# Downstream Downstream is an open research model that connects published studies to estimate the effects of worker displacement on income, health, family stability, and children’s future earnings. Adjust a scenario and trace each result through its evidence, assumptions, and math. ## Explore this displacement exposure: 1000 worker equivalents Sitewide impact uses a shared one-worker national reference multiplied by modeled displacement exposure. Dollar totals and expected event counts scale linearly. Relative study effects remain unchanged. These conditional estimates exclude exposure uncertainty and use two children per worker and a 20-year high-seniority male mortality reference. Illustrative reference calculations. Population applicability is not established. These figures are ineligible for public headlines. | Outcome | Estimate | Parameter support range | Applicability | |---|---|---|---| | Excess deaths over 20 years | 28.76 | 11.26 to 50.1 | Illustrative reference calculation · population applicability is not established | | Child lifetime earnings lost | $478,894,050 | $124,388,060 to $808,522,420 | Illustrative reference calculation · population applicability is not established | Input content SHA-256: 65625244b6014b6429cf6d6fd7f3f525fdafb6dce287e996ad1a82b5db273d17. Bundle SHA-256: 99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153. Adapter SHA-256: 605700852536cef19bdae955f055979ab182f352c107882e7b46fb6cccd3e68e. Source-profile mortality point (deaths): 28.7587289025 No sustained excess from year 7 (deaths): 20.5233516129 Declared structural comparison; not a confidence interval or a model probability. Outcome statistics use the displayed exposure. Baselines, coefficients, annual family schedules and component records retain their source normalization. ```json { "displayed_workers": 1000, "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": 28.758728902534, "low": 11.262285668944308, "high": 50.095604971890204, "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": 28.758728902534, "low": 11.262285668944308, "high": 50.095604971890204, "evidence_status": "source_profile_with_transport_assumptions", "citations": [ "sullivan2009" ] }, "no_sustained_excess": { "point": 20.52335161286114, "low": 9.190865367189433, "high": 35.36127570190213, "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": 8.235377289672858, "structural_point_range": { "low": 20.52335161286114, "high": 28.758728902534, "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": 478894046.40000015, "low": 124388064.00000012, "high": 808522416.0000001, "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." } }, "blocked": [ "local_service_jobs_lost: requires a documented net local loss of tradable jobs; worker displacement alone is not this exposure" ] } ``` ## Investigate all outcomes Cohort totals scale with the worker input. Study rates and effects keep their source populations. Structural projections connect studies through stated assumptions. Open any result to inspect the math. | Outcome | Displayed effect | Source result | Meaning | Calculation | Inputs and units | Study population | Source studies | Citation check | |---|---|---|---|---|---|---|---|---| | Child lifetime earnings lost | $478,894,050 | $478,894,046.40 | The model applies the child earnings effect to two children per worker and the US male lifetime earnings benchmark. This is a conditional total, not an observed loss. | 1,000 × 2 × (1 − 0.9076) × $2,591,418.00 = $478,894,046.40 | Two children per worker. SSA male lifetime earnings benchmark in 2024 dollars. | Canada 39k father-son pairs firm closures | oreopoulos2008 | Model conversion: The 0.9076 factor exponentiates the −0.097 log-earnings coefficient for sons of displaced Canadian fathers. A lifetime dollar loss also requires the model’s duration and earnings baseline. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.037). | | Parents’ income lost · layoff year | Estimate withdrawn | Estimate withdrawn | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: Hilger’s abstract describes large family-income losses. The original pinned loss, standard error and annual-income baseline could not be checked against the original table. The amount is excluded from public estimates. Range: Exact source interval and denominator unverified. | | Expected excess deaths · 20 years | 28.76 | 28.76 | The model compares 20-year survival with and without job loss. The difference gives expected additional deaths. It does not count observed deaths or establish that this employer caused them. | 1,000 × (S₀ − S₁) = 28.7587289; S₀ = (1 − m)²⁰; S₁ = ∏ᵧ(1 − qᵧ); qᵧ = rᵧm / (1 − m + rᵧm) | CDC male age 45–54 annual rate: 0.004944. Annual probability m = 1 − exp(−0.004944) = 0.004931798548. Odds ratios rᵧ: 2.6696 in year 1; 1.9838 in year 2; 1.7316 in years 3–4; 1.2712 in years 5–6; 1.135 in years 7–20. | US high-seniority displaced men born 1930-1959 | sullivan2009 | Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. | | Workers’ long-run earnings | −20% | 80% | Workers retain 80% of comparison earnings in the model. This row shows the earnings loss, not the share of workers who lose a job. | 0.80 × comparison earnings | Long-run earnings relative to the same worker without displacement. No worker lifetime-dollar total uses this coefficient. | US high-tenure displaced men | jacobson1993; oreopoulos2008; davis2011 | Model assumption: The 0.80 retained-earnings factor is a cross-study selection. Jacobson reports about 25% losses; Davis and von Wachter describe losses of 15–20% after 20 years. These are different cohorts and follow-up periods. Range: Cross-study model band, not a confidence interval. | | Children’s adult earnings | −9.2% | 90.76% | Children retain 90.76% of comparison adult earnings. This direct study estimate also supplies the child lifetime-dollar calculation above. | 0.9076 × comparison earnings; loss = 1 − 0.9076 = 9.24% | Direct displacement-to-child estimate. The model does not multiply it by the worker earnings loss. | Canada 39k father-son pairs firm closures | oreopoulos2008 | Model conversion: The 0.9076 factor exponentiates the −0.097 log-earnings coefficient for sons of displaced Canadian fathers. A lifetime dollar loss also requires the model’s duration and earnings baseline. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.037). | | Lifetime earnings lost per grandchild · structural projection | $131,700 | $131,695.86 | The model projects part of the child earnings loss into the next generation. The amount is for one grandchild. It is not a total for this employer. | g₂ = 1 − 0.55 × (1 − 0.9076) = 0.94918; loss = (1 − g₂) × $2,591,418.00 | One descendant. The same national earnings benchmark applies. Descendant counts are not assumed. | US IGE literature | solon1992; corak2013; chetty2014 | Model conversion: The 0.9076 factor exponentiates the −0.097 log-earnings coefficient for sons of displaced Canadian fathers. A lifetime dollar loss also requires the model’s duration and earnings baseline. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.037). Model assumption: The 0.55 factor is a structural persistence assumption. Solon and Corak provide intergenerational-earnings context; Chetty’s baseline IGE is 0.344, distinct from its rank–rank slope. These associations do not measure transmission of a displacement-induced earnings change. Range: Selected literature band, not a confidence interval. | | Lifetime earnings lost per great-grandchild · structural projection | Estimate withdrawn | Estimate withdrawn | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | No verified population and outcome match for this numerical input. | | Model conversion: The 0.9076 factor exponentiates the −0.097 log-earnings coefficient for sons of displaced Canadian fathers. A lifetime dollar loss also requires the model’s duration and earnings baseline. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.037). Model assumption: The 0.55 factor is a structural persistence assumption. Solon and Corak provide intergenerational-earnings context; Chetty’s baseline IGE is 0.344, distinct from its rank–rank slope. These associations do not measure transmission of a displacement-induced earnings change. Range: Selected literature band, not a confidence interval. Source unverified · estimate withdrawn: The 0.55 factor remains a model assumption. Lindahl documents multigeneration persistence but does not establish this specific earnings-gap transmission rule. The Adermon source record has not been identified. Range: Assumed persistence band; source support unresolved. | | Children enrolled in college · ages 18–22 | Estimate withdrawn | Estimate withdrawn | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: Hilger’s abstract describes a small college-enrollment response. The original pinned coefficient, standard error and enrollment baseline could not be checked against the original table. The unsupported conversion is excluded from public estimates. Range: Exact source interval and denominator unverified. | | Children who repeat a school grade | +14.7% | 6.31% | The share repeating a grade rises from 5.5% to 6.31%, an increase of 0.81 percentage points. The study measures children ages 5–19, at least one year after job loss. | 5.5% × 1.1473 = 6.31%; change = 0.81 percentage points | Model denominator 0.055: the source’s sample average, not a control-group mean. The relative probability is a model conversion. | US children 5-19 (SIPP 1996/2001/2004 panels), head-of-household involuntary job loss (fired/discharged, employer sold/bankrupt, slack work), child fixed effects, N=167,449 child-years / 2,170 displaced children / 1,196 job losses | stevens2011 | Model conversion: The model divides the 0.0081 grade-repetition probability effect by the 0.055 sample average. This is a relative-probability conversion, not an estimated hazard ratio or a measured test-score effect. Range: Source coefficient ± 1.96 standard errors, divided by a fixed sample average. | | Children with no grade-9 results | Estimate withdrawn | Estimate withdrawn | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: The 0.0054 effect (SE 0.0027) is verified. The 0.0785 denominator is labeled “Constant” in a controlled regression, not a verified control-group mean. The withdrawn ratio relies on that unsupported baseline interpretation. Range: Coefficient uncertainty scaled by an unsupported denominator; not an estimated hazard ratio. | | Children finishing high school by 19 | −4.9% | 72.3% | The completion rate falls from 76% to 72.3%, a decrease of 3.7 percentage points. The study’s uncertainty range also allows no decrease. | 0.76 + (-0.037) = 0.723 | Study control mean. Children of displaced single mothers. This rate does not apply to all assumed children. | children of single mothers, US NLSY79 (NLSY79 women's children), MATERNAL job displacement at child age 0-17 (PSM kernel TT); outcome = HS completion by age 19, control mean 0.760 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is −0.037 for high-school completion by age 19; its interval crosses zero. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.022). | | Children ever attending college by 21–22 | −14.8% | 36.4% | The share ever attending college falls from 42.7% to 36.4%, a decrease of 6.3 percentage points. This measures any attendance by this age, not current enrollment. | 0.427 + (-0.063) = 0.364 | Study control mean. Children of displaced single mothers. This rate does not apply to all assumed children. | same scope as the hs_completion row; outcome = some college attendance by age 21-22, control mean 0.427 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is −0.063 for college attendance in young adulthood. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.023). | | Children earning a bachelor’s degree by 25 | −21.3% | 13.3% | The completion rate falls from 16.9% to 13.3%, a decrease of 3.6 percentage points. This study concerns children of single mothers. | 0.169 + (-0.036) = 0.133 | Study control mean. Children of displaced single mothers. This rate does not apply to all assumed children. | same scope as the hs_completion row; outcome = college completion (BA) by age 25, control mean 0.169 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is −0.036 for college completion in young adulthood. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.016). | | Adult children’s depression symptoms | +0.025 score | 0.233 | The average symptom score rises from 0.208 to 0.233 on a 0–1 scale. Higher scores mean more symptoms. This study concerns children of single mothers. It does not measure the share diagnosed with depression. | 0.208 + (0.025) = 0.233 | Study control mean on a 0–1 CESD symptom scale. This is an index, not a probability. | same scope as the hs_completion row; outcome = CESD 7-item depressive-symptom index (0-1) at ages 25-29, control mean 0.208 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is +0.025 on the 0–1 CESD index at ages 25–29, not a standard-deviation change. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.011). | | Babies’ birth weight | −4.6% | 95.41% of comparison birth weight | Birth weight is 4.59% lower in the source study. A birth-weight baseline and a matching infant population are needed to convert this to grams or birth counts. | Study coefficient = 0.9541; support = [0.912, 0.9981] | Birth-weight ratio. An infant cohort and birth-weight baseline are needed for grams or birth counts. | US PSID children 1985+, husband displacement, mother fixed effects | lindo2011 | Model conversion: The factor exponentiates the −0.047 log-birth-weight coefficient in IZA 5213. The sample includes births after displacement, including exposure years before birth; it is not an estimate restricted to in-utero job loss. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.023). | | Marriages that end | +11% | 1.11 × comparison rate | Marriages are 11% more likely to dissolve over the study follow-up. This is a relative increase, not 11 extra divorces per 100 marriages. | Study coefficient = 1.11; support = [1.05, 1.25] | Married-worker study effect. The selected input does not specify a married cohort or a compatible dissolution baseline. | married displaced workers | rege2007; charles2004 | Model assumption: The Norwegian study reports an 11% higher probability of dissolution by 2003, not an estimated hazard ratio. Charles and Stephens find a divorce response to layoffs, with no significant response to plant closings. Range: Selected model band across contexts, not a reported confidence interval. | | Death rate · heart & circulatory disease | +54% | 1.54 × comparison hazard | The death hazard is 54% higher than in the comparison group. Hazard means the death rate among people still alive. This is not a death count or a 54% chance of dying. | Study coefficient = 1.54; support = [1.29, 1.83] | Cause-specific study hazard ratio. A hazard ratio is not a probability. No cause-specific count is added to all-cause deaths. | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | browningheinesen2012 | Source estimate: The inspected 2011 report gives a cumulative hazard ratio over years 1–4 for Danish men with strong labor-market attachment after plant closure. It is not an annual hazard or an odds ratio. Range: Reported 95% confidence interval for the specified cause and follow-up window. | | Death rate · alcohol-related causes | +62% | 1.62 × comparison hazard | The alcohol-related death hazard is 62% higher than in the comparison group. Hazard means the death rate among people still alive. These deaths are not added to the all-cause total above. | Study coefficient = 1.62; support = [1.09, 2.41] | Cause-specific study hazard ratio. No cause-specific count is added to all-cause deaths. | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | browningheinesen2012 | Source estimate: The inspected 2011 report gives a cumulative hazard ratio over years 1–4 for Danish men with strong labor-market attachment after plant closure. It is not an annual hazard or an odds ratio. Range: Reported 95% confidence interval for the specified cause and follow-up window. | | Death rate · injuries & suicide | +53% | 1.53 × comparison hazard | External causes include injuries, suicide and traffic deaths. The death hazard is 53% higher than in the comparison group. These deaths are not added to the all-cause total above. | Study coefficient = 1.53; support = [1.15, 2.04] | Cause-specific study hazard ratio. No cause-specific count is added to all-cause deaths. | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | browningheinesen2012 | Source estimate: The inspected 2011 report gives a cumulative hazard ratio over years 1–4 for Danish men with strong labor-market attachment after plant closure. It is not an annual hazard or an odds ratio. Range: Reported 95% confidence interval for the specified cause and follow-up window. | | Partners’ mental-health scores | −0.194 SD | -0.194 SD change | Partners’ mental-health scores fall about 11 months after job loss. Lower scores mean worse mental health. SD is a score-spread unit, not a percentage of partners. | Study coefficient = -0.194; support = [-0.327, -0.061] | MCS score change in standard-deviation units. Lower scores mean worse mental health. | spouses of displaced workers, German couples (SOEP 2002-2010), 109 displaced-worker couples vs >14,000 entropy-balanced controls; MCS normed mean 50 SD 10 | marcus2013 | Model conversion: Table 3’s spouse mental-health effect is −1.94 MCS points (SE 0.68). The source normalizes the score to SD 10; division by 10 gives −0.194 SD. The follow-up is about one year after unemployment following closure. Range: Coefficient ± 1.96 standard errors, divided by 10. | | Children’s mathematics grades · grade 9 | −0.0206 SD | -0.0206 SD change | Teacher-assessed mathematics grades fall after a parent’s job loss. SD means standard deviation, a unit of score spread. This is a score change, not a percentage of children. | Study coefficient = -0.0206; support = [-0.0402, -0.001] | Grade-9 mathematics score. The estimate is conditional on taking the exam. | children exposed to parental plant closure age 0-16 (average across exposure stages), Denmark, conditional on taking grade-9 exams; mathematics | bingley2026 | Source estimate: Table 4 reports −0.0206 SD (SE 0.0100) for teacher-assessed mathematics grades in the Danish sample. The separate standardized-test estimate is smaller and not significant. These outcomes are not interchangeable. Range: Coefficient ± 1.96 standard errors. | | Distress among unemployed adults | Estimate withdrawn | Estimate withdrawn | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The publisher’s text describes d = 0.51. The exact outlier-excluded table and stored 0.47–0.54 interval could not be checked. The abstract’s overall d = 0.54 is a different summary. Range: Exact source interval unverified. | | Couples having a baby · layoff year | −0.5 percentage points | -0.5 percentage-point change | The annual probability of a birth falls by 0.5 percentage points after a woman’s job loss. This study effect does not apply to male job loss. | Study coefficient = -0.005; support = [-0.0089, -0.0011] | Female-displacement study. A baseline birth probability and an eligible couple cohort are needed for counts. | couples, Finnish FLEED registers, WOMEN displaced by plant closures (base years 1991-1993) vs matched non-displaced; outcome = couple's probability of a birth in the year | huttunenkellokumpi2016 | Source estimate: Table 3’s female plant-closure coefficient is −0.005 (SE 0.002), a 0.5 percentage-point probability change. The Finnish sample is women aged 20–40; it is not a change in total births for every worker. Range: Coefficient ± 1.96 standard errors. | | Children reported with depression or anxiety | +0.8 percentage points | 0.8 percentage-point change | The reported share rises by 0.8 percentage points. That is an additional 0.8 reports per 100 children in the study population, not a 0.8% relative increase. | Study coefficient = 0.008; support = [0.0002, 0.0158] | Paternal job-loss study. A compatible baseline and child cohort are needed for counts. | children ages 6-17, US MEPS, PATERNAL job loss (tenured-father sample, >=1y tenure), individual-FE LPM; outcome = child depression/anxiety report | schallerzerpa2019 | Source estimate: Table 2’s probability effect is +0.008: 0.8 percentage points, not 0.008 percentage points. The inspected MEPS sample is children aged six and older with a tenured displaced father. Range: Coefficient ± 1.96 standard errors (SE 0.004). | | Grandchildren’s cognitive scores · structural projection | −0.007828 SD | -0.007828 SD | The model links Danish child mathematics grades to a Norwegian father–son IQ relationship. The tests differ. This is a projection, not a measured job-loss effect on grandchildren. | -0.0206 × 0.38 = -0.007828 SD | A structural link from Danish mathematics scores to a Norwegian father–son IQ persistence slope. The measures differ. | Norway male conscripts (IQ at age 18, father-son) | blackdevereuxsalvanes2009 | Source estimate: Table 4 reports −0.0206 SD (SE 0.0100) for teacher-assessed mathematics grades in the Danish sample. The separate standardized-test estimate is smaller and not significant. These outcomes are not interchangeable. Range: Coefficient ± 1.96 standard errors. Model assumption: The source reports a 0.38 father–son IQ correlation in Norway. The authors give it no causal interpretation. Applying it to an induced achievement change is a structural assumption, not a measured intergenerational treatment effect. Range: Selected literature band, not a confidence interval. | | Adult earnings · through lower birth weight · structural projection | −0.5% | 99.53% of comparison earnings | The model links lower birth weight to later earnings. This separate projection is not added to the direct child earnings loss. It needs a matching infant population to give a total. | 0.9541 ^ (0.1) = 0.9953123424 | Structural dose-response connection. It stays separate from the direct child earnings estimate and all-cause mortality total. | Norway twin sample, twin fixed effects on ln(birth weight), cohorts 1967-1988 (military conscription + earnings registries); IZA DP 1864 Table 5 'Ln(Earnings) FT', all-twins FE column | black2007 | Model conversion: The factor exponentiates the −0.047 log-birth-weight coefficient in IZA 5213. The sample includes births after displacement, including exposure years before birth; it is not an estimate restricted to in-utero job loss. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.023). Source estimate: The 2005 working paper’s Table 5 reports 0.10 (SE 0.04) for log full-time earnings on log birth weight in a twin fixed-effects sample. This is not a causal bridge from parental displacement to adult earnings. Range: Coefficient ± 1.96 standard errors. | | Adult diabetes odds · through lower birth weight · structural projection | +4.6% | 1.046322 × comparison | The model links lower birth weight to adult type-2 diabetes odds. Odds compare people with and without an outcome. This is not a disease probability or a count of future cases. | 0.9541 ^ (-0.9637) = 1.046322014 | Structural dose-response connection. It stays separate from the direct child earnings estimate and all-cause mortality total. | adults, pooled random-effects dose-response, 32 studies / ~7.6M participants (Knop et al. JAHA 2018, 7(23):e008870, OR per +1 kg birth weight; read via PMC6405546 full text) | knop2018 | Model conversion: The factor exponentiates the −0.047 log-birth-weight coefficient in IZA 5213. The sample includes births after displacement, including exposure years before birth; it is not an estimate restricted to in-utero job loss. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.023). Model conversion: The meta-analysis reports odds ratio 0.78 [0.70, 0.87] per 1 kg. The model converts this using ln(OR) / ln(4.4/3.4). The 3.4 kg baseline and constant elasticity are assumptions; odds are not hazards. Range: Transformed reported 95% odds-ratio limits, conditional on the model’s assumed baseline. | | Adult heart-disease odds · through lower birth weight · structural projection | +3.3% | 1.033408 × comparison | The model links lower birth weight to adult cardiovascular disease odds. This is not a disease probability or a count of future cases. It is not added to the all-cause death total. | 0.9541 ^ (-0.6994) = 1.0334085 | Structural dose-response connection. It stays separate from the direct child earnings estimate and all-cause mortality total. | adults, pooled random-effects dose-response, 33 studies / ~5.9M participants (same source as the T2D row; OR per +1 kg birth weight) | knop2018 | Model conversion: The factor exponentiates the −0.047 log-birth-weight coefficient in IZA 5213. The sample includes births after displacement, including exposure years before birth; it is not an estimate restricted to in-utero job loss. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.023). Model conversion: The meta-analysis reports 16.5% lower odds, with a printed rounded odds ratio of 0.84 [0.81, 0.86] per 1 kg. The model converts this using ln(OR) / ln(4.4/3.4). The 3.4 kg baseline and constant elasticity are assumptions; odds are not hazards. Range: Transformed reported 95% odds-ratio limits, conditional on the model’s assumed baseline. | | Adult daughters’ marriage breakdown · structural projection | 1.006418× hazard | 1.006418 × comparison hazard | The model projects a small increase in daughters’ marriage-disruption rate through additional parental separations. Hazard means the rate of breakdown among marriages still intact. This is not a lifetime divorce probability. No estimate is available for sons. | s′ = 1 − (1 − 0.069) ^ 1.11; r′ = 1 + (s′ − 0.069) × (1.88 − 1) | The model combines Norwegian parental dissolution data with a US association for white daughters. Only additional disrupted families transmit the gap. This is a relative hazard, not a divorce probability. A son-specific coefficient is not available. | US women (NSFG cycles I-III), white daughters who spent part of childhood with a divorced/separated/never-married parent vs two-parent families; proportional-hazard model of own marital disruption | rege2007; charles2004; mclanahanbumpass1988 | Model assumption: The Norwegian study reports an 11% higher probability of dissolution by 2003, not an estimated hazard ratio. Charles and Stephens find a divorce response to layoffs, with no significant response to plant closings. Range: Selected model band across contexts, not a reported confidence interval. Model assumption: The 0.069 value is the observed dissolution share among Norwegian couples with husbands at stable plants, from 1995 to 2003. The 0.072 endpoint is the closing-plant group’s observed mean, not an uncertainty limit. Range: Two observed cohort means; not a confidence interval or annual baseline. Model conversion: The inspected 1986 draft’s Appendix Table A1 gives 0.63 (SE 0.09) for white women in a background-adjusted proportional-hazard model. Parent absence includes divorce, separation, never-married parents and neither parent, not divorce alone. Range: Exponentiated coefficient ± 1.96 standard errors, rounded. | ### Complete parameter ledger Every link in the pinned model appears below. The citation check distinguishes reported estimates, model conversions, assumptions and unresolved support. Range definitions vary by parameter. A separate exposure or missing baseline prevents an absolute prediction. | Link | Calculation | Parameter support | Population | Studies | Citation check | |---|---|---|---|---|---| | displacement->worker_earnings | Outcome level = 0.8 × comparison level; relative loss = 1 − 0.8 | 0.75 – 0.85 | US high-tenure displaced men | jacobson1993;oreopoulos2008;davis2011 | Model assumption: The 0.80 retained-earnings factor is a cross-study selection. Jacobson reports about 25% losses; Davis and von Wachter describe losses of 15–20% after 20 years. These are different cohorts and follow-up periods. Range: Cross-study model band, not a confidence interval. | | earnings_shock->mortality_sustained | q = 1.1354m / (1 − m + 1.1354m); m = annual baseline probability | 1.0335 – 1.2474 | US high-seniority displaced men born 1930-1959 | sullivan2009 | Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. | | earnings_shock->mortality_peak | q = 2.6698m / (1 − m + 2.6698m); m = annual baseline probability | 2.1144 – 3.3711 | US high-seniority displaced men born 1930-1959 | sullivan2009 | Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. | | earnings_shock->mortality_offset_1 | q = 1.9838m / (1 − m + 1.9838m); m = annual baseline probability | 1.3697 – 2.8732 | US high-seniority displaced men born 1930-1959 | sullivan2009 | Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. | | earnings_shock->mortality_offsets_2_3 | q = 1.7315m / (1 − m + 1.7315m); m = annual baseline probability | 1.3238 – 2.2649 | US high-seniority displaced men born 1930-1959 | sullivan2009 | Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. | | earnings_shock->mortality_offsets_4_5 | q = 1.2712m / (1 − m + 1.2712m); m = annual baseline probability | 0.97 – 1.6661 | US high-seniority displaced men born 1930-1959 | sullivan2009 | Model conversion: The values exponentiate log-odds coefficients in Table 5, column 3 of the 2007 working paper. They are mortality odds ratios for high-seniority Pennsylvania men after mass layoffs. They do not isolate an earnings-loss mechanism. Range: Exponentiated coefficient ± 1.96 standard errors; source offsets and cohort apply. | | displacement->divorce_hazard | Outcome rate or hazard = 1.11 × its comparison rate or hazard; counts require a matching cohort and baseline | 1.05 – 1.25 | married displaced workers | rege2007;charles2004 | Model assumption: The Norwegian study reports an 11% higher probability of dissolution by 2003, not an estimated hazard ratio. Charles and Stephens find a divorce response to layoffs, with no significant response to plant closings. Range: Selected model band across contexts, not a reported confidence interval. | | displacement->child_earnings | Outcome level = 0.9076 × comparison level; relative loss = 1 − 0.9076 | 0.844 – 0.976 | Canada 39k father-son pairs firm closures | oreopoulos2008 | Model conversion: The 0.9076 factor exponentiates the −0.097 log-earnings coefficient for sons of displaced Canadian fathers. A lifetime dollar loss also requires the model’s duration and earnings baseline. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.037). | | divorce->child_earnings | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: Gruber studies childhood exposure to unilateral-divorce laws. That treatment is not parental divorce itself. The results differ by gender and do not establish a common 0.95 child-earnings multiplier. Range: Model band; the cited source does not establish this parameter. | | family_size->child_earnings | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: Black, Devereux and Salvanes study education. The family-size effect becomes negligible after birth-order controls and twin-IV checks. The paper does not establish a 0.98 earnings multiplier per additional child. Range: Model band; the cited source does not establish this parameter. | | child_earnings->grandchild_earnings | g′ = 1 − 0.55(1 − g) | 0.4 – 0.6 | US IGE literature | solon1992;corak2013;chetty2014 | Model assumption: The 0.55 factor is a structural persistence assumption. Solon and Corak provide intergenerational-earnings context; Chetty’s baseline IGE is 0.344, distinct from its rank–rank slope. These associations do not measure transmission of a displacement-induced earnings change. Range: Selected literature band, not a confidence interval. | | grandchild_earnings->greatgrandchild_earnings | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The 0.55 factor remains a model assumption. Lindahl documents multigeneration persistence but does not establish this specific earnings-gap transmission rule. The Adermon source record has not been identified. Range: Assumed persistence band; source support unresolved. | | ipv_exposure->daughter_violence_odds | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The exact 2.5 daughter partner-violence odds ratio was not verified. Widom studies later official arrests after abuse or neglect. Ehrensaft’s abstract supports a relationship with adult partner violence, but does not establish this number or range. Range: Unverified model band. | | displacement->local_service_jobs | Service jobs lost = net tradable jobs lost × class multiplier (1.6 manufacturing; 5.0 high-tech). Both inputs are required; this span is not an uncertainty band. | 1.6 – 5 | US metros | moretti2010 | Model assumption: Moretti reports 4.9 local jobs per additional high-tech manufacturing job and 1.59 for manufacturing overall. The model rounds these to 5 and 1.6. Applying additions to losses requires a symmetry assumption and evidence of a net employment change. Range: Different sector estimates, not a confidence interval. | | school_spending->child_earnings | Full study exposure: earnings ratio = 1.07; exposure = +10% per-pupil spending sustained for 12 years. | 1.03 – 1.1 | US school-finance reforms | jackson2016 | Model assumption: The working-paper abstract reports 7.25% higher wages for a 10% spending increase over all 12 school years. The model rounds this to a 1.07 earnings factor. Range: Assumed 1.03–1.10 band, not the paper’s confidence interval. | | youth_wages->youth_crime | Δ% crime = -1 × Δ% youth wages | -1.5 – -0.5 | US counties / young men | gould2002;grogger1998 | Model assumption: The −1 wage elasticity is a rounded model selection. Grogger describes crime-participation elasticities around −0.61 to −0.89; Gould studies local crime and low-skilled male labor-market conditions. Their outcomes and samples differ. Range: Assumed rounding band, not a reported confidence interval. | | wage_ratio->household_ipv | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: Aizer’s −0.813 coefficient relates log female assault hospitalizations to the level of the female/male wage ratio. It is a semi-elasticity per unit ratio, not the log–log elasticity used by this model link. Range: The coefficient’s SE is 0.317; its interval does not resolve the unit mismatch. | | displacement->infant_birth_weight | Outcome level = 0.9541 × comparison level; relative loss = 1 − 0.9541 | 0.912 – 0.9981 | US PSID children 1985+, husband displacement, mother fixed effects | lindo2011 | Model conversion: The factor exponentiates the −0.047 log-birth-weight coefficient in IZA 5213. The sample includes births after displacement, including exposure years before birth; it is not an estimate restricted to in-utero job loss. Range: Exponentiated coefficient ± 1.96 standard errors (SE 0.023). | | import_shock->non_displaced_wage_spillover | Δ% wages = -0.822 × (import exposure dollars per worker / 1000) | -1.3042 – -0.3398 | US commuting zones 1990-2007, noncollege workers OUTSIDE manufacturing, 2SLS state-clustered SE | adh2013 | Source estimate: The −0.822 estimate concerns average log weekly wages of non-college workers outside manufacturing, per $1,000 import exposure per worker. An area average is not a panel of verified continuously employed workers. Range: Coefficient ± 1.96 standard errors (SE 0.246). | | family_income_shock->child_achievement_sd | Δachievement SD = 0.061 × (income change dollars / 1000) | 0.0157 – 0.1063 | US children (NLSY79 mothers) ages 5-14, EITC instrumental variables | dahl2012 | Source estimate: Table 3 of the inspected working paper reports 0.0610 SD per $1,000 of family income in 2000 dollars. That source’s population, income measure and test outcome apply. Range: Coefficient ± 1.96 standard errors (SE 0.0231). | | family_income_shock->life_expectancy_years | Δlife years = 0.1333 × (income change dollars / 1000). Local income–longevity association; not a causal death count. | 0.1167 – 0.15 | US adults age 40, household earnings P15-P20 ($14k-$20k 2012 dollars), men+women averaged | chetty2016 | Model conversion: The model divides the midpoint of an associated 0.7–0.9-year longevity difference by a $6,000 income difference. Chetty’s result is an income–longevity association, not a causal response to an income shock. Range: Converted example endpoints, not a confidence interval. | | displacement->college_enrollment | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: Hilger’s abstract describes a small college-enrollment response. The original pinned coefficient, standard error and enrollment baseline could not be checked against the original table. The unsupported conversion is excluded from public estimates. Range: Exact source interval and denominator unverified. | | displacement->parental_income_shortrun | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: Hilger’s abstract describes large family-income losses. The original pinned loss, standard error and annual-income baseline could not be checked against the original table. The amount is excluded from public estimates. Range: Exact source interval and denominator unverified. | | unemployment_rate->property_crime | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The paper’s identity is established. The specified Table 5 coefficient of 5.018 and its standard error could not be read from an accessible original. A secondary transcription is not accepted as numerical verification. Range: Source-table extraction unverified. | | eitc_exposure->adult_earnings_early | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The exact $564 earnings coefficient and SE 244.9 could not be checked against Bastian and Michelmore’s original Table 2. A percentage result in an abstract does not verify this dollar amount. Range: Source-table extraction unverified. | | male_earnings->marital_fertility | Δln(marital fertility) = 1.24 × Δln(male earnings) | 0.397 – 2.083 | US PUMAs, fracking boom 1997-2012, women 18-34, IV (shale reserves), PUMA-clustered SE | kearney2018fracking | Source estimate: The 1.24 elasticity is in Table 8, Panel B of the 2017 working paper: marital birth rates for women aged 18–34 during the fracking boom. Nonmarital births have the same elasticity. Reversing a positive-income shock is a model assumption. Range: Coefficient ± 1.96 standard errors (SE 0.43), rounded. | | import_shock->gop_win_probability | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: The published Table 4 verifies 24.08 (SE 12.07), but the dose is a percentage-point change in employment-weighted Chinese import penetration. It is not $1,000 per worker. The model’s dollar-input interpretation is unsupported. Range: The published coefficient interval cannot repair the exposure-unit mismatch. | | male_job_loss_rate->child_maltreatment | Δ% maltreatment reports = 6 × Δmale job-loss percentage points | 3.65 – 8.35 | California counties, child-maltreatment reports, county-year panel, county-clustered SE | lindo2018maltreatment | Model conversion: Table 3 gives a Poisson slope of 0.060 per percentage-point increase in California’s male mass-layoff rate. Six percent is the small-change approximation; the exact change is about 6.18%. The outcome is reports, not measured incidence. Range: 100 × (coefficient ± 1.96 standard errors), rounded; SE 0.012. | | displacement->grade_retention_hazard | Outcome rate or hazard = 1.1473 × its comparison rate or hazard; counts require a matching cohort and baseline | 1.0119 – 1.2827 | US children 5-19 (SIPP 1996/2001/2004 panels), head-of-household involuntary job loss (fired/discharged, employer sold/bankrupt, slack work), child fixed effects, N=167,449 child-years / 2,170 displaced children / 1,196 job losses | stevens2011 | Model conversion: The model divides the 0.0081 grade-repetition probability effect by the 0.055 sample average. This is a relative-probability conversion, not an estimated hazard ratio or a measured test-score effect. Range: Source coefficient ± 1.96 standard errors, divided by a fixed sample average. | | eviction_order->emergency_shelter_use | Outcome rate or hazard = 4.778 × its comparison rate or hazard; counts require a matching cohort and baseline | 1.076 – 8.48 | US eviction-court cases (compliers), Cook County + NYC, heads 18-55, judge-leniency IV (first-stage F=934/288) | collinson2024 | Model conversion: The model divides the first-year IV shelter-use effect of 0.034 by the rounded non-evicted mean of 0.009. It is a converted first-year ratio, not a reported universal homelessness effect. Range: Source coefficient ± 1.96 standard errors (SE 0.017), scaled by a fixed rounded mean. | | eviction_order->eviction_earnings_response | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: Table VI reports −$613 for quarters 5–8 with a comparison mean of $4,254. The model instead divides by $4,300, the quarters 1–4 mean. The withdrawn ratio mixes follow-up periods. Range: The source SE is 248; the model’s denominator is from the wrong period. | | foreclosure_order->house_price_gap | Nearby house-price ratio = 0.99; loss = 1 − 0.99. Distance and property cohort are required. | 0.9875 – 0.9925 | US all-type house transactions, Massachusetts 1987-2008 (1.78M sales; Warren Group), reference distance 0.05 miles | campbell2011 | Model assumption: The source describes an approximately 1% price reduction for neighboring sales within 0.05 mile of a foreclosure. The model selects 0.99 and adds a ±25% band on that effect. Range: Assumed band, not a reported confidence interval. | | household_ipv->child_internalizing_sd | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The original repository abstract confirms mean weighted d = 0.48. The exact stored confidence limits could not be checked against the full text. These are exposure associations across studies, not an intervention estimate. Range: Mean confirmed; exact interval unverified. | | household_ipv->child_externalizing_sd | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The original repository abstract confirms mean weighted d = 0.47. The exact stored confidence limits could not be checked against the full text. These are exposure associations across studies, not an intervention estimate. Range: Mean confirmed; exact interval unverified. | | local_unemp_shock->household_ipv | Odds ratio = 1.58 ^ u; u = 12-month proportional unemployment increase (1 = doubling); q = odds ratio × q₀ / (1 − q₀ + odds ratio × q₀). | 1.49 – 1.58 | mothers of the Fragile Families birth cohort (1998-2000 births in 20 large US cities), Waves 3-5 pooled person-waves (2001-2010), all-mothers sample including unpartnered; N=10,656 area models / 10,584 distress models; UR shock 1.0=flat, 2.0=doubling | schneider2016 | Model assumption: The 1.58 point exponentiates the lagged-outcome combined violence/controlling-behavior coefficient, 0.454. Table 3’s logit and fixed-effects coefficients are 0.401 and 0.453. Physical violence alone is not significant. Range: Range across specifications, not a confidence interval. | | household_hardship->household_ipv | Prevalence ratio = 2.14; q = 2.14 × q₀. Source contrast: 15% versus 7%. | 1.61 – 2.68 | mothers of the Fragile Families birth cohort (1998-2000 births in 20 large US cities), Waves 3-5 pooled person-waves (2001-2010), all-mothers sample including unpartnered; N=10,656 area models / 10,584 distress models; hardship = 1+ of 10 material-hardship items, past 12 months | schneider2016 | Model conversion: The 2.14 ratio divides the paper’s predicted probabilities, 15% and 7%. It is not the reported logit odds ratio or an established causal hardship effect. The outcome includes controlling behavior. Range: Assumed ±25% rounding band, not a confidence interval. | | couple_unemployment->household_ipv | Prevalence ratio = 1.3; q = 1.3 × q₀. Source contrast: 13% versus 10%. | 1.04 – 1.63 | mothers of the Fragile Families birth cohort (1998-2000 births in 20 large US cities), Waves 3-5 pooled person-waves (2001-2010), all-mothers sample including unpartnered; N=10,656 area models / 10,584 distress models; either partner unemployed and looking | schneider2016 | Model conversion: The 1.30 ratio divides predicted probabilities, 13% and 10%. Exposure includes some noncoresiding unemployed mothers. The combined-outcome logit coefficient is 0.306; the bundle note’s 0.404 belongs to another specification. Range: Assumed rounding band, not a confidence interval. | | unemployment_status->mental_health_sd | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source unverified · estimate withdrawn: The publisher’s text describes d = 0.51. The exact outlier-excluded table and stored 0.47–0.54 interval could not be checked. The abstract’s overall d = 0.54 is a different summary. Range: Exact source interval unverified. | | import_shock->radical_right_vote_share | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: The inspected manuscript reports 0.132 (SE 0.051) in vote-share fractions per €1,000 per worker, measured over the two years before an election. Converting the outcome to 13.2 percentage points does not convert euros to US dollars or establish persistence. Range: Rounded coefficient ± 1.96 standard errors; the exposure-unit mismatch remains. | | neighborhood_exposure->child_outcomes_modifier | Annual exposure coefficient = 0.037; moving age and origin/destination income-rank difference are required. | 0.031 – 0.043 | children of families moving across counties (US tax data, births 1980-88); county-level predictions of permanent residents' income ranks at age 24 | chettyhendren2018 | Source estimate: Appendix Table V reports 0.037 income-rank points per additional childhood year in a county with one rank-point better permanent-resident outcomes. Multiplying a displacement penalty by this place factor is a model assumption. Range: Coefficient ± 1.96 standard errors (SE 0.003), rounded. | | unconditional_income->child_education_years | Δeducation years = 1.127 for the source's approximately $4,000 annual transfer per eligible adult. | 0.247 – 2.007 | children in Eastern Band of Cherokee area households previously in poverty (Great Smoky Mountains Study, age cohorts 9/11 at wave 1), treated by ~$4,000/yr per adult member for four pre/post childhood survey waves | akee2010 | Source estimate: Table 4’s previously poor-household coefficient is 1.127 education years (SE 0.449), N = 438. It is the youngest-cohort interaction per eligible tribal-member parent, not per arbitrary household or $1,000. Range: Coefficient ± 1.96 standard errors. | | unconditional_income->youth_any_crime | Δarrest probability = -0.224 for the source transfer exposure; eligible child cohort required. | -0.377 – -0.071 | same population as the education row (previously-poor eligible households; arrests from administrative records merged at the individual level) | akee2010 | Source estimate: Table 6 reports −0.224 probability points for any arrest at ages 16–17. Treatment is the youngest-cohort interaction per eligible tribal-member parent receiving casino transfers. Range: Coefficient ± 1.96 standard errors (SE 0.078). | | unconditional_income->youth_minor_crime_ever | Δminor-offense probability = -0.179 for the source transfer exposure; eligible child cohort required. | -0.353 – -0.005 | same population as the education row (previously-poor eligible households) | akee2010 | Source estimate: Table 6 reports −0.179 probability points for ever a minor arrest by age 21. It is a specified cohort/eligible-parent contrast, not a generic income elasticity. Range: Coefficient ± 1.96 standard errors (SE 0.089). | | youth_crime_conviction_share->youth_crime_convicted | Δconviction probability = 0.061 × Δarea youth conviction-share percentage points | 0 – 0.123 | male refugee children in Denmark assigned quasi-randomly to municipalities 1986-1998 (avg age at assignment 9; N=4,425) | damm2014 | Model conversion: The model divides a 0.043 probability effect by the neighborhood conviction-share SD of 0.70 percentage points. This concerns Danish refugee boys’ later convictions, not the volume of reported neighborhood crimes. Range: Coefficient ± 1.96 standard errors (SE 0.022), scaled by 0.70; lower endpoint rounded to zero. | | youth_violent_crime_conviction_share->youth_crime_convicted | Δconviction probability = 0.366 × Δarea violent-conviction-share percentage points | 0.143 – 0.589 | same population as the overall-share row (male refugee children, quasi-random municipality assignment, N=4,425) | damm2014 | Model conversion: The model divides a 0.045 probability effect by the violent conviction-share SD of 0.123 percentage points. The source’s male refugee population and conviction-share exposure apply; girls’ estimates are not significant. Range: Coefficient ± 1.96 standard errors (SE 0.014), scaled by 0.123. | | displacement->circulatory_mortality_hazard | Outcome rate or hazard = 1.54 × its comparison rate or hazard; counts require a matching cohort and baseline | 1.29 – 1.83 | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | browningheinesen2012 | Source estimate: The inspected 2011 report gives a cumulative hazard ratio over years 1–4 for Danish men with strong labor-market attachment after plant closure. It is not an annual hazard or an odds ratio. Range: Reported 95% confidence interval for the specified cause and follow-up window. | | displacement->alcohol_mortality_hazard | Outcome rate or hazard = 1.62 × its comparison rate or hazard; counts require a matching cohort and baseline | 1.09 – 2.41 | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | browningheinesen2012 | Source estimate: The inspected 2011 report gives a cumulative hazard ratio over years 1–4 for Danish men with strong labor-market attachment after plant closure. It is not an annual hazard or an odds ratio. Range: Reported 95% confidence interval for the specified cause and follow-up window. | | displacement->external_cause_mortality_hazard | Outcome rate or hazard = 1.53 × its comparison rate or hazard; counts require a matching cohort and baseline | 1.15 – 2.04 | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | browningheinesen2012 | Source estimate: The inspected 2011 report gives a cumulative hazard ratio over years 1–4 for Danish men with strong labor-market attachment after plant closure. It is not an annual hazard or an odds ratio. Range: Reported 95% confidence interval for the specified cause and follow-up window. | | displacement_event->spouse_mental_health_sd | Outcome = baseline + (-0.194); change is in standard-deviation units | -0.327 – -0.061 | spouses of displaced workers, German couples (SOEP 2002-2010), 109 displaced-worker couples vs >14,000 entropy-balanced controls; MCS normed mean 50 SD 10 | marcus2013 | Model conversion: Table 3’s spouse mental-health effect is −1.94 MCS points (SE 0.68). The source normalizes the score to SD 10; division by 10 gives −0.194 SD. The follow-up is about one year after unemployment following closure. Range: Coefficient ± 1.96 standard errors, divided by 10. | | displacement_event->child_achievement_sd | Outcome = baseline + (-0.0206); change is in standard-deviation units | -0.0402 – -0.001 | children exposed to parental plant closure age 0-16 (average across exposure stages), Denmark, conditional on taking grade-9 exams; mathematics | bingley2026 | Source estimate: Table 4 reports −0.0206 SD (SE 0.0100) for teacher-assessed mathematics grades in the Danish sample. The separate standardized-test estimate is smaller and not significant. These outcomes are not interchangeable. Range: Coefficient ± 1.96 standard errors. | | displacement_event->exam_noncompletion_hazard | Estimate withdrawn | Estimate withdrawn | No verified population and outcome match for this numerical input. | | Source mismatch · estimate withdrawn: The 0.0054 effect (SE 0.0027) is verified. The 0.0785 denominator is labeled “Constant” in a controlled regression, not a verified control-group mean. The withdrawn ratio relies on that unsupported baseline interpretation. Range: Coefficient uncertainty scaled by an unsupported denominator; not an estimated hazard ratio. | | displacement_event->hs_completion | Outcome = baseline + (-0.037); change is in probability points | -0.0801 – 0.0061 | children of single mothers, US NLSY79 (NLSY79 women's children), MATERNAL job displacement at child age 0-17 (PSM kernel TT); outcome = HS completion by age 19, control mean 0.760 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is −0.037 for high-school completion by age 19; its interval crosses zero. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.022). | | displacement_event->college_attendance | Outcome = baseline + (-0.063); change is in probability points | -0.1081 – -0.0179 | same scope as the hs_completion row; outcome = some college attendance by age 21-22, control mean 0.427 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is −0.063 for college attendance in young adulthood. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.023). | | displacement_event->college_completion | Outcome = baseline + (-0.036); change is in probability points | -0.0674 – -0.0046 | same scope as the hs_completion row; outcome = college completion (BA) by age 25, control mean 0.169 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is −0.036 for college completion in young adulthood. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.016). | | displacement_event->adult_depression_cesd | Outcome = baseline + (0.025); change is in 0–1 index units | 0.0034 – 0.0466 | same scope as the hs_completion row; outcome = CESD 7-item depressive-symptom index (0-1) at ages 25-29, control mean 0.208 | brand2014 | Source estimate: Table 3’s kernel-matching estimate is +0.025 on the 0–1 CESD index at ages 25–29, not a standard-deviation change. The sample is children of single mothers; selection on observed characteristics is not random assignment. The displayed baseline is the unadjusted comparison-group mean in Table 1; applying the matched effect to it is a model choice. Range: Coefficient ± 1.96 standard errors (SE 0.011). | | displacement_event->spouse_participation_elasticity | Δln(wife labor-force participation) = -0.04 × Δln(husband earnings) | -0.07 – -0.03 | married couples, Austrian ASOS registers 1990-2007, HUSBANDS displaced by firm closure/mass layoff vs non-event firm controls; wife's labor-force participation response | halla2020 | Model assumption: The inspected AEA manuscript’s Table 2 reports employment elasticity −0.043 (SE 0.011) for wives after husbands’ displacement. The model rounds to −0.04. This is an elasticity, not a percentage-point participation coefficient. Range: Rounded subgroup band, not the main estimate’s confidence interval. | | displacement_event->annual_birth_response | Outcome = baseline + (-0.005); change is in probability points | -0.0089 – -0.0011 | couples, Finnish FLEED registers, WOMEN displaced by plant closures (base years 1991-1993) vs matched non-displaced; outcome = couple's probability of a birth in the year | huttunenkellokumpi2016 | Source estimate: Table 3’s female plant-closure coefficient is −0.005 (SE 0.002), a 0.5 percentage-point probability change. The Finnish sample is women aged 20–40; it is not a change in total births for every worker. Range: Coefficient ± 1.96 standard errors. | | displacement_event->child_depression_anxiety | Outcome = baseline + (0.008); change is in probability points | 0.0002 – 0.0158 | children ages 6-17, US MEPS, PATERNAL job loss (tenured-father sample, >=1y tenure), individual-FE LPM; outcome = child depression/anxiety report | schallerzerpa2019 | Source estimate: Table 2’s probability effect is +0.008: 0.8 percentage points, not 0.008 percentage points. The inspected MEPS sample is children aged six and older with a tenured displaced father. Range: Coefficient ± 1.96 standard errors (SE 0.004). | | child_achievement_sd->grandchild_achievement_sd | Δgrandchild SD = 0.38 × Δchild SD | 0.38 – 0.42 | Norway male conscripts (IQ at age 18, father-son) | blackdevereuxsalvanes2009 | Model assumption: The source reports a 0.38 father–son IQ correlation in Norway. The authors give it no causal interpretation. Applying it to an induced achievement change is a structural assumption, not a measured intergenerational treatment effect. Range: Selected literature band, not a confidence interval. | | child_education_years->grandchild_education_years | Δgrandchild education years = 0.296 × Δchild education years | 0.255 – 0.337 | Sweden, Malmö four-generation register (G3 children, N=1,823) | lindahl2015 | Source estimate: Table 2 reports a 0.296 association between parent and child years of education. It is an observational regression coefficient, not the causal transmission of an induced schooling change. Range: Coefficient ± 1.96 standard errors (SE 0.021), rounded. | | infant_birth_weight->child_earnings | y / y₀ = (x / x₀) ^ (0.1); x / x₀ is the named exposure ratio | 0.0216 – 0.1784 | Norway twin sample, twin fixed effects on ln(birth weight), cohorts 1967-1988 (military conscription + earnings registries); IZA DP 1864 Table 5 'Ln(Earnings) FT', all-twins FE column | black2007 | Source estimate: The 2005 working paper’s Table 5 reports 0.10 (SE 0.04) for log full-time earnings on log birth weight in a twin fixed-effects sample. This is not a causal bridge from parental displacement to adult earnings. Range: Coefficient ± 1.96 standard errors. | | infant_birth_weight->adult_type2_diabetes_hazard | y / y₀ = (x / x₀) ^ (-0.9637); x / x₀ is the named exposure ratio | -1.3834 – -0.5401 | adults, pooled random-effects dose-response, 32 studies / ~7.6M participants (Knop et al. JAHA 2018, 7(23):e008870, OR per +1 kg birth weight; read via PMC6405546 full text) | knop2018 | Model conversion: The meta-analysis reports odds ratio 0.78 [0.70, 0.87] per 1 kg. The model converts this using ln(OR) / ln(4.4/3.4). The 3.4 kg baseline and constant elasticity are assumptions; odds are not hazards. Range: Transformed reported 95% odds-ratio limits, conditional on the model’s assumed baseline. | | infant_birth_weight->adult_cardiovascular_disease_hazard | y / y₀ = (x / x₀) ^ (-0.6994); x / x₀ is the named exposure ratio | -0.8173 – -0.585 | adults, pooled random-effects dose-response, 33 studies / ~5.9M participants (same source as the T2D row; OR per +1 kg birth weight) | knop2018 | Model conversion: The meta-analysis reports 16.5% lower odds, with a printed rounded odds ratio of 0.84 [0.81, 0.86] per 1 kg. The model converts this using ln(OR) / ln(4.4/3.4). The 3.4 kg baseline and constant elasticity are assumptions; odds are not hazards. Range: Transformed reported 95% odds-ratio limits, conditional on the model’s assumed baseline. | | divorce_hazard->child_divorce_hazard | s′ = 1 − (1 − s)^r; child hazard ratio = 1 + (s′ − s) × (1.88 − 1) | 1.57 – 2.24 | US women (NSFG cycles I-III), white daughters who spent part of childhood with a divorced/separated/never-married parent vs two-parent families; proportional-hazard model of own marital disruption | mclanahanbumpass1988 | Model conversion: The inspected 1986 draft’s Appendix Table A1 gives 0.63 (SE 0.09) for white women in a background-adjusted proportional-hazard model. Parent absence includes divorce, separation, never-married parents and neither parent, not divorce alone. Range: Exponentiated coefficient ± 1.96 standard errors, rounded. | | married_cohort->parental_dissolution_share | Counterfactual dissolution share s = 0.069; use only for the matched married cohort. | 0.069 – 0.072 | married workers at Norwegian plants 1995-2000 (the rege2007 entry population and follow-up window, dissolution measured by 2003) | rege2007 | Model assumption: The 0.069 value is the observed dissolution share among Norwegian couples with husbands at stable plants, from 1995 to 2003. The 0.072 endpoint is the closing-plant group’s observed mean, not an uncertainty limit. Range: Two observed cohort means; not a confidence interval or annual baseline. | | undocumented_share_change_pp->receiving_violent_crime_log_rate | log(rate1/rate0) = -0.12 × share change in percentage points; rate ratio = exp(log-rate change). Requires the undocumented-resident share margin. | -0.18 – -0.06 | US 50 states + DC 1990-2014; lagged percentage-point undocumented population share; Light-Miller 2018 Table 2 Model 4 | lightmiller2018 | Source estimate: Table 2’s unweighted fixed-effects Model 5 gives −0.12 (SE 0.03) for log violent-crime rates per percentage-point undocumented population share. It is an observational association; the weighted model differs. Range: Coefficient ± 1.96 standard errors, rounded to two decimals. | | regular_immigrant_share_ratio->receiving_total_crime_rate | rate1/rate0 = (share1/share0)^0.105. Shares require both population denominators; this is a ten-year endpoint contrast. | -0.2616 – 0.4716 | Italy 95 provinces 1991-2001; log valid residence permits / total province population; 2010 working-paper ten-year-difference IV | bianchibuonannopinotti2012 | Source estimate: Table 5 of the 2010 manuscript gives IV 0.105 (SE 0.187) for log total-crime rate versus log valid residence permits / population. The interval includes zero. This is a ten-year endpoint-rate contrast in Italian provinces. Range: Coefficient ± 1.96 standard errors, rounded; not a cumulative incident count. | ### Earnings effects across generations Each figure compares expected adult earnings with the earnings expected without displacement. Dollar figures apply the model's $2,591,418 SSA lifetime-earnings benchmark to one descendant, not to an assumed number of grandchildren. The later-generation figures carry forward only the modeled child earnings gap. They are structural projections, not direct study estimates. | Comparison | Figure | |---|---| | Displaced worker earnings | 80.0¢ per $1 expected without displacement · cross-study model assumption | | Grandchild adult earnings | 94.9¢ per $1 expected without displacement · model-based projection | | Grandchild lifetime earnings, per person | $2,459,722 · $131,696 below the $2,591,418 SSA benchmark | | Great-grandchild adult earnings | Estimate withdrawn | | Great-grandchild lifetime earnings, per person | Estimate withdrawn | ## Study findings Every link in the pinned model appears below. The citation check distinguishes reported estimates, model conversions, assumptions and unresolved support. Range definitions vary by parameter. A separate exposure or missing baseline prevents an absolute prediction. | Measured outcome | Model input | Unit | Study · population | Result kind | |---|---|---|---|---| | Worker earnings | 80.0¢ | per $1 expected | Jacobson · Davis & von Wachter · High-tenure US displacement; range across three long-run studies | Model assumption | | Adult child earnings | −9.24% | annual earnings | Oreopoulos · Page · Stevens · Canadian father–son firm closures | Model conversion | | Grade retention | +0.81 pp | from 5.5% | Stevens · Schaller · US children, 1+ year after involuntary household job loss | Model conversion | | Birth weight | −4.59% | births after loss | Lindo (2011) · US PSID; husband displacement; sibling comparison | Model conversion | | Marriage dissolution | +11% | relative likelihood | Rege · Telle · Votruba · Norwegian married couples after plant closure | Model assumption | | Mortality odds | 2.67× | displacement phase | Sullivan · von Wachter · High-seniority male Pennsylvania mass layoffs | Model conversion | ### Separate evidence families These study families answer different questions. The model does not start them from a worker displacement. | Named input | Study outcome | Why it stays separate | |---|---|---| | Net metro tradable jobs | Local service employment | Needs a measured metro employment change and a named job mix. | | Import exposure | Wages · political outcomes | A region-level trade-shock input, not a worker count. | | Eviction order | Shelter use · earnings | A court order, studied by comparing cases assigned to strict and lenient judges. | | Unconditional income | Schooling · youth crime | A recurring transfer program, not a displacement effect. | | Neighborhood exposure | Adult mobility outcomes | Studied among families that moved between counties; combining it with displacement stays an assumption. | ### Nulls and refused paths The evidence corpus keeps null and negative findings: the receiving-community crime stream records a null aggregate effect on total crime beside the identified negative effect on violent crime. A path without a compatible input stays blank: local service employment needs measured net job loss, not a worker count, and the work-banned asylum property-crime branch is recorded as findings and never merged into displacement effects. ### Mortality timing profile: five study phases | Period | Odds ratio | Study range | |---|---|---| | Displacement | 2.670× | 2.114× to 3.371× | | +1 year | 1.984× | 1.370× to 2.873× | | +2–3 years | 1.732× | 1.324× to 2.265× | | +4–5 years | 1.271× | 0.970× to 1.666× | | +6 years onward | 1.135× | 1.034× to 1.247× | The five phases come from the study's own year-by-year table. Each range is the statistical band around that study estimate; it is not any one person's range of outcomes. The calculator converts each phase with a cited mortality baseline and compares survival over the follow-up. ## What these estimates mean Default results are illustrative reference calculations. A reviewed population decision is required for each outcome before headline use. Downstream estimates consequences if the stated displacement occurs and the study assumptions apply. It does not establish that an employer caused job loss. Predictive accuracy for future events is not established. The source repository documents the validation results and their limits. [Inspect validation and model limits](https://github.com/xh1b/downstream/blob/d7691dac652a81bddb16c9f91a9cf8ecd88b70db/docs/model_card.md#evaluation-status) ## Methods and evidence ## The two-stage pipeline Stage 1 · XH1B displacement exposure (method v1.2): certified H-1B labor condition applications, compared with national BLS occupational medians (benchmarked to the latest BLS survey), plus matched WARN notices. The output is modeled worker equivalents per employer, person, law firm, and area. It is not a count of documented displaced people. Stage 2 · Downstream conditional consequences (pinned bundle v1.52, engine 0.4.0): a stated number of displaced workers becomes conditional earnings, mortality, and other modeled outcomes with cited studies. It does not validate stage 1's exposure. Neither stage observes an actual H-1B hire or proves that a hire displaced a worker. A matched WARN notice is a review signal, not proof of replacement. ### Stage 1 method definition: Displacement Exposure Model v1.2 Stage one of the two-stage pipeline. It turns certified H-1B labor condition applications into a modeled count of worker equivalents exposed to displacement, per employer, person, law firm, and geography. Stage two (the Downstream model) takes a stated exposure and estimates conditional consequences. | Rule | Definition | |---|---| | Eligibility | Visa class H-1B only. Case status starts with Certified (including certified-then-withdrawn). Rows carrying a data-quality flag are excluded. This covers flagged H-1B filings, and WARN notices whose layoff count is flagged suspect. | | Worker fallback | A filing with no recorded worker count counts as one worker. | | Wage gap | Each filing is compared with the latest national BLS occupational median wage for its canonical SOC code. The gap is the shortfall below that median, as a share of the median: max(0, (BLS median − wage offer) / BLS median). Filings with no BLS match or no positive wage offer contribute no wage gap. | | WARN match | For employer and geography totals, the model adds reported layoffs from matched WARN events. The event matcher uses same-employer H-1B submission dates from three months before through six months after the notice date, with the effective date as fallback. Matching includes all decision outcomes and worksites. It is separate from the certified filing cohort used for the LCA term. A WARN notice with a suspect layoff count or an unproved location association matches nothing until review repairs it. Complete source observations stay stored. A match does not prove replacement. | | Scopes | Employers: LCA term plus matched WARN layoffs. Persons (attorneys and points of contact): LCA term only. Law firms: LCA term only, per firm name. States, counties, and ZIP codes: LCA term plus matched WARN layoffs for the area. | | Rounding | Totals and components round to three decimals; the average wage-gap percentage rounds to one decimal. | | Known limits | The model does not observe an actual H-1B hire and does not prove replacement. Terms are additive across filings and notices, so the same person can be represented more than once. A WARN count is a filed-notice count, not a verified layoff count. Geography totals exclude flagged WARN counts. The math expander shows the as-published total beside the quarantined one. The wage-gap term is a wage-depression exposure, not a wage-law finding. | | What the version is not | The version labels a traceable calculation. It is not a claim that each requested position became a hire, that each hire displaced a worker, or that a matched notice proves replacement. | ## Reference scenario: 1,000 displaced workers This example states an input: 1,000 workers in an illustrative displacement cohort, two children per worker, 20 years of follow-up, compared with the same people without a displacement. It is not an observed group and not the site's exposure estimate for any employer. | Outcome | Estimate | Parameter p05–p95 | Unit | Study basis | Scope | |---|---|---|---|---|---| | Child lifetime earnings lost | $478,894,046 | $158,288,021 to $774,074,264 | 2024 dollars | Oreopoulos, Page & Stevens (2008) × SSA 2025 | Illustrative reference calculation; Canadian father–son firm closures | | Excess deaths over 20 years | 28.76 | 22.04 to 36.68 | deaths | Sullivan & von Wachter (2007 working paper) × CDC WONDER | Illustrative reference calculation; high-seniority male Pennsylvania displacement | Parameter intervals are central 90% parameter-only intervals (p05–p95). They hold the exposure, baselines, and pooling fixed; they exclude exposure estimation error and unmodeled pathways. They are not confidence intervals and not ranges for one person. Parent income stays in the study's own dollars and is not added to, or compared with, the 2024-dollar child figure. Why "Child lifetime earnings lost": Oreopoulos, Page & Stevens (2008); population children of Canadian fathers in firm closures; parameter −9.24% annual earnings per displaced father; baseline US male lifetime-earnings benchmark (SSA, 2024 dollars). Main limit: Canadian firm-closure setting; transport to US displacement is an applicability decision, not a measurement Why "Excess deaths over 20 years": Sullivan & von Wachter (2007 working paper); population high-seniority men in Pennsylvania mass layoffs; parameter mortality odds 2.67× in the displacement year, declining phases after; baseline US men aged 45–54 all-cause mortality (CDC WONDER D76, 2015–2019). Main limit: a male reference-cohort result; a mixed population does not inherit it without a reviewed transport rule The model first states what a study result measures. It then applies only the matching calculation: an earnings ratio changes an earnings level, a mortality ratio needs a mortality baseline, and a local-jobs result stays a jobs result. This prevents combining numbers that describe different things. ```latex \begin{aligned} \text{level:}\;&v' = vp & \text{direct:}\;&v'=p \\ \text{remaining loss:}\;&v'=1-t(1-v) & \text{rate:}\;&q'=q_{0}\,p \\ \text{count ratio:}\;&n'=np & \text{elasticity:}\;&\Delta\%y=p\,\Delta\%x \end{aligned} ``` A rate becomes a count only after the model applies a cited baseline. A local-jobs multiplier cannot be added to an earnings result. The child estimate is the starting point. The model applies an intergenerational transmission assumption t to the part of the gap that remains. It does not multiply the original shock into every generation or add other harms later in life. Grandchild and great-grandchild figures are structural projections, not direct study estimates. ```latex \begin{aligned} g_1 &= p_{\mathrm{displacement}\to\mathrm{child}} \\ g_2 &= 1-t_{12}(1-g_1) \\ g_3 &= 1-t_{23}(1-g_2) \\ \neq\;& g_1t_{12}\quad\text{or}\quad g_1g_2 \end{aligned} ``` The child-dollar result uses the direct displacement study. Divorce and family-size studies can describe the same children, so adding them would count one loss twice. Local-service-job research answers a separate question: what happens after a metro's net tradable employment changes. | Path | Leads to | Treatment | |---|---|---| | Displacement | Child earnings | counted once | | Divorce / family size | Child earnings | visible, not added | | Net tradable jobs lost | Local services | requires net-job evidence | The model converts the study's odds ratio into a risk using an annual mortality baseline. It applies five study phases and compares survival over 20 years. Source offset +6 starts in follow-up year 7. ```latex \begin{aligned} q(r) &= \frac{rm}{1-m+rm} \\ S_Y &= \prod_{y=1}^{Y}(1-q_y) \\ D_{\mathrm{excess}} &= N(S_{Y,\mathrm{baseline}}-S_{Y,\mathrm{exposed}}) \end{aligned} ``` For independent paths, the model calculates the first three moments of the combined distribution and compares its approximation with a joint simulation. Nonlinear or correlated paths use the simulation directly. Repeated transmission relationships share one uncertainty draw. ```latex \begin{aligned} \mu &= \mathbb{E}[V] \\ \sigma^2 &= \mathbb{E}[V^2]-\mu^2 \\ \gamma_1 &= \frac{\mathbb{E}[V^3]-3\mu\sigma^2-\mu^3}{\sigma^3} \end{aligned} ``` The equations use relative levels unless they explicitly produce a count or dollar amount. A level of 1 means the no-displacement comparison; a level below 1 means a loss. | Symbol | Meaning | |---|---| | v | earnings level before the next link; 1 means no earnings gap | | v′ | earnings level after the next link | | p | the cited study estimate or multiplier | | t | share of the remaining earnings gap passed to the next generation | | g₁, g₂, g₃ | child, grandchild, and great-grandchild earnings levels | | n | a count before a count multiplier is applied | | x, y | an input and its outcome in an elasticity calculation | | Δ% | a percentage change | | N | number of workers in the stated scenario | | m | annual mortality risk in the comparison population | | r | study odds ratio for mortality | | q(r), Sᵧ, Dₑₓcₑss | exposed annual risk, survival through year Y, and excess deaths | | q₀ | annual rate before a study multiplier is applied | | Y | number of follow-up years | | V | a combined model result treated as a random variable in simulation | | μ, σ², γ₁ | the mean, variance, and skewness of V | | Rule type | Operation | What it prevents | |---|---|---| | remaining loss | 1 − t × (1 − g) | Treating a transmission rate as a new earnings level. | | relative risk | Apply to a cited baseline | Reporting an absolute count without a baseline. | | count multiplier | Multiply one count or dollar level | Chaining a jobs result into an earnings result. | | elasticity | %Δ outcome = elasticity × %Δ input | Dropping the input unit or changing the sign. | ### Uncertainty contracts Source studies: a confidence interval describes the sampling uncertainty of one study estimate. The model retains those source details. It does not call a combined model result a confidence interval. Technical materials: the white paper and source repository show what changes when declared parameters vary, and the simulation results for eligible paths. Those are sensitivity checks, not odds that a real-world outcome falls inside a stated range. Neither procedure resolves uncertainty about the documented exposure, baseline measurement, use in a new population, model choices, or effects that the evidence does not identify. ### Browse the evidence graph This is the preserved bundle note. It may contain extraction or interpretation errors. The citation check above states the current source assessment. | Link | Evidence role | Source parameter [support] | Study | Study population | Original model note | |---|---|---|---|---|---| | displacement->worker_earnings | conditional | 0.8 [0.75, 0.85] | jacobson1993;oreopoulos2008;davis2011 | US high-tenure displaced men | long-run earnings multiplier; band = cross-study spread: JLS early-80s PA losses vs D&vW 2011 full-text synthesis (still 15-20% below controls after 20y) | | earnings_shock->mortality_sustained | conditional | 1.1354 [1.0335, 1.2474] | sullivan2009 | US high-seniority displaced men born 1930-1959 | Sullivan & von Wachter NBER WP 13626 (2007), Table 5 column 3, offset +6 onward: log-odds 0.127 (SE 0.048), transformed as exp(coefficient +/- 1.96 SE) and rounded to parameter-file precision. Source offsets are relative to displacement; with displacement as follow-up year 1 this begins in year 7. The profile is sourced coherently from this working-paper table; reconcile against the published QJE version before treating the locator as published-version extraction. High-seniority male Pennsylvania mass-layoff cohort in the early-1980s recession; not automatically transportable to ordinary layoffs.; browningheinesen2012 CROSS-CHECK (v1.38): 20-year cumulative hazard ratio 1.10 [1.05, 1.16], still significant at 20y (authors rebut harvesting: yearly hazard ratios exceed 1 in almost all years) vs the SvW sustained annual OR 1.135 - different estimands and windows, not a like-for-like replication; cumulative hazard ratios cannot validate an annual OR magnitude or be pooled with it; bloemen2018 (v1.43): Dutch men 45-59, 5y +0.5968pp (SE 0.1763) = +33.5% (2y 60.9%, 3y 39.4%, 4y 41.2% - declining pattern consistent with peak-then-decay); DECLARED DIVERGENCE: eliasonstorrie2009 reports long-run all-cause estimates compatible with the null (5-8y HR 0.98, 9-12y 0.91, both n.s., 12y follow-up, baseline-displacement design) - the sustained-effect SIZE is design-heterogeneous across countries; positions never averaged (CITING 5), the SvW anchor stays; REPLACED 2026-10-14 v1.51: source beta/SE transformation re-executed at four decimals; prior stored point/low/high 1.135/1.033/1.247 remain in Git. Numerical source is the working-paper version; canonical publication tier under CITING section 1, pending published-version reconciliation. | | earnings_shock->mortality_peak | conditional | 2.6698 [2.1144, 3.3711] | sullivan2009 | US high-seniority displaced men born 1930-1959 | Sullivan & von Wachter NBER WP 13626 (2007), Table 5 column 3, displacement offset: log-odds 0.982 (SE 0.119), transformed as exp(coefficient +/- 1.96 SE). The profile is sourced coherently from this working-paper table; reconcile against the published QJE version before treating the locator as published-version extraction. High-seniority male Pennsylvania mass-layoff cohort in the early-1980s recession; not automatically transportable to ordinary layoffs.; browningheinesen2012 CROSS-CHECK (v1.38): Danish plant closures (males 20-60, PSW), year-of-displacement cumulative hazard ratio 1.84 [1.44, 2.34] = +84% within its own study; the cumulative hazard ratio is not numerically comparable to the annual SvW OR without estimand/baseline harmonization; rechecked from 2011 AKF working-paper Table 6.1, PDF page 23; CROSS-COUNTRY FINDINGS WITH DIFFERENT SCALES AND WINDOWS (v1.43): eliasonstorrie2009 Swedish PSW establishment closures, men <=4y all-cause HR 1.44 [1.19, 1.76] (external 2.07 [1.42, 3.02], suicide 2.15 [1.28, 3.59], alcohol-related 2.21 [1.14, 4.31] beside); bloemen2018 Dutch LPM, men 45-59 at closing firms, year-1 +0.2229pp (SE 0.0812) = +85.8%; REPLACED 2026-10-14 v1.51: source beta/SE transformation re-executed at four decimals; prior stored point/low/high 2.6696/2.1151/3.3696 remain in Git. Numerical source is the working-paper version; canonical publication tier under CITING section 1, pending published-version reconciliation. | | earnings_shock->mortality_offset_1 | conditional | 1.9838 [1.3697, 2.8732] | sullivan2009 | US high-seniority displaced men born 1930-1959 | Sullivan & von Wachter NBER WP 13626 (2007), Table 5 column 3, offset +1: log-odds 0.685 (SE 0.189), transformed as exp(coefficient +/- 1.96 SE). The profile is sourced coherently from this working-paper table; reconcile against the published QJE version before treating the locator as published-version extraction. High-seniority male Pennsylvania mass-layoff cohort in the early-1980s recession; not automatically transportable to ordinary layoffs.; REPLACED 2026-10-14 v1.51: source beta/SE transformation re-executed at four decimals; prior stored point/low/high 1.9838/1.3672/2.8777 remain in Git. Numerical source is the working-paper version; canonical publication tier under CITING section 1, pending published-version reconciliation. | | earnings_shock->mortality_offsets_2_3 | conditional | 1.7315 [1.3238, 2.2649] | sullivan2009 | US high-seniority displaced men born 1930-1959 | Sullivan & von Wachter NBER WP 13626 (2007), Table 5 column 3, offsets +2 through +3: log-odds 0.549 (SE 0.137), transformed as exp(coefficient +/- 1.96 SE). The profile is sourced coherently from this working-paper table; reconcile against the published QJE version before treating the locator as published-version extraction. High-seniority male Pennsylvania mass-layoff cohort in the early-1980s recession; not automatically transportable to ordinary layoffs.; REPLACED 2026-10-14 v1.51: source beta/SE transformation re-executed at four decimals; prior stored point/low/high 1.7316/1.3244/2.2641 remain in Git. Numerical source is the working-paper version; canonical publication tier under CITING section 1, pending published-version reconciliation. | | earnings_shock->mortality_offsets_4_5 | conditional | 1.2712 [0.97, 1.6661] | sullivan2009 | US high-seniority displaced men born 1930-1959 | Sullivan & von Wachter NBER WP 13626 (2007), Table 5 column 3, offsets +4 through +5: log-odds 0.240 (SE 0.138), transformed as exp(coefficient +/- 1.96 SE). v1.50 corrects the former SE 0.077 copied from column 6 offsets +2-3. Visually re-extracted from PDF page 54; source SHA256 20617cbe3924c8b58f6d3888cb0a0ea26ca908d60486f4aad304398dd6ef9c8f. Stable employment 1974-79 at employer over 50 workers; birth cohort 1930-59. The 45-54 baseline is a reference stratum, not the full source sample. Reconcile against the published QJE version before treating this as a published-version extraction; not automatically transportable to ordinary layoffs.; REPLACED 2026-10-14 v1.51: source beta/SE transformation re-executed at four decimals; prior stored point/low/high 1.2712/0.9700/1.6661 remain in Git. Numerical source is the working-paper version; canonical publication tier under CITING section 1, pending published-version reconciliation. | | displacement->divorce_hazard | conditional | 1.11 [1.05, 1.25] | rege2007;charles2004 | married displaced workers | Norway plant closures: marriages +11% more likely dissolved by 2003 (80k couples); Charles & Stephens 2004 confirm direction; band = cross-study spread widened for US generalization; internal evidence table said +23% - corrected 2026-09-06 against DP514 abstract; HALLA-SCHMIEDER-WEBER 2020 CROSS-CHECK (v1.43): Austrian registers, quarterly divorce hazard +0.004pp (SE 0.001) vs clean-firm controls = ~0.5pp cumulative over 5 years on a ~6% base (relative ~1.08 over 5y) - an order smaller than the shipped multiplier; PRECISE ZERO vs mass-layoff-firm controls (-0.001, SE 0.001) - firm-level uncertainty, not the displacement per se, carries the small effect; huttunenkellokumpi2016 beside (Finnish plant closures: divorce dpl1 +0.011 n.s. female, +0.011* male) - divergence declared, never averaged (CITING 5), rege2007 stays the anchor | | displacement->child_earnings | conditional | 0.9076 [0.844, 0.976] | oreopoulos2008 | Canada 39k father-son pairs firm closures | REPLACED v1.11: was 0.91 [0.86,0.96] abstract-derived; Table 2 col 3 (income-controlled, N=38342) log coeff -0.097 (SE 0.037) -> multiplier exp(-0.097)=0.9076, 95% CI [0.844,0.976]; band WIDENED by evidence (CITING 4: bands never shrink); col 4 firm-controls -0.092 (.037) sits inside; huttunen2019 CROSS-CHECK (v1.37, recorded beside, NOT replacing: CITING 4 bands never shrink): Finland plant closures 1991-2000 (ILA matched employer-employee registers), child earnings at age 30 Table 2 col 3: -575.476 EUR (SE 278.543) on mean 25883.871 -> -2.2% (author prose), i.e. multiplier ~0.978 [1.96 SE band 0.957, 0.999]; males -2.4% (Table 6a: -762.501 SE 427.932 on 30647.315), females and displaced-mother households NULL (Table 6b/7); same-plant employment -0.006 (0.003) and same study choice -0.013 (0.006) at 25 -> operating channel is career/education choice, not skill formation (no GPA/crime effects, Table 4a). Nordic institutions + recession-cohort context; cross-jurisdiction spread vs the Canadian -9.2% anchor recorded honestly | | child_earnings->grandchild_earnings | structural | 0.55 [0.4, 0.6] | solon1992;corak2013;chetty2014 | US IGE literature | IGE band; composes in GAP SPACE: grandchild gap = 1 - IGE*(1 - child gap); BEHRMAN-TAUBMAN 1990 CROSS-CHECK (v1.14): PSID one-year-measure correlation 0.20 (elasticity ~0.07) vs correlations OVER 0.5 with longer-run income measures - the transitory-income attenuation Solon 1992 corrected; our multi-year IGE band [0.40,0.60] sits inside their long-run range and the one-year number documents why naive single-year IGEs bias low | | displacement->local_service_jobs | conditional | 5 [1.6, 5] | moretti2010 | US metros | LEVEL ratio: ~5 local service jobs per high-tech job lost (1.6 for manufacturing); applied as count*n, never chained as a multiplier | | school_spending->child_earnings | boundary | 1.07 [1.03, 1.1] | jackson2016 | US school-finance reforms | per +10% per-pupil sustained 12y -> ~+7% adult earnings; module normalizes by exposure fraction | | youth_wages->youth_crime | boundary | -1 [-1.5, -0.5] | gould2002;grogger1998 | US counties / young men | elasticity of youth crime participation w.r.t. local wages (~-1); band = rounding band, exact CI extraction queued | | displacement->infant_birth_weight | conditional | 0.9541 [0.912, 0.9981] | lindo2011 | US PSID children 1985+, husband displacement, mother fixed effects | Table 2 col 3 log birth weight -0.047 (SE 0.023) -> level multiplier exp(); 95% CI band; robustness cols 2-5: -0.041 to -0.047; effects concentrated below median birth weight (Fig 2); read via IZA DP 5213 | | import_shock->non_displaced_wage_spillover | boundary | -0.822 [-1.3042, -0.3398] | adh2013 | US commuting zones 1990-2007, noncollege workers OUTSIDE manufacturing, 2SLS state-clustered SE | REPLACED-queue-24 LANDED v1.12: THE SPILLOVER LINK - wage response of NON-displaced workers per $1,000/worker decadal import exposure. Table 7 Panel B col 6: -0.822 (SE 0.246) log pts per $1k -> 95% CI +/-1.96SE. All-workers nonmfg col 4: -0.761 (0.260). Pooled male TOTAL CZ wage response incl. the directly displaced (Table 6 col 2): -0.892 (0.294) - use that for the V1 total-response cross-check (V1 earnings row undershot ~5x; this link closes the gap). Authors caveat (note 39): CZ-average wages may understate composition-constant losses. Boundary-applied coefficient: NEVER chained | | family_income_shock->child_achievement_sd | conditional | 0.061 [0.0157, 0.1063] | dahl2012 | US children (NLSY79 mothers) ages 5-14, EITC instrumental variables | queue-8 LANDED v1.12: +$1,000 (year-2000 $) current family income -> +0.0610 SD combined math-reading achievement. AER Table 3 col (i), SE 0.0231, N=8609 published (8608 in NBER w14599; verified against published AER tables 2026-09-07, coefficient+SE identical), two-year differences (child FE); 95% CI = point +/- 1.96 SE. Sign: an income LOSS -> achievement LOSS (apply against a negative shock). Robustness Table 4 specs A-F: 0.053-0.086 all sig; lasting-effects Table 5: small/imprecise (effect mostly contemporaneous). PARALLEL stream: boundary-applied, never chained with the earnings-gap multiplier; CARNEIRO-LOPEZ-GARCIA-SALVANES-TOMINEY 2021 TIMING CORROBORATION (v1.15, Norway admin, fixed permanent income): income in EARLY (0-5) and LATE (12-17) childhood has high marginal productivity for child human capital; MIDDLE (6-11) is low; balanced profiles beat imbalanced. Structural-model quantities - deliberately NOT a composed row; it bounds which childhood window the model's income streams may claim to harm; bingley2026 CROSS-CHECK (v1.40): Danish plant-closure children (JEEA 2026) - displacement's math-achievement hit concentrates in below-median-income families and in breadwinner displacements; authors' mediation slope +0.0008 SD math per +1,000 DKK/year family income (p<.01); timing concentrated below age 5, matching the early/late-window productivity finding recorded above | | family_income_shock->life_expectancy_years | boundary | 0.1333 [0.1167, 0.15] | chetty2016 | US adults age 40, household earnings P15-P20 ($14k-$20k 2012 dollars), men+women averaged | queue-19 LANDED v1.12: LOCAL income-longevity slope for the earnings->life-years conversion. DERIVED FROM the paper own concavity example (Results): $14k->$20k (P15 vs P20), $161k->$224k (P90/P95), $224k->$1.95M (P95/P100) each carry +0.7 to 0.9 years; taking the P15-P20 bracket (the displaced-worker income range): 0.8/6 = 0.1333 y per $1k, band 0.7/6 - 0.9/6. The gradient is approximately LINEAR in income PERCENTILE and CONCAVE in dollars - this slope applies near the working-class income range and OVERSTATES per-$ gains higher up. HONESTY: association, not causal - authors state unmeasured confounding means causal effects are likely SMALLER; the model causal deaths stream stays anchored on sullivan2009 rate ratios, this row is a conversion/summary factor only. Sex-specific anchors from the same text: P1-P99 gap 14.6y men [14.4,14.8], 10.1y women [9.9,10.3]. Boundary-applied: NEVER chained | | male_earnings->marital_fertility | boundary | 1.24 [0.397, 2.083] | kearney2018fracking | US PUMAs, fracking boom 1997-2012, women 18-34, IV (shale reserves), PUMA-clustered SE | queue-7 LANDED v1.14: elasticity of ln(marital birth rate) w.r.t. ln(male earnings per capita) = 1.24 (SE 0.43), fracking boom IV (Table 8 Panel B col 2, women 18-34, N=32,704 PUMA-years, 1997-2012), 95% CI = 1.96SE. DECLARED CAVEATS: first-stage F=11.8 (weak-ish instrument); nonmarital births carry the SAME elasticity (col 3) - income moves births, NOT marriage (Table 4 finds no marriage response); cross-context anchor: Appalachian coal boom marital elasticity 0.75 (0.23) - the band brackets both. Read via NBER w23408; REStat 100(4):678-690 is the version of record. MODEL DIRECTION: this is a POSITIVE-income-on-births estimate - a displacement earnings LOSS applies it negatively (fertility falls). Boundary/elasticity composition; never a level chain. THORNTON 1980 CROSS-CHECK (v1.18): cross-generation fertility transmission, PSID two-generation OLS (Population and Environment 3(1):51-72, Table 3) - ACTUAL family size transmits near-null (siblings-of-husband -> total expected fertility: zero-order .070, standardized .058 with education controls, ns; parity sign-inconsistent across 1972 (-.044) and 1974 (.032)); IDEAL family size (preferences) transmits strongly (.282* zero-order, .237* with controls; unstandardized: +1 child in parental ideal -> child ideal +0.15, expected +0.08); parental economic status correlates negatively with child parity, attenuated by education controls. OBSERVATIONAL correlations - no parameter row licensable (CITING 1: quasi-experimental designs only); the model carries NO cross-generation fertility multiplier and this note is the recorded reason. Sample: couples married by 1971-1973 (N 293-566, Table 1) | | male_job_loss_rate->child_maltreatment | boundary | 6 [3.65, 8.35] | lindo2018maltreatment | California counties, child-maltreatment reports, county-year panel, county-clustered SE | queue-14 LANDED v1.16: +1pp male mass-layoff rate -> +6.0% child-maltreatment reports (SE 1.2), Table 3 Panel A col 3 (preferred: county controls + county linear trends), Poisson semi-elasticity, California counties, N=817 county-years, county-clustered SE, 95% CI = 1.96SE. GENDER SCOPE (declared): the FEMALE mass-layoff coefficient is opposite-signed (-6.5% in the same spec) per the authors' family-time-use framework - this row models the male-shock channel, matching the displacement pool's male skew; do NOT apply to female-shock scenarios. Overall unemployment rate is NEGATIVELY associated (-2.1 to -2.4%, Table 2) - endogeneity warning the authors themselves flag; the mass-layoff quasi-experiment is the identification. Cross-stream corroboration: raphael2001 (male job loss -> property crime). Read via NBER w18994; JPubE 163:77-98 is the version of record. Boundary-applied: NEVER chained | | displacement->grade_retention_hazard | conditional | 1.1473 [1.0119, 1.2827] | stevens2011 | US children 5-19 (SIPP 1996/2001/2004 panels), head-of-household involuntary job loss (fired/discharged, employer sold/bankrupt, slack work), child fixed effects, N=167,449 child-years / 2,170 displaced children / 1,196 job losses | queue-12 LANDED v1.20. QUEUE TARGET CORRECTED: the paper has NO math/reading test scores - the outcome is grade retention, the authors' own proxy for academic difficulties (correlated with test scores per McCoy-Reynolds 1994; causal-retention literature Jacob-Lefgren 2009 cited). VENUE CORRECTED: version of record is Economics of Education Review 30(2):289-299 (Crossref-verified); the queue and prior bib said Sociology of Education 84(3):201-223 - no such Crossref record exists. Full text read via NBER w15480. Anchor: Table 4 col 1 (full sample, child FE), head's job loss one or more years ago +0.0081 (SE 0.0038) on the 0.055 sample average = +0.8pp ~ +15% relative; multiplier = 1 + 0.0081/0.055 = 1.147, 95% CI from 1.96SE scaled by the same base. TIMING STRUCTURE (the identification): current-year coefficient 0.0032 (0.0040) is null - children are not coded as repeating until the second attempt year, so only the lagged coefficient carries the causal effect; no pre-trend. HETEROGENEITY (Table 5): effects concentrated where the head has HS education or less (+0.0099, 0.0058) vs some-college +0.0026 (0.0039, ns) - the model's displaced population skews less-educated, so the full-sample point is if anything conservative for them. Income mechanism measured in-sample: family income -10.9% (SE 2.8pp) 1+ years after loss (Table 3). PARALLEL STREAM: grade retention is a school-progress indicator in hazard space, NOT child_achievement_sd - never compose with the dahl2012 income mechanism row or the earnings-gap multiplier. Boundary-applied: NEVER chained | | eviction_order->emergency_shelter_use | boundary | 4.778 [1.076, 8.48] | collinson2024 | US eviction-court cases (compliers), Cook County + NYC, heads 18-55, judge-leniency IV (first-stage F=934/288) | queue-17 LANDED v1.21. QUEUE TARGET CORRECTED: version of record is collinson2024, QJE 139(1):57-120 (Crossref-verified) - the queue named the Collinson & Reed 2018 WP, which the QJE paper subsumes; read via NBER w30382 (rev. July 2023). Emergency-shelter use in the FIRST YEAR after filing: IV +3.4pp (SE 1.7) on the 0.9% non-evicted base = rate ratio (0.009+0.034)/0.009 = 4.78; 95% band = 1.96SE on the delta rescaled by the same base. Table V col 3 (combined equal-weighted two-city estimates; Cook County +2.3pp / NYC +4.6pp separately - NYC larger, consistent with right-to-shelter). TIMING: the acute spike is year-1 concentrated - year-2 emergency-shelter IV is null (-0.1pp, SE 1.3) but ANY homelessness services stays elevated in year 2 (+3.6pp, SE 1.5, on the 1.2% base) - transition out of acute shelter into persistent service contact. CROSS-CHECK: the superseded NYC-only C&R 2018 design measured shelter APPLICATION (right-to-shelter, broader): IV +12.7pp (SE 6.2) on a 3.4% application base - different outcome, same direction. PARALLEL STREAM: hazard-space outcome; NEVER composed with the worker_earnings multiplier or chained into the child streams. Boundary-applied: NEVER chained | | foreclosure_order->house_price_gap | boundary | 0.99 [0.9875, 0.9925] | campbell2011 | US all-type house transactions, Massachusetts 1987-2008 (1.78M sales; Warren Group), reference distance 0.05 miles | queue-18 LANDED v1.22: forced-sale price spillover. POINT is the authors' PREFERRED estimate: each foreclosure ~0.05 miles away lowers the price of a house by about 1% (lead-vs-lag difference-in-difference in the Leigh-Rockoff style: foreclosures within 0.1mi before the sale vs within 0.1mi after, inner-circle 0.1mi vs outer-ring 0.25mi; zero distance -2%, 0.05mi -1%). Stored as a gap multiplier: 1 - 0.01 = 0.99. BAND: the preferred DiD reports NO standard error, so the band is the rounding band (point +/-25%, CITING section 3 rule 3 phrasing) with the SE-carrying hedonic associates recorded beside, NOT averaged in: per foreclosure within 0.25mi year-before-sale -1.8% (col 1), -1.1% controlling recent neighborhood unforced prices (col 2); 0.1mi distance-weighted at zero distance -9.1% (col 1) / -7.3% (col 2) - clustering-inflated per the authors' own diagnosis, recorded to bound the same-location tail (their 99.9th-percentile dummies reach -21% to -26%). PERSISTENCE (Table 14): lagged foreclosures keep comparable coefficients a year out - spillovers are not transitory liquidity discounts. HETEROGENEITY (Table 13): larger for single-family and condos, absent for multifamily; larger for cheap houses in cheap zipcodes (vandalism mechanism). AGGREGATE (their 2008Q1 calculation): typical foreclosure cost $46,000 on the foreclosed house + $406,000 total on neighbors (col-2 model) or $110,000 (DiD). IDENTIFICATION LIMIT (authors' own statement): no instrument found; estimates are NOT structural - timing (lead vs lag) and distance gradient are the only quasi-experimental handles, so this lands as a PARALLEL-STREAM boundary-applied level response, never composed into the earnings/child chains (housing-contagion composition is a queued P3 item). CLASS/VERSION CAVEAT: read via NBER w14866 (April 2009 pre-publication draft); the published AER 2011 abstract confirms the preferred estimate (about 1% at 0.05mi) and the 27% foreclosure discount - table-level numbers are the WP's, tier therefore EXACT-results not EXACT. QUEUE TARGET CORRECTED: venue is AER 101(5):2108-31, NOT QJE 126; Immergluck & Smith 2006 (Housing Studies) is their CRIME paper - the price-spillover study is Immergluck & Smith 2005 Woodstock report / Housing Policy Debate, unread, recorded as a cross-check lead only | | local_unemp_shock->household_ipv | boundary | 1.58 [1.49, 1.58] | schneider2016 | mothers of the Fragile Families birth cohort (1998-2000 births in 20 large US cities), Waves 3-5 pooled person-waves (2001-2010), all-mothers sample including unpartnered; N=10,656 area models / 10,584 distress models; UR shock 1.0=flat, 2.0=doubling | queue-22 LANDED v1.24: Table 3, violent-or-controlling outcome. Logistic coeff .454* (p<.05) per unit of the 12-month UR change (1.0 = doubling); LDV .401*, FE .406* - the band is the exp() range across the three specs (1.49-1.58); the point is Model 1 (logit), the paper's headline spec. Authors' own predictions: UR worsening 50% -> prevalence 10%->12%; UR doubling -> 14% (prevalence ratios 1.2/1.4, recorded here). Controlling-only coefficients: .472*/.482*/.453* (logit/LDV/FE). IDENTIFICATION: area-level unemployment is exogenous to individual traits; LDV and individual-FE specs; cluster-robust SEs by city. LEVEL-NULL discipline: the UR LEVEL (12-month average, Table 8) is null on all three outcomes - only the 12-month CHANGE moves abuse; recorded so no surface wires the level. Violent-only is null for BOTH unemployment measures; hardship->violent is the authors' own reverse-causality concern (violent behavior dis-orders household finances). FE: couple-unemployment magnitude unchanged, hardship magnitude reduced (controlling) but still significant. CLASS: observational regression coefficients = points (CITING section 1); no SEs printed in the text, bands declared. PARALLEL STREAM: boundary-applied shock responses - NEVER chained into the earnings/IGE chains | | household_hardship->household_ipv | boundary | 2.14 [1.61, 2.68] | schneider2016 | mothers of the Fragile Families birth cohort (1998-2000 births in 20 large US cities), Waves 3-5 pooled person-waves (2001-2010), all-mothers sample including unpartnered; N=10,656 area models / 10,584 distress models; hardship = 1+ of 10 material-hardship items, past 12 months | queue-22 LANDED v1.24: Table 1 Model 1 prose predictions - hardship -> violent-or-controlling prevalence 15% vs 7% (point 2.14); controlling-only 13% vs 7%; violent-only 2% vs 0.05% (reverse-causality-flagged above). Table 1 coefficients (scrambled by text extraction; ~OR 2.15-2.31 across logit/LDV/FE) NOT used for the band - the band is the declared rounding band +/-25% (campbell2011 precedent). IDENTIFICATION: area-level unemployment is exogenous to individual traits; LDV and individual-FE specs; cluster-robust SEs by city. LEVEL-NULL discipline: the UR LEVEL (12-month average, Table 8) is null on all three outcomes - only the 12-month CHANGE moves abuse; recorded so no surface wires the level. Violent-only is null for BOTH unemployment measures; hardship->violent is the authors' own reverse-causality concern (violent behavior dis-orders household finances). FE: couple-unemployment magnitude unchanged, hardship magnitude reduced (controlling) but still significant. CLASS: observational regression coefficients = points (CITING section 1); no SEs printed in the text, bands declared. PARALLEL STREAM: boundary-applied shock responses - NEVER chained into the earnings/IGE chains | | couple_unemployment->household_ipv | boundary | 1.3 [1.04, 1.63] | schneider2016 | mothers of the Fragile Families birth cohort (1998-2000 births in 20 large US cities), Waves 3-5 pooled person-waves (2001-2010), all-mothers sample including unpartnered; N=10,656 area models / 10,584 distress models; either partner unemployed and looking | queue-22 LANDED v1.24: Table 1 Model 1 prose predictions - couple unemployment -> violent-or-controlling prevalence 13% vs 10% (point 1.3); controlling-only 12% vs 9%; violent-only ns. Table 1 logit coeff .404** (OR ~1.50); FE magnitude unchanged (stronger survival than hardship). Disaggregation (results on request): one-partner and both-partner unemployment both significant in logit/LDV, n.s. in FE; male-partner coefficients ~50% larger than mother-own for controlling outcomes (Table 2) but male/female-specific FE estimates n.s. IDENTIFICATION: area-level unemployment is exogenous to individual traits; LDV and individual-FE specs; cluster-robust SEs by city. LEVEL-NULL discipline: the UR LEVEL (12-month average, Table 8) is null on all three outcomes - only the 12-month CHANGE moves abuse; recorded so no surface wires the level. Violent-only is null for BOTH unemployment measures; hardship->violent is the authors' own reverse-causality concern (violent behavior dis-orders household finances). FE: couple-unemployment magnitude unchanged, hardship magnitude reduced (controlling) but still significant. CLASS: observational regression coefficients = points (CITING section 1); no SEs printed in the text, bands declared. PARALLEL STREAM: boundary-applied shock responses - NEVER chained into the earnings/IGE chains | | neighborhood_exposure->child_outcomes_modifier | structural | 0.037 [0.031, 0.043] | chettyhendren2018 | children of families moving across counties (US tax data, births 1980-88); county-level predictions of permanent residents' income ranks at age 24 | queue-23 LANDED v1.30: annual childhood exposure effect gamma, Appendix Table V Column 1 (county level, baseline spec): gamma = 0.037 (SE 0.003), N = 595,244. Interpretation quoted verbatim from the paper: the impact of spending an ADDITIONAL YEAR of childhood in a county where children of permanent residents have 1 percentile point higher income ranks (at a given level of parental income). CZ-level baseline (Table II col 1) = 0.040 (SE 0.002, N = 1,553,021) recorded beside; county-level is the pin because places.csv is county geography and the authors note gamma is SMALLER at smaller geographies (selection stronger within CZs). DOSE: the engine multiplies by a declared 18-year complete childhood (DOSE_YEARS, place.py) = 0.666 pickup per 1 percentile gap vs national; the paper's own full-childhood extrapolation (birth movers to age 20 pick up ~80%, abstract + sec IV) brackets this. Dose years differ from the paper's age-23 window - DECLARED in place.py. Family FE = 0.033 (SE 0.011), time-varying controls 0.032 (SE 0.011), age-orthogonal 0.036 (SE 0.005): robust. Similar exposure effects on college attendance, marriage, teen birth (abstract) - only the income-rank effect is landed. Outcomes converge LINEARLY in exposure; place effects act through time spent, not age of arrival. Band = reported SE x 1.96 = [0.0312, 0.0428] rounded [0.031, 0.043]. APPLIED TO: child-window adult-outcome multipliers (child_earnings and the generation line), via the place multiplier; the displacement penalty and the place modifier compose MULTIPLICATIVELY - a declared modeling assumption, not a claim of the paper | | unconditional_income->child_education_years | boundary | 1.127 [0.247, 2.007] | akee2010 | children in Eastern Band of Cherokee area households previously in poverty (Great Smoky Mountains Study, age cohorts 9/11 at wave 1), treated by ~$4,000/yr per adult member for four pre/post childhood survey waves | queue-25 LANDED v1.32: Table 4 col 1 (households previously in poverty), years of education at age 21 = +1.127 (SE 0.449, 1% level), OLS, N=1045 - the abstract's '+1 year at age 21 for the poorest households'. Per-treatment dose: four additional years of the ~$4k/y exogenous transfer; the dose lives in the exposure description, never a per-dollar chain step. SCOPE (never averaged away): full-sample coefficient is 0.379 (SE 0.447, n.s. - Table 3 col 1) because households NEVER previously in poverty show null/negative effects (Table 4 cols 3-4: -0.166 ns / +0.129 ns); the effect concentrates where poverty already binds. Robustness (fn18 predicted-poverty sample, N~600): 1.273 (1% level). GENDER OF RECIPIENT: mother-receipt drives it (Interaction 1 = 1.48, SE 0.606, 5% level; father-receipt n.s.) - consistent with Duflo 2003; declared. Companion HS-grad row: prob of HS graduation by age 19 +0.391 (SE 0.135, 1% level, T4 col 2) - the authors note the HS effect reads like a conditional-cash incentive (children become payment-eligible at 21 only via diploma-or-wait). MECHANISM (Table 8): parental supervision +0.062 (0.023)***/activities-with-mother +0.069 (0.024)***, maternal labor force participation NULL (Table 7: +0.069/−0.089 n.s.) - income, not employment, is the channel. OBSERVATIONAL CROSS-CHECK (barred from a point by CITING SS1) recorded on the queue-9 refusal: zg2012 Table S5 col 1 - prenatal-age-2 income +$10k/y among <$25k families -> ln adult annual earnings +0.63 (SE 0.21), age 3-5 +0.34 (0.21) n.s. | | unconditional_income->youth_any_crime | boundary | -0.224 [-0.377, -0.071] | akee2010 | same population as the education row (previously-poor eligible households; arrests from administrative records merged at the individual level) | queue-25 LANDED v1.32: Table 6 col 1, probit marginal effect on committing ANY crime (arrest) at ages 16-17 = -0.224 (SE 0.078, 1% level), N=1093 - the abstract's 'reduces having ever committed a minor crime by 22% at ages 16-17' (the abstract conflates: T6 shows the 22% on ANY arrest at 16-17 and 18% on ever-minor by 21; both landed as separate rows). AGE WINDOW (declared): the effect exists ONLY while the child is a MINOR - ages 18-19 (-0.068, SE 0.072) and 20-21 (+0.051, SE 0.075) are NULL, consistent with parental control ending at majority; no surface may generalize this row past 18. OFFENSE TYPE: the reduction is MINOR-CRIME ONLY (ever-moderate -0.002 n.s., ever-violent +0.002 n.s.) - an entry effect: income changes WHETHER a child enters criminality, not the NUMBER of crimes once entered (count regressions n.s.). Male-driven (little female criminality overall). Robust to a casino-distance interaction (fn21: -0.299 with distance interaction, 1% level). Boundary-applied, never chained | | unconditional_income->youth_minor_crime_ever | boundary | -0.179 [-0.353, -0.005] | akee2010 | same population as the education row (previously-poor eligible households) | queue-25 LANDED v1.32: Table 6 col 4, prob of EVER committing a minor crime (disorderly conduct, trespassing, shoplifting) by age 21 = -0.179 (SE 0.089, 5% level), N=1045. Panel design: the treatment covers four pre/post childhood waves; effect = reduced ENTRY into criminality (counts-of-crimes regressions n.s. by category). Moderate/violent nulls beside (see the any-crime row); males-only analysis holds for minor crimes with diminished significance and strengthens for moderate. Band = 1.96 SE. Boundary-applied, never chained | | youth_crime_conviction_share->youth_crime_convicted | boundary | 0.061 [0, 0.123] | damm2014 | male refugee children in Denmark assigned quasi-randomly to municipalities 1986-1998 (avg age at assignment 9; N=4,425) | queue-24 LANDED v1.33 (queue target CORRECTED: the paper has NO clean exposure-duration elasticity - age at assignment is perfectly correlated with potential exposure years and the age-cohort splits confound duration with age, authors' own caveat; the landed number is the per-1pp conviction-SHARE exposure effect). Table 3 panel A, spec 5 (municipality FE - the authors' identification-focused spec isolating crime from fixed area characteristics): +0.043 probability points per 1 SD (0.70pp) of the area youth-crime conviction rate, SE 0.022 -> per 1pp: 0.061 (SE 0.031), band 1.96 SE; the band's lower edge rounds to 0.000 (the FE-spec SE leaves the interval at the no-effect line). Conservative spec 4 (full controls incl. police efficiency, no FE) recorded beside: 0.033/1pp (SE 0.017). RELATIVE scaling (paper prose): per 1pp -> +7-13% on the 46% male base conviction probability; count-of-convictions row beside: 0.169/0.70 = 0.241 convictions per 1pp (spec 5, SE 0.138). AGE-COHORT shape (declared): ages 10-14 at assignment most affected; <6 small/large SE. FEMALE NULL (declared, panel B - all specs n.s.). OPERATIVE-CHANNEL discipline (Table 6): the COMMITTED-crime rate is a NULL - only the share of CONVICTED YOUTH moves children; violent share is the operative crime type (property/drugs null, Table 5); co-national share channel (Table 7: co-nationals +0.023 per SD, immigrant shares null - social interaction via co-nationals). Boundary-applied, never chained. Read via Aarhus WP 2013-17 (Sept 2013 draft of the AER 104(6) version of record) | | youth_violent_crime_conviction_share->youth_crime_convicted | boundary | 0.366 [0.143, 0.589] | damm2014 | same population as the overall-share row (male refugee children, quasi-random municipality assignment, N=4,425) | queue-24 LANDED v1.33: Table 5 panel A col 2 (spec 5, municipality FE): +0.045 probability points per 1 SD (0.123pp) of the VIOLENT youth-crime conviction rate (mean 0.286%), SE 0.014 -> per 1pp: 0.366 (SE 0.114), band 1.96 SE. Spec 4 beside: 0.276/1pp (SE 0.089, 1% level). The violent share is the paper's OPERATIVE finding (abstract: 'in particular violent crimes'); property (0.029/0.528pp n.s.) and drug (null) shares recorded as nulls - the effect is peer CONVICTION exposure, not crime volume. FEMALE NULL (declared). Education null + 'active' decline by 23-25 recorded as longer-term context (Table 8), not landed. Boundary-applied, never chained; the violent share is a thin LEVEL (mean 0.286%) - never chained from a crime-count delta. Read via Aarhus WP 2013-17 (Sept 2013 draft of the AER 104(6) version of record) | | displacement->circulatory_mortality_hazard | conditional | 1.54 [1.29, 1.83] | browningheinesen2012 | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | queue-sweep READ+LANDED v1.38: Browning & Heinesen 2012 (J Health Econ 31(4):599-616), Tables 6.1/6.2, cumulative hazard ratios years 1-4 after base year. Circulatory death. MI-or-stroke 1-4y 1.58 [1.24, 2.00] (Table 6.2); All-circulatory 1-20y 1.16 [1.07, 1.25] remains significant (Table 6.1); MI-or-stroke 1-20y 1.09 [0.97, 1.23] is null-compatible (Table 6.2). Year-1 peak beside. Propensity score weighting + non-parametric duration analysis; band = reported 95% CI on the cumulative hazard ratio. dist withheld: the reported hazard-ratio CI is asymmetric around the point; a symmetric sampler would fabricate the shape. Boundary-applied: NEVER chained. Source version rechecked 2026-10-14: 2011 AKF working paper hosted by VIVE, Tables 6.1/6.2 (PDF pages 23/25), SHA256 85465f4715493cce44be9fb78ddc1ecf08e838bc69b74858575e2fc6724ca164; the 2012 JHE citation identifies the published study, not a verified published-version extraction; REPLICATIONS (v1.43): bloemen2018 Dutch LPM circulatory +0.2453pp within 5y (SE 0.0975, p=.012) = +52.8% relative, cerebrovascular +0.0875pp (SE 0.0427) = +152.9% - the stress/circulatory channel corroborated across countries; eliasonstorrie2009 male <=4y circulatory 1.24 [0.90, 1.71] n.s. - direction consistent, imprecise; Publication tier corrected to canonical under CITING section 1: source is the 2011 working paper; published-version reconciliation remains queued. | | displacement->alcohol_mortality_hazard | conditional | 1.62 [1.09, 2.41] | browningheinesen2012 | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | queue-sweep READ+LANDED v1.38: Browning & Heinesen 2012 (J Health Econ 31(4):599-616), Tables 6.1/6.2, cumulative hazard ratios years 1-4 after base year. Alcohol-related death (psychiatric + somatic: poisoning, addiction, liver, pancreas). The deaths-of-despair channel. 1-20y 1.15 [0.96, 1.38] n.s. - the effect concentrates in the first years. Year-1 peak beside. Propensity score weighting + non-parametric duration analysis; band = reported 95% CI on the cumulative hazard ratio. dist withheld: the reported hazard-ratio CI is asymmetric around the point; a symmetric sampler would fabricate the shape. Boundary-applied: NEVER chained. Source version rechecked 2026-10-14: 2011 AKF working paper hosted by VIVE, Tables 6.1/6.2 (PDF pages 23/25), SHA256 85465f4715493cce44be9fb78ddc1ecf08e838bc69b74858575e2fc6724ca164; the 2012 JHE citation identifies the published study, not a verified published-version extraction; Publication tier corrected to canonical under CITING section 1: source is the 2011 working paper; published-version reconciliation remains queued. | | displacement->external_cause_mortality_hazard | conditional | 1.53 [1.15, 2.04] | browningheinesen2012 | Danish full-time male workers age 20-60 with strong labor-market attachment displaced by plant closures 1986-2002 (base years 1985-2001; propensity-score weighted matched controls; Danish full registers 1980-2006) | queue-sweep READ+LANDED v1.38: Browning & Heinesen 2012 (J Health Econ 31(4):599-616), Tables 6.1/6.2, cumulative hazard ratios years 1-4 after base year. External causes (incl. suicide, traffic). Suicide year-1 4.31 [1.64, 11.37] (15 deaths - wide), suicide-or-traffic 1-4y 1.74 [1.21, 2.48] (Table 6.2); 1-20y 1.20 [1.01, 1.42]. Cancer intervals include 1 across reported horizons (year-1 point 1.38, CI spans 1); null-compatible does not establish zero - cause-specific discipline: not all causes move. Year-1 peak beside. Propensity score weighting + non-parametric duration analysis; band = reported 95% CI on the cumulative hazard ratio. dist withheld: the reported hazard-ratio CI is asymmetric around the point; a symmetric sampler would fabricate the shape. Boundary-applied: NEVER chained. Source version rechecked 2026-10-14: 2011 AKF working paper hosted by VIVE, Tables 6.1/6.2 (PDF pages 23/25), SHA256 85465f4715493cce44be9fb78ddc1ecf08e838bc69b74858575e2fc6724ca164; the 2012 JHE citation identifies the published study, not a verified published-version extraction; REPLICATIONS + HETEROGENEITY (v1.43): eliasonstorrie2009 male <=4y external causes 2.07 [1.42, 3.02] and suicide 2.15 [1.28, 3.59] corroborate the deaths-of-despair channel; bloemen2018 DIVERGES - external-except-suicide -0.0389pp (SE 0.0176) and suicide +0.0063 n.s. - cause-specific patterns are country/period-heterogeneous, declared, never averaged; Publication tier corrected to canonical under CITING section 1: source is the 2011 working paper; published-version reconciliation remains queued. | | displacement_event->spouse_mental_health_sd | conditional | -0.194 [-0.327, -0.061] | marcus2013 | spouses of displaced workers, German couples (SOEP 2002-2010), 109 displaced-worker couples vs >14,000 entropy-balanced controls; MCS normed mean 50 SD 10 | queue-sweep READ+LANDED v1.38: Marcus 2013 (J Health Econ 32(3):546-558), Table 3 spec 4 (entropy-balancing DiD, ~11 months after closure): spouse MCS -1.94 (SE 0.68) = -0.194 SD. OWN EFFECT beside: -2.72 (0.74) = -0.272 SD, recorded as a paul2009 cross-check (inside the causal-clean factory-closure subset); own-vs-spouse difference p=0.38 - the spillover is as large as the displaced worker's own effect. Husband-displaced spouses -2.09 (0.78), wife-displaced -1.67 (0.78). PLACEBO: closure WITHOUT unemployment own -0.77 n.s. - the unemployment experience, not the event, carries it (declared). Band = 1.96 SE. Read via SOEPpapers 488 (2012 WP draft of the JHE version of record; damm2014 read-via precedent). Boundary-applied: NEVER chained | | displacement_event->child_achievement_sd | conditional | -0.0206 [-0.0402, -0.001] | bingley2026 | children exposed to parental plant closure age 0-16 (average across exposure stages), Denmark, conditional on taking grade-9 exams; mathematics | queue-sweep READ+LANDED v1.40: Bingley, Cappellari & Ovidi, JEEA (advance article 2026, DOI 10.1093/jeea/jvag048), Danish admin registers, displaced-parent plant closures matched to controls, children age 0-16 at closure. Point = Table 4 col 2 (preferred: baseline covariates, SE clustered at family) 'Treated X Exposure (age 0-16)': teacher grade in mathematics -0.0206 SD (SE 0.0100); band = 1.96 SE. BESIDE: exam test scores -0.0117 n.s. (SE 0.0101); Danish/language smaller and n.s. - the GPA decline is math-driven. TIMING STRUCTURE (the paper's headline; travels in notes - the model has no age-at-exposure selector): infancy (0-1) -0.0521 (SE 0.0154; 1.96SE -0.0823..-0.0219); early childhood (2-5) -0.0184 n.s.; mid (6-11) -0.0073 n.s.; late (12-16) -0.0274 (SE 0.0118) - concentrated before age 5 and again in adolescence. MECHANISM (declared, income channel): hit concentrates in below-median-income families and when the displaced parent is the breadwinner (main-earner infancy ~-0.07 both measures; maternal-breadwinner infancy -0.2 grades); authors' mediation: +1,000 DKK (~EUR 150) per year family income -> +0.0008 SD math (p<.01) - recorded as the dahl2012 cross-check; maternal time investment partially offsets. LEFT-TAIL beside: non-completion +0.54pp avg on 7.85% control mean (own row); upper-secondary enrolment at 17 -1.6pp infancy (6.5% of control mean). Read via IZA DP 16367 (Aug 2023 WP draft of the JEEA version of record; marcus2013/damm2014 read-via precedent). Conditional: transport assumes Danish institutions/welfare, plant-closure identification, grade-9 timing | | displacement_event->hs_completion | conditional | -0.037 [-0.0801, 0.0061] | brand2014 | children of single mothers, US NLSY79 (NLSY79 women's children), MATERNAL job displacement at child age 0-17 (PSM kernel TT); outcome = HS completion by age 19, control mean 0.760 | LANDED v1.42 (user-directed node design 2026-09-13): Brand & Simon Thomas 2014 (AJS 119(4):955-1001), Table 3 kernel-matching TT: -0.037 (SE 0.022), p<.10 - the band honestly crosses zero. TIMING (Table 6 TT): age 0-5 -0.004 n.s.; 6-11 -0.016 n.s.; adolescence 12-17 -0.115** (SE 0.040; 1.96SE -0.1934..-0.0366) - an ADOLESCENCE effect; the always-exposure point stays the row because the model has no age-at-exposure selector. Beside: unmatched difference -0.053; TUT -0.052 - TUT>TT everywhere: effects LARGEST for children of LOW-displacement-propensity mothers (SM strata confirm; opposite gradient to bingley2026's income concentration). DESIGN DECLARED: propensity-score kernel matching = selection on observables, the weakest identification class in this parameter set (no quasi-experimental variation) - corroboration of the grade-retention/achievement streams, never an anchor. Read via PMC4372265 author manuscript of the published AJS version of record. Conditional: transport assumes the US single-mother NLSY79 cohort and the PSM design | | displacement_event->college_attendance | conditional | -0.063 [-0.1081, -0.0179] | brand2014 | same scope as the hs_completion row; outcome = some college attendance by age 21-22, control mean 0.427 | LANDED v1.42, same read as the hs_completion row: Table 3 kernel TT -0.063 (SE 0.023), p<.01; band = 1.96 SE. TIMING (Table 6 TT): 0-5 -0.032 n.s.; 6-11 -0.082* (SE 0.034); 12-17 -0.099* (SE 0.039). Beside: unmatched -0.089; TUT -0.099***. ESTIMAND DISCIPLINE: a stock (ever some college by ~21) - DISTINCT from the hilger2016 college_enrollment annual-flow node; the two must never be merged or converted. Conditional: same cohort/design transport as the hs_completion row | | displacement_event->college_completion | conditional | -0.036 [-0.0674, -0.0046] | brand2014 | same scope as the hs_completion row; outcome = college completion (BA) by age 25, control mean 0.169 | LANDED v1.42, same read as the hs_completion row: Table 3 kernel TT -0.036 (SE 0.016), p<.05; band = 1.96 SE. TIMING (Table 6 TT): 0-5 -0.035 n.s.; 6-11 -0.027 n.s.; 12-17 -0.052 (SE 0.027, p<.10). Beside: unmatched -0.051; TUT -0.043*. The paper reports NO propensity trend for this outcome (unlike HS/attendance). Conditional: same cohort/design transport as the hs_completion row | | displacement_event->adult_depression_cesd | conditional | 0.025 [0.0034, 0.0466] | brand2014 | same scope as the hs_completion row; outcome = CESD 7-item depressive-symptom index (0-1) at ages 25-29, control mean 0.208 | LANDED v1.42, same read as the hs_completion row: Table 3 kernel TT +0.025 (SE 0.011), p<.05 on the 0-1 index; band = 1.96 SE. Beside: CESD ages 20-24 +0.014 n.s. (SE 0.009); unmatched +0.030**; TUT +0.034**. TIMING (Table 6 TT): 0-5 -0.021 n.s.; 6-11 +0.047** (SE 0.017); 12-17 +0.034 (SE 0.019, p<.10); adolescence also raises CESD 20-24 (+0.031*, SE 0.015). CHANNEL: the displacement event transmits psychological distress to the CHILD into adulthood - the adult-child complement of spouse_mental_health_sd (partner) and unemployment_status->mental_health_sd (worker); direction-consistent, distinct unit (0-1 index, not SDs). Conditional: same cohort/design transport as the hs_completion row | | displacement_event->spouse_participation_elasticity | conditional | -0.04 [-0.07, -0.03] | halla2020 | married couples, Austrian ASOS registers 1990-2007, HUSBANDS displaced by firm closure/mass layoff vs non-event firm controls; wife's labor-force participation response | LANDED v1.43 (sweep #3): Halla, Schmieder & Weber 2020 (AEJ:Applied 12(4):253-287, DOI 10.1257/app.20180671), Table 9 eta-participation + text: full-sample participation elasticity ~-0.04; subgroup range -0.03 (small-shock households) to -0.07 (previously-inactive wives, Table 6) - the BAND IS THE PAPER'S SUBGROUP RANGE, not a CI (dist empty). THE ADDED-WORKER EFFECT IS SMALL: one order of magnitude below the AWE-literature average (-0.4, the paper's own Table A1 survey); husbands lose 21-24% earnings / 16-17% employment over 5y while wives' employment rises ~1% (extensive margin only - NO intensive-margin response among already-employed wives); the response recovers a tiny fraction of the household loss; most responsive: mothers with children 3-15; zero response among childless wives/very young children; local labor markets condition it (no response when male unemployment above median). Read via IZA DP 11752 (WP draft of the AEJ version of record; read-via precedent). Conditional: Austrian institutions/UI generosity, married couples, closure/layoff identification | | displacement_event->annual_birth_response | conditional | -0.005 [-0.0089, -0.0011] | huttunenkellokumpi2016 | couples, Finnish FLEED registers, WOMEN displaced by plant closures (base years 1991-1993) vs matched non-displaced; outcome = couple's probability of a birth in the year | LANDED v1.43 (sweep #4): Huttunen & Kellokumpi (Journal of Labor Economics 34(2), 2016, DOI 10.1086/683645 - VENUE CORRECTED from the sweep's 'Labour Economics'), IZA DP 6707 Table 3 'Gave birth' column, plant-closure sample: displacement-year marginal effect -0.005 (SE 0.002), p<.01; band = 1.96 SE on a ~10%/yr base (~5% relative reduction). Timing: year-3 -0.005** (0.002) recurs; years 2, 4-11 individually n.s. - the effect CUMULATES: ~-4 births per 100 displaced women by year 11 (Figure 6 event study; high-education women -0.05; low-education null - career-concern channel, NOT income: the couple's income drop does NOT predict the fertility response). MALE NULL declared beside (Table 4 'Gave birth': plant-closure dpl1 -0.002 (0.002) n.s.; mass-layoff -0.003*) - consistent with halla2020's husband-displacement births null (-0.001, SE 0.001). Distinct treatment from the shipped kearney2018fracking row (local-shock elasticity, never merged). Read via IZA DP 6707 (WP draft of the JLE version of record; read-via precedent). Conditional: Finnish registers, deep-recession displacement window (1991-93), women 20-40 | | displacement_event->child_depression_anxiety | conditional | 0.008 [0.0002, 0.0158] | schallerzerpa2019 | children ages 6-17, US MEPS, PATERNAL job loss (tenured-father sample, >=1y tenure), individual-FE LPM; outcome = child depression/anxiety report | LANDED v1.43 (sweep #5): Schaller & Zerpa 2019 (American Journal of Health Economics; NBER w21745), Table 2 MENTAL HEALTH panel, father-displaced tenured column: +0.008pp (SE 0.004), p<.05; band = 1.96 SE on a small base (~100-150% relative increase per the authors). SPEC SENSITIVITY declared: firm-closure-only +0.006* (0.004), all-involuntary +0.002 n.s. - the effect concentrates where identification is strongest but imprecision grows. Beside: child mental-health-'excellent' report FALLS - father closure -0.044** (0.021), mother tenured -0.038** (0.017), mother closure -0.058** (0.026); physical health-'excellent' father closure -0.051*** (0.017); MATERNAL depression/anxiety NULL declared (-0.004/-0.006/+0.003 all n.s.) - the paternal stress channel is the operative one, opposite to the fertility stream (maternal displacement operates there, huttunenkellokumpi2016) and the education stream (maternal, brand2014). THE CHILD'S OWN SHORT-RUN MENTAL HEALTH - distinct from adult outcomes (adult_depression_cesd ages 25-29, brand2014) and from the spouse's (marcus2013). HONESTY BESIDE (mork2019, Swedish workplace closures, registers, 10y): child hospitalization/mortality NULLS (maternal +1.8/1000 = +0.6% n.s.; paternal mental/behavior admissions -2.8/1000 = -8.3%, a DECLINE), paternal education NULLS; maternal GPA/HS negatives carry similar pre-trends and are questioned by the authors themselves - survey-vs-register outcome scope declared. Read via NBER w21745 (WP of the AJHE version of record; read-via precedent). Conditional: US MEPS survey reports, short-run window | | child_achievement_sd->grandchild_achievement_sd | structural | 0.38 [0.38, 0.42] | blackdevereuxsalvanes2009 | Norway male conscripts (IQ at age 18, father-son) | father-son IQ correlation .38: 'The correlation we observe between father's IQ and that of his son is .38' (IZA DP 3651 p.8; identical to the Boucher & McGue 1981 weighted average). STANDARDIZED SLOPE: composes sd shifts linearly (linear_shift kind). CAVEAT carried from the authors: the correlation 'has no causal interpretation whatsoever' (p.9) - a displacement-induced shift is not assumed to transmit causally; this is a structural transmission assumption like the IGE band. Band pinned, not widened: lower edge = the single-measure replications (.38 here = .38 Boucher-McGue); upper edge = Bowles-Gintis 2002 lower bound .42 (their .42-.72 range uses two-parent averages, inflated per BDS p.8). IQ-at-18-to-achievement and Norway-to-US transport are declared caveats, not band widening. Read via IZA DP 3651 PDF (results section), NBER w14274 abstract beside | | child_education_years->grandchild_education_years | structural | 0.296 [0.255, 0.337] | lindahl2015 | Sweden, Malmö four-generation register (G3 children, N=1,823) | parent->child years-of-schooling slope 0.296 (SE 0.021), Table 2 cell (parent x child), bivariate regression with birth-year quadratics, family-clustered SEs; band = 95% CI (0.296 +/- 1.96 x 0.021), dist normal. LINEAR_SHIFT: composes year shifts linearly. CAVEAT carried from the authors: their own IV estimate (great-grandparent education as instrument) implies 'no causal effect of parental education on childrens' educational attainment' conditional on transmission (Sec. 4) - this row is a structural transmission assumption (persistence), not an identified intervention response. DANGLING UPSTREAM: no displacement->child_education_years entry yet (queue #33) - the hs_completion/college rows are probability-scale; the walk exists only once an admitted entry lands. Read via IZA DP 6463 full text (Table 2); published JHR 50(1) is the same study | | infant_birth_weight->child_earnings | conditional | 0.1 [0.0216, 0.1784] | black2007 | Norway twin sample, twin fixed effects on ln(birth weight), cohorts 1967-1988 (military conscription + earnings registries); IZA DP 1864 Table 5 'Ln(Earnings) FT', all-twins FE column | LANDED v1.45 fetal dose-response stream (user-directed 2026-09-14): coefficient on ln(BW) 0.10 (SE 0.04) - a ln-ln elasticity BY CONSTRUCTION: +10% BW -> +0.95% adult full-time earnings ('about 1%', authors' text); band = 1.96 x SE. OLS 0.10 (0.02) similar; all-earnings (incl. part-time) 0.09 (0.05); MZ-only column attenuates 0.09 (0.09) n.s. - recorded as declared upper-robustness, not the row. TRANSPORT/ROLE: a within-twin (fetal-growth) slope applied to a shock-induced BW shift is a structural_transmission_assumption - Almond-Currie 2011 caveat travels: BW is a crude fetal-health summary and the twin slope may not act identically along every margin. SCOPE: composes ONLY after displacement->infant_birth_weight (lindo2011, in-utero exposure window) - the IN-UTERO cohort; NEVER additive with displacement->child_earnings (oreopoulos2008 = TOTAL effect for the childhood-exposure cohort; different children). Composed point: 0.9541^0.10 = 0.995312 -> -0.47% adult earnings, ~an order of magnitude below the childhood channel (-9.24%). | | infant_birth_weight->adult_type2_diabetes_hazard | conditional | -0.9637 [-1.3834, -0.5401] | knop2018 | adults, pooled random-effects dose-response, 32 studies / ~7.6M participants (Knop et al. JAHA 2018, 7(23):e008870, OR per +1 kg birth weight; read via PMC6405546 full text) | LANDED v1.45 fetal dose-response stream: pooled OR 0.78 (95% CI 0.70-0.87) per +1 kg increment in birth weight (I2=72.6%). Log-elasticity conversion: ln(OR)/ln(4.4/3.4) with the US mean-birth-weight anchor 3.4 kg DECLARED (NCHS order-of-magnitude, canonical); band = CI endpoints converted identically. Sign convention: elasticity is negative (more BW, less diabetes risk); a displacement-induced BW LOSS composes to an odds INCREASE. Composed point: 0.9541^-0.9637 = 1.04632 -> +4.6% adult T2D odds on the in-utero cohort. SHAPE CAVEAT: the association is J-shaped with lowest risk at 3.5-4.0 kg - the inverse branch is the one a downward shift applies to; the high-tail upturn (>4.5 kg, female-concentrated) never enters this model's shifts and travels as undeclared heterogeneity (row is pooled-sex). | | infant_birth_weight->adult_cardiovascular_disease_hazard | conditional | -0.6994 [-0.8173, -0.585] | knop2018 | adults, pooled random-effects dose-response, 33 studies / ~5.9M participants (same source as the T2D row; OR per +1 kg birth weight) | LANDED v1.45 fetal dose-response stream: pooled OR 0.835 (95% CI 0.81-0.86) per +1 kg increment in birth weight (I2=0.0 - the most homogeneous gradient in the meta-analysis). POINT PRECISION: the source sentence reads 'a 16.5% (OR: 0.84, 95% CI: 0.81-0.86) reduction' - the point is taken at its stated precision 1-0.165 = 0.835, which reconciles with the CI geometric center sqrt(0.81x0.86) = 0.8346 (the parenthetical 0.84 is 2-dp rounding). Same conversion and 3.4 kg declared anchor as the T2D row. Composed point: 0.9541^-0.6994 = 1.033419 -> +3.3% adult CVD odds on the in-utero cohort. Same J-shape caveat (lowest risk 4.0-4.5 kg; downward shifts stay on the inverse branch). | | divorce_hazard->child_divorce_hazard | structural | 1.88 [1.57, 2.24] | mclanahanbumpass1988 | US women (NSFG cycles I-III), white daughters who spent part of childhood with a divorced/separated/never-married parent vs two-parent families; proportional-hazard model of own marital disruption | LANDED v1.46 (sweep #6, queue row 35): McLanahan & Bumpass 1988 (AJS 94(1):130-152, DOI 10.1086/228954 verified via Crossref), Appendix Table A1 marital-disruption column + prose cross-check. Background-controlled model: beta 0.63 (SE 0.09); band = exp(beta +/- 1.96 SE) = 1.88 [1.57, 2.24]. ZERO-ORDER beta 0.65 (SE 0.09) = exp 1.92, matching the text's '92 percent more likely to experience a marital disruption' - the prose/table cross-check that validates the OCR read. BESIDE: education-controlled beta 0.51 -> HR 1.67 (the association survives own-education adjustment); Black women beta 0.31 (SE 0.08) -> HR 1.36 (smaller, same direction); widowhood weaker (beta 0.30) - disruption carries the effect, not parent absence per se. dist withheld: the band is exponentiated from a log-hazard CI, asymmetric around the multiplier (B&H precedent). READ-VIA: IRP DP 805-86 (WP of the AJS version of record; OCR pass - table digits validated against the stated prose percentages). THE WALK IS STILL BLOCKED: this row composes ONLY through a conditional/mixture kind (only the displaced marriages that actually dissolve transmit) - designed separately; gruber2004 is NOT a pin (law-exposure ITT, 'no rise in the odds of being divorced', venue corrected to JOLE 22(4)) | | married_cohort->parental_dissolution_share | conditional | 0.069 [0.069, 0.072] | rege2007 | married workers at Norwegian plants 1995-2000 (the rege2007 entry population and follow-up window, dissolution measured by 2003) | LANDED v1.47 (queue row 35b): the counterfactual dissolution share for the conditional-mixture divorce transmission - SAME source, population, and window as the displacement->divorce_hazard entry (SSB DP 514 Table 1 + prose: 'About 7.0 percent of the couples got divorced from 1995 to 2003'; stable plants 6.9%, closing plants 7.2%). Point = the stable-plant share 0.069 (the counterfactual the walk compares against); band [0.069, 0.072] = the paper's observed range across plant types (no CI reported for the share). Feeds conditional_mixture: extra share = 1-(1-s)^m - s; at m=1.11, s=0.069 -> +0.73pp extra dissolutions, matching the paper's own adjusted +0.78pp (+11%) - the coherence check that the window and population align | | undocumented_share_change_pp->receiving_violent_crime_log_rate | conditional | -0.12 [-0.18, -0.06] | lightmiller2018 | US 50 states + DC 1990-2014; lagged percentage-point undocumented population share; Light-Miller 2018 Table 2 Model 4 | CORRECTED 2026-10-15 v1.52: published Criminology PDF SHA256 4af68d79d437943601cac72ba25692fbe999588e4fda88792d5729dfc0114df9, Table 1 p377 and focal-measure definition p379: undocumented share is unlogged, expressed in percentage points; violent crime rate is logged. Table 2 Model 4 p386: b=-0.12, clustered SE=0.03 (Models 3-5 have the same rounded b/SE). This is a semi-log slope per 1 percentage point, NOT a log-log immigrant-stock elasticity. The previous immigrant_influx linkage and +10% stock -> -1.2% claim were unsafe and retired. Source coefficient and rounded support [-0.18,-0.06] unchanged (1.96*SE rounded to two decimals). Named adapter uses exp(b*delta_share_pp), annual outcome with predictors lagged one year, NOT a cumulative multi-year count. Preferred FE association; IV robustness does not turn this FE coefficient into the IV estimand. Population-weighted Model 6 b=-0.05 SE=.02 and cross-spec sensitivity remain beside. Not transferable to regular-resident or work-banned margins by relabeling. | | regular_immigrant_share_ratio->receiving_total_crime_rate | conditional | 0.105 [-0.2616, 0.4716] | bianchibuonannopinotti2012 | Italy 95 provinces 1991-2001; log valid residence permits / total province population; 2010 working-paper ten-year-difference IV | CORRECTED 2026-10-15 v1.52: source regressor is log(valid residence permits / total province population), not log immigrant stock alone. Accessible 2010 working-paper mirror SHA256 4857b7f55b25466dccb4df477191bdaee433d129c087fb68472a2884e2239daf, Eq3 p7 and Table5 col3 p33: IV b=.105, robust SE=.187, 95 Italian provinces, 1991-2001 differences. original rounded support [-.2616,.4716] unchanged and includes zero. Different from the formerly pinned HAL draft (SHA256 02442aa8b0c716be00cc598ba5948dce31e835ad2b19bd60cd1ea598a45e5c66, Table4 locator); published JEEA version not re-extracted in this correction. Tier canonical under CITING working-paper rule. Named adapter uses (post_share/reference_share)^b, including both total-population denominators. This is an endpoint crime RATE contrast, NOT ten-year cumulative incidents. Margin is valid residence-permit residents, not all immigrants, H-1B arrivals or asylum/work-banned migrants. OLS .156 SE.049 and alternative IV .029 SE.125 / -.029 SE.175 remain distinct specifications, never averaged or replaced by zero. | ### Bundle inventory and reproducibility | Measure | Value | |---|---| | Pinned bundle | v1.52 · engine 0.4.0 | | Bundle sha256 | 99173fbf23e75037da3fb9b4a9017a1e56909260ccb112f9902bc5ac86242153 | | Bibliography entries | 110 | | Active parameter rows | 67 | | Mortality risk phases | 5 | | Fixed scenario inputs | children per worker (2); follow-up window (20 years); every study effect size and its uncertainty; mortality and earnings baselines | Reproduce the reference scenario (see the downstream repository README for setup): ```text downstream scenario --workers 1000 --children 2 --tradable-share 1 --exposure-years 20 ``` ### Evidence and receipts The bibliography contains 110 sources and 216 named author records (people and organizations), 1979-2026. The parameters cite 53 sources with 121 named author records; these are not counts of independent research teams. The bibliography includes research, methods and context sources; inclusion does not establish peer review or independent validation. Modeled numbers carry their cited inputs and declared structural assumptions. The complete versioned bibliography for the shipped model bundle. Each row gives its source identifier, DOI, and how the number entered the repo: a full-text table extraction, a published abstract, or an established literature value. Not every cited work is a direct effect study. The bundle contains 110 reference records. Duplicate identifiers share one document entry. These labels describe the bundle’s extraction records; they do not certify that each source supports every modeled outcome. | Key | Work | Authors | Year | Evidence | Attributed studies | |---|---|---|---|---|---| | jacobson1993 | Earnings Losses of Displaced Workers · Working-paper edition registered by this DOI; 1992 | Jacobson, Louis S. and LaLonde, Robert J. and Sullivan, Daniel G. | 1992 | abstract | [DOI / publisher](https://doi.org/10.17848/wp92-11) | | oreopoulos2008 | The Intergenerational Effects of Worker Displacement · UC Davis author manuscript, Table 2, column 3 (PDF page 31); manuscript has no printed revision date | Oreopoulos, Philip and Page, Marianne E. and Stevens, Ann Huff | 2008 | fulltext-table | [Source](https://poverty.ucdavis.edu/sites/main/files/file-attachments/stevens_2008jole_finalman.pdf#page=31) · [DOI / publisher](https://doi.org/10.1086/588493) | | sullivan2009 | Mortality, Mass-Layoffs, and Career Outcomes: An Analysis using Administrative Data · NBER Working Paper 13626, Table 5, column 3 (PDF page 54) | Sullivan, Daniel and von Wachter, Till | 2007 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w13626/w13626.pdf#page=54) · [DOI / publisher](https://doi.org/10.3386/w13626) | | rege2007 | Plant Closure and Marital Dissolution · Statistics Norway Discussion Paper 514 (2007), Tables 1–2 (PDF pages 12–13) | Rege, Mari and Telle, Kjetil and Votruba, Mark | 2007 | abstract | [Source](https://www.ssb.no/publikasjoner/DP/pdf/dp514.pdf#page=12) | | charles2004 | Job Displacement, Disability, and Divorce · Working-paper edition registered by this DOI; 2001 | Charles, Kerwin Kofi and Stephens, Melvin, Jr. | 2001 | canonical | [DOI / publisher](https://doi.org/10.3386/w8578) | | gruber2004 | Is Making Divorce Easier Bad for Children? The Long-Run Implications of Unilateral Divorce · NBER Working Paper7968 (2000), unilateral-divorce-law exposure | Gruber, Jonathan | 2000 | canonical | [Source](https://www.nber.org/system/files/working_papers/w7968/w7968.pdf) · [DOI / publisher](https://doi.org/10.3386/w7968) | | black2005 | The More the Merrier? The Effect of Family Composition on Children’s Education · NBER Working Paper10720 (2004), family composition and children’s education | Black, Sandra E. and Devereux, Paul J. and Salvanes, Kjell G. | 2004 | canonical | [Source](https://www.nber.org/system/files/working_papers/w10720/w10720.pdf) · [DOI / publisher](https://doi.org/10.3386/w10720) | | solon1992 | Intergenerational Income Mobility in the United States · American Economic Review 82(3), 393–408 (1992) | Solon, Gary | 1992 | canonical | [Source](https://cpi.stanford.edu/_media/pdf/Classic_Media/Solon_1992_Children.pdf) | | corak2013 | Income Inequality, Equality of Opportunity, and Intergenerational Mobility · IZA Discussion Paper7520 (2013), literature synthesis | Corak, Miles | 2013 | canonical | [Source](https://docs.iza.org/dp7520.pdf) | | chetty2014 | Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States | Chetty, Raj and Hendren, Nathaniel and Kline, Patrick and Saez, Emmanuel | 2014 | canonical | [DOI / publisher](https://doi.org/10.3386/w19843) | | lindahl2015 | The Intergenerational Persistence of Human Capital: An Empirical Analysis of Four Generations · IZA Discussion Paper 6463, April 2012; Table 2 (PDF page 16) | Lindahl, Mikael and Palme, M{\aa}rten and Massih, Sofía Sandgren and Sj{\"o}gren, Anna | 2012 | fulltext | [Source](https://docs.iza.org/dp6463.pdf#page=16) | | widom1989 | The Cycle of Violence | Widom, Cathy Spatz | 1989 | canonical | [DOI / publisher](https://doi.org/10.1126/science.2704995) | | ehrensaft2003 | Intergenerational Transmission of Partner Violence: A 20-Year Prospective Study | Ehrensaft, Miriam K. and Cohen, Patricia and Brown, Jocelyn and Smailes, Elizabeth and Chen, Henian and Johnson, Jeffrey G. | 2003 | canonical | [DOI / publisher](https://doi.org/10.1037/0022-006x.71.4.741) | | moretti2010 | Local Multipliers · Author-hosted 2010 prepress manuscript, Section III and Tables 1–2 (PDF pages 4–5) | Moretti, Enrico | 2010 | abstract | [Source](https://eml.berkeley.edu/~moretti/multipliers.pdf#page=4) · [DOI / publisher](https://doi.org/10.1257/aer.100.2.373) | | jackson2016 | The Effects of School Spending on Educational and Economic Outcomes: Evidence from School Finance Reforms · NBER Working Paper 20847 (2015), abstract (PDF page 2); reported wage effect, not a reported 3%–10% interval | Jackson, C. Kirabo and Johnson, Rucker C. and Persico, Claudia | 2015 | canonical | [Source](https://www.nber.org/system/files/working_papers/w20847/w20847.pdf#page=2) · [DOI / publisher](https://doi.org/10.3386/w20847) | | gould2002 | Crime Rates and Local Labor Market Opportunities in the United States: 1979--1997 · Original Review of Economics and Statistics article on Stanford’s research archive | Gould, Eric D. and Weinberg, Bruce A. and Mustard, David B. | 2002 | canonical | [Source](https://cpi.stanford.edu/_media/pdf/Reference%20Media/Gould%2C%20Weinberg%2C%20and%20Mustard_2002_Crime%20and%20the%20Legal%20System.pdf) · [DOI / publisher](https://doi.org/10.1162/003465302317331919) | | grogger1998 | Market Wages and Youth Crime · Working-paper edition registered by this DOI; 1997 | Grogger, Jeff | 1997 | canonical | [DOI / publisher](https://doi.org/10.3386/w5983) | | vonwachter2009 | Long-Term Earnings Losses due to Mass Layoffs During the 1982 Recession: An Analysis Using U.S. Administrative Data from 1974 to 2004 · April 2009 conference draft | von Wachter, Till and Song, Jae and Manchester, Joyce | 2009 | canonical | [Source](https://conference.nber.org/confer/2009/LSEEEs09/von%20Wachter.pdf) | | eliason2009; eliasonstorrie2009 | Does Job Loss Shorten Life? | Eliason, Marcus and Storrie, Donald | 2009 | canonical | [DOI / publisher](https://doi.org/10.1353/jhr.2009.0020) | | autor2019 | When Work Disappears: Manufacturing Decline and the Falling Marriage-Market Value of Young Men | Autor, David and Dorn, David and Hanson, Gordon | 2019 | fulltext | [DOI / publisher](https://doi.org/10.1257/aeri.20180010) | | aizer2010 | The Gender Wage Gap and Domestic Violence | Aizer, Anna | 2010 | fulltext | [DOI / publisher](https://doi.org/10.1257/aer.100.4.1847) | | kearney2020; kearney2018fracking | Male Earnings, Marriageable Men, and Nonmarital Fertility: Evidence from the Fracking Boom · NBER Working Paper 23408 (2017), Table 8, Panel B, column 2 (PDF page 45) | Kearney, Melissa S. and Wilson, Riley | 2017 | canonical | [Source](https://www.nber.org/system/files/working_papers/w23408/w23408.pdf#page=45) · [DOI / publisher](https://doi.org/10.3386/w23408) | | colantone2018 | The Trade Origins of Economic Nationalism: Import Competition and Voting Behavior in Western Europe · Author manuscript, July14,2017, ETSG conference copy, Table1 column10 (PDF page24) | Colantone, Italo and Stanig, Piero | 2017 | fulltext-table | [Source](https://www.etsg.org/ETSG2017/papers/colantone_stanig_etsg.pdf#page=24) | | putnam2007 | E Pluribus Unum: Diversity and Community in the Twenty-first Century—The 2006 Johan Skytte Prize Lecture | Putnam, Robert D. | 2007 | canonical | [DOI / publisher](https://doi.org/10.1111/j.1467-9477.2007.00176.x) | | chetty2016jama; chetty2016 | The Association Between Income and Life Expectancy in the United States, 2001--2014 · Results: income-dollar concavity example ($14,000 to $20,000) | Chetty, Raj and Stepner, Michael and Abraham, Sarah and Lin, Shelby and Scuderi, Benjamin and Turner, Nicholas and Schrag, Augustin and Cutler, David | 2016 | canonical | [Source](https://pmc.ncbi.nlm.nih.gov/articles/PMC4866586/) | | lindo2011 | Parental Job Loss and Infant Health · IZA Discussion Paper 5213, September 2010, Table 2, column 3 (PDF page 26) | Lindo, Jason M. | 2010 | fulltext-table | [Source](https://docs.iza.org/dp5213.pdf#page=26) | | stevens2011 | Short-Run Effects of Parental Job Loss on Children's Academic Achievement · NBER Working Paper 15480 (2009), Table 4, column 1 (PDF page 38); sample mean in results prose | Stevens, Ann Huff and Schaller, Jessamyn | 2009 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w15480/w15480.pdf#page=38) · [DOI / publisher](https://doi.org/10.3386/w15480) | | ananat2017 | Linking Job Loss, Inequality, Mental Health, and Education | Ananat, Elizabeth O. and Gassman-Pines, Anna and Francis, David V. and Gibson-Davis, Christina M. | 2017 | abstract | [DOI / publisher](https://doi.org/10.1126/science.aam5347) | | paul2009 | Unemployment Impairs Mental Health: Meta-Analyses | Paul, Karsten I. and Moser, Klaus | 2009 | fulltext-table | [DOI / publisher](https://doi.org/10.1016/j.jvb.2009.01.001) | | immergluck2006 | The Impact of Single-Family Mortgage Foreclosures on Neighborhood Crime | Immergluck, Dan and Smith, Geoff | 2006 | canonical | [DOI / publisher](https://doi.org/10.1080/02673030600917743) | | campbell2011 | Forced Sales and House Prices · NBER Working Paper 14866 (2009), abstract and neighborhood externality estimates | Campbell, John Y. and Giglio, Stefano and Pathak, Parag | 2009 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w14866/w14866.pdf#page=2) · [DOI / publisher](https://doi.org/10.3386/w14866) | | doran2022 | The Effects of High-Skilled Immigration Policy on Firms: Evidence from Visa Lotteries · Working-paper edition registered by this DOI; 2014 | Doran, Kirk and Gelber, Alexander and Isen, Adam | 2014 | fulltext-table | [DOI / publisher](https://doi.org/10.3386/w20668) | | ousey2018 | Immigration and Crime: Assessing a Contentious Issue | Ousey, Graham C. and Kubrin, Charis E. | 2018 | abstract | [DOI / publisher](https://doi.org/10.1146/annurev-criminol-032317-092026) | | davis2011 | Recessions and the Costs of Job Loss · NBER Working Paper17638 (2011, revised March2017), earnings-loss discussion | Davis, Steven J. and von Wachter, Till | 2011 | results | [Source](https://www.nber.org/system/files/working_papers/w17638/w17638.pdf) · [DOI / publisher](https://doi.org/10.3386/w17638) | | autor2020 | Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure · Working-paper edition registered by this DOI; 2016 | Autor, David and Dorn, David and Hanson, Gordon and Majlesi, Kaveh | 2016 | abstract | [DOI / publisher](https://doi.org/10.3386/w22637) | | fetzer2019 | Did Austerity Cause Brexit? · Edition registered by this DOI; 2018 | Fetzer, Thiemo | 2018 | canonical | [DOI / publisher](https://doi.org/10.2139/ssrn.3251187) | | mclanahan1994 | Growing Up with a Single Parent: What Hurts, What Helps | McLanahan, Sara and Sandefur, Gary | 1994 | canonical | [Source](https://www.jstor.org/stable/j.ctv22tnmnn) · [DOI / publisher](https://doi.org/10.2307/j.ctv22tnmnn) | | damm2014 | Does Growing Up in a High Crime Neighborhood Affect Youth Criminal Behavior? · Aarhus Economics Working Paper 2013-17, Tables 3 and 5 (PDF pages 40 and 42) | Damm, Anna Piil and Dustmann, Christian | 2013 | fulltext-table | [Source](https://repec.econ.au.dk/repec/afn/wp/13/wp13_17.pdf#page=40) | | yang2008 | International Migration, Remittances, and Household Investment: Evidence from Philippine Migrants' Exchange Rate Shocks · Working-paper edition registered by this DOI; 2006 | Yang, Dean | 2006 | canonical | [DOI / publisher](https://doi.org/10.3386/w12325) | | ganong2022 | Liquidity versus Wealth in Household Debt Obligations: Evidence from Housing Policy in the Great Recession · American Economic Review 110(10), 3100–3138 (October 2020) | Ganong, Peter and Noel, Pascal | 2020 | canonical | [DOI / publisher](https://doi.org/10.1257/aer.20181243) | | schneider2016 | Intimate Partner Violence in the Great Recession · Tables 1 and 3 and results prose on predicted probabilities | Schneider, Daniel and Harknett, Kristen and McLanahan, Sara | 2016 | fulltext-table | [Source](https://pmc.ncbi.nlm.nih.gov/articles/PMC4860387/) | | evans2008 | Exposure to Domestic Violence: A Meta-Analysis of Child and Adolescent Outcomes | Evans, Sarah E. and Davies, Corrie and DiLillo, David | 2008 | fulltext-table | [DOI / publisher](https://doi.org/10.1016/j.avb.2008.02.005) | | costello2003 | Relationships Between Poverty and Psychopathology: A Natural Experiment | Costello, E. 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The Electoral Consequences of Rising Trade Exposure · Published AER article, Equation1 and Table4, column6 (PDF page29) | Autor, David and Dorn, David and Hanson, Gordon and Majlesi, Kaveh | 2020 | fulltext-table | [Source](https://www.ddorn.net/papers/ADHM-PoliticalPolarization.pdf#page=29) · [DOI / publisher](https://doi.org/10.1257/aer.20170011) | | lindo2018maltreatment | Caution! Men Not at Work: Gender-Specific Labor Market Conditions and Child Maltreatment · NBER Working Paper 18994 (2013), Table 3, Panel A, column 3 (PDF page 41) | Lindo, Jason M. and Schaller, Jessamyn and Hansen, Benjamin | 2013 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w18994/w18994.pdf#page=41) · [DOI / publisher](https://doi.org/10.3386/w18994) | | desmond2016 | Housing and Employment Insecurity among the Working Poor | Desmond, Matthew and Gershenson, Carl | 2016 | fulltext-table | [DOI / publisher](https://doi.org/10.1093/socpro/spv025) | | collinson2024 | Eviction and Poverty in American Cities · NBER Working Paper 30382 (2022, revised July 2023), Tables V–VI (PDF pages 46–47) | Collinson, Robert and Humphries, John Eric and Mader, Nicholas S. and Reed, Davin K. and Tannenbaum, Daniel I. and van Dijk, Winnie | 2022 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w30382/w30382.pdf#page=46) · [DOI / publisher](https://doi.org/10.3386/w30382) | | chettyhendren2018 | The Impacts of Neighborhoods on Intergenerational Mobility {I}: Childhood Exposure Effects · NBER Working Paper 23001 (2016, revised May 2017), Appendix Table V, column 1 (PDF page 57) | Chetty, Raj and Hendren, Nathaniel | 2016 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w23001/w23001.pdf#page=57) · [DOI / publisher](https://doi.org/10.3386/w23001) | | zg2012 | Early Childhood Poverty, Immune-Mediated Disease Processes, and Adult Productivity | Ziol-Guest, Kathleen M. and Duncan, Greg J. and Kalil, Ariel and Boyce, W. Thomas | 2012 | fulltext-table | [DOI / publisher](https://doi.org/10.1073/pnas.1203167109) | | huttunen2019 | Parental Job Loss and Children's Careers · IZA Discussion Paper 12788, November 2019 | Huttunen, Kristiina and Riukula, Krista | 2019 | fulltext-table | [Source](https://docs.iza.org/dp12788.pdf) | | brand2014 | Job Displacement Among Single Mothers: Effects on Children's Outcomes in Young Adulthood · Author manuscript of the 2014 AJS article; Table 3, propensity-score kernel matching TT column | Brand, Jennie E. and Simon Thomas, Juli | 2014 | fulltext-table | [Source](https://pmc.ncbi.nlm.nih.gov/articles/PMC4372265/) · [DOI / publisher](https://doi.org/10.1086/675409) | | browningheinesen2012 | Effect of Job Loss Due to Plant Closure on Mortality and Hospitalisation · AKF working paper, April 2011; Tables 6.1–6.2 (PDF pages 23 and 25) | Browning, Martin and Heinesen, Eskil | 2011 | fulltext-table | [Source](https://www.vive.dk/media/pure/yxd91ozg/2078384#page=23) | | marcus2013 | The Effect of Unemployment on the Mental Health of Spouses: Evidence from Plant Closures in Germany · SOEPpapers 488 (2012), Table 3, specification 4 (PDF page 17) | Marcus, Jan | 2012 | fulltext-table | [Source](https://www.diw.de/documents/publikationen/73/diw_01.c.409023.de/diw_sp0488.pdf#page=17) | | bingley2026 | When It Hurts the Most: Timing of Parental Job Loss and a Child's Education · IZA Discussion Paper 16367, August 2023; Table 4, column 2 (PDF page 50), and Table 2 (PDF page 48) | Bingley, Paul and Cappellari, Lorenzo and Ovidi, Marco | 2023 | fulltext-table | [Source](https://docs.iza.org/dp16367.pdf) | | schallerstevens2015 | Short-Run Effects of Job Loss on Health Conditions, Health Insurance, and Health Care Utilization | Schaller, Jessamyn and Stevens, Ann Huff | 2015 | fulltext | [DOI / publisher](https://doi.org/10.1016/j.jhealeco.2015.07.003) | | bloemen2018 | Job Loss, Firm-Level Heterogeneity and Mortality: Evidence from Administrative Data | Bloemen, Hans and Hochguertel, Stefan and Zweerink, Jochem | 2018 | fulltext-table | [DOI / publisher](https://doi.org/10.1016/j.jhealeco.2018.03.005) | | halla2020 | Job Displacement, Family Dynamics, and Spousal Labor Supply · AEA-hosted manuscript, Table 2 (PDF page 39), subgroup tables (PDF pages 41–43) | Halla, Martin and Schmieder, Julia and Weber, Andrea | 2020 | fulltext-table | [Source](https://www.aeaweb.org/content/file?id=11380#page=39) · [DOI / publisher](https://doi.org/10.1257/app.20180671) | | huttunenkellokumpi2016 | The Effect of Job Displacement on Couples' Fertility Decisions · IZA Discussion Paper 6707, July 2012; Table 3, plant-closure sample (PDF page 39) | Huttunen, Kristiina and Kellokumpu, Jenni | 2012 | fulltext-table | [Source](https://docs.iza.org/dp6707.pdf#page=39) | | schallerzerpa2019 | Short-Run Effects of Parental Job Loss on Child Health · NBER Working Paper 21745, November 2015; Table 2, father-displaced tenured column (PDF page 31) | Schaller, Jessamyn and Zerpa, Mariana | 2015 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w21745/w21745.pdf#page=31) | | mork2019 | Consequences of Parental Job Loss on the Family Environment and on Human Capital Formation: Evidence from Plant Closures · IZA Discussion Paper 12559, August 2019 | Mörk, Eva and Sjögren, Anna and Svaleryd, Helena | 2019 | fulltext | [Source](https://docs.iza.org/dp12559.pdf) | | blackdevereuxsalvanes2009 | Like Father, Like Son? A Note on the Intergenerational Transmission of IQ Scores · IZA Discussion Paper 3651 (2008), Results (PDF page 8), Table 3 | Black, Sandra E. and Devereux, Paul J. and Salvanes, Kjell G. | 2008 | results | [Source](https://docs.iza.org/dp3651.pdf#page=8) | | black2007 | From the Cradle to the Labor Market? The Effect of Birth Weight on Adult Outcomes · NBER Working Paper 11796 (2005), Table 5, All Twins / Ln(Earnings) FT (PDF page 50) | Black, Sandra E. and Devereux, Paul J. and Salvanes, Kjell G. | 2005 | fulltext-table | [Source](https://www.nber.org/system/files/working_papers/w11796/w11796.pdf#page=50) · [DOI / publisher](https://doi.org/10.3386/w11796) | | knop2018 | Birth Weight and Risk of Type 2 Diabetes Mellitus, Cardiovascular Disease, and Hypertension in Adults: A Meta-Analysis of 7~646~267 Participants From 135 Studies · Results: dose-response analyses of T2DM and CVD per 1 kg birth weight | Knop, Michael R. and Geng, Tianti T. and Gorny, Anna W. and Ding, Rui and Li, Changwei and Ley, Sylvia H. and Huang, Tao | 2018 | fulltext-table | [Source](https://pmc.ncbi.nlm.nih.gov/articles/PMC6405546/) | | royer2009 | Separated at Girth: US Twin Estimates of the Effects of Birth Weight | Royer, Heather | 2009 | abstract | [DOI / publisher](https://doi.org/10.1257/app.1.1.49) | | mclanahanbumpass1988 | Intergenerational Consequences of Family Disruption · IRP Discussion Paper 805-86 (May 1986), Appendix Table A1, white women, first background-adjusted block (PDF page 26) | McLanahan, Sara and Bumpass, Larry | 1986 | fulltext | [Source](https://www.irp.wisc.edu/publications/dps/pdfs/dp80586.pdf#page=26) | | lightmiller2018 | Does Undocumented Immigration Increase Violent Crime? · Original 2018 article manuscript, Table 2, Model 5; Table 1 units | Light, Michael T. and Miller, Ty | 2018 | fulltext-table | [Source](https://pmc.ncbi.nlm.nih.gov/articles/PMC6241529/) | | lightheobey2020 | Comparing Crime Rates between Undocumented Immigrants, Legal Immigrants, and Native-Born {US} Citizens in Texas | Light, Michael T. and He, Jingying and Robey, Jason P. | 2020 | fulltext-table | [DOI / publisher](https://doi.org/10.1073/pnas.2014704117) | | bellfasanimachin2013 | Crime and Immigration: Evidence from Large Immigrant Waves | Bell, Brian and Fasani, Francesco and Machin, Stephen | 2013 | fulltext-table | [DOI / publisher](https://doi.org/10.1162/REST_a_00337) | | bianchibuonannopinotti2012 | Do Immigrants Cause Crime? · February 2010 working-paper manuscript on a public mirror; Equation 3 and Table 5, column 3 (PDF page 33) | Bianchi, Milo and Buonanno, Paolo and Pinotti, Paolo | 2010 | fulltext-table | [Source](https://www.antoniocasella.eu/nume/bianchi_buonanno_pinotti_2010.pdf#page=33) | ### Original pinned record · excluded from estimates This input is excluded from public estimates because its source, units or numerical extraction could not be substantiated. The original pinned record is retained below. ```json [ { "id": "divorce->child_earnings", "from": "divorce_hazard", "to": "child_earnings", "tier": "canonical", "evidenceRole": "boundary", "citation": "gruber2004", "populationScope": "US divorce-law-reform cohorts", "point": 0.95, "low": 0.9, "high": 0.99, "notes": "adult children of easier-divorce states: lower earnings + attainment, higher own divorce; PARALLEL stream (never composed with the displacement path silently)" }, { "id": "family_size->child_earnings", "from": "family_size", "to": "child_earnings", "tier": "canonical", "evidenceRole": "boundary", "citation": "black2005", "populationScope": "Norway admin", "point": 0.98, "low": 0.95, "high": 1, "notes": "per-child penalty for larger families / later birth order; PARALLEL stream" }, { "id": "grandchild_earnings->greatgrandchild_earnings", "from": "grandchild_earnings", "to": "greatgrandchild_earnings", "tier": "canonical", "evidenceRole": "structural", "citation": "lindahl2015;adermon2018", "populationScope": "Sweden 3-generation admin", "point": 0.55, "low": 0.4, "high": 0.6, "notes": "same IGE band; weakest-identified layer - Lindahl 2015 shows persistence beyond the middle generation survives conditioning; BEHRMAN-TAUBMAN 1990 CROSS-CHECK (v1.14): PSID one-year-measure correlation 0.20 (elasticity ~0.07) vs correlations OVER 0.5 with longer-run income measures - the transitory-income attenuation Solon 1992 corrected; our multi-year IGE band [0.40,0.60] sits inside their long-run range and the one-year number documents why naive single-year IGEs bias low" }, { "id": "ipv_exposure->daughter_violence_odds", "from": "household_ipv", "to": "daughter_violence_odds", "tier": "canonical", "evidenceRole": "boundary", "citation": "widom1989;ehrensaft2003", "populationScope": "US prospective cohorts", "point": 2.5, "low": 2, "high": 3, "notes": "cycle-of-violence transmission; upstream household_ipv incidence link queued (aizer2010)" }, { "id": "wage_ratio->household_ipv", "from": "wage_ratio", "to": "household_ipv_elasticity", "tier": "EXACT-results", "evidenceRole": "boundary", "citation": "aizer2010", "populationScope": "US counties 1990-2003, women's assault hospitalizations", "point": -0.813, "low": -1.45, "high": -0.18, "notes": "elasticity of ln(IPV) w.r.t. female/male wage ratio; AER Table 2 col 3 (lagged-DV spec), 95% CI from clustered SE 0.317. SIGN: male displacement RAISES the ratio and so LOWERS IPV against women (Aizer bargaining); wiring this into the daughter chain needs incidence weights for who is displaced - deliberately not composed here" }, { "id": "displacement->college_enrollment", "from": "displacement_event", "to": "college_enrollment", "tier": "EXACT", "evidenceRole": "conditional", "citation": "hilger2016", "populationScope": "US children of ~7M laid-off fathers, ages 18-22 enrollment, 1999-2009 administrative data", "point": 0.9894, "low": 0.9848, "high": 0.9939, "notes": "queue-11 LANDED v1.13: paternal layoff -> college enrollment -0.432pp (SE 0.094) on a 40.66% base = -1.06% relative; multiplier = 1-0.432/40.66, 95% CI from 1.96SE. THE HONESTY LOADSTONE: single-difference closure estimates are 13x larger (-5.54pp, Table 4 col 1) but Hilger DD on closures is wrong-signed (+0.00569, SE 0.0032) - firm-closure designs carry assortative-selection bias, and his footnote 31 names oreopoulos2008 and sullivan2009 as exposed. Our child-earnings and mortality anchors ARE closure/displacement designs: tension recorded, V2 cross-check queued, child-earnings band NOT silently changed" }, { "id": "displacement->parental_income_shortrun", "from": "displacement_event", "to": "parental_income_shortrun", "tier": "EXACT", "evidenceRole": "conditional", "citation": "hilger2016", "populationScope": "US laid-off fathers, annual income in the layoff event window (base $59,832)", "point": 0.864, "low": 0.8568, "high": 0.8712, "notes": "queue-11 companion LANDED v1.13: layoff -> parental income -$8,138.09/yr (SE 219.53) on base $59,832 = -13.60%; multiplier + CI from 1.96SE. SHORT-RUN event-window income - do not compose into worker_earnings (long-run JLS band); useful to scale exposure magnitudes in US data. STEVENS-SCHALLER 2011 CROSS-CHECK (v1.20): US SIPP family income -10.9% (SE 2.8pp) one-or-more years after the head's involuntary job loss (Table 3, read via NBER w15480) - corroborates this row's short-run income-loss magnitude in a second US sample; row values unchanged" }, { "id": "unemployment_rate->property_crime", "from": "unemployment_rate", "to": "property_crime_response", "tier": "EXACT", "evidenceRole": "boundary", "citation": "raphael2001", "populationScope": "US states 1971-97, N=1,293 state-years, 2SLS defense-contracts + oil-cost instruments", "point": 5.018, "low": 2.795, "high": 7.241, "notes": "queue-10 LANDED v1.13: +1pp state unemployment -> +5.018% property crime (SE 1.134), Table 5 \"All property crime\" linear+quadratic-trends 2SLS (95% CI = 1.96SE); overidentification PASSES for property crime in all 2SLS specs. OLS full-spec 1.635 (0.182); the paper summary quotes OLS 1.6-2.4% per pp. Violent crime: null/mixed (2SLS insig 2 of 3 specs, overID rejected in the third) - deliberately NOT landed. Lin 2008 second anchor still queued for the band. Boundary-applied: NEVER chained" }, { "id": "eitc_exposure->adult_earnings_early", "from": "eitc_exposure", "to": "adult_earnings_early", "tier": "EXACT", "evidenceRole": "boundary", "citation": "bastian2018", "populationScope": "US PSID children, EITC exposure ages 13-18, PSID 1968-2013, state-clustered SE", "point": 564, "low": 83.996, "high": 1044.004, "notes": "queue-bonus LANDED v1.14: +$1,000 EITC exposure during ages 13-18 -> +$564 annual earnings at ages 22-27 (SE 244.9, p<0.05; Table 2 col 6, 95% CI = 1.96SE; 2013 dollars). First stage: $1k exposure ~ $12,000 family income over the window (~$2k/yr x 6y) -> implies ~+$47 per $1k income. IV-scaled version (Table 6 col 6: +$57.2, SE 32.4) is significant only at 10% - recorded here, NOT landed as its own row to avoid implying precision it lacks. TIMING: exposure ages 0-12 ~ null on education outcomes (F-test p=0.006 for HS: teen exposure dominates) - corroborates Carneiro et al. timing; the adolescent income stream is the one that bites. Education outcomes (HS grad +1.2pp on 0.92, college grad +1.3pp on 0.31) recorded, not landed. Sign note: displacement INCOME LOSS applies this row negatively. Boundary-applied: NEVER chained; CARNEIRO-LOPEZ-GARCIA-SALVANES-TOMINEY 2021 TIMING CORROBORATION (v1.15, Norway admin, fixed permanent income): income in EARLY (0-5) and LATE (12-17) childhood has high marginal productivity for child human capital; MIDDLE (6-11) is low; balanced profiles beat imbalanced. Structural-model quantities - deliberately NOT a composed row; it bounds which childhood window the model's income streams may claim to harm" }, { "id": "import_shock->gop_win_probability", "from": "import_shock_per_worker", "to": "gop_win_probability", "tier": "EXACT", "evidenceRole": "boundary", "citation": "autor2020polarization", "populationScope": "US county-congressional-district cells 2002-2010, N=3,772, 2SLS full controls", "point": 24.08, "low": 0.423, "high": 47.737, "notes": "queue-16 LANDED v1.15: change in the probability of electing a Republican to the House, in percentage points, per $1k/worker decadal import exposure = 24.08 (SE 12.07; t=2.00), Table 4 col 6, 2002-2010, N=3,772 county-district cells, 2SLS full controls (spec = Table 3 col 5), 95% CI = 1.96SE. Authors' own scaling: x 0.49 (p75-p25 exposure gap) = 11.8pp. HONEST SCOPE: the two-party VOTE-SHARE columns are NULL (all districts -1.08, SE 5.98; competitive +6.10, SE 4.93; solid-GOP -6.24, SE 3.93 - re-sorting, not uniform right shift); the win-probability effect emerges only from the 2010 mid-term (null 2002-2008, Feigenbaum-Hall consistency). Boundary-applied: NEVER chained" }, { "id": "eviction_order->eviction_earnings_response", "from": "eviction_order", "to": "eviction_earnings_response", "tier": "EXACT", "evidenceRole": "boundary", "citation": "collinson2024", "populationScope": "same design as the shelter row", "point": 0.8574, "low": 0.7444, "high": 0.9705, "notes": "queue-17 LANDED v1.21: evicted tenants' average QUARTERLY earnings, quarters 5-8 post-filing: IV -$613 (SE 248) on the $4,300 non-evicted mean = -14.3%; 95% CI = 1.96SE; stored as a gap multiplier: 1 - 613/4300 = 0.8574 (band 1 - CI/4300), 2016 USD in the derivation above. Year-1 window (quarters 1-4) is -$323 (SE 175), NOT significant - recorded, not landed (the stevens2011 timing pattern: the sustained window carries the identified effect). OLS -$269*** is SMALLER than IV - the authors read complier effects as larger than the average evicted tenant's. SUBGROUPS (Table VI): concentration among female (-$767, SE 295) and Black (-$931, SE 307) tenants in year 2; formal equality tests do not reject, so the full-sample point stands with the concentration noted. REFUSAL WIRING: the desmond2016 matched +11-22pp JOB-LOSS estimate is NOT encoded (CITING §1 class + collinson2024 refutes the size: employment IV -1.5pp (SE 2.1) year 1 / -1.8pp (SE 2.7) year 2, both null); see SPEC §10. PARALLEL STREAM: quarterly-earnings LEVEL response for the eviction-court population - NEVER composed into the worker_earnings displacement multiplier. Boundary-applied: NEVER chained" }, { "id": "household_ipv->child_internalizing_sd", "from": "household_ipv", "to": "child_internalizing_sd", "tier": "EXACT", "evidenceRole": "boundary", "citation": "evans2008", "populationScope": "children/adolescents 18 or younger exposed to interparental physical violence (second-generation studies, 1990-2006); k=58 samples, N=7,602", "point": 0.48, "low": 0.39, "high": 0.57, "notes": "queue-21 LANDED v1.23: meta-analytic internalizing effect. Random-effects model, k=58 samples (60 studies / 61 samples; second-generation 1990-2006 literature), N=7,602; d = .48 (SE .04), 95% CI .39-.57, z = 11.25; homogeneity ns (Q(56) = 70.61, p > .05) - so no moderator split landed. CROSS-CHECKS recorded, never averaged (CITING section 5): Kitzmann et al. 2003 d = -.50 (group design, published+unpublished 1978-2000); Wolfe et al. 2003 d = .38 (zr = .19 converted). Gender ns (boys .44 vs girls .39, QB = .34, p = .56). PARALLEL STREAM: boundary-applied exposure contrast - NEVER composed into the child_earnings/IGE chains or the achievement SD row; gender/age nulls declared. CLASS: meta-analysis sets points per CITING section 1 (band = reported CI); exposure mostly dichotomous and studies mostly cross-sectional - the ordering caveat is the authors' own. TRAUMA REFUSAL: d = 1.54 (SE .59, CI .38-2.71) NOT landed - k=6, heterogeneous (Q(5) = 18.35, p < .01), the authors themselves say interpret with caution. Read via the accepted manuscript (Nebraska DigitalCommons psychfacpub/321, Elsevier permission copy via Wayback mirror of the WAF-blocked PDF)" }, { "id": "household_ipv->child_externalizing_sd", "from": "household_ipv", "to": "child_externalizing_sd", "tier": "EXACT", "evidenceRole": "boundary", "citation": "evans2008", "populationScope": "children/adolescents 18 or younger exposed to interparental physical violence (second-generation studies, 1990-2006); k=53 samples, N=7,200; pooled across gender - boys .46 / girls .23", "point": 0.47, "low": 0.38, "high": 0.56, "notes": "queue-21 LANDED v1.23: meta-analytic externalizing effect. Random-effects model, k=53 samples, N=7,200; d = .47 (SE .05), 95% CI .38-.56, z = 10.11; HETEROGENEOUS (Q(52) = 80.35, p < .01) - moderators examined. CROSS-CHECKS recorded, never averaged (CITING section 5): Kitzmann et al. 2003 d = -.50 (group design, published+unpublished 1978-2000); Wolfe et al. 2003 d = .38 (zr = .19 converted). GENDER MODERATOR (significant, scope declared): boys d = .46 vs girls d = .23 (QB = 4.11, p < .05) - the pooled .47 pools a strong boy effect and a weak girl effect; age and age-by-gender ns (adolescent cells underpowered, k=4). PARALLEL STREAM: boundary-applied exposure contrast - NEVER composed into the child_earnings/IGE chains or the achievement SD row; gender/age nulls declared. CLASS: meta-analysis sets points per CITING section 1 (band = reported CI); exposure mostly dichotomous and studies mostly cross-sectional - the ordering caveat is the authors' own. TRAUMA REFUSAL: d = 1.54 (SE .59, CI .38-2.71) NOT landed - k=6, heterogeneous (Q(5) = 18.35, p < .01), the authors themselves say interpret with caution. Read via the accepted manuscript (Nebraska DigitalCommons psychfacpub/321, Elsevier permission copy via Wayback mirror of the WAF-blocked PDF)" }, { "id": "unemployment_status->mental_health_sd", "from": "unemployment_status", "to": "mental_health_sd", "tier": "EXACT", "evidenceRole": "boundary", "citation": "paul2009", "populationScope": "involuntary unemployed vs employed adults (26 countries, 1950-2004); cross-sectional meta k=315 samples, N=209,379, outliers excluded", "point": 0.51, "low": 0.47, "high": 0.54, "notes": "queue-20 LANDED v1.25: overall cross-sectional random-effects meta, outliers-excluded row (k=315 samples, N=209,379; 237 cross-sectional + 87 longitudinal studies, 26 mostly-Western countries, 1950-2004). Band = reported CI (CITING section 1 meta class; random-effects, conservative model by the authors' own choice). ALL-STUDIES row beside: d = 0.54 (SE .0184, CI .50-.57, k=323, N=458,820); outlier exclusion reduced it 0.54->0.51. HETEROGENEOUS (H = 1.91-2.70 across indicators; Q p<.001) - moderators examined. CASE-RATE translation (practical-importance anchor): psychological-problem case rates 34% (CI .31-.38, k=76) among unemployed vs 16% (CI .14-.18, k=74) among employed. CAUSALITY ANCHORS recorded beside (never averaged - CITING section 5): factory-closure natural experiments d = .38 (CI .25-.51, k=27, N=4,246, Qb=3.99 p<.05 vs other designs .55 - the causal-clean subset); longitudinal job loss d = .19 (CI .10-.29, k=19), reemployment d = .35 (CI .42-.28, k=45), RETEST-CORRECTED 0.25/0.29 (the repeated-measurement artifact explanation for the earlier metas' puzzling asymmetry); school->unemployment d = .10 ns. SELECTION effects (reverse causation) small but significant: distress->job loss d = .23, distress->worse reemployment d = .15, school .08 - declared: selection runs the OTHER way and is weak, not the driver. MODERATORS (scope-declared): men stronger (beta .22/.20 controlled), blue-collar stronger (beta .19 controlled; partially confounded with gender, reduced to .13 marginal), duration linear beta .13/.15 + curvilinear - distress peaks at 9 months (d = .73), stabilizes elevated in year 2, renewed worsening after 29 months UNSTABLE (k=5, cubic marginal in controlled analysis - not landed); country moderators: low-GDP d = .62 vs .49 (Qb=11.84), high-Gini .57 vs .48 (Qb=4.97), weak protection .58 vs .46 (Qb=8.61, confounded with Gini per the authors); age U-shape UNSTABLE (vanished when marital status controlled - not landed); marital status ns. PARALLEL STREAM: boundary-applied status contrast - NEVER composed into the child_earnings/IGE chains or the achievement SD rows. Read via owner-downloaded ScienceDirect PDF; marcus2013 CROSS-CHECK (v1.38): SOEP plant-closure entropy-balancing DiD, own mental health -2.72 MCS points = -0.272 SD (SE 0.74) ~11 months after closure - inside the causal-clean factory-closure subset (.25-.51), consistent; schallerstevens2015 CROSS-CHECK (v1.40): US MEPS (J Health Econ 43:190-203), preferred individual-FE + baseline-trend spec - P(fair/poor mental health) +1.39pp on 3.4% base (+40.9% relative), depression/anxiety +1.64pp on 7.3%; probability units, not SD-convertible - directional corroboration from US survey data; no chronic-condition incidence increase survives baseline-trend controls" }, { "id": "import_shock->radical_right_vote_share", "from": "import_shock_per_worker", "to": "radical_right_vote_share", "tier": "EXACT", "evidenceRole": "boundary", "citation": "colantone2018", "populationScope": "15 Western European countries, 76 legislative elections 1988-2007, 198 NUTS-2 regions; district-election panel N=7,782 (IV), country-year FE, SE clustered NUTS-2 x year", "point": 13.2, "low": 3.2, "high": 23.2, "notes": "queue-15 LANDED v1.26: IV Table 1 col 10, radical-right vote share. Coefficient .132*** (SE .051) in vote-share FRACTIONS per 1.0 ($1k/worker change in Chinese import exposure over the past 2 years) = 13.2 pp per $1k/worker of exposure (SE 5.1), CI = 1.96 SE. AUTHORS' OWN SCALING: one SD of the 2-year shock (.133 = $133/worker) -> +1.7pp radical-right vote share, on an average RR share of 5% (SD 7%). IV (.132) > OLS (.041, SE .023): positive domestic demand shocks attenuate the OLS association (authors' interpretation). First stage: Chinese imports to the US as instrument, Kleibergen-Paap F = 19.2. Robustness (Table 3-4): historical-trajectory trend interactions (coefficients equal or larger), year-specific regional controls (larger), alternative exchange-rate IV, exports and FDI nulls, EU-import controls (EU15 negative on Nationalist Autarchy, EU12 positive on the radical right). NO-LEFT-WING discipline: protectionist left NULL (IV -.052, SE .047), protectionist left proper NULL (-.081, SE .042), liberal right NULL (-.017, SE .075) - NO polarization, which CONTRASTS with the Autor et al. 2020 US finding (declared on that row); pro-trade left NEGATIVE significant (-.134**, SE .054) - the electorate abandons mainstream social-democratic parties; protectionist right POSITIVE .278*** (SE .094). INDIVIDUAL-LEVEL (ESS waves 1-4, Table 5-6): confirms the district evidence; NO significant group heterogeneity - interactions all n.s., the response is SOCIOTROPIC (service and public-sector workers respond too; only students sheltered, n.s. overall) - declared so no surface reads this row as a displaced-manufacturers-only effect, and so no surface quotes paul2009's person-level unemployment distress as the transmission mechanism here. WINDOW DISCIPLINE: the regression's shock is the 2-year window change; the row stores the same coefficient expressed per $1k/worker of cumulative exposure (13.2pp), which assumes each window's shock persists to the next election - the authors' 1-SD scaling reads directly off this coefficient. Boundary-applied: NEVER chained into the earnings/IGE chains. Read via the owner-downloaded PDF (the published AJPS doi, not the SSRN preprint doi the staging bib carried)" }, { "id": "displacement_event->exam_noncompletion_hazard", "from": "displacement_event", "to": "exam_noncompletion_hazard", "tier": "EXACT", "evidenceRole": "conditional", "citation": "bingley2026", "populationScope": "same children/scope as the child_achievement_sd row; outcome = obtains NO grade-9 exam scores or teacher assessments (control mean 7.85%)", "point": 1.0688, "low": 1.0014, "high": 1.1362, "notes": "queue-sweep LANDED v1.40, same read as the child_achievement_sd row. DERIVED RELATIVE (pp effect / control mean; stevens2011 derivation precedent): Table 2 col 2 (preferred) 'Treated X Exposure (age 0-16)' +0.0054 (SE 0.0027) on control mean 0.0785 -> 1 + 0.0054/0.0785 = 1.0688; band = 1.96 x SE/0.0785. AUTHORS' FRAME: explains 6-9% of observed non-completion (base ~7%; test-taking near-universal at 16). TIMING STRUCTURE, monotone by age at exposure: infancy (0-1) +0.99pp (SE 0.41) -> 1.126 [1.96SE 1.024..1.228]; early childhood (2-5) +0.76pp -> ~1.097; mid (6-11) +0.45pp n.s.; late (12-16) +0.30pp n.s.; exposure at age >=18 jointly zero (p=0.986 - identifying-assumption placebo). Completing exams BY AGE 16: infancy -1.44pp (SE 0.65). Concentrated in below-median-income families (no detectable effect above median); displaced father > mother, sons > daughters (qualitative). Conditional: Danish compulsory-school institution; left-tail outcome capturing the most vulnerable children" } ] ``` ### Unidentified records · excluded from citations These original bibliography records could not be identified. They are retained for inspection and are not used as evidence. ```json [ { "key": "adermon2018", "author": "Adermon, Adrian and Lindahl, Mikael and Waldenstr{\\\"o}m, Daniel", "title": "Intergenerational Mobility in Pension Income: An Adoptee Perspective", "year": "2018", "evidence": "canonical" }, { "key": "lindo2018", "author": "Lindo, Jason M. and Schaller, Jessamyn and Hansen, Benjamin", "title": "Causes and Consequences of Child Maltreatment: Evidence from the Supplemental Nutrition Assistance Program", "year": "2018", "evidence": "canonical" } ] ``` The linked methods, paper and parameter file preserve the original model release. They include inputs withdrawn from the estimates on this page. ## More - Full page (charts, tables, interactive): /downstream Methods paper PDF (identifies parameter set v1.52): https://github.com/xh1b/downstream/blob/d7691dac652a81bddb16c9f91a9cf8ecd88b70db/paper/downstream.pdf Readable methods HTML: /downstream/methods-48a2c71b96fb1726.html Specification: https://github.com/xh1b/downstream/blob/d7691dac652a81bddb16c9f91a9cf8ecd88b70db/SPEC.md Source repository: https://github.com/xh1b/downstream