2014 County Population Estimates



2014 county population estimates

New 2014 county population estimates were released Thursday by the Census. Franklin County had its 2nd highest growth year since 1970 and within a few years of passing Cuyahoga County to become the most populated in Ohio.

Top 25 Largest Ohio Counties and Rank for Census 2010, July 1, 2013 and July 1, 2014
2010———————————–2013—————————–2014

1. Cuyahoga: 1,280,122–1. Cuyahoga: 1,265,889–1. Cuyahoga: 1,259,828
2. Franklin: 1,163,414—–2. Franklin: 1,213,834——2. Franklin: 1,231,393
3. Hamilton: 802,374——3. Hamilton: 804,429——-3. Hamilton: 806,631
4. Summit: 541,781——–4. Summit: 541,787———4. Summit: 541,943
5. Montgomery: 535,153–5. Montgomery: 534,764–5. Montgomery: 533,116
6. Lucas: 441,815———-6. Lucas: 436,803———–6. Lucas: 435,286
7. Stark: 375,586———–7. Stark: 375,222————7. Stark: 375,736
8. Butler: 368,130———-8. Butler: 371,511————8. Butler: 374,158
9. Lorain: 301,356———-9. Lorain: 303,306———–9. Lorain: 304,216
10. Mahoning: 238,823—10. Mahoning: 234,336—-10. Mahoning: 233,204
11. Lake: 230,041———-11. Lake: 229,634———–11. Lake: 229,230
12. Warren: 212,693——-12. Warren: 219,578——-12. Warren: 221,659
13. Trumbull: 210,312—–13. Trumbull: 206,480——13. Trumbull: 205,175
14. Clermont: 197,363—–14. Clermont: 200,254—–14. Clermont: 201,560
15. Delaware: 174,214—-15. Delaware: 185,202—–15. Delaware: 189,113
16. Medina: 172,332——-16. Medina: 174,792——–16. Medina: 176,029
17. Licking: 166,492——–17. Licking: 168,503——–17. Licking: 169,390
18. Greene: 161,573——-18. Greene: 163,465——–18. Greene: 163,820
19. Portage: 161,419——-19. Portage: 161,423——-19. Portage: 161,882
20. Fairfield: 146,156——-20. Fairfield: 148,797——-20. Fairfield: 150,381
21. Clark: 138,333———-21. Clark: 136,803———–21. Clark: 136,554
22. Wood: 125,488———22. Wood: 129,209———-22. Wood: 129,590
23. Richland: 124,475—–23. Richland: 122,292——23. Richland: 121,942
24. Wayne: 114,520——-24. Wayne: 115,144———24. Wayne: 115,537
25. Columbiana: 107,841–25. Columbiana: 105,885–25. Columbiana: 105,686

Top 25 Counties with the Largest Numerical Growth, July 1, 2013 to July 1, 2014
1. Franklin: +17,559
2. Delaware: +3,911
3. Butler: +2,647
4. Hamilton: +2,202
5. Warren: +2,081
6. Fairfield: +1,584
7. Clermont: +1,306
8. Lorain: +1,210
9. Licking: +887
10. Madison: +646
11. Stark: +514
12. Miami: +484
13. Portage: +459
14. Pickaway: +410
15. Union: +396
16. Wayne: +393
17. Wood: +381
18. Greene: +355
19. Knox: +244
20. Holmes: +236
21. Geauga: +236
22. Athens: +198
23. Fulton: +162
24. Summit: +156
25. Muskingum: +122

Top 25 Counties with the Largest Numerical Growth, Census 2010 to July 1, 2014
1. Franklin: +67,850
2. Delaware: +14,924
3. Warren: +8,791
4. Butler: +6,028
5. Hamilton: +4,257
6. Fairfield: +4,229
7. Clermont: +4,197
8. Wood: +4,102
9. Medina: +3,696
10. Licking: +2,906
11. Lorain: +2,860
12. Greene: +2,251
13. Holmes: +1,532
14. Union: +1,509
15. Miami: +1,394
16. Pickaway: +1,178
17. Wayne: +1,023
18. Geauga: +885
19. Hancock: +555
20. Madison: +488
21. Portage: +461
22. Morrow: +325
23. Knox: +237
24. Tuscarawas: +206
25. Summit: +157

Top 25 Counties for Total Birth July 1, 2013 to July 1, 2014
1. Franklin: 18,595
2. Cuyahoga: 14,801
3. Hamilton: 11,009
4. Montgomery: 6,708
5. Summit: 6,235
6. Lucas: 5,742
7. Butler: 4,572
8. Stark: 4,106
9. Lorain: 3,340
10. Warren: 2,396
11. Mahoning: 2,369
12. Clermont: 2,357
13. Lake: 2,204
14. Delaware: 2,119
15. Trumbull: 2,070
16. Licking: 1,948
17. Greene: 1,757
18. Medina: 1,732
19. Fairfield: 1,647
20. Clark: 1,567
21. Wayne: 1,501
22. Richland: 1,413
23. Wood: 1,370
24. Portage: 1,369
25. Allen: 1,288

Top 25 Counties for Total Deaths July 1, 2013 to July 1, 2014
1. Cuyahoga: 13,316
2. Franklin: 9,197
3. Hamilton: 7,718
4. Montgomery: 5,632
5. Summit: 5,595
6. Lucas: 4,365
7. Stark: 3,910
8. Butler: 3,186
9. Mahoning: 2,957
10. Trumbull: 2,407
11. Lake: 2,366
12. Warren: 1,636
13. Clark: 1,631
14. Clermont: 1,574
15. Licking: 1,505
16. Medina: 1,352
17. Greene: 1,350
18. Portage: 1,329
19. Richland: 1,313
20. Fairfield: 1,233
21. Columbiana: 1,140
22. Ashtabula: 1,092
23. Allen: 1,063
24. Wayne: 1,055
25. Delaware: 1,019

Top 25 Counties for Total Natural Change (Births vs. Deaths) July 1, 2013 to July 1, 2014
1. Franklin: 9,398
2. Hamilton: 3,291
3. Cuyahoga: 1,481
4. Lucas: 1,377
5. Butler: 1,386
6. Delaware: 1,100
7. Montgomery: 1,076
8. Clermont: 783
9. Warren: 760
10. Summit: 640
11. Lorain: 546
12. Holmes: 506
13. Wayne: 446
14. Licking: 443
15. Fairfield: 414
16. Greene: 407
17. Medina: 380
18. Wood: 359
19. Union: 271
20. Hancock: 249
21. Allen: 225
22. Shelby: 212
23. Geauga: 199
24. Stark: 196
25. Huron: 165



Domestic Migration by State Report



domestic migration by state

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.

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.