Conditions for economic mobility
Economic mobility in this survey refers to whether respondents see conditions for all the various factors that contribute to economic mobility leading to movement upward or downward. The survey question is not intended to measure whether economic mobility is occurring; rather, we are interested in this measure insofar as it speaks to overall economic conditions in LMI communities and the potential economic outcomes associated with those conditions.
As shown in Figure 2, over half of respondents reported that conditions at the time of the survey favored downward economic mobility, and that those conditions had worsened over the previous year. Respondents were mixed on what they expected for conditions for economic mobility over the next year.
Almost one-third of respondents said that employment was the most important factor contributing to upward mobility. According to responses to the survey’s employment questions, employment has been and is expected to remain the strongest component of the economy for LMI populations. One of the respondents noted:
“There is plenty of access to jobs, and there is some upwards wage pressure, but housing costs are going up faster than wages.”
Figure 2: Conditions for Economic Mobility
a. April 2024 (N=37)
b. Expectations for year ahead (N=924)
Housing showed up as both a top positive factor and a top negative factor, as shown in Table 1. While many respondents stated they were seeing some improvement in the housing situation, the sentiment on housing was strongly negative for almost half of survey respondents. Comments largely centered on housing, but they also suggested that housing, transportation, food, and wages were all intersecting problems. For example, respondents indicated that while jobs were widely available, they were predominantly low paying and offered few opportunities for higher wages. Without higher wages, entities reported that their clients have struggled under the combined price pressures of housing, food, and transportation. Respondents further reported that such price pressures limited the ability of LMI populations to pursue skills training or education opportunities. Finally, higher-paying jobs were farther away from where their clients could afford to live. One respondent indicated how increasing costs are playing out in lives of people they serve:
“The increasing cost and lack of availability of affordable housing and quality child care are keeping some individuals out of the labor market and creating instability in terms of living conditions. More individuals are working multiple jobs to try and stay even, not to get ahead. Rent, food, and fuel costs are increasing more rapidly than income.”
Table 1: Top-Ranked Factors Affecting Conditions for Economic Mobility over the Next Year, According to Survey Respondents
Positive Factors |
1. |
Employment (29%) |
2. |
Housing (16%) |
3. |
Government assistance (e.g., Earned Income Tax Credit, Child Tax Credit, food/utility/rent assistance) (13%) |
Negative Factors |
1. |
Housing (48%) |
2. |
Employment (11%) |
3. |
Credit (6%) |
Note: Respondents were asked to choose one top positive and negative factor affecting conditions for economic mobility.
Economic conditions in low- and moderate-income communities
Next, we highlight results from the various topics covered in the survey. Respondents were asked to provide data on topics they selected based on their entity’s top programming area. For example, if a respondent chose “Housing-Renters” because their programming was mainly focused on housing issues, they would only be asked about conditions for renters, and they would not be asked about employment or small business conditions. Each of the following sections—with the exception of human services and emergency assistance—covers two topics in that sector of the economy.
Employment
Conditions for finding work were neither good nor bad for 43% of survey respondents (Figure 3). For the rest, conditions for finding work were more negative than positive. Almost one-third of respondents said conditions were poor or very poor, compared with just under a quarter (23.5%) saying conditions were good or very good. Job quality conditions were worse, as 50.8% of respondents indicated that they were poor or very poor. Two respondents made comments regarding quality of jobs that illustrate the challenge:
“[There are] lots of low-wage jobs with little flexibility in hours and no benefits.”
“Finding work may not be difficult, but finding work that pays a living wage is very challenging, especially for individuals without education.”
Figure 3: Conditions for Employment, April 2024
a. Finding work (N=200)
b. Job quality (N=130)
Most respondents did not expect conditions to worsen for either the ability to find work or job quality (Figure 4). Nearly half of respondents (44.7%) expected the ability to find work to improve, and more than one-third expected an improvement in job quality over the next year.
Figure 4: Expectations for Employment Conditions over the Next Year
a. Finding work (N=199)
b. Job quality (N=122)
Respondents largely expected jobs to remain widely available and wages to continue to increase over the next year (Table 2). Wages were not anticipated to rise to a level that would put workers in a better financial situation, though, with most respondents rating wages as the largest negative contributor to job quality in the next year (Table 2). Similarly, respondents noted several factors that posed significant barriers to finding employment over the same horizon, including lack of affordable child care, background checks and drug testing, skill/credential requirements, and the cost transportation. Several respondents indicated that a lack of digital skills was also a significant barrier to entering the workforce. One of the respondents’ comments highlights the importance of digital skills:
“All applications are done online and some LMI populations do not understand how to use computers or do not have access to the digital tools necessary to apply.”
Table 2: Top-Ranked Factors Affecting Conditions for Finding Work and Job Quality over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting conditions for finding work |
1. |
Availability of jobs (36%) |
2. |
Ability to get to available jobs (14%) |
3. |
Government assistance (e.g., Earned Income Tax Credit, Child Tax Credit, food/utility/rent assistance) (13%) |
Factors affecting job quality |
1. |
Wages (65%) |
2. |
Treated with dignity and respect (12%) |
3. |
Advancement opportunities (4%) |
Negative Factors |
Factors affecting conditions for finding work |
1. |
Housing (48%) |
2. |
Employment (11%) |
3. |
Cost of transportation (11%) |
Factors affecting job quality |
1. |
Wages (42%) |
2. |
Inflexible or lack of advanced scheduling (16%) |
3. |
Lack of advancement opportunities (7%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Housing
Of survey topics, respondents were most pessimistic about conditions for housing, particularly rental housing, and very few said that they expected any positive change in housing conditions over the next year.
Most survey respondents indicated poor housing conditions for both renters (84.9%) and homeowners (71%) (Figure 5). More than 60% of respondents reported that housing conditions had worsened over the past year.
Figure 5: Conditions for Housing, April 2024
a. Renters (N=265)
b. Homeowners (N=214)
b
Figure 6 shows that 56.2% of respondents indicated that they expect further deterioration of rental conditions over the next year, with rental prices and an insufficient supply of affordable or subsidized units as the main challenges (Table 3). As one respondent noted, “Affordability continues to worsen. Developer-led investment continues to focus on high-end housing. Many eviction prevention and subsidy programs are now ending.” While prices were also listed as a positive contributor for future conditions, that is likely due to some markets in the United States having experienced softening prices and to broader expectations that price increases will eventually slow. Regardless, respondents indicated that they do not expect prices to decline enough to provide relief for LMI households.
With respect to homeownership, approximately 40% of respondents expected conditions to continue to worsen. Cost of housing was one of the major concerns, as one respondent noted:
“[There are] no homes [on the market] under $200,000 unless they need substantial repairs.”
Ongoing costs were also a concern for those who were already homeowners, as one respondent indicated:
“The carrying costs of maintaining a home (insurance, repairs, property taxes, utilities) are all burdening fixed- and low-income homeowners.”
Figure 6: Expectations for Housing Conditions over the Next Year
a. Renters (N=263)
b. Homeowners (N=211)
Table 3: Top-Ranked Factors Affecting Housing Conditions for Renters and Homeowners over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting conditions for LMI renters |
1. |
No positive factors (28%) |
2. |
Availability of affordable, nonsubsidized units (14%) |
3. |
Prices (19%) |
Factors affecting conditions for LMI homeownership |
1. |
Availability of down payment assistance (23%) |
2. |
Ability to get financing for purchase (12%) |
3. |
Availability of homes for purchase (12%) |
Negative Factors |
Factors affecting conditions for LMI renters |
1. |
Prices (59%) |
2. |
Availability of affordable, nonsubsidized units (18%) |
3. |
Availability of subsidized units (11%) |
Factors affecting conditions for LMI homeownership |
1. |
Prices (54%) |
2. |
Availability of homes for purchase (20%) |
3. |
Ability to get financing for purchase (8%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Personal Finance
Financial stability among LMI populations at the time of the survey was largely seen as poor, and most respondents did not expect that to improve, mostly due to income not keeping up with the cost of living.
As Figure 7 shows, a significant portion of respondents indicated that conditions were poor or very poor for financial stability (66.1%) and personal credit (64%) in the communities they served. More than half of respondents (53%) noted that conditions for financial stability had worsened over the previous year, and 38.3% expected conditions to worsen over the coming year (Figure 8). The outlook was slightly less negative for personal credit conditions, with one-fifth noting that conditions had improved over the past year and a similar percentage expecting conditions to improve over the coming year.
Figure 7: Household Budget and Credit Conditions, April 2024
a. Financial stability (N=168)
b. Personal credit (N=89)
Figure 8: Expectations for Household Budget and Credit Conditions over the Next Year
a. Financial stability (N=167)
b. Personal credit (N=88)
Respondents reported that they had noticed wages were increasing, but also that they were not increasing enough to offset increased costs of living—as indicated by income appearing as both a positive and a negative contributor to their expectations for financial stability and personal credit conditions over the next year (Table 4). Meanwhile, many comments from the survey pointed to LMI populations taking on more debt through credit cards and alternative financial services to cover basic expenses, which put them on an unsustainable financial path. As one respondent stated, “The credit extended to LMI [populations] is usually very costly and places them in a position to default.”
Table 4: Top-Ranked Factors Affecting Conditions for Financial Stability and Personal Credit over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting conditions for financial stability |
1. |
Income (30%) |
2. |
Access to banking services (11%) |
3. |
Government assistance (e.g., TANF, SNAP, housing vouchers) (15%) |
Factors affecting conditions for LMI homeownership |
1. |
New products focused on helping LMI borrowers access credit (36%) |
2. |
No positive factors (22%) |
3. |
Credit availability (13%) |
Negative Factors |
Factors affecting conditions for financial stability |
1. |
Cost of living (49%) |
2. |
Income (27%) |
3. |
Availability of subsidized units (11%) |
Factors affecting personal credit conditions |
1. |
Cost of credit (e.g., fees, interest rates) (37%) |
2. |
Use of alternative financial services (e.g., payday loans, pawn shops) (19%) |
3. |
Credit card debt (12%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Small Business
While survey respondents noted high interest rates were a challenge for small businesses, they were generally optimistic about conditions for small businesses in the near term.
“Higher interest rates and inflation are having a negative impact on small businesses. Additionally, the customers of these businesses have less money to spend (inflation) at the very time the businesses need the revenue.”
While nearly 40% of respondents indicated operating conditions for small businesses were poor or very poor in April 2024 (Figure 9), a similar share (39.4%) expected conditions to improve over the next year (Figure 10). The expectation for improving conditions was due to the availability of technical assistance and grant funding (Table 5). While many respondents said that they expected their ability to find reliable employees to continue to improve, a far larger share expected the labor market to remain a significant challenge for businesses. Several respondents also noted that they expected higher costs for small businesses and their inability to pass costs to consumers to contribute negatively to business operations over the next year. One respondent described how inflation impacts small businesses:
“Inflation can drive up operating costs that, when passed on to poor consumers, drives away business.”
Business credit conditions were considered poor by half of respondents, with 43% noting that they had worsened over the previous year. While expectations for business credit conditions over the next year were mixed, optimism outweighed negativity. One of the barriers identified as facing small businesses in LMI communities was the cost of credit, and a respondent illustrated a negative consequence of not having access to credit:
“Many small businesses took credit from predatory lenders out of desperation and have been paying extremely high interest rates on loans and can’t get ahead, forcing closures.”
Figure 9: Conditions for Small Businesses, April 2024
a. Business operations (N=123)
b. Business credit (N=94)
Figure 10: Expectations for Small Business Conditions over the Next Year
a. Business operations (N=122)
b. Business credit (N=94)
Table 5: Top-Ranked Factors Affecting Conditions for Small Business Operations and Credit over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting conditions for small business operations |
1. |
Availability of technical assistance for day-to-day operations (28%) |
2. |
Availability of public or private grant funding (17%) |
3. |
Ability to find reliable employees (12%) |
Factors affecting small business credit conditions |
1. |
Availability of micro/small-dollar loans (26%) |
2. |
Availability of technical assistance for credit applications (18%) |
3. |
Availability of credit (18%) |
Negative Factors |
Factors affecting conditions for small business operations |
1. |
Ability to find reliable employees (42%) |
2. |
Operational costs (21%) |
3. |
Revenue (12%) |
Factors affecting small business credit conditions |
1. |
Cost of credit (e.g., fees, interest rates) (31%) |
2. |
Startup capital (15%) |
3. |
Business debt (10%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Health
Most survey respondents rated public health conditions and access to health care as poor, with insurance coverage and mental health needs as the main challenges.
More than half of respondents reported poor overall health conditions (55.5%), as well as poor access to health care (56.3%), in the LMI communities they served (Figure 11). Over the previous year, conditions had either worsened or remained unchanged in either area, most respondents noted. Their outlook over the next year was a bit more positive, with approximately one-fifth saying that they expected health conditions and access to health care to improve (Figure 12).
When asked about factors that contributed to their expectations for public health conditions and health care access, insurance coverage showed up as both a positive and a negative contributor (Table 6). This suggests respondents are seeing improvements in insurance coverage, but that there are considerable challenges with uninsured populations. Respondents also reported improving availability of free/low-cost clinics, telehealth options, and nutritious foods.
Finally, respondents expected substance abuse and a lack of availability of mental health care providers to negatively impact health conditions in LMI communities, and comments throughout multiple survey sections related back to these issues. Many respondents in public health noted they were seeing some improvements in mental health needs being met, but also that a substantial need remained.
One respondent captured this well, noting, “Substance use is increasing among the most vulnerable populations. Access to benefits/insurance/Medicaid continues to have obstacles. Mental health services are improving, but access to appointments is challenging [for] LMI populations that work during the day and must sacrifice pay to seek treatment.”
Figure 11: Overall Health and Health Care Conditions, April 2024
a. Public health/general health (N=110)
b. Access to health care (N=96)
Figure 12: Expectations for Overall Health and Health Care Conditions over the Next Year
a. Public health/general health (N=110)
b. Access to health care (N=95)
Table 6: Top-Ranked Factors Affecting Overall Health Conditions and Access to Health Care over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting overall health conditions in LMI communities |
1. |
Insurance coverage (private, employer-provided, Medicaid, or Medicare) (31%) |
2. |
Availability of nutritious food (16%) |
3. |
Mental health needs (19%) |
Factors affecting LMI communities’ access to health care |
1. |
Availability of free/low-cost clinics (21%) |
2. |
Insurance coverage (private, employer-provided, Medicaid, or Medicare) (17%) |
3. |
Access to telehealth options (12%) |
Negative Factors |
Factors affecting overall health conditions in LMI communities |
1. |
Mental health needs (24%) |
2. |
Substance abuse (22%) |
3. |
Insurance coverage (private, employer-provided, Medicaid, or Medicare) (22%) |
Factors affecting LMI communities’ access to health care |
1. |
Cost (32%) |
2. |
Insurance coverage (private, employer-provided, Medicaid, or Medicare) (16%) |
3. |
Availability of mental health providers (6%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Education
According to the survey results, conditions strongly differed between pre-K to 12th grade and adult education.
With respect to pre-K to 12th grade education, 45.7% of respondents indicated that conditions were poor, with 41% saying that they had worsened over the previous year (Figure 13). Fewer than 30% of respondents were optimistic for conditions in the near term (Figure 14). As one respondent noted:
“Teacher shortages and excessive absences, along with lack of caregiver support at home, contribute to poor academic performance.”
Conversely, only 26.7% of respondents said that conditions in adult education were poor (Figure 13), with 46% indicating no change over the previous year. Nearly half of respondents (48.1%) expected conditions in adult education to improve over the next year (Figure 14). However, costs and support for program completion continued to be a challenge (Table 7). As one respondent noted:
“In our community, I see a growing number of adult participants, but [they] have some problems with transportation, day care, and having to also work and miss classes.”
Figure 13: Conditions for Education, April 2024
a. Pre-K to 12th grade education (N=140)
b. Adult education (N=131)
Figure 14: Expectations for Education Conditions over the Next Year
a. Pre-K to 12th grade education (N=140)
b. Adult education (N=131)
Table 7: Top-Ranked Factors affecting Conditions for Pre-K to 12th Grade and Adult Education over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting pre-K through 12th grade education in LMI communities |
1. |
Availability of early childhood education (24%) |
2. |
Availability of programs and counselors to support students (academically and emotionally) (13%) |
3. |
Teacher hiring and retention (8%) |
Factors affecting conditions for adult education in LMI communities |
1. |
Participation in skills training and degrees (13%) |
2. |
Support for program completion (e.g., child care, transportation, tutoring, mentoring) (13%) |
3. |
Flexible learning arrangements (e.g., online courses, night/weekend classes) (6%) |
Negative Factors |
Factors affecting overall health conditions in LMI communities |
1. |
Teacher hiring and retention (20%) |
2. |
Student home life ( 19%) |
3. |
School funding (19%) |
Factors affecting conditions for adult education in LMI communities |
1. |
Cost (37%) |
2. |
Support for program completion (e.g., child care, transportation, tutoring, mentoring) (17%) |
3. |
Completion rates (10%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Human services and emergency assistance
Given that a large segment of survey respondents provided human services and emergency assistance, it is important to note that a separate report covers entities’ financial and operational health; this section’s summary focuses primarily on human services conditions. Nearly half of respondents noted that conditions for human services and emergency assistance were poor, with a large fraction expecting conditions to worsen over the next year (Figure 15). Based on comments, housing and mental health challenges appeared to be overwhelming service providers.
“Our organization is currently assisting 1,500+ families a month. As rent, food, and utility costs increase, we have seen a rise in new families needing assistance. We add 150-200 families to our services every month.”
Among the sectors measured in the survey, human services had the second largest share of respondents reporting that conditions were very poor (22%). (The largest was rental housing, at 37%.) Nearly half of respondents also noted that conditions for human services had worsened over the previous year. Like housing, there was little optimism in the human services sector over the next year, with 44.8% expecting conditions to worsen (Figure 15).
Many respondents saw coordination between organizations improving (Table 8), but many also mentioned in comments that the areas they serve were facing increased struggles because of a lack of coordination, suggesting that experiences are uneven across the United States. In addition to housing security and economic conditions negatively affecting their near-term expectations for human services conditions, a significant share of respondents also mentioned in comments that their clients were struggling to get help due to administrative burdens, eligibility problems, and difficulties reaching services.
Figure 15: Conditions for Human Services and Emergency Assistance
a. April 2024 (N=273)
b. Expectations for conditions of human services and emergency assistance over the next year (N=272)
Table 8: Top-Ranked Factors Affecting Conditions for Human Services and Emergency Assistance over the Next Year, According to Survey Respondents
Positive Factors |
1. |
Coordination among entities (39%) |
2. |
Economic conditions (17%) |
3. |
Funding (13%) |
Negative Factors |
1. |
Housing security (20%) |
2. |
Economic conditions (26%) |
3. |
Funding (16%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Access to Digital Skills, Internet, and Technology
While over one-third of respondents reported that conditions for internet access were poor, most indicated that conditions had been improving and they expected them to continue improving over the next year. Nevertheless, the discontinuation of the federal Affordable Connectivity Program is expected to contribute to the loss of internet access among LMI populations.
While the largest shares of respondents said that conditions for access to internet, technology, and digital skills were neither good nor poor, a significant portion did indicate that conditions in 2024 were poor (Figure 16). However, respondents indicated that conditions had improved recently, with one-third seeing improved conditions for access to internet and one-quarter seeing improved conditions for access to technology and digital skills over the year preceding the survey. More than one-third of respondents expected conditions in both areas to keep improving over the next year (Figure 17).
Figure 16: Conditions for Access to Internet, Technology and Digital Skills, April 2024
a. Internet access (N=392)
b. Access to technology and digital skills (N=524)
Figure 17: Expectations for Access to Internet, Technology, and Digital Skills over the Next Year
a. Internet access (N=386)
b. Access to technology and digital skills (N=518)
Respondents identified internet service availability, availability of subsidized internet service, and awareness of subsidized internet options as top factors expected to shape conditions for access in the near term (Table 9). Several comments from respondents pointed to the positive impacts of federal funds for expanding broadband infrastructure, particularly in rural areas. However, respondents reported that when broadband was available, people in LMI communities have struggled to afford plans, and several comments attributed expected struggles in the future to the end of the Affordable Connectivity Program. Respondents also indicated concern about increasing connectivity when many of their clients struggle with technology literacy and a lack of programs to help. One comment captured the dynamic well:
“Quality internet access in the most rural locations has been poor but is now improving. Many LMI people, however, lack the technology literacy to apply for online jobs, etc., or apply such skills to the workplace.”
Table 9: Top-Ranked Factors Affecting Conditions for Access to Digital Skills, Internet, and Technology over the Next Year, According to Survey Respondents
Positive Factors |
Factors affecting internet access in LMI communities |
1. |
Availability of subsidized internet service (34%) |
2. |
Internet service availability (25%) |
3. |
Access internet primarily via cell phone (15%) |
Factors affecting conditions for access to technology and digital skills in LMI communities |
1. |
Basic digital device skills (e.g., computer, cell phone) (30%) |
2. |
Availability of services to improve digital skills (14%) |
3. |
Availability of computers for home use (12%) |
Negative Factors |
Factors affecting internet access in LMI communities |
1. |
Availability of subsidized internet service (30%) |
2. |
Administrative barriers to getting subsidized internet service (14%) |
3. |
Awareness of subsidized internet options (13%) |
Factors affecting conditions for access to technology and digital skills in LMI communities |
1. |
Use cell phones primarily so do not develop skills (23%) |
2. |
Availability of computers for home use (20%) |
3. |
Basic digital device skills (e.g., computer, cell phone) (20%) |
Note: Percentages are the share of respondents ranking the item as the No. 1 factor. Overall ranking is based on a weighted ranking of the top three factors.
Respondent profiles
Figure 18: Entity Type
Does the entity you represent offer services directly to individuals and families? (N=1117) |
No |
14% |
Unsure |
2.2% |
Yes |
83.9% |
To which type of geographic area does your entity dedicate the most resources? (N=1107) |
Equal across all geographic areas |
41.5% |
Metropolitan |
40.0% |
Rural (including frontier) |
18.5% |
What type of geographic area does your entity serve? (N=737) |
Nationwide |
4.8% |
Statewide or multiple states |
17.7% |
Within a county or some counties within a state |
45.7% |
Within a metropolitan statistical area (MSA) |
31.8% |
Currently, is the entity you represent led by a person of color? (N=718) |
Yes |
40.7% |
No |
56.3% |
Unsure |
2.9% |
Note: Totals may not add up to 100% due to rounding.
Figure 19: Share of Entities by Majority Demographic Served
About the survey
Starting in 2020, the Federal Reserve System began conducting surveys to better understand the range of challenges facing low- and moderate-income (LMI) communities as an effect of the COVID-19 pandemic. That collection of surveys was called “Perspectives from Main Street.”
While the United States is no longer amid a pandemic-induced public health and economic crisis, lower-income and under-resourced communities continue to face obstacles that may hinder their full participation in the economy. The need to better understand such challenges and those faced by entities serving these communities is still crucial. To that end, the Federal Reserve began implementing the Community Perspectives Survey in 2024.
The Community Perspectives Survey is a national survey aimed at reporting the economic conditions of LMI communities and the health of the entities that serve them. This survey has two objectives:
- Monitor the economic conditions of LMI communities
- Uncover the needs and capacity of entities serving LMI communities
The survey was open from April 2 to May 3, 2024. Responses were collected through a convenience sampling method that relied on contact databases to identify representatives of nonprofit organizations, financial institutions, government agencies, and other community organizations. These representatives were invited to participate in the survey via emails, newsletters, and social media posts. The survey had a total of 937 responses from entities who serve LMI communities. However, the total number of responses across sectors could differ because not all entities provide services in each area asked about on the survey. Respondents were asked to select a topic area based on their entity’s top programming focus and answer questions related to that sector specifically and not others. All responses are from entities that serve LMI communities.
The views expressed in this report are those of the report team and do not necessarily represent the views of the Federal Reserve System.
Please cite this report as: Chalise, Nishesh, Violeta Gutkowski, and Steven Howland. “Community Perspectives Survey: Insights from the Field – Part I: Economic Conditions in Low- and Moderate-income Communities,” August 2024.
Survey topic areas and how they were referred to in the survey
Low and moderate income: Low income is defined as family median income that is less than 50% of the area median income; moderate income is defined as family median income that is between 50% and 80% of the area median income.
Economic mobility: Conditions for economic mobility were defined in the survey as the combination of factors (such as employment conditions, community safety, or digital access, among others) that may lead to a person’s potential to improve their economic position through changes in income and wealth.
Employment—finding work: Conditions for finding work were defined in the survey as those affecting LMI people’s ability to find work if they are looking for it. Both the economy and a firm’s hiring criteria affect how easy it is for people to find work.
Employment—job quality: Conditions for job quality were defined in the survey as the ability of LMI people to hold jobs that have high levels of job quality. Respondents were asked to consider LMI individuals who have jobs and those looking for jobs when answering.
Housing—renters: Conditions for rental housing were defined in the survey as those (such as price and availability of rental housing) affecting LMI renters.
Housing—homeownership: Conditions for homeownership were defined in the survey as those facing both current and prospective LMI homeowners.
Household budget and credit—financial stability: Conditions for financial stability were defined in the survey as those (such as financial management skills and savings) affecting LMI people’s financial stability. This includes access to banking services.
Household budget and credit—personal credit: Conditions for personal credit were defined in the survey as those (such as amount of debt and access to credit) facing LMI people.
Small business—operations: Conditions for small business operations were defined in the survey as those (such as business activity, costs, and ability to find employees) affecting LMI-owned small businesses.
Small business—credit: Conditions for small business credit were defined in the survey as those facing LMI-owned small businesses.
Health—public health/general health conditions: Condition regarding public health were defined in the survey as the overall health of LMI people in the communities served by the respondent’s entity.
Health—access to health care: Conditions regarding access to health care were defined in the survey as LMI people’s ability to access health care in the communities served by the respondent’s entity.
Education—pre-K to 12th Grade: Conditions regarding pre-K to 12th grade education were defined in the survey as pre-K to 12th grade schools’ ability to meet the needs of LMI children and prepare them for careers or college.
Education—adult: Conditions regarding adult education were defined in the survey as those in adult education and institutions’ ability to enhance the skills of LMI people for career advancement. This includes skills certifications and postsecondary education.
Human services and emergency assistance: Conditions regarding human services and emergency assistance were defined in the survey as demand for human services and emergency assistance and the ability of providers to meet that demand. Services may include food, housing, counseling, legal aid, and others with a goal of improving the quality of life for people with fewer resources and helping them get by in times of emergency.
Internet access: Conditions for internet access were defined in the survey as LMI people’s ability to access the internet. This includes the availability of internet access at home, the quality of internet service available, and price.
Technology access and digital skills: Conditions for technology access and digital skills access were defined in the survey as access to technology for finding employment, business development and skills training, among other economic factors. This can include access to cell phones, computers, software programs, specialized technology, and the training necessary to use them.
Acknowledgements
The Federal Reserve’s community development function seeks to promote the economic resilience and mobility of LMI and underserved households and communities across the United States. . We thank the following survey team members for their contributions.
Survey advisors
Daniel Paul Davis, Federal Reserve Bank of St. Louis
Michael Grover, Federal Reserve Bank of Minneapolis
David Kaufmann, Federal Reserve Board of Governors
Karen Leone de Nie, Federal Reserve Bank of Atlanta
Survey core group
Nishesh Chalise, Federal Reserve Bank of St. Louis
Surekha Carpenter, Federal Reserve Bank of Richmond
Violeta Gutkowski, Federal Reserve Bank of St. Louis
Steven Howland, Federal Reserve Bank of Kansas City
Heidi Kaplan, Federal Reserve Board of Governors
Matthew Klesta, Federal Reserve Bank of Cleveland
Lisa Nelson, Federal Reserve Bank of Cleveland
Report assistance
Whitney Felder, Fed Communities
Crystal Flynn, Fed Communities
Melissa Kueker, Federal Reserve Bank of St. Louis
Nicholas A. Ledden, Federal Reserve Bank of St. Louis
Derek Stacey, Federal Reserve Bank of Cleveland
Allyson M. Sykora, Federal Reserve Bank of St. Louis
Survey fielding team
Surekha Carpenter, Federal Reserve Bank of Richmond
Suzanne Cummings, Federal Reserve Bank of Boston
Michelle Dailey, Federal Reserve Bank of St. Louis
Molly Hubbert Doyle, Federal Reserve Bank of Dallas
Steven Howland, Federal Reserve Bank of Kansas City
Kellye Jackson, Federal Reserve Bank of New York
Heidi Kaplan, Federal Reserve Board of Governors
Elizabeth Kneebone, Federal Reserve Bank of San Francisco
Susan Longworth, Federal Reserve Bank of Chicago
Grace Meagher, Federal Reserve Bank of Atlanta
Edison Reyes, Federal Reserve Bank of New York
John Rees, Federal Reserve Bank of Atlanta
Brianna Smith, Federal Reserve Bank of Chicago