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.

Columbus Foreign-Born Population and Comparison to Peers

The Census just came out with 2015 demographic numbers for all places with at least 65,000 people. Given that half the decade is over, it’s a good point to look at where Columbus stands relative to its national/Midwest peers. A few days ago, I gave numbers for GDP. In the next few posts, I will look at the people that make up the populations of these places.

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 2015
1. Chicago, IL: 628,903———–1. Chicago: 557,674—————1. Chicago: 573,463
2. San Jose, CA: 329,750——–2. San Jose: 366,194————-2. San Jose: 401,493
3. San Antonio, TX: 133,675—-3. San Antonio: 192,741———-3. San Antonio: 208,046
4. Austin, TX: 109,006————4. Austin: 148,431——————4. Austin: 181,686
5. Las Vegas, NV: 90,656——-5. Las Vegas: 130,503————-5. Charlotte: 128,897
6. Sacramento, CA: 82,616—–6. Chalotte: 106,047—————6. Las Vegas: 127,609
7. Portland, OR: 68,976———7. Sacramento: 96,105————-7. Sacramento: 112,579
8. Charlotte, NC: 59,849——–8. Columbus: 86,663—————-8. Columbus: 101,129
9. Minneapolis, MN: 55,475—–9. Portland: 83,026—————–9. Nashville: 88,193
10. Columbus: 47,713———–10. Indianapolis: 74,407———–10. Portland: 86,041
11. Milwaukee, WI: 46,122—–11. Nashville: 73,327—————11. Indianapolis: 72,456
12. Detroit, MI: 45,541———–12. Minneapolis: 57,846———–12. Minneapolis: 70,769
13. Providence, RI: 43,947—–13. Milwaukee: 57,222————-13. Milwaukee: 58,321
14. Nashville, TN: 38,936——-14. Providence: 52,926————14. Providence: 53,532
15. Indianapolis, IN: 36,067—-15. Orlando: 43,747—————-15. Orlando: 50,558
16. Virginia Beach, VA: 28,276–16. Virginia Beach: 40,756—–16. Omaha: 48,263
17. Orlando, FL: 26,741———17. Omaha: 39,288—————–17. Detroit: 39,861
18. Omaha, NE: 25,687———18. Kansas City: 35,532———18. Virginia Beach: 38,360
19. Kansas City, MO: 25,632—19. Detroit: 34,307—————-19. Kansas City: 37,787
20. Cleveland: 21,372————20. St. Louis: 23,011————–20. Pittsburgh: 28,187
21. Grand Rapids, MI: 20,814–21. Pittsburgh: 18,698————21. St. Louis: 21,802
22. St Louis, MO: 19,542——-22. Cleveland: 17,739————-22. Grand Rapids: 19,176
23. Pittsburgh, PA: 18,874—–23. Grand Rapids: 16,615——–23. Cleveland: 18,830
24. Cincinnati: 12,461———–24. Cincinnati: 16,531————-24. Cincinnati: 16,896
25. Toledo: 9,475—————–25. Toledo: 11,559—————–25. Akron: 10,024
26. Akron: 6,911——————26. Akron: 8,524——————–26. Toledo: 9,257
27. Dayton: 3,245—————-27. Dayton: 5,102——————-27. Dayton: 7,381
28. Youngstown: 1,605———28. Youngstown: 3,695————28. Youngstown: 1,058

Here’s the 2000-2015 total change.

And the 2000-2015 change by %.

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

Millennials and the City: A Comparison Part 2

The first part of this comparison, seen here: seemed to be well-received, so I wanted to expand the examination of the 25-34 age group. In the first post, I just compared growth of this population by Columbus’ peers, but let’s take a closer look at this group through educational attainment. I will use the same 33 cities I used in the first post.

Educational Attainment 2014 Rank by City of Bachelors Degree or Higher within 25-34 Population
1. Chicago: 268,470
2. Austin: 97,721
3. Columbus: 75,305
4. San Jose: 68,392
5. Charlotte: 63,132
6. San Antonio: 62,572
7. Portland: 60,259
8. Minneapolis: 51,043
9. Indianapolis: 48,188
10. Pittsburgh: 35,860
11. Kansas City: 32,101
12. Madison: 30,039
13. Milwaukee: 29,661
14. Omaha: 28,984
15. St. Louis: 28,946
16. Sacramento: 27,304
17. Cincinnati: 25,496
18. St. Paul: 22,929
19. Virginia Beach: 22,134
20. Orlando: 20,181
21. Wichita: 19,659
22. Las Vegas: 17,817
23. Lincoln: 16,429
24. Grand Rapids: 15,724
25. Detroit: 14,285
26. Fort Wayne: 12,228
27. Cleveland: 12,013
28. Des Moines: 10,089
29. Providence: 10,432
30. Toledo: 8,514
31. Akron: 6,600
32. Dayton: 4,029
33. Youngstown: 1,084

Columbus has the 3rd highest total of 25-34 year olds with at least a bachelor’s degree, even compared to some cities with larger populations in the city or metro area. This is likely due to the high number of colleges and universities in the area, not least of which includes Ohio State.

2014 % of Total 25-34 Age Group with Bachelors or Higher
1. Madison: 67.0%
2. Pittsburgh: 57.4%
3. Minneapolis: 56.3%
4. Portland: 51.5%
5. Chicago: 51.1%
6. Austin: 48.9%
7. Cincinnati: 47.0%
8. St. Louis: 46.9%
9. Charlotte: 44.5%
10. San Jose: 44.5%
11. Columbus: 44.1%
12. St. Paul: 42.1%
13. Lincoln: 41.0%
14. Omaha: 40.8%
15. Grand Rapids: 40.5%
16. Kansas City: 40.5%
17. Orlando: 37.1%
18. Indianapolis: 34.3%
19. Wichita: 33.7%
20. Providence: 32.7%
21. Sacramento: 32.5%
22. Fort Wayne: 32.4%
23. Des Moines: 29.8%
24. Milwaukee: 29.6%
25. Virginia Beach: 29.3%
26. San Antonio: 27.6%
27. Akron: 23.4%
28. Cleveland: 21.4%
29. Las Vegas: 19.7%
30. Toledo: 19.5%
31. Dayton: 19.1%
32. Detroit: 15.9%
33. Youngstown: 12.8%

While just outside of the top 10 in the peer group, Columbus still performs in the top 1/3rd when it comes to the % of 25-34 year olds that have at least a bachelor’s degree.

2000-2014 Total Change in Age 25-34 with a Bachelor’s Degree or Higher
1. Chicago: +78,514
2. Austin: +38,348
3. Portland: +26,042
4. San Antonio: +23,504
5. Columbus: +21,601
6. Charlotte: +19,149
7. Pittsburgh: +19,060
8. Minneapolis: +15,629
9. St. Louis: +14,538
10. San Jose: +13,372
11. Sacramento: +11,530
12. Kansas City: +10,499
13. Madison: +8,774
14. Orlando: +8,600
15. Omaha: +8,521
16. Indianapolis: +8,369
17. Milwaukee: +7,031
18. Grand Rapids: +6,275
19. Wichita: +6,049
20. Fort Wayne: +5,350
21. Cincinnati: +5,083
22. Las Vegas: +4,433
23. St. Paul: +4,316
24. Virginia Beach: +4,167
25. Lincoln: +3,450
26. Providence: +2,488
27. Des Moines: +806
28. Dayton: +59
29. Youngstown: -108
30. Cleveland: -522
31. Akron: -628
32. Detroit: -1,471
33. Toledo: -1,639

Another great showing is in the total growth of 25-34 year olds with at least a bachelor’s degree. Again, Columbus is outperforming several larger cities/metros on the list.

2000-2014 Total % Change in Age 25-34 with a Bachelor’s Degree or Higher
1. Pittsburgh: +113.45%
2. St. Louis: +100.90%
3. Fort Wayne: +77.78%
4. Portland: +76.11%
5. Orlando: +74.26%
6. Sacramento: +73.09%
7. Grand Rapids: +66.41%
8. Austin: +64.59%
9. San Antonio: +60.16%
10. Kansas City: +48.60%
11. Wichita: +44.45%
12. Minneapolis: +44.13%
13. Charlotte: +43.54%
14. Omaha: +41.64%
15. Chicago: +41.33%
16. Madison: +41.26%
17. Columbus: +40.22%
18. Las Vegas: +33.12%
19. Providence: +31.32%
20. Milwaukee: +31.07%
21. Lincoln: +26.58%
22. Cincinnati: +24.90%
23. San Jose: +24.30%
24. St. Paul: +23.19%
25. Virginia Beach: +23.19%
26. Indianapolis: +21.02%
27. Des Moines: +8.68%
28. Dayton: +1.49%
29. Cleveland: -4.16%
30. Akron: -8.69%
31. Youngstown: -9.06%
32. Detroit: -9.34%
33. Toledo: -16.14%

So in Part 1, it was shown that Columbus had one of the fastest growing 25-34 populations. These numbers show that it also has one of the largest age 25-34 populations with a Bachelor’s degree or higher in terms of totals, and one of the fastest growing in terms of totals. By %, however, it performs a bit worse, but part of the reason for that is because so many of these cities started with relatively low educated populations to begin with. Overall, Columbus seems to be very attractive, not only to this age group, but also for those within the group that are highly educated.

Economic Segregation in Columbus

Luckily, I saved all of my maps that I did for this report, so not all was lost. Instead of making it a 2-part post, I’m just reposting it all in one this time.

In any case, economic segregation is basically where people living in the same city are segregated in terms of financial characteristics, such as housing prices or income. This is considered negative as the more economically segregated an area is, the harder it is for people, especially in lower income brackets, to move up financially. My report focuses on household income within census tracts in Franklin County and where those household incomes are changing the most.

First of all, let’s look at the household income levels around the county, both in 2000 and 2014.

In 2000, the median household income for the county was highest in the Upper Arlington and Grandview, Dublin, Bexley, Hilliard and the New Albany area. Downtown and adjacent areas had the lowest, as well as the general urban core and East Side.

By 2014, household income remained the highest in the same areas it was in 2000, but there were major improvements in many parts of the urban core, especially around Downtown, the Near East Side, Near South, Clintonville and the Short North. To illustrate this change better, take a look at the next map.

Unfortunately, because not all of 2014’s census tracts existed in 2000, I don’t have data for the entire county for comparison. But the trend is very clear. The areas that saw the biggest improvements in median household incomes were in the dead center of the county- Downtown, Near South and East Sides, as well as the Short North and Grandview. Only parts of Hilliard, Clintonville and Worthington really saw anything remotely as close. This indicates, at least to me, that the beating heart of revitalization and growth in the county is along the High Street corridor.

So now that we’ve established what the incomes look like across the county, let’s break it down further into income level brackets. This will help determine where economic segregation is a problem and where it isn’t.

The lowest household income I looked at was Below $25K a year. In 2000, this income level was most heavily concentrated in the Downtown area and adjacent neighborhoods. The Near East Side, as well as Linden down through the east side of I-71 had the county’s highest % of households that earned this level of income. Hilltop and the West Broad Corridor were also fairly high.

By 2014, the lowest household income level looked largely the same. However, there were also some noticeable difference. Downtown, the Near East Side, the Near South Side and parts of the North High Corridor saw obvious declines in this population, while it seemed to spread further east outside of 270 into suburban areas.

In the map above, we can see how Below $25K household incomes had changed in the tracts between 2000 and 2014 by % point change. Ironically, the urban core, especially along High and Broad streets saw the most consistent declines in this population while areas around and outside of 270 saw the most consistent increases. The good news is that more tracts saw declines than increases, but the map does indicate that poverty is perhaps moving further out from the core.

Next up is the household income level change that would be considered closest to middle class- $50K-$99K.

The urban core areas clearly saw the most consistent increases in middle class household income levels, while the outer suburbs almost universally declined in this metric. One explanation for this is that the lowest incomes in the core moved up into the middle class, while in the suburbs, middle class incomes moved into the upper class incomes. That would explain both the rise in the core, but the decline in the suburbs. But to prove if this is true or not, we have to look at the highest income levels- those of $100K and above.

In 2000 the highest incomes were almost entirely outside of 270 except for Bexley and the Northwest Side communities like Dublin and Upper Arlington. It is likely that the New Albany area also had high incomes, but again, those tracts didn’t exist in 2000, so it is difficult to give that information.

By 2014, while the Northern areas of Franklin County continued to have the highest incomes in general, gains were made in many parts of the county, including several within the urban core area.

Between 2000 and 2014, there was almost universal growth of $100K+ incomes in Franklin County, with only small areas seeing declines. The Northwest communities, as well as areas in and around Downtown seemed to do the best.

Okay, so incomes levels are clearly improving in most of the county, but especially in urban core areas. But what is the difference between the highest and lowest incomes within each census tract? To find out, I took the % of households in each tract earning less than $25K a year vs. the % of households earning $100K or more. The % point difference between these two groups is a good indication of how much economic segregation exists. The closer this number is to 0, the more economically integrated a tract is. Negative numbers indicate that Below $25K household incomes outweigh those making $100K or more, while positive numbers are the reverse.

The 2000 map shows that Below $25K household incomes dominate inside I-270, particularly around Downtown and the East Side. Many tracts contain at least 40 % points more $25K incomes than $100K incomes. This shows that poverty was deeply concentrated around the center of the county. Suburban areas were more dominated by the reverse, where middle and upper class households were concentrated.

In 2014, the severely concentrated levels of the lowest incomes have eased in most locations. There are fewer tracts of 40+ point differences, especially around Downtown and the general High Street Corridor. Only the Campus area, for obvious reasons, and parts of Linden, largely remain unchanged.

So what does all this ultimately mean about economic segregation in Frankly County? To get a simplified sense of that picture, considering the final set of maps.

In the coloring, the blue tracts are tracts that have income point differences that are between -15 and +15. These are the tracts that are most economically integrated. Green tracts are those with differences of +/- 15 to 29 points, while orange represent those with +/- 30 points or more. Orange tracts are the most economically segregated. In 2000, most of the orange tracts were within I-270. In fact, they very closely represent the most urban part of Columbus- the 1950 city boundary. They are amazingly similar. Meanwhile, almost all the outer suburbs in 2000 were well integrated.

Fast forward to 2014 and the picture becomes significantly more convoluted. Being in the urban core vs. the suburbs does not automatically guarantee economic integration. Many suburbs are now as severely segregated as some of the urban core is, while parts of the urban core are as integrated as some suburbs.

Overall, it appears that Franklin County has improved its economic integration in the last decade or so, but there is still more than can be done. Economic incentives for providing more mixed-income housing and bringing more jobs to urban areas would likely help achieve a more integrated city and county.

2013 Census Tract Estimates

The Census released updated tract estimates for 2013, and they showed some interesting things. There are 285 census tracts that make up Franklin County.

First, let’s take a look at the Franklin County trends 2000-2013.

In regards to the above map, it’s a mix of both the 2013 official estimates and some that I did. For example, the official estimates had the Downtown tracts 30 and 40 losing population, as well as most of the Short North. That’s rather absurd considering the level of residential construction in these areas, as well as population estimates the city has done in the last few years for Downtown. In fact, the 2013 official estimates have Downtown tract population BELOW 2010. That’s just not the reality. So I looked over the tracts and adjusted them according to their long-term growth/decline trends. Most of them I left alone, but some adjustments had to be made. However, I was very conservative with any changes, and several tracts that the official estimates showed gains, I actually had losses.

Here are all the tracts that grew by at least 300 people between 2010 and 2013 in Franklin County, as well as their locations.

Blacklick #7395: +1,609
Dublin #6230: +1,214
Columbus-West Side #7951: +1,002
Columbus-Northwest #6372: +966
Columbus Northeast #6931: +963
Hilliard #7921: +955
Columbus-East Side #9361: +952
Columbus-West Side #8350: +951
Columbus-Northwest: #6384: +949
Dublin #6220: +933
Columbus-West Side #8141: +921
Columbus-Easton #7551: +793
Columbus-Southeast #9373: +749
Hilliard #7933: +688
Minerva Park #7112: +675
Columbus-South Side #8340: +652
Hilliard #7954: +643
Columbus North Side #7044: +636
Columbus Northeast #7132: +615
Columbus Northwest #6396: +557
Dublin #6386: +549
Columbus North Side #6921: +540
Columbus Northwest #6393: +492
Columbus-West Side: +489
Gahanna #7492: +473
New Albany #7209: +472
Columbus-Hilltop #8321: +466
Columbus-Southeast #9374: +455
Grove City #9740: +441
Columbus Northeast #6945: +438
Hillard #7931: +432
Columbus-West Side #7812: +427
Columbus-South Side #9590: +411
Columbus-South Side #8710: +407
Hilliard #10602: +407
Columbus-South Side #8822: +403
Whitehall #9230: +398
Columbus-West Side #8163: +397
Columbus-East Side #9362: +389
Columbus-Downtown #30: +387
Hilliard #7953: +382
Columbus-West Side #6330: +371
Columbus-Northwest #6387: +361
Columbus-East Side #9322: +352
Columbus-South Side #8825: +349
Columbus-Southwest #8161: +346
West Side-Marble Cliff #43: +345
Columbus-Southwest #8370: +340
Grandview #85: +332
Columbus-Downtown #40: +321
Hilliard #7922: +320
Dublin #6371: +312
Grove City #9751: +304
Columbus-Campus Area #13: +303

As far as the core of the city, the 1950 boundaries, here are the results.

There are 78 tracts that make up the original 1950 city boundary. Using the official estimates, 38 of the 78 tracts grew between 2010-2013, yet had a total loss of 3,229. However, again, it had all the Downtown and adjacent tracts inexplicably losing population, yet the opposite is occurring in these areas. For Downtown, the combined loss was about 370, and for the Short North, it had the loss at more than 700.

Using my adjusted estimates, 35 tracts are growing, adding 1,166 people 2010-2013. Most of the gains were made in the Downtown and adjacent tracts, and some of the losses were simply not as steep. For example, the official estimates had tract #10, in the Campus area, losing nearly 1,300 people since 2010, which is a ridiculous loss, especially considering it grew by almost 8% 2000-2010. In fact, most of the largest losses from the official estimates were around Campus and the Short North. Nonsense.