# ZIP 14068: H-1B profile
> ZIP profile: https://www.xh1b.org/zip/14068 · [county](https://www.xh1b.org/county/36029)
Employers in 14068 (NY) submitted 673 certified H-1B applications requesting 718 workers across 104 companies. The median offered wage is $79,020/yr. The largest filers are Citibank, N.A., Citigroup Global Markets Inc. and GGK TECHNOLOGIES, Inc.. The displacement model assigns 1.2K worker-equivalent exposures to these filings. Separately, 319 layoffs appear in matched WARN notices.
| Metric | Value |
|---|---|
| H-1B filings | 673 |
| Workers requested | 718 |
| US workers displaced (modeled) | 1,199 |
| Distinct employers | 104 |
| H-1B filings with offered wage data | 590 |
| Filings below prevailing wage (share with offered wage data) | 0% |
| Wage gap vs BLS | -13% |
| Metric | Value |
|---|---|
| Average offered wage | $87K |
| Average prevailing wage | $73K |
| Average BLS market wage | $100K |
Headline filing and employer counts use certified H-1B records. The below-prevailing share uses filings with offered wage data as its denominator. Offered, prevailing and BLS averages use independently available values; their populations can differ. The BLS reference averages national occupation medians linked to certified filings, using each occupation's latest available year. It is not a ZIP-wide market median. The employer list includes all LCA outcomes and visa classes; quality-flagged rows are excluded.
## Top employers (of 106)
| Employer | Filings | Workers | Avg wage |
|---|---|---|---|
| [Citibank, N.A.](https://www.xh1b.org/org/citibank-na-0aa6e9be12) | 228 | 228 | $89K |
| [Citigroup Global Markets Inc.](https://www.xh1b.org/org/citigroup-global-markets-inc-a2df086da7) | 61 | 61 | $78K |
| [Centene Management Company, LLC](https://www.xh1b.org/org/centene-management-company-llc-367768d062) | 33 | 33 | $108K |
| [NEW York State Catholic Health Plan Inc.](https://www.xh1b.org/org/new-york-state-catholic-health-plan-inc-ff3edaf085) | 32 | 32 | $75K |
| [GGK TECHNOLOGIES, Inc.](https://www.xh1b.org/org/ggk-technologies-inc-70d7f1a72b) | 31 | 38 | $90K |
| [BlackRock Financial Management, Inc.](https://www.xh1b.org/org/blackrock-financial-management-inc-422d2ad61d) | 29 | 29 | $78K |
| [Tata Consultancy Services Limited](https://www.xh1b.org/org/tata-consultancy-services-limited-25762f048c) | 19 | 29 | $62K |
| [London Stock Exchange Group Holdings, Inc.](https://www.xh1b.org/org/london-stock-exchange-group-holdings-inc-d331f65154) | 16 | 16 | $65K |
## SOC breakdown (of 37)
| SOC | Title | Filings | Workers | Avg wage |
|---|---|---|---|---|
| 15-1132 | Software Developers, Applications | 110 | 129 | $87K |
| 13-2099 | Financial Specialists, All Other | 78 | 78 | $74K |
| 15-1121 | Computer Systems Analysts | 66 | 68 | $76K |
| 13-2051 | Financial and Investment Analysts | 51 | 65 | $74K |
| 15-1199 | Computer Occupations, All Other | 43 | 43 | $81K |
| 15-1252 | Software Developers | 33 | 33 | $119K |
| 15-1133 | Software Developers, Systems Software | 23 | 23 | $87K |
| 15-2051 | Data Scientists | 22 | 22 | $103K |
## Recent LCA filings (latest 10 of 693)
| Case number | Employer | Job title | Wage | Decision | Status |
|---|---|---|---|---|---|
| [I-200-26070-696885](https://www.xh1b.org/lca/I-200-26070-696885) | [Citibank, N.A.](https://www.xh1b.org/org/citibank-na-0aa6e9be12) | Data Governance Foundation Senior Lead Analyst | $147K | 2026-03-18 | Certified |
| [I-200-26048-645734](https://www.xh1b.org/lca/I-200-26048-645734) | [Government Employee Insurance Company (GEICO)](https://www.xh1b.org/org/government-employee-insurance-company-ge-766523b94f) | Engineer II | $147K | 2026-02-24 | Certified |
| [I-200-26042-633770](https://www.xh1b.org/lca/I-200-26042-633770) | [Government Employee Insurance Company (GEICO)](https://www.xh1b.org/org/government-employee-insurance-company-ge-766523b94f) | Engineer II | $147K | 2026-02-19 | Certified |
| [I-200-26035-618633](https://www.xh1b.org/lca/I-200-26035-618633) | [DONATO TECHNOLOGIES INC](https://www.xh1b.org/org/donato-technologies-inc-a5abde5f1d) | Network Engineer | $108K | 2026-02-11 | Certified |
| [I-200-26028-598321](https://www.xh1b.org/lca/I-200-26028-598321) | [M&T Bank](https://www.xh1b.org/org/mt-bank-4c73ad00a4) | Senior Software Engineer | $125K | 2026-02-04 | Certified |
| [I-200-26021-578419](https://www.xh1b.org/lca/I-200-26021-578419) | [Citibank, N.A.](https://www.xh1b.org/org/citibank-na-0aa6e9be12) | Risk Reporting Senior Analyst | $103K | 2026-01-28 | Certified |
| [I-200-26006-537820](https://www.xh1b.org/lca/I-200-26006-537820) | [Centene Management Company, LLC](https://www.xh1b.org/org/centene-management-company-llc-367768d062) | Senior Application Development Engineer | $122K | 2026-01-13 | Certified |
| [I-200-25363-514066](https://www.xh1b.org/lca/I-200-25363-514066) | [Axelon Services Corporation](https://www.xh1b.org/org/axelon-services-corporation-1b5674d9ce) | Business Office Management Associate | $158K | 2026-01-06 | Certified |
| [I-200-25343-469979](https://www.xh1b.org/lca/I-200-25343-469979) | [Federal Express Corporation](https://www.xh1b.org/org/federal-express-corporation-3717cfe136) | Software Engineer III | $111K | 2025-12-16 | Certified |
| [I-200-25338-456198](https://www.xh1b.org/lca/I-200-25338-456198) | [Columbus McKinnon Corporation](https://www.xh1b.org/org/columbus-mckinnon-corporation-92d216ea4c) | Supervisor, HR Technology | $102K | 2025-12-10 | Certified |
## WARN mass-layoff notices
| Employer | Laid off | City | Date |
|---|---|---|---|
| [First Transit, Inc. a subsidiary of Transdev, North America Inc.](https://www.xh1b.org/org/first-transit-inc-a-subsidiary-of-transd-9408da8505) | 65 | - | 2024-06-30 |
| [Cygnus Home Service, LLC, d/b/a Yelloh](https://www.xh1b.org/org/cygnus-home-service-llc-dba-yelloh-ab8089187e) | 15 | - | 2024-05-28 |
| [University Inn & Conference Center, Inc. d/b/a Ramada Hotel & Conference Center, Inc.](https://www.xh1b.org/org/university-inn-conference-center-inc-dba-332c81d3aa) | 72 | - | 2016-09-30 |
| [Menorah Licensed Homecare](https://www.xh1b.org/org/menorah-licensed-homecare-604fbf3c34) | 63 | - | 2015-09-15 |
| [NCO Financial Systems, Inc.](https://www.xh1b.org/org/nco-financial-systems-inc-643f39c75d) | 104 | - | 2013-10-29 |
_ZIP-level displacement uses the LCA formula only (no WARN component)._
## Modeled consequence estimates
**Conditional impacts associated with modeled displacement**
These are conditional population estimates scaled from ZIP 14068's current modeled displacement count. They are not observed outcomes, a prediction about any person, or evidence that this entity caused displacement.
[Explore ZIP 14068’s scenario: Earnings · children · health · adjust the worker count](https://www.xh1b.org/downstream?workers=1199.226&entity=ZIP%2014068#downstream-explorer)
| Metric | Value |
|---|---|
| Exposure method version | 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` |
| Outcome | Applicability | Estimate | Range |
|---|---|---|---|
| Excess deaths over 20 years | Illustrative reference calculation · population applicability is not established | 34.4882154269 | 13.5060257936 to 60.075951968 |
| Child lifetime earnings lost | Illustrative reference calculation · population applicability is not established | $574,302,191.69 | $149,169,400.44 to $969,601,102.85 |
20-year reference scenario: high-seniority male displacement effect. This is not an expected count for an unknown population.
Source-profile mortality point (deaths): 34.4882154269
No sustained excess from year 7 (deaths): 24.6121368613
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: `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 34.4882154269 (range 13.5060257936 to 60.075951968); child lifetime earnings lost $574,302,191.69 (range $149,169,400.44 to $969,601,102.85);
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": 1199.226,
"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": 34.48821542687024,
"low": 13.506025793625408,
"high": 60.07595196802001,
"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": 34.48821542687024,
"low": 13.506025793625408,
"high": 60.07595196802001,
"evidence_status": "source_profile_with_transport_assumptions",
"citations": [
"sullivan2009"
]
},
"no_sustained_excess": {
"point": 24.61213686128502,
"low": 11.021924710833115,
"high": 42.40616121488929,
"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": 9.876078565585223,
"structural_point_range": {
"low": 24.61213686128502,
"high": 34.48821542687024,
"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": 574302191.6880866,
"low": 149169400.43846416,
"high": 969601102.8500162,
"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 v1.54 · model v1.54+engine0.4.1+d84162591c94d06c8148c4834ae705ff3f9a015c29955d95d26749834cd136ed+national-reference1
## Community well-being (ZIP 14068)
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 | 7.7% | 9.4 points below All ZIPs |
| Adults receiving SNAP | 2023 | 6.4% | 7.9 points below All ZIPs |
| Frequent mental distress | 2023 | 12.4% | 4.4 points below All ZIPs |
| Adult smoking | 2023 | 8.2% | 5.0 points below All ZIPs |
## More
- Full page (charts, tables, interactive): https://www.xh1b.org/zip/14068
- JSON API: https://www.xh1b.org/api/zip-lcas?zip=14068
- JSON API: https://www.xh1b.org/api/zip-employers?zip=14068
- JSON API: https://www.xh1b.org/api/zip-soc?zip=14068
## References
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.
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.
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.
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.
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.
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.