebuild the capabilities we’ve lost. We can’t simply dust off old manuals or recreate training programs from the 1950s. Some government functions work reasonably well. But the overall trajectory is clear.

That said, we can take careful inventory of what works. We can systematically document successful approaches. We can learn from exceptions like Barnes & Noble and Toyota, cases where operational excellence was actually achieved through domain expertise, genuine decentralization, patient capital, proper incentives.

We can stop confusing viral reach with operational alpha, speed with competence, dramatic gestures with systematic improvement.

Why Government Failures Matter More

Government systems affect everyone with no exit option. When private companies fail, consumers might choose alternatives (though as we learned with the baby formula crisis, significant lag time may occur before alternatives emerge). When government fails operationally (when USAID programs collapse, when FAA fires aviation safety specialists, when permitting processes make housing construction impossible), citizens cannot opt out. The failure is imposed universally, or nearly so. The stakes are categorically higher.

Government systems are often more complex than private sector equivalents: more stakeholders, more constraints, more competing objectives, longer time horizons, higher accountability demands. This means the operational execution gap matters more, not less.

And yet: government systematically underinvests in this operational alpha. Agencies inherit procedures from decades past, bolted onto legacy systems, encrusted with workarounds. Nobody really designed the current system; it evolved. Because there’s no systematic improvement process anymore, the same failures persist.

The Incentive Problem: Why Failure Pays

Here’s what makes the pattern sustainable: the people who generate operational catastrophes rarely bear the costs.

Mr. Beast and Logan Paul continue accumulating wealth, launching new ventures, commanding massive audiences despite repeated operational failures. The market allows them to fail repeatedly because their personal brands remain intact. The operational failures damage suppliers, manufacturing partners, employees, consumers. The influencers move on to the next launch.

Musk’s DOGE disbanded in failure after generating massive documented costs and contributing to hundreds of thousands of deaths. His net worth continued growing throughout. The fired-then-rehired federal employees bore the costs. The children who died from halted HIV treatment and malaria prevention bore the costs. American taxpayers who funded the chaos bore the costs. Musk faced no meaningful consequences, and received bigger and bigger pay packages from the Tesla Board and funding from the US for SpaceX (The youtuber Thunderf00t does a great job at explaining what is going on with SpaceX) .

The consequences of failed private equity operational improvements fall on portfolio company employees, suppliers, communities. PE partners collect management fees and carried interest regardless. The rhetoric generates fundraising success even when reality fails.

Hype and rhetoric remain bad for operational outcomes but wonderful for personal wealth. Those with reach or capital face minimal accountability for operational failures. The broader market rewards narrative over operations, visibility over competence, dramatic gestures over systematic improvement. As long as individuals can extract wealth while externalizing operational failures onto others (and as long as the costs fall on suppliers, employees, taxpayers, and the vulnerable rather than decision-makers) the incentive to develop genuine operational competence remains weak.

The Verdict

We’ve run the experiment of treating government dysfunction as a resource problem, as a leadership problem, as a boldness problem.

The results are in.

None of these work. Until we recognize that operations is hard in ways that audience mobilization, financial engineering, and performative action are not, until we stop mistaking moldy cheese for revolution, mass firings for efficiency, and 600,000 deaths for success, we should expect government dysfunction to persist.

Not because the problems are unsolvable. They’re not. But because we keep trying to solve them by putting charismatic salespeople with methods that hasnot, cannot, and doesnot work. The system is doing exactly what it’s designed to do. Until incentives realign, actors will continue to optimize what’s measured and rewarded.

Which increasingly means optimizing the scoreboard rather than the game itself. And as long as optimizing the scoreboard generates personal wealth while the costs of losing the game fall on everyone else, we should expect more of the same.

Government grants for business research and development (R&D) helped small and medium-sized companies spend more and attract private investment. But for large firms, these grants actually seemed to replace private funding, according to new research using data from the Czech Republic ("Crowding in or crowding out? Evidence from discontinuity in the assignment of business R&D subsidies" by Matěj Bajgar and Martin Srholec).

Why it matters: Governments worldwide spend billions on R&D direct grants, loans, and procurement contracts (over $50 billion each year in developed countries before 20). They hope this encourages companies to innovate more than they would on their own, thinking that sometimes good ideas don't get funded because of risks or information gaps. Knowing who these grants help and how they help is important for making good policies. Past studies have shown mixed results, partly because it's hard to prove cause-and-effect and get good data. This study shows that who gets the grant matters a lot.

About The Paper: The researchers used a strong method called regression discontinuity (RD) to study the effects of a major Czech R&D grant program called "ALFA." This method helps figure out the real impact of the grants.

• The Program: ALFA gave out about 340 million euros between 2011 and 2018. It funded research projects (usually lasting 3-4 years) in areas like advanced technology. Companies often worked with universities or research groups. The average grant for a company was about 190,000 euros, which was often small compared to the company's total R&D spending (around 1.3 million euros) or sales (around 36 million euros). The grants covered costs like salaries, materials, and sometimes equipment.

• The Setup: ALFA gave grants based on scores from expert reviews. Companies whose project scores were just above the cutoff score needed to get funding were compared to companies whose scores were just below. Because these companies were likely very similar in other ways, this comparison helps show the true effect of the grant. The researchers used standard statistical techniques for this type of analysis.

• The Data: A key part of the study was linking official records about ALFA applicants and their scores with detailed, private data about the companies from the Czech Statistical Office (CZSO). This data covered 2007 to 2021 and included how much companies spent on R&D (total, private funding, government funding), patents, sales, number of employees, and productivity. Having this direct R&D spending data was a big advantage over many past studies. The study looked at 994 company projects after matching data and removing extreme cases.

Data & Insights:

The researchers carefully checked their method (making sure scores weren't manipulated near the cutoff and that companies just above and below the cutoff looked similar before the grants). They found very different results depending on the company's size:

• SMEs Get a Boost (Companies with fewer than 250 employees):

  • More Private Money: Grants strongly encouraged SMEs to spend more on R&D. During the grant period, their total R&D spending went up by about 71%. Importantly, their spending using private money also went up significantly (by about 156%). This means the grants brought in additional private investment. For every 1 euro of grant money, SMEs spent about 2.3 euros more on R&D in total.

  • Lasting Effects: The boost to R&D spending lasted long after the grant money ran out (up to 8 years later). Total R&D spending was about 186% higher in the years after the grant ended. This seems connected to the fact that companies that got ALFA grants were more likely to get future grants from the same government agency (TA CR), but not from other government sources. The effect came from spending on current costs (like salaries), not from buying long-term equipment with the initial grant.

  • Performance: SMEs that got grants saw a short-term increase in their sales per employee (about 18% higher during the grant period).

  • Limits: However, the grants didn't lead to more patents, long-term growth in sales or productivity, or more jobs for these SMEs near the funding cutoff. This might mean the projects funded right at the edge were smaller steps rather than big breakthroughs.

• Large Firms React Differently (Companies with 250 or more employees):

  • No Boost: Grants did not increase total R&D spending for large firms. The results were near zero or even negative.

  • Less Private Money: Evidence showed that grants replaced private R&D spending in large firms. Their spending from private funds went down significantly (by about 38%) during the grant period. They basically used the government money instead of their own.

• Why the Difference?

  • Money Problems: Financial challenges seemed to be a big reason. Grants had much stronger positive effects on companies that likely had trouble getting funding elsewhere (based on a financial health score called the Altman Z-score). The effects on financially healthy companies were small or zero. (Company age wasn't a good indicator here because most companies in the study were older).

  • Grant Size: The positive effect was also bigger when the grant amount was larger compared to the company's usual R&D budget.

Between the lines: This study is strong because it used a reliable method (RD) and had direct data on R&D spending, allowing clear conclusions about whether private money was added or replaced. The long timeframe showed that getting one grant can lead to more grants from the same agency later. For large companies without money problems, grants might just pay for R&D they would have done anyway. For SMEs, grants can make R&D possible that wouldn't happen otherwise and build connections with funding agencies, even if the results aren't major new inventions right away. The study confirmed its results held up even when changing details of the analysis.

The bottom line: R&D grants work differently for different companies. They seem very effective at encouraging more R&D spending in smaller companies by helping them overcome funding challenges and building relationships with the grant agency. But giving grants to large, financially stable companies might just be substituting public funds for money they would have spent anyway, without increasing overall R&D. To get the most "bang for the buck," targeting grants towards companies that genuinely need the financial help seems important. This ensures public money supports truly additional R&D activity. These conclusions apply most clearly to projects near the funding cutoff; projects that scored much higher might have had bigger, more groundbreaking results.

A new study (The Economic Footprint of Short-Term Rentals on Local Businesses: Evidence from Portugal by Ronize Cruz, Francisco Nobre, and João Pereira dos Santos) reveals how Airbnb-style rentals transform local business landscapes, especially in Lisbon and Porto. The research uses extensive firm-level data to track how different types of businesses fare when exposed to increasing short-term rentals.

Key Context & Numbers

• Short-term rentals represented 47% of tourist accommodations in Portugal by 2019

• Housing used for short-term rentals (2015-2020):

  • Porto: 12%

  • Lisbon: 11%

  • For comparison: Paris (4.6%), Madrid (3%), Barcelona (9.3%)

• The study analyzed 46,928 private firms:

  • 73% located in Lisbon

  • All single-establishment businesses

  • Tracked from 2013-2019

Major Findings

Business Closures

Areas with higher exposure to short-term rentals saw increased business closures. Most affected were businesses that had been operating with:

• Had about half the sales of surviving businesses

• ~40,000 lower sales per worker annually

• Often operated with negative profits

Closure mechanisms:

• Commercial rents rose dramatically in high-rental areas after 2015

• Tourist-oriented businesses saw 0.913-1.13% higher closure rates

• Restaurants and bars: ~1% higher closure probability

• Retail stores: significant closure increases when using broader industry categories

Surviving Businesses

Tourist-oriented businesses saw significant gains:

• Employment metrics:

  • 23% increase in hours worked

  • 25% increase in employee numbers

  • 28% increase in wages

• Financial performance:

  • 16% increase in sales

  • Significant increases in net profits

  • 14% increase in total liabilities

  • 17% increase in external expenses

  • 10% increase in liquidity

Resident-oriented businesses:

• 16% increase in sales

• 11% increase in total liabilities

• Some productivity gains

• No significant profit changes

Hotels:

• No negative impact on sales

• 1.27% increase in net profits

• 22% increase in liquidity

Local retail stores:

• 77% increase in sales

• Significant productivity gains

New Business Formation

Higher rental areas saw:

• 2.5-6% higher probability of new tourist-oriented vs. resident-oriented businesses

• 1-2.8% higher probability of tourist businesses vs. other types

• 0.7-1.6% higher probability of new restaurants/bars

New businesses compared to closed ones:

• Higher sales volume

• No significant productivity advantages

• No clear profit advantages

• Higher initial costs in high-rental areas

Methodology Details

• Used comprehensive firm-level accounting data

• Created registry rate measure: new short-term rentals in 2016 divided by the number of dwellings

• Employed shift-share instrumental variable based on:

  • Distance to top tourist attractions

  • TripAdvisor reviews

  • Google search data

• Controlled for:

  • Parish unemployment rate

  • Population density

  • Firm age

  • Pre-treatment trends

  • Industry and municipality fixed effects

Why It Matters

The ripple effects of short-term rentals fundamentally reshape urban economies in ways we're just beginning to understand. We're watching entire neighborhoods transform their identity as tourist-focused areas become more distinct from residential ones. This shift is fascinating because it happens through market forces reacting to urban planning. For cities worldwide, Portugal's experience offers a crystal ball view of what happens when short-term rentals become a significant force in the local economy.

What to Watch

Keep your eyes on how other tourist hotspots handle this transformation. The real story isn't just about housing anymore – how entire urban ecosystems adapt. Watch for cities experimenting with new zoning laws to balance tourist and resident needs. Commercial real estate markets will be particularly telling – they might start pricing in the "tourist premium" in specific neighborhoods. And pay attention to the types of businesses opening in high-tourist areas. Will we see a complete transformation of business districts, with traditional local services giving way to tourist-oriented ventures? The answers to these questions could reshape urban planning for decades to come.

As automation technologies spread, understanding their impact on employment is crucial for policymakers and businesses. This study, "Automation and flexible labor contracts: Firm-level evidence from Italy," by Silvio Traverso, Massimiliano Vatiero, and Enrico Zaninotto, explores how automation investments relate to firms' use of flexible labor contracts.

The big picture: New research finds that firms investing in automation also tend to increase their use of flexible labor contracts, suggesting these technologies complement rather than replace workers. This relationship may have been overlooked in previous debates about labor market reforms.

Key findings:

• Firms that invested in automation saw a 9% increase in flexible workers compared to non-investing firms.

• Automation investment was also associated with the following:

  • 5% increase in total employment

  • 7-8% increase in employee turnover

  • 10-12% increase in hiring

  • No significant effect on job terminations

• About 2/3 of the increase in flexible workers was directly related to automation, with 1/3 indirectly due to overall employment growth.

• The study used data from about 10,450 Italian firms between 2015-2018.

Between the lines: The researchers argue that automation and flexible labor are complementary because they both enhance firms' "operational flexibility"—the ability to quickly adjust production to market changes.

• Automated systems are reprogrammable, allowing rapid task switching.

• Flexible contracts enable swift workforce adjustments.

• These provide maximum adaptability for firms facing volatile demand and intense competition.

The catch: While the study shows automation increases hiring, it also boosts the use of flexible contracts. Previous research indicates that such contracts reduce job security and wages over the long term. This creates potential tension: more jobs but lower paying and less stable ones.

What they're saying: If the complementarity hypothesis holds, changes in employment legislation that increase the costs for firms to adjust their workforce promptly will also diminish the returns on firms' investments in automation

About the paper:

• The study considered "hard" automation technologies like robotics, IoT, big data, and augmented reality.

• It used a matched difference-in-differences approach to compare firms that invested in automation to similar non-investing firms.

• The authors suggest that future labor reforms should protect workers without compromising firms' workforce flexibility.

  • Introducing minimum wages or direct support for low-income workers

  • Promoting training programs for task-specific skills

  • Developing national skill certification systems

  • Encouraging internal workforce flexibility

Bottomline: Policymakers aiming to improve worker protections should be mindful of how this may impact firms' ability to benefit from automation investments. The complementarity between flexible labor and automation may be stronger than previously recognized.