ZIP Code

ZIP 90504

High activity

County page · 356 H-1B filings

Employers in 90504 (CA) submitted 356 certified H-1B applications requesting 428 workers across 99 companies. The median offered wage is $107,689/yr. The largest filers are Garrett Transportation I Inc., Deloitte Consulting LLP and Honeywell International, Inc.. The displacement model assigns 631 worker-equivalent exposures to these filings. Separately, 153 layoffs appear in matched WARN notices.

Source import recorded Sep 2, 2026

Overview

H-1B Filings

356

356

Workers

428

requested

Employers

99

certified filings

Avg Offered

$109.8K

annual

BLS reference

$103K

occupation average

Offered vs BLS reference

7%

above benchmark

Below prevailing

0%

325 filings with offered wage data

WARN notices

1

reported records

Headline filing and employer counts use certified H-1B records. The below-prevailing share uses filings with offered wage data as its denominator. Offered, prevailing and BLS averages use independently available values; their populations can differ. The BLS reference averages national occupation medians linked to certified filings, using each occupation's latest available year. It is not a ZIP-wide market median. The employer list includes all LCA outcomes and visa classes; quality-flagged rows are excluded.

Offered wage vs BLS reference

$0$27.5K$54.9K$82.4K$109.8K$109.8KZIP 90504 avgoffer$103KAverage BLSreferenceannual wage

Employers & jobs

Employers (110)

EmployerFilings
1

Garrett Transportation I Inc.

$131.4K avg

60
2

Honeywell International, Inc.

$123.5K avg

41
3

Spinifex Group, Inc.

$165.2K avg

28
4

Wolters Kluwer United States Inc.

$132.5K avg

20
5

CarParts.com, Inc.

$154.1K avg

18
6

NTT DATA, Inc.

$82.8K avg

15
7

KIM & LEE, LLP

$60.4K avg

11
8

Jinon Corporation

$43.2K avg

11

Job categories (52)

  • Mechanical Engineers44 · 24.9%
  • Software Developers, Applications30 · 16.9%
  • Accountants and Auditors27 · 15.3%
  • Computer Occupations, All Other21 · 11.9%
  • Computer Systems Analysts18 · 10.2%
  • Computer and Information Systems Managers14 · 7.9%
  • Computer Occupations, All Other14 · 7.9%
  • Training and Development Specialists9 · 5.1%
Job categoryH-1B vs BLS
17-2141 Mechanical EngineersH-1B $118.2K vs BLS $104.1K+14%

44 workers · 44 filings · $126K wage theft

13-2011 Accountants and AuditorsH-1B $70.8K vs BLS $83.7K-15%

27 workers · 27 filings · $536K wage theft

54 workers · 18 filings

14 workers · 14 filings · $119K wage theft

15-1299 Computer Occupations, All OtherH-1B $136.5K vs BLS $116.6K+17%

14 workers · 14 filings · $98K wage theft

9 workers · 9 filings · $116K wage theft

Filings

LCA filings (433)

Title · Worksite

A negative % sits below the BLS market median; a positive % sits above.

Americans displaced (modeled estimate)

631

The math
Base (1 per certified worker)
+428
Wage-gap multiplier

195 of 356 filings below BLS median

+50
WARN layoffs (government-reported)

1 notices filed

+153
Total631

Σ workers×(1+wage_gap) + Σ WARN layoffs. The 1.0 base rate per certified H-1B worker request is a site model assumption. Wage gap multiplier = (BLS median − offered wage) / BLS median, applied only to filings offering less than the BLS median. Related research provides context, not validation of these exact coefficients. This is a modeled estimate, not a count of actual displacements. WARN layoff counts are government-reported.

Exposure method v1.2 · This is a modeled worker-equivalent count.

Modeled consequence estimates

Conditional impacts associated with modeled displacement

Explore ZIP 90504’s scenarioEarnings · children · health · adjust the worker count

These are conditional population estimates scaled from ZIP 90504's current modeled displacement count. They are not observed outcomes, a prediction about any person, or evidence that this entity caused displacement.

Exposure method v1.2 (stored with this aggregate) · benchmarked to the latest BLS survey. Consequence parameters v1.54; build v1.54+engine0.4.1+d84162591c94d06c8148c4834ae705ff3f9a015c29955d95d26749834cd136ed+national-reference1

Excess deaths over 20 years

Illustrative reference calculation · population applicability is not established

18.15

Range: 7.11 to 31.62

20-year reference scenario: high-seniority male displacement effect. This is not an expected count for an unknown population.

Source-profile mortality point (deaths)
18.1524809246
No sustained excess from year 7 (deaths)
12.9543190147

Declared structural comparison; not a confidence interval or a model probability.

Baseline population: US prime-age men (45-54).

Child lifetime earnings lost

Illustrative reference calculation · population applicability is not established

$302.3M

Range: $78.5M to $510.3M

Canadian father–son firm-closure effect, applied to a US male lifetime-earnings baseline in 2024 dollars. The reference result uses 2 children per worker.

Baseline population: US male median lifetime earnings.

The mortality effect comes from a high-seniority male study cohort. Treat the count as a reference scenario unless the population matches. A mixed population needs a reviewed transport rule.

The range is the engine's parameter-support envelope: it varies declared parameters only and adds none of the exposure input's uncertainty.

The math, limits, and citations

Illustrative reference calculation scaled by the supplied worker-equivalent exposure. Two children per worker; 20-year mortality follow-up. This does not establish that an entity caused these outcomes.

Input SHA-256: a771d456f24b73ab4a27e51e83ec07640a0d93114d4ffc968aae925e700d843d

Excess deaths over 20 years: {"status":"illustrative_reference_calculation","eligible_for_public_headline":false,"target_population":null,"decision":null,"transport_assumptions":["high-tenure male mass-layoff cohort, ages 45–54","Pennsylvania early-1980s response transported to target place and calendar time","fixed baseline age rate over follow-up; cohort aging is not modeled"],"reason":"Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."}

Child lifetime earnings lost: {"status":"illustrative_reference_calculation","eligible_for_public_headline":false,"target_population":null,"decision":null,"transport_assumptions":["Canadian father-son firm-closure estimate transported to the target families","US male synthetic career earnings convert a relative adult earnings effect to dollars","lifetime dollars are undiscounted; this is not an annual loss"],"reason":"Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."}

Projection eligibility: {"child":{"status":"direct_estimate","eligible_for_validated_direct_contrast":true,"reason":"direct displacement-to-child adult earnings estimate; transport still requires an applicability decision"},"grandchild":{"status":"structural_projection","eligible_for_validated_direct_contrast":false,"reason":"combines a direct child estimate with an intergenerational persistence assumption; not an identified displacement intervention effect"},"greatgrandchild":{"status":"source_withdrawn","eligible_for_validated_direct_contrast":false,"reason":"source withdrawn for grandchild_earnings->greatgrandchild_earnings: The source measures earnings for three generations and education for four. It does not estimate .55 causal gap transmission to a fourth earnings generation. Retaining a projection would require an explicit uncalibrated assumption, not a source-identified default."}}

Exposure source: {"source":"one-worker normalized reference input","method":"scale by the stored warehouse worker-equivalent exposure at read time"}

Exact values: excess deaths over 20 years 18.1524809246 (range 7.10874345195 to 31.6202957627); child lifetime earnings lost $302,277,443.19 (range $78,513,621.61 to $510,338,540.46);

The displayed range is a parameter-support envelope, not a confidence interval.

Place reference: national reference.

Not included: exposure estimation error; baseline estimation error; unmodeled pathways.

Blocked model paths: local_service_jobs_lost: requires a documented net local loss of tradable jobs; worker displacement alone is not this exposure.

  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_peak; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_offset_1; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_offsets_2_3; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_offsets_4_5; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Excess deaths over 20 years: sullivan2009 (earnings_shock->mortality_sustained; canonical) Study population: US high-seniority displaced men born 1930-1959.
  • Child lifetime earnings lost: oreopoulos2008 (displacement->child_earnings; EXACT) Study population: Canada 39k father-son pairs firm closures.
Scenario assumptions, sensitivity and source records

Outcome statistics use the displayed exposure. Baselines, coefficients, annual family schedules and component records retain their source normalization.

{
  "displayed_workers": 631.199,
  "source_normalization_workers": 1,
  "applicability": {
    "excess_deaths": {
      "status": "illustrative_reference_calculation",
      "eligible_for_public_headline": false,
      "target_population": null,
      "decision": null,
      "transport_assumptions": [
        "high-tenure male mass-layoff cohort, ages 45–54",
        "Pennsylvania early-1980s response transported to target place and calendar time",
        "fixed baseline age rate over follow-up; cohort aging is not modeled"
      ],
      "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
    },
    "child_lifetime_earnings_lost_usd": {
      "status": "illustrative_reference_calculation",
      "eligible_for_public_headline": false,
      "target_population": null,
      "decision": null,
      "transport_assumptions": [
        "Canadian father-son firm-closure estimate transported to the target families",
        "US male synthetic career earnings convert a relative adult earnings effect to dollars",
        "lifetime dollars are undiscounted; this is not an annual loss"
      ],
      "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
    }
  },
  "target_population": null,
  "projection_eligibility": {
    "child": {
      "status": "direct_estimate",
      "eligible_for_validated_direct_contrast": true,
      "reason": "direct displacement-to-child adult earnings estimate; transport still requires an applicability decision"
    },
    "grandchild": {
      "status": "structural_projection",
      "eligible_for_validated_direct_contrast": false,
      "reason": "combines a direct child estimate with an intergenerational persistence assumption; not an identified displacement intervention effect"
    },
    "greatgrandchild": {
      "status": "source_withdrawn",
      "eligible_for_validated_direct_contrast": false,
      "reason": "source withdrawn for grandchild_earnings->greatgrandchild_earnings: The source measures earnings for three generations and education for four. It does not estimate .55 causal gap transmission to a fourth earnings generation. Retaining a projection would require an explicit uncalibrated assumption, not a source-identified default."
    }
  },
  "child_applicability": {
    "source": "oreopoulos2008",
    "source_age_at_displacement": [
      10,
      14
    ],
    "source_child_sex": "Male",
    "source_parent_sex": "Male",
    "source_geography": "Canada",
    "source_event": "father firm closure 1980-1982",
    "target_child_profiles": null,
    "incompatible_children": [],
    "unknown_children": [],
    "source_income_quartile": null,
    "income_rank_definition": null,
    "eligible_for_reviewed_transport": false,
    "status": "unknown",
    "limitations": [
      "No response curve across child ages is identified by this narrow cohort.",
      "Income groups refer to father's average pre-displacement income in 1978-1979; target rank mapping requires a transport argument.",
      "A subgroup's nonsignificant coefficient is retained with its uncertainty, not replaced with zero."
    ]
  },
  "child_valuation": null,
  "assumptions": {
    "mortality_method": "odds_survival",
    "mortality_timing": "Source-offset profile: displacement, +1, +2–3, +4–5, and +6+; displacement is follow-up year 1, so offset +6 begins in follow-up year 7. Annual baseline rates use a constant-hazard rate-to-risk conversion; odds ratios modify annual risk, and survival compounds across phases. The selected baseline age rate is held fixed over the follow-up horizon.",
    "mortality_contract": {
      "method": "odds_survival",
      "timing": "source_profile",
      "baseline_conversion": "1-exp(-annual_rate)",
      "phases": [
        {
          "phase": "displacement",
          "start_offset": 0,
          "duration_years": 1,
          "first_follow_up_year": 1
        },
        {
          "phase": "offset_1",
          "start_offset": 1,
          "duration_years": 1,
          "first_follow_up_year": 2
        },
        {
          "phase": "offsets_2_3",
          "start_offset": 2,
          "duration_years": 2,
          "first_follow_up_year": 3
        },
        {
          "phase": "offsets_4_5",
          "start_offset": 4,
          "duration_years": 2,
          "first_follow_up_year": 5
        },
        {
          "phase": "offset_6_plus",
          "start_offset": 6,
          "duration_years": null,
          "first_follow_up_year": 7
        }
      ],
      "description": "Source-offset profile: displacement, +1, +2–3, +4–5, and +6+; displacement is follow-up year 1, so offset +6 begins in follow-up year 7. Annual baseline rates use a constant-hazard rate-to-risk conversion; odds ratios modify annual risk, and survival compounds across phases. The selected baseline age rate is held fixed over the follow-up horizon."
    },
    "place_application": "initial_only",
    "place_counterfactual": "national child-dollar result is the reference"
  },
  "exposure_provenance": {
    "source": "one-worker normalized reference input",
    "method": "scale by the stored warehouse worker-equivalent exposure at read time"
  },
  "place": null,
  "place_mix": [],
  "input_content_sha256": "a771d456f24b73ab4a27e51e83ec07640a0d93114d4ffc968aae925e700d843d",
  "engine_version": "0.4.1",
  "bundle_sha256": "d84162591c94d06c8148c4834ae705ff3f9a015c29955d95d26749834cd136ed",
  "exposure_input_sha256": "8b4c78f6529f0fbefd8fc3154c9e9b976065d910b4c6e9d55690e36d5c3cdeaa",
  "input_hash": null,
  "engine_sha256": "d84162591c94d06c8148c4834ae705ff3f9a015c29955d95d26749834cd136ed",
  "adapter_sha256": "5fe4b51a9cebfb247cfcd74c734a2b6cb0eae44fce1073917b01455525c6ae52",
  "outcomes": {
    "excess_deaths": {
      "point": 18.152480924550556,
      "low": 7.108743451951978,
      "high": 31.62029576265212,
      "unit": "deaths",
      "baseline": {
        "value": 0.004944,
        "annual_probability": 0.004931798548274205,
        "unit": "deaths_per_person_year",
        "citation": "cdc_wonder D76 (Underlying Cause of Death, 1999-2020), Male 45-54 years, pooled 2015-2019: 514314 deaths / 104024440 person-years = 494.4 per 100k; pulled 2026-09-06 via scraper.cli wonder-mortality into warehouse wonder_mortality",
        "population": "US prime-age men (45-54)",
        "notes": "Pre-pandemic window: excludes 2020 (COVID-distorted; 2020 crude rate 601.5/100k). Single-year 2019 = 490.0/100k. Ages 45-54 match the Sullivan & von Wachter prime-age counterfactual population",
        "sex": "Male",
        "age": "45-54 years",
        "years": "2015-2019",
        "cause": "All causes",
        "geography": "US"
      },
      "steps": [
        {
          "link": "earnings_shock->mortality_peak",
          "phase": "displacement",
          "point": 2.6698,
          "low": 2.1144,
          "high": 3.3711,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_offset_1",
          "phase": "offset_1",
          "point": 1.9838,
          "low": 1.3697,
          "high": 2.8732,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_offsets_2_3",
          "phase": "offsets_2_3",
          "point": 1.7315,
          "low": 1.3238,
          "high": 2.2649,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_offsets_4_5",
          "phase": "offsets_4_5",
          "point": 1.2712,
          "low": 0.97,
          "high": 1.6661,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        },
        {
          "link": "earnings_shock->mortality_sustained",
          "phase": "offset_6_plus",
          "point": 1.1354,
          "low": 1.0335,
          "high": 1.2474,
          "citation": "sullivan2009",
          "tier": "canonical",
          "population_scope": "US high-seniority displaced men born 1930-1959",
          "evidence_role": "conditional"
        }
      ],
      "components": {
        "follow_up_years": 20,
        "method": "odds_survival",
        "timing": "source_profile"
      },
      "applicability": {
        "status": "illustrative_reference_calculation",
        "eligible_for_public_headline": false,
        "target_population": null,
        "decision": null,
        "transport_assumptions": [
          "high-tenure male mass-layoff cohort, ages 45–54",
          "Pennsylvania early-1980s response transported to target place and calendar time",
          "fixed baseline age rate over follow-up; cohort aging is not modeled"
        ],
        "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
      },
      "interpretation": "Conditional modeled expected difference; parameter bands are support envelopes, not a confidence interval.",
      "persistence_sensitivity": {
        "available": true,
        "status": "declared_structural_sensitivity",
        "eligible_for_public_headline": false,
        "unit": "deaths",
        "variants": {
          "source_profile": {
            "point": 18.152480924550556,
            "low": 7.108743451951978,
            "high": 31.62029576265212,
            "evidence_status": "source_profile_with_transport_assumptions",
            "citations": [
              "sullivan2009"
            ]
          },
          "no_sustained_excess": {
            "point": 12.95431901468634,
            "low": 5.801265028904602,
            "high": 22.320001861764922,
            "evidence_status": "structural_assumption",
            "motivating_citations": [
              "eliasonstorrie2009"
            ],
            "assumption": "Retain source odds through offset +5; set offset +6 onward OR=1.",
            "first_changed_follow_up_year": 7,
            "fixed_late_odds_ratio": 1
          }
        },
        "source_minus_no_sustained_point": 5.1981619098642176,
        "structural_point_range": {
          "low": 12.95431901468634,
          "high": 18.152480924550556,
          "interpretation": "Range of point estimates across these two assumptions; not a confidence interval or a bound on the true effect."
        },
        "shared_inputs": [
          "exposure",
          "resolved mortality baseline",
          "follow-up horizon",
          "source odds through offset +5"
        ],
        "limitations": [
          "No probabilities or model-average weights are assigned to the structures.",
          "A nonsignificant long-run estimate does not establish an exactly zero effect.",
          "The Swedish study differs in population, design, effect scale and follow-up; this hybrid does not reproduce its estimates or substitute its hazard ratios for odds ratios.",
          "The cutoff follows the source profile's offset +6 phase, not the Swedish study's windows; persistence beyond its 12-year follow-up is an assumption in either direction.",
          "Baseline aging and target-population transport remain unresolved in both structures."
        ]
      }
    },
    "child_lifetime_earnings_lost_usd": {
      "point": 302277443.1936337,
      "low": 78513621.60873607,
      "high": 510338540.456784,
      "steps": [
        {
          "link": "displacement->child_earnings",
          "kind": "direct",
          "citation": "oreopoulos2008",
          "tier": "EXACT",
          "param_point": 0.9076,
          "param_low": 0.844,
          "param_high": 0.976,
          "value_point": 0.9076,
          "value_low": 0.844,
          "value_high": 0.976,
          "causal_role": "direct_displacement_estimate",
          "population_scope": "Canada 39k father-son pairs firm closures",
          "evidence_role": "conditional"
        }
      ],
      "unit": "usd_2024",
      "baseline": {
        "value": 2591418,
        "unit": "usd_2024",
        "citation": "SSA Annual Statistical Supplement 2025, Table 4.B6 (CWHS/Master Earnings File, 1 percent sample): male median earnings by age, 2023 (preliminary) — synthetic career ages 20-64 = 5x(24218+42561+52485+60423+64962+67506+68160+64854)+2x60666+3x56666 = 2517175 usd_2023; CPI-U annual averages 304.702->313.689 (BLS series CUUR0000SA0, pulled 2026-09-06) -> 2591418 usd_2024; warehouse ssa_median_earnings (pulled via ssa-earnings-download)",
        "population": "US male median lifetime earnings",
        "notes": "Derivation declared: the cross-sectional age profile summed over a 45-year working life (ages 20-64) is a synthetic cohort — the sum of age-band medians approximates rather than equals the median of individual lifetime sums; median-of-workers semantics excludes non-working years; 2023 medians are preliminary (SSA replaces them with final data in a later edition)"
      },
      "applicability": {
        "status": "illustrative_reference_calculation",
        "eligible_for_public_headline": false,
        "target_population": null,
        "decision": null,
        "transport_assumptions": [
          "Canadian father-son firm-closure estimate transported to the target families",
          "US male synthetic career earnings convert a relative adult earnings effect to dollars",
          "lifetime dollars are undiscounted; this is not an annual loss"
        ],
        "reason": "Target cohort applicability and transport have not been established for this outcome; display as an illustrative reference calculation."
      },
      "interpretation": "Conditional modeled expected difference; parameter bands are support envelopes, not a confidence interval."
    }
  }
}

Parameter set v1.54 · model v1.54+engine0.4.1+d84162591c94d06c8148c4834ae705ff3f9a015c29955d95d26749834cd136ed+national-reference1

Layoffs & community

WARN notices

Renewal by Andersen LLC

2026-11-02 · Torrance

153

Community well-being

Food insecurity, SNAP receipt, mental distress, smoking, and overdose mortality in this area. CDC models these from survey data: treat them as local estimates, not headcounts. Bars compare each estimate against population-weighted averages of all reporting areas for the same data year.

Food insecurity

2023

13.8%: 3.3 points below All ZIPs

Adults receiving SNAP

2023

10.8%: 3.5 points below All ZIPs

Frequent mental distress

2023

14.0%: 2.8 points below All ZIPs

Adult smoking

2023

9.0%: 4.2 points below All ZIPs

Source: CDC PLACES 2025 release (BRFSS survey year 2023) and NCHS drug poisoning mortality. PLACES values are model-based small-area estimates, not survey counts. Benchmarks are population-weighted averages across all reporting areas.

Read the data

Questions about the data & methods

How many H-1B filings are in ZIP 90504, CA?

356 H-1B labor condition applications requesting 428 workers have been filed in ZIP 90504, CA, per Department of Labor disclosure records.

How many employers have H-1B filings in ZIP 90504, CA?

99 distinct employers have filed H-1B labor condition applications in ZIP 90504, CA. The employer list on this page is ranked by filings and wage impact.

What worker-equivalent exposure does the displacement model estimate for ZIP 90504, CA?

The model estimates 631 worker-equivalents of displacement exposure in ZIP 90504, CA: one per requested worker on a certified H-1B filing, raised where the offered wage sits below the occupation's BLS median, plus government-reported WARN layoffs matched to filings. This is a modeled exposure estimate, not a count of documented job losses; the formula is on the About page.

What is the median H-1B wage in ZIP 90504, CA?

$107,689 per year is the median wage offered on H-1B labor condition applications filed for work in ZIP 90504, CA. The wage-distribution chart on this page shows the spread around that median.

Who files the most H-1B filings in ZIP 90504, CA?

Garrett Transportation I Inc. leads with 60 filings, about 17% of all ZIP 90504, CA filings. Its dossier page carries the full filing, wage, and layoff history.

What share of ZIP 90504, CA H-1B filings does DOL deny?

DOL disclosure records show 345 certified, 7 denied, 4 withdrawn of 356 labor condition applications with reported outcomes in ZIP 90504, CA. The denial share is 2% across the reported outcomes.

How many WARN layoff notices has ZIP 90504, CA recorded?

1 Worker Adjustment and Retraining Notification (WARN) notice. Where a layoff employer then filed H-1B labor condition applications in the same window, the pair is recorded as a displacement event with an evidence score.

When did H-1B use peak in ZIP 90504, CA?

Filings peaked in 2025 at 39 labor condition applications. The filings-by-year chart on this page shows the full trend since records began.

Which immigration law firms file the most H-1B filings in ZIP 90504, CA?

76 distinct law firms and agents have filed H-1B applications for employers in ZIP 90504, CA. The law-firm table on this page ranks them by filings and by the wage gap their filings carry.

Do ZIP 90504, CA H-1B employers hold federal contracts?

200 federal contract actions in ZIP 90504, CA name employers that also file H-1B labor condition applications. The contracts table links each award to the employer dossier. A shared employer name does not show how award funds were spent.

Where does the ZIP 90504, CA H-1B data come from?

Every figure on this page traces to a public government record: DOL OFLC disclosure files (LCA filings, wages, outcomes), BLS OES wage data (occupation medians), state WARN notices, and federal contract awards. The archive is read-only evidence; nothing is crowdsourced or anonymous.

Public source records and site analysis. We do not attest to accuracy. Read the full disclaimer.

Dataset guides and site methods

  1. [1] Dataset documentation · DOL OFLC. LCA public disclosure record layout (FY2026 Q3). Pages 1–4: application, DOL outcome and dates, requested positions, employer, representatives, worksites and pay unitsThis layout covers determinations issued October 1, 2025 through June 30, 2026. It documents employer-provided application fields and DOL decisions, not USCIS decisions, payroll verification, legal bills or worker-linked moves. Older layouts can differ.Checked 2026-10-17.
  2. [2] Dataset documentation · BLS. OEWS technical notes (May 2025). Scope of the survey; occupational coding; concepts and estimation methodologyDocuments occupation and geographic wage estimates, not an individual worker’s pay. Use the estimate year and geography stated by the site; older releases can differ.Checked 2026-10-17.
  3. [3] XH1B method or registry · XH1B. WARN Notices (mass layoffs): source registry; Calculation and Matching Methods; Reading Public Records and Derived Indicators. Source registry entry: warn; Filing units, annualization, weighting, wage comparisons, and inference limits; Reading records: units, source coverage, wage gaps, entity links, and inference limitsXH1B dataset description: One row per source_notice_id. The definition of a mass layoff and the layoff threshold vary by state. The threshold is typically 50 or more employees.; These are the site's review methods, not validated predictions of wrongdoing. Inspect underlying records and alternative explanations.
  4. [4] Dataset documentation · USAspending / U.S. Treasury. Federal Spending Guide: contract transactions. Pages 3, 5, 9 and 17: transactions, amount fields and recipient identifiersContract downloads contain prime award transactions. XH1B’s use of recipient identifiers for employer links is its own processing step.Checked 2026-10-18.
  5. [5] XH1B method or registry · XH1B. Displacement Model and Assumptions. Eligibility, requested-position weighting, scopes, WARN matching, and counting limitsModel outputs are estimates. A matched layoff notice does not prove that an H-1B worker replaced a laid-off worker.
  6. [6] XH1B method or registry · XH1B. Downstream Research and Methods. Study populations, parameter bounds, baselines, and expected outcomes; linked model card