The Midwest Beat the South in Regional Domestic Migration in 2016

For years, if not decades, we’ve been hearing a familiar tale- that anyone and everyone is moving from the Midwest and Northeast to the South and West. This trend began during and after the collapse of Northern manufacturing, and as higher cost of living began to make the lower-cost South more attractive in particular. However, a lot of the South’s growth over the years- indeed a majority- never had anything to do with region-to-region migration. Instead, it was due largely to natural growth (births vs. deaths) and international migration, particularly from Central America. What received all the attention, though, was the belief that people were packing up and moving to the South from places like Ohio and other struggling Northern states. While that may have been true for a while, that is increasingly looking like it is no longer the case.

The Midwest, especially, has been derided as the region no one wants to live in. Despite its growing population approaching 66 million people, the common refrain was that its colder winters, flailing economies and questionable demographic future meant that it was simply a region being left behind by the booming Southern states.

Recently, the US Census released estimates for 2015-2016 geographic mobility, and they tell a very different story altogether.

First, let’s look at the total domestic migration moving to the Midwest from other regions.
South to Midwest: +309,000
West to Midwest: +72,000
Northeast to Midwest: +61,000
Total to Midwest: +442,000

And then compare that to the total that the Midwest sends to other regions.
Midwest to South: -254,000
Midwest to West: -224,000
Midwest to Northeast: -34,000
Total from Midwest: -512,000

Net difference by region.
Midwest vs. South: +55,000
Midwest vs. West: -152,000
Midwest vs. Northeast: +27,000
Total Net: -70,000

So while the Midwest is seeing and overall net domestic migration loss, it is entirely to the Western states.

This could just be an off year, as almost all recent years showed losses to the South, but then again, maybe not. The South has been in a boom for several decades now, and in that time, the region still lags the other 3 in almost every quality of life metric used. All booms end eventually, and the South’s 2 biggest perceived advantages, low cost of living and business-friendly climate, have been gradually eroding over time. As Census surveys show, people don’t actually move for a change in weather, so it’s the economic factors that are going to make the biggest impacts long-term. The Midwest now has many cities and several states that are doing well economically, including Columbus, and perhaps they are becoming more attractive than they have in many years. Time will tell, but last year, the narrative of an unattractive Midwest vs. South was at least temporarily shelved.

Columbus Foreign-Born Population and Comparison to Peers

The Census just came out with 2016 demographic numbers for cities. Given that more than half the decade is over, it’s a good point to look at where Columbus stands relative to its national/Midwest peers.

First up, let’s take a look at foreign-born populations. I have looked at this topic some in the past, but I have never done a full-scale comparison for this topic.

Total Foreign-Born Population Rank by City 2000, 2010 and 2016
2000—————————————-2010———————————-2016
1. Chicago, IL: 628,903———–1. Chicago: 557,674—————1. Chicago: 559,623
2. San Jose, CA: 329,750——–2. San Jose: 366,194————-2. San Jose: 402,776
3. San Antonio, TX: 133,675—-3. San Antonio: 192,741———-3. San Antonio: 219,520
4. Austin, TX: 109,006————4. Austin: 148,431——————4. Austin: 166,877
5. Las Vegas, NV: 90,656——-5. Las Vegas: 130,503————-5. Charlotte: 138,097
6. Sacramento, CA: 82,616—–6. Chalotte: 106,047—————6. Las Vegas: 137,583
7. Portland, OR: 68,976———7. Sacramento: 96,105————-7. Sacramento: 112,901
8. Charlotte, NC: 59,849——–8. Columbus: 86,663—————-8. Columbus: 101,300
9. Minneapolis, MN: 55,475—–9. Portland: 83,026—————–9. Portland: 87,599
10. Columbus: 47,713———–10. Indianapolis: 74,407———–10. Nashville: 82,505
11. Milwaukee, WI: 46,122—–11. Nashville: 73,327—————11. Indianapolis: 82,207
12. Detroit, MI: 45,541———–12. Minneapolis: 57,846———–12. Orlando: 64,369
13. Providence, RI: 43,947—–13. Milwaukee: 57,222————-13. Minneapolis: 63,585
14. St. Paul, MN: 41,138——-14. Providence: 52,920————14. St. Paul: 60,909
15. Nashville, TN: 38,936——-15. St. Paul: 50,366—————-15. Milwaukee: 58,300
16. Indianapolis, IN: 36,067—-16. Orlando: 43,747—————-16. Providence: 51,290
17. Virginia Beach, VA: 28,276–17. Virginia Beach: 40,756—–17. Omaha: 47,566
18. Orlando, FL: 26,741———18. Omaha: 39,288—————18. Virginia Beach: 45,650
19. Omaha, NE: 25,687———19. Kansas City: 35,532———19. Detroit: 39,555
20. Kansas City, MO: 25,632—20. Detroit: 34,307—————-20. Kansas City: 38,564
21. Cleveland: 21,372————21. St. Louis: 23,011————–21. Pittsburgh: 26,604
22. Grand Rapids, MI: 20,814–22. Pittsburgh: 18,698————22. Cleveland: 21,336
23. St Louis, MO: 19,542——-23. Cleveland: 17,739————-23. Grand Rapids: 20,270
24. Pittsburgh, PA: 18,874—–24. Grand Rapids: 16,615——–24. St. Louis: 19,245
25. Cincinnati: 12,461———–25. Cincinnati: 16,531————-25. Cincinnati: 15,625
26. Toledo: 9,475—————–26. Toledo: 11,559—————–26. Akron: 14,441
27. Akron: 6,911——————27. Akron: 8,524——————–27. Toledo: 8,830
28. Dayton: 3,245—————-28. Dayton: 5,102——————-28. Dayton: 7,058
29. Youngstown: 1,605———29. Youngstown: 3,695————29. Youngstown: 1,125

Here’s the 2000-2016 total change.

And the 2000-2016 change by %.

So Columbus has an above average total and growth compared to its peers nationally.

In Franklin County, Young Adults Prefer Density

I’ve seen several articles across the internet lately questioning the idea that young professionals and Millennials really prefer urban areas or not. I decided to see how this played out in Franklin County overall. I first looked at the total population aged 20-34 in the year 2000 and the year 2015 by Census Tract.
Here were the maps for those years.

After looking at the numbers for both years, I came up with this map for how that age group had changed in the 2000-2015 period.

Unfortunately, some tracts, particularly in the eastern suburban areas, did not exist in 2000, and so I was not able to figure out the change for them during the period. The rest of the map, however, shows that the strongest growth in this age group was not only inside 270, but closest to Downtown and central corridors along Broad and High Streets.
These maps don’t tell us about the relationship between those changes and the population density of the census tracts. So I went further and broke the tracts into increments of density to see where the strongest growth was occurring.

With a few exceptions, there appears to be a correlation between average 20-34 aged population growth and the density of the census tracts it occurs in. This suggests that this age group, at least in Franklin County, prefers areas with moderate to high density, which typically translates to urban living.

Metro Population Density Comparison- 2016 Update

I originally posted some data on this subject back in March 2013, which included this information for 2011 and 2012. I have updated to include new information.

The Columbus Metropolitan Area resides within a group of metros between 1.5 and 2.5 million people. I wanted to take a look at population densities between that group of metros to see how different they really are and where Columbus might fall within them.

Metro Area Size in Square Miles (Land Only) in 2016
1. Las Vegas, NV: 7,891
2. San Antonio, TX: 7,340
3. Kansas City, MO: 7,255
4. Portland, OR: 6,683
5. Nashville, TN: 6,300
6. Pittsburgh, PA: 5,282
7. Sacramento, CA: 5,096
8. Charlotte, NC: 5,068
9. Columbus: 4,796
10. Cincinnati: 4,391
11. Indianapolis, IN: 4,306
12. Austin, TX: 4,219
13. Orlando, FL: 3,477
14. San Jose, CA: 2,679
15. Virginia Beach, VA: 2,089
16. Cleveland: 1,996
17. Providence, RI: 1,587
18. Milwaukee, WI: 1,455

Metro Area Population Census 2010 and July 1, 2016 (using 2013 updated boundaries)
2010———————————————————-2016
1. Pittsburgh: 2,356,285————————–1. Charlotte: 2,474,314
2. Portland: 2,226,009—————————-2. Orlando: 2,441,257
3. Charlotte: 2,217,012—————————3. San Antonio: 2,429,609
4. Sacramento: 2,149,127———————–4. Portland: 2,424,955
5. San Antonio: 2,142,508———————–5. Pittsburgh: 2,342,299
6. Orlando: 2,134,411—————————–6. Sacramento: 2,296,418
7. Cincinnati: 2,114,580————————–7. Cincinnati: 2,165,139
8. Cleveland: 2,077,240————————–8. Las Vegas: 2,155,664
9. Kansas City: 2,009,342———————–9. Kansas City: 2,104,509
10. Las Vegas: 1,951,269———————–10. Austin: 2,056,405
11. Columbus: 1,901,974————————11. Cleveland: 2,055,612
12. Indianapolis: 1,887,877———————-12. Columbus: 2,041,520
13. San Jose: 1,836,911————————-13. Indianapolis: 2,004,230
14. Austin: 1,716,289—————————–14. San Jose: 1,978,816
15. Virginia Beach: 1,676,822——————15. Nashville: 1,865,298
16. Nashville: 1,670,890————————-16. Virginia Beach: 1,726,907
17. Providence: 1,600,852———————-17. Providence: 1,614,750
18. Milwaukee: 1,555,908———————–18. Milwaukee: 1,572,482

Metro Area Population Density by Square Mile Census 2010 and July 1, 2016
2010—————————————–2016
1. Milwaukee: 1069.4—————1. Milwaukee: 1080.7
2. Cleveland: 1040.5—————-2. Cleveland: 1029.7
3. Providence: 1008.7—————3. Providence: 1017.5
4. Virginia Beach: 802.7———–4. Virginia Beach: 826.7
5. San Jose: 685.7——————5. San Jose: 738.6
6. Orlando: 613.9——————–6. Orlando: 702.1
7. Cincinnati: 481.6—————–7. Cincinnati: 493.1
8. Pittsburgh: 446.1—————–8. Charlotte: 488.2
9. Indianapolis: 438.4—————9. Austin: 487.4
10. Charlotte: 437.5—————-10. Indianapolis: 465.4
11. Sacramento: 421.7————11. Sacramento: 450.6
12. Austin: 406.8——————–12. Pittsburgh: 443.4
13. Columbus: 396.6—————13. Columbus: 425.7
14. Portland: 333.1—————–14. Portland: 362.9
15. San Antonio: 291.9————15. San Antonio: 331.0
16. Kansas City: 277.0————16. Nashville: 296.1
17. Nashville: 265.2—————-17. Kansas City: 290.1
18. Las Vegas: 247.3————–18. Las Vegas: 273.2

Density Change Rank 2010-2016
1. Orlando: 88.3
2. Austin: 80.6
3. San Jose: 53.0
4. Charlotte: 50.8
5. San Antonio: 39.1
6. Nashville: 30.9
7. Portland: 29.8
8. Columbus: 29.1
9. Sacramento: 28.9
10. Indianapolis: 27.0
11. Las Vegas: 25.9
12. Virginia Beach: 24.0
13. Kansas City: 13.1
14. Cincinnati: 11.5
15. Milwaukee: 11.4
16. Providence: 8.8
17. Pittsburgh: -2.6
18. Cleveland: -10.8

Core County Population Census 2010 and July 1, 2016 by Rank
2010————————————————————-2016
1. Clark (Las Vegas): 1,951,269———————1. Clark: 2,155,664
2. Santa Clara (San Jose): 1,781,642————–2. Bexar: 1,928,680
3. Bexar (San Antonio): 1,714,773——————3. Santa Clara: 1,919,402
4. Sacramento (Sacramento): 1,418,788———-4. Sacramento: 1,514,460
5. Cuyahoga: 1,280,122——————————-5. Orange: 1,314,367
6. Allegheny (Pittsburgh): 1,223,348—————6. Franklin: 1,264,518
7. Franklin: 1,163,414———————————-7. Cuyahoga: 1,249,352
8. Orange (Orlando): 1,145,956———————8. Allegheny: 1,225,365
9. Travis: (Austin): 1,024,266————————9. Travis: 1,199,323
10. Milwaukee (Milwaukee): 947,735————–10. Mecklenburg: 1,054,835
11. Mecklenburg (Charlotte): 919,628————-11. Milwaukee: 951,448
12. Marion (Indianapolis): 903,393—————–12. Marion: 941,229
13. Hamilton: 802,374———————————13. Hamilton: 809,099
14. Multnomah (Portland): 735,334—————-14. Multnomah: 799,766
15. Jackson (Kansas City): 674,158—————15. Jackson: 691,801
16. Davidson (Nashville): 626,681——————16. Davidson: 684,410
17. Providence (Providence): 626,667————17. Providence: 633,473
18. Virginia Beach (Virginia Beach): 437,994—18. Virginia Beach: 452,602

Core County Population Density Per Square Mile Census 2010 and July 1, 2016 by Rank
2010———————————————————————— 2016
1. Milwaukee: 3932.5————————–1. Milwaukee: 3947.9
2. Cuyahoga: 2801.1————————–2. Franklin: 2376.9
3. Marion: 2279.6——————————3. Marion: 2375.0
4. Franklin: 2186.9—————————–4. Cuyahoga: 2733.8
5. Hamilton: 1976.3—————————-5. Mecklenburg: 2013.0
6. Virginia Beach: 1759.0——————–6. Hamilton: 1992.9
7. Mecklenburg: 1755.0———————–7. Multnomah: 1855.6
8. Multnomah: 1706.1————————8. Virginia Beach: 1817.7
9. Allegheny: 1675.8————————–9. Allegheny: 1678.6
10. Providence: 1528.5———————-10. Sacramento: 1569.4
11. Sacramento: 1470.2———————11. Bexar: 1555.4
12. Bexar: 1382.9—————————–12. Providence: 1545.1
13. Santa Clara: 1381.1———————13. Santa Clara: 1487.9
14. Orange: 1269.1—————————14. Orange: 1455.6
15. Davidson: 1243.4————————15. Davidson: 1358.0
16. Jackson: 1116.2————————–16. Travis: 1211.4
17. Travis: 1034.6—————————–17. Jackson: 1145.4
18. Clark: 247.3——————————–18. Clark: 273.2

The core counties of metros within the Midwest are clearly the most dense, with most hovering between 1500-2500 people per square mile. Columbus’ Franklin County moved up to 2nd most dense in 2016.

Core County Population Density Change 2010-2016
1. Mecklenburg: 258.0
2. Franklin: 190.0
3. Orange: 186.5
4. Travis: 176.8
5. Bexar: 172.5
6. Multnomah: 149.5
7. Davidson: 114.5
8. Santa Clara: 106.8
9. Sacramento: 99.1
10. Marion: 95.5
11. Virginia Beach: 58.7
12. Jackson: 29.2
13. Clark: 25.9
14. Providence: 16.6
15. Hamilton: 16.6
16. Milwaukee: 15.4
17. Allegheny: 2.8
18. Cuyahoga: -67.3

Columbus’ Franklin County densified at the 2nd fastest rate 2010-2016 of any of its metro peers, indicating that it’s receiving a large portion of the total metro population growth.

To see other metro population data, go to http://allcolumbusdata.com/?p=6139




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.