In order to determine changes in home value differ between 1990 and 2000, a 1990 to 2000 (ten years) data sets were used.
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To enhance proper analysis of the data sets, common variables need to be identified for 1990 and 2000 data sets:
The descriptive statistic below shows the summary statistics of all the variables used for analysis.
| Statistic | Min | Pctl(25) | Median | Mean | Pctl(75) | Max |
| mhmval90 | 0 | 58,800 | 86,500 | 112,399 | 141,800 | 500,001 |
| mhmval00 | 0 | 81,600 | 119,900 | 144,738 | 173,894 | 1,000,001 |
| hinc90 | 4,999 | 24,355 | 32,033 | 34,160 | 41,520 | 150,001 |
| hu90 | 0 | 916 | 1,337 | 1,382 | 1,804 | 11,003 |
| own90 | 0 | 422 | 744 | 788 | 1,093 | 8,180 |
| rent90 | 0 | 168 | 358 | 476 | 663 | 8,653 |
| empclf90 | 0 | 1,015 | 1,555 | 1,625 | 2,157 | 11,816 |
| clf90 | 0 | 1,101 | 1,664 | 1,732 | 2,291 | 12,497 |
| unemp90 | 0 | 49 | 88 | 107 | 143 | 1,165 |
| prof90 | 0 | 192 | 359 | 451 | 616 | 6,290 |
| dpov90 | 0 | 2,219 | 3,250 | 3,332 | 4,365 | 23,619 |
| npov90 | 0 | 112 | 248 | 406 | 526 | 5,890 |
| ag25up90 | 0 | 1,444 | 2,121 | 2,187 | 2,865 | 18,461 |
| hs90 | 0 | 626 | 1,064 | 1,141 | 1,559 | 12,383 |
| col90 | 0 | 162 | 335 | 483 | 652 | 8,575 |
| pop90.x | 0 | 2,283 | 3,325 | 3,419 | 4,464 | 35,721 |
| nhwht90 | 0 | 1,262 | 2,424 | 2,513 | 3,575 | 21,561 |
| nhblk90 | 0 | 18 | 76 | 426 | 331 | 12,121 |
| hisp90 | 0 | 27 | 75 | 347 | 280 | 13,873 |
| asian90 | 0 | 9 | 31 | 111 | 94 | 7,899 |
| p.white | 0 | 64 | 87 | 74 | 95 | 100 |
| p.black | 0 | 1 | 3 | 12 | 10 | 100 |
| p.hisp | 0 | 1 | 3 | 10 | 9 | 100 |
| p.asian | 0 | 0 | 1 | 3 | 3 | 94 |
| p.hs | 0 | 69 | 74 | 74 | 80 | 100 |
| p.col | 0 | 10 | 18 | 22 | 30 | 100 |
| p.prof | 0 | 17 | 25 | 27 | 34 | 100 |
| p.unemp | 0 | 4 | 5 | 7 | 8 | 64 |
| pov.rate | 0 | 4 | 8 | 12 | 16 | 100 |
Initial conditions for data in 1990 and the home value for inflation.
| Statistic | Min | Pctl(25) | Median | Mean | Pctl(75) | Max |
| MedianHomeValue1990 | 0 | 77,616 | 114,180 | 148,367 | 187,176 | 660,001 |
| MedianHomeValue2000 | 0 | 81,600 | 119,900 | 144,738 | 173,894 | 1,000,001 |
| Change.90.to.00 | -660,001 | -23,339 | 453 | -3,629 | 19,100 | 1,000,001 |
This histogram shows the distribution of home value changes between 1990 and 2000:
The distributions below compares the distribution of the data raw data between 1990 and 2000:
The small initial values in the data are skewing the percentages. Assuming and average home value below /$10K is a vacant lot, these data can be removed. Outliers with over 500% change should also be removed to limit data skew.
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## -1.00000 -0.15942 0.00436 0.05019 0.20222 28.32257 145
How many entries show a >500% increase:
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Preview of the data with large increase (>500%) to see if this makes sense.
With the outliars removed to minimize skew, we can now accurately represent the percent change in home value between 1990 and 2000.
We often want to disagregate descriptive by some grouping in the data, such as metro areas. dplyr makes this easy by grouping then summarizing the data.
| cbsaname | ave.change.d | growth |
|---|---|---|
| Corvallis, OR | $73,403 | 75.42 |
| Portland-Vancouver-Beaverton, OR-WA | $67,900 | 71.8 |
| Salt Lake City, UT | $61,005 | 69.02 |
| Boulder, CO | $94,414 | 68.56 |
| Provo-Orem, UT | $60,131 | 67.84 |
| Salem, OR | $48,726 | 61.27 |
| Eugene-Springfield, OR | $51,072 | 61.11 |
| Fort Collins-Loveland, CO | $57,232 | 56.31 |
| Longview, WA | $40,726 | 55.06 |
| Missoula, MT | $45,520 | 54.35 |
| Jackson, MI | $28,210 | 53.41 |
| Greeley, CO | $41,416 | 51.69 |
| Wenatchee, WA | $45,676 | 50.45 |
| Detroit-Livonia-Dearborn, MI | $28,733 | 49.37 |
| Yakima, WA | $30,828 | 49.34 |
| Ogden-Clearfield, UT | $42,194 | 48.51 |
| Denver-Aurora, CO | $52,010 | 47.94 |
| Monroe, MI | $42,004 | 47.38 |
| Bay City, MI | $26,654 | 47.04 |
| Logan, UT-ID | $35,543 | 46.43 |
| Eau Claire, WI | $27,792 | 43.02 |
| Madison, WI | $42,897 | 42.14 |
| Sioux Falls, SD | $31,025 | 41.11 |
| Grand Junction, CO | $34,334 | 40.9 |
| Mount Vernon-Anacortes, WA a | $41,944 | 40.61 |
Comparing the median home value between 1990-2000 and 2000-2010. The above analysis shows that 1990-2000 has a median change of $453. Reviewing the tutorial analysis, 2000-2010 has a median change of $36,268. Change in home values have increased by over $35,000 in just ten years!
The average percent change in growth in home value between 1990 and 2000 is only 5% where the average percent change in growth in home value between 2000 and 2010 is 33%!
The original merged dataset we saved as d.full, so we do not need to reload it:
Recall our data steps thus far:
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. | NA’s |
|---|---|---|---|---|---|---|
| -100 | -15.94 | 0.4362 | 5.019 | 20.22 | 2832 | 145 |
The selection of variables for operationalizing and defining gentrification: We added some variables from 2000:
The table below describes the summary statistics for the selected change variables.
| Statistic | Min | Pctl(25) | Median | Mean | Pctl(75) | Max |
| mhv.90 | 11,712 | 77,880 | 114,312 | 148,728 | 187,440 | 660,001 |
| mhv.00 | 0 | 81,600 | 119,900 | 144,738 | 173,894 | 1,000,001 |
| mhv.change | -660,001 | -23,448 | 396 | -4,122 | 18,968 | 963,701 |
| pct.change | -100 | -16 | 0 | 5 | 20 | 2,832 |
| p.white.90 | 0 | 64 | 87 | 74 | 95 | 100 |
| p.black.90 | 0 | 1 | 3 | 12 | 10 | 100 |
| p.hisp.90 | 0 | 1 | 3 | 10 | 9 | 100 |
| p.asian.90 | 0 | 0 | 1 | 3 | 3 | 94 |
| p.hs.edu.90 | 0 | 69 | 74 | 74 | 80 | 100 |
| p.col.edu.90 | 0 | 10 | 18 | 22 | 30 | 100 |
| p.prof.90 | 0 | 17 | 25 | 27 | 34 | 100 |
| p.unemp.90 | 0 | 4 | 5 | 7 | 8 | 64 |
| pov.rate.90 | 0 | 4 | 8 | 12 | 16 | 100 |
| p.white.00 | 0 | 47 | 78 | 67 | 91 | 100 |
| p.black.00 | 0 | 1 | 4 | 14 | 14 | 100 |
| p.hisp.00 | 0 | 2 | 4 | 13 | 15 | 100 |
| p.asian.00 | 0 | 1 | 2 | 5 | 5 | 95 |
| p.hs.edu.00 | 0 | 67 | 72 | 72 | 77 | 100 |
| p.col.edu.00 | 0 | 12 | 21 | 26 | 36 | 100 |
| p.prof.00 | 0 | 23 | 31 | 34 | 43 | 100 |
| p.unemp.00 | 0 | 3 | 5 | 6 | 8 | 100 |
| pov.rate.00 | 0 | 4 | 9 | 12 | 17 | 100 |
| metro.mhv.pct.90 | 1 | 20 | 41 | 45 | 68 | 100 |
| metro.mhv.pct.00 | 1 | 20 | 41 | 45 | 68 | 100 |
| metro.median.pay.90 | 14,871 | 28,906 | 32,457 | 32,924 | 35,833 | 52,374 |
| metro.median.pay.00 | 23,012 | 39,457 | 43,139 | 45,054 | 49,522 | 73,701 |
| metro.mhv.pct.change | -99 | -5 | 0 | 0 | 6 | 99 |
| pay.change | 4,930 | 9,775 | 11,441 | 12,130 | 14,001 | 26,211 |
| race.change | -100 | -12 | -5 | -8 | -2 | 100 |
| metro.race.rank.90 | 1 | 20 | 41 | 45 | 68 | 100 |
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By the above definition, based on the analysis only 2.1 percent of urban tracts experience gentrification between 1990 and 2000 as compared to 5.7 percent from 2000 to 2010.
17560 of census tracts are candidates, and 371 transitioned into advanced stage of gentrification.
The dorling cartogram shows the census data and groups from clustering.
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The cartogram above shows candidates for gentrification in 1990 disaggregated by mean home value. The map shows a higher median home value in the North-West region of the city and lower median home values toward the center.
From 2000:
The cartogram above shows candidates for gentrification in 2000 disaggregated by mean home value. The map shows a higher median home value in the North and South-West region of the city and lower median home values toward the center.
The cartogram above shows the distribution of gentrification across the city between 1990 and 2000. The map shows that change in the median home value happens more toward the north and north-west areas of Pittsburgh.
The cartogram above shows that the percent change in median home value as a result of the distribution of gentrification happens in the far northern area of Pittsburgh.