Where Will U.S. Population Growth Occur? A Glimpse at 2020 and 2030 By Dr. Peter Linneman, NAI Global Chief Economist Linneman Associates believes that the confluence of strengthening macroeconomic and real estate fundamentals has created select investment opportunities in the U.S. commercial real estate sector. The delayed recovery to date has created a prolonged opportunistic investment period for well-capitalized investors. However, given varying stages of recovery by region and asset quality, investors must be highly selective.
Where Will U.S. Population Growth Occur? A Glimpse at 2020 and 2030 By Dr. Peter Linneman, NAI Global Chief Economist Impact on Population Share Change 1990-2010 (Basis Point) Population change 1980-1990 +100bp 0.03 Population share change 1980-1990 +100bp 46.95 Share foreign-born in 1990 +100bp 0.26 % with bachelor's degree or higher in 1990 +100bp 0.09 % with less than a high school diploma in 1990 +100bp -0.13 % white in 1990 +100bp -0.05 % over 65 years old in 1990 +100bp -0.22 % under 25 years old in 1990 +100bp -0.32 Income tax per capita / Income per capita in 1990 +100bp -0.72 Sales tax per capita / Income per capita in 1990 +100bp 0.33 Presidential election vote over 55% Republican in 1992 If Yes 0.67 Presidential election vote below 45% Republican in 1992 If Yes 2.82 All state senators Republican in 1990 If Yes 0.83 All state senators Democrat in 1990 If Yes 0.43 Average precipitation +1% -0.03 January average temperature +1% 0.02 average January sun days +1% -0.02 Share housing older than 30 years in 1990 +100bp -0.19 Share housing newer than 11 years in 1990 +100bp -0.04 County borders an ocean or a Great Lake If Yes -1.95 Hills or mountains in county If Yes -0.28 Northeast If Yes 0.96 South If Yes -1.07 West If Yes -5.96 Observations 1159.00 Adj R-squared 0.71 Source: Linneman Associates Despite being 5 full years into economic recovery, we believe that we are still only in the 3rd or 4th inning of the growth cycle. It is important to note that the 2008-2009 recession was far deeper than all other post-world War II recessions, with a loss of 8.7 million jobs or 6.2% of the U.S. job base. In comparison, the super recessions of 1973-1975 and 1980-1982 only saw job losses of 1.3 million (1.6%) and 2 million (2.2%), respectively, and recovered all lost jobs within 9-10 months. This time, it took 5 full years from the official end of the recession to recover all of the 8.7 million jobs lost. Thus, we are back to where we started at the beginning of the recession at year-end 2007, but the population has grown by 16 million. As a result, the U.S. still has tremendous growth potential due to pent-up demand associated with housing, automobiles, and other durable goods - this is in addition to new growth going forward. In 2006, Peter Linneman and Albert Saiz co-authored a study in which they forecasted U.S. population by county and metropolitan statistical area (MSA) through 2020. With the release of 2010 Census data, Linneman Associates has since updated and extended population forecasts through 2030. Our analysis employs historical population data for 1,161 counties and 381 metropolitan statistical are as (MSAs). MSA definitions are those published in February 2013 by the Census Bureau. Our revised 2020 population forecasts are based on changes in population and other variables from 2000 to 2010, while the 2030 forecasts are based on changes between 1990 and 2010. MSA population as a percent of the total U.S. population is the dependent variable in our analysis, while local factors such as the share of foreign-born residents, educational attainment, race and age share percentages, taxes
Large cities tend to be attractive because of their concentrations of businesses, culture, entertainment, transportation infrastructure, education, etc. per capita, voting trends, political party representation, weather characteristics, age of housing stock, proximity to an ocean or Great Lake, and geographic region are independent variables. We do not directly forecast U.S. population growth, but rather overlay our estimates of local population share of the total U.S. population with the U.S. Census forecasts of total U.S. population in 2020 and 2030 to obtain local population estimates. County forecasts are then aggregated at the MSA level. Between 2000 and 2013, the Houston, Dallas, and Atlanta MSAs registered the greatest absolute population growth. We find that the single most important factor in determining future population growth is past growth. In fact, past growth accounts for 69% of the forces driving the 2030 forecasts. Many factors create a county s attractiveness, but even if underlying conditions change noticeably, reputation and growth may lag. Agglomeration economies occur as firms cluster in a location and share a large pool of input resources, resulting in an increased efficiency, greater innovation, and declining costs. Large cities tend to be attractive because of their concentrations of businesses, culture, entertainment, transportation infrastructure, education, etc. Additional factors that influence population growth are diversity, education levels, race, age, taxes, weather characteristics, age of housing stock, geographic location, regulations, and politics. Our research reveals that more diverse local economies experience greater Largest Absolute Growth Largest Percent Growth Metropolitan Statistical Area Change in Population Metropolitan Statistical Area CAGR (%) Houston-Sugar Land-Baytown, TX 1,619,997 The Villages, FL 5.5 Dallas-Fort Worth-Arlington, TX 1,606,787 St. George, UT 3.9 Atlanta-Sandy Springs-Roswell, GA 1,259,504 Raleigh-Cary, NC 3.3 Phoenix-Mesa-Scottsdale, AZ 1,146,886 Austin-Round Rock-San Marcos, TX 3.2 Riverside-San Bernardino-Ontario, CA 1,126,057 Myrtle Beach-Conway-North Myrtle Beach, SC-NC 3.2 Washington-Arlington-Alexandria, DC-VA-MD-WV 1,112,431 Cape Coral-Fort Myers, FL 3.2 New York-Newark-Jersey City, NY-NJ-PA 1,004,983 Provo-Orem, UT 3.1 Miami-Fort Lauderdale-Pompano Beach, FL 820,627 Greeley, CO 3.1 Los Angeles-Long Beach-Santa Ana, CA 765,804 Las Vegas-Henderson-Paradise, NV 3.0 Las Vegas-Henderson-Paradise, NV 652,103 Bend-Redmond, OR 2.8 Austin-Round Rock-San Marcos, TX 633,288 McAllen-Edinburg-Mission, TX 2.8 Orlando-Kissimmee-Sanford, FL 623,285 Fayetteville-Springdale-Rogers, AR-MO 2.7 Charlotte-Concord-Gastonia, NC-SC 617,986 Kennewick-Pasco-Richland, WA 2.7 Seattle-Tacoma-Bellevue, WA 566,227 Hilton Head Island-Bluffton-Beaufort, SC 2.6 San Antonio-New Braunfels, TX 565,847 Boise City-Nampa, ID 2.6 Denver-Aurora-Lakewood, CO 539,720 Daphne-Fairhope-Foley, AL 2.6 Tampa-St. Petersburg-Clearwater, FL 474,572 Orlando-Kissimmee-Sanford, FL 2.5 Chicago-Naperville-Elgin, IL-IN-WI 438,973 Port St. Lucie, FL 2.5 Minneapolis-St. Paul-Bloomington, MN-WI 427,228 Charlotte-Concord-Gastonia, NC-SC 2.4 Sacramento--Arden-Arcade--Roseville, CA 418,913 Laredo, TX 2.4 Raleigh-Cary, NC 417,445 Phoenix-Mesa-Scottsdale, AZ 2.4 San Diego-Carlsbad-San Marcos, CA 397,419 Naples-Immokalee-Marco Island, FL 2.3 San Francisco-Oakland-Hayward, CA 392,536 Gainesville, GA 2.3 Portland-Vancouver-Hillsboro, OR-WA 386,673 Riverside-San Bernardino-Ontario, CA 2.3 Nashville-Davidson--Murfreesboro--Franklin, TN 376,625 Houston-Sugar Land-Baytown, TX 2.3 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 347,531 Dover, DE 2.3 Indianapolis-Carmel-Anderson, IN 295,499 Wilmington, NC 2.2 Boston-Cambridge-Quincy, MA-NH 292,955 San Antonio-New Braunfels, TX 2.2 Columbus, OH 292,053 Coeur d'alene, ID 2.2 Jacksonville, FL 271,874 Auburn-Opelika, AL 2.1 McAllen-Edinburg-Mission, TX 246,533 Idaho Falls, ID 2.1 Kansas City, MO-KS 243,219 Lake Havasu City-Kingman, AZ 2.1 Oklahoma City, OK 224,256 Dallas-Fort Worth-Arlington, TX 2.1 Cape Coral-Fort Myers, FL 220,227 Bakersfield-Delano, CA 2.1 Baltimore-Columbia-Towson, MD 217,744 Ocala, FL 2.1 Bakersfield-Delano, CA 202,479 Greenville, NC 2.1 Salt Lake City, UT 201,361 Sioux Falls, SD 2.0 Richmond, VA 190,081 Midland, TX 2.0 Provo-Orem, UT 185,465 Charleston-North Charleston-Summerville, SC 2.0 Boise City-Nampa, ID 185,448 Atlanta-Sandy Springs-Roswell, GA 2.0 Source: U.S. Census Bureau, Linneman Associates CAGR = Compounded annual growth rate Historical MSA Population Growth (2000-2013) growth, because it will be less likely for the area to be calcified by the social and political control of a single industry constituency. This is exemplified by Houston, which has boomed as it transformed from a pure play oil city to a more diversified economy, while New Orleans remained tied to the oil industry and stagnated. Locating in areas where young workers want to live has become increasingly important to innovation and growth. Our research underscores that areas with highly educated workers grow more rapidly, while those with high levels
of unemployment and high school dropout rates grow more slowly. Our research also reveals that immigrants, a great source of growth, tend to move to where immigrants already represent a large portion of the population. Additionally, education and age distribution are important indicators. Areas with prosperous industries offer more and better job opportunities, and therefore attract those with higher education attainment. Fertility rates are high and mortality rates are low for the 25-65-yearold population, hence the importance of this age cohort in population growth. People also clearly prefer to live near better schools. This factor, however, is becoming somewhat less important as the proportion of childless households grows. This may bode well for central city areas but should not mask the fact that good schools remain an important growth determinant. Metropolitan Statistical Area To assess the impact of local taxes, we examined income and sales tax data from the Annual Surveys of State & Local Government Finance. We found that higher tax rates reduce a county s attractiveness to residents and businesses, all else being equal. However, higher taxes may reflect better public services, like schools, public transportation, police service, and emergency response systems. We find that the local income tax has a negative impact on population growth, but only at 75% confidence level. The effect of the local sales tax is even weaker. Our research shows that, in today s world, both firms and individuals are too competitive and mobile to be captured by high tax communities. In fact, more local government spending Absolute Growth Change in Population Metropolitan Statistical Area CAGR (%) Atlanta-Sandy Springs-Roswell, GA 2,517,921 Walla Walla, WA 6.3 Washington-Arlington-Alexandria, DC-VA-MD-WV 2,097,882 Hinesville-Fort Stewart, GA 5.7 Dallas-Fort Worth-Arlington, TX 1,719,465 Carson City, NV 5.4 New York-Newark-Jersey City, NY-NJ-PA 1,541,427 Valdosta, GA 5.2 Houston-Sugar Land-Baytown, TX 1,275,241 Rapid City, SD 5.2 Chicago-Naperville-Elgin, IL-IN-WI 897,409 Charlottesville, VA 5.1 Riverside-San Bernardino-Ontario, CA 871,873 Lewiston, ID-WA 5.0 Minneapolis-St. Paul-Bloomington, MN-WI 862,641 Brunswick, GA 5.0 Richmond, VA 852,159 Albany, GA 4.7 San Antonio-New Braunfels, TX 819,441 Wenatchee-East Wenatchee, WA 4.5 Phoenix-Mesa-Scottsdale, AZ 807,050 Athens-Clarke County, GA 4.4 Charlotte-Concord-Gastonia, NC-SC 797,544 Winchester, VA-WV 4.2 Nashville-Davidson--Murfreesboro--Franklin, TN 784,256 Bismarck, ND 4.0 Denver-Aurora-Lakewood, CO 762,012 Macon, GA 4.0 Virginia Beach-Norfolk-Newport News, VA-NC 749,353 Idaho Falls, ID 3.9 Austin-Round Rock-San Marcos, TX 671,833 Pine Bluff, AR 3.7 Indianapolis-Carmel-Anderson, IN 618,639 Kennewick-Pasco-Richland, WA 3.7 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 618,415 Grand Island, NE 3.7 Kansas City, MO-KS 615,817 Hattiesburg, MS 3.7 Orlando-Kissimmee-Sanford, FL 605,308 The Villages, FL 3.7 St. Louis, MO-IL 593,308 Amarillo, TX 3.6 Las Vegas-Henderson-Paradise, NV 562,488 Warner Robins, GA 3.6 Cincinnati, OH-KY-IN 543,422 Jefferson City, MO 3.5 Columbus, OH 539,662 Victoria, TX 3.5 Louisville-Jefferson County, KY-IN 510,400 St. George, UT 3.4 Sacramento--Arden-Arcade--Roseville, CA 484,669 Hilton Head Island-Bluffton-Beaufort, SC 3.4 Memphis, TN-MS-AR 467,341 Dalton, GA 3.4 Portland-Vancouver-Hillsboro, OR-WA 458,430 College Station-Bryan, TX 3.3 Miami-Fort Lauderdale-Pompano Beach, FL 457,228 New Bern, NC 3.3 Baton Rouge, LA 446,268 Manhattan, KS 3.3 Raleigh-Cary, NC 412,394 El Centro, CA 3.2 Tampa-St. Petersburg-Clearwater, FL 411,025 Ithaca, NY 3.2 Seattle-Tacoma-Bellevue, WA 399,936 Burlington-South Burlington, VT 3.2 Oklahoma City, OK 394,100 Bend-Redmond, OR 3.2 Jacksonville, FL 394,058 Yuma, AZ 3.2 Boise City-Nampa, ID 392,550 Wichita Falls, TX 3.2 Baltimore-Columbia-Towson, MD 389,665 Parkersburg-Vienna, WV 3.2 Albuquerque, NM 389,228 Bowling Green, KY 3.2 San Francisco-Oakland-Hayward, CA 378,597 Sioux Falls, SD 3.2 Columbia, SC 374,822 Morristown, TN 3.1 Source: U.S. Census Bureau, Linneman Associates CAGR = Compounded annual growth rate MSA Population Forecasts 2013-2030 Percent Growth always leads to less growth unless this spending is on highways. However, politicians refuse to grasp the simple message that high taxes are the death knell for long-term growth. Not surprisingly, weather and geographic characteristics are strong predictors of population growth. Americans, both retirees and workers, have clearly demonstrated a preference for warm, dry locations over the last 35 years by moving en masse to the Sun Belt. A large stock of
Not surprisingly, weather and geographic characteristics are strong predictors of population growth. Metropolitan Statistical Area Absolute Growth Change in Population Metropolitan Statistical Area CAGR (%) Urban Honolulu, HI -30,222 Grand Forks, ND-MN -0.8 Anchorage, AK -15,321 Anchorage, AK -0.2 Grand Forks, ND-MN -12,523 Kahului-Wailuku-Lahaina, HI -0.2 Kahului-Wailuku-Lahaina, HI -5,368 Urban Honolulu, HI -0.2 Fairbanks, AK -2,855 Fairbanks, AK -0.2 Muncie, IN 738 Muncie, IN 0.0 Springfield, OH 1,429 Springfield, OH 0.1 Williamsport, PA 4,244 Los Angeles-Long Beach-Santa Ana, CA 0.1 Danville, IL 6,634 Buffalo-Cheektowaga-Niagara Falls, NY 0.1 Johnstown, PA 7,523 Williamsport, PA 0.2 Lima, OH 9,437 Detroit-Warren-Dearborn, MI 0.2 Decatur, IL 9,968 Pittsburgh, PA 0.3 Bay City, MI 10,923 Johnstown, PA 0.3 Cumberland, MD-WV 11,525 San Diego-Carlsbad-San Marcos, CA 0.3 Waterloo-Cedar Falls, IA 11,643 Bridgeport-Stamford-Norwalk, CT 0.3 Longview, WA 12,788 Mobile, AL 0.4 Great Falls, MT 13,301 Dayton, OH 0.4 Lewiston-Auburn, ME 13,658 Cleveland-Elyria-Mentor, OH 0.4 Bangor, ME 14,162 Boston-Cambridge-Quincy, MA-NH 0.4 Mansfield, OH 14,625 Waterloo-Cedar Falls, IA 0.4 Altoona, PA 15,529 New Haven-Milford, CT 0.4 Elmira, NY 17,533 New York-Newark-Jersey City, NY-NJ-PA 0.4 Niles-Benton Harbor, MI 17,627 Miami-Fort Lauderdale-Pompano Beach, FL 0.4 Kokomo, IN 18,435 Danville, IL 0.5 Gadsden, AL 20,135 San Francisco-Oakland-Hayward, CA 0.5 Battle Creek, MI 20,335 Toledo, OH 0.5 Weirton-Steubenville, WV-OH 20,405 Lima, OH 0.5 Dubuque, IA 20,645 Canton-Massillon, OH 0.5 Beckley, WV 21,188 Utica-Rome, NY 0.5 Sheboygan, WI 21,885 Decatur, IL 0.5 Pittsfield, MA 22,115 Scranton--Wilkes-Barre--Hazleton, PA 0.5 Racine, WI 23,208 Erie, PA 0.5 Michigan City-La Porte, IN 23,512 Bangor, ME 0.5 Buffalo-Cheektowaga-Niagara Falls, NY 24,405 Chicago-Naperville-Elgin, IL-IN-WI 0.5 Ocean City, NJ 24,539 Youngstown-Warren-Boardman, OH-PA 0.5 Lebanon, PA 25,186 San Jose-Sunnyvale-Santa Clara, CA 0.5 Erie, PA 25,759 Santa Rosa-Petaluma, CA 0.5 Mobile, AL 25,870 Duluth, MN-WI 0.5 Wausau, WI 26,036 Flint, MI 0.6 Albany, OR 26,614 Bay City, MI 0.6 Source: U.S. Census Bureau, Linneman Associates CAGR = Compounded annual growth rate MSA Population Forecasts 2013-2030 Percent Growth old housing negatively affects population share change. A high percentage of old housing may indicate relatively less business activity and development in recent years as well as lower quality housing. In contrast, areas with a good transportation infrastructure, newer housing, and more open space tend to attract growth. The major problem faced by many central cities is that their housing stocks are not what people desire today.. In contrast to our original research, countries that border Atlantic, Pacific Ocean, and Great Lakes experience slower population growth on average compared to inland counties after controlling for other factors. This phenomenon most likely reflects greater regulatory opposition to growth in coastal areas which has resulted in high home prices, muting the latent desire to live in these areas. That is, if approvals for the necessary housing and workspace to accommodate growth are difficult, expensive, and uncertain, latent growth is diverted elsewhere. For example, there is little doubt that a beautiful city such as San Francisco would exhibit lower growth than expected over the past 25 if not for stringent regulations, since its location has highly desirable attributes such as fair weather, lively culture, and strong economy. Political affiliations generally do not impact population growth. However, our research reveals that a key to growth is a competitive political environment. Areas dominated by a single party (either Democrats or Republicans) tend to grow more slowly than communities where political control is tenuous. Thus, political competition, similar to economic competition, fuels growth. Wild cards for growth are unforeseen factors such as the Cuban immigration wave or the presence of an extraordinarily successful entrepreneur who generates massive job opportunities, such as Bill Gates in Seattle. What will be the wild cards over the next 20 years? No one can know, but our research indicates that they will explain as much as a third of the variation in growth across U.S.
Percent Thousands 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 3,000 2,500 2,000 1,500 1,000 500 0 Total Population Growth Per Year 0.97 0.96 0.93 0.95 0.93 0.88 0.83 0.73 0.74 0.72 0.70 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 722 Household Formations Per Year 1,627 1,343 1,041 772 398 357 2,389 1,157 1,375 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Estimated Land Absorption Through 2030 Estimated population growth 42,000,000 People per U.S. Household 2.6 Estimated household growth 16,153,846 City HH/Acre Est. Required Acres Philadelphia 6.8 2,388,228 Miami 6.6 2,454,874 Los Angeles 4.4 3,677,212 Atlanta 2.1 7,690,142 Phoenix 1.6 10,348,856 Looking Forward. Over the past 20 years through 2013, the U.S. population has grown by about 56 million people and 26 million households. While the U.S. population growth rate has slowed from 1% to about 0.75% per year, consistently positive growth is a major distinguishing feature of the U.S. economy relative to other developed economies. In 2013, the total U.S. population was estimated at 316 million, while the Census Bureau projects populations of 334 million and 358 million for 2020 and 2030, respectively, for compounded annual growth rates of 0.78 and 0.74%. To put these figures in perspective, over the next 17 years, the U.S. will add the combined population of the Berlin, London, Paris, Madrid, and Beijing, or nearly 18.6 million households. It is this growth that fuels U.S. real estate development. As illustrated in Figure [2020 and 2030 Population Table 4], the projected population increase will require significant real estate development. For example, if this new population lives with the density of the Philadelphia MSA, this population growth of 42 million will require nearly 2.4 million acres of new development. We estimate that of this required land, more than 60% will be for residential use, with the remainder for office, retail, industrial, hotel, institutional and infrastructure, and open space. Figure [2020 and 2030 Population-Table 2] reveals that Atlanta, Washington, D.C., and Dallas, MSAs lead the pack in our 2030 population growth forecasts (versus 2013) on an absolute level, while Walla Walla, WA; Hinesville, GA; and Carson City, WV show the strongest percentage growth through 2030. Combined, the top 10 percentage growth markets are expected to add only 1.5 million new people through 2030, while the top 10 absolute growth markets will increase in population by 13.5 million on an aggregate basis through 2030.
In the end, future growth will be driven by a community s openness to change and competitive political environment. Of those, Richmond (68.4%), Atlanta (45.6%), and San Antonio (36%) have the highest projected percentage growth over the 17-year period. The aggregate sample population (212.6 million) in our statistical analysis represents about 67.3% of the total 2013 population of 316.1 million. We project that the sample urban population will experience a net increase of 61.5 million people, or about 29%, by 2030. Conclusion. Real median household income is estimated at just under $53,000 in May 2014. If it grows by 2% per year through 2030, it will be roughly 40% higher rising to roughly $74,000. This real income increase means greater demand for amenities, such as gadgets, travel, and cosmetic surgery. It also means that the outdated housing stock will have an even harder time competing for these households. Similarly, if real wealth grows by approximately 40%, to over $940,000 per household by 2030, individuals will own homes and retire far sooner and more comfortably than ever before. With their unprecedented wealth, boomers will desire easyto-navigate, warm, and safe communities with access to the best medical facilities. Ultimately, higher real incomes and real wealth will increase the latent demand to live in the most desirable areas. Aging Echo workers will increasingly work in the healthcare and service sectors and will choose to live in places that are attractive. As they delay marriages and parenthood longer than any previous generation, they will desire urban, social environments. Firms will produce where the talent desires to live. This is often confused with areas with universities. While great universities are obviously very important, the best young talents tend to migrate to wherever there are the best job networks and excitement after graduation. Many firms in industries such as healthcare and airlines will expand to the Sun Belt to be near their customer base. In the end, future growth will be driven by a community s openness to change and a competitive political environment. Those areas that have grown over the past 20 years (controlling for the factors we have discussed above) will continue to grow because of their openness to growth. Despite surpassing its previous high, the U.S. economy continues to be far below its long-term trend, with real GDP nearly $2.3 trillion (13.5% of GDP) below trend. This gap represents a loss of $7,140 per capita, and surpasses the GDPs of Russia, Italy, and Brazil, and approaches the GDPs of the U.K. and France. That is, the gap is now greater than all but the top six largest economies in the world. And while real GDP and real GDP per capita are now at their highest levels in history, they remain about a standard deviation below trend. With pent-up demand on top of new population growth, the potential to close the GDP gap is concentrated in the housing, automobile, and durable goods sectors. This will translate into demand for both residential (seniors, student, multifamily, and single family)and commercial real estate (retail, industrial, office, lodging, and selfstorage). naiglobal.com