Data current as of Sep 2, 2026
Workers requested
238.7K
Requests on filings, not hires
Median offered wage
$84K
Annual, certified filings
Below prevailing
0.02%
Share of 125.1K filings with a wage on record
Latest year
1.9K
Calendar 2026 · peak 2019 at 11.4K
Americans displaced (modeled estimate)
293,635
The math
97119 of 133004 filings below BLS median
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.
Exposure method v1.2 · This is a modeled worker-equivalent count.
Inside the state
Where inside the state the activity concentrates.Modeled consequences
Estimates scaled from the modeled displacement figure above. Not observed outcomes.Modeled consequence estimates
Conditional impacts associated with modeled displacement
These are conditional population estimates scaled from Arizona'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 v1.52; build v1.52+engine0.4.0+99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153+national-reference1
Excess deaths over 20 years
Illustrative reference calculation · population applicability is not established
8,444.57
Range: 3,307 to 14,709.83
20-year reference scenario: high-seniority male displacement effect. This is not an expected count for an unknown population.
- Source-profile mortality point (deaths)
- 8,444.57255351
- No sustained excess from year 7 (deaths)
- 6,026.37662893
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
$140.6B
Range: $36.5B to $237.4B
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: 65625244b6014b6429cf6d6fd7f3f525fdafb6dce287e996ad1a82b5db273d17
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":"structural_projection","eligible_for_validated_direct_contrast":false,"reason":"repeats an intergenerational persistence assumption beyond the identification core"}}
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 8,444.57255351 (range 3,307.00250251 to 14,709.8285265); child lifetime earnings lost $140,620,106,471.90 (range $36,524,702,979.72 to $237,410,569,368.15);
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": 293635.111,
"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": "structural_projection",
"eligible_for_validated_direct_contrast": false,
"reason": "repeats an intergenerational persistence assumption beyond the identification core"
}
},
"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": "65625244b6014b6429cf6d6fd7f3f525fdafb6dce287e996ad1a82b5db273d17",
"engine_version": "0.4.0",
"engine_sha256": "99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153",
"adapter_sha256": "605700852536cef19bdae955f055979ab182f352c107882e7b46fb6cccd3e68e",
"outcomes": {
"excess_deaths": {
"point": 8444.57255351448,
"low": 3307.002502514171,
"high": 14709.82852653313,
"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": 8444.57255351448,
"low": 3307.002502514171,
"high": 14709.82852653313,
"evidence_status": "source_profile_with_transport_assumptions",
"citations": [
"sullivan2009"
]
},
"no_sustained_excess": {
"point": 6026.37662893451,
"low": 2698.7607722807247,
"high": 10383.312115829634,
"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": 2418.1959245799685,
"structural_point_range": {
"low": 6026.37662893451,
"high": 8444.57255351448,
"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": 140620106471.9032,
"low": 36524702979.71513,
"high": 237410569368.1482,
"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 v1.52 · model v1.52+engine0.4.0+99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153+national-reference1
Employers & filings
Who files here, and the filings behind every number above.Top employers (11,609)
5 largest employers account for 20% of the 133,004 filings attributed to 11,609 employers here (the records). See the ranking
Context & calculation notes how the share is built
Share = filings by the top 5 employers ÷ all filings in this geography with a resolved employer. Filings whose employer is not yet linked sit outside both numbers, so the denominator can be smaller than the geography's headline filing count.
The share describes this one geography. A high share is a concentration signal for inspection, not a finding about any employer.
Labor condition applications (139,576)
Visam Technologies Inc.(1 position requested)
Software Developer · Phoenix 85054 · 2026-03-31
GP Technologies LLC(1 position requested)
UX Designer · PHOENIX 85032 · 2026-03-31
The University of Arizona(1 position requested)
Postodoctoral Research Associate III · Tucson 85721 · 2026-03-31
GP Technologies LLC(1 position requested)
UX Designer · PHOENIX 85032 · 2026-03-31
Amazon.com Services LLC(1 position requested)
Software Development Engineer III · Tempe 85281 · 2026-03-31
Bechtel Global Corporation(1 position requested)
Senior Oracle Developer · Glendale 85305 · 2026-03-31
Amazon.com Services LLC(10 positions requested)
Software Development Engineer II · TEMPE 85281 · 2026-03-31
Smart Prism Solutions Inc.(1 position requested)
Business Intelligence Analyst · Chandler 85286 · 2026-03-31
A negative % sits below the BLS market median; a positive % sits above.
What the filing rows show One application per row
Each row links to the disclosure record. The wage badge compares an offer with available benchmarks; it is a screening calculation, not a finding of a wage violation.
Wages & occupations
What wages are being offered, against which benchmarks.Wages
0.02% of the 125,088 filings with a wage on record offer below the employer's own prevailing wage. The prevailing wage is the floor the employer attested to, not a market benchmark.
Offered-wage distribution
Percentiles across 124,677 positive year-unit LCA offers, all outcomes and visa classes.
| p10 | p25 | Median | p75 | p90 |
|---|---|---|---|---|
| $57,720 | $67,538 | $84,000 | $106,000 | $135,000 |
Context & calculation notes wage sources and averages
Offered wages are employer-reported on the DOL record, annualized to year rates. Averages mix occupations and years: a geography-level average is a screening comparison, not a matched-role finding.
The BLS market median is the OES national median for the filing's occupation (latest available year). The prevailing wage is the employer's own attested floor. The two answer different questions and are not interchangeable.
The distribution covers positive offers with wage unit Year, across all outcomes and visa classes. It differs from the certified H-1B summary cohort. Hourly and other wage units are outside this distribution.
Definitions & methodology ↗Wage gap by job category: H-1B vs BLS
3,503 filings · $309.2M certified gap (est.)
10,504 filings · $299.2M certified gap (est.)
2,133 filings · $285.1M certified gap (est.)
3,836 filings · $140.0M certified gap (est.)
1,034 filings · $74.7M certified gap (est.)
896 filings · $50.4M certified gap (est.)
1,161 filings · $49.6M certified gap (est.)
Programs & time
What kinds of foreign-labor activity happen here, and how the volume moved.Program mix
| Program | Records | Share of rows |
|---|---|---|
| H-1BLabor condition applications, certified slice | 133,004 | 98.7% |
| H-1B1 (Chile)LCA sibling class, all recorded outcomes | 234 | 0.2% |
| H-1B1 (Singapore)LCA sibling class, all recorded outcomes | 94 | 0.1% |
| E-3 (Australia)LCA sibling class, all recorded outcomes | 1,359 | 1% |
Compare on a chart share of rows shown above
- H-1B133,004 · 98.7%
- H-1B1 (Chile)234 · 0.2%
- H-1B1 (Singapore)94 · 0.1%
- E-3 (Australia)1,359 · 1.0%
A filing, certification, or determination is a DOL record, not a visa issuance and not observed employment. Prevailing-wage determinations carry no county or ZIP on the source record.
Activity over time
Outcome breakdown (all years)
- Certified133,004 · 96.5%
- Denied1,652 · 1.2%
- Withdrawn3,206 · 2.3%
Certified, denied, and withdrawn are application decisions. They do not count visas issued or workers hired.
Context
Enforcement, community health, and money linked to this state's record.WARN notices (1,365)
Federal WARN requires 60 days' advance notice; statutory exceptions can shorten or excuse notice. This site publishes notices as filed and does not judge compliance.
Arizona layoffs and WARN noticesImmigration law firms (2,248)
Federal contracts (27,637)
Medical workforce: licensed vs H-1B
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
202315.8%: 0.7 points above U.S.
Households on SNAP
202311.1%: 0.7 points below U.S.
Frequent mental distress
202315.4%: 0.7 points below U.S.
Adult smoking
202311.4%: 0.6 points below U.S.
Drug overdose deaths
202138.8: 6.7 above U.S.
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.
Evidence & sources
Scope, methods, and source coverage for this state record.Public source records and site analysis. We do not attest to accuracy. Read the full disclaimer.
Dataset guides and site methods
- [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] 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] 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] 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] 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] XH1B method or registry · XH1B. Downstream Research and Methods. Study populations, parameter bounds, baselines, and expected outcomes; linked model card
- [7] Dataset documentation · National Council of State Boards of Nursing. Active RN Licenses. RN licensure statistics by jurisdiction; linked table header; licensure data compiled through NursysCounts active licenses, not jobs. Check the source year. License and employment figures have different units and do not identify nurses who are not working.Checked 2026-10-18.
- [8] Dataset documentation · DOL OFLC. PERM public disclosure record layout (FY2026 Q3). Pages 1–7: ETA-9089 application, DOL outcome and dates, employer, wages and recruitment fieldsThis layout covers determinations issued October 1, 2025 through June 30, 2026, on the form introduced June 1, 2023. A DOL certification is not I-140 approval or permanent residence. Older layouts can differ.Checked 2026-10-17.
- [9] Dataset documentation · DOL OFLC. Prevailing Wage disclosure record layout, FY2026 Q3. Page 1: CASE_NUMBER, CASE_STATUS, VISA_CLASS; pages 5–6: PWD_WAGE_RATE, PWD_UNIT_OF_PAY, wage source and validityApplication-level prevailing-wage requests and determinations. Wage units and case status must be read; a determination is not evidence of pay received.Checked 2026-10-18.
- [10] Dataset documentation · DOL OFLC. H-2A disclosure record layout, FY2026 Q3. Page 1: application case number and decision; page 5: separate job-order number, requested and certified H-2A workersEmployer application and labor-certification records, not a worker roster or arrival record. A case number differs from a job-order number.Checked 2026-10-18.
- [11] Dataset documentation · DOL OFLC. H-2B disclosure record layout, FY2026 Q3. Pages 1–2: case number, requested and certified workers, cap estimates and temporary-need categoriesCap-subject and cap-exempt counts are estimated requested workers. Temporary need includes seasonal, peakload, one-time and intermittent work.Checked 2026-10-18.
- [12] Dataset documentation · DOL OFLC. CW-1 disclosure record layout, FY2026 Q3. Page 1: application case number, status and cap-exempt flag; job information: requested and certified workersEmployer applications and labor-certification determinations. A certification is separate from a visa-petition decision or an admission.Checked 2026-10-18.
Questions about the data & methods
How many H-1B filings are in Arizona?
133,004 H-1B labor condition applications requesting 238,699 workers have been filed in Arizona, per Department of Labor disclosure records.
How many employers have H-1B filings in Arizona?
11,609 distinct employers have filed H-1B labor condition applications in Arizona. The employer list on this page is ranked by filings and wage impact.
What worker-equivalent exposure does the displacement model estimate for Arizona?
The model estimates 293,635 worker-equivalents of displacement exposure in Arizona: 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 Arizona?
$84,000 per year is the median wage offered on H-1B labor condition applications filed for work in Arizona. The wage-distribution chart on this page shows the spread around that median.
Who files the most H-1B filings in Arizona?
INFOSYS LIMITED leads with 9,482 filings, about 7% of all Arizona filings. Its dossier page carries the full filing, wage, and layoff history.
What share of Arizona H-1B filings does DOL deny?
DOL disclosure records show 133,004 certified, 1,652 denied, 3,206 withdrawn of 137,862 labor condition applications with reported outcomes in Arizona. The denial share is 1% across the reported outcomes.
How many WARN layoff notices has Arizona recorded?
1,365 Worker Adjustment and Retraining Notification (WARN) notices. 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 Arizona?
Filings peaked in 2019 at 11,378 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 Arizona?
2,248 distinct law firms and agents have filed H-1B applications for employers in Arizona. The law-firm table on this page ranks them by filings and by the wage gap their filings carry.
Do Arizona H-1B employers hold federal contracts?
27,637 federal contract actions in Arizona 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 Arizona 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.