2017 Family Prosperity Index Demographics

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  1. Introduction
  2. Economics
  3. Family Self-Sufficiency
  4. Family Structure
  5. Family Culture
  6. Family Health

DEMOGRAPHICS

The term “Demographic Winter” sounds ominous, and rightly so. Shrinking population levels in certain regions of the country portend 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.

Economically, 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. With a growing population, businesses can plan on new customers simply because there are more people.

However, with a shrinking population, businesses not only lose the prospects of new customers, they must also face losing existing customers. If businesses are unable to find new markets, they will be faced with ongoing declines in revenue—or, put simply, an economic depression.

More specifically, researchers Robert Arnott and Denis Chaves state that based on their international demographic analysis:

[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]

The general assumption is that the primary negative impact of Demographic Winter is a reduced labor supply. A new study published by RAND finds the consequences to be much greater, though, eventually resulting in overall slower growth in labor productivity:

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 . . . [W]e interpret this as indicating that older and younger workers are complements in production, and so the productivity of the older workforce affects the productivity of younger workers. This pattern could also arise from a loss of positive productivity spillovers from older to younger workers if productive older workers are more likely to exit the labor force.[3]

Demographic Winter alone will position the American economy at stall speed. Minor economic hiccups will quickly send the economy into an actual recession or even depression.

Additionally, Demographic Winter will have a negative fiscal impact on federal, state, and local governments. First, people over the age of 65 impose significantly greater costs to government than younger age cohorts. Chart 16 shows that 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 educational costs factored in.[4]

While these costs predominantly fall on the federal government (Social Security and Medicare), state governments should be prepared for a significant spike in Medicaid costs for those over the age of 65, especially expenses associated with long-term care.[5]

Second, while expenses soar for those over the age of 65, the taxes paid by this age cohort drop by two-thirds as shown in Chart 17.[6] The primary reason for this drop is the natural decline in payroll and income taxes as people retire from the labor force. As such, the primary fiscal concern for policymakers moving forward is the eroding income tax base as the country continues to age.

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 the fertility rate (the number of children a woman gives birth to over her lifetime).

There is no single explanatory reason for the drop in the fertility rate. Some of the more common explanations include:

  1. Higher opportunity costs for women: The mass entry of women into the workforce post-WWII significantly boosted household income, which allowed for greater consumption—another car, bigger homes, more vacations, etc. Having a child became a material sacrifice.[7]
  2. Legalization of abortion and advent of “the pill” and other forms of contraception: A baby that is never born directly reduces the fertility rate.[8]
  3. The decline in religiosity: Religious families have a higher fertility rate than non-religious families.[9]- [10]However, 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 6.7 percent to 22.8 percent from 16.1 percent.[11]
  4. The increase in sexually transmitted disease (STD): 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.”[12] In 2014, there were 1,436,496 cases of chlamydia and another 348,179 cases of gonorrhea (see section on STDs), which cause pelvic inflammatory disease that can then lead to infertility.
  5. The increase in the average age of women having their first child: 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.[13]

In the short run, states can shift the tides of demographic change through migration between the states. An economically thriving state will be attractive to families who are in search of greener pastures. For example, Illinois has long seen its residents moving to states such as Texas and Florida.[14] The net migration (+/-) of families is an important feedback mechanism for state leaders, political and otherwise, to better understand the social and economic health of their state.

As shown in Chart 18 and Table 3:

STATE HIGHLIGHT: WISCONSIN[15]

Two FPI variables are particularly responsible for the drag on Wisconsin’s overall score (17th)—entrepreneurship (47th) and marriage (44th)—and three other measures show signs of worsening—the fertility rate (28th), net natural population rate (30th), and domestic migration (30th).

Wisconsin’s fertility rate has persistently been below the national average. While the gap has closed in recent years, this is more a result of the national average falling more quickly than the Wisconsin average. Overall, in 2015, Wisconsin had only the 30th highest fertility rate. Not surprisingly, the long-term impact of a below-average fertility rate is also affecting the net natural rate of population growth, which is the difference between the number of births and deaths.

Since 2008, the national average has been trending downward and Wisconsin has followed that trend—due entirely to a drop in the birth rate, which fell 13 percent in Wisconsin from 2008 to 2016. In 2016, Wisconsin had the 29th highest net natural population rate.

More troubling, the data by county shows that 22 Wisconsin counties in 2015 (the year for which the most recent data is available) already had a negative net natural population rate—meaning they had more deaths than births. As the statewide trend of lower births continues, more and more counties will fall into this “Demographic Winter” category.

In the short run, states can shift the tides of demographic change through migration between the states. An economically thriving state will be attractive to families who are in search of greener pastures. The net migration (+/-) of families is an important feedback mechanism for state leaders, political and otherwise, to better understand the social and economic health of their state.

According to data from the U.S. Census Bureau, between 1991 and 2005, Wisconsin gained 107,717 residents from other states. However, in 2006, Wisconsin’s in-migration quickly reversed to out-migration. Between 2006 and 2015, Wisconsin lost 76,810 residents to other states.

As such, nearly the entire gain in residents between 1991 and 2005 has been lost. To make matters worse, Wisconsin’s out-migration shows no sign of abating with a record 15,568 people leaving in 2015 and another 12,395 in 2016.

While the Census Bureau data is comprehensive, it is also very shallow. Fortunately, the Internal Revenue Service (IRS) provides an annual snapshot of taxpayer migration via tax returns, which provides for a much richer picture of migrants.[16] As shown in Table A, a key insight from this analysis is that the majority of the net out-migration of income is from taxpayers over the age of 45 earning more than $100,000.[17]

Why is this important? As shown in Chart B there are significant differences in the characteristics of taxpayers earning more than $100,000 versus less than $100,000 (as a percent of taxpayers). They tend to be married (89 percent versus 32 percent), give to charity (81 percent versus 18 percent) and be heavily involved in business activity. Additionally, and just as importantly, average family size is higher (2.9 versus 1.7 children) among those at the $100,000+ income level.

In other words, Wisconsin’s net out-migrants predominantly fall in the demographic group most likely to be the state’s business and community leaders. This further saps the state’s entrepreneurial vitality as well as its share of successful, intact families—the two weakest areas identified by the FPI. Stemming this out-flow is the first step toward solving the state’s entrepreneurship and marriage deficits.

This will not be an easy task since the two states benefiting most from Wisconsin’s out-migration are Texas and Florida. While nothing can be done about the obvious temperature differences, Wisconsin has leveled half of the playing field with its enactment of Right-to-Work laws in the state. This will equalize union membership levels over time, thus making Wisconsin more attractive as a place to do business. However, not nearly as much progress has been made in equalizing the differences in tax burdens between Wisconsin and its migratory rivals.

Lowering the state and local tax burden on Wisconsin’s families and businesses would help boost entrepreneurship and job creation and should be an immediate policy priority.

Percent of Population Under Age 18

As shown in Chart 19, the percent of the population under the age of 18 decreased nationally by 11 percent to 23 percent in 2015 from 25.7 percent in 2000. In 2015, Utah had the greatest under-18 population at 30.5 percent, while Vermont had the lowest under-18 population at 19.2 percent—a difference of 59 percent.[18]

Overall, for the under-18 sub-index, Utah had the top score (10.00), followed by Texas (8.68), Idaho (8.42), Nebraska (7.74), and South Dakota (7.59). Vermont had the lowest score (0.46), followed by New Hampshire (0.72), Maine (0.74), Rhode Island (1.60), and Massachusetts (2.17).

Percent of Population Over Age 65

As shown in Chart 20, the percent of the population over the age of 65 increased nationally by 20 percent to 14.9 percent in 2015 from 12.4 percent in 2000. In 2015, Florida had the highest over-65 population at 19.5 percent, while Alaska had the lowest over-65 population at 9.9 percent—a difference of 97 percent.[19]

Overall, for the over-65 sub-index, Utah had the top score (9.86), followed by Alaska (9.34), Texas (8.49), North Dakota (7.49), and Georgia (6.97). Florida had the lowest score (1.06), followed by Maine (1.16), West Virginia (2.04), Vermont (2.32), and Montana (2.91).

Net Natural Population Change

Charts 21 and 22 show the variance in the net natural population change—including births, deaths and the net difference—nationally and in the 50 states from 2000 to 2016.[20]

As shown in Chart 21, the birth rate (as a percent of population) declined nationally by 13 percent to 1.23 percent in 2016 from 1.41 percent in 2000. In 2016, Utah had the highest birth rate at 1.69 percent, while New Hampshire had the lowest birth rate at 0.92 percent—a difference of 83 percent.

As shown in Chart 22, the death rate (as a percent of population) increased nationally by 1 percent to 0.85 percent in 2016 from 0.84 percent in 2000. In 2016, West Virginia had the highest death rate at 1.23 percent, while Utah had the lowest death rate at 0.54 percent—a difference of 128 percent.

As shown in Chart 23, there is a large variance in the net natural population growth rate (birth rate minus death rate) among the 50 states. In 2016, Utah had the highest net natural growth rate at 1.15 percent, while West Virginia had the lowest net natural growth rate at -0.15 percent. Only one other state, Maine (-0.1 percent), had a negative net natural growth rate.

Overall, for the net natural population change sub-index, Utah had the top score (9.75), followed by Alaska (8.77), North Dakota (8.51), Texas (8.16), and Nebraska (7.26). West Virginia had the lowest score (1.43), followed by Maine (1.58), New Hampshire (2.58), Pennsylvania (3.00), and Rhode Island (3.01).

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

As shown in Chart 24, there is a large variance in domestic people migration among the 50 states.[21] In 2016, Oregon had the highest net people in-migration at 1.22 percent, while New York had the highest level of net people out-migration at -0.97 percent.

As shown in Chart 25, there is a large variance in domestic income migration among the 50 states.[22] In 2014, Florida had the highest net income in-migration at 2.34 percent, while Illinois had the highest level of net income out-migration at -0.88 percent.

Overall, for the net domestic migration sub-index, Nevada had the top score (9.92), followed by Oregon (9.55), Florida (9.31), South Carolina (9.10), and Arizona (8.85). Illinois had the lowest score (1.39), followed by New York (1.40), Connecticut (1.42), North Dakota (1.86), and New Jersey (2.03).

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

Fertility Rate

As shown in Chart 26, the fertility rate (per 100 women between the ages of 15 and 44) declined nationally by 5 percent to 62.5 in 2015 from 65.9 in 2000. In 2015, South Dakota had the highest fertility rate at 78.2, while Vermont had the lowest fertility rate at 51.1—a difference of 53 percent.[23]

Overall, for the fertility sub-index, North Dakota had the top score (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), followed by Vermont (0.96), Connecticut (1.05), New Hampshire (1.06), and Rhode Island (1.97).

Also, Chart 27 illustrates how the U.S. fertility rate has plummeted 47 percent between 1960 (118) to 2015 (62.5). In particular, it also compares the fertility rate for the states in 2015 to the U.S. average as it moves through time.

For example, South Dakota had the highest fertility rate (78.2) in 2015. The last time the U.S. achieved this average rate was between 1971 and 1972, and even then, the rate was still 34 percent lower than the 1960 U.S. average. Note in Chart 27 that Texas and Wyoming’s fertility rate (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.

However, not shown in Chart 27 are the 24 states with fertility rates below the 2015 U.S. average, which puts them more firmly in the midst of Demographic Winter. Vermont’s fertility rate is 18 percent below the U.S. average (51.1) and is the lowest in the country.

Jump to Section:

  1. Introduction
  2. Economics
  3. Family Self-Sufficiency
  4. Family Structure
  5. Family Culture
  6. Family Health


[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, 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] 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

[13] 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

[14] 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

[15] The full Wisconsin study can be found at http://www.familyprosperity.org/application/files/9314/6712/8986/WisconsinFPI-Paper-DRAFT4.pdf and migration update: http://www.familyprosperity.org/application/files/8914/7708/4401/Wisconsin_Family_Prosperity_Index_Migration_Update_102016.pdf

[16] The IRS migration data is available at the state and county levels and can be found at https://www.irs.gov/uac/soi-tax-stats-migration-data

[17] Internal Revenue Service, “Gross Migration File,” Various Years, https://www.irs.gov/uac/soi-tax-stats-migration-data

[18] Population Estimates, U.S. Department of Commerce: Census Bureau http://www.census.gov/data/tables/2015/demo/popest/state-detail.html

[19] Ibid.

[20] Ibid.

[21] Population Estimates, U.S. Department of Commerce: Census Bureau http://www.census.gov/data/tables/2016/demo/popest/state-total.html

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

[23] 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_0...