Predictors of Upward Mobility for Fresno, California

Fresno Demographics:

Race and Ethnicity Overview

Comparing Fresno Race and Ethnicities over Time

Source: 5-year 2018-2022 American Community Survey data (treemap plots) and 5-year 2008-2012, 2013-2017, and 2018-2022 American Community Survey data (line charts).

Notes: The charts above show the racial and ethnic breakdown of Fresno City and Fresno County from the 2008-2012, 2013-2017, and 2018-2022 5-year American Community Survey data. 2018-2022 data is the most recently available data at the time of the dashboard’s creation. The subgroups shown are identified by the Census. We include Hmong, Asian Indian, and Mexican because they compose a large share of Fresno’s population and because they are reliable (see below for more details).

The Boosting Upward Mobility framework includes a “Descriptive Representation” predictor which is defined as the “[r]atio of the share of local elected officials of a racial or ethnic group to the share of residents of the same racial or ethnic group.” Instead of collecting demographic information from elected officials, this dashboard shows a more detailed racial and ethnic breakdown of Fresno. You can a list see Fresno (county)’s elected officials here and learn more about them at the county registrar website.

There is inherent unreliability in American Community Survey data. To determine whether or not to visualize racial or ethnic subgroups, we use the Coefficient of Variation (CV) where \(CV = standard error/ estimate\). While there is not a hard and fast rule, academic literature suggests that data with a CV below .12 can be considered “highly reliable,” and a CV between .12 and .40 can be considered to have “medium reliability.” In general, all data plotted is of “high reliability,” but two exceptions to this are made. First, the county-level Hispanic data from the American Community Survey data pulled is missing margin of error columns. However, the Fresno city-level Hispanic data has a CV below .12, and the county is a larger geography. This suggests that the CV would also fall below .12. Second, the Some Other Race data at the county scale and the Some Other Race, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander data tend to have “medium reliability.” Consequently, for these charts, error bars are also plotted. Even so, incorporating these populations into the dashboard is important so that all people viewing the it can see themselves to at least some extent in these charts. Lastly, note that the Census Bureau reports that interpreting changes over time can be challenging due to changes in weighting methodology and the tendency of multi-year estimates to smooth out sudden changes.

Inclusive Recovery Indices:

Source: The Inclusive Recovery Indices were developed by the Urban Institute. The data presented here is a compilation of metrics previously developed for the years 1980, 1990, 2000, 2013, and 2016. That data can be downloaded here. Index results from 2020 were developed specifically for this project.

Notes: The economic inclusion index is a combination of four variables capturing the following concepts: income segregation, rent burden, working poor, and percent 16- to 19-year-olds who are not enrolled in school and are not high school graduates. The racial inclusion index is composed of variables capturing the following five concepts: racial segregation, percentage people of color, poverty gap between Non-Hispanic White people and people of color, racial education gap between Non-Hispanic White people and people of color, and homeownership gap between Non-Hispanic White people and people of color. The overall inclusion index is a combination of the four economic inclusion indices and the five racial inclusion indices. The 274 cities were selected because they had populations greater than 100,000 in any decade between 1970 and 2010. The cities also were required to be “incorporated,” meaning that they have municipal governments. To read more about the creation of these metrics, please see this Urban Institute report.

Economic Development:

Employment opportunities: Employment-to-population ratio for adults ages 25 to 54

Source (County): US Census Bureau’s 2018 & 2021 5-Year American Community Survey Public Use Microdata Sample (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time period: 2014-18 & 2017-21)

Notes (County): The share of adults between the ages of 25 and 54 in a given community who are employed.

Source (City): US Census Bureau’s 2018 & 2021 1-Year American Community Survey and 5-Year American Community Survey Public Use Microdata Sample (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time period: 2014-18 & 2017-21)

Notes (City): The share of adults between the ages of 25 and 54 in a given community who are employed.

Jobs paying living wages: Ratio of pay on average job to the cost of living

Source (County): US Bureau of Labor Statistics Quarterly Census of Employment and Wages (QCEW) data, 2018 & 2021; Massachusetts Institute of Technology Living Wage Calculator, 2018 & 2022. (Time period: 2018 & 2021)

Notes (County): What an average job pays relative to the cost of living in a particular area. The metric is computed by dividing the average earnings for a job in an area by the cost of meeting a family of three’s (for a 1 adult and 2 child household) basic expenses in that area. Ratio values greater than 1 indicate that the average job pays more than the cost of living, while values less than 1 suggest the average job pays less than the cost of living.For the 2021 metric, we were only able to access the 2022 Living Wage data. We deflated the 2022 data to 2021 using the consumer price index (for all urban consumers), for a correct comparison with the 2021 QCEW.

Income: Household income at 20th, 50th, and 80th percentiles

Do you want to see related data visualized spatially? You can see maps showing Fresno tract-level income at the 20th, 40th, 60th, and 80th percentiles on the Map page.

Source (County): US Census Bureau’s 2018 & 2021 5-Year American Community Survey Public Use Microdata Sample (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time Periods: 2014-18 & 2017-21)

Notes (County): To identify income percentiles, all households are ranked by income from lowest to highest. The income level threshold for the poorest 20 percent of households is the value at the 20th percentile. The 50th percentile income threshold indicates the median, with half of households earning less and half of households earning more. The income level threshold for the richest 20 percent of households is the value at the 80th percentile. The difference in income between households at the 20th percentile and the 80th percentile illustrates the level of local economic inequality.

Source (City): US Census Bureau’s 2018 & 2021 1-Year American Community Survey and 5-Year American Community Survey Public Use Microdata Sample (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time Periods: 2014-18 & 2017-21)

Notes (City): To identify income percentiles, all households are ranked by income from lowest to highest. The income level threshold for the poorest 20 percent of households is the value at the 20th percentile. The 50th percentile income threshold indicates the median, with half of households earning less and half of households earning more. The income level threshold for the richest 20 percent of households is the value at the 80th percentile. The difference in income between households at the 20th percentile and the 80th percentile illustrates the level of local economic inequality.

Additional Interpretation: For example, household income is the lowest for Black, Non-Hispanic households in New Orleans, LA and Detroit, MI and for Hispanic households in Buffalo, NY (<$20,000, found in the 20th percentile graph). Household income is the highest for White, Non-Hispanic households in San Francisco, CA (>$300,000, found in the 80th percentile graph). The largest racial disparities for this metric among the cities and counties shown in the dashboard exist between White, Non-Hispanic and Black, Non-Hispanic households for the 20th percentile (>$40,000 difference) and 50th percentile graphs (>$110,000 difference). Fresno’s (city and county) average income across all races and ethnicities is below an estimate of the average income across the state of California.

Financial Security: Share of households with debt in collections

Source (County): August 2018 credit bureau data from Urban Institute’s Debt in America feature. (Time periods: August 2018)

Notes (County): The county-level measure captures the share of adults in an area with a credit bureau record with debt sent to collections. For county-level August 2018 data, “majority” means that at least 60% of residents in a zip code are members of the specified population group.

Source (City): August 2021 credit bureau data, from Urban Institute’s Financial Health and Wealth Dashboard. (Time period: August 2021)

Notes (City): The city-level measure captures the share of adults in an area with a credit bureau record with any derogatory debt, which is primarily debt in collections. For city-level August 2021 data, ‘majority’ means that at least 50% of residents in a zip code are members of the specified population group.

Wealth-building opportunities: Percentage point difference in the share of a community’s home values held by a racial or ethnic group to the share of households of the same group

Do you want to see related data visualized spatially? You can see a map of Fresno showing the share of households of a given race or ethnic group who own their homes on the Map page.

Source (County): US Census Bureau’s 2018 & 2021 1-Year American Community Survey Public Use Microdata Sample (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time periods: 2018 & 2021)

Notes (County): The estimate shown in the chart reflects the share of primary-residence housing wealth for a given race and ethnic group subtracted by the share of households who are headed by a member of that race and ethnic group. If the difference is greater than 0, then that group controls a higher proportion of the total value of homes relative to their presence in the county. This metric is based on self-reported housing value, does not account for the extent of mortgage debt, and does not account for other important demographic variations such as differences in age composition across race and ethnic groups, and as such this metric may not fully reflect the size of the actual housing wealth gap. Even so, this metric is useful in determining whether there are racial disparities in terms of a community’s home values and how drastic those disparities are.

Source (City): US Census Bureau’s 2018 & 2021 1-Year American Community Survey Public Use Microdata Sample (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time periods: 2018 & 2021)

Notes (City): The estimate shown in the chart reflects the share of primary-residence housing wealth for a given race and ethnic group subtracted by the share of households who are headed by a member of that race and ethnic group. If the difference is greater than 0, then that group controls a higher proportion of the total value of homes relative to their presence in the city. This metric is based on self-reported housing value, does not account for the extent of mortgage debt, and does not account for other important demographic variations such as differences in age composition across race and ethnic groups, and as such this metric may not fully reflect the size of the actual housing wealth gap. Even so, this metric is useful in determining whether there are racial disparities in terms of a community’s home values and how drastic those disparities are.

Please note that the city-level data quality is considered “Marginal.” For more details, see the discussion of data quality on the Use the Data page.

Additional Interpretation: For example, if there were no racial disparities, all racial dots (green, blue, yellow, and pink) would fall on the 0% line. This would mean that each racial or ethnic group’s share of their community’s home values would equal the share of the community’s households headed by that racial or ethnic group. In reality, in Fresno County, CA, Hispanic households’ share of housing wealth is 14 percentage points less than their ethnic representation among households in the community.

Economic Inclusion: Share of people experiencing poverty who live in high-poverty neighborhoods

Do you want to see related data visualized spatially? You can see a map showing poverty levels by census tract and race and ethnicity in Fresno on the Map page.

Source (County): US Census Bureau’s 2018 & 2021 5-Year American Community Survey. (Time periods: 2014-18 & 2017-21)

Notes (County): The share of a city’s or county’s residents living in poverty who also live in high-poverty neighborhoods (defined as census tracts). A high-poverty neighborhood is one in which over 40 percent of the residents live in poverty. People and families are classified as being in poverty if their income (before taxes and excluding capital gains or noncash benefits) is less than their poverty threshold, as defined by the US Census Bureau. Poverty thresholds vary by the size of the family and age of its members and are updated for inflation, but do not vary geographically. ’Black’ includes Black Hispanics. ‘Other Races and Ethnicities’ includes those of races not explicitly listed and those of multiple races. Those who identify as other race or multiple races and Hispanic are counted in both the ‘Hispanic’ and ‘Other Races and Ethnicities’ categories.

Source (City): US Census Bureau’s 2021 5-Year American Community Survey; Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time period: 2017-2021)

Notes (City): The share of a city’s or county’s residents living in poverty who also live in high-poverty neighborhoods (defined as census tracts). A high-poverty neighborhood is one in which over 40 percent of the residents live in poverty. People and families are classified as being in poverty if their income (before taxes and excluding capital gains or noncash benefits) is less than their poverty threshold, as defined by the US Census Bureau. Poverty thresholds vary by the size of the family and age of its members and are updated for inflation, but do not vary geographically.

‘Black’ includes Black Hispanics. ‘Other Races and Ethnicities’ includes those of races not explicitly listed and those of multiple races. Those who identify as other race or multiple races and Hispanic are counted in both the ‘Hispanic’ and ‘Other Races and Ethnicities’ categories.

Digital Access: Share of households with a computer and broadband internet subscription in the home

Do you want to see related data visualized spatially? You can see maps showing Fresno tract-level estimates of households’ access to a computer and broadband by race and ethnicity on the Maps page.

Source (County): US Census Bureau’s 2021 5-Year American Community Survey. (Time period: 2017-2021)

Notes (County): The chart shows for each racial or ethnic group the percentage of households of that group that have access to broadband internet (including cable, fiber optic, DSL, or cellular data) and a computer (including desktop, laptop, and cell phone).

Human Development:

Access to preschool: Share of children enrolled in nursery school or preschool

Source (County): US Census Bureau’s 2018 & 2021 5-Year American Community Survey (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time period: 2014-18 & 2017-21)

Notes (County): The share of a community’s children aged three to four who are enrolled in nursery or preschool.

Please note that the data quality for Black, Non-Hispanic children is considered “Weak.” For more details, see the discussion of data quality on the Use the Data page.

Source (City): US Census Bureau’s 2018 & 2021 1-Year American Community Survey and 5-Year American Community Survey (via IPUMS); Missouri Census Data Center Geocorr 2022: Geographic Correspondence Engine. (Time period: 2014-18 & 2017-21)

Notes (City): The share of a community’s children aged three to four who are enrolled in nursery or preschool.

Educational achievement: Mathematics

Source: California Assessment of Student Performance and Progress (CAASPP) Smarter Balanced Assessments for students grades 3 - 11 (all available). The charts show the percentage of students who met or exceeded standards Data collected from years 2015 - 2023 and accessed via the California Department of Education website.

Notes: This dataset was not included in original Upward Mobility dataset. It provides additional context on California students’ educational performance. No data is available in the 2019-2020 school year due to the COVID-19 pandemic. Data was collected from the “statewide” files and subsequently filtered to include only counties and the state of California as a whole. The data and documentation do not clarify whether racial groups are Hispanic. For example, the “White” group in the data is not said to be either “Non-Hispanic White” or to include Hispanic Whites.

“AIAN” stands for “American Indian and Alaska Natives.” “NHPI” stands for “Native Hawaiian and Pacific Islanders.”

Educational achievement: English language arts

Source: California Assessment of Student Performance and Progress (CAASPP) Smarter Balanced Assessments for students grades 3 - 11 (all available). The charts show the percentage of students who met or exceeded standards. Data collected from years 2015 - 2023 and accessed via the California Department of Education website.

Notes: This dataset was not included in original Upward Mobility dataset. It provides additional context on California students’ educational performance. No data is available in the 2019-2020 school year due to the COVID-19 pandemic. Data was collected from the “statewide” files and subsequently filtered to include only counties and the state of California as a whole. The data and documentation do not clarify whether racial groups are Hispanic. For example, the “White” group in the data is not said to be either “Non-Hispanic White” or to include Hispanic Whites.

“AIAN” stands for “American Indian and Alaska Natives.” “NHPI” stands for “Native Hawaiian and Pacific Islanders.”

School Economic Diversity: Share of students attending high-poverty schools, by student race or ethnicity