The homeownership rate in 2016 fell to 63.4 percent, according to the Census Bureau’s Housing Vacancies and Homeownership Survey
–down 0.3 percentage points in the past year. To find a lower homeownership rate, you have to go all the way back to 1965. Since the homeownership rate peaked in 2004, it has fallen by 5.6 percentage points.
2004: 69.0% (peak year)
Homeownership Rate by Age, 2016
The nation’s homeownership rate fell to 63.4 percent in 2016, according to the Census Bureau’s Housing Vacancies and Homeownership Survey
. This was down from the peak
of 69.0 percent in 2004–a 5.6 percentage point decline. Among householders ranging in age from 30 to 44, the decline was in the double digits, including a 12 percentage-point drop among householders aged 30 to 34 as the age of first-time home buying continues to advance.
Homeownership rate in 2016
(and percentage-point decline since 2004 peak)
Total households: 63.4% (-5.6)
Under 25: 21.9% (-3.3)
25 to 29: 30.9% (-9.3)
30 to 34: 45.4% (-12.0)
35 to 39: 55.3% (-10.9)
40 to 44: 62.0% (-10.0)
45 to 54: 69.3% (-7.9)
55 to 64: 75.0% (-6.7)
65-plus: 78.8% (-2.3)
Homeownership by Region, 2016
Nationally, the rate of homeownership fell to 63.4 percent in 2016, according to the Census Bureau’s Housing Vacancies and Homeownership survey
. To find a lower national rate, you have to go all the way back to 1965. But trends vary by region…
Northeast homeownership rate
2016: 60.2% (lowest rate since 1976)
2005: 65.2% (peak year)
Midwest homeownership rate
2016: 68.4% (slightly higher than in 2015)
2015: 68.3% (lowest rate since 1989)
2004: 73.8% (peak year)
South homeownership rate
2016: 65.0% (lowest rate since 1965)
2004: 70.9% (peak year)
West homeownership rate
2016: 58.5% (lowest rate since 1987)
2006: 64.7% (peak year)
Labor Force Participation Rises among Older Men in 2016
The labor force participation rate of men aged 65 or older climbed to 24.0 percent in 2016, the highest rate since 1972 according to a Demo Memo analysis of Bureau of Labor Statistics data
. From an all-time low of 15.6 percent in 1993, the labor force participation rate of older men has increased by more than 8 percentage points in the past two decades. But it will be a while before the rate matches what it was in 1950, when 45.8 percent of men aged 65 or older were in the labor force.
Labor force participation rate of men aged 65 or older
1993: 15.6% (low point)
How Much Have Workers Saved?
Most American workers are saving for retirement. Overall, 61 percent of workers aged 25 or older say they or their spouse have saved money for retirement, according to the Employee Benefit Research Institute’s 2017 Retirement Confidence Survey
. In every age group, most say they have saved for retirement, with the figure ranging from a low of 52 percent among workers aged 25 to 34 to a high of 70 percent among workers aged 55 or older.
But many workers have not saved much. Most aged 25 to 34 have less than $10,000 in savings and investments, not counting home equity or defined-benefit pensions. At the other extreme, the majority of workers aged 55 or older have saved at least $100,000, and 35 percent have saved $250,000 or more.
Percent of workers with <$10,000 in savings
Aged 25 to 34: 58%
Aged 35 to 44: 31%
Aged 45 to 54: 33%
Aged 55-plus: 28%
Percent of workers with $10,000 to $100,000 in savings
Aged 25 to 34: 29%
Aged 35 to 44: 35%
Aged 45 to 54: 26%
Aged 55-plus: 17%
Percent of workers with $100,000 or more in savings
Aged 25 to 34: 13%
Aged 35 to 44: 34%
Aged 45 to 54: 42%
Aged 55-plus: 53%
Many Households Face Retirement Risk
Many Americans are not prepared for retirement. Some know it, but many don’t. Conversely, among households that are adequately prepared for retirement, substantial numbers think they are at risk. A recent study by the Center for Retirement Research
measured the size of each of these groups in an attempt to determine the accuracy with which households assess their retirement readiness.
The Center for Retirement Research study analyzed data from the National Retirement Risk Index (NRRI), which is based on the Federal Reserve Board’s Survey of Consumer Finances. The NRRI defines households at risk as those whose retirement income will not be enough to replace a targeted percentage of pre-retirement earnings. The Survey of Consumer Finances also asks households how well prepared they think they are for retirement. Comparing those two measures–retirement readiness and perception of retirement readiness, the CRR study found the following…
52% of households are at risk
33% of households are at risk and they know it
19% of households are at risk but they don’t know it
48% of households are not at risk
24% of households are well prepared and they know it
24% of households are well prepared but they don’t know it
The 19 percent of households that are unaware of their retirement risk tend to be those with defined-contribution retirement plans and high incomes. The 24 percent that are well-prepared but think they are at risk tend to be homeowners with defined-benefit pension plans.
Average Number of Televisions Is Declining
The number of televisions in the average American home is declining, according to newly released data from the 2015 Residential Energy Consumption Survey
. There were an average of 2.3 televisions per household in 2015, down from 2.6 in 2009. Fewer households have three or more TVs (39 percent, down from 44 percent in 2009), and more households have no TVs (2.6 percent, up from 1.3 percent in 2009).
The number of televisions per household member rises with age. Households headed by people aged 75 or older have twice as many televisions per household member (1.47) as the youngest householders (0.72).
Televisions per household member (and per household), 2015
Under age 25: 0.72 (2.07)
Aged 25 to 34: 0.81 (2.36)
Aged 35 to 44: 0.83 (2.89)
Aged 45 to 54: 1.08 (3.06)
Aged 55 to 64: 1.27 (2.77)
Aged 65 to 74: 1.34 (2.55)
Aged 75-plus: 1.47 (2.40)
Can Google Street View Determine Local Demographics?
Using 50 million Google Street View images of cars in 200 American cities, the study’s researchers determined, with the help of a “machine vision framework based on deep learning,” the make, model, and year of each car (2,657 categories). They then used that information to “accurately estimate income, race, education, and voting patterns, with single-precinct resolution.” The average precinct has a population of only about 1,000, say the researchers. Here are some of the findings, in the researchers’ own words…
- “We successfully detected 22 million distinct vehicles, comprising 32% of all the vehicles in the 200 cities we studied, and 8% of all vehicles in the United States.”
- “Our model detects strong associations between vehicle distribution and disparate socioeconomic trends.”
- “The vehicular feature that was most strongly associated with Democratic precincts was sedans, whereas Republican precincts were most strongly associated with extended-cab pickup trucks.”
- “Our estimates accurately determined that Seattle, Washington is 69% Caucasian.”
- “We estimated educational background in Milwaukee, Wisconsin zip codes, accurately determining the fraction of the population with less than a high school degree.”
The researchers ask whether this type of analysis eventually could replace costly and time-consuming door-to-door efforts such as the American Community Survey. “As digital imagery becomes ubiquitous and machine vision techniques improve, automated data analysis may provide a cheaper and faster alternative,” they suggest.
Younger Adults Have More Laptops
Households headed by people under age 35 have an average of 1.5 laptops per household–one for every two household members. This is a greater concentration of laptops than in any other age group, according to the Energy Information Administration’s 2015 Residential Energy Consumption Survey
. The RECS examines household ownership of a variety of electronic devices including televisions, computers, and smartphones.
Laptops per household member (and per household), 2015
Under age 25: 0.52 (1.5)
Aged 25 to 34: 0.51 (1.5)
Aged 35 to 44: 0.40 (1.4)
Aged 45 to 54: 0.49 (1.4)
Aged 55 to 64: 0.48 (1.0)
Aged 65 to 74: 0.42 (0.8)
Aged 75-plus: 0.29 (0.5)
34% Experience Income Volatility
More than one-third of American households experience income volatility in a year’s time, according to Pew Charitable Trusts’ 2015 Survey of American Family Finances. Pew defines volatility as a year-over-year change in annual household income of at least 25 percent. Here are the percentages who experienced volatility by generation…
Households with at least a 25% change in income, 2014-15 (and % gaining or losing)
Millennials: 43% (26% gain; 17% loss)
Gen Xers: 31% (18% gain; 13% loss)
Boomers: 31% (15% gain; 16% loss)
Silent: 31% (15% gain; 16% loss)
Income volatility is a hardship says Pew, and survey findings bear this out. The 34 percent of households experiencing income volatility between 2014 and 2015 were more likely than those with stable incomes to have experienced financial shortfalls in the past year. They were less likely to have savings or the ability to come up with $2,000 to pay for unexpected expenses. Households with a financial loss of 25 percent or more had median savings of just $1,550. Those with a financial gain of 25 percent or more had savings of $3,000. Those with stable incomes had median savings of $5,500.
The most commonly cited reason for income volatility is an irregular work schedule, says Pew.
Many Have Past-Due Medical Debt
Among adults under age 65, a substantial 24 percent had past-due medical debt in 2015, according to a study by the Urban Institute
. The figure varies by state, ranging from a low of 5.9 percent in Hawaii to a high of 37.4 percent in Mississippi. Among the 10 states with the highest rates of past-due medical debt, 8 are in the South…
States with largest percentage of 18-to-64-year-olds with past-due medical debt:
West Virginia: 33.0%
South Carolina: 32.4%
Hawaii is the only state in which the percentage of 18-to-64-year-olds with past-due medical debt is below 10 percent. Minnesota has the second-lowest rate (13.3%), followed by California (16.0%), Massachusetts (16.1%), and Connecticut (16.3%).
Drug Overdose Deaths by State, 2015
Drug overdose deaths are surging, according to the National Center for Health Statistics
. The age-adjusted death rate nearly tripled between 1999 and 2015, rising from 6.1 to 16.3 deaths per 100,000 population. By race and Hispanic origin, non-Hispanic Whites have by far the highest drug overdose death rate–21.1 deaths per 100,000 population for non-Hispanic Whites versus 12.2 for Blacks and 7.7 for Hispanics. By age, the biggest increase in drug overdose deaths occurred among people aged 55 to 64, the rate rising five-fold from 4.2 to 21.8 deaths per 100,000 population between 1999 and 2015.
The age-adjusted drug overdose death rate is much higher in some states than in others. Here are the states with the highest and lowest drug overdose death rates in 2015…
States with the highest rate of drug overdose deaths per 100,000 population:
West Virginia: 41.5
New Hampshire: 34.3
Rhode Island: 28.2
States with the lowest rate of drug overdose deaths per 100,000 population:
North Dakota: 8.6
South Dakota: 8.4
Younger Adults Have More Smartphones
Households headed by people under age 25 own more than two smartphones on average, or 0.83 smartphones per household member. This is a greater concentration of smartphones than in any other age group, according to the Energy Information Administration’s 2015 Residential Energy Consumption Survey
. Not far behind are households headed by 25-to-34-year-olds, with 0.80 smartphones per household member. Smartphone ownership is lowest among householders aged 75 or older, just 0.30 per household member.
Smartphones per household member (and per household), 2015
Under age 25: 0.83 (2.4)
Aged 25 to 34: 0.80 (2.3)
Aged 35 to 44: 0.69 (2.4)
Aged 45 to 54: 0.75 (2.1)
Aged 55 to 64: 0.64 (1.4)
Aged 65 to 74: 0.52 (1.0)
Aged 75-plus: 0.30 (0.5)
Minority Share of 10 Largest Metros, 2015
Asians, Blacks, Hispanics, and other minorities accounted for 38 percent of the total U.S. population in 2015, according to Census Bureau
data. Minorities are the majority in 7 of the 10 largest metropolitan areas.
Minority share of 10 largest metropolitan areas
New York: 53.1%
Los Angeles: 70.1%
Washington, DC: 53.9%
Note: Minorities are calculated by subtracting non-Hispanic Whites from the total population.
Number of Children in Lifetime, 2015
American women will have an average of 1.84 children in their lifetime, according to National Center for Health Statistics
‘ estimates based on birth rates by age in 2015. This is well below the average of two children per woman required to sustain the U.S. population at its current size absent immigration. Here is the average number of children women will have in their lifetime by race and Hispanic origin…
Average number of children in lifetime
2.12 children for Hispanics
1.86 children for non-Hispanic Blacks
1.75 children for non-Hispanic Whites
1.65 children for Asians
1.26 children for American Indians
Many Births Are Unplanned
Unplanned births are common, according to the Urban Institute
. Fully 36 percent of respondents to the Urban Institute’s nationally representative survey of women aged 18 to 44 reported experiencing an unplanned birth. Among women who had given birth, the 62 percent majority said they had experienced at least one unplanned birth.
How do women feel about these unplanned births? Among all women aged 18 to 44, the majority thought an unplanned birth would have a negative effect on four key aspects of a woman’s life-education (66 percent negative), job (58 percent), income (63 percent), and mental health (59 percent). But among women who had actually experienced an unplanned birth, a smaller share reported negative effects in those four areas: education (36 percent negative), job (31.5 percent), income (47 percent), and mental health (40 percent).
“When considering the effects of an unplanned birth on women’s lives in general, respondents who had experienced an unplanned birth were less likely than those who had not to perceive mostly negative effects,” reports the Urban Institute. Still, a substantial share of women reported negative consequences. “For women who experience an unplanned birth, access to targeted services and supports could reduce the negative impact of an unplanned birth on a woman’s life,” concludes the report.