Report on Domestic Migration by State

Over the last few decades, much attention has been given to the fact that domestic migration 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 US Census does 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.

Domestic Migration Rank, 2005 vs. 2012, by Total
2005___________________________________2012
1. Florida: +188,035__________________________1. Florida: +108,823
2. Arizona: +131,501_________________________2. Texas: +105,565
3. Texas: +124,522__________________________3. Colorado: +43,530
4. Georgia: +88,250__________________________4. Washington: +37,187
5. North Carolina: +51,575_____________________5. North Carolina: +34,846
6. Tennessee: +43,901________________________6. South Carolina: +34,149
7. Oregon: +43,360___________________________7. Nevada: +25,835
8. Washington: +38,093________________________8. Arizona: +25,615
9. South Carolina: +32,312______________________9. Georgia: +25,204
10. Arkansas: +30,765_________________________10. Missouri: +20,176
11. Nevada: +26,839__________________________11. North Dakota: +14,254
12. Idaho: +20,308____________________________12. Tennessee: +13,255
13. Colorado: +16,963_________________________13. Virginia: +12,110
14. Oklahoma: +16,372_________________________14. Arkansas: +11,981
15. Alabama: +14,501__________________________15. Oregon: +10,742
16. New Mexico: +13,714_______________________16. New Hampshire: +10,711
17. Delaware: +12,561_________________________17. Delaware: +10,610
18. Virginia: +11,121___________________________18. Kentucky: +8,899
19. Kentucky: +7,451___________________________19. Mississippi: +6,569
20. Missouri: +6,338____________________________20. Oklahoma: +6,402
21. Iowa: +5,406_______________________________21. Utah: +5,717
22. Montana: +4,185____________________________22. Vermont: +4,375
23. Pennsylvania: +2,868________________________23. South Dakota: +3,578
24. Maine: +2,447______________________________24. Montana: +3,410
25. Hawaii: +2,388______________________________25. Idaho: +3,400
26. West Virginia: +998__________________________26. Wisconsin: +1,468
27. New Hampshire: +497________________________27. Iowa: +275
28. South Dakota: +360__________________________28. Ohio: -105
29. Wyoming: -366______________________________29. West Virginia: -300
30. Minnesota: -1,154____________________________30. Wyoming: -639
31. Kansas: -2,244______________________________31. Maryland: -2,821
32. North Dakota: -2,553__________________________32. Rhode Island: -2,948
33. Wisconsin: -2,756____________________________33. Louisiana: -4,741
34. Vermont: -3,580_____________________________34. Kansas: -4,850
35. Nebraska: -5,128____________________________35. Nebraska: -5,174
36. Utah: -5,639________________________________36. Hawaii: -6,364
37. Connecticut: -6,536__________________________37. Connecticut: -6,712
38. Mississippi: -7,120___________________________38. Washington D.C.: -7,470
39. Indiana: -9,222______________________________39. New Mexico: -9,228
40. Maryland: -9,718____________________________40. Alabama: -9,431
41. Washington D.C.: -12,872_____________________41. Indiana: -10,460
42. Rhode Island: -15,037________________________42. Maine: -11,025
43. New Jersey: -22,051_________________________43. Minnesota: -14,904
44. Alaska: -23,567_____________________________44. Massachusetts: -15,579
45. Ohio: -40,841______________________________45. Pennsylvania: -21,656
46. Massachusetts: -52,726______________________46. Michigan: -41,761
47. Michigan: -53,852___________________________47. Alaska: -49,250
48. Illinois: -55,932_____________________________48. Illinois: -68,356
49. Louisiana: -99,684__________________________49. California: -73,345
50. New York: -239,848_________________________50. New Jersey: -89,666
51. California: -266,243_________________________51. New York: -135,149

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.

Total Change 2005-2012 By Rank
1. California: +192,898
2. New York: +104,699
3. Louisiana: +94,943
4. Ohio: +40,736
5. Massachusetts: +37,147
6. Colorado: +26,567
7. North Dakota: +16,807
8. Missouri: +13,838
9. Mississippi: +13,689
10. Michigan: +12,091
11. Rhode Island: +12,089
12. Utah: +11,356
13. New Hampshire: +10,214
14. Vermont: +7,955
15. Maryland: +6,897
16.Washington, D.C.: +5,402
17. Wisconsin: +4,224
18. South Dakota: +3,218
19. South Carolina: +1,837
20. Kentucky: +1,448
21. Virginia: +989
22. Nebraska: -46
23. Connecticut: -176
24. Wyoming: -273
25. Montana: -775
26. Washington: -906
27. Nevada: -1,004
28. Indiana: -1,238
29. West Virginia: -1,298
30. Delaware: -1,951
31. Kansas: -2,606
32. Iowa: -5,131
33. Hawaii: -8,752
34. Oklahoma: -9,970
35. Illinois: -12,424
36. Maine: -13,472
37. Minnesota: -13,750
38. North Carolina: -16,729
39. Idaho: -16,908
40. Arkansas: -18,784
41. Texas: -18,957
42. New Mexico: -22,942
43. Alabama: -23,932
44. Pennsylvania: -24,524
45. Alaska: -25,683
46. Tennessee: -30,646
47. Oregon: -32,618
48. Georgia: -63,046
49. New Jersey: -67,615
50. Florida: -79,212
51. Arizona: -105,886

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.

In Part 2, we’ll look more closely at how regions and individual states are performing relative to each other.

The Diversification of the Columbus Metro vs. Peers

In a related post to the recent metro population comparison of Columbus to its peer 1.5-2.5 million group, I wanted to see where the metros stood as far as their current racial makeup as well as where they are trending.

First, let’s take a look at the breakdown of race by metro in 2012, the last year that data is availabe.

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Columbus had the 5th highest % of its metro population as White, non-Hispanic.

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Columbus came in at #8 for the % of its metro population being Black, non Hispanic.

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Columbus ranks 9th for its % of metro population that is Asian, non-Hispanic.

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Columbus ranked poorly in this group, coming in at 15th of 18.

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Finally, Columbus ranked 7th in the population of Other, non-Hispanic as a % of the total metro population.

So currently, what is the overall diversity ranking of the 18 metros? To find out, I used a simple formula: Each metro would be assigned points (1-18) based on the ranking position in each racial group. Here are the final rankings.

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Overall, Columbus comes in as the 8th most-diverse metro in its 18-peer group. So a bit better than average and perhaps a bit surprising to some.

But what about where this diversity is trending? To find out, I looked at 2005 and 2012 and calculated how each racial group had changed over the period.

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Columbus did relatively well with Whites, growing at the 5th best pace.

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The Columbus metro came in the top 10, at #7, for non-Hispanic Black population growth.

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The metro didn’t fare as well on growth in the Asian population, coming in at 10th.

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Columbus came in at #6.

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So using the same point system from above, what are the fastest diversifying metros as of 2012?

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The Columbus metro was the 5th fastest diversifying metro in its peer group in 2012.

Overall, Columbus ranks higher than and much higher than average in both current racial diversity and the rate of racial diversity growth, respectively.

Columbus Area Housing Market- December

December ended a 2-month decline in home sales for the area, with overall sales up 2.5%.

Here are the stats for the 21 major areas of Franklin County that I look at housing stats for.

Top 10 December 2013 Sales Totals
1. Columbus: 657
2. Westerville: 47
3. Dublin: 45
4. Clintonville: 42
5. Upper Arlington: 41
6. Grove City: 39
7. Reynoldsburg: 38
8. Gahanna: 31
9. Hilliard: 22
10. Pickerington: 18

Top 10 December 2013 Sales Increases over December 2012
1. Minerva Park: +200.0%
2. Obetz: +200.0%
3. Reynoldsburg: +72.7%
4. Clintonville: +55.6%
5. Gahanna: +55.0%
6. Pataskala: +27.3%
7. Dublin: +15.4%
8. German Village: +10.0%
9. Worthington: +6.3%
10. Columbus: +3.8%

Top 10 Year-to-Date Sales Through December 2013
1. Columbus: 10,267
2. Dublin: 797
3. Upper Arlington: 719
4. Clintonville: 701
5. Westerville: 630
6. Grove City: 609
7. Hilliard: 556
8. Gahanna: 526
9. Reynoldsburg: 505
10. Pickerington: 312

Top 10 Year-to-Date Increases Through December 2013 Over 2012
1. Minerva Park: +51.9%
2. Gahanna: +31.8%
3. Pataskala: +31.0%
4. Reynoldsburg: +30.8%
5. Whitehall: +27.3%
6. Clintonville: +26.3%
7. Hilliard: +23.6%
8. Whitehall: +23.4%
9. Westerville: +21.9%
10. Bexley: +21.5%

Average Sales December 2013
Urban: 74.5
Suburban: 28.2
Urban without Columbus: 14.7

Average % Change December 2013 vs. December 2012
Urban: +40.5%
Suburban: +6.4%
Urban without Columbus: +44.2%

Average YTD Sales Through December 2013
Urban: 1,177.1
Suburban: 466.5
Urban without Columbus: 268.1

Average YTD % Change YTD Through December 2013
Urban: +15.7%
Suburban: +19.4%
Urban without Columbus: +15.3%

Top 10 Average Sales Price December 2013
1. New Albany: $563,187
2. Upper Arlington: $377,943
3. Bexley: $376,592
4. Dublin: $351,279
5. Downtown: $314,583
6. German Village: $303,136
7. German Village: $271,656
8. Hilliard: $249,811
9. Worthington: $232,741
10. Clintonville: $223,250

Top 10 Average Sales Price % Change December 2013 Over December 2012
1. Whitehall: +37.3%
2. New Albany: +32.8%
3. Pataskala: +29.6%
4. Reynoldsburg: +26.3%
5. Upper Arlington: +25.8%
6. Clintonville: +25.3%
7. Bexley: +23.7%
8. Hilliard: +21.9%
9. Gahanna: +19.6%
10. Dublin: +13.1%

Top 10 Average Sales Prices YTD Through December 2013
1. New Albany: $542,634
2. Upper Arlington: $365,143
3. Bexley: $352,214
4. Dublin: $336,048
5. German Village: $298,199
6. Downtown: $287,976
7. Worthington: $248,857
8. Grandview Heights: $223,185
9. Hilliard: $217,078
10. Gahanna: $199,546

Top 10 Average YTD Sales Price % Change Through December 2013 vs. 2012
1. Whitehall: +18.9%
2. Downtown: +14.0%
3. Minerva Park: +14.0%
4. Upper Arlington: +13.8%
5. Gahanna: +12.1%
6. New Albany: +9.8%
7. Reynoldsburg: +9.6%
8. Obetz: +9.0%
9. Worthington: +7.5%
10. Bexley: +5.8%

Average Sales Price December 2013
Urban: $218,764
Suburban: $233,048
Urban without Columbus: $227,832

Average Sales Price Change December 2012 vs. December 2012
Urban: -1.6%
Suburban: +15.5%
Urban without Columbus: -2.9%

Average Sales Price YTD
Urban: $217,056
Suburban: $224,060
Urban without Columbus: $226,017

Average Sales Price % Change YTD
Urban: +5.6%
Suburban: +5.6%
Urban without Columbus: +5.7%

Top 10 Fastest Selling Markets December 2013 (Based on Average # of Days for Listings to Sell)
1. Bexley: 26
2. Obetz: 42
3. New Albany: 47
4. Hilliard: 50
5. Clintonville: 51
6. Pataskala: 57
7. Gahanna: 58
8. Upper Arlington: 58
9. Reynoldsburg: 61
10. Grove City: 63

Top 10 Fastest Selling Markets YTD
1. Worthington: 42
2. Upper Arlington: 46
3. Grandview Height: 49
4. Clintonville: 50
5. Westerville: 53
6. Hilliard: 54
7. Bexley: 57
8. Gahanna: 59
9. Dublin: 63
10. Grove City: 64

Average # of Days Before Sale, December 2013
Urban: 73.4
Suburban: 63.9
Urban without Columbus: 73.8

Average # of Days Before Sale YTD
Urban: 61.3
Suburban: 62.9
Urban without Columbus: 60.9

Top 10 Lowest Market Housing Supplies (Based on # of Months to Sell all Listings)
1. Worthington: 1.2
2. Bexley: 1.8
3. Clintonville: 1.9
4. Hilliard: 1.9
5. Upper Arlington: 1.9
6. Grandview Heights: 2.1
7. Westerville: 2.1
8. Gahanna: 2.2
9. Minerva Park: 2.2
10. German Village: 2.3

A healthy housing supply is considered to be around 5 months. Anything less than 3 months is considered very low. All of the 21 areas I looked at were below 5 months, indicating a county-wide shortage. This shortage has only deepened over the last year, with December having the lowest number of available homes in nearly 15 years.

Average # of Months to Sell All Listings, December 2013
Urban: 2.7
Suburban: 3.2
Urban without Columbus: 2.6

Average % Change of Single-Family Home Sales December 2013 vs. December 2012
Urban: +28.5%
Suburban: +14.3%
Urban without Columbus: +30.8%

Average % Change of Single-Family Home Sales YTD vs. YTD 2012
Urban: +9.8%
Suburban: +19.0%
Urban without Columbus: +8.8%


Average % Change of Condo Sales December 2013 vs. December 2012

Urban: +20.5%
Suburban: -4.2%
Urban without Columbus: +20.5%

Average % Change of Condo Sales YTD vs. YTD 2012
Urban: +29.0%
Suburban: +23.5%
Urban without Columbus: +29.9%

Ohio vs. the Midwest GDP and Income

The Bureau of Economic Analysis recently issued GDP numbers for 2012, along with revised data for previous years.

First, let’s look at how Ohio is doing in relation to the other Midwest states.

2012 Gross Domestic Product By State in Millions, Highest to Lowest
1. Illinois: $695,238
2. Ohio: $509,393
3. Michigan: $400,504
4. Indiana: $298,625
5. Minnesota: $294,729
6. Wisconsin: $261,548
7. Missouri: $258,832
8. Iowa: $152,436
9. Kansas: $138,953
10. Nebraska: $99,557
11. North Dakota: $46,016
12. South Dakota: $42,464

Total Midwest GDP in 2012 in Millions: $3,198,295

So Ohio has the 2nd largest economy in the Midwest, only behind Illinois and its Chicago powerhouse. Ohio has also reclaimed its spot as the 7th largest state economy after catching up to and surpassing New Jersey, which passed Ohio in 2006.

Ohio’s more than half-trillion economy is also growing faster than almost every state in the Midwest, as shown below.

Total GDP Change 2000-2012 in Millions, Highest to Lowest
1. Illinois: +$220,718
2. Ohio: +$128,498
3. Minnesota: +$105,911
4. Indiana: +$100,387
5. Wisconsin: +$84,193
6. Missouri: +$77,865
7. Michigan: +$63,045
8. Iowa: +$59,124
9. Kansas: +$53,231
10. Nebraska: +$42,224
11. North Dakota: +$27,750
12. South Dakota: +$18,426

Difference in Millions Between Ohio’s GDP and that of Other States 2000 and 2012
Ohio vs. Illinois
2000: -$93,865
2010: -$185,845
Ohio vs. Indiana
2000: $182,657
2010: $210,768
Ohio vs. Iowa
2000: $287,583
2010: $356,957
Ohio vs. Kansas
2000: $295,173
2010: $370,440
Ohio vs. Michigan
2000: $43,436
2010: $108,889
Ohio vs. Minnesota
2000: $192,077
2010: $214,664
Ohio vs. Missouri
2000: $199,928
2010: $250,561
Ohio vs. Nebraska
2000: $323,562
2010: $409,836
Ohio vs. North Dakota
2000: $362,629
2010: $463,377
Ohio vs. South Dakota
2000: $356,857
2010: $466,929
Ohio vs. Wisconsin
2000: $203,540
2010: $247,845

So Ohio has increased its GDP lead over every Midwest state except for Illinois.

Per-Capita GDP, however, is not Ohio’s strong point.

2012 Per-Capita GDP in Dollars, Highest to Lowest
1. North Dakota: $55,250
2. Minnesota: $47,028
3. Illinois: $46,161
4. Nebraska: $44,943
5. South Dakota: $43,181
6. Iowa: $42,222
7. Kansas: $41,070
8. Wisconsin: $39,308
9. Indiana: $39,065
10. Ohio: $37,690
11. Missouri: $36,815
12. Michigan: $35,298

Per-Capita GDP, does not tell us income, however.

2012 Per-Capita Income By State, Highest to Lowest
1. North Dakota: $51,893
2. Minnesota: $46,227
3. Illinois: $44,815
4. South Dakota: $43,659
5. Nebraska: $43,143
6. Iowa: $42,126
7. Kansas: $41,835
8. Wisconsin: $40,537
9. Ohio: $39,289
10. Missouri: $39,049
11. Michigan: $37,497
12. Indiana: $36,902

Ohio does slightly better here. The question would be, why is Ohio’s so low in comparison? It may have a bit to do with the overall cost of living, at least according to the following link.
http://www.missourieconomy.org/indicators/cost_of_living/index.stm

Cost of Living Rank by State (out of 50), 2nd Quarter 2013
Nebraska: 2
Indiana: 5
Iowa: 9
Kansas: 11
Ohio: 13
Missouri: 16
Michigan: 19
Illinois: 20
Wisconsin: 23
North Dakota: 30
South Dakota: 31
Minnesota: 34

Ohio is less expensive to live in than 7 of the other Midwest states and is cheaper than 37 states in total. This almost certainly plays a role in wages. All in all, perhaps the state is far better off economically than the perception may indicate, at least by these metrics.

In Part 2, I’ll look at metro areas specifically.




2012 City Estimates and Urban vs. Suburban Trends

I posted the 2012 city estimates yesterday, and within them may be an interesting trend that has long-term implications for Columbus.

A lot of the talk in the news in recent years has been how urban core cities are seeing a comeback of sorts. I’ve made mention of it several times, myself. However, there is some disagreement between urban proponents and suburban proponents about what’s really going on, and that disagreement seems to focus mostly around if the city is growing faster than the suburbs, and if so, if that trend can be sustained.

Looking over the estimates, I noticed something that may support the urban back-to-the-city argument, at least in Columbus. What I noticed was that those villages/towns/cities that were growing tended to be clustered closer to the urban core of the metro than those that were losing population.

I first gathered the data on the Columbus metro area’s 99 incorporated places, ranging in population from 36 on up to Columbus’ 809,798. I then measured the distance between Columbus’ Downtown center and the center of all 99 places. I then broke them up into increments of about 5 miles each. Here is some of what I found.

Average Total Population Growth by Place 2010-2012 by Distance from Columbus’ Center

0-4.9 Miles: 3,962.8
5-9.9 Miles: 438.4
10-14.9 Miles: 342.8
15-19.9 Miles: 26.5
20-24.9 Miles: 148.9
25+ Miles: 10.5

What this says, is that for the most part, the closer a place is to the center, the more total average growth it’s had since 2010. While the 0-4.9 mile distance is somewhat skewed because it includes Columbus’ growth, there is also a significant drop-off beyond 15 miles from the center.

Next, I looked at all the places that saw either 0 population change or a loss during the 2010-2012 period. Again, it was separated by the distance from Columbus’ center.

0-4.9 Miles: 0 of 6, or 0.0%
5-9.9 Miles: 0 of 12, or 0.0%
10-14.9 Miles: 1 of 12, or 8.3%
15-19.9 Miles: 2 of 8, or 25.0%
20-24.9 Miles: 2 of 10, or 20.0%
25+ Miles: 21 of 51, or 41.2%

What this shows is that the further the distance away from the center, in general, the more places there were that were stagnant or lost population since 2010.

Finally, I looked at the top 15 total population increases of all places from 2010-2012, as well as their distance from Columbus’ center.

1. Columbus (obviously): +22,765- 0 Miles
2. Hilliard: +2,129- 9.9 Miles
3. Grove City: +1,257- 7.4 Miles
4. Delaware: +1,172- 23.6 Miles
5. Dublin: +1,155- 11.3 Miles
6. Westerville: +953- 12.0 Miles
7. New Albany: +783- 13.0 Miles
8. Gahanna: +580- 7.5 Miles
9. Powell: +460- 14.2 Miles
10. Reynoldsburg: +454- 9.9 Miles
11. Upper Arlington: +432- 4.1 Miles
12. Pickerington: +401- 14.1 Miles
13. Grandview Heights: +374- 2.6 Miles
14. Whitehall: +341- 6.0 Miles
15. Canal Winchester: +292- 12.7 Miles

12 of the 15 are within Franklin County. Another 2 (Pickerington and Powell) are near the Franklin County border. Only Delaware is beyond 15 miles from Columbus’ center.

So do these numbers show a real trend? Maybe. Some of the questions are: Do 2 years of data support a real trend or just a blip? Is this really an urban movement or a rural decline… or both? Is this a new/recent trend or have the numbers been changing? Those questions and others need to be answered before making a definitive statement, but if nothing else, they are a positive indication that Columbus and it’s immediate surroundings remain the metro’s (and Ohio’s) strongest population draw.