The Origins of the Columbus Metro’s Domestic Migration

Top 30 Largest Net Domestic In-Migration Origins (Ohio Counties and States)

2006-2010————————2009-2013—————————-2010-2014
1. Cuyahoga: 1602———-1. Cuyahoga: 1905————–1. Cuyahoga: 1702
2. Montgomery: 1020——-2. Michigan: 1425—————-2. Michigan: 1473
3. Michigan: 893————-3. Montgomery: 1123————3. Montgomery: 1098
4. Maryland: 745————-4. Summit: 744——————–4. Washington (state): 740
5. Lorain: 740—————–5. Lorain: 715———————-5. Summit: 689
6. Virginia: 636—————6. Indiana: 694———————6. Lucas: 635
7. Mahoning: 603————7. Lucas: 569———————–7. Stark: 632
8. Stark: 584——————8. Maryland: 512——————-8. New Jersey: 579
9. Lucas: 554—————–9. Hamilton: 504——————–9. Indiana: 536
10. Summit: 531————-10. Clermont: 466—————–10. Medina: 465
11. Highland: 499———–11. Stark: 466———————–11. Richland: 465
12. New Jersey: 497——-12. Arizona: 463——————–12. Fayette: 436
13. Hamilton: 483———–13. Alabama: 431——————-13. Trumbull: 404
14. New York: 419———-14. Trumbull: 401——————-14. Wayne: 383
15. Allen: 384—————-15. Mahoning: 387——————15. Erie: 368
16. Tennessee: 375——–16. Fayette: 354———————16. Clermont: 355
17. Logan: 328—————17. Washington (state): 353—–17. Illinois: 355
18. Trumbull: 325————18. Coshocton: 346—————-18. Massachusetts: 325
19. Coshocton: 310———19. Medina: 322——————–19. Allen: 320
20. Jefferson: 290———–20. Allen: 302————————20. Maryland: 294
21. Scioto: 259—————21. Erie: 290————————-21. Butler: 275
22. Belmont: 254————22. Highland: 270——————-22. Puerto Rico: 268
23. Huron: 245—————23. Puerto Rico: 265—————23. Lake: 267
24. Darke: 217—————24. Adams: 260———————24. West Virginia: 257
25. Lake: 212—————-25. Warren: 260———————25. Highland: 256
26. Tuscarawas: 202——-26. Massachusetts: 259———-26. Lorain: 249
27. Iowa: 200—————–27. Wayne: 259———————27. Mahoning: 244
28. Shelby: 199————–28. Morgan: 255——————–28. Adams: 226
29. Medina: 196————-29. Tuscarawas: 253————–29. Columbiana: 225
30. Massachusetts: 192—30. Ashtabula: 244—————–30. Arizona: 221

Top 30 Largest Net Domestic Out-Migration Destinations (Ohio counties and States)

2006-2010——————————-2009-2013—————————-2010-2014
1. Texas: -1371———————-1. Georgia: -1024—————-1. Florida: -1243
2. Knox: -942————————-2. Florida: -1013——————2. Georgia: -984
3. North Carolina: -782————3. Greene: -524——————-3. Knox: -608
4. Georgia: -718———————4. Missouri: -516——————4. Colorado: -456
5. Athens: -679———————-5. Colorado: -448—————–5. Minnesota: -405
6. Kentucky: -516——————-6. California: -436—————–6. California: -396
7. South Carolina: -499———–7. South Carolina: -431———-7. Greene: -382
8. California: -364——————-8. Knox: -418———————-8. Athens: -375
9. Florida: -360———————-9. North Carolina: -417———-9. Missouri: -348
10. Wood: -351———————10. Wisconsin: -395————–10. Utah: -325
11. Richland: -344——————11. Athens: -336——————11. Tennessee: -264
12. Greene: -239——————–12. Minnesota: -308————-12. Logan: -242
13. West Virginia: -236————13. Utah: -290———————13. Mississippi: -214
14. Missouri: -219——————-14. Richland: -266—————14. Wisconsin: -197
15. Crawford: -209——————15. Portage: -265—————–15. Oregon: -161
16. Hardin: -179———————16. Kentucky: -257—————16. Texas: -156
17. Noble: -177———————-17. Logan: -242——————-17. South Carolina: -144
18. Muskingum: -175—————18. Pennsylvania: -242———18. Seneca: -141
19. Butler: -173———————-19. Tennessee: -200————19. Louisiana: -140
20. Holmes: -163——————–20. Oregon: -187—————-20. Sandusky: -134
21. Marion: -138———————21. Wood: -166——————21. Wood: -134
22. Portage: -134——————-22. Sandusky: -157————–22. Darke: -109
23. Ottawa: -131——————–23. Mississippi: -151————-23. Jefferson: -103
24. Sandusky: -124—————-24. Jefferson: -127—————24. Noble: -98
25. Oregon: -120——————-25. Kansas: -98——————-25. Hardin: -96
26. Indiana: -116——————-26. Delaware (state): -88——-26. Idaho: -89
27. Idaho: -115———————27. Idaho: -74———————-27. Kansas: -81
28. Utah: -103———————- 28. Crawford: -73—————–28. Marion: -78
29. Fayette: -93———————29. Hardin: -68——————–29. Meigs: -70
30. Kansas: -90———————30. Seneca: -66——————-30. Ottawa: -67

Top 25 Largest Positive Swings Between 2006-2010 and 2010-2014
1. Texas: +1215
2. North Carolina: +808
3. Washington: +807
4. Kentucky: +675
5. Indiana: +652
6. Michigan: +580
7. West Virginia: +493
8. Athens: +369
9. Knox: +358
10. South Carolina: +355
11. Arizona: +288
12. Alaska: +283
13. Puerto Rico: +268
14. Illinois: +236
15. Hardin: +198
16. Marion: +187
17. Maine: +160
18. Alabama: +153
19. Logan: +149
20. Darke: +139
21. Massachusetts: +133
22. Rhode Island: +131
23. Wyoming: +127
24. Greene: +104
25. Champaign: +101

Top 25 Largest Negative Swings Between 2006-2010 and 2010-2014
1. Florida: -883
2. Tennessee: -639
3. Colorado: -619
4. Virginia: -595
5. Minnesota: -529
6. Maryland: -451
7. Lucas: -392
8. Montgomery: -384
9. New York: -308
10. Cuyahoga: -288
11. Muskingum: -276
12. Georgia: -266
13. Stark: -246
14. Utah: -222
15. Wisconsin: -215
16. Hamilton: -193
17. Scioto: -170
18. Miami: -154
19. Mississippi: -150
20. Clermont: -142
21. New Mexico: -140
22. Louisiana: -137
23. Mahoning: -131
24. Missouri: -129
25. Pennsylvania: -116

Total Counts By Period
Positive Ohio Counties
2006-2010: 53
2009-2013: 57
2010-2014: 53

Positive States, including DC and Puerto Rico
2006-2010: 21
2009-2013: 24
2010-2014: 29

Total Net In-Migration
Ohio
2006-2010: +8,008
2009-2013: +11,366
2010-2014: +10,101

Outside Ohio
2006-2010: -1,158
2009-2013: -466
2010-2014: +1,007

Ohio and Outside Ohio
2006-2010: +6,850
2009-2013: +10,900
2010-2014: +11,108

All these figures show that the Columbus metro has net positive domestic migration. While the majority of that comes from within the state, Columbus’ previously negative net total from outside the state has more recently become positive as well. Combined, the net total has been climbing. For a long time, Columbus’ relative success was not well-known outside of the state, but perhaps word is finally getting out.

Housing Trends of Columbus

***Originally Posted May 23, 2014, updated with 2014 data 9/18/2015 and again on 5/29/2016 with 2015 data***

I posted a graph recently showing housing permits for Franklin County to show how construction was trending. Today, I found more long-term data for both the city and county that continue to show some interesting trends.

First, let’s look at just the city of Columbus.

The chart above goes back through the mid-1990s. The first thing to notice is the housing boom from 1999-2002. Both single-family and multi-family construction was booming. The very good economic conditions, or seemingly good ones, during the 1999-2000 period is probably most responsible for this. What’s most interesting is that the boom seemed to last through at least part of the mild recession experienced in 2001-2002. After that, housing of both types started to decline through the late 2000s. This shows that construction in the city began to decline as early as 2002-2003, before the peak of the general housing boom in the mid-2000s.

Another interesting fact is at the end of the period. Multi-family units have recovered and are back in boom territory. This boom, however, is much different than the one that occurred more than a decade ago, as shown by the below chart.

During the 1999-2002 housing boom, multi-family housing averaged 59.3% of all the units constructed. In the current boom, which began in 2012, multi-family housing has averaged 81.4% of all the units constructed. The average difference between the types 1999-2002 was just 18.6 points. In the current boom, the difference is almost 63 points! In that regard, there really is no comparison between the housing boom a decade ago and the current one. Multi-family construction is in MUCH higher relative demand now than it was at any time in the last 20 years, including during the last housing boom.

But what does this tell us about where the housing is actually being constructed? Well, for that, we have to look at the entirety of Franklin County. Is the county also seeing a similar multi-family boom, or has single-family construction recovered there more than in the city?

This chart, in some aspects, is the opposite of the one for the city. While in the city, multi-family units consistently outnumbered single-family, the opposite is true for the county as a whole. This is likely because the county takes into account all the suburban areas, most of which are dominated by single-family housing. In only a few instances did multi-family housing units outnumber single-family before 2010. After 2010, it’s clear that the multi-family boom is hitting the rest of the county and not just Columbus itself. This may actually represent an even greater shift in housing construction. While it appeared that single-family construction was gradually rising since 2011, it once again fell off some in 2015 while multi-family went up. It appears that the new reality is, at least for now, holding steady.

Here’s the % of total chart for the county.

So it’s also clear that the county is seeing most of its construction in recent years be multi-family units.