{
  "alt": "Two tabs. The first is a scatter plot of tract life expectancy against median home value on a logarithmic axis, a cloud rising from lower left to upper right with twenty markers for twentieths of tracts rising at every step. The second is a bar chart of housing dollars per year of life in each metro, from Cincinnati and other Midwest metros at the lowest to San Francisco-Oakland, New York and San Jose at the highest.",
  "caption": "Life expectancy rises across the whole range of home values, and a year of life costs the fewest housing dollars in Cincinnati, Cleveland and Indianapolis and the most in San Francisco-Oakland, New York and San Jose. The first tab plots a random sample of {fact:price_n_sample} tracts, with {fact:price_n_outside} tracts outside the plotted range left out of the sample; the second tab gives, for each of {fact:price_n_metros} metros, the median tract home value divided by the within-metro slope of life expectancy on the log of home value.",
  "data": [],
  "id": "home_value_vs_le",
  "notes": [
    "The sample is {fact:price_n_tracts} census tracts that have a life expectancy estimate and a median home value, with institutional tracts such as prisons and nursing facilities left out. Each tract carries its own ACS median home value, which the Census Bureau top-codes at about two million dollars. An earlier version of this figure used ZIP code areas and a ZIP-level home value of unstated, older vintage.",
    "The dots are drawn at random from the tracts inside the plotted range with seed 12345. Every estimate in the chapter uses all tracts.",
    "Twentieths hold equal numbers of tracts. Intervals on the markers resample whole counties; intervals in the second tab resample the tracts of one metro and treat them as independent, so they are narrower than they should be. Each tract takes the metro of its county, and a metro enters with at least {fact:price_metro_min_tracts} tracts and {fact:price_metro_min_pop} residents in the sample.",
    "Life expectancy is the estimate for deaths in 2010 to 2015 and home values are for 2019 to 2023, so the two describe different years."
  ],
  "source": "USALEEP life expectancy 2010-2015 (non-institutional tracts, area-weighted onto 2020 tracts) and ACS 2019-2023 tract median home value; population-weighted twentieths, unweighted fitted line, modeled estimates",
  "spec": {
    "panels": [
      {
        "figure": {
          "alt": "Scatter plot of tract life expectancy against median home value on a logarithmic axis. A wide cloud of dots rises from the lower left to the upper right, twenty markers for twentieths of tracts climb at every step, and a dashed fitted line runs through the cloud.",
          "caption": "Dots drift up from left to right, and the markers for twentieths of tracts by home value rise at every step, from {fact:price_le_lo} years in the lowest twentieth to {fact:price_le_hi} years in the highest. The dashed line is fitted across all {fact:price_n_tracts} tracts, each counted once, and has slope {fact:price_doubling_yrs} years per doubling of home value.",
          "data": [],
          "id": "home_value_scatter",
          "spec": {
            "overlays": [
              {
                "hi": "hi",
                "kind": "line",
                "label": "Twentieths of tracts, population-weighted, with 95% intervals",
                "lo": "lo",
                "rows": [
                  {
                    "hi": 73.93,
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                    "x": 74200,
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                  {
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                    "lo": 74.72,
                    "n_units": 3835,
                    "x": 103400,
                    "y": 74.96
                  },
                  {
                    "hi": 75.92,
                    "lo": 75.51,
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                    "x": 124100,
                    "y": 75.72
                  },
                  {
                    "hi": 76.51,
                    "lo": 76.16,
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                  {
                    "hi": 76.88,
                    "lo": 76.55,
                    "n_units": 3835,
                    "x": 167800,
                    "y": 76.71
                  },
                  {
                    "hi": 77.38,
                    "lo": 77.04,
                    "n_units": 3835,
                    "x": 186700,
                    "y": 77.21
                  },
                  {
                    "hi": 77.64,
                    "lo": 77.33,
                    "n_units": 3835,
                    "x": 205700,
                    "y": 77.49
                  },
                  {
                    "hi": 78.09,
                    "lo": 77.76,
                    "n_units": 3835,
                    "x": 225200,
                    "y": 77.92
                  },
                  {
                    "hi": 78.52,
                    "lo": 78.19,
                    "n_units": 3835,
                    "x": 244200,
                    "y": 78.34
                  },
                  {
                    "hi": 78.78,
                    "lo": 78.41,
                    "n_units": 3836,
                    "x": 267600,
                    "y": 78.59
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                  {
                    "hi": 79.19,
                    "lo": 78.81,
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                  {
                    "hi": 79.35,
                    "lo": 78.93,
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                  {
                    "hi": 79.68,
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                  {
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                    "lo": 79.71,
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                  {
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                    "hi": 83.18,
                    "lo": 82.47,
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                    "x": 1191950,
                    "y": 82.84
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                ],
                "x": "x",
                "y": "y"
              },
              {
                "kind": "line",
                "label": "Line fitted across tracts",
                "rows": [
                  {
                    "x": 10400,
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                    "x": 11901,
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                  {
                    "x": 202042,
                    "y": 77.361
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                  {
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                  {
                    "x": 264588,
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                    "y": 78.646
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                    "y": 79.502
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                    "y": 79.93
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                    "x": 519266,
                    "y": 80.358
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                  {
                    "x": 594229,
                    "y": 80.786
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                  {
                    "x": 680014,
                    "y": 81.214
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                  {
                    "x": 778184,
                    "y": 81.642
                  },
                  {
                    "x": 890525,
                    "y": 82.07
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                    "y": 82.498
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                    "y": 82.926
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                    "x": 1334560,
                    "y": 83.354
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                  {
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                ],
                "x": "x",
                "y": "y"
              }
            ],
            "payload": "home_value_scatter.json",
            "x": "value",
            "xDomain": [
              10000,
              2100000
            ],
            "xFormat": {
              "digits": 0,
              "prefix": "$",
              "thousands": true
            },
            "xLabel": "Median home value, 2019 to 2023 (dollars, log scale)",
            "xScale": "log",
            "y": "le",
            "yDomain": [
              60,
              92
            ],
            "yFormat": {
              "digits": 0
            },
            "yLabel": "Life expectancy at birth, deaths in 2010 to 2015 (years)"
          },
          "subtitle": "Life expectancy at birth in years against median home value in dollars on a log scale, one dot per census tract (random sample), with population-weighted means for twentieths of tracts",
          "title": "Life expectancy is higher in tracts with higher home values, a correlation of {fact:price_r} with the log of home value",
          "type": "scatter"
        },
        "label": "Census tracts"
      },
      {
        "figure": {
          "alt": "Horizontal bars for large metros, sorted from the lowest dollars per year of life at the top to the highest at the bottom. Cincinnati, Cleveland and Indianapolis are at the top with the shortest bars, and San Francisco-Oakland, New York and San Jose are at the bottom with the longest bars, each with an interval.",
          "caption": "The bars climb from Cincinnati, Cleveland and Indianapolis at the top to San Francisco-Oakland, New York and San Jose at the bottom, and the intervals for the three lowest bars lie below those for the three highest. Each bar is the housing dollars that separate two tracts one year of life apart near the metro median, with a 95% interval from a bootstrap over tracts.",
          "data": [
            {
              "conf_high": 37.55,
              "conf_low": 30.32,
              "correlation": 0.713,
              "dollars_k": 33.5,
              "metro": "Cincinnati",
              "n": 514
            },
            {
              "conf_high": 39.58,
              "conf_low": 32.99,
              "correlation": 0.766,
              "dollars_k": 36.05,
              "metro": "Cleveland",
              "n": 581
            },
            {
              "conf_high": 41.56,
              "conf_low": 32.15,
              "correlation": 0.7,
              "dollars_k": 36.46,
              "metro": "Indianapolis",
              "n": 451
            },
            {
              "conf_high": 41.44,
              "conf_low": 34.14,
              "correlation": 0.743,
              "dollars_k": 37.6,
              "metro": "Columbus, OH",
              "n": 466
            },
            {
              "conf_high": 44.86,
              "conf_low": 36.61,
              "correlation": 0.674,
              "dollars_k": 40.32,
              "metro": "Pittsburgh",
              "n": 672
            },
            {
              "conf_high": 46.8,
              "conf_low": 38.91,
              "correlation": 0.759,
              "dollars_k": 42.56,
              "metro": "St. Louis",
              "n": 663
            },
            {
              "conf_high": 47.92,
              "conf_low": 39.11,
              "correlation": 0.755,
              "dollars_k": 43.39,
              "metro": "Kansas City",
              "n": 552
            },
            {
              "conf_high": 50.63,
              "conf_low": 38.75,
              "correlation": 0.761,
              "dollars_k": 44,
              "metro": "Jacksonville",
              "n": 318
            },
            {
              "conf_high": 47.1,
              "conf_low": 42.07,
              "correlation": 0.778,
              "dollars_k": 44.42,
              "metro": "Detroit",
              "n": 1214
            },
            {
              "conf_high": 57.66,
              "conf_low": 40.14,
              "correlation": 0.653,
              "dollars_k": 47.65,
              "metro": "Virginia Beach-Norfolk",
              "n": 428
            },
            {
              "conf_high": 60.15,
              "conf_low": 51.65,
              "correlation": 0.743,
              "dollars_k": 55.92,
              "metro": "Baltimore",
              "n": 660
            },
            {
              "conf_high": 64.51,
              "conf_low": 51.84,
              "correlation": 0.673,
              "dollars_k": 57.89,
              "metro": "Charlotte",
              "n": 594
            },
            {
              "conf_high": 62.47,
              "conf_low": 54.77,
              "correlation": 0.608,
              "dollars_k": 58.45,
              "metro": "Chicago",
              "n": 2159
            },
            {
              "conf_high": 68.5,
              "conf_low": 52.92,
              "correlation": 0.61,
              "dollars_k": 59.66,
              "metro": "San Antonio",
              "n": 451
            },
            {
              "conf_high": 64.08,
              "conf_low": 56.52,
              "correlation": 0.695,
              "dollars_k": 59.96,
              "metro": "Philadelphia",
              "n": 1438
            },
            {
              "conf_high": 71.95,
              "conf_low": 53.88,
              "correlation": 0.504,
              "dollars_k": 61.95,
              "metro": "Minneapolis-St. Paul",
              "n": 845
            },
            {
              "conf_high": 73.11,
              "conf_low": 62.19,
              "correlation": 0.617,
              "dollars_k": 67.43,
              "metro": "Atlanta",
              "n": 1336
            },
            {
              "conf_high": 82.12,
              "conf_low": 56.15,
              "correlation": 0.521,
              "dollars_k": 67.66,
              "metro": "Providence",
              "n": 354
            },
            {
              "conf_high": 77.71,
              "conf_low": 64.76,
              "correlation": 0.545,
              "dollars_k": 70.5,
              "metro": "Houston",
              "n": 1382
            },
            {
              "conf_high": 88.03,
              "conf_low": 62.9,
              "correlation": 0.53,
              "dollars_k": 73.22,
              "metro": "Nashville",
              "n": 383
            },
            {
              "conf_high": 87.29,
              "conf_low": 73.01,
              "correlation": 0.615,
              "dollars_k": 79.85,
              "metro": "Dallas-Fort Worth",
              "n": 1449
            },
            {
              "conf_high": 97.33,
              "conf_low": 71.4,
              "correlation": 0.491,
              "dollars_k": 83.4,
              "metro": "Tampa",
              "n": 682
            },
            {
              "conf_high": 131.17,
              "conf_low": 76.66,
              "correlation": 0.416,
              "dollars_k": 98.47,
              "metro": "Orlando",
              "n": 449
            },
            {
              "conf_high": 118.45,
              "conf_low": 88.09,
              "correlation": 0.547,
              "dollars_k": 101.56,
              "metro": "Sacramento",
              "n": 515
            },
            {
              "conf_high": 126.65,
              "conf_low": 88.37,
              "correlation": 0.464,
              "dollars_k": 105.09,
              "metro": "Portland, OR",
              "n": 533
            },
            {
              "conf_high": 142.34,
              "conf_low": 102.47,
              "correlation": 0.495,
              "dollars_k": 119.69,
              "metro": "Phoenix",
              "n": 932
            },
            {
              "conf_high": 168.55,
              "conf_low": 94.07,
              "correlation": 0.4,
              "dollars_k": 125.86,
              "metro": "Las Vegas",
              "n": 467
            },
            {
              "conf_high": 147.96,
              "conf_low": 114.95,
              "correlation": 0.391,
              "dollars_k": 130.21,
              "metro": "Miami",
              "n": 1347
            },
            {
              "conf_high": 172.85,
              "conf_low": 112.94,
              "correlation": 0.492,
              "dollars_k": 137.82,
              "metro": "Riverside-San Bernardino",
              "n": 929
            },
            {
              "conf_high": 167.78,
              "conf_low": 116.54,
              "correlation": 0.446,
              "dollars_k": 139.92,
              "metro": "Denver",
              "n": 623
            },
            {
              "conf_high": 165.85,
              "conf_low": 121.59,
              "correlation": 0.605,
              "dollars_k": 140.37,
              "metro": "Seattle",
              "n": 823
            },
            {
              "conf_high": 176.6,
              "conf_low": 134.05,
              "correlation": 0.383,
              "dollars_k": 153.61,
              "metro": "Washington, D.C.",
              "n": 1324
            },
            {
              "conf_high": 190.04,
              "conf_low": 148.74,
              "correlation": 0.461,
              "dollars_k": 166.38,
              "metro": "Boston",
              "n": 1032
            },
            {
              "conf_high": 213.29,
              "conf_low": 142.06,
              "correlation": 0.405,
              "dollars_k": 171.84,
              "metro": "Austin",
              "n": 432
            },
            {
              "conf_high": 242.37,
              "conf_low": 205.18,
              "correlation": 0.449,
              "dollars_k": 222.42,
              "metro": "Los Angeles",
              "n": 2829
            },
            {
              "conf_high": 279.95,
              "conf_low": 186.03,
              "correlation": 0.45,
              "dollars_k": 227.46,
              "metro": "San Diego",
              "n": 667
            },
            {
              "conf_high": 274.25,
              "conf_low": 227.13,
              "correlation": 0.556,
              "dollars_k": 247.91,
              "metro": "San Francisco-Oakland",
              "n": 1024
            },
            {
              "conf_high": 357.68,
              "conf_low": 275.25,
              "correlation": 0.288,
              "dollars_k": 311.05,
              "metro": "New York",
              "n": 4281
            },
            {
              "conf_high": 947.03,
              "conf_low": 481.6,
              "correlation": 0.322,
              "dollars_k": 657.8,
              "metro": "San Jose",
              "n": 400
            }
          ],
          "id": "price_by_metro",
          "spec": {
            "category": "metro",
            "domain": [
              0,
              1000
            ],
            "format": {
              "digits": 0,
              "prefix": "$",
              "suffix": "k"
            },
            "hi": "conf_high",
            "lo": "conf_low",
            "n": "n",
            "orientation": "h",
            "sort": "asc",
            "value": "dollars_k",
            "valueLabel": "Housing dollars per year of life (thousands of dollars)"
          },
          "subtitle": "Median tract home value divided by the within-metro slope of life expectancy on the log of home value, thousands of dollars per year of life, metros with enough tracts",
          "title": "A year of life costs between {fact:price_cheap_usd} and {fact:price_dear_usd} in housing dollars at the lowest and highest point estimates among large metros, a ratio of {fact:price_ratio}",
          "type": "bar"
        },
        "label": "Dollars per year of life"
      }
    ]
  },
  "subtitle": "Life expectancy at birth (deaths in 2010 to 2015) against median home value (ACS 2019 to 2023) across census tracts, and the housing dollars per year of life in each large metro",
  "title": "Life expectancy is {fact:price_doubling_yrs} years higher for each doubling of tract home value, and a year of life costs {fact:price_cheap_usd} in housing dollars in Cincinnati and {fact:price_dear_usd} in San Jose",
  "type": "tabs",
  "width": "wide"
}