# Bannock, ID (FIPS 16005): H-1B profile

> County profile: https://www.xh1b.org/county/16005

Employers in Bannock, ID submitted 425 certified H-1B applications requesting 469 workers across 74 companies. The median offered wage is $68,359/yr. The largest filers are Idaho State University, VTCU Corp. and ON Semiconductor. The displacement model assigns 2.25K worker-equivalent exposures to these filings. Separately, 1,658 layoffs appear in matched WARN notices.

| Metric | Value |
|---|---|
| H-1B filings | 425 |
| Workers requested | 469 |
| US workers displaced (modeled) | 2,255 |
| Distinct employers | 74 |
| Filings below prevailing wage (share of compared filings) | 0% |
| Wage gap vs BLS | 0% |

| Metric | Value |
|---|---|
| Average offered wage | $79K |
| Average prevailing wage | $63K |
| Average BLS market wage | $110K |

## US workers displaced (modeled)

| Metric | Value |
|---|---|
| Base rate (1.0 per certified worker) | 469 |
| Wage-gap multiplier | 128 |
| Matched WARN notice layoff counts | 1,658 |
| Certified filings | 425 |
| Filings below BLS median | 311 |
| **Total (modeled)** | **2,255** |
| Exposure method version | v1.2 |

These are derived estimates, not raw counts. The formula and every component are shown on the full HTML page.

## Modeled consequence estimates

**Conditional impacts associated with modeled displacement**

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

[Explore Bannock County’s scenario: Earnings · children · health · adjust the worker count](https://www.xh1b.org/downstream?workers=2254.834&entity=Bannock%20County#downstream-explorer)

| Metric | Value |
|---|---|
| Exposure method version | 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` |

| Outcome | Applicability | Estimate | Range |
|---|---|---|---|
| Excess deaths over 20 years | Illustrative reference calculation · population applicability is not established | 64.8461597262 | 25.394584644 to 112.957273341 |
| Child lifetime earnings lost | Illustrative reference calculation · population applicability is not established | $1,079,826,578.22 | $280,474,435.90 to $1,823,083,833.36 |

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

Source-profile mortality point (deaths): 64.8461597262

No sustained excess from year 7 (deaths): 46.2767510106

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

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

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 64.8461597262 (range 25.394584644 to 112.957273341); child lifetime earnings lost $1,079,826,578.22 (range $280,474,435.90 to $1,823,083,833.36);

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.

### Scenario assumptions, sensitivity and source records

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

```json
{
  "displayed_workers": 2254.834,
  "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": 64.84615972621634,
      "low": 25.39458464404837,
      "high": 112.95727334118706,
      "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": 64.84615972621634,
            "low": 25.39458464404837,
            "high": 112.95727334118706,
            "evidence_status": "source_profile_with_transport_assumptions",
            "citations": [
              "sullivan2009"
            ]
          },
          "no_sustained_excess": {
            "point": 46.276751010634136,
            "low": 20.723875719361217,
            "high": 79.73380673602279,
            "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": 18.569408715582206,
        "structural_point_range": {
          "low": 46.276751010634136,
          "high": 64.84615972621634,
          "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": 1079826578.2202978,
      "low": 280474435.90137625,
      "high": 1823083833.358944,
      "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."
    }
  }
}
```

- 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.

Parameter set v1.52 · model v1.52+engine0.4.0+99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153+national-reference1

## Filings by year

Calendar submission years 2007–2026. One row per filing.

| Year | Filings | Workers | Employers |
|---|---|---|---|
| 2007 | 4 | 4 | 1 |
| 2008 | 16 | 16 | 8 |
| 2009 | 12 | 12 | 8 |
| 2010 | 2 | 2 | 2 |
| 2011 | 22 | 23 | 7 |
| 2012 | 10 | 10 | 4 |
| 2013 | 14 | 14 | 5 |
| 2014 | 8 | 8 | 3 |
| 2015 | 32 | 33 | 7 |
| 2016 | 49 | 49 | 18 |
| 2017 | 50 | 54 | 17 |
| 2018 | 35 | 73 | 16 |
| 2019 | 42 | 42 | 11 |
| 2020 | 20 | 20 | 7 |
| 2021 | 19 | 19 | 7 |
| 2022 | 34 | 34 | 9 |
| 2023 | 19 | 19 | 10 |
| 2024 | 27 | 27 | 14 |
| 2025 | 34 | 34 | 15 |
| 2026 | 9 | 9 | 4 |

## Offered-wage percentiles (403 filings)

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.

| p10 | p25 | Median | p75 | p90 |
|---|---|---|---|---|
| $48K | $56K | $69K | $85K | $115K |

## Top employers (of 79)

| Employer | Filings | Workers | Avg wage | BLS gap |
|---|---|---|---|---|
| [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | 157 | 157 | $68K | - |
| [VTCU Corp.](https://www.xh1b.org/org/vtcu-corp-f746d7c775) | 62 | 63 | $77K | - |
| [ON Semiconductor](https://www.xh1b.org/org/on-semiconductor-3eac04617c) | 38 | 57 | $68K | - |
| [Farm Bureau Mutual Insurance Company of Idaho](https://www.xh1b.org/org/farm-bureau-mutual-insurance-company-of--dc5078c31b) | 25 | 25 | $63K | - |
| [Semiconductor Components Industries, LLC](https://www.xh1b.org/org/semiconductor-components-industries-llc-a108bf45a6) | 19 | 42 | $81K | - |
| [Urtek](https://www.xh1b.org/org/urtek-8739ad16dc) | 11 | 11 | $86K | - |
| [Stratus Technology Services, LLC](https://www.xh1b.org/org/stratus-technology-services-llc-6f67578078) | 9 | 9 | $83K | - |
| [HTC Global Services Inc.](https://www.xh1b.org/org/htc-global-services-inc-c2b93d74e7) | 9 | 9 | $91K | - |
| [LHP Pocatello, LLC,](https://www.xh1b.org/org/lhp-pocatello-llc-804d84848f) | 7 | 7 | $345K | - |
| [Global Infotech Inc.](https://www.xh1b.org/org/global-infotech-inc-57723d3b70) | 6 | 6 | $78K | - |

## SOC breakdown (of 67)

| SOC | Title | Filings | Workers | Avg wage | Gap | Wage theft |
|---|---|---|---|---|---|---|
| 17-2071 | Electrical Engineers | 33 | 37 | $75K | -38% | $1.7M |
| 17-2141 | Mechanical Engineers | 12 | 31 | $64K | -38% | $1.3M |
| 17-2199 | Engineers, All Other | 19 | 19 | $59K | -52% | $1.2M |
| 17-2072 | Electronics Engineers, Except Computer | 11 | 30 | $90K | -31% | $1.1M |
| 29-1212 | Cardiologists | 5 | 5 | $380K | -23% | $684K |
| 15-1252 | Software Developers | 12 | 12 | $101K | -26% | $502K |
| 25-1071 | Health Specialties Teachers, Postsecondary | 21 | 21 | $102K | -5% | $361K |
| 25-1081 | Education Teachers, Postsecondary | 12 | 12 | $52K | -31% | $284K |

## WARN mass-layoff notices

| Employer | Laid off | City | Date |
|---|---|---|---|
| [LA Semiconductor LLC](https://www.xh1b.org/org/la-semiconductor-llc-a596c081ff) | 342 | Pocatello | 2026-04-10 |
| [Onsemi](https://www.xh1b.org/org/onsemi-67db4f113b) | 90 | Pocatello | 2024-09-27 |
| [ATCO](https://www.xh1b.org/org/atco-e5ca6834f4) | 158 | Pocatello | 2020-06-19 |
| [Safe Haven Health Care](https://www.xh1b.org/org/safe-haven-health-care-01068a57ed) | 117 | Pocatello | 2017-11-01 |
| [Mt. West Research Center](https://www.xh1b.org/org/mt-west-research-center-f1e163fa57) | 194 | Pocatello | 2016-12-31 |

## Medical workforce: Local supply vs H-1B

AHRF county-level data cross-referenced with H-1B medical LCAs. Comparisons are against the median US county.

| Metric | Value |
|---|---|
| MDs per 100k residents | 188 (US county median 75) |
| Active MDs (non-federal) | 170 |
| Nurse Practitioners per 100k | 142 (US county median 96) |
| County population | 90,400 |
| Primary Care HPSA designations | 3 |
| H-1B medical workers certified | 10 |
| H-1B medical median vs BLS | 58% of BLS ($208K vs $356K) |

## Immigration law firms (of 41)

| Firm | LCAs filed | Below prevailing |
|---|---|---|
| [Ware \| Immigration](https://www.xh1b.org/firm/Ware%20%7C%20Immigration) | 13 | 0% |
| [Jeffrey van Doren PLLC](https://www.xh1b.org/firm/JEFFREY%20VAN%20DOREN%20PLLC) | 6 | 0% |
| [Graham Adair, Inc.](https://www.xh1b.org/firm/Graham%20Adair%2C%20Inc.) | 5 | 0% |
| [Antonini and Cohen Immigration Law Group](https://www.xh1b.org/firm/Antonini%20and%20Cohen%20Immigration%20Law%20Group) | 5 | 0% |
| [Graham ADAIR, Inc.](https://www.xh1b.org/firm/GRAHAM%20ADAIR%2C%20INC.) | 5 | 0% |
| [Dewan & Associates, PLLC](https://www.xh1b.org/firm/Dewan%20%26%20Associates%2C%20PLLC) | 5 | 0% |
| [Bashyam Shah LLP](https://www.xh1b.org/firm/BASHYAM%20SHAH%20LLP) | 4 | 0% |
| [Fragomen, Del Rey, Bernsen & Loewy, LLP](https://www.xh1b.org/firm/Fragomen%2C%20Del%20Rey%2C%20Bernsen%20%26%20Loewy%2C%20LLP) | 4 | 0% |

## Federal contracts (of 168)

| Recipient | Agency | Action obligated | Date |
|---|---|---|---|
| [SUNDANCE CONSULTANTS, LLC](https://www.xh1b.org/org/sundance-consultants-llc-32bc38b095) | Department of Homeland Security | $4.7M | 2026-04-21 |
| [SUNDANCE CONSULTANTS, LLC](https://www.xh1b.org/org/sundance-consultants-llc-32bc38b095) | Department of Homeland Security | $4.0M | 2026-04-28 |
| [SUNDANCE CONSULTING, INC.](https://www.xh1b.org/org/sundance-consulting-inc-6d3364319f) | Department of the Interior | $1.3M | 2026-05-15 |
| [SUNDANCE CONSULTANTS, LLC](https://www.xh1b.org/org/sundance-consultants-llc-32bc38b095) | Department of the Interior | $729K | 2026-03-20 |
| [NEW DAY PRODUCTS, INC.](https://www.xh1b.org/org/new-day-products-inc-f313b724ac) | Department of Justice | $669K | 2026-07-16 |
| [SUNDANCE CONSULTING, INC.](https://www.xh1b.org/org/sundance-consulting-inc-6d3364319f) | Department of the Interior | $577K | 2026-02-20 |
| [SUNDANCE-EA ASSOCIATES II](https://www.xh1b.org/org/sundance-ea-associates-ii-867a39506e) | Department of Defense | $439K | 2026-01-22 |
| [SUNDANCE CONSULTANTS, LLC](https://www.xh1b.org/org/sundance-consultants-llc-32bc38b095) | Department of the Interior | $430K | 2026-06-15 |

## Recent LCA filings (latest 10 of 472)

| Case number | Employer | Job title | Wage | Decision |
|---|---|---|---|---|
| [I-200-26065-685182](https://www.xh1b.org/lca/I-200-26065-685182) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Associate Director for Strategic Enrollment Analysis | $80K | 2026-03-13 |
| [I-200-26063-679103](https://www.xh1b.org/lca/I-200-26063-679103) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Assistant Professor | $130K | 2026-03-11 |
| [I-200-26056-663262](https://www.xh1b.org/lca/I-200-26056-663262) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Assistant Professor | $100K | 2026-03-04 |
| [I-200-26046-642256](https://www.xh1b.org/lca/I-200-26046-642256) | [VTCU Corporation](https://www.xh1b.org/org/vtcu-corp-f746d7c775) | Senior Manager of Mechanical Engineering & Development | $200K | 2026-02-23 |
| [I-200-26044-639943](https://www.xh1b.org/lca/I-200-26044-639943) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Assistant Professor | $62K | 2026-02-23 |
| [I-200-26034-617842](https://www.xh1b.org/lca/I-200-26034-617842) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Assistant Professor | $68K | 2026-02-10 |
| [I-200-26034-617066](https://www.xh1b.org/lca/I-200-26034-617066) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Assistant Professor | $69K | 2026-02-10 |
| [I-200-26034-617647](https://www.xh1b.org/lca/I-200-26034-617647) | [Metis Foundation](https://www.xh1b.org/org/metis-foundation-55001c7fd8) | Associate Scientist | $74K | 2026-02-10 |
| [I-200-26033-613690](https://www.xh1b.org/lca/I-200-26033-613690) | [LHP Pocatello, LLC,](https://www.xh1b.org/org/lhp-pocatello-llc-804d84848f) | Physician (Interventional Cardiologist) | $600K | 2026-02-09 |
| [I-200-23136-026213](https://www.xh1b.org/lca/I-200-23136-026213) | [Idaho State University](https://www.xh1b.org/org/idaho-state-university-8ed1a90048) | Professor and Department Chair | $130K | 2026-01-13 |

## Community well-being (Bannock County)

CDC PLACES model-based small-area estimates (BRFSS survey year 2023); overdose mortality from NCHS. Values are local estimates, not survey counts. The gap column compares against the population-weighted average of all reporting areas for the same data year.

| Indicator | Data year | Local value | Gap vs benchmark |
|---|---|---|---|
| Food insecurity | 2023 | 14.4% | 0.8 points below U.S. |
| Households on SNAP | 2023 | 9.9% | 1.9 points below U.S. |
| Frequent mental distress | 2023 | 17.0% | 1.0 points above U.S. |
| Adult smoking | 2023 | 12.9% | 0.8 points above U.S. |
| Drug overdose deaths | 2021 | 38.6 | 6.4 above U.S. |

## More

- Full page (charts, tables, interactive): https://www.xh1b.org/county/16005
- JSON API: https://www.xh1b.org/api/county-lcas?fips=16005
- JSON API: https://www.xh1b.org/api/county-employers?fips=16005
- JSON API: https://www.xh1b.org/api/county-soc?fips=16005


## References

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-lca-data"></a>

1. Dataset documentation · DOL OFLC. [LCA public disclosure record layout (FY2026 Q3)](https://www.dol.gov/sites/dolgov/files/ETA/oflc/pdfs/FY26Q3/LCA_Record_Layout_FY2026_Q3.pdf). Pages 1–4: application, DOL outcome and dates, requested positions, employer, representatives, worksites and pay units. This 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.

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-bls-data"></a>

2. Dataset documentation · BLS. [OEWS technical notes (May 2025)](https://www.bls.gov/oes/2025/may/oes_tec.htm). Scope of the survey; occupational coding; concepts and estimation methodology. Documents 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.

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-dataset-warn"></a>
<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-calculation-method"></a>
<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-indicators-method"></a>

3. XH1B method or registry · XH1B. [WARN Notices (mass layoffs): source registry; Calculation and Matching Methods; Reading Public Records and Derived Indicators](https://www.xh1b.org/data-sources). Source registry entry: warn; Filing units, annualization, weighting, wage comparisons, and inference limits; Reading records: units, source coverage, wage gaps, entity links, and inference limits. XH1B 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.

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-dataset-federal_contracts"></a>

4. Dataset documentation · USAspending / U.S. Treasury. [Federal Spending Guide: contract transactions](https://www.usaspending.gov/data/Federal-Spending-Guide.pdf#page=9). Pages 3, 5, 9 and 17: transactions, amount fields and recipient identifiers. Contract downloads contain prime award transactions. XH1B’s use of recipient identifiers for employer links is its own processing step. Checked 2026-10-18.

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-displacement-method"></a>

5. XH1B method or registry · XH1B. [Displacement Model and Assumptions](https://www.xh1b.org/displacement). Eligibility, requested-position weighting, scopes, WARN matching, and counting limits. Model outputs are estimates. A matched layoff notice does not prove that an H-1B worker replaced a laid-off worker.

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-downstream-method"></a>

6. XH1B method or registry · XH1B. [Downstream Research and Methods](https://www.xh1b.org/downstream#downstream-methods). Study populations, parameter bounds, baselines, and expected outcomes; linked model card.

<a id="reference-data-lca-data-bls-data-dataset-warn-dataset-federal_contracts-calculation-method-indicators-method-displacement-method-downstream-method-ahrf-data-ahrf-data"></a>

7. Dataset documentation · HRSA. [Area Health Resources Files: 2024–2025 technical documentation](https://data.hrsa.gov/DataDownload/AHRF/AHRF_USER_TECH_2024-2025.zip). County User Guide: physicians, Table 10 NPI professions, population estimates and missing values; Technical Documentation: variable years and sources. Clinician 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.