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.
