County intelligence

Fayette County

Kentucky (KY) · FIPS 21067 · 806 employers · 4,206 filings with wage data

Employers in Fayette, KY submitted 4,569 certified H-1B applications requesting 8,881 workers across 787 companies. The median offered wage is $66,509/yr. The largest filers are Wipro Limited, University of Kentucky and Deloitte Consulting LLP. The displacement model assigns 12.3K worker-equivalent exposures to these filings. Separately, 1,052 layoffs appear in matched WARN notices.

Data current as of Sep 2, 2026

What the local records contain / DOL & WARN

4,206H-1B filings with wage dataCertified applications with a recorded wage8,881Workers requestedRequests, not confirmed hires806EmployersNamed in county filings

4 WARN notices Public layoff notices 18,498 Federal awards Linked county contractors 221 Law firms Filing representation records

What XH1B calculates / Local wage comparisons

$90,150Average offered wageAnnualized offers in available filings0%Below prevailing wage0 of 4,206 compared22%below BLS medianBLS median $115,329

How to read the wage comparison

County wage averages combine occupations, locations, and years. They are a screening comparison, not a finding about any individual filing.

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.

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Certified, denied, and withdrawn counts describe application decisions.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 4,134 positive year-unit LCA offers, all outcomes and visa classes.

Application outcomes all available years

Certified4,448 · 95.4%
Denied77 · 1.7%
Withdrawn136 · 2.9%

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)

12,284

The math

Base (1 per certified worker)

+8,881

Wage-gap multiplier

2784 of 4569 filings below BLS median

+2,351

WARN layoffs (government-reported)

4 notices filed

+1,052

Total12,284

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

These are conditional population estimates scaled from Fayette 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 v1.52; build v1.52+engine0.4.0+99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153+national-reference1

Excess deaths over 20 years

Illustrative reference calculation · population applicability is not established

353.27

Range: 138.34 to 615.37

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

Source-profile mortality point (deaths): 353.267912029
No sustained excess from year 7 (deaths): 252.10577271

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

$5.9B

Range: $1.5B to $9.9B

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 353.267912029 (range 138.344227814 to 615.366897134); child lifetime earnings lost $5,882,662,631.87 (range $1,527,964,319.97 to $9,931,768,079.78);

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": 12283.85,
  "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": 353.2679120293923,
      "low": 138.34422781446153,
      "high": 615.3668971339534,
      "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": 353.2679120293923,
            "low": 138.34422781446153,
            "high": 615.3668971339534,
            "evidence_status": "source_profile_with_transport_assumptions",
            "citations": [
              "sullivan2009"
            ]
          },
          "no_sustained_excess": {
            "point": 252.10577270964436,
            "low": 112.89921154074992,
            "high": 434.3726065308105,
            "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": 101.16213931974794,
        "structural_point_range": {
          "low": 252.10577270964436,
          "high": 353.2679120293923,
          "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": 5882662631.870643,
      "low": 1527964319.9664013,
      "high": 9931768079.7816,
      "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

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

51.4: 19.2 above U.S.

This county51.4

Kentucky51.5

U.S.32.1

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 residents856↑ 10.4× median

Active MDs (non-federal)2,740

Nurse practitioners per 100k448↑ 3.7× median

County population320,154

Primary care HPSA designations4

H-1B medical workers certifiedhealthcare SOCs (29-* + 31-2*)52955% of BLS

Full medical breakdown

Fayette County in context

DOL filings CountyRecordH-1B intensity by county across Kentucky. 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 (806)

DOL filings EmployerRecordRanked by applications in this county.

EmployerFilings

University of Kentucky

1,939

Wipro Limited ⚠ Dep

278

Tata Consultancy Services Limited ⚠ Dep

126

Fayette County Public Schools

Sitek, Inc. ⚠ Dep

Deloitte Consulting LLP

Piramal Pharma Solutions Inc.

Populus Group LLC

DOL wage offers BLS occupationsSignalOccupation averages need not describe each filing.

Job categoryH-1B vs BLS

19-1042 Medical Scientists, Except EpidemiologistsH-1B $57.2K vs BLS $103.4K-45%

290 workers · 290 filings · $14.4M wage theft

17-2071 Electrical EngineersH-1B $82.1K vs BLS $120.6K-32%

157 workers · 50 filings · $7.4M wage theft

17-2141 Mechanical EngineersH-1B $77.5K vs BLS $104.1K-26%

117 workers · 45 filings · $4.1M wage theft

19-1021 Biochemists and BiophysicistsH-1B $50.9K vs BLS $127.4K-60%

41 workers · 41 filings · $3.1M wage theft

15-1252 Software DevelopersH-1B $105.2K vs BLS $136K-23%

85 workers · 83 filings · $2.9M wage theft

29-1229 Physicians, All OtherH-1B $245.6K vs BLS $265.9K-8%

74 workers · 74 filings · $2.8M wage theft

13-2011 Accountants and AuditorsH-1B $57K vs BLS $83.7K-32%

63 workers · 14 filings · $2.7M wage theft

19-1029 Biological Scientists, All OtherH-1B $51.7K vs BLS $98.9K-48%

55 workers · 55 filings · $2.6M wage theft

Labor condition applications (4,823)

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

Title · Worksite