County intelligence

Delaware County

Pennsylvania (PA) · FIPS 42045 · 1,356 employers · 8,063 filings with wage data

Employers in Delaware, PA filed 8,621 certified H-1B applications requesting 15,224 workers across 1,320 companies. The median offered wage is $92,082/yr. The largest filers are Cognizant Technology Solutions U.S. Corporation, SAP America, Inc. and Cognizant Technology Solutions US Corp.. The displacement model assigns 18K worker-equivalent exposures to these filings. Separately, 246 layoffs appear in matched WARN notices.

Source import recorded Sep 2, 2026

What the local records contain / DOL & WARN

What XH1B calculates / Local wage comparisons

How to read the wage comparison

County averages mix occupations and years. Offered wages and the latest available national BLS occupation medians are averaged separately over available records, so their populations can differ. This is a screening comparison, not a comparison of matched filings or a finding about an individual wage.

Definitions & methodology ↗

Filings & wages

Annual filing records and a county-level wage comparison.

Filing history

Annual DOL filing records. Workers requested are not confirmed hires.

05001K2K2K3Kpeak 793 (2019)2007: 56 filings (64 workers)2008: 427 filings (591 workers)2009: 289 filings (339 workers)2010: 75 filings (86 workers)2011: 371 filings (404 workers)2012: 333 filings (527 workers)2013: 265 filings (469 workers)2014: 79 filings (287 workers)2015: 614 filings (2,888 workers)2016: 748 filings (2,594 workers)2017: 640 filings (1,385 workers)2018: 655 filings (1,185 workers)2019: 793 filings (826 workers)2020: 692 filings (756 workers)2021: 645 filings (775 workers)2022: 528 filings (719 workers)2023: 515 filings (555 workers)2024: 514 filings (531 workers)2025: 526 filings (526 workers)2026: 120 filings (120 workers)200720082009201020112012201320142015201620172018201920202021202220232024202520262007: 64 workers2008: 591 workers2009: 339 workers2010: 86 workers2011: 404 workers2012: 527 workers2013: 469 workers2014: 287 workers2015: 2,888 workers2016: 2,594 workers2017: 1,385 workers2018: 1,185 workers2019: 826 workers2020: 756 workers2021: 775 workers2022: 719 workers2023: 555 workers2024: 531 workers2025: 526 workers2026: 120 workersfilings
filingsworkers (scaled)
Inspect filing outcomes All available years and DOL statuses

Certified, denied, and withdrawn counts describe application decisions. They do not measure visas issued or workers hired.

Offered-wage distribution

Percentiles across 7,894 positive year-unit LCA offers, all outcomes and visa classes.

$49,590$76,477$103,365$130,253$157,140$92,394annual wage

Application outcomes all available years

  • Certified8,431 · 97.0%
  • Denied105 · 1.2%
  • Withdrawn159 · 1.8%
How this distribution is built Year-unit offers, all outcomes and visa classes

The distribution covers positive offers with wage unit Year, across all outcomes and visa classes. It differs from the certified H-1B summary cohort. It does not adjust for occupation, employer, or worksite mix.

Downstream impact

Conditional effects of this county's modeled displacement exposure.

Americans displaced (modeled estimate)

18,036

The math
Base (1 per certified worker)
+15,224
Wage-gap multiplier

4863 of 8621 filings below BLS median

+2,566
WARN layoffs (government-reported)

3 notices filed

+246
Total18,036

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 Delaware County’s scenarioEarnings · children · health · adjust the worker count

These are conditional population estimates scaled from Delaware County'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

518.69

Range: 203.13 to 903.52

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

Source-profile mortality point (deaths)
518.688523299
No sustained excess from year 7 (deaths)
370.156378514

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

$8.6B

Range: $2.2B to $14.6B

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 518.688523299 (range 203.125052654 to 903.517518271); child lifetime earnings lost $8,637,267,891.28 (range $2,243,446,205.53 to $14,582,400,335.93);

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": 18035.864,
  "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": 518.6885232989725,
      "low": 203.1250526542286,
      "high": 903.5175182707355,
      "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": 518.6885232989725,
            "low": 203.1250526542286,
            "high": 903.5175182707355,
            "evidence_status": "source_profile_with_transport_assumptions",
            "citations": [
              "sullivan2009"
            ]
          },
          "no_sustained_excess": {
            "point": 370.15637851374424,
            "low": 165.76519780493868,
            "high": 637.7711594260114,
            "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": 148.53214478522827,
        "structural_point_range": {
          "low": 370.15637851374424,
          "high": 518.6885232989725,
          "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": 8637267891.280094,
      "low": 2243446205.5272985,
      "high": 14582400335.927427,
      "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

Local connections

County context, public notices, and linked public records.

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.

Drug overdose deaths

2021

56.1: 23.9 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.

Medical workforce context

AHRF supply DOL filingsRecordAHRF county supply data and H-1B medical LCAs. Comparisons use the median US county.
MDs per 100k residents402↑ 4.4× median
Active MDs (non-federal)2,316
Nurse practitioners per 100k110↑ 15% above
County population576,720
Primary care HPSA designations3
H-1B medical workers certifiedhealthcare SOCs (29-* + 31-2*)43233% of BLS
Full medical breakdown

Delaware County in context

DOL filings CountyRecordH-1B intensity by county across Pennsylvania. This county is highlighted. Click any county to drill in.
Loading map…
Read the county map County-level H-1B intensity

The map gives geographic context. A county average does not classify every filing, employer, or worker within it.

Employers & occupations

The sponsors and job categories recorded in this county.

Employers (1,356)

DOL filings EmployerRecordRanked by applications in this county.
EmployerFilings
1

SAP America, Inc.

2,563
2

Cognizant Technology Solutions US Corp. ⚠ Dep

464
3

Villanova University

177
4

Cognizant Technology Solutions U.S. Corporation ⚠ Dep

173
5

Capgemini America Inc. ⚠ Dep

166
6

SAP Labs, LLC

161
7

Mercy Catholic Medical Center

131
8

Swarthmore College

115

Job categories (184)

  • Management Analysts$12.5M · 33.9%
  • Software Developers$8.4M · 22.9%
  • Physicians, All Other$3.4M · 9.3%
  • Physical Therapists$3M · 8.3%
  • Computer and Information Systems Managers$2.9M · 7.8%
  • Financial and Investment Analysts$2.4M · 6.5%
  • Occupational Therapists$2.1M · 5.7%
  • Computer Occupations, All Other$2.1M · 5.6%
DOL wage offers BLS occupationsSignalOccupation averages need not describe each filing.
Job categoryH-1B vs BLS
13-1111 Management AnalystsH-1B $82.1K vs BLS $101.9K-19%

620 workers · 109 filings · $12.5M wage theft

15-1252 Software DevelopersH-1B $116.8K vs BLS $136K-14%

342 workers · 322 filings · $8.4M wage theft

29-1229 Physicians, All OtherH-1B $153.1K vs BLS $265.9K-42%

28 workers · 27 filings · $3.4M wage theft

29-1123 Physical TherapistsH-1B $67.8K vs BLS $102.8K-34%

79 workers · 44 filings · $3.0M wage theft

125 workers · 119 filings · $2.9M wage theft

13-2051 Financial and Investment AnalystsH-1B $92.2K vs BLS $102.7K-10%

97 workers · 71 filings · $2.4M wage theft

29-1122 Occupational TherapistsH-1B $61.9K vs BLS $100.3K-38%

55 workers · 11 filings · $2.1M wage theft

15-1299 Computer Occupations, All OtherH-1B $112.7K vs BLS $116.6K-3%

151 workers · 151 filings · $2.1M wage theft

Labor condition applications (8,961)

DOL filings BLS occupationsRecordAll recorded outcomes and visa classes. Use the wage badge to inspect an offer against available benchmarks.
Title · Worksite

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. A wage comparison is a screening calculation, not a finding of a wage violation.

WARN notices (8)Public layoff notices: open to inspect
WARN EmployerReviewOpen a notice to inspect its stated effective date and worker count. Coverage varies by state; some states file no public WARN data.

Records to inspect

Open the linked public records behind this county's filings.

Immigration law firms (446)

DOL filings Law firmRecordNames are shown as recorded.

Federal contracts (15,012)

Federal awards EmployerRecordAmounts are individual award actions, not total contract values.
THE BOEING COMPANY
Department of Defense · Oct 27, 2025
$876.4M
THE BOEING COMPANY
Department of Defense · May 19, 2026
$396.8M
BOEING COMPANY, THE
Department of Defense · Mar 26, 2026
$326.1M
THE BOEING COMPANY
Department of Defense · Nov 20, 2025
$271.7M
THE BOEING COMPANY
Department of Defense · Dec 18, 2025
$183.2M
THE BOEING COMPANY
Department of Defense · Jan 16, 2026
$118.8M
THE BOEING COMPANY
Department of Defense · Jan 13, 2026
$89.1M
THE BOEING COMPANY
Department of Defense · Mar 25, 2026
$52.2M

Evidence & sources

Scope, methods, and source coverage for this county record.

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
  7. [7] Dataset documentation · HRSA. Area Health Resources Files: 2024–2025 technical documentation. County User Guide: physicians, Table 10 NPI professions, population estimates and missing values; Technical Documentation: variable years and sourcesClinician categories and variable years differ. County APRN counts use NPI taxonomy; physician active and federal status matter. Release year is not the year of every measure.Checked 2026-10-18.
Questions about the data & methods

How many H-1B filings are in Delaware County, PA?

8,621 H-1B labor condition applications requesting 15,224 workers have been filed in Delaware County, PA, per Department of Labor disclosure records.

How many employers have H-1B filings in Delaware County, PA?

1,320 distinct employers have filed H-1B labor condition applications in Delaware County, PA. The employer list on this page is ranked by filings and wage impact.

What worker-equivalent exposure does the displacement model estimate for Delaware County, PA?

The model estimates 18,036 worker-equivalents of displacement exposure in Delaware County, PA: 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 Delaware County, PA?

$92,082 per year is the median wage offered on H-1B labor condition applications filed for work in Delaware County, PA. The wage-distribution chart on this page shows the spread around that median.

Who files the most H-1B filings in Delaware County, PA?

SAP America, Inc. leads with 2,563 filings, about 30% of all Delaware County, PA filings. Its dossier page carries the full filing, wage, and layoff history.

What share of Delaware County, PA H-1B filings does DOL deny?

DOL disclosure records show 8,431 certified, 105 denied, 159 withdrawn of 8,695 labor condition applications with reported outcomes in Delaware County, PA. The denial share is 1% across the reported outcomes.

How many WARN layoff notices has Delaware County, PA recorded?

8 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 Delaware County, PA?

Filings peaked in 2019 at 793 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 Delaware County, PA?

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

Do Delaware County, PA H-1B employers hold federal contracts?

15,012 federal contract actions in Delaware County, PA 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 Delaware County, PA 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.