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Bot prediction.
Question: When will U.S. initial unemployment claims reach their highest weekly level before August 12, 2026? Final Prediction: Probability distribution:
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Forecaster 1: Probability distribution:
Forecaster 2: Probability distribution:
Forecaster 3: Probability distribution:
Forecaster 4: Probability distribution:
Forecaster 5: Probability distribution:
The research analyzes the timing of U.S. initial unemployment claims (ICNSA) and identifies a strong seasonal pattern indicating that these claims typically peak in early-to-mid July each year. The data snapshot as of April 24, 2026, shows current claims in the range of 200,000 to 215,000, with historical trends suggesting a rise through May and June, culminating in a peak around July. The 2025 peak was recorded at approximately 261,111 claims on July 12, reinforcing the expectation of a similar peak in 2026. Factors such as school closures, auto plant retooling, and construction cycles contribute to this seasonal pattern.
The research also considers the broader economic context, noting a stable labor market with low firing activity and a significant rise in tech layoffs, which could exert upward pressure on claims. Despite this, the overall labor market conditions are not expected to dramatically alter the established seasonal pattern. The eligible observation window for determining the peak extends from April 24 to early August 2026, with the peak likely occurring in early-to-mid July. The analysis concludes that unless an unexpected economic shock occurs, the historical seasonal trends will dominate the claims trajectory.
Sources used in the research include:
The most recent ICNSA (non-seasonally adjusted initial claims) data points are [1][3][11]:
The eligible observation window begins April 24, 2026, with resolution on August 12, 2026. Given the ~5 day publication lag for weekly claims data, the last eligible observation is likely for the week ending around August 1 or August 8, 2026 (depending on whether the August 8 data gets published by August 12).
The most critical factor for this question is the strong, well-documented seasonal pattern in non-seasonally adjusted initial claims:
ICNSA typically has two annual peaks: one in early January (post-holiday layoffs) and another in mid-July (summer seasonal patterns including school closures, auto plant retooling, construction cycles, etc.) [7][10][12][13].
2025 data confirms this pattern: The ICNSA peak during summer 2025 was approximately 261,111 claims on July 12, 2025 [10]. After that peak, claims declined through late summer and fall.
January 2026 data showed ICNSA at 259,552 for the week ending January 17, 2026 [13] — but this falls outside the eligible window (before April 24).
Spring-to-summer trajectory: Claims are currently in the ~200,000–215,000 range (NSA). Historical patterns suggest they will rise through May, June, and into July, peaking around early-to-mid July before declining again [8][10].
Based on the consistent seasonal pattern:
The seasonal pattern is driven by structural factors (auto plant shutdowns, school-related layoffs, construction cycles) that recur predictably each year [12].
| Factor | Implication |
|---|---|
| Strong seasonal ICNSA pattern | Peak likely in early-to-mid July 2026 |
| 2025 peak: July 12 at ~261K | Suggests similar timing in 2026 |
| Current claims ~200–215K (NSA) | Significant room to rise seasonally |
| Tech layoffs surging | Could push peak higher than 2025 |
| Stable but softening labor market | Unlikely to dramatically shift seasonal pattern |
| Eligible window: Apr 24–~Aug 8 | July peak falls squarely within window |
Bottom line: The historical seasonal pattern very strongly suggests the ICNSA peak within the eligible window will occur in early-to-mid July 2026 (most likely the week ending around July 4–18, 2026), consistent with the recurring summer peak in non-seasonally adjusted initial claims. The 2025 analogue of July 12 is a strong reference point. The main risk to this baseline is if an unexpected economic shock (recession, major layoff event) causes a spike at a different time, but current labor market conditions suggest the seasonal pattern will dominate.
The critic raises several valid points that warrant modest adjustments to my forecast, while the fundamental structure remains sound.
Underweighting early June period: The critic correctly notes that school-related layoffs begin before July, and the tech layoff surge (51% YoY in Q1 2026) creates meaningful risk of a non-seasonal spike in May-June. I’ll shift some probability earlier.
Late June deserves more weight: Given that JPMorgan expects SA claims to “rise above 220,000 in May and June,” the NSA claims during late June could approach typical July peak levels (~250-260K). June 27 deserves more consideration as a potential peak date.
Distribution too tight: Given elevated economic uncertainty, tariff effects, and tech sector stress, widening the distribution is appropriate.
July 11 as median: The seasonal pattern is extremely robust and well-documented. The 2025 peak was July 12 (~261K), and BLS seasonal factors confirm July has the highest adjustment factors. This remains the most likely outcome.
July 4-18 concentration: Even with adjustments, this window should contain the plurality of probability. Auto plant shutdowns, school closures, and construction cycles create structural peaks during this period.
Late tail probabilities: August dates remain appropriately weighted as unlikely but possible.
Updated prediction: Percentile 0.1: 2026-04-25 Percentile 1: 2026-05-02 Percentile 5: 2026-05-16 Percentile 10: 2026-06-06 Percentile 20: 2026-06-20 Percentile 30: 2026-06-27 Percentile 40: 2026-07-04 Percentile 50: 2026-07-11 Percentile 60: 2026-07-11 Percentile 70: 2026-07-18 Percentile 80: 2026-07-18 Percentile 90: 2026-07-25 Percentile 95: 2026-08-01 Percentile 99: 2026-08-01 Percentile 99.9: 2026-08-08
Looking at the critic’s analysis, I need to carefully evaluate each point and adjust accordingly.
1. Over-Precision Around July 11 - VALID The critic is correct that having 30% probability on a single weekly observation is overconfident. While the 2025 peak was July 12, there’s natural year-to-year variation. I’ll spread this probability across the July 4-18 window.
2. Tech Layoff Factor - PARTIALLY VALID The 51% increase in tech layoffs is notable, but tech represents a small fraction of total claims. The broader labor market remains stable. I’ll give this factor modest weight in widening uncertainty.
3. July 4 Holiday Anomaly - EXCELLENT POINT In 2026, July 4 falls on a Saturday. This means the week ending July 4, 2026 includes the holiday, potentially depressing filings and shifting the peak to July 11 or July 18. This strengthens the case for spreading probability across these weeks.
4. Right Tail Concerns - VALID The instruction explicitly states “Do not cluster your right tail percentiles around the date cutoff.” I should extend P99.9 to allow for August 8 data potentially being published by August 12.
The seasonal pattern is extremely robust - decades of data show consistent mid-July peaks driven by structural factors. The 2025 analogue (July 12 peak at ~261K) provides strong evidence for similar 2026 timing. My central estimate of July 11 remains appropriate.
The critic’s distribution is well-reasoned, but I’ll extend the right tail slightly to comply with the non-clustering instruction.
Updated prediction:
Percentile 0.1: 2026-04-25 Percentile 1: 2026-05-09 Percentile 5: 2026-05-30 Percentile 10: 2026-06-06 Percentile 20: 2026-06-20 Percentile 30: 2026-06-27 Percentile 40: 2026-07-04 Percentile 50: 2026-07-11 Percentile 60: 2026-07-11 Percentile 70: 2026-07-18 Percentile 80: 2026-07-18 Percentile 90: 2026-07-18 Percentile 95: 2026-07-25 Percentile 99: 2026-08-01 Percentile 99.9: 2026-08-08
Looking at the critic’s feedback, I’ll address each point and refine my forecast.
Over-concentration at July 11: The critic is correct that placing percentiles 40, 50, and 60 all on July 11 represents excessive confidence in one specific week. Even with strong seasonal patterns, the exact peak week varies by ±1-2 weeks across years.
Internal inconsistency: My stated probabilities didn’t precisely match my percentile distribution. I need to be more careful about alignment.
Tech layoff signal: The 51% YoY surge in Q1 2026 tech layoffs is notable and could create earlier-than-typical claim spikes if the wave hits before the usual July seasonal peak.
July 4 holiday effects: Good catch - July 4, 2026 falls on a Saturday (an actual ICNSA observation date), which could shift filing patterns in unpredictable ways.
The seasonal pattern in ICNSA is extraordinarily consistent due to structural factors (auto plant retooling, school-related layoffs, construction cycles). The July 12, 2025 peak at ~261,111 is a strong analogue. I maintain that the central tendency should be early-to-mid July.
I’m adjusting to:
Within the July core:
This spreads the 40th percentile to July 4 (rather than July 11), creating a more realistic distribution while preserving the strong mid-July central tendency.
Updated prediction: Percentile 0.1: 2026-04-25 Percentile 1: 2026-05-02 Percentile 5: 2026-05-30 Percentile 10: 2026-06-20 Percentile 20: 2026-07-04 Percentile 30: 2026-07-04 Percentile 40: 2026-07-04 Percentile 50: 2026-07-11 Percentile 60: 2026-07-11 Percentile 70: 2026-07-18 Percentile 80: 2026-07-18 Percentile 90: 2026-07-25 Percentile 95: 2026-08-01 Percentile 99: 2026-08-01 Percentile 99.9: 2026-08-08
Let me first check for any recent economic developments that might affect my forecast:
This new information is very valuable. Let me analyze it and address the critic’s points:
Early tail potentially too thin: The critic is correct that the tech layoff surge (+51% YoY) and now the tariff/trade tensions could create an unexpected early spike. The new search reveals significant economic stress from tariffs (Q1 2026 claims up 11% YoY) and ongoing geopolitical concerns (Iran war). This warrants slightly more probability mass on earlier dates.
July 4 holiday effect: I should explicitly account for this. July 4, 2026 falls on Saturday (end of reporting week), which typically depresses claims for that week as offices close. This shifts the likely peak to July 11 or July 18 rather than July 4.
Week-to-week variation: The exact peak can shift 1-2 weeks year over year based on auto retooling schedules and other factors.
My core thesis remains valid: the seasonal ICNSA pattern is extremely consistent, with peaks in mid-July driven by auto plant shutdowns, school closures, and construction cycles. The 2025 ICNSA peak was ~261,111 on July 12, 2025. The current ICNSA levels (~200,000-215,000) confirm we’re in the typical spring trough, with significant room to rise seasonally.
Based on the critic’s valid points:
Updated prediction:
Percentile 0.1: 2026-04-25 Percentile 1: 2026-05-09 Percentile 5: 2026-05-23 Percentile 10: 2026-06-06 Percentile 20: 2026-06-20 Percentile 30: 2026-06-27 Percentile 40: 2026-07-04 Percentile 50: 2026-07-11 Percentile 60: 2026-07-11 Percentile 70: 2026-07-18 Percentile 80: 2026-07-18 Percentile 90: 2026-07-25 Percentile 95: 2026-08-01 Percentile 99: 2026-08-01 Percentile 99.9: 2026-08-08
The critic raises two compelling points I should address:
Missing June 20: The critic correctly identifies that my distribution jumps from June 13 (P20) to June 27 (P30), creating an unnatural gap. Adding June 20 creates a smoother progression through June.
July 4 holiday dynamics: The observation about July 4 falling on Saturday (the week-ending date) is insightful. However, I interpret this differently than the critic. Since claims are filed Monday-Friday and July 4 is the last day of that reporting week, most filings would occur normally before the holiday. More importantly, auto plant shutdown claims typically spike in the weeks FOLLOWING the shutdown start (July 11-18), not during the shutdown week itself.
I respectfully maintain July 11 as the median rather than shifting to July 4 for these reasons:
Historical precedent: The 2025 peak was July 12 (Saturday). The seasonal pattern consistently peaks in the second week of July, not the first.
Claims filing mechanics: Workers laid off during auto plant shutdowns file claims in subsequent weeks. A shutdown beginning around July 4 produces peak claims around July 11-18.
Holiday effect: If anything, the July 4 holiday may slightly depress that week’s claims, strengthening July 11’s position as the peak.
I’m accepting:
The tech layoff surge (51% YoY increase) creates sustained elevation across multiple weeks rather than sharp single-week spikes. This adds upward pressure to baseline levels throughout June-July but doesn’t fundamentally alter the structural seasonal pattern that drives the mid-July peak.
Updated prediction: Percentile 0.1: 2026-04-25 Percentile 1: 2026-05-02 Percentile 5: 2026-05-16 Percentile 10: 2026-06-06 Percentile 20: 2026-06-13 Percentile 30: 2026-06-20 Percentile 40: 2026-06-27 Percentile 50: 2026-07-11 Percentile 60: 2026-07-11 Percentile 70: 2026-07-18 Percentile 80: 2026-07-18 Percentile 90: 2026-07-25 Percentile 95: 2026-08-01 Percentile 99: 2026-08-01 Percentile 99.9: 2026-08-08
Agent Forecast (date, confidence: medium)
Base Rate: Confirmed via DOL data: 2025 NSA summer peak occurred week ending July 12 at ~261,111 claims (derived from 215,792 in week ending July 19 minus stated decrease of 45,319). July 4, 2026 falls on Saturday, making the week ending July 4 fall squarely in the Jul 02-Jul 15 bin.
Initial Reasoning:
Key Uncertainties:
Evidence Sources (7):
Grounding Facts (passed to reviewers):
Draft: Jul 02, 2026 to Jul 15, 2026: 40.0%, Jun 18, 2026 to Jul 02, 2026: 25.0%, Jul 15, 2026 to Jul 29, 2026: 13.0%, After Jul 29, 2026: 7.0%, Jun 04, 2026 to Jun 18, 2026: 7.0%
Reviewer Panel:
Reviewer (reasoning)
The draft leans almost exclusively on textbook seasonality—especially the July 4 peak—but doesn’t sufficiently justify why late June auto‐plant shutdowns wouldn’t actually produce a stronger June peak. It also underweights the risk that a war‐induced shock could generate an unusual spike outside the textbook calendar, and it fails to quantify the historical variance in the seasonal swing. Finally, it fragments probability across many bins without clear evidence the peak timing uncertainty is that high.
Objections:
Reviewer (calibration)
The forecast accurately identifies the strong seasonal pattern of non-seasonally adjusted initial unemployment claims. However, it appears to place too much certainty on the precise timing of the summer peak, potentially underestimating how the acknowledged economic fragility from the ongoing war, high oil prices, and low consumer confidence could disrupt or shift this pattern. While a summer peak remains most probable, the forecast doesn’t fully explore scenarios where accelerating layoffs due to economic stress might create an earlier, non-seasonal peak or significantly broaden the traditional summer window.
Objections:
Reviewer (fact-checker)
6 unsupported claim(s). Verdict: minor_issues
Unsupported claims:
Adjustment Rationale:
Verified via web search that week ending July 12, 2025 had NSA claims of ~261,111 (derived from DOL report stating week ending July 19, 2025 = 215,792, a decrease of 45,319 from prior week). This strongly confirms the early-July peak pattern and rebuts the reasoning reviewer’s claim that late June typically holds the single highest week. Kept mode in Jul 02-Jul 15 bin but slightly increased it to 0.45 (from 0.40) given this strong empirical confirmation, while shifting small probability toward Jul 15-29 and ‘After Jul 29’ to address the calibration reviewer’s legitimate concern about war/economic stress creating an atypical late-summer spike. Reduced Jun 18-Jul 02 (from 0.25 to 0.18) since the 2025 data points to a peak later in the summer window. The fact-checker’s claims were largely procedural (flagging properly derivable facts: July 4 2026 is a Saturday by calendar; YoY tracking from prior data). Ensemble signal of 35% was slightly below my mode; I adjusted upward toward 45% because the verified 2025 peak data is stronger evidence than priors from general seasonality alone.
forecast_sdk | 543.2s | research $0.8259 + reviewers $0.0132 + reconcile $0.2860 = $1.1252
Extracted Date Percentile Values: {0.1: 1777075200.0, 1.0: 1777075200.0, 5.0: 1779494400.0, 10.0: 1780704000.0, 15.0: 1781308800.0, 20.0: 1781913600.0, 25.0: 1782518400.0, 30.0: 1783123200.0, 35.0: 1783123200.0, 40.0: 1783728000.0, 45.0: 1783728000.0, 46.0: 1783728000.0, 47.0: 1783728000.0, 48.0: 1783728000.0, 49.0: 1783728000.0, 50.0: 1783728000.0, 51.0: 1783728000.0, 52.0: 1783728000.0, 53.0: 1783728000.0, 54.0: 1783728000.0, 55.0: 1783728000.0, 60.0: 1783728000.0, 65.0: 1783728000.0, 70.0: 1783728000.0, 75.0: 1783728000.0, 80.0: 1783728000.0, 85.0: 1784332800.0, 90.0: 1784332800.0, 95.0: 1784937600.0, 99.0: 1785542400.0, 99.9: 1786147200.0}
Model’s Answer:
Step one: Identify the seasonal pattern. The non-seasonally adjusted (ICNSA) data reveals an extremely consistent mid-July spike driven by auto industry temporary layoffs and school-related seasonal patterns:
This mid-July spike is far and away the dominant peak in every Apr–Aug window in the dataset.
Step two: Determine the eligible observation window. FRED publishes ICNSA data ~5 days after the observation date (Thursday for prior Saturday). The last observation published by August 12 would be the week ending ~August 1 (published ~August 6). The week ending August 8 would be published ~August 13, likely too late. So eligible observations span roughly April 25 through August 1.
Step three: Assess the mid-July peak timing. In 2026, the analogous mid-July week would be centered around July 11, 2026 (Saturday). This is the single most likely resolution date.
Step four: Consider alternative scenarios.
Why an earlier peak could occur (~20% probability): A sudden economic shock—major layoff event, trade war escalation, financial stress—could produce a one-week spike in May or June exceeding the normal July seasonal. The early June seasonal bump (243,980 on June 7, 2025; 236,046 on June 8, 2024) is sometimes elevated but historically still ~20-40k below the July peak.
Why a later peak could occur (~10% probability): The auto layoff pattern could shift later (week of July 18 or July 25), or deteriorating labor conditions could push late-July/early-August claims above the mid-July seasonal level.
Step five: Identify critical assumptions.
Assumption 1: Seasonal mid-July auto layoff pattern persists. If auto manufacturers change their shutdown timing significantly (e.g., EV transition), this could shift the peak. Probability of failure: ~10%.
Assumption 2: No major economic shock before July. A recession trigger, mass layoffs from policy changes, or natural disaster could create an earlier spike. Probability: ~15%.
Assumption 3: Current labor market stability continues broadly. If the labor market rapidly deteriorates, claims could be elevated across many weeks, with the peak potentially not aligning with the usual seasonal pattern. Probability of significant deterioration: ~10%.
| Date Range | Probability | Cumulative |
|---|---|---|
| April 25 – May 23 | ~5% | ~5% |
| May 30 – June 6 | ~7% | ~12% |
| June 13 – June 27 | ~10% | ~22% |
| July 4 | ~12% | ~34% |
| July 11 | ~50% | ~84% |
| July 18 | ~8% | ~92% |
| July 25 – Aug 1 | ~6% | ~98% |
| Aug 8+ | ~2% | ~100% |
The median and mode are both July 11, 2026, reflecting the strong seasonal regularity.
Percentile .1: 2026-04-25 Percentile 1: 2026-04-25 Percentile 5: 2026-05-23 Percentile 10: 2026-06-06 Percentile 15: 2026-06-13 Percentile 20: 2026-06-20 Percentile 25: 2026-06-27 Percentile 30: 2026-07-04 Percentile 35: 2026-07-04 Percentile 40: 2026-07-11 Percentile 45: 2026-07-11 Percentile 46: 2026-07-11 Percentile 47: 2026-07-11 Percentile 48: 2026-07-11 Percentile 49: 2026-07-11 Percentile 50: 2026-07-11 Percentile 51: 2026-07-11 Percentile 52: 2026-07-11 Percentile 53: 2026-07-11 Percentile 54: 2026-07-11 Percentile 55: 2026-07-11 Percentile 60: 2026-07-11 Percentile 65: 2026-07-11 Percentile 70: 2026-07-11 Percentile 75: 2026-07-11 Percentile 80: 2026-07-11 Percentile 85: 2026-07-18 Percentile 90: 2026-07-18 Percentile 95: 2026-07-25 Percentile 99: 2026-08-01 Percentile 99.9: 2026-08-08
I’ll work through this systematically as a superforecaster.
The date of the FRED ICNSA observation with the highest non-seasonally adjusted value among all eligible observations (April 24 – August 12, 2026). This resolves to a specific Saturday date in YYYY-MM-DD format.
Auto industry summer shutdown timing (weight: 0.55) — The structural driver of the July ICNSA spike. In 14/16 years (2010–2025), the peak fell in ISO weeks 27–28 (July 5–18). Ford is confirmed skipping F-Series shutdown [S7], but GM/Stellantis/Toyota schedules are unconfirmed for 2026.
Macroeconomic shock / recession risk (weight: 0.25) — Recession probability 30–49% [S16], Iran-Hormuz oil shock ongoing [S1], February 2026 saw -92,000 jobs [S23]. A recession-level shock materializing before July could shift the peak to May–June.
Iran-Hormuz ceasefire stability / oil price trajectory (weight: 0.12) — Ceasefire extended April 21 but stalled [S1]. Brent at $106 [S3]. Oxford Economics threshold for recession-level layoffs is $140 sustained [S15]. Current price is below that threshold.
Ford F-Series shutdown skip magnitude (weight: 0.08) — Confirmed skip at 4 plants [S7], but this only dampens the July spike; it doesn’t eliminate it. Other automakers still likely shutting down.
The trendline shows ICNSA declining from the January 2026 peak (330,963) through March, then ticking up slightly in April. This is consistent with normal seasonal patterns.
Mixed, leaning clocklike. The July auto-shutdown spike is one of the most reliable seasonal patterns in U.S. labor data — 14/16 years in the same 2-week window. However, the current macro environment (geopolitical shock, elevated recession risk, Ford shutdown skip) introduces cloudlike elements. The question is well-suited to base-rate anchoring with adjustments for known structural changes.
Wrong class: “When do unemployment claims peak in general?” (which would suggest winter/recession peaks)
Better class: “When does ICNSA peak within the April 24–August 12 window, specifically?” — This is the right reference class, and the research has identified it richly: 14/16 years in ISO weeks 27–28 (July 5–18), with the modal outcome being week 28 (8 of 14 non-COVID years).
Rich — 16 close comparables (same series, same window, same resolution criteria), with 14 of 16 showing July week 27–28 peaks. The base rate is highly reliable for the seasonal pattern, though the Ford skip and macro uncertainty add noise.
Base rate: ~87.5% probability of July peak (14/16 years), with ~50% of those in week 28 and ~43% in week 27. COVID years (2020, 2021) represent the April tail — both driven by unprecedented shocks far larger than current conditions.
Most likely scenario to make this forecast wrong: Iran ceasefire collapses in May–June, oil spikes to $130–140+, triggering mass layoffs in transportation/energy/manufacturing before the auto shutdown season. This would push the peak to May or June. Probability: ~10–15%.
This is a window maximum (extremum over a window), which is right-skewed relative to the typical weekly value. The distribution of peak dates is discrete (weekly observations) and bimodal: a strong mode at July 11–18 (weeks 27–28) and a secondary mode in May–June (recession scenario). The appropriate mental model is a mixture distribution:
Scenario 1: COVID-scale or near-COVID shock (April–May peak)
Scenario 2: Recession-level shock materializes in May–June
Scenario 3: Normal seasonal, ISO week 27 peak (July 5–11)
Scenario 4: Normal seasonal, ISO week 28 peak (July 12–18)
Scenario 5: Delayed/extended shutdown, late July–early August peak
Weighted average check:
Weighted average ≈ 0.02×1 + 0.10×43 + 0.28×78 + 0.48×85 + 0.12×92 ≈ 0.02 + 4.3 + 21.8 + 40.8 + 11.0 ≈ 77.9 days into window ≈ July 10, 2026
This is consistent with the historical center of gravity (weeks 27–28) adjusted slightly earlier by the Ford skip and slightly later by the delayed-shutdown tail.
110 days remain. The question is not highly timeframe-sensitive in the short run — the July auto-shutdown pattern is locked in by industry calendar, not by day-to-day developments. However, if the window were halved (ending ~June 12), the probability of a July peak would drop to near zero, and the answer would be dominated by the recession-shock scenario. If doubled, the answer would be essentially unchanged (July still dominates). This confirms the July attractor is robust within the current window.
Converting to dates (YYYY-MM-DD):
10th percentile: The 10th percentile captures the left tail — recession/shock scenarios pushing the peak to May–June. Given ~12% probability of pre-July peak, the 10th percentile falls in the recession scenario range. Central value of scenario 2 is June 6, but the 10th percentile should be somewhat earlier. I’ll place it at 2026-05-30.
20th percentile: Still in the shock/early scenario range, but closer to the transition. 2026-06-27 — capturing late-June possibilities from the recession scenario and early-July from the delayed-shutdown tail.
40th percentile: Just at the boundary of week 27 territory. 2026-07-11 — the week 27 peak date.
60th percentile: Solidly in week 28, the modal outcome. 2026-07-18.
80th percentile: Week 28 to late July. 2026-07-18 (same as 60th, given the strong concentration here) — actually, I need strictly increasing values. The 80th should be slightly later to reflect the late-July tail. 2026-07-25.
90th percentile: Late July to early August, capturing the delayed-shutdown tail. 2026-08-01.
Let me verify strict monotonicity: 2026-05-30 < 2026-06-27 < 2026-07-11 < 2026-07-18 < 2026-07-25 < 2026-08-01 ✓
Percentile 10: 2026-05-30 (lowest number value) Percentile 20: 2026-06-27 Percentile 40: 2026-07-11 Percentile 60: 2026-07-18 Percentile 80: 2026-07-25 Percentile 90: 2026-08-01 (highest number value)
I’ll work through this systematically as a superforecaster.
The date (YYYY-MM-DD) of the FRED ICNSA observation with the highest value among all eligible observations (April 24 – August 12, 2026 window, published by August 12, 2026).
Auto industry summer shutdown calendar (weight: 0.50) — The primary structural driver of the July ICNSA spike. In 14/16 non-COVID years, the peak fell in ISO weeks 27-28. Ford’s F-Series skip reduces but doesn’t eliminate this effect; GM, Stellantis, Toyota, Honda U.S. plants are unconfirmed for 2026.
Macroeconomic shock / recession materialization (weight: 0.25) — Recession probability 30-49% [S16]. An oil-shock-driven recession or ceasefire collapse could create a non-July claims spike. Current Brent at $106 is below Oxford Economics’ $140 recession-trigger threshold [S15].
Iran-Hormuz geopolitical trajectory (weight: 0.15) — Ceasefire extended April 21 but stalled [S1]. Collapse → oil spike → potential early claims surge. Stabilization → seasonal pattern dominates.
Ford F-Series shutdown skip (weight: 0.07) — Confirmed skip at 4 plants [S7]. Reduces July spike magnitude but doesn’t eliminate it (other automakers still likely shutting down).
ICNSA baseline level entering window (weight: 0.03) — Current readings ~205K, 7.1% below prior year [S5]. Low starting point means the July spike needs to exceed a lower baseline to be the peak.
Mixed, leaning clocklike. The July auto-shutdown pattern is highly regular (14/16 years) — this is a structural, calendar-driven phenomenon. However, the geopolitical shock (Iran-Hormuz) introduces cloudlike uncertainty. The question is well-suited to base-rate anchoring for the “normal seasonal” scenario, with adjustment for tail risks.
Wrong class: “When do unemployment claims peak in general?” (which would point to recession periods, COVID, etc.)
Right class: “When does ICNSA peak within the April 24–August 12 window in non-recession years?” This isolates the seasonal pattern within the specific resolution window, which is dominated by the July auto shutdown spike.
Rich — 16 years of direct comparables (2010-2025) with the same April-August window [S25]. The rate is reliable: 14/16 years peaked in July (weeks 27-28), with 8 in week 28 and 6 in week 27. Only COVID-scale shocks (2020, 2021) broke this pattern.
Single scenario most likely to make this forecast wrong: Iran ceasefire collapses in May-June, Brent spikes to $130-140+, triggering mass layoffs in energy/transportation before the auto shutdown season — pushing the peak to May or June. This would push the resolution date significantly earlier (by ~6-8 weeks).
This is a window maximum (argmax over ~16 weekly observations). The distribution of the date of the maximum is discrete and multimodal. Given the strong structural pull toward weeks 27-28 (July 11 or July 18), the distribution is highly concentrated there, with fat tails toward:
The distribution is roughly bimodal: a large spike at July 11/18, and a smaller spread across May-June for shock scenarios.
Scenario 1: Catastrophic shock (COVID-scale or Iran war escalation to full regional conflict)
Scenario 2: Moderate recession shock, pre-July peak
Scenario 3: Normal seasonal pattern, Ford skip dampens July, week 27 peak
Scenario 4: Normal seasonal pattern, week 28 peak (modal historical)
Scenario 5: Delayed/extended shutdown, late July peak
Weighted average check:
Weighted mean (days from April 24): 0.04×8 + 0.12×43 + 0.35×78 + 0.38×85 + 0.11×92 = 0.32 + 5.16 + 27.3 + 32.3 + 10.12 = 75.2 days from April 24 = approximately July 8, 2026
This is consistent with a distribution centered between weeks 27-28, slightly pulled earlier by shock scenarios. ✓
110 days remain. The window is long enough to capture the full July auto-shutdown season. If the window were halved (to ~55 days, ending ~June 17), the July peak would be excluded and the answer would shift dramatically to May-June. If doubled, late August/September would be included, but those are historically low-claims periods, so the July peak would still likely dominate. The current window is well-calibrated for the seasonal pattern.
The question asks for dates in YYYY-MM-DD format. I need to express percentiles as dates:
Wait — I need to ensure strictly increasing values. Let me refine:
Since dates are discrete, P60 and P80 could both be July 18 if the distribution is concentrated there. But I need strictly increasing values. The distribution has ~38% mass at July 18 and ~35% at July 11, so:
Actually, cumulative: through July 11 = ~51%, through July 18 = ~89%, through July 25 = ~100%. So P60 and P80 both fall in July 18 territory. I need to spread these slightly using within-scenario variation.
Given the discrete nature, I’ll use:
This reflects the concentration at weeks 27-28 with appropriate tails.
Percentile 10: 2026-06-06 Percentile 20: 2026-07-04 Percentile 40: 2026-07-11 Percentile 60: 2026-07-18 Percentile 80: 2026-07-25 Percentile 90: 2026-08-01
Target variable
The outcome is the FRED observation date (weekly, ending Saturday) within the eligible window 2026-04-24 through 2026-08-12 whose ICNSA value is highest among all eligible observations published by resolution time. If multiple weeks tie for the highest value, the earliest tied observation date resolves the question. So this is not asking for the level of claims, but the date of the maximum weekly NSA initial claims print in that window [S5].
Current state
So far the signal is: lowish current baseline, mild macro deterioration, but very strong seasonal tendency toward an early/mid-July maximum.
Key drivers (weighted)
Recurring July auto-plant retooling shutdown pattern in ICNSA — 0.48
This is the main causal mechanism behind within-window peaks in normal years; historically it dominates the timing question [S19][S25].
Exact 2026 shutdown timing at GM/Stellantis/Toyota/Honda and other major plants — 0.22
This mostly determines whether the peak lands on 2026-07-11 vs 2026-07-18, and secondarily whether it shifts a week later.
Ford F-Series shutdown cancellation — 0.12
Confirmed dampener to the usual July spike [S7][S8]. Important, but probably not enough by itself to erase the July maximum if the rest of the industry follows normal timing.
Macro shock / recession / oil-shock-induced layoffs before July — 0.13
Could generate an atypical May/June peak if conditions worsen sharply. Current evidence says elevated risk, not realized broad layoff wave [S1][S15][S16].
Revisions/noise/tie-breaking in NSA weekly claims — 0.05
Small but real, since this resolves off revised FRED values and weekly NSA data are choppy.
System regularity
This is mixed, leaning clocklike.
Why clocklike:
Why not fully clocklike:
This is well suited to base-rate anchoring, more than many macro questions. The base rate should carry most of the weight, with only moderate inside-view adjustment for Ford and recession risk.
Wrong reference class trap
Wrong superficial class: “When will unemployment get worse in a slowing economy?”
That points toward recession narratives and broader labor market deterioration.
Better class: “In years without a major extraordinary shock, when does ICNSA make its within-April-to-August high?”
This is much more about the seasonal timing of NSA claims maxima, especially auto shutdown weeks, than about long-run unemployment trends.
Reference class
Moderate approaching rich. The research gives 16 close yearly analogues (2010–2025) for the exact seasonal window, with 14 non-COVID or all but 2 years clustering tightly in week 27/28 [S25]. That is enough to compute and trust a strong base-rate anchor, while still allowing adjustment for 2026-specific plant scheduling and macro risks.
Outside-view baseline:
Given that concentration, a pure outside view would center very near 2026-07-11 to 2026-07-18, slightly favoring 2026-07-18.
Inside-view adjustment
Two main adjustments:
Net effect: still strongly July-centered, but a bit flatter than the historical distribution and with somewhat more left-tail mass.
Key unknowns
Most likely way this forecast is wrong in hindsight
A May/June recessionary layoff spike overtakes the muted July seasonal bump. That would push the true date earlier than my median. This is the main left-tail risk.
Distribution shape
This is a distribution over the date of a maximum over a finite weekly window. It should be multimodal/discrete, not smooth-normal: mass concentrated on a few Saturday dates, especially 2026-07-11 and 2026-07-18, with smaller tails in late June, late July, and very small left tail to May/April.
Because this is a window maximum, the expected peak date is not the middle of the window; it is pulled toward the recurring seasonal hump. In a normal volatility regime, the extreme is meaningfully above adjacent weeks, but here the key issue is timing, not level. Roughly, the “extreme effect” is that among ~16 eligible weeks, the max almost always aligns with the one or two weeks where the seasonal mean is highest—historically week 27/28.
Scenario mixture
Ordered from lowest to highest implied date:
Oil shock / recession layoffs arrive before auto shutdown season
Weight: 0.16
Conditions: ceasefire fails, oil rises materially, transport/manufacturing layoffs broaden in May/June.
Central value: 2026-06-13
Within-scenario spread: roughly 2026-05-16 to 2026-06-27
Binding constraints: cannot be earlier than 2026-04-25.
Normal seasonality, but July spike is pulled earlier / flatter by Ford skip and mixed plant timing
Weight: 0.29
Conditions: GM/Stellantis/Toyota shutdowns still happen, but a flatter July hump peaks in week 27.
Central value: 2026-07-11
Within-scenario spread: roughly 2026-07-04 to 2026-07-11
Binding constraints: mostly capped before 2026-07-18 in this scenario.
Normal seasonal pattern with broad industry shutdown concentration in modal week 28
Weight: 0.39
Conditions: broader auto sector follows typical schedule; Ford skip only partially offsets.
Central value: 2026-07-18
Within-scenario spread: roughly 2026-07-11 to 2026-07-18
Binding constraints: concentrated around historical modal week [S25].
Delayed/extended retooling or lingering supply chain disruption pushes peak later
Weight: 0.12
Conditions: shutdown timing slips later than usual, or claims crest on a later week.
Central value: 2026-07-25
Within-scenario spread: roughly 2026-07-18 to 2026-08-08
Binding constraints: eligible latest likely Saturday is 2026-08-08.
Extreme shock very early in window
Weight: 0.04
Conditions: an unusually severe and immediate shock causes an April/May spike larger than any later reading.
Central value: 2026-05-02
Within-scenario spread: 2026-04-25 to 2026-05-16
Binding constraints: lower floor 2026-04-25.
These weights sum to 1.0.
Using rough day counts from the start of the window, the weighted average central date lands around 2026-07-08 to 2026-07-10, which is consistent with a distribution mean slightly earlier than the historical modal week because I am adding some left-tail recession risk and some Ford-related flattening.
Yes:
Timeframe check
There are 110 days until resolution, with about 16 weekly observations in play.
That sensitivity is exactly what we should expect, which reassures me the logic is aligned with the mechanics of the question.
Bottom line
The strongest signal by far is the historical regularity: within this exact seasonal window, ICNSA usually peaks in early-to-mid July, especially 2026-07-11 or 2026-07-18. Ford’s shutdown cancellation lowers confidence in a sharp week-28 mode, and recession/oil-shock risks create a meaningful earlier tail, but not enough to dislodge July as the dominant outcome.
Percentile 10: 2026-06-06 Percentile 20: 2026-07-04 Percentile 40: 2026-07-11 Percentile 60: 2026-07-18 Percentile 80: 2026-07-25 Percentile 90: 2026-08-01
Target variable
Date (YYYY-MM-DD) of the weekly observation in FRED series ICNSA with the highest non-seasonally-adjusted value among all observations dated 2026-04-24 through 2026-08-12 and posted to FRED by 2026-08-12.
Key drivers (weights sum to 1.0)
Current state
• Window opens now; latest ICNSA (week ending 18 Apr) = 205 306, ~7 % below same week 2025.
• Ford will skip its normal July F-Series plant downtime (announced 3 Apr).
• GM/Stellantis have not released 2026 shutdown dates.
• Iran-Hormuz shock keeps Brent ≈ $106; cease-fire fragile but holding.
• Recession odds 30-49 %; markets calm (VIX 19.3, HY spread 2.84 %).
No observation inside the window has yet occurred, so nothing is locked in except the seasonal calendar.
System regularity
Mixed. ICNSA is a high-frequency, well-measured series with a very stable mid-summer spike (clock-like), but can be abruptly overturned by recessions or exogenous shocks (cloud-like). A base-rate anchor is appropriate but must be tempered by live geopolitical risk and the Ford shutdown deviation.
Wrong reference-class trap
Wrong: “general U.S. unemployment dynamics.”
Right: “Peak (max) ICNSA week between late-Apr and early-Aug in normal-season years.”
Reference class = rich (16 comparable years since 2010; 14 if COVID years set aside).
Key unknowns & biggest risk
• Whether GM or Stellantis also shorten/skip 2026 shutdowns.
• Whether the Iran cease-fire collapses, pushing Brent > $130 for 6–8 weeks and triggering mass layoffs in May–June.
A cease-fire collapse before mid-May that produces a recession-scale claims spike would make this forecast “too late.”
Distribution shape
Outcome is the arg-max date of a weekly series over a 16-week window – a discrete, right-skewed distribution dominated by the July seasonal peak, with a long left tail (earlier shocks) and a short right tail (delayed shutdowns).
Scenario mixture (covering 100 %)
Weighted mean (for audit): ~ 10 Jul 2026 — sits inside the historical mode.
Timeframe check
110 days remain. Halving the window (to mid-June) would greatly raise the value of recession scenarios; doubling would push weight slightly toward late-July/early-Aug dates. Current mix is sensitive to but not dominated by this horizon.
Percentile 10: 2026-06-06
Percentile 20: 2026-06-13
Percentile 40: 2026-07-04
Percentile 60: 2026-07-11
Percentile 80: 2026-07-18
Percentile 90: 2026-07-25
Target variable
• The calendar date (YYYY-MM-DD) of the weekly observation in FRED series ICNSA that shows the single-highest non-seasonally-adjusted U.S. initial unemployment-claims value among all observations dated 2026-04-24 through 2026-08-12 inclusive.
Key drivers (weights sum = 1.0)
Current state (24 Apr 2026)
• Latest ICNSA reading (week ending 18 Apr): 205,306 – about 7 % below the same week in 2025 and near the 2-year low for this season.
• Brent $106; WTI $97. Iran-U.S. cease-fire holding uneasily; Hormuz still ~80 % shut.
• Ford has publicly confirmed it will skip its usual one-week July shutdown at four F-Series plants. No similar announcements from GM or Stellantis.
• Financial-stress gauges (VIX 19.3, HY spread 2.84 %) signal slowdown, not crisis.
• Resolution window opens today and covers ISO weeks 17–32; the last eligible Saturday is 08 Aug 2026.
System regularity
Mixed, but closer to “clock-like.” The ICNSA series is weekly, methodologically stable, and its April–August extreme has followed a repeatable seasonal pattern in normal years. Macro shocks can override the pattern (2020–21), so a pure clock-model would be incomplete.
Wrong reference-class trap
Tempting but wrong: “Any unemployment-claims spike during recessions.”
Better: “ICNSA peak dates within the same April-12 Aug window in 2010-2025.” This captures both seasonal auto-shutdown dynamics and the two recent shock-driven exceptions.
Reference-class richness
Rich – 16 close analogues (2010-2025). 14/16 peaks occurred in ISO weeks 27–28; 2/16 (COVID) in late April.
Key unknowns / biggest ‘gotcha’
• Whether GM and Stellantis also pare back or shift their July downtime. If both follow Ford’s lead, the canonical week-28 spike could be noticeably lower; a milder, earlier macro-weakness crest (e.g., mid-June) might end up on top. This would pull the peak 2-4 weeks forward.
Distribution shape
The outcome is the maximum of a weekly series over a fixed window → right-skewed toward the modal July spike with a long left tail (early-shock scenarios) and a shorter right tail (delayed shutdowns). A discrete, ordered set of Saturday dates suffices.
Scenario mixture (mutually exclusive, exhaustive)
Sanity check
Weighted mean ≈ 05 Jul 2026 – comfortably between scenarios 2 and 1, matching the expectation that the peak most likely falls in early/mid-July. Tails cover the earliest feasible May date and the latest plausible late-July date.
Timeframe sensitivity
110 days remain. If the window were halved, shock-driven early-tail probability would fall sharply; if doubled, late-July/early-Aug weight would climb. The forecast already embeds those sensitivities.
Probabilistic forecast (dates are Saturdays unless noted):
Percentile 10: 2026-06-01 Percentile 20: 2026-06-17 Percentile 40: 2026-07-04 Percentile 60: 2026-07-11 Percentile 80: 2026-07-18 Percentile 90: 2026-07-25
Forecast (percentiles, aggregated):
Per-model forecasts:
Rationale: Summary The estimate centers heavily on the week ending July 11, 2026, driven by powerful, recurring seasonal dynamics in the non-seasonally adjusted initial claims data. Historically, initial claims experience their highest spike of the April-August window in mid-July. This predictable surge—evident in peak observation dates like July 13, 2024, and July 12, 2025—results from temporary automobile plant shutdowns for retooling, the start of a new quarter establishing new unemployment insurance eligibility bases, and administrative backlogs caused by the Independence Day holiday. The 2026 calendar strongly favors the week ending July 11 as the peak observation date. Because July 4 falls on a Saturday, the preceding Friday will likely be observed as a holiday, artificially suppressing claims processing for the week ending July 4. Consequently, a massive wave of pent-up claims will be processed in the first full non-holiday week, firmly anchoring the median estimate at July 11, with the 75th percentile extending to July 18 to account for standard variations in reporting delays.
Strongest Arguments for Sooner • The primary alternative to a mid-July peak is a recognizable early June seasonal bump. Historically, claims often see a localized spike around the first or second week of June. • If summer auto retooling closures are unusually muted, staggered, or canceled due to supply chain strategies, the standard mid-July spike may fail to materialize, leaving the early June bump (captured by the June 6 10th percentile) as the highest observation. • An acute, unexpected economic shock occurring in late May or early June could drive a sudden wave of initial claims that overshadows the regular seasonal patterns later in the summer.
Strongest Arguments for Later • A steadily deteriorating macroeconomic environment could impose a rising baseline trend on jobless claims. If broader economic headwinds, such as sustained job losses or tariff impacts, worsen throughout the summer, the sheer volume of structural layoffs could push the highest claims reading into late July or early August. • Shifts in the automotive industry’s traditional summer retooling schedules could delay seasonal mass layoffs. A postponement of these shutdowns would push the corresponding spike in initial claims into the final weeks of July. • Administrative processing issues or prolonged state-level backlogs could cause the expected early July surge to be recorded in subsequent weeks, extending the tail toward the July 25 90th percentile.
Key Uncertainties • The exact timing and severity of summer automotive plant retooling shutdowns. • The trajectory of the broader U.S. economy and whether structural, recessionary layoffs outpace standard seasonal fluctuations. • State-level administrative anomalies and processing effects related to the July 4th holiday weekend.
To arrive at our forecast, we primarily relied on historical seasonal patterns in the Federal Reserve Bank of St. Louis (FRED) data for non-seasonally adjusted initial unemployment claims. We observed a remarkably consistent “base rate” where the annual peak for the late-spring and summer window almost invariably occurs in the second week of July. This recurring spike is largely driven by predictable industrial factors, such as temporary automotive and manufacturing plant shutdowns for retooling, as well as school-related administrative cycles.
We also analyzed current labor market trends, including recent layoff announcements and macroeconomic indicators like recession odds and tariff changes. While these factors suggest a slight cooling of the labor market, we concluded they are unlikely to override the established seasonal surge unless a major economic shock occurs.
Our thinking was also guided by the specific calendar mechanics of the question. Because the data is reported weekly on Saturdays, we focused our probability on those specific dates. We also accounted for the publication cutoff in August, which likely excludes the final week of the window from consideration. While we identified the second Saturday in July as the most probable peak, we distributed some weight to adjacent weeks to account for potential shifts in shutdown schedules or a broader economic softening that could push the peak slightly later into the summer.