Economic Well-Being
In 2017, more people gave a positive assessment of their own economic well-being than in the prior year, a trend that has continued annually over the five years of this survey. This improvement in self-reported well-being is consistent with the broader economic expansion over that same period. The national unemployment rate was 4.1 percent at the time of the most recent survey in 2017, down from 6.9 percent at the first survey in 2013.2 Despite these gains, stark differences in economic well-being remain, in particular, by education and race.
Current Financial Situation
Nearly three-quarters of adults say they are either living comfortably (33 percent) or doing okay (40 percent), when asked to describe how they are managing financially. The share who are at least managing okay has risen consistently over the past five years and is over 10 percentage points higher than in 2013 when this survey began.
Similarly, fewer people are finding it difficult to get by, or just getting by, than was the case five years ago. The 7 percent of adults in 2017 who find it difficult to get by financially is about half of what was seen in 2013. This decline in financial hardship is consistent with the decline in the national unemployment rate over this period (figure 1).
Figure 1. Self-report struggling financially and the national unemployment rate (by survey year)
Note: Unemployment rate is from the Current Population Survey as reported by the Bureau of Labor Statistics. Here and in subsequent figures, percents may not sum to 100 due to rounding and question non-response.
The overall positive trend in self-reported well-being masks some notable differences across groups. Adults with a bachelor's degree or higher are far more likely (85 percent) to be at least doing okay financially than those with a high school degree or less (66 percent). Despite this persistent gap, economic well-being improved in 2017, and over the past five years, at every education level (figure 2).
Figure 2. At least doing okay financially (by survey year and education)
More education is associated with greater economic well-being; however, at each education level, blacks and Hispanics are worse off than whites.3 In fact, whites with only a high school degree are more likely to report doing okay financially than blacks or Hispanics with some college education or an associate degree (figure 3). This pattern, combined with the fact that blacks and Hispanics typically have completed less education, results in substantially lower overall economic well-being for black and Hispanic adults.4
Figure 3. At least doing okay financially (by education and race/ethnicity)
Differences in well-being extend beyond education and race and ethnicity--and are also apparent by income level, marital and parental status, and community characteristics (table 1).5 Urban residents, for example, are slightly more positive about their financial situation than those living in rural areas. Although differences across these groups remain, economic well-being has generally improved over the past year, and since 2013, for individuals with a wide range of backgrounds.
Table 1. Share of adults at least doing okay financially (by demographic characteristics)
Percent
| Characteristic | 2017 | Change from 2016 | Change from 2013 |
|---|---|---|---|
| Family income | |||
| Less than $40,000 | 56 | +5 | +14 |
| $40,000-$100,000 | 78 | +2 | +13 |
| Greater than $100,000 | 94 | +2 | +11 |
| Race/ethnicity | |||
| White | 77 | +5 | +12 |
| Black | 65 | +1 | +12 |
| Hispanic | 66 | +2 | +10 |
| Urban/rural residence | |||
| Urban | 74 | +4 | +11 |
| Rural | 71 | +4 | +12 |
| Neighborhood income | |||
| Low or moderate income 1 | 63 | +3 | n/a n/a |
| Middle or upper income | 77 | +4 | n/a |
| Marital/parent status | |||
| Unmarried, no children under 18 | 66 | +3 | +8 |
| Married, no children under 18 | 84 | +4 | +9 |
| Unmarried, children under 18 | 57 | +2 | +14 |
| Married, children under 18 | 76 | +3 | +14 |
| Overall | 74 | +4 | +11 |
Note: Census tracts were not included in the 2013 SHED so changes since 2013 are not available. Here and in subsequent tables, percents may not sum to 100 due to rounding and question non-response.
1. Low- and moderate-income neighborhoods are defined here as those census tracts with a median family income less than 80 percent of the national median income. Return to table
n/a Not applicable.
The financial well-being question discussed so far has the advantage of being broadly defined and easy for respondents to understand. However, it may miss some aspects of well-being. As a check, respondents also complete a series of five questions on specific components of their financial lives.6 The responses to these questions are then converted to a single score on a 100-point scale of financial well-being. Earlier research found that a score of 50 or below on this scale is associated with a high probability of material hardship, such as the inability to afford food, medical treatment, housing, or utilities. A score over 60 is associated with low rates of material hardship.7
This alternative multiple-question measure of well-being shows somewhat higher rates of financial challenges than the single-question measure. About 2 in 5 adults have scores that suggest a high likelihood of material hardship, which is above the share who said that they are "just getting by" or "finding it difficult to get by." However, by either measure, those with more education, white adults, and people living in middle- and upper-income neighborhoods areas exhibit higher levels of financial well-being (table 2).
Table 2. Financial well-being score (by demographic characteristics)
Percent
| Characteristic | High likelihood of material hardship1 | Low likelihood of material hardship 1 |
|---|---|---|
| Education | ||
| High school degree or less | 50 | 24 |
| Some college or associate degree | 46 | 27 |
| Bachelor's degree or more | 29 | 39 |
| Race/ethnicity | ||
| White | 38 | 34 |
| Black | 46 | 26 |
| Hispanic | 52 | 22 |
| Urban/rural residence | ||
| Urban | 41 | 31 |
| Rural | 45 | 28 |
| Neighborhood income | ||
| Low or moderate income | 51 | 22 |
| Middle or upper income | 38 | 33 |
| Overall | 42 | 30 |
Note: See table 1 for definitions of low- and moderate-income neighborhoods.
1. Individuals with a high likelihood of material hardship are those with a financial well-being score of 50 or below. Individuals with a low likelihood of material hardship are those with a financial well-being score of above 60. Return to table
Changes in Financial Situation
over Time
More individuals say that their financial situation improved in the year prior to the survey (33 percent) than indicate it worsened (15 percent). Additionally, the share with improving finances is higher than in the 2016 survey.
Those with less education report less improvement financially than those with more education, consistent with the pattern in the past two surveys. Even so, at all education levels, reports of improving finances are more common than worsening finances (table 3). In 2017, at each education level, blacks and Hispanics experienced similar rates of improvement as whites. This contrasts with the previous two years when racial and ethnic minorities had larger improvements than whites, thereby narrowing the gap in well-being.
Table 3. Change in financial situation compared to 12 months ago (by education and race/ethnicity)
Percent
| Characteristic | Better off | Same | Worse off |
|---|---|---|---|
| High school degree or less | |||
| White | 25 | 59 | 15 |
| Black | 29 | 53 | 19 |
| Hispanic | 31 | 49 | 19 |
| Overall | 27 | 56 | 17 |
| Some college | |||
| White | 30 | 53 | 16 |
| Black | 36 | 44 | 19 |
| Hispanic | 31 | 49 | 19 |
| Overall | 31 | 51 | 17 |
| Bachelor's or more | |||
| White | 38 | 50 | 12 |
| Black | 43 | 42 | 15 |
| Hispanic | 50 | 37 | 13 |
| Overall | 39 | 49 | 12 |
| Overall | 33 | 52 | 15 |
Local and National Economic Conditions
In addition to their own family's finances, individuals are asked to assess the economic conditions in their local community and in the nation as a whole. Generally, people have a more positive attitude about their local economy than the nation's. Individuals are substantially more likely to view their local economy as "good" or "excellent" (57 percent) than the national economy (41 percent).
This more positive assessment of local than national conditions varies across the country. In particular, individuals in urban areas are 22 percentage points more likely to report that their local economy is faring well than individuals in rural areas. This urban-rural gap also holds for opinions about the national economy, though less starkly so (table 4).
Residents of low- and moderate-income neighborhoods have less favorable views of economic conditions than those living in higher-income areas. Blacks and Hispanics are less likely than whites to have a positive impression of either the local or national economic situation. Other individual and neighborhood attributes, such as exposure to the opioid epidemic, may also relate to differing perceptions of economic conditions (see box 1).
Table 4. Self-assessment of the local and national economy as good or excellent (by select characteristics)
Percent
| Characteristic | Local economy | National economy |
|---|---|---|
| Race/ethnicity | ||
| White | 61 | 44 |
| Black | 45 | 29 |
| Hispanic | 51 | 39 |
| Urban/rural residence | ||
| Urban | 60 | 42 |
| Rural | 38 | 35 |
| Neighborhood income | ||
| Low or moderate income | 38 | 34 |
| Middle or upper income | 64 | 43 |
| Overall | 57 | 41 |
Note: See table 1 for definitions of low- and moderate-income neighborhoods.
Box 1. Local Economic Conditions and the Opioid Epidemic
The sharp rise in opioid addiction and overdoses is a subject of national concern, so the 2017 SHED added a question on opioids to explore links to economic well-being.1 One hypothesis, advanced by Anne Case and Angus Deaton, is that a long-standing decline in economic opportunities was an important driver of the current opioid epidemic (2017).2 They refer to these as "deaths of despair." Yet, the existing evidence on the role of economic conditions is mixed. For example, Christopher Ruhm (2018) has argued against this hypothesis, using geographic variation in economic outcomes.3 This year's survey sheds light on the debate by linking individual-level exposure to opioid addiction with subjective assessments of economic conditions. There are large differences in exposure to the opioid epidemic by race and ethnicity and smaller differences by economic conditions.
To measure exposure to the opioid epidemic, individuals report whether they "personally know someone who has been addicted to opioids or prescription painkillers."4 By this measure, about one-fifth of adults have been personally exposed to the opioid epidemic. White adults, regardless of education, are about twice as likely to be personally exposed to opioid addiction as black or Hispanic adults (figure A).5
To investigate the "deaths of despair" hypothesis, figure B compares individuals' assessments of local and national economic conditions by their exposure to the opioid epidemic. Adults who have been personally exposed to the opioid epidemic have somewhat less favorable assessments of economic conditions than those who have not been exposed. Among whites, the gap in perceptions of economic conditions by opioid exposure is larger. However, local unemployment rates are similar in the neighborhoods where those exposed to opioids live and where those not exposed live.6 Subjective assessments of economic conditions do show more support for the "deaths of despair" hypothesis than objective outcomes, like local unemployment. Still, over half of adults exposed to opioid addiction say that their local economy is good or excellent. Altogether, this analysis suggests the need to look beyond economic conditions to understand the roots of the current opioid epidemic.
Figure A. Personally exposed to the opioid epidemic (by race/ethnicity and education)
Figure B. Self-assessment of the local and national economy as good or excellent (by exposure to opioid epidemic)
1. See, for example, analysis from the Centers for Disease Control and Prevention on opioid-related deaths, "Understanding the Epidemic," www.cdc.gov/drugoverdose/epidemic/index.html. Return to text
2. Anne Case and Angus Deaton, "Mortality and Morbidity in the 21 st Century," Brookings Papers on Economic Activity(Spring 2017): 397-476. Return to text
3. Christopher J. Ruhm, "Deaths of Despair or Drug Problem?" NBER Working Paper 24188 (2018). Return to text
4. This question is modeled after an April 2017 survey that found 27 percent of adults personally knew someone addicted to opioids (American Psychiatric Association, APA Public Opinion Poll - Annual Meeting 2017, www.psychiatry.org/newsroom/apa-public-opinion-poll-annual-meeting-2017). Two other recent surveys found even higher rates of exposure (Robert J. Blendon and John M. Benson, "The Public and the Opioid-Abuse Epidemic," New England Journal of Medicine 378 (2018): 407-11. Return to text
5. The survey does not include potentially more-sensitive questions about illicit drug use or an individual's own use of opioids. Since the measure does not ask about the respondent's own addiction, it may not reflect the ethnicities, education, or geographies of people personally struggling with addiction. Return to text
6. The local unemployment rates, measured with the five-year average from the 2012-16 American Community Survey at the census tract of the respondent, are 7.4 percent for those exposed and 7.3 percent for those who are not. The gap, while still modest, is somewhat larger for the local employment-population ratios for working-age adults (ages 25 to 64), 72.7 percent versus 73.2 percent. Return to text
References
2. The 2017 SHED was fielded in November and December 2017. Since 2013, the SHED has been fielded in the fourth quarter of the year, though the exact survey period has varied somewhat. Any comparison to statistics from other sources, such as the national unemployment rate from the Census Bureau's Current Population Survey, is made relative to the fourth quarter of the year. Return to text
3. These differences persist across different age groups. With the exception of those over age 60, who report higher levels of economic well-being, relatively little variation exists by age. As a result, the gaps in self-reported well-being by race and ethnicity within education levels generally remain even after taking age into account. Return to text
4. For details on educational attainment by race and ethnicity, see Camille L. Ryan and Kurt Bauman, Educational Attainment in the United States: 2015(Washington: United States Census Bureau, March 2016). Return to text
5. Income is measured as the income of the respondent and his or her spouse or partner. Urban communities are those in a metropolitan statistical area and rural ones are those outside of a metropolitan statistical area. Return to text
6. The Consumer Financial Protection Bureau (CFPB) developed the five questions and the mapping of responses to a 100-point scale. The questions focus on how well certain statements describe the respondent's situation. Examples include "because of my money situation, I feel like I will never have the things I want in life" and "my finances control my life." The CFPB's financial well-being scale was added to the SHED in 2017 to support further study of the scale. See Financial Well-Being in America(September 2017), www.consumerfinance.gov/documents/5606/201709_cfpb_financial-well-being-in-America.pdf, for details on the development of these questions and their relation to material hardships. Mapping to the well-being scale uses Austin Nichols's PFWB package in Stata: Austin Nichols, "PFWB: Stata Module to Predict Financial-Well-Being Scale Scores from CFPB Survey Instrument," Statistical Software Components S458353 (2017), Boston College Department of Economics. Return to text
7. Ibid. Return to text