Franklin County Gentrification Trends 1990-2015

**Note: This was originally posted on March 8, 2016. However, the data went to 2014 rather than 2015 and I actually posted it without adding all the maps and other information intended.

I saw this post (http://www.citylab.com/housing/2016/03/mapping-the-resegregation-of-diverse-neighborhoods-in-4-us-cities/472086/) the other day about changing neighborhood demographics in certain cities, particularly when it comes to racial segregation and gentrification. Surprisingly, of all the maps and posts I’ve done on demographics, I hadn’t thought to do one like this. Well, now I have.

A bit of an explanation is needed for the color coding:
-For those categories marked “Steady”, the demographic listed has been the majority throughout the period, with little to no change of other demographics.
-For those mixed categories of one decline and one rise, it means that the majority demographic has declined at least 5 percentage points, while a secondary demographic has risen at least 5 percentage points.
-For the category of recent or steady integration, there are at least 2 demographics at 10% or more of the total population, as well as a 3rd demographic reaching at least 5% of the population.

A few things that stand out to me: The eastern half of the county is in much greater flux than the western half, and integration is respectable county-wide. These neighborhoods of demographic equilibrium are largely the result of increasing Hispanic and Asian populations, particularly on the Northeast and West Sides, as well as the Whitehall area. In the center core, almost all of the High Street corridor has remained Steady White, suggesting that other demographics have, so far, been unable to tap into the building boom along and adjacent to this corridor. One other thing I notice is that there are FAR more tracts with a growing black population than there are with a growing White population, suggesting that perhaps the idea of Whites moving into neighborhoods and displacing residents is not quite as big of an issue as some might believe.

Here are the integrated tracts by year, based the above criteria, and their racial breakdown.

Top 10 Tracts with the Highest White Population

1990
1. 7205: 99.6%
2. 98: 99.1%
3. 7207: 98.9%
4. 120, 9240: 98.8%
5. 7201, 7203, 80: 98.7%
6. 7922, 9440, 9752: 98.6%
7. 9751, 10601: 98.5%
8. 110, 8141, 8821, 9711, 9740: 98.4%
9. 9450, 9800: 98.3%
10. 6230, 7210: 98.2%
2015
1. 65: 98.7%
2. 6810: 97.4%
3. 6822, 9712: 97.0%
4. 98: 96.0%
5. 6721, 6950: 95.9%
6. 220: 95.8%
7. 9497: 95.6%
8. 66: 95.5%
9. 6330: 94.8%
10. 7394: 94.7%

Breakdown of # of Tracts by % of White Population
1990
95% or Higher: 80
90%-94.9%: 73
80%-89.9%: 64
70%-79.9%: 10
60%-69.9%: 11
50%-59.9%: 6
Total Majority White Tracts: 244
40%-49.9%: 7
30%-39.9%: 9
20%-29.9%: 5
10%-19.9%: 9
0.1%-9.9%: 9
0%: 0
Total Minority White Tracts: 39
2015
95% or Higher: 11
90%-94.9%: 35
80%-89.9%: 62
70%-79.9%: 52
60%-69.9%: 30
50%-59.9%: 19
Total Majority White Tracts: 209
40%-49.9%: 11
30%-39.9%: 17
20%-29.9%: 25
10%-19.9%: 15
0.1%-9.9%: 6
0%: 0
Total Minority White Tracts: 74

Top 10 Tracts with the Highest Black Population
1990
1. 730: 94.2%
2. 5420: 93.4%
3. 15, 28: 92.3%
4. 36: 91.8%
5. 5410: 91.4%
6. 7551: 91.1%
7. 7512: 90.9%
8. 23: 89.0%
9. 2520: 87.4%
10. 29: 87.2%
2015
1. 7512: 88.1%
2. 9337: 87.7%
3. 730: 84.9%
4. 7511: 83.6%
5. 23: 82.2%
6. 15: 81.9%
7. 55: 81.4%
8. 5420, 9332: 81.0%
9. 29: 80.9%
10. 8813: 79.1%

Breakdown of # of Tracts by % of Black Population
1990
95% or Higher: 0
90%-94.9%: 7
80%-89.9%: 10
70%-79.9%: 4
60%-69.9%: 8
50%-59.9%: 6
Total Majority Black Tracts: 35
40%-49.9%: 7
30%-39.9%: 10
20%-29.9%: 9
10%-19.9%: 32
0.1%-9.9%: 190
0%: 0
Total Minority Black Tracts: 248
2015
95% or Higher: 0
90%-94.9%: 0
80%-89.9%: 9
70%-79.9%: 8
60%-69.9%: 28
50%-59.9%: 9
Total Majority Black Tracts: 52
40%-49.9%: 20
30%-39.9%: 17
20%-29.9%: 24
10%-19.9%: 44
0.1%-9.9%: 126
0%: 0
Total Minority Black Tracts: 231

Top 10 Tracts with the Highest Asian Population
1990
1. 7820: 23.3%
2. 1122: 11.2%
3. 1110: 10.8%
4. 105: 9.0%
5. 1810: 8.2%
6. 6372: 7.6%
7. 6384: 7.3%
8. 1121: 7.2%
9. 6386: 6.9%
10. 6395: 6.8%
2015
1. 7820: 34.1%
2. 7721: 26.8%
3. 6230: 26.7%
4. 1122: 21.9%
5. 7830: 17.0%
6. 1110: 16.6%
7. 105: 16.2%
8. 6395: 15.5%
9. 6372: 15.3%
10. 6386: 14.9%

Breakdown of # of Tracts by % of Asian Population
1990
95% or Higher: 0
90%-94.9%: 0
80%-89.9%: 0
70%-79.9%: 0
60%-69.9%: 0
50%-59.9%: 0
Total Majority Asian Tracts: 0
40%-49.9%: 0
30%-39.9%: 0
20%-29.9%: 1
10%-19.9%: 2
0.1%-9.9%: 273
0%: 7
Total Minority Asian Tracts: 283
2015
95% or Higher: 0
90%-94.9%: 0
80%-89.9%: 0
70%-79.9%: 0
60%-69.9%: 0
50%-59.9%: 0
Total Majority Asian Tracts: 0
40%-49.9%: 0
30%-39.9%: 1
20%-29.9%: 4
10%-19.9%: 17
0.1%-9.9%: 215
0%: 46
Total Minority Asian Tracts: 283

Top 10 Tracts with the Highest Hispanic Population
1990
1. 7820: 2.9%
2. 1122, 7209: 2.5%
3. 1810, 30: 2.3%
4. 8163, 9323, 9336: 2.1%
5. 6352, 7830: 2.0%
6. 1110, 1121, 2750: 1.9%
7. 10, 32, 40, 42, 7533: 1.8%
8. 12, 17, 1901, 6353, 7041, 7199: 1.7%
9. 6, 1820, 6945, 7531, 7551, 7721, 9326, 99: 1.6%
10. 13, 2710, 6933, 7120, 7532, 8164, 8230, 8730, 103: 1.5%
2015
1. 8230: 39.3%
2. 8164: 28.7%
3. 8163: 26.4%
4. 26: 24.2%
5. 9321: 22.7%
6. 8210: 22.6%
7. 99: 21.4%
8. 9230: 21.0%
9. 7043: 19.8%
10. 6945: 18.9%

Breakdown of # of Tracts by % of Hispanic Population
1990
95% or Higher: 0
90%-94.9%: 0
80%-89.9%: 0
70%-79.9%: 0
60%-69.9%: 0
50%-59.9%: 0
Total Majority Hispanic Tracts: 0
40%-49.9%: 0
30%-39.9%: 0
20%-29.9%: 0
10%-19.9%: 0
0.1%-9.9%: 278
0%: 5
2015
95% or Higher: 0
90%-94.9%: 0
80%-89.9%: 0
70%-79.9%: 0
60%-69.9%: 0
50%-59.9%: 0
Total Majority Hispanic Tracts: 0
40%-49.9%: 0
30%-39.9%: 1
20%-29.9%: 7
10%-19.9%: 33
0.1%-9.9%: 241
0%: 9

Integrated Tracts By Year
1990: 2
2015: 98

Most Integrated Tract by Year
1990
1122: White: 76.6% Black: 9.6% Asian: 11.2% Hispanic: 2.5%
2015
7721: White: 33.9% Black: 31.2% Asian: 26.8% Hispanic: 10.1%

All in all, the data shows that the county is much less racially stratified/segregated now than it was in 1990, and that it doesn’t appear that gentrification is really affecting many areas in terms of forcing out one racial group for another.

The Real Makeup of the Columbus Economy

Over the years, there have been endless claims about how the Columbus economy is dominated by jobs related to state government and OSU. These claims are usually made from other Ohioans complaining that Columbus has an unfair advantage and is mooching public dollars from the rest of the state to prop up the economy.

Let’s first address two points made: 1. That the number of government jobs is far above what they are in all other major Ohio cities, and 2. That overall, government jobs are becoming a larger slice of the metro economy.

The first claim is easy to look into. The Bureau of Labor Statistics, or BLS, produces numbers every single month on job industry numbers by metro area. The most recent numbers are from June 2016.
Here are the total government jobs for Ohio’s largest cities.

Columbus: 162,600
Cleveland: 138,800
Cincinnati: 124,200
Dayton: 62,300
Toledo: 44,800
Akron: 40,600

So as to the first claim, that the total of government jobs in Columbus is higher than the other cities, that is true. As the state capital, this is no surprise. However, how dependent on government jobs is Columbus really versus those other cities? To find out, you have to divide government jobs by all total jobs within the metro. In June 2016, here was the percentage of the total.

Dayton: 16.17%
Columbus: 15.30%
Toledo: 14.21%
Cleveland: 12.90%
Akron: 11.84%
Cincinnati: 11.43%

Interestingly enough, Columbus is not the top government-dependent city. That spot goes to Dayton.

Now onto the 2nd claim- that Columbus is increasingly reliant on those government jobs. Let’s look at the % of total jobs that government jobs made up going back to 1990. The figures are for June of each year given.

1990: 17.97%
1995: 17.25%
2000: 15.97%
2005: 17.18%
2010: 17.81%
2015: 15.34%
2016: 15.30%

So it does not appear that Columbus has become more or less dependent on government jobs over the last 26 years. Indeed, if there is any pattern at all, it appears that during economic downturns, the number of government jobs increase, and during periods of stability/recovery, government jobs decline. The early 1990s and late 2000s had high levels of governments jobs, both periods of recession. In June 2016, nearly 85% of the local economy was not government-related, not statistically much different than other Ohio cities.

Finally, let’s look at how total government jobs have changed since the beginning of this decade, 2010, by Ohio city. The figures are for June 2010 and June 2016.

Toledo: +2.75%
Columbus: -0.91%
Cleveland: -1.56%
Cincinnati: -3.72%
Dayton: -4.30%
Akron: -10.38%

All cities except Toledo have seen declines.

So that brings us to the actual makeup of the Columbus metro economy. What are the industries that most people work for? What are the industries that have the greatest % of the total jobs? Let’s compare June 1990 and June 2016.

1990
Trade/Transportation/Utilities: 20.51%
Government: 17.97%
Manufacturing: 13.49%
Professional and Business Services: 11.46%
Health and Education: 9.41%
Leisure and Hospitality: 8.63%
Financial Activities: 8.26%
Mining/Logging/Construction: 4.30%
Other Services: 3.46%
Information: 2.51%

2016
Trade/Transportation/Utilities: 18.37%
Professional and Business Services: 17.11%
Government: 15.30%
Health and Education: 14.43%
Leisure and Hospitality: 10.89%
Financial Activities: 7.63%
Manufacturing: 6.84%
Other Services: 4.10%
Mining/Logging/Construction: 3.75%
Information: 1.57%

If anything, Columbus’ economy is actually more diverse in 2016 than it was in 1990, not less.



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Cool Link of the Day: Demographics by Distance

http://statchatva.org/changing-shape-of-american-cities/

This link, entitled The Changing Shape of American Cities, gives comparison maps for multi-demographic data points between 1990 and 2012 for dozens of cities, including Columbus. It gives this demographic information by breaking it down by the status at the mile distance from “City Hall”, or from the center of each city’s downtown area.

Using these graphs, here are some examples of the information we can see for Columbus’s immediate downtown.

% of Population with a Bachelor’s Degree at Mile 0
1990: 26%
2012: 51%

% of Population Aged 22-34 at Mile 0
1990: 32%
2012: 38%

% of Population Living Below the Poverty Line at Mile 0
1990: 30%
2012: 27%

Check out these and lots more.



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