The Census released updated 2013 census tract estimates, 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.
Over the last few decades, much attention has been given to the fact that domestic migration by state has heavily favored the “Sun Belt”, states made up of the Southeast west to the West Coast. While Northern states weren’t all losing people, the region as a whole sent far more people to the Sun Belt than they retained. This helped fuel the respective Southern boom, and media story after media story over the years have made sweeping predictions of this growing powerhouse region, often centered around the idea that the boom had no foreseeable end. The irony with these predictions is that they ignored history. For more than 2 centuries, the North was where people moved. Its states and cities saw massive influxes of population. As recently as the decade of the 1950s, Ohio grew by nearly 2 million alone. Economic conditions in decline, job losses, particularly in the manufacturing industry, increases in the cost of living and other factors ended the boom and helped to bring about the rise of the South, so to speak. Since at least the 1960s, the story has been about the Sun Belt/West.
The Censusdoes state migration estimates every year, and there are some interesting things going on in the data that may indicate that the boom in the South is faltering while the North’s fortunes are not looking as grim as they once did.
First, what are the regions? South: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia and West Virginia. North: Connecticut, Delaware, Washington D.C., Illinois, Indiana, Iowa, Kansas, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Dakota, Ohio, Pennsylvania, Rhode Island, South Dakota, Vermont and Wisconsin. West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington and Wyoming.
Let’s next look at the states by rank of domestic migration in 2005, the earliest available year for the state data, and compared it to 2012, the most recent year available. This period covers the period just before and just after the Great Recession.
So in 2005, the breakdown was as follows: 12 of 14 Southern states had positive domestic migration. The only 2 that did not, Louisiana and Mississippi, were heavily influenced in 2005 by Hurricane Katrina, which caused large numbers of displaced residents to leave the states entirely. 7 of 24 Northern states has positive domestic migration. The 7 states were mixed between the Midwest and the Northeast/Mid-Atlantic. Just one Great Lakes State had positive domestic migration in 2005. 9 of 13 Western states had positive domestic migration. Only California and a few Mountain West states had negative numbers.
The 2005 numbers show the overall domestic migration picture as it had been for at least the last few decades, if not much longer. The South and West were the dominant net gainers of domestic migration, while most of the North sent people to those regions.
In 2012, the breakdown was as follows: 11 of 14 Southern states had positive domestic migration. Even with Katrina-hit state Mississippi having net gains in 2012, the overall number of states with positive gains declined. 8 of 24 Northern states had positive domestic migration, a slight improvement over 2005. 8 of 13 Western states had positive domestic migration, a slight decline over 2005.
But the breakdowns don’t tell us the whole story. When trying to compare the two years, trends are very important, and the trends are far more revealing.
5 of 14 Southern states improved their domestic migration rates 2005-2012. 13 of 24 Northern states improved their domestic migration rates 2005-2012. 3 of 13 Western states improved their domestic migration rates 2005-2012.
Ohio had the 4th best improvement over the period, a huge change. But some might ask, is it really a change when the rates may still be positive or negative like they were before? Well, yes and no. 7 years is not that long, and we’re talking about decades-long patterns here. Those won’t change like flipping a switch. It will take time. The point is more that for many states that have faced negative numbers for a long time, there is positive momentum now that they did not have before. Another question some may ask, however, is if the recession during the period reduced mobility. In some cases, I’m sure that it did, but if so, that reduction seems to have been centered on the South. A reduction in mobility would only indicate that migration rates would reduce to levels around 0, neither particularly positive nor negative. That reduction would NOT necessarily support switches from positive to negative or increases in negative or positive rates that already exist. Meaning that reduced mobility would mean that positive would become less positive as fewer people moved in, and negative would become less negative as fewer people left. On a state and regional basis, there is a wide range of results that do not support that geographic mobility alone is the culprit, or even a primary factor.
June’s housing data for the Columbus region was just released. The month continued the same story as the previous 5 months, with home sales down due to a lack of inventory. Prices continued to rise and the number of days to sell a home continued to fall in relation to this problem. As always, I looked at 21 major areas of the Columbus region, both urban and suburban. Here is how those areas performed.
Top 10 June 2014 Sales Totals 1. Columbus: 1,045 2. Upper Arlington: 109 3. Dublin: 108 4. Clintonville: 83 5. Westerville: 77 6. Gahanna: 63 7. Grove City: 62 8. Reynoldsburg: 59 9. New Albany: 38
Top 10 June 2014 Sales Increases over June 2013 1. Downtown: +72.0% 2. Grove City: +14.5% 3. Gahanna: +12.7% 4. German Village: +10.5% 5. Grandview Heights: +6.3% 6. Canal Winchester: +3.8% 7. Hilliard: 0.0% 8. Minerva Park: 0.0% 9. Columbus: -1.8% 10. Reynoldsburg: -5.1%
Top 10 Year-to-Date Sales Through June 2014 1. Columbus: 4,803 2. Dublin: 362 3. Grove City: 332 4. Clintonville: 323 5. Westerville: 299 6. Upper Arlington: 294 7. Reynoldsburg: 265 8. Hilliard: 258 9. Gahanna: 221 10. Pickerington: 136
Top 10 Year-to-Date Increases Through June 2014 Over 2013 1. Obetz: +42.1% 2. Downtown: +13.4% 3. Grove City: +11.0% 4. New Albany: +2.8% 5. Reynoldsburg: -0.4% 6. Westerville: -3.2% 7. Pataskala: -3.4% 8. German Village: -3.9% 9. Columbus: -5.3% 10. Clintonville: -5.8%
Average Sales June 2014 Urban: 122.3 Suburban: 55.1 Urban without Columbus: 30
Average % Change June 2014 vs. June 2013 Urban: -5.8% Suburban: -5.1% Urban without Columbus: -6.0%
Average YTD Sales Through June 2014 Urban: 545 Suburban: 222.6 Urban without Columbus: 119.2
Average YTD % Change YTD Through June 2014 Urban: -4.8% Suburban: -5.3% Urban without Columbus: -4.7%
Top 10 Average Sales Price June 2014 1. New Albany: $659,186 2. Upper Arlington: $389,575 3. Bexley: $382,496 4. Dublin: $377,541 5. German Village: $307,753 6. Downtown: $300,582 7. Worthington: $283,209 8. Grandview Heights: $246,271 9. Hilliard: $230,396 10. Gahanna: $229,845
Top 10 Average Sales Price % Change June 2014 vs. June 2013 1. Whitehall: +55.6% 2. Worthington: +17.7% 3. New Albany: +15.8% 4. Bexley: +15.6% 5. Columbus: +12.2% 6. Clintonville: +9.3% 7. Hilliard: +8.5% 8. Canal Winchester: +7.4% 9. Pickerington: +6.7% 10. Gahanna: +6.4%
Top 10 Average Sales Prices YTD Through June 2014 1. New Albany: $541,077 2. Dublin: $360,202 3. Upper Arlington: $348,160 4. Bexley: $334,491 5. Downtown: $305,215 6. German Village: $302,117 7. Worthington: $261,659 8. Grandview Heights: $245,946 9. Hilliard: $225,849 10. Gahanna: $213,782
Top 10 Average YTD Sales Price % Change Through June 2014 vs. 2013 1. Obetz: +24.7% 2. Grandview Heights: +15.5% 3. Worthington: +11.3% 4. Pataskala: +10.8% 5. Columbus: +10.6% 6. Pickerington: +9.9% 7. Canal Winchester: +9.5% 8. Downtown: +9.5% 9. Dublin: +9.2% 10. Westerville: +8.5%
Average Sales Price June 2014 Urban: $232,965 Suburban: $253,488 Urban without Columbus: $240,917
Average Sales Price Change June 2014 vs. June 2013 Urban: +7.6% Suburban: +5.0% Urban without Columbus: +7.1%
Average Sales Price YTD Through June 2014 Urban: $220,893 Suburban: $234,492 Urban without Columbus: $229,327
Average Sales Price % Change YTD Through June 2014 Urban: +6.6% Suburban: +7.5% Urban without Columbus: +6.2%
Top 10 Fastest Selling Markets June 2014 (Based on Average # of Days for Listings to Sell) 1. Worthington: 21 2. Upper Arlington: 36 3. Clintonville: 38 4. Gahanna: 39 5. Hilliard: 39 6. Dublin: 40 7. German Village: 42 8. Obetz: 45 9. Bexley: 46 10. Pataskala, Westerville: 47
Average # of Days Before Sale, June 2014 Urban: 47.8 Suburban: 54.3 Urban without Columbus: 47.3
Average # of Days Before Sale YTD Through June 2014 Urban: 58.6 Suburban: 67.8 Urban without Columbus: 57.4
Top 10 Lowest Market Housing Supplies June 2014 (Based on # of Months to Sell all Listings) 1. Grandview Heights: 1.0 2. Worthington: 1.4 3. Westerville: 2.0 4. Clintonville: 2.1 5. German Village: 2.1 6. Gahanna: 2.3 7. Hilliard: 2.5 8. Minerva Park: 2.7 9. Obetz: 2.7 10. Upper Arlington: 2.7
A healthy housing supply is considered to be around 5-6 months. Anything less than 3 months is considered very low. Grandview’s 1 month is ridiculously low and the lowest reading I’ve seen for any area.
Average # of Months to Sell All Listings, June 2014 Urban: 2.7 Suburban: 3.5 Urban without Columbus: 2.6
Average % Change of Single-Family Home Sales June 2014 vs. June 2013 Urban: +33.2% Suburban: -5.4% Urban without Columbus: +36.8%
Average % Change of Single-Family Home Sales YTD Through June 2014 vs. YTD 2013 Urban: -8.8% Suburban: -5.4% Urban without Columbus: -8.9%
Average % Change of Condo Sales June 2014 vs. June 2013 Urban: -4.0% Suburban: +41.0% Urban without Columbus: -5.0%
Average % Change of Condo Sales YTD Through June 2014 vs. YTD 2013 Urban: +19.3% Suburban: +7.0% Urban without Columbus: +21.0%
Over the years, I’ve learned that Columbus has a very suburban reputation, meaning that it is perceived to have very low density throughout, especially because it aggressively annexed suburban areas into the city limits decades ago. With those claims, I wondered what the metro population densities would be if Columbus’ area size was scaled down to others, with the goal of finding out if it really deserves the suburban reputation. Bare with me, because there is a lot to look at.
First, I used Columbus’ 18 peer metros (population 1.5-2.5 million) per the Census, as well as the 14 largest Midwest metros. Since there was some overlap in the 2 groups, it made for a total group comparison of 27. So a fairly sizeable group. Next, I used the mile marker population, which in the City Hall census analysis is made up of circles going out from the center. So it’s just a matter of finding the area of each circle and dividing the population into that. What’s left is the density by area.
Density at Mile Marker 3, with an Area of 28.27 Square Miles 2000————————————2010 1. Chicago: 17,528.7_____________________ 1. Chicago: 18,003.2 2. San Jose, CA: 13,883.0________________ 2. San Jose, CA: 14,549.2 3. Las Vegas: 11,646.0___________________ 3. Las Vegas: 11,576.2 4. Minneapolis: 11,494.2_________________ 4. Minneapolis: 11,503.3 5. Milwaukee: 11,448.9___________________ 5. Milwaukee: 11,288.0 6. Providence: 11,173.7__________________ 6. Providence, RI: 11,240.2 7. Pittsburgh: 10,594.4__________________ 7. Pittsburgh: 9,738.7 8. San Antonio. TX: 9,234.3______________ 8. Portland, OR: 8,973.6 9. Portland, OR: 8,257.0_________________ 9. San Antonio, TX: 8,846.8 10. Cincinnati: 8,141.9__________________ 10. Columbus: 7,834.0 11. Columbus: 8,134.9____________________ 11. Sacramento, CA: 7,668.7 12. Sacramento, CA: 7,261.5______________ 12. Austin, TX: 7,534.0 13. Austin, TX: 7,232.3__________________ 13. Cincinnati: 7,273.6 14. Akron: 6,925.4_______________________ 14. Grand Rapids, MI: 6,540.0 15. Grand Rapids, MI: 6,852.0____________ 15. Akron: 6,284.9 16. Indianapolis: 6,727.9________________ 16. Orlando: 6,055.1 17. Toledo: 6,651.5______________________ 17. Omaha: 5,968.3 18. Dayton: 6,382.8______________________ 18. Toledo: 5,982.1 19. St. Louis: 6,093.7___________________ 19. Indianapolis: 5,879.9 20. Kansas City: 6,025.1_________________ 20. St. Louis: 5,663.8
Density at Mile Marker 4, with an Area of 50.27 Square Miles 2000———————————2010 1. Chicago: 15,447.2____________________ 1. Chicago: 15,205.9 2. San Jose, CA: 12,209.3_______________ 2. San Jose, CA: 12,629.6 3. Las Vegas: 9,788.0___________________ 3. Las Vegas: 10,022.2 4. Minneapolis: 8,874.4_________________ 4. Minneapolis: 8,921.8 5. Milwaukee: 8,823.8___________________ 5. Milwaukee: 8,725.5 6. Providence, RI: 8,454.3______________ 6. Providence, RI: 8,483.8 7. Pittsburgh: 8,216.0__________________ 7. Portland, OR: 7,785.5 8. Portland, OR: 7,282.9________________ 8. Pittsburgh: 7,602.6 9. San Antonio, TX: 7,208.6_____________ 9. San Antonio, TX: 6,995.5 10. Cincinnati: 6,922.8_________________ 10. Cincinnati: 6,279.4 11. Columbus: 6,449.3___________________ 11. Columbus: 6,257.4 12. Sacramento, CA: 5,744.7_____________ 12. Sacramento, CA: 6,138.5 13. Austin, TX: 5,541.5_________________ 13. Austin, TX: 5,847.2 14. St. Louis: 5,447.5__________________ 14. Omaha: 5,047.2 15. Cleveland: 5,356.2__________________ 15. St. Louis: 5,001.6 16. Indianapolis: 5,348.8_______________ 16. Grand Rapids, MI: 4,922.9 17. Detroit: 5,163.1____________________ 17. Orlando: 4,911.7 18. Omaha: 5,019.8______________________ 18. Indianapolis: 4,793.5 19. Akron: 4,900.7______________________ 19. Akron: 4,532.0 20. Dayton: 4,889.3_____________________ 20. Cleveland: 4,521.8
Density at Mile Marker 5, with an Area of 78.54 Square Miles Note that this area size is about the current city size of Cincinnati and Cleveland. 2000————————————2010 1. Chicago: 14,213.6___________________ 1. Chicago: 13,591.0 2. San Jose, CA: 10,464.0______________ 2. San Jose, CA: 11,037.1 3. Las Vegas: 8,521.9__________________ 3. Las Vegas: 9,062.8 4. Minneapolis: 7,443.0________________ 4. Minneapolis: 7,455.9 5. Milwaukee: 7,081.2__________________ 5. Milwaukee: 7,029.1 6. Pittsburgh: 7,009.9_________________ 6. Pittsburgh: 6,492.7 7. San Antonio, TX: 6,326.6____________ 7. Portland, OR: 6,442.3 8. Providence, RI: 6,048.3_____________ 8. San Antonio, TX: 6,223.4 9. Portland, OR: 5,950.1_______________ 9. Providence, RI: 6,055.8 10. Cincinnati: 5,588.9________________ 10. Sacramento, CA: 5,664.2 11. Cleveland: 5,494.6_________________ 11. Orlando: 5,274.1 12. Columbus: 5,252.9__________________ 12. Columbus: 5,152.1 13. Sacramento, CA: 5,104.0____________ 13. Cincinnati: 5,096.2 14. Orlando: 4,993.7___________________ 14. Austin, TX: 4,993.7 15. Austin, TX: 4,786.5________________ 15. Cleveland: 4,602.4 16. Detroit: 4,748.7___________________ 16. St. Louis: 4,285.4 17. St. Louis: 4,731.5_________________ 17. Indianapolis: 4,086.1 18. Indianapolis: 4,447.7______________ 18. Omaha: 3,962.2 19. Akron: 4,025.9_____________________ 19. Grand Rapids, MI: 3,887.3 20. Grand Rapids, MI: 3,990.6__________ 20. Akron: 3,778.8
So if Columbus was the same size as Cincinnati and Cleveland, it would be the most dense city of the 3. And it’s generally in the top half of the grouping in its most urban areas.
But what about further out, past the urban core?
Density at Mile Marker 10, with an Area of 314.16 Square Miles. This area size is much larger than the city limits of Columbus, but it gives an idea of the larger area’s density and not just within the city limits. 2000———————————–2010 1. Chicago: 9,344.3______________________ 1. Chicago: 8,795.0 2. San Jose, CA: 4,563.2_________________ 2. San Jose, CA: 4,809.8 3. Minneapolis: 4,183.2__________________ 3. Las Vegas: 4,794.2 4. Detroit: 4,117.4______________________ 4. Portland, OR: 4,230.3 5. Las Vegas: 3,877.3____________________ 5. Minneapolis: 4,178.3 6. Portland: 3,780.8_____________________ 6. San Antonio, TX: 3,454.9 7. Cleveland: 3,308.4____________________ 7. Detroit: 3,354.7 8. Pittsburgh: 3,279.8___________________ 8. Columbus: 3,163.9 9. San Antonio, TX: 3,217.8______________ 9. Pittsburgh: 3,080.4 10. Milwaukee: 3,013.7___________________ 10. Orlando: 3,055.0 11. Columbus: 2,973.3____________________ 11. Sacramento, CA: 3,016.4 12. St. Louis: 2,937.6___________________ 12. Milwaukee: 3,006.2 13. Cincinnati: 2,873.4__________________ 13. Cleveland: 2,923.7 14. Orlando: 2,783.9_____________________ 14. Indianapolis: 2,772.6 15. Sacramento, CA: 2,736.7______________ 15. St. Louis: 2,751.3 16. Indianapolis: 2,652.6________________ 16. Cincinnati: 2,746.8 17. Kansas City: 2,599.0_________________ 17. Kansas City: 2,538.3 18. Providence, RI: 2,360.0______________ 18. Austin, TX: 2,439.6 19. Austin, TX: 2,111.3__________________ 19. Providence, RI: 2,375.1 20. Dayton: 1,920.7______________________ 20. Charlotte, NC: 2,332.7
So what does all this tell us? That while Columbus is not the most dense city of its peer group, or within the Midwest group, it probably does not wholly deserve its low-density, suburban reputation. Most of the measurements are in the top half of the grouping for density, yes, but it is clearly the most weak in the urban core closest to Downtown, as that ranking is the lowest for it. The Mile 0 population, for example, is down near the very bottom, and that is a good reason why densities are not as high as they should/could be. Currently, Downtown and surrounding neighborhoods are seeing a residential development boom, so that will help, but the city needs to think a lot bigger if it wants that stereotype to truly go away. The recent abandonment of the Convention Center mixed-use project is not a good way to go about that goal… and it should be a goal.
Today, the Census released new population figures for cities and incorporated places. I looked at all those places within the Columbus metro area and came up with the following stats on 2013 city population estimates.
So by the trends, it definitely appears that most suburbs have slowed, while Columbus and its inner suburbs increased. This seems like a pretty good indication of the ongoing urban movement to me.
