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Family Demographics

 

[Note: Text that references rankings, charts, and data will be updated as work progresses on the 2020 Family Prosperity Index.]

 

The term “Demographic Winter” sounds ominous, and rightly so. A shrinking population is an omen of dire long-term economic conditions and the cascading consequences that accompany them. The Demographics major index measures population changes in the states and their impact on the potential for families and communities to thrive.

 

The economic effects of Demographic Winter will be akin to a slow-moving depression as a state—or the nation as a whole—shifts from population growth to population decline. When the population in a region is growing, businesses can plan on new customers simply because there will be more people.

 

But with a shrinking population, businesses lose the prospects of new customers, not to mention the customers they already have. If they are unable to find new markets, they will be faced with ongoing declines in revenue—or, put simply, an economic depression will result.

 

Demographic trends have already set the U.S. on a difficult economic path, Robert Arnott and Denis Chaves concluded after conducting an international analysis of demographics:

 

[W]e show that the past 60 years—which we think of as ‘normal’—enjoyed a demographic tailwind which we can quantify. It was worth about 1% per year, meaning that, if we think of 3% growth as normal, it’s really 2% growth plus a demographic tailwind of 1%.

 

The coming decades—due to the rising support ratios from the aging boomers—will experience a demographic headwind of (very roughly—these will be wildly out-of-sample conditions) roughly the same 1%. So, if 3% growth was normal, 1% growth (again, very roughly) becomes normal. This is the reason behind my concerns regarding the legacy of monetary and fiscal experiments, and debt and deficits we leave our children.[1]-[2]

 

Economists and others who study Demographic Winter usually assume that having fewer workers is its primary negative effect. But the consequences are much greater, according to a new study published by RAND, including slower growth in labor productivity and, in turn, lower economic growth:

 

We find that a 10% increase in the fraction of the population ages 60+ decreases the growth rate of GDP per capita by 5.5%. Two-thirds of the reduction is due to slower growth in the labor productivity of workers across the age distribution, while one-third arises from slower labor force growth. Our results imply annual GDP growth will slow by 1.2 percentage points this decade and 0.6 percentage points next decade due to population aging.[3]

 

Demographic Winter, apart from any other social or economic change, will cause the American economy to stall, giving it an even smaller margin for error: Minor economic hiccups will quickly send the economy into an actual recession or even depression.

 

Demographic Winter will have a negative fiscal impact on federal, state, and local governments. First, it will make recessions more likely and more severe, depressing tax revenue and increasing expectations for public spending.

 

Second, people over the age of 65, who are projected to become an even larger percentage of the population in coming years, impose significantly greater costs to government than younger age cohorts. A typical person over the age of 65 costs government nearly three times as much as a person under the age of 18—even with the costs of educating children factored in (Chart 19).[4]

 

The public costs of an older population, including Social Security and Medicare, fall predominantly on the federal government. But state governments are at risk, too. They should be prepared for a significant spike in Medicaid costs for those over the age of 65, especially for expenses associated with long-term care.[5]

 

Third, while government expenses soar for those over the age of 65, the taxes paid by an age cohort that reaches 65 drops by two-thirds (Chart 20).[6]   The major reason, not surprisingly, is that when people retire from the labor force, they stop receiving earned income that is subject to income and payroll taxes. As the country continues to age, policymakers will have to contend with an eroding income tax base.

 

Clearly, Demographic Winter will be the major economic and fiscal issue for the next few decades. Reversing it will not be an easy task. Of course, understanding why it is happening is the first step toward fixing it. To this end, let’s examine the steep drop in what scholars call the fertility rate, or the number of children the average woman gives birth to over her lifetime.

 

No single reason explains the drop in the fertility rate. Some of the more common explanations include:

 

There are now higher opportunity costs for bearing and rearing children: The mass entry of women into the workforce during and after World War II significantly boosted household incomes, which allowed for greater consumption—another car, a bigger home, more vacations, etc. Having a child became a material sacrifice.[7]

 

Abortion was made legal and “the pill” made contraception more effective:     Both technologies reduce the number of babies who are born, directly reducing the fertility rate.[8]

 

Americans have become less religious: Religious families have a higher fertility rate than non-religious families.[9]-[10]  And according to a recent study by the Pew Foundation, religiosity is in major decline in America. Between 2007 and 2014, the number of people who claim to be unaffiliated with any religion rose 41.6 percent from 16.1 percent to 22.8 percent.[11]

 

The U.S. population is concentrated in expensive urban areas: As more people moved to high-density cities, the cost of living, especially for housing, also increased. Families have responded to the higher prices for housing (less space for the dollar) by becoming smaller.[12]

 

Sexually transmitted diseases (STDs) often cause infertility: A 2004 report to Congress found that “more than 50% of all preventable infertility among women is a result of sexually transmitted diseases (STDs), primarily chlamydial infection and gonorrhea.”[13]
In 2014, there were 1,436,496 cases of chlamydia and another 348,179 cases of gonorrhea. Both can cause pelvic inflammatory disease that can then lead to infertility. The section in this report on family health will have more to say about the incidence and costs of STDs.

 

The average woman is having her first child later in life: According to the CDC:

...[T]he average age of first-time mothers increased by 1.4 years from 2000 to 2014, with most of the increase occurring from 2009 to 2014 . . . This trend and the more recent uptick in delayed initial childbearing can affect the number of children a typical woman will have in her lifetime, family size, and the overall population change in the United States.[14]

 

Some research shows that fertility, at least in the short run, can be positively influenced through large and relatively sudden increases in wealth. Most Americans derive their wealth from their home values. One study found that a $100,000 increase in housing wealth increased total fertility by 0.22 children (18.8 percent).[15] Another found that a $10,000 increase in housing prices leads to a 0.8 percent increase in fertility rates.[16]

 

The fertility rate of a given state can be affected by state-to-state migration. An economically thriving state will attract families looking for greener pastures, while a troubled state will lose them. Illinois, for example, has lost many of its residents to states such as Texas and Florida.[17] The net migration of families (incoming minus outgoing) is an important feedback mechanism that tells state leaders, political and otherwise, something about the social and economic health of their state.

 

As shown in Chart 21 and Table 3:

 

Percent of Population Under Age 18

 

The presence of children in a family represents confidence in the future, and the percent of the population under the age of 18 decreased nationally by 11 percent from 2000 to 2016, going from 25.7 percent to 22.8 percent (Chart 22). In 2016, Utah had the largest under-18 population at 30.3 percent, while Vermont had the lowest at 19 percent— or 63 percent of the Utah rate.[1]

 

Utah had the top score for the under-18 sub-index (10.00), followed by Texas (8.76). The next highest states were Idaho (8.46), South Dakota (8.05), and Alaska (7.93). Vermont had the lowest score (0.50). Other low-scoring states included New Hampshire (0.54), Maine (0.81), Rhode Island (1.33), and Massachusetts (1.94).

 

Percent of Population Over Age 65

 

While the prevalence of minor children has gone down, the percent of the population over the age of 65 increased nationally by 23 percent from 2000 to 2016, going from 12.4 percent to 15.2 percent (Chart 23). Florida had the highest over-65 population in 2016 at 19.8 percent, while Alaska had the lowest at 10.4 percent—or 53 percent of the Florida rate.[2]

 

Utah had the top score (9.79) for the over-65 sub-index, followed by Alaska (8.80). They were followed by Texas (8.51), North Dakota (7.12), and Georgia (7.02). Maine had the lowest score (1.26). Other low-scoring states included Florida (1.32), West Virginia (2.01), Vermont (2.28), and Montana (2.79).

 

Net Natural Population Change

 

The number of births and deaths interact to produce the net natural population change, and all three numbers vary over time and across states (Charts 24 through 26).[3]

 

The birth rate, or births as a percent of the population, declined from 1.41 percent in 2000 to 1.21 percent in 2017, a change of 14 percent (Chart 24). In 2016, the birth rate was highest in Utah, 1.66 percent, while New Hampshire had the lowest birth rate at 0.93 percent—or 56 percent of the Utah rate.

 

The death rate, or deaths as a percent of the population, slightly increased nationally from 2000 to 2017 (Chart 25). The increase was so small that the rate in both years was the same when it was rounded to two decimal points: 0.84 percent. West Virginia had the highest death rate in 2017 at 1.22 percent, while Utah had the lowest death rate at 0.53 percent—or 44 percent of the West Virginia rate.

 

States vary greatly in their net natural population growth rate (Chart 26). In 2017, Utah had the highest net natural growth rate at 1.12 percent, while West Virginia had the lowest net natural growth rate at -0.17 percent. Only one other state, Maine (-0.09 percent), had a negative net natural growth rate.

 

Utah had the top score (9.67) for the net natural population change sub-index, followed by Alaska (8.52), North Dakota (8.12), Texas (7.88), and Nebraska (7.17). West Virginia had the lowest score (1.15). Other low-scoring states included Maine (1.87), New Hampshire (2.87), Vermont (2.94), and Pennsylvania (3.14).

 

Note: The birth rate, death rate, and net natural population growth rate were weighted equally in the net natural population change sub-index.

 

Net Domestic Migration

 

States also varied greatly in domestic people migration, or the difference between how many people move in and how many move away (Chart 27).[4] In 2017, Idaho had the highest net in-migration at 1.43 percent, while Wyoming had the highest net out-migration at -1.49 percent.

 

Not surprisingly, states also varied greatly in domestic income migration, or amount of personal income coming into or leaving a state due to migration (Chart 28).[5] In 2015, Florida had the highest net in-migration at 3.3 percent, while Connecticut had the highest out-migration at -1.7 percent.

 

Idaho had the top score (9.40) for the net domestic migration sub-index, followed by Nevada (8.48), South Carolina (8.21), Oregon (8.01), and Florida (7.81). Wyoming had the lowest score (1.36). Other low-scoring states included North Dakota (1.44), Alaska (1.51), New York (2.29), and Illinois (2.49).

 

Note: The net people migration is worth 80 percent of the net domestic migration sub-index while the net income migration was worth 20 percent.

 

Fertility Rate

 

 

The fertility rate (births per 100 women between the ages of 15 and 44) declined from 65.9 in 2000 to 62.5 in 2015, a drop of 5 percent (Chart 29). In 2015, South Dakota had the highest fertility rate at 78.2, while Vermont had the lowest at 51.1— or 65 percent of the South Dakota rate.[6]

 

North Dakota had the top score for the fertility sub-index (10.00), followed by South Dakota (9.98), Alaska (9.02), Utah (8.48), and Nebraska (8.22). Massachusetts had the lowest score (0.73). Other low-scoring states included Vermont (0.96), Connecticut (1.05), New Hampshire (1.06), and Rhode Island (1.97).

 

Nationally, the fertility rate plummeted 47 percent (Chart 30) between 1960 (118) and 2015 (62.5). No state today has a fertility rate that the U.S. had even a few years ago. For example, South Dakota had the highest fertility rate (78.2) in 2015. But the last time the U.S. achieved this rate was between 1971 and 1972—a rate that was itself 34 percent lower than the 1960 U.S. rate. The fertility rate in Texas and Wyoming (70.2) is equivalent to the 1990 U.S. average, and Tennessee and Washington’s rate (62.8) is equivalent to the 2015 U.S. average.

 

There are the 24 states with fertility rates below the 2015 U.S. average, which puts them firmly in the midst of Demographic Winter. Vermont’s fertility rate is 18 percent below the U.S. average (51.1) and the lowest in the country.

 


[1]                    Population Estimates, U.S. Department of Commerce: Census Bureau

 

[2]                    Ibid.

 

[3]                    Ibid.

 

[4]                    Ibid.

 

[5]      Internal Revenue Service. https://www.irs.gov/uac/soi-tax-stats-migration-data

 

[6]      U.S. Department of Health and Human Services: Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System. https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf

 


[1]      Mauldin, John, “Mind the [Expectations] Gap: Demographic Trends and GDP,” Outside the Box, August 7, 2013. http://www.mauldineconomics.com/outsidethebox/mind-the-expectations-gap-demographic-trends-and-gdp

 

[2]      To read their full demographic analysis, see: Arnott, Robert D. and Chaves, Denis B., “Demographic Changes, Financial Markets, and the Economy,” Financial Analysts Journal, Vol. 68, No. 1. http://www.cfapubs.org/doi/pdf/10.2469/faj.v68.n1.4

 

[3]      Maestas, Nicole; Mullen, Kathleen J;, and Powell, David, “The Effect of Population Aging on Economic Growth, the Labor Force and Productivity,” Rand Corporation, July, 2016. http://www.rand.org/content/dam/rand/pubs/working_papers/WR1000/WR1063-1/RAND_WR1063-1.pdf

 

[4]      Edwards, Ryan and Lee, Ronald, “The Fiscal Impact of Population Aging in the US: Assessing the Uncertainties,” Center on the Economics and Demography of Aging, UC Berkeley, 2002. http://escholarship.org/uc/item/9480n177

 

[5]      Moses, Stephen A., “Cassandra’s Quandary: The Future of Long Term Care in New Hampshire,” Federalism In Action and Center for Long Term Care Reform, March 2016. http://graniteinstitute.org/application/files/3514/7802/8415/FIA-Cassandra-Quandry.pdf

 

[6]      Edwards, Ryan and Lee, Ronald, “The Fiscal Impact of Population Aging in the US: Assessing the Uncertainties,” Center on the Economics and Demography of Aging, UC Berkeley, 2002. http://escholarship.org/uc/item/9480n177

 

[7]      Bloom, David E.; Canning, David; Fink, Gunther; and Finlay, Jocelyn E., “Fertility, Female Labor Force Participation, and the Demographic Dividend,” National Bureau of Economic Research, Working Paper 13583, November 2007. http://www.nber.org/papers/w13583.pdf

 

[8]      Kane, Thomas J.; Levine, Phillip B.; Staiger, Douglas; and Zimmerman, David J., “Roe V. Wade and American Fertility,” National Bureau of Economic Research, Working Paper 5615, June 1996. http://www.nber.org/papers/w5615.pdf

 

[9]      Hayford, Sarah R. and Morgan, S. Philip, “Religiosity and Fertility in the United States: The Role of Fertility Intentions,” Soc Forces, 2008, Vol. 86, No. 3, pp. 1163-1188. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2723861/

 

[10]     Zhang, Lee, “Religious Affiliation, Religiosity, and Male and Female Fertility,” Max Planck Institute for Demographic Research, April 2008, Vol. 18, No. 8, pp. 233-262. http://www.demographic-research.org/volumes/vol18/8/18-8.pdf

 

[11]     Cooperman, Alan; Ritchey, Katherine; and Smith, Gregory, “America’s Changing Religious Landscape,” Pew Research Center, May 12, 2015. http://www.pewforum.org/files/2015/05/RLS-08-26-full-report.pdf

 

[12]     Cox, Wendell; Kotkin, Joel; Modarres, Ali; and Shroff, Anuradha, “The Rise of Post-Familialism: Humanity’s Future?” Civil Service College, Singapore, 2012. https://www.cscollege.gov.sg/Knowledge/Documents/CGL/The%20Rise%20of%20Post-Familialism.pdf

 

[13]     Gerberding, Julie Louise, “Report to Congress: Infertility and Prevention of Sexually Transmitted Diseases 2000 – 2003,” Centers for Disease Control and Prevention, November 2004. http://www.cdc.gov/std/infertility/ReportCongressInfertility.pdf

 

[14]     Hamilton, Brady E. and Matthews, T.J., “Mean Age of Mothers is on the Rise: United States, 2000-2014,” Centers for Disease Control and Prevention, NCHS Data Brief, No. 232, January 2016. http://www.cdc.gov/nchs/data/databriefs/db232.pdf

 

[15]     Lovenheim, Michael F. and Mumford, Kevin J., “Do Family Wealth Shocks Affect Fertility Choices? Evidence from the Housing Market,” Review of Economics and Statistics, Vol. 95, Issue 2, May 2013. http://www.krannert.purdue.edu/faculty/kjmumfor/papers/Wealth%20and%20Fertility.pdf

 

[16]     Dettling, Lisa J. and Kearney, Melissa S., “House Prices and Birth Rates: The Impact of the Real Estate Market on the Decision to Have a Baby,” Journal of Public Economics, Volume 110, February 2014, Pages 82-100. https://www.sciencedirect.com/science/article/pii/S0047272713001904

 

[17]     Moody, J. Scott and Warholik, Wendy P., “Policy Lessons from Illinois’ Exodus of People and Money,” Illinois Policy Institute, Special Report, July 2014. https://d2dv7hze646xr.cloudfront.net/wp-content/uploads/2014/07/Moody_out_migration1.pdf