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MaxGhenis/state_ui_child_poverty.ipynb

Created January 31, 2026 21:19
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Impact of UI on child poverty by state: repeal vs. doubling (PolicyEngine-US 2026, state-level microsims)
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state_ui_child_poverty.ipynb
{
"nbformat": 4,
"nbformat_minor": 5,
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.14.0"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Impact of unemployment insurance on child poverty by state: repeal vs. doubling\n",
"\n",
"This notebook analyzes how repealing and doubling UI benefits would affect child poverty\n",
"in each of the 50 states + DC in 2026, using PolicyEngine-US microsimulation with\n",
"state-level calibrated datasets from HuggingFace.\n",
"\n",
"**Methodology:**\n",
"- For each state, run three microsimulations: baseline, UI zeroed (repeal), UI doubled\n",
"- State datasets are calibrated to match state-level IRS SOI targets\n",
"- Uses SPM (Supplemental Poverty Measure) for poverty measurement\n",
"- Changes cascade through tax calculations and other benefits (SNAP, etc.)\n",
"\n",
"**Total runtime:** 765.5s (12.8 min) for 51 jurisdictions \u00d7 3 simulations = 153 total sims\n",
"\n",
"**PolicyEngine-US version:** 1.525.0"
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"from policyengine_us import Microsimulation\n",
"import numpy as np\n",
"import pandas as pd\n",
"import time\n",
"\n",
"YEAR = 2026\n",
"HF_BASE = \"hf://policyengine/policyengine-us-data/states\"\n",
"\n",
"STATES = [\n",
" \"AL\", \"AK\", \"AZ\", \"AR\", \"CA\", \"CO\", \"CT\", \"DC\", \"DE\", \"FL\",\n",
" \"GA\", \"HI\", \"IA\", \"ID\", \"IL\", \"IN\", \"KS\", \"KY\", \"LA\", \"MA\",\n",
" \"MD\", \"ME\", \"MI\", \"MN\", \"MO\", \"MS\", \"MT\", \"NC\", \"ND\", \"NE\",\n",
" \"NH\", \"NJ\", \"NM\", \"NV\", \"NY\", \"OH\", \"OK\", \"OR\", \"PA\", \"RI\",\n",
" \"SC\", \"SD\", \"TN\", \"TX\", \"UT\", \"VA\", \"VT\", \"WA\", \"WI\", \"WV\",\n",
" \"WY\",\n",
"]"
],
"execution_count": 1,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Run simulations for each state"
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"def run_state(state_code):\n",
" \"\"\"Run baseline, repeal, and doubling sims for a single state.\"\"\"\n",
" dataset = f\"{HF_BASE}/{state_code}.h5\"\n",
"\n",
" baseline = Microsimulation(dataset=dataset)\n",
" is_child = baseline.calc(\"is_child\", period=YEAR)\n",
" total_children = float(is_child.sum())\n",
" baseline_poverty = baseline.calc(\"person_in_poverty\", period=YEAR)\n",
" baseline_rate = float(baseline_poverty[is_child.values == 1].mean())\n",
" baseline_ui = float(baseline.calc(\"unemployment_compensation\", period=YEAR).sum())\n",
" baseline_net_income = baseline.calc(\"spm_unit_net_income\", period=YEAR)\n",
"\n",
" repeal = Microsimulation(dataset=dataset)\n",
" repeal.set_input(\"unemployment_compensation\", YEAR,\n",
" repeal.calc(\"unemployment_compensation\", period=YEAR).values * 0)\n",
" repeal_poverty = repeal.calc(\"person_in_poverty\", period=YEAR)\n",
" repeal_rate = float(repeal_poverty[is_child.values == 1].mean())\n",
" repeal_net_income_change = float(\n",
" (repeal.calc(\"spm_unit_net_income\", period=YEAR) - baseline_net_income).sum())\n",
"\n",
" doubled = Microsimulation(dataset=dataset)\n",
" doubled.set_input(\"unemployment_compensation\", YEAR,\n",
" doubled.calc(\"unemployment_compensation\", period=YEAR).values * 2)\n",
" doubled_poverty = doubled.calc(\"person_in_poverty\", period=YEAR)\n",
" doubled_rate = float(doubled_poverty[is_child.values == 1].mean())\n",
" doubled_net_income_change = float(\n",
" (doubled.calc(\"spm_unit_net_income\", period=YEAR) - baseline_net_income).sum())\n",
"\n",
" return {\n",
" \"state\": state_code,\n",
" \"total_children\": total_children,\n",
" \"total_ui_billions\": baseline_ui / 1e9,\n",
" \"baseline_child_poverty_rate\": baseline_rate,\n",
" \"repeal_child_poverty_rate\": repeal_rate,\n",
" \"doubled_child_poverty_rate\": doubled_rate,\n",
" \"repeal_increase_pp\": repeal_rate - baseline_rate,\n",
" \"doubled_reduction_pp\": baseline_rate - doubled_rate,\n",
" \"repeal_children_into_poverty\": total_children * (repeal_rate - baseline_rate),\n",
" \"doubled_children_lifted\": total_children * (baseline_rate - doubled_rate),\n",
" \"repeal_net_income_change_billions\": repeal_net_income_change / 1e9,\n",
" \"doubled_net_income_change_billions\": doubled_net_income_change / 1e9,\n",
" }\n",
"\n",
"\n",
"total_start = time.time()\n",
"results = []\n",
"for i, state in enumerate(STATES):\n",
" t0 = time.time()\n",
" result = run_state(state)\n",
" results.append(result)\n",
" elapsed = time.time() - t0\n",
" print(f\"[{i+1}/{len(STATES)}] {state}: {elapsed:.1f}s | \"\n",
" f\"baseline={result['baseline_child_poverty_rate']:.1%} \"\n",
" f\"repeal={result['repeal_child_poverty_rate']:.1%} \"\n",
" f\"doubled={result['doubled_child_poverty_rate']:.1%}\")\n",
"\n",
"total_elapsed = time.time() - total_start\n",
"print(f\"\\nTotal: {total_elapsed:.1f}s ({total_elapsed/60:.1f} min) for {len(STATES)} states\")\n",
"\n",
"df = pd.DataFrame(results)"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[1/51] AL: ... | baseline=19.7% repeal=19.7% doubled=19.6%\n[2/51] AK: ... | baseline=21.4% repeal=21.4% doubled=21.4%\n[3/51] AZ: ... | baseline=25.4% repeal=25.6% doubled=25.4%\n[4/51] AR: ... | baseline=18.1% repeal=18.2% doubled=18.1%\n[5/51] CA: ... | baseline=29.5% repeal=30.2% doubled=29.2%\n[6/51] CO: ... | baseline=16.5% repeal=16.6% doubled=16.4%\n[7/51] CT: ... | baseline=21.1% repeal=21.8% doubled=21.0%\n[8/51] DC: ... | baseline=21.5% repeal=21.8% doubled=21.5%\n[9/51] DE: ... | baseline=20.9% repeal=21.1% doubled=20.9%\n[10/51] FL: ... | baseline=32.5% repeal=32.6% doubled=32.4%\n[11/51] GA: ... | baseline=25.1% repeal=25.1% doubled=25.0%\n[12/51] HI: ... | baseline=23.7% repeal=24.1% doubled=23.4%\n[13/51] IA: ... | baseline=15.0% repeal=15.2% doubled=15.0%\n[14/51] ID: ... | baseline=14.1% repeal=14.3% doubled=14.1%\n[15/51] IL: ... | baseline=22.3% repeal=22.7% doubled=22.2%\n[16/51] IN: ... | baseline=19.3% repeal=19.4% doubled=19.3%\n[17/51] KS: ... | baseline=14.9% repeal=15.0% doubled=14.9%\n[18/51] KY: ... | baseline=18.9% repeal=19.1% doubled=18.8%\n[19/51] LA: ... | baseline=24.2% repeal=24.3% doubled=24.2%\n[20/51] MA: ... | baseline=23.4% repeal=24.3% doubled=23.1%\n[21/51] MD: ... | baseline=24.9% repeal=25.1% doubled=24.8%\n[22/51] ME: ... | baseline=19.2% repeal=19.4% doubled=19.2%\n[23/51] MI: ... | baseline=21.7% repeal=22.1% doubled=21.7%\n[24/51] MN: ... | baseline=15.5% repeal=15.8% doubled=15.4%\n[25/51] MO: ... | baseline=18.8% repeal=18.9% doubled=18.7%\n[26/51] MS: ... | baseline=20.0% repeal=20.1% doubled=20.0%\n[27/51] MT: ... | baseline=17.9% repeal=18.1% doubled=17.8%\n[28/51] NC: ... | baseline=22.3% repeal=22.3% doubled=22.3%\n[29/51] ND: ... | baseline=14.6% repeal=14.6% doubled=14.6%\n[30/51] NE: ... | baseline=17.1% repeal=17.1% doubled=17.1%\n[31/51] NH: ... | baseline=19.6% repeal=19.8% doubled=19.6%\n[32/51] NJ: ... | baseline=21.1% repeal=21.8% doubled=20.8%\n[33/51] NM: ... | baseline=25.7% repeal=26.0% doubled=25.7%\n[34/51] NV: ... | baseline=28.4% repeal=29.0% doubled=28.4%\n[35/51] NY: ... | baseline=27.4% repeal=27.9% doubled=27.3%\n[36/51] OH: ... | baseline=19.8% repeal=19.9% doubled=19.8%\n[37/51] OK: ... | baseline=22.0% repeal=22.1% doubled=21.9%\n[38/51] OR: ... | baseline=25.2% repeal=25.7% doubled=25.2%\n[39/51] PA: ... | baseline=21.7% repeal=22.2% doubled=21.6%\n[40/51] RI: ... | baseline=22.7% repeal=23.7% doubled=22.7%\n[41/51] SC: ... | baseline=20.5% repeal=20.6% doubled=20.5%\n[42/51] SD: ... | baseline=20.2% repeal=20.2% doubled=20.2%\n[43/51] TN: ... | baseline=22.7% repeal=22.8% doubled=22.7%\n[44/51] TX: ... | baseline=28.7% repeal=29.1% doubled=28.6%\n[45/51] UT: ... | baseline=13.9% repeal=14.0% doubled=13.9%\n[46/51] VA: ... | baseline=21.4% repeal=21.5% doubled=21.4%\n[47/51] VT: ... | baseline=20.6% repeal=21.0% doubled=20.6%\n[48/51] WA: ... | baseline=24.7% repeal=26.1% doubled=24.6%\n[49/51] WI: ... | baseline=17.3% repeal=17.4% doubled=17.3%\n[50/51] WV: ... | baseline=21.6% repeal=21.7% doubled=21.5%\n[51/51] WY: ... | baseline=13.6% repeal=13.6% doubled=13.5%\n\nTotal: 765.5s (12.8 min) for 51 states"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## National aggregates"
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"total_children = df[\"total_children\"].sum()\n",
"national_baseline = (df[\"baseline_child_poverty_rate\"] * df[\"total_children\"]).sum() / total_children\n",
"national_repeal = (df[\"repeal_child_poverty_rate\"] * df[\"total_children\"]).sum() / total_children\n",
"national_doubled = (df[\"doubled_child_poverty_rate\"] * df[\"total_children\"]).sum() / total_children\n",
"\n",
"print(\"NATIONAL AGGREGATES (child-weighted across states)\")\n",
"print(f\" Baseline child poverty: {national_baseline:.2%}\")\n",
"print(f\" Repeal UI: {national_repeal:.2%} (+{national_repeal - national_baseline:.2%})\")\n",
"print(f\" Double UI: {national_doubled:.2%} (-{national_baseline - national_doubled:.2%})\")\n",
"print(f\" Children into poverty (repeal): {df['repeal_children_into_poverty'].sum():,.0f}\")\n",
"print(f\" Children lifted (doubling): {df['doubled_children_lifted'].sum():,.0f}\")\n",
"print(f\" Total UI (baseline): ${df['total_ui_billions'].sum():.1f}B\")\n",
"print(f\" Net income change (repeal): ${df['repeal_net_income_change_billions'].sum():.1f}B\")\n",
"print(f\" Net income change (doubling): ${df['doubled_net_income_change_billions'].sum():.1f}B\")"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"NATIONAL AGGREGATES (child-weighted across states)\n Baseline child poverty: 23.91%\n Repeal UI: 24.24% (+0.33%)\n Double UI: 23.83% (-0.08%)\n Children into poverty (repeal): 254,365\n Children lifted (doubling): 63,024\n Total UI (baseline): $42.4B\n Net income change (repeal): $-34.4B\n Net income change (doubling): $33.4B"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Top 10 states by repeal impact (child poverty increase)"
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"top_repeal = df.nlargest(10, \"repeal_increase_pp\")\n",
"top_repeal[[\"state\", \"baseline_child_poverty_rate\", \"repeal_child_poverty_rate\",\n",
" \"repeal_increase_pp\", \"repeal_children_into_poverty\"]].style.format({\n",
" \"baseline_child_poverty_rate\": \"{:.2%}\",\n",
" \"repeal_child_poverty_rate\": \"{:.2%}\",\n",
" \"repeal_increase_pp\": \"+{:.2%}\",\n",
" \"repeal_children_into_poverty\": \"{:,.0f}\",\n",
"})"
],
"execution_count": 4,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" state baseline_child_poverty_rate repeal_child_poverty_rate repeal_increase_pp repeal_children_into_poverty\n47 WA 0.247143 0.260597 0.013454 23683.071850\n39 RI 0.227004 0.236659 0.009655 2145.162720\n19 MA 0.234324 0.243064 0.008740 12737.398739\n6 CT 0.211020 0.218134 0.007114 5525.743126\n31 NJ 0.210556 0.217514 0.006957 14805.772559\n4 CA 0.295325 0.301625 0.006300 56625.902204\n33 NV 0.284125 0.289951 0.005826 4238.041076\n38 PA 0.216508 0.221572 0.005064 14397.662886\n34 NY 0.274450 0.279381 0.004931 20836.353414\n37 OR 0.252346 0.256602 0.004256 3744.121133"
]
},
"metadata": {},
"execution_count": 4
}
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Top 10 states by doubling impact (child poverty reduction)"
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"top_doubled = df.nlargest(10, \"doubled_reduction_pp\")\n",
"top_doubled[[\"state\", \"baseline_child_poverty_rate\", \"doubled_child_poverty_rate\",\n",
" \"doubled_reduction_pp\", \"doubled_children_lifted\"]].style.format({\n",
" \"baseline_child_poverty_rate\": \"{:.2%}\",\n",
" \"doubled_child_poverty_rate\": \"{:.2%}\",\n",
" \"doubled_reduction_pp\": \"-{:.2%}\",\n",
" \"doubled_children_lifted\": \"{:,.0f}\",\n",
"})"
],
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" state baseline_child_poverty_rate doubled_child_poverty_rate doubled_reduction_pp doubled_children_lifted\n11 HI 0.237300 0.233781 0.003519 1087.619537\n19 MA 0.234324 0.231383 0.002941 4286.188429\n4 CA 0.295325 0.292440 0.002885 25930.013116\n31 NJ 0.210556 0.208398 0.002158 4592.444680\n34 NY 0.274450 0.272760 0.001690 7140.500802\n47 WA 0.247143 0.245859 0.001284 2260.485893\n20 MD 0.249268 0.248206 0.001061 1531.155141\n6 CT 0.211020 0.210233 0.000787 611.273614\n12 IA 0.150406 0.149733 0.000673 516.879625\n18 LA 0.242484 0.241831 0.000653 740.856899"
]
},
"metadata": {},
"execution_count": 5
}
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Full state results"
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"# All states sorted alphabetically\n",
"display_cols = [\"state\", \"total_children\", \"total_ui_billions\",\n",
" \"baseline_child_poverty_rate\", \"repeal_child_poverty_rate\",\n",
" \"doubled_child_poverty_rate\", \"repeal_increase_pp\",\n",
" \"doubled_reduction_pp\", \"repeal_children_into_poverty\",\n",
" \"doubled_children_lifted\"]\n",
"df[display_cols].sort_values(\"state\").style.format({\n",
" \"total_children\": \"{:,.0f}\",\n",
" \"total_ui_billions\": \"${:.2f}B\",\n",
" \"baseline_child_poverty_rate\": \"{:.2%}\",\n",
" \"repeal_child_poverty_rate\": \"{:.2%}\",\n",
" \"doubled_child_poverty_rate\": \"{:.2%}\",\n",
" \"repeal_increase_pp\": \"+{:.2%}\",\n",
" \"doubled_reduction_pp\": \"-{:.2%}\",\n",
" \"repeal_children_into_poverty\": \"{:,.0f}\",\n",
" \"doubled_children_lifted\": \"{:,.0f}\",\n",
"})"
],
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"State Children UI ($B) Baseline Repeal Double Repeal \u0394 Double \u0394\n AL 1,202,651 $0.20 19.68% 19.71% 19.65% +0.03% -0.03%\n AK 175,056 $0.09 21.43% 21.43% 21.43% +0.00% -0.00%\n AZ 1,685,809 $0.46 25.39% 25.60% 25.38% +0.20% -0.02%\n AR 732,074 $0.14 18.12% 18.24% 18.07% +0.11% -0.05%\n CA 8,988,055 $9.16 29.53% 30.16% 29.24% +0.63% -0.29%\n CO 1,290,231 $0.59 16.48% 16.63% 16.44% +0.15% -0.04%\n CT 776,764 $0.82 21.10% 21.81% 21.02% +0.71% -0.08%\n DC 139,333 $0.08 21.50% 21.77% 21.50% +0.27% -0.00%\n DE 225,678 $0.10 20.93% 21.12% 20.90% +0.20% -0.03%\n FL 4,769,900 $1.33 32.49% 32.57% 32.44% +0.08% -0.04%\n GA 2,668,404 $0.59 25.06% 25.14% 25.02% +0.09% -0.04%\n HI 309,099 $0.27 23.73% 24.14% 23.38% +0.41% -0.35%\n IA 768,072 $0.32 15.04% 15.19% 14.97% +0.15% -0.07%\n ID 488,435 $0.15 14.08% 14.26% 14.06% +0.18% -0.02%\n IL 2,898,799 $1.90 22.26% 22.68% 22.21% +0.42% -0.05%\n IN 1,675,297 $0.36 19.28% 19.41% 19.27% +0.13% -0.01%\n KS 721,175 $0.15 14.95% 14.96% 14.90% +0.02% -0.05%\n KY 1,065,433 $0.36 18.89% 19.06% 18.85% +0.17% -0.04%\n LA 1,134,012 $0.27 24.25% 24.32% 24.18% +0.07% -0.07%\n MA 1,457,348 $2.42 23.43% 24.31% 23.14% +0.87% -0.29%\n MD 1,442,745 $0.59 24.93% 25.08% 24.82% +0.16% -0.11%\n ME 263,488 $0.14 19.21% 19.44% 19.21% +0.22% -0.00%\n MI 2,251,464 $1.23 21.75% 22.08% 21.73% +0.33% -0.02%\n MN 1,378,158 $1.04 15.47% 15.81% 15.42% +0.35% -0.05%\n MO 1,451,419 $0.32 18.77% 18.87% 18.73% +0.09% -0.04%\n MS 718,888 $0.13 19.96% 20.06% 19.96% +0.09% -0.00%\n MT 247,133 $0.13 17.86% 18.09% 17.81% +0.22% -0.06%\n NC 2,481,945 $0.41 22.30% 22.33% 22.26% +0.03% -0.04%\n ND 192,884 $0.08 14.58% 14.58% 14.57% +0.00% -0.01%\n NE 506,288 $0.09 17.07% 17.09% 17.07% +0.02% -0.00%\n NH 272,691 $0.16 19.56% 19.81% 19.56% +0.25% -0.00%\n NJ 2,128,088 $2.69 21.06% 21.75% 20.84% +0.70% -0.22%\n NM 478,991 $0.22 25.70% 25.96% 25.70% +0.25% -0.00%\n NV 727,406 $0.46 28.41% 29.00% 28.40% +0.58% -0.01%\n NY 4,225,639 $3.52 27.45% 27.94% 27.28% +0.49% -0.17%\n OH 2,733,370 $0.98 19.79% 19.91% 19.77% +0.12% -0.02%\n OK 1,023,852 $0.27 21.96% 22.08% 21.91% +0.12% -0.05%\n OR 879,785 $0.65 25.23% 25.66% 25.18% +0.43% -0.06%\n PA 2,843,147 $2.02 21.65% 22.16% 21.63% +0.51% -0.03%\n RI 222,181 $0.29 22.70% 23.67% 22.68% +0.97% -0.02%\n SC 1,211,730 $0.23 20.54% 20.57% 20.51% +0.03% -0.03%\n SD 220,971 $0.06 20.17% 20.17% 20.17% +0.00% -0.00%\n TN 1,662,310 $0.40 22.74% 22.75% 22.74% +0.02% -0.00%\n TX 7,925,725 $3.32 28.66% 29.06% 28.65% +0.40% -0.01%\n UT 962,101 $0.18 13.88% 13.96% 13.87% +0.08% -0.01%\n VA 2,003,654 $0.37 21.40% 21.46% 21.39% +0.06% -0.01%\n VT 125,498 $0.08 20.63% 21.01% 20.63% +0.38% -0.00%\n WA 1,760,288 $1.94 24.71% 26.06% 24.59% +1.35% -0.13%\n WI 1,316,984 $0.44 17.35% 17.44% 17.34% +0.10% -0.01%\n WV 379,073 $0.16 21.57% 21.72% 21.52% +0.15% -0.05%\n WY 137,283 $0.05 13.57% 13.57% 13.53% +0.00% -0.04%"
]
},
"metadata": {},
"execution_count": 6
}
]
},
{
"cell_type": "code",
"metadata": {},
"source": [
"from importlib.metadata import version\n",
"print(f\"PolicyEngine-US version: {version('policyengine-us')}\")"
],
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"PolicyEngine-US version: 1.525.0"
]
}
]
}
]
}
Raw
state_ui_child_poverty_results.csv
state total_children total_ui_billions baseline_child_poverty_rate repeal_child_poverty_rate doubled_child_poverty_rate repeal_increase_pp doubled_reduction_pp repeal_children_into_poverty doubled_children_lifted repeal_net_income_change_billions doubled_net_income_change_billions
AL 1202650.6300404768 0.20334580025176704 0.19682392603794643 0.19710691134671182 0.19649718766514757 0.00028298530876538774 0.0003267383727988682 340.33245987889245 392.952109904959 -0.1717821577758353 0.17073778955456603
AK 175056.13950728183 0.0903962333692376 0.21431718288320262 0.21431718288320262 0.21431718288320262 0.0 0.0 0.0 0.0 -0.06535990134695355 0.0727991005189191
AZ 1685809.130016325 0.4602573131932434 0.25393554256592926 0.2559557668361029 0.2537585565377616 0.0020202242701736206 0.0001769860281676805 3405.7125193392567 298.36466217040226 -0.3754060711609629 0.35769625264472643
AR 732073.7678552107 0.14320999353524078 0.18123011554273097 0.18235781003690613 0.18068902257264885 0.0011276944941751577 0.0005410929700821188 825.5555573403836 396.11996936798346 -0.11662832186838669 0.11344168673428413
CA 8988054.538800022 9.155268136615948 0.29532458282799096 0.30162471173343997 0.29243964115300686 0.0063001289054490095 0.0028849416749840984 56625.90220364618 25930.01311601416 -7.687854340099521 7.465531186398171
CO 1290230.7273362658 0.5900320453821395 0.16475055431486152 0.16626747596812105 0.16435133561041326 0.0015169216532595342 0.00039921870444825647 1957.1789279971797 515.0842394065157 -0.4599073123810685 0.45188357898899556
CT 776763.6104155292 0.8211252124254173 0.21102011840723078 0.21813392118045744 0.21023316906269654 0.007113802773226652 0.0007869493445342435 5525.743125915538 611.2736140745532 -0.6495314952980937 0.6202491798839798
DC 139332.83242663316 0.08318128697926229 0.21498446758687859 0.21770313421578413 0.21498446758687859 0.0027186666289055472 0.0 378.7995218291763 0.0 -0.06798402830296235 0.06682152262747475
DE 225678.4563994806 0.09648983567298158 0.20927847667145794 0.21124989667973731 0.20898725854701727 0.0019714200082793787 0.000291218124440662 444.90702438354145 65.72165679932046 -0.07621446369123663 0.07372200279472703
FL 4769900.065206092 1.3270832728799704 0.32486122320761235 0.3256693141896995 0.3244160385565304 0.0008080909820871729 0.0004451846510819535 3854.513228150061 2123.486296224561 -1.0950223887049337 1.0714428552911193
GA 2668403.7976327967 0.588906870713737 0.2505711551004414 0.2514347089077316 0.25016305466372635 0.000863553807290196 0.00040810043671507534 2304.3102588334195 1088.9767551461098 -0.4744885969687842 0.4602364022885087
HI 309099.0156309607 0.2699570155100037 0.23729963893633618 0.24138979610179545 0.2337809621293804 0.004090157165459268 0.0035186768069557783 1264.2635536193802 1087.619537353523 -0.20274403729098683 0.20266436362783802
IA 768072.1373110258 0.3226278084169104 0.15040559255046254 0.15188591105026325 0.1497326354158384 0.001480318499800709 0.000672957134624147 1136.991394042982 516.8796247094723 -0.2639253571252238 0.2517333284493637
ID 488434.92865129746 0.14786675060754473 0.140824476718541 0.1425812963934009 0.14059546939772782 0.001756819674859883 0.00022900732081318487 858.0920925433826 111.85517440201274 -0.11874520585595405 0.11531473512537131
IL 2898799.2429649658 1.8959320847474246 0.2225501582648133 0.22676893201727433 0.2220579063297603 0.004218773752461019 0.0004922519350530064 12229.37815987447 1426.9395366796944 -1.499323652386219 1.4425440385621457
IN 1675296.6298815827 0.355778572909399 0.19278249131093378 0.19411920612852077 0.19271523400546933 0.001336714817586987 6.725730546444653e-05 2239.3938290162537 112.67593717950342 -0.28991925320305373 0.2813575158303727
KS 721174.8136803242 0.15485422007861344 0.1494685368571491 0.14962052958637148 0.14898044605821636 0.00015199272922239437 0.0004880907989327221 109.61332817772424 351.99879097938646 -0.12544205431362676 0.12067523837351674
KY 1065433.374547214 0.36114224382739984 0.18890184305897265 0.19059440592863622 0.1884577479906471 0.001692562869663572 0.00044409506832554513 1803.3129698589757 473.1537072658611 -0.28692599462295426 0.2779121743810364
LA 1134012.0194222308 0.27089546026321354 0.24248436367286166 0.2431614831387961 0.24183105763564988 0.0006771194659344337 0.0006533060372117816 767.8616129544096 740.8568985592675 -0.2192973706597456 0.2094116994823436
MA 1457347.919335797 2.4188011337825612 0.23432415496099535 0.24306427704873396 0.23138306699433211 0.008740122087738611 0.0029410879666632306 12737.398739306707 4286.188428800209 -1.8978025640809928 1.8385603975726594
MD 1442745.1270782095 0.5873625943713037 0.2492676924401436 0.25082447522507445 0.24820641341594818 0.001556782784930849 0.0010612790241954217 2246.040776878227 1531.155140628262 -0.4614401391479247 0.4514791823714639
ME 263487.5172661381 0.1403829336312841 0.19211060838330665 0.19435361402412618 0.19211054751022563 0.0022430056408195287 6.087308102031841e-08 591.0039875134808 0.01603929698638417 -0.11044054361227694 0.10539802499792507
MI 2251463.790653994 1.2307367904858681 0.21748455229041933 0.2207505285343129 0.2172533772920387 0.0032659762438935758 0.00023117499838062883 7353.227254262522 520.4821381584815 -0.9688930219203333 0.9463126656067748
MN 1378158.4031145456 1.0428961427347447 0.1546585944633963 0.15814142634707204 0.1541873117396364 0.0034828318836757355 0.00047128272375990266 4799.894027122977 649.502245992421 -0.8191648972759188 0.7700783787022445
MO 1451418.8307794249 0.3215921706851125 0.18773824038425793 0.18868000332331128 0.18734143204203801 0.0009417629390533477 0.00039680834221991756 1366.8924638722046 575.9351001083546 -0.2620008789961781 0.2495636413275326
MS 718887.6861817541 0.13148217981289545 0.19964474263788742 0.20057128411303468 0.19962040009928192 0.0009265414751472578 2.434253860550406e-05 666.0792572200414 17.499551253900837 -0.1069334502267543 0.10553170436367255
MT 247133.007207261 0.12787498677784756 0.1786374011200733 0.18086072588475824 0.17807209936238058 0.0022233247646849252 0.0005653017576927322 549.4569350949615 139.7047233581553 -0.1026889340928633 0.09919220859834003
NC 2481944.5208605714 0.40890613774279017 0.22300140152643239 0.22329154406435667 0.2225922995722702 0.0002901425379242817 0.00040910195416218875 720.1176822697515 1015.368353606197 -0.3248791765047771 0.3184249908558844
ND 192883.94486008462 0.077859855751616 0.145750423412809 0.14578073289283544 0.14568610556993145 3.0309480026441404e-05 6.431784287755371e-05 5.84621207415796 12.405879259113656 -0.0653817239206461 0.0626127860770946
NE 506287.63118712086 0.08705346130796501 0.17071167127273235 0.17086208294684188 0.17071092786303146 0.00015041167410953515 7.434097008818252e-07 76.15157018780575 0.37637913646098536 -0.07082287562668976 0.0703300937344564
NH 272691.31441301794 0.1612741767858445 0.1956408454148181 0.19811785891707426 0.19564084040011984 0.0024770135022561535 5.014698267746809e-09 675.4600677490234 0.0013674646620165615 -0.13932879897056327 0.13384619600626535
NJ 2128087.727897618 2.6853639087412127 0.21055646784773618 0.21751378091544343 0.20839845310992638 0.006957313067707249 0.002158014737809799 14805.772558529527 4592.444680155229 -2.2503250206546377 2.1922166615404524
NM 478991.4751615741 0.2233678255998862 0.25704114079020385 0.2595864637290444 0.2570411225222703 0.0025453229388405774 1.826793355474976e-08 1219.187989237841 0.008750184441543206 -0.17816620471980035 0.16952613102914144
NV 727405.5718059521 0.4633757290546251 0.28412481076972634 0.2899510530205655 0.28400606544229134 0.005826242250839164 0.00011874532743499921 4238.04107595166 86.37601280214062 -0.3924751119873389 0.3810686663110962
NY 4225639.276017142 3.521945643864442 0.2744501075766828 0.2793810427684279 0.27276030389603045 0.004930935191745089 0.0016898036806523575 20836.35341373317 7140.500801722931 -2.7141078132310414 2.6052184869905015
OH 2733370.119419235 0.9836366266703656 0.19788860407282727 0.19913527601664766 0.1976925925680425 0.0012466719438203877 0.00019601150478476548 3407.6158399569426 535.7719902410784 -0.7986618066681604 0.7842271353679009
OK 1023852.2601124952 0.2657748627974801 0.21955321966842856 0.22079392078867596 0.2190552329715945 0.001240701120247406 0.0004979866968340685 1270.2946460894113 509.864805059517 -0.2103618986949487 0.20244219176454356
OR 879785.0487799975 0.6473884878626265 0.25234597323582647 0.25660169585656384 0.2517724984524852 0.004255722620737368 0.0005734747833412435 3744.121133479564 504.53454023597436 -0.49470820582786346 0.47405425223027586
PA 2843147.3518972876 2.0234345616782234 0.2165075720003143 0.2215715595832518 0.21625162723001234 0.005063987582937496 0.00025594477030196905 14397.662886469489 727.6886959160029 -1.694803376653566 1.6568565435831937
RI 222180.86815058364 0.29232266354158715 0.227004104970129 0.2366591339448361 0.22679932559961968 0.009655028974707103 0.00020477937050930595 2145.1627196194636 45.49805831908762 -0.23599275240306206 0.22663995165503378
SC 1211730.3729222403 0.22686630206302053 0.2054182404445394 0.2056739129464381 0.20514940225483924 0.0002556725018987016 0.0002688381897001657 309.8061360716759 325.7593998611218 -0.1847144248937156 0.18036741273530724
SD 220971.3609758336 0.05767950211360584 0.20171994454278433 0.20172048830422296 0.20171994454278433 5.437614386261114e-07 0.0 0.12015570513938904 0.0 -0.04902296204819046 0.04810145953693895
TN 1662310.286777633 0.4002357039832469 0.22738473919225344 0.227546583678733 0.22738473917480234 0.00016184448647957317 1.7451096123721754e-11 269.03575473323804 2.900913660200795e-05 -0.3422621053879919 0.3224569332672493
TX 7925724.555441186 3.3211870638130594 0.2865618277162261 0.290596763884305 0.2864925567072443 0.004034936168078873 6.927100898185268e-05 31979.792666980487 549.0229368676567 -2.6660098690287715 2.6497791320535207
UT 962101.4703104672 0.17870525813408125 0.13882100218112534 0.13957455356294662 0.13868179935249797 0.000753551381821288 0.0001392028286273661 724.9928924047455 133.92724609376492 -0.14389701227098337 0.14092183140254813
VA 2003654.4960256969 0.3695392379292323 0.21401573281514533 0.21458878860602 0.21388989423897323 0.0005730557908746603 0.00012583857617209926 1148.2058118595746 252.1370289206988 -0.3082503899463744 0.3046398042769084
VT 125497.50217012578 0.07951920174340077 0.2062866375431428 0.2100699650877392 0.2062866375431428 0.0037833275445963988 0.0 474.7981567382832 0.0 -0.06329539850535763 0.0610411200379675
WA 1760287.6989703444 1.935070419837364 0.24714306327384566 0.2605971548200949 0.24585890620438783 0.013454091546249214 0.0012841570694578364 23683.07184968339 2260.4858929124357 -1.578974716313693 1.5452288083286043
WI 1316983.8377566077 0.4444222843993473 0.17345556111604366 0.17444255375870285 0.1733677890486371 0.0009869926426591957 8.777206740656629e-05 1299.8533583668436 115.59439418093133 -0.3582071872818706 0.34847519022507917
WV 379072.7853454807 0.15749364730713744 0.21574503807736106 0.21719787430718357 0.2152262121872637 0.0014528362298225073 0.0005188258900973575 550.7306762896447 196.67277526855355 -0.12380070008073142 0.12153004893575325
WY 137282.95519420505 0.04904928937802332 0.13565129631523193 0.1356585072942688 0.13525006679659562 7.210979036859078e-06 0.0004012295186363035 0.9899445120234766 55.08197402954011 -0.04251130414996716 0.04068513909766804
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