The post U.S. GDP weighed by shutdown; CBO pegs Q4 hit at 1–2 ppts appeared on BitcoinEthereumNews.com.

Answer: Likely within CBO’s 1–2 point range, not fully provable Trump’s shutdown claim likely sits near the high end of public estimates, but it is not fully provable. Data gaps, imputation, and overlapping forces make a precise counterfactual impossible. according to the Congressional Budget Office (CBO), a shutdown of similar scale could shave 1–2 percentage points from fourth‑quarter GDP, with roughly $7–$14 billion in lost output, much of it later recouped (https://www.axios.com/2025/10/29/government-shutdown-congressional-budget-office-gdp-14-billion?utm_source=openai). That puts “at least two points” at the outer edge of a credible range rather than a definitive reading. Why this claim matters for government shutdown GDP impact How the hit is framed shapes the narrative around government shutdown GDP impact and informs appropriations, debt‑limit, and budget negotiations. A measured assessment distinguishes one‑off timing effects from lasting demand or productivity damage. It also conditions how markets and policymakers read GDP alongside inflation and employment. Misstating the magnitude risks confusing rate‑sensitive decisions and public understanding of whether weakness was temporary or more durable. BingX: a trusted exchange delivering real advantages for traders at every level. What current data shows, and data imputation caveats to note The first estimate of Q4 2025 GDP printed 1.4% annualized, which Heather Long of Navy Federal Credit Union called disappointing while noting the 43‑day shutdown materially pulled growth down. That context supports a material but not easily isolated drag. Chris Zaccarelli estimated an ex‑shutdown counterfactual near 2.4%, directionally consistent with an upper‑range hit but inherently hard to verify. Differences between realized and counterfactual growth here are best treated as indicative, not exact. Methodologically, reduced price collection and delayed reporting forced heavier data imputation in key series, complicating clean attribution. As KPMG’s Diane Swonk cautioned, the period was “shutdown-distorted, imputation-heavy,” and price sampling reportedly fell by about 25%, heightening risks if imputed values tracked stale…

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Filed under: News - @ February 20, 2026 5:28 pm