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 demographics by distance, meaning that the information is broken down by the status at the mile distance from “City Hall”, or from the center of each city’s downtown area.
This allows users to compare cities using standardized areas even though cities come in very different sizes.
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%
This kind of post seems obligatory at this time of year. I thought about making just one big post, but there was so much that happened this year that I decided to break it up by month. This won’t include every single piece of news, of course, but rather just the highlights. First up is the January 2014 review.
Weather January 2014 continued what December 2013 had started. Snowfall was nearly 2x above normal and temperatures were almost 7 degrees below normal. The month tied for the 15th coldest January and the 16th snowiest. The coldest low was -11 and the low hit 0 or below 7 times, the most since 1994. The biggest snow event occurred on the 25th-26th with 8.3″. This was the 10th largest January snowstorm of all time. Snow depth reached at least 1″ on 19 days.
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%
