Hi @TJ Walker,
Real estate prices follow secular trends. Just looking at how population varies every 10 years over the last 50 years gives a good idea of what will happen to a city in the next 20 years.
- large population decline will cause an increase in vacant housing stock. This put downward pressure on market prices and cause neighborhoods to decline.
- a rapid population increase will cause a shortage of housing, and this will tend to increase rents and prices.
We are not talking about identifying specific up and coming neighborhoods on their way to gentrification, this is very hard to do without being very familiar with a given neighborhood, but about painting the states with a very wide brush and see what cities are going to grow at a macro level.
## Statistical Areas defined for US Census
Analyzing commute routes to identify economic ties is not new. The USOMB (U.S. Office of Management and Budget) which gathers census statistics is using this technique for its definition of MSA ([Metropolitan Statistical Area](https://en.wikipedia.org/wiki/Metropolitan_statistical_area)) along similar lines. There are also Micropolitan Statistical Area, that define economically connected rural communities that do not have a large city as a nexus point
The MSA are then combined into CSA ([combined statistical areas](https://en.wikipedia.org/wiki/Combined_statistical_area#List_of_combined_statistical_areas)) as some criteria of economic interconnection are verified.
### Fastest Growing Combined Statistical Areas
There is much to say about a beautiful visualisation, and the CSA map does not look as attractive to the human eye as the above Mega-region map:
!(https://upload.wikimedia.org/wikipedia/commons/thumb/4/40/Combined_statistical_areas_of_the_United_States_and_Puerto_Rico_2013.gif/800px-Combined_statistical_areas_of_the_United_States_and_Puerto_Rico_2013.gif)
CSA population changes at a slower pace than their constituent MSA due to averaging, we show here the most dynamic CSA with a population above 500,000. The data was obtained from wikipedia in Dec 2016.
<!-- html table generated in R 3.2.0 by xtable 1.7-4 package -->
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<table>
<tr> <th> Rank </th> <th> Combined.Statistical.Area </th> <th> 2015 Estimate </th> <th>Cumulative Change </th> </tr>
<tr> <td> 1 </td> <td> Cape Coral-Fort Myers-Naples, FL </td> <td> 1,059,287 </td> <td> 12.66% </td> </tr>
<tr> <td> 2 </td> <td> Houston-The Woodlands, TX </td> <td> 6,855,069 </td> <td> 12.11% </td> </tr>
<tr> <td> 3 </td> <td> Orlando-Deltona-Daytona Beach, FL </td> <td> 3,129,308 </td> <td> 11.04% </td> </tr>
<tr> <td> 4 </td> <td> Raleigh-Durham-Chapel Hill, NC </td> <td> 2,117,103 </td> <td> 10.68% </td> </tr>
<tr> <td> 5 </td> <td> Denver-Aurora, CO </td> <td> 3,418,876 </td> <td> 10.61% </td> </tr>
<tr> <td> 6 </td> <td> Dallas-Fort Worth, TX-OK </td> <td> 7,504,362 </td> <td> 10.08% </td> </tr>
<tr> <td> 7 </td> <td> Nashville-Davidson?Murfreesboro, TN </td> <td> 1,951,644 </td> <td> 9.13% </td> </tr>
<tr> <td> 8 </td> <td> North Port-Sarasota-Bradenton, FL </td> <td> 977,491 </td> <td> 8.96% </td> </tr>
<tr> <td> 9 </td> <td> Charlotte-Concord, NC-SC </td> <td> 2,583,956 </td> <td> 8.77% </td> </tr>
<tr> <td> 10 </td> <td> Salt Lake City-Provo-Orem, UT </td> <td> 2,467,709 </td> <td> 8.63% </td> </tr>
<tr> <td> 11 </td> <td> McAllen-Edinburg, TX </td> <td> 906,099 </td> <td> 8.42% </td> </tr>
<tr> <td> 12 </td> <td> Boise City-Mountain Home-Ontario, ID-OR </td> <td> 756,061 </td> <td> 8.39% </td> </tr>
<tr> <td> 13 </td> <td> Des Moines-Ames-West Des Moines, IA </td> <td> 782,390 </td> <td> 8.32% </td> </tr>
<tr> <td> 14 </td> <td> Oklahoma City-Shawnee, OK </td> <td> 1,430,327 </td> <td> 8.16% </td> </tr>
<tr> <td> 15 </td> <td> Miami-Fort Lauderdale-Port St. Lucie, FL </td> <td> 6,654,565 </td> <td> 7.91% </td> </tr>
<tr> <td> 16 </td> <td> Atlanta-Athens-Clarke-Sandy Springs </td> <td> 6,365,108 </td> <td> 7.70% </td> </tr>
<tr> <td> 17 </td> <td> Seattle-Tacoma, WA </td> <td> 4,602,591 </td> <td> 7.67% </td> </tr>
<tr> <td> 18 </td> <td> Las Vegas-Henderson, NV-AZ </td> <td> 2,362,015 </td> <td> 7.59% </td> </tr>
<tr> <td> 19 </td> <td> Columbus-Auburn-Opelika, GA-AL </td> <td> 504,865 </td> <td> 7.57% </td> </tr>
<tr> <td> 20 </td> <td> Savannah-Hinesville-Statesboro, GA </td> <td> 532,048 </td> <td> 7.32% </td> </tr>
<tr> <td> 21 </td> <td> Jacksonville-St. Marys-Palatka, FL-GA </td> <td> 1,573,606 </td> <td> 7.01% </td> </tr>
<tr> <td> 22 </td> <td> San Jose-San Francisco-Oakland, CA </td> <td> 8,713,914 </td> <td> 6.87% </td> </tr>
<tr> <td> 23 </td> <td> Portland-Vancouver-Salem, OR-WA </td> <td> 3,110,906 </td> <td> 6.49% </td> </tr>
24 Washington-Baltimore-Arlington, DC-MD-VA-WV-PA 9,625,360 6.33%
<tr> <td> 25 </td> <td> New Orleans-Metairie-Hammond, LA-MS </td> <td> 1,493,205 </td> <td> 5.60% </td> </tr>
<tr> <td> 26 </td> <td> Omaha-Council Bluffs-Fremont, NE-IA </td> <td> 952,018 </td> <td> 5.54% </td> </tr>
<tr> <td> 27 </td> <td> Sacramento-Roseville, CA </td> <td> 2,544,026 </td> <td> 5.35% </td> </tr>
<tr> <td> 28 </td> <td> Lexington-Fayette Richmond Frankfort, KY </td> <td> 723,849 </td> <td> 5.34% </td> </tr>
<tr> <td> 29 </td> <td> Columbus-Marion-Zanesville, OH </td> <td> 2,424,831 </td> <td> 5.04% </td> </tr>
</table>
It should be noted that a 5 year evolution is enough to show a trend. For instance, New Orleans population rebounded following the 2005 [Katrina](https://en.wikipedia.org/wiki/Effects_of_Hurricane_Katrina_in_New_Orleans) disaster, so that the 2010-2015 evolution paints a much rosier picture than 2000-2010 would.
### Fastest Growing Metropolitan Statistical Areas
The MSA map looks as follow, these areas, though still very large show even more disparity in population evolution that CSA.
!(https://upload.wikimedia.org/wikipedia/commons/thumb/1/16/Metropolitan_and_Micropolitan_Statistical_Areas_%28CBSAs%29_of_the_United_States_and_Puerto_Rico%2C_Feb_2013.gif/800px-Metropolitan_and_Micropolitan_Statistical_Areas_%28CBSAs%29_of_the_United_States_and_Puerto_Rico%2C_Feb_2013.gif)
- iweblists gives [here](http://www.iweblists.com/us/population/MetropolitanStatisticalAreaPop.html) a list of the 100 largest ones with a convenient possibility to sort by population evolution from 2000 to 2010 census.
- wikipedia features a more complete [list](https://en.wikipedia.org/wiki/List_of_Metropolitan_Statistical_Areas#United_States) with all 382 areas.
Putting the data together allows to check that the long term trend is persistent, and get the top areas in the US:
<!-- html table generated in R 3.2.0 by xtable 1.7-4 package -->
<!-- Fri Dec 16 14:15:53 2016 -->
<table>
<tr> <th> Rank </th> <th> Metropolitan Statistical Area </th> <th> 2015 Estimate </th> <th> 2010-2015 yoy</th> <th> 2000-2010 yoy</th> <th> Cumul Change </th> </tr>
<tr> <td> 1 </td> <td> Austin-Round Rock-San Marcos, TX </td> <td> 2,000,860 </td> <td> 3.90% </td> <td> 2.83% </td> <td> 60.10% </td> </tr>
<tr> <td> 2 </td> <td> Raleigh-Cary, NC </td> <td> 1,273,568 </td> <td> 3.19% </td> <td> 3.17% </td> <td> 59.78% </td> </tr>
<tr> <td> 3 </td> <td> Cape Coral-Fort Myers, FL </td> <td> 701,982 </td> <td> 3.43% </td> <td> 3.01% </td> <td> 59.22% </td> </tr>
<tr> <td> 4 </td> <td> Greenville-Mauldin-Easley, SC </td> <td> 874,869 </td> <td> 6.97% </td> <td> 1.10% </td> <td> 56.24% </td> </tr>
<tr> <td> 5 </td> <td> Provo-Orem, UT </td> <td> 585,799 </td> <td> 1.61% </td> <td> 3.68% </td> <td> 55.48% </td> </tr>
<tr> <td> 6 </td> <td> Las Vegas-Paradise, NV </td> <td> 2,114,801 </td> <td> 2.54% </td> <td> 3.09% </td> <td> 53.72% </td> </tr>
<tr> <td> 7 </td> <td> McAllen-Edinburg-Mission, TX </td> <td> 842,304 </td> <td> 3.00% </td> <td> 2.47% </td> <td> 47.91% </td> </tr>
<tr> <td> 8 </td> <td> Boise City-Nampa, ID </td> <td> 676,909 </td> <td> 2.45% </td> <td> 2.58% </td> <td> 45.62% </td> </tr>
<tr> <td> 9 </td> <td> Ogden-Clearfield, UT </td> <td> 642,850 </td> <td> 3.88% </td> <td> 1.85% </td> <td> 45.23% </td> </tr>
<tr> <td> 10 </td> <td> Orlando-Kissimmee-Sanford, FL </td> <td> 2,387,138 </td> <td> 3.05% </td> <td> 2.25% </td> <td> 45.15% </td> </tr>
<tr> <td> 11 </td> <td> Houston-Sugar Land-Baytown, TX </td> <td> 6,656,947 </td> <td> 3.05% </td> <td> 1.96% </td> <td> 41.17% </td> </tr>
<tr> <td> 12 </td> <td> Phoenix-Mesa-Glendale, AZ </td> <td> 4,574,531 </td> <td> 1.33% </td> <td> 2.79% </td> <td> 40.67% </td> </tr>
<tr> <td> 13 </td> <td> Charlotte-Gastonia-Rock Hill, NC-SC </td> <td> 2,426,363 </td> <td> 1.82% </td> <td> 2.49% </td> <td> 39.99% </td> </tr>
<tr> <td> 14 </td> <td> Nashville-Davidson--Murfreesboro--Franklin, TN </td> <td> 1,830,345 </td> <td> 3.37% </td> <td> 1.69% </td> <td> 39.53% </td> </tr>
<tr> <td> 15 </td> <td> San Antonio-New Braunfels, TX </td> <td> 2,384,075 </td> <td> 3.25% </td> <td> 1.73% </td> <td> 39.28% </td> </tr>
<tr> <td> 16 </td> <td> Riverside-San Bernardino-Ontario, CA </td> <td> 4,489,159 </td> <td> 1.75% </td> <td> 2.37% </td> <td> 37.92% </td> </tr>
<tr> <td> 17 </td> <td> Dallas-Fort Worth-Arlington, TX </td> <td> 7,102,796 </td> <td> 2.43% </td> <td> 2.01% </td> <td> 37.61% </td> </tr>
<tr> <td> 18 </td> <td> Charleston-North Charleston-Summerville, SC </td> <td> 744,526 </td> <td> 2.93% </td> <td> 1.62% </td> <td> 35.61% </td> </tr>
<tr> <td> 19 </td> <td> Atlanta-Sandy Springs-Marietta, GA </td> <td> 5,710,795 </td> <td> 1.21% </td> <td> 2.38% </td> <td> 34.44% </td> </tr>
<tr> <td> 20 </td> <td> Lakeland-Winter Haven, FL </td> <td> 650,092 </td> <td> 2.29% </td> <td> 1.84% </td> <td> 34.34% </td> </tr>
<tr> <td> 21 </td> <td> Bakersfield-Delano, CA </td> <td> 882,176 </td> <td> 1.96% </td> <td> 1.92% </td> <td> 33.33% </td> </tr>
<tr> <td> 22 </td> <td> Indianapolis-Carmel, IN </td> <td> 1,988,817 </td> <td> 3.00% </td> <td> 1.18% </td> <td> 30.41% </td> </tr>
<tr> <td> 23 </td> <td> North Port-Bradenton-Sarasota, FL </td> <td> 768,918 </td> <td> 2.25% </td> <td> 1.55% </td> <td> 30.33% </td> </tr>
<tr> <td> 24 </td> <td> Colorado Springs, CO </td> <td> 697,856 </td> <td> 2.47% </td> <td> 1.40% </td> <td> 29.84% </td> </tr>
<tr> <td> 25 </td> <td> Des Moines-West Des Moines, IA </td> <td> 622,899 </td> <td> 2.29% </td> <td> 1.46% </td> <td> 29.39% </td> </tr>
<tr> <td> 26 </td> <td> Denver-Aurora-Broomfield, CO </td> <td> 2,814,330 </td> <td> 2.34% </td> <td> 1.41% </td> <td> 29.14% </td> </tr>
<tr> <td> 27 </td> <td> Jacksonville, FL </td> <td> 1,449,481 </td> <td> 1.99% </td> <td> 1.58% </td> <td> 29.10% </td> </tr>
<tr> <td> 28 </td> <td> Stockton, CA </td> <td> 726,106 </td> <td> 1.55% </td> <td> 1.78% </td> <td> 28.83% </td> </tr>
<tr> <td> 29 </td> <td> Madison, WI </td> <td> 641,385 </td> <td> 2.70% </td> <td> 1.13% </td> <td> 27.82% </td> </tr>
30 Washington-Arlington-Alexandria, DC-VA-MD-WV 6,097,684 2.62% 1.11% 27.14%
<tr> <td> 31 </td> <td> Sacramento--Arden-Arcade--Roseville, CA </td> <td> 2,274,194 </td> <td> 1.51% </td> <td> 1.62% </td> <td> 26.57% </td> </tr>
<tr> <td> 32 </td> <td> Columbia, SC </td> <td> 810,068 </td> <td> 2.16% </td> <td> 1.18% </td> <td> 25.17% </td> </tr>
<tr> <td> 33 </td> <td> Tampa-St. Petersburg-Clearwater, FL </td> <td> 2,975,225 </td> <td> 1.71% </td> <td> 1.33% </td> <td> 24.17% </td> </tr>
<tr> <td> 34 </td> <td> Oklahoma City, OK </td> <td> 1,358,452 </td> <td> 2.41% </td> <td> 0.97% </td> <td> 24.01% </td> </tr>
<tr> <td> 35 </td> <td> Portland-Vancouver-Hillsboro, OR-WA </td> <td> 2,389,228 </td> <td> 1.60% </td> <td> 1.36% </td> <td> 23.93% </td> </tr>
<tr> <td> 36 </td> <td> Seattle-Tacoma-Bellevue, WA </td> <td> 3,733,580 </td> <td> 2.22% </td> <td> 0.95% </td> <td> 22.66% </td> </tr>
<tr> <td> 37 </td> <td> Salt Lake City, UT </td> <td> 1,170,266 </td> <td> 0.96% </td> <td> 1.42% </td> <td> 20.79% </td> </tr>
</table>