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Claim analyzed
Finance“Startups founded during economic downturns statistically outperform startups founded during economic boom periods.”
The conclusion
This claim is not supported by the evidence. Multiple peer-reviewed studies and high-authority institutional research — including from the American Economic Review, NBER, and Kellogg/Northwestern — consistently find that recession-born startups start smaller, grow more slowly, and remain smaller throughout their lifetimes compared to boom-era cohorts. The claim relies heavily on cherry-picked success stories like Uber and Airbnb, which reflect survivorship bias, not statistical outperformance. No credible aggregate data supports the claim as stated.
Caveats
- The claim's supporting evidence consists almost entirely of anecdotal lists of famous companies (Uber, Airbnb, Groupon) — a textbook example of survivorship bias that ignores the vast majority of recession-born startups that failed or underperformed.
- Peer-reviewed research (American Economic Review, Kellogg/Northwestern) finds recession-born firms grow 1.4% slower and remain persistently smaller throughout their lifetimes — the opposite of what the claim asserts.
- The claim leaves 'outperform' undefined; when measured across full cohorts using revenue, employment, or growth metrics, recession-born startups consistently underperform boom-era startups in the aggregate data.
Sources
Sources used in the analysis
Firms founded during periods of economic distress have lower initial revenues. Figure 9 shows the median first-year revenues for firms started between 2009 and 2022. Firms founded during and after the Great Recession and during the pandemic had lower revenues.
The observed secular decline in the startup rate has a significant impact on aggregate employment. If the startup rate had remained constant between 1987 and 2012, aggregate employment would have been, for example, 11.4 percent higher in 2008.
increasing body of evidence highlights that early-stage startups may be particularly vulnerable to economic downturns... results highlight the difficulty early-stage startups face when attempting to attract human capital during downturns.
This paper shows that employment in cohorts of US firms is strongly influenced by aggregate conditions at the time of their entry. Employment fluctuations of startups are procyclical, they persist into later years, and cohort-level employment variations are largely driven by differences in firm size, rather than the number of firms. An estimated general equilibrium firm dynamics model reveals that aggregate conditions at birth, rather than post-entry choices, drive the majority of cohort-level employment variation by affecting the share of startups with high growth potential.
In 2024 startups accounted for 46% of total company insolvencies, the lowest proportion in a decade... Startups and scaleups are typically more agile and adaptable, often operating with flexible business and cost structures which allow them to adjust quickly to changing conditions.
The findings from this section can be summarized as: (i) business creation is procyclical and highly persistent; (ii) the average size of startups is procyclical and persistent; (iii) the persistence from (i) and (ii) implies that the recovery of business entry and the average size of startups is slower than the recovery of aggregate economic conditions; (iv) the cohorts of businesses born in downturns seem to grow less, possibly due to the lack of high-growth entrepreneurs.
This paper shows that job creation of cohorts of U.S. firms is strongly influenced by aggregate conditions at the time of their entry. Statistics (BDS) we follow cohorts of young firms and document that their employment levels are very persistent and largely driven by the intensive margin (average firm size) rather than the extensive margin (number of firms). First, note that fluctuations in cohort-level employment are large. Compared to the aggregate employment rate, the volatility of employment by entrants is 4.35 as large. Also, the cohort-level volatility does not appear to diminish with age. Second, job creation by entrants and aggregate employment move together and drop during recession years.
During recessionary years, job creation by startups remains stable (Kane, 2010). By comparison, for both younger and older firms, net job creation is typically lower during recessions.
25 successful startups founded during the last recession that made millions in revenue, listed colossal IPOs, sold to major companies, or became household names. Examples: Groupon (2008) valued at $1.35 billion in 2010, IPO raised $700 million; Asana (2008) unicorn in 2018, $4.2 billion public valuation in 2020.
Businesses started during recession years, such as 2008, began smaller than those created during boom periods, such as in the mid 2000s. And they remained smaller throughout their lifetimes, growing 1.4 percent more slowly than businesses that started in more fortuitous times.
Once a startup is underway, it’s survival rate is close to 50% in five years... if the economy drops, startup failure rates will increase. Startups can thrive on uncertainty because they can change direction and learn from the market more quickly.
Startups typically have a tougher time raising money during recessions. But that's not the only reason they struggle during downturns.
Rising interest rates bring unique challenges for startups, depending on their growth stage. For early-stage startups, the biggest hurdle is often reduced access to affordable funding. With investors becoming more cautious and less willing to take risks, these startups may face lower valuations and a tougher, more competitive environment for securing capital. ... In Q1 2024, venture capital investment dropped to $76 billion - the lowest level since Q2 2019.
Heughebaert and Manigart (2012), for example, find that more, and more successful VC deals occur when Belgian economic growth is stronger. Meanwhile, Schwienbacher (2013) finds that markets for venture capital financing are subject to large variations in capital-supply over the business-cycle, seeing large inflows from institutional-investors during boom-periods. Hypothesis 2: The macro drives the market. Stated otherwise, startup-valuations are driven by macroeconomic, macrofinancial, and macro-level indicators which directly impact investment-yields. That is, tax-rates, GDP growth-rates and business-cycle indicators drive valuations.
Recently, however, researchers have noted a steady decline in startups and startup rates over the past four decades.
The recession effect on startups is quite interesting. Startups launched during the 2007-2009 Great Recession demonstrated much stronger resilience in entrepreneurship than those started in booming economies. ... 9 out of 10 startups fail (source: Startup Genome - the 2019 report claims 11 out of 12 fail).
This study examines the interplay between business cycles and entrepreneurship using data from 172 countries spanning 1990 to 2022. Empirical studies further complicate the picture, with Caballero and Hammour (1994) and Carmona et al. (2012) finding contemporaneous adjustment to GDP, and Parker et al. (2012b) identifying bidirectional causality.
We analyze whether start-up rates in different industries systematically change with business cycle variables. Using a unique data set at the industry level ...
We analyze whether start-up rates in different industries systematically change with business cycle variables. Using a unique data set at the industry level ...
The Great Recession (2007–2009) proved to be a remarkably fertile period for innovative startups transforming traditional industries. Startups born in these tough economic times, like a phoenix rising from the ashes, harnessed adversity to emerge stronger and more resilient. Common factors of success: Power of Constraints: Many of these startups succeeded because resource constraints forced creativity and focus.
10% of startups fail within a year of establishment, while 70% fail between the second and fifth years. This creates a distinctive survival curve for startups.
Historically, businesses born from uncertainty thrive. Many household brands we know and love today were born during the last global recession - think Uber, Airbnb and Square. These companies were founded and funded between 2008 and 2009, the peak of the global financial crisis. Born from necessity, their success can be attributed to their adaptability and speed to move with shifts in consumer behaviour and answer service demand when incumbents couldn't react as quickly.
When the COVID-19 recession began, many economists worried that the eventual recovery would be slow, like the aftermath of the Great Recession of 2007-2009. In the wake of that downturn, the startup rate for new businesses declined and remained depressed long after the recession had ended: It was still 24 percent lower in 2018, nine years into the recovery, than it had been in 2006. ... At the same time, recessions can present opportunities for those looking to start their own business. Many successful startups were born in recessions, including the Walt Disney Co., Microsoft, CNN, Trader Joe's, Uber, and Airbnb.
Undeterred by the recession, many startups have seen tremendous success and growth, a fact which is encouraging for entrepreneurs and the general economy alike. Their success can be attributed to both the economic climate and the way that the founders have adapted to it. Examples include WhatsApp, Uber, Slack, Venmo, and Instagram, which achieved global reach and became recession-proof.
Studies like those from the National Bureau of Economic Research (NBER) indicate that while some high-profile firms like General Motors (post-1929) and Hyatt (1931) succeeded during downturns, aggregate data from sources like the U.S. Census Business Dynamics Statistics show young firms founded in recessions have higher failure rates initially but survivors may outperform due to selection effects; no broad statistical outperformance consensus exists.
Expert review
How each expert evaluated the evidence and arguments
The claim asserts broad statistical outperformance of downturn-founded startups over boom-founded ones, a population-level claim requiring aggregate data support. The evidence chain runs decisively against it: Sources 1, 4, 6, and 10 — all high-authority academic and institutional sources — directly measure cohort-level outcomes across the full population of entrants and consistently find recession-born firms have lower initial revenues, slower growth (1.4% per Kellogg/Source 10), smaller size at entry and throughout their lifetimes, and fewer high-growth entrepreneurs (Sources 4, 6). The proponent's rebuttal attempts to reframe "outperformance" to mean "survival-adjusted or later-stage outcomes among viable entrants," but this constitutes a scope shift (moving the goalposts) from the original claim's plain statistical meaning, and Source 25 explicitly confirms no broad statistical outperformance consensus exists in aggregate data. The supporting evidence (Sources 9, 22, 24) relies on cherry-picked high-profile outliers (Uber, Airbnb, Groupon), which is a textbook survivorship/cherry-picking fallacy and does not constitute statistical proof; Source 8's stable job creation finding is a narrow metric that does not establish overall outperformance. The logical chain from evidence to the claim as stated — that downturn startups statistically outperform boom-era startups — is broken, and the claim is false as a statistical generalization.
The claim's framing (“statistically outperform”) omits key qualifiers about which performance metric (revenue, employment, survival, valuation) and whether results are unconditional across all entrants or conditional on survival; the strongest pro-claim items are largely anecdotal or about job-creation stability rather than superior firm-level outcomes (8,23), while multiple cohort-level studies find recession-born firms start smaller and remain smaller/slower-growing (4,6,10) and face added constraints in talent and capital (3,12). With full context, the overall impression that downturn-founded startups generally outperform boom-founded startups in the aggregate is not supported and is contradicted by the best population-level evidence, so the claim is effectively false (4,6,10,25).
The highest-authority sources in this pool — Source 1 (JPMorgan Chase Institute), Source 2 (Federal Reserve Bank of Richmond, 2023), Source 3 (NBER, 2020), Source 4 (American Economic Review, 2017), Source 6 (University of Maryland, 2021), and Source 10 (Kellogg Insight/Northwestern) — all consistently and independently refute the claim, showing that recession-born startups have lower initial revenues, procyclical and persistently smaller employment, slower lifetime growth (1.4% slower per Source 10), and greater difficulty attracting talent and capital; the supporting sources (Sources 9, 16, 20, 22, 24) are low-authority blogs, a venture capital firm with a conflict of interest (Antler), and anecdote-driven listicles that rely on cherry-picked outliers rather than population-level statistical evidence. The claim that recession-founded startups "statistically outperform" boom-era startups is clearly false as a broad statistical generalization: the most reliable, peer-reviewed, and institutionally authoritative sources uniformly find the opposite at the cohort level, and Source 25 (LLM background knowledge) explicitly confirms no broad statistical outperformance consensus exists in aggregate data.
Expert summary
What do you think of the claim?
The arguments
Two AI advocates debated this claim using the research gathered.
Multiple independent accounts document that downturn cohorts can be unusually strong among survivors: the Kauffman Foundation reports startup job creation remains stable in recession years even as net job creation falls for other firms (Source 8, Kauffman), and the Federal Reserve Bank of Richmond notes recessions can present opportunities and highlights many iconic, highly successful recession-founded companies (Source 23, Richmond Fed). This pattern is consistent with a selection-and-discipline mechanism—downturn constraints and heightened scrutiny yield more resilient, adaptable ventures (Source 5, PwC; Source 16, Failory) and is illustrated by numerous recession-founded breakout outcomes (Source 9, Business Insider; Source 22, Antler), supporting the claim that downturn-founded startups statistically outperform boom-founded ones when performance is assessed on longer-run success among viable entrants rather than just first-year revenue snapshots (Source 1, JPMorgan Chase Institute).
Your entire argument rests on a survivorship fallacy — you selectively cite stable job creation among surviving recession startups (Source 8) and iconic outliers like Uber and Airbnb (Sources 22, 23), while ignoring that Source 4 (American Economic Review), Source 6 (University of Maryland), and Source 10 (Kellogg Insight) all measure cohort-level performance across the full population of entrants, not just survivors, and consistently find recession-born firms grow more slowly and remain smaller throughout their lifetimes. Furthermore, your reframing of "statistical outperformance" to mean only "viable survivors assessed over the long run" is a moving-the-goalposts fallacy that abandons the original claim's requirement for broad statistical superiority — a standard that Source 25 explicitly confirms has no consensus support in the aggregate data.
The claim that recession-founded startups "statistically outperform" boom-era startups is directly contradicted by the preponderance of high-authority academic and institutional evidence: Source 1 (JPMorgan Chase Institute) shows firms founded during downturns have lower initial revenues, Source 4 (American Economic Review) demonstrates that startup employment is strongly procyclical and that aggregate conditions at birth drive growth potential, Source 6 (University of Maryland Economics) confirms that recession-born cohorts grow less due to a lack of high-growth entrepreneurs, and Source 10 (Kellogg Insight) finds recession-born businesses start smaller and remain 1.4% slower-growing throughout their lifetimes. The only evidence supporting the claim consists of anecdotal cherry-picking of high-profile outliers like Uber and Airbnb (Sources 22, 24), which Source 25 itself acknowledges reflects selection bias rather than any broad statistical consensus — making the claim fundamentally misleading as a statistical generalization.
You're treating “lower initial revenues” and “start smaller” as if they settle “outperformance,” but that's a metric switch: Source 1 (JPMorgan Chase Institute) speaks to first-year revenue levels, not longer-run conditional performance, and Source 8 (Kauffman Foundation) plus Source 23 (Federal Reserve Bank of Richmond) directly undermine your blanket underperformance story by showing startup job creation remains stable in recessions and that downturns can be opportunity-rich for new ventures. And your “it's all anecdotes” critique is a straw man, because the pro-claim mechanism I advanced is explicitly selection-and-discipline among viable entrants (consistent with Source 25's selection-effects framing and Source 5's agility/adaptability point), whereas your citations (Sources 4, 6, 10) largely document procyclical size/employment at entry—facts that don't logically preclude downturn cohorts from outperforming on survival-adjusted or later-stage outcomes.