Governance that is attentive to the needs of all community members and residents who are deeply engaged in collective decisionmaking are hallmarks of a community that supports upward mobility. A responsive local government empowers the people it serves by ensuring their concerns are addressed. By allocating resources equitably, local governments can help ensure all residents have good prospects for economic success. And when public institutions that are intended to serve and protect communities act with justice and restraint, residents feel that they are valued and respected members of the community.
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PREDICTORS
POLITICAL PARTICIPATION
Political participation takes many forms, such as whether voting-eligible individuals vote in elections. Political participation can reflect a voter’s own sense of power and autonomy, sense of well-being, self-rated health, and political representation. For example, people living in states with low voter turnout are far more likely to report being in fair or poor health than people in states with high voter turnout. Other research found that individuals reporting greater political participation scored higher on self-rated indices of empowerment.
Metric: Share of the voting-age population who turn out to vote.
This metric measures the share of the voting-eligible population that voted in the local election in a year with a presidential election.
Validity: This metric is well established. Scholars of political science have used this metric in articles published in peer-reviewed journals.
Availability: Data are reported out by local governments and are available to the public.
Frequency: New data for the metric are available at election cycles.
Geography: Data are broadly available at the electoral district level.
Consistency: Voter turnout is measured consistently over time and geography, but the values can be volatile from year to year, with higher turnouts in years involving a presidential election, so we focus our metric to occur during presidential elections.
Subgroups: Voter turnout by race or ethnicity within a jurisdiction can be measured using different methods depending on the demographic balance of the jurisdiction. For diverse or integrated communities, ecological inference or rows by column inference is preferred. For less diverse or highly segregated communities, homogenous precinct analysis is preferred. Each is based on the census-defined racial and ethnic characteristics of the jurisdiction.
Limitations: Residential mobility can affect this metric, so it is important to interpret changes in voter turnout in the context of demographic shifts in the jurisdiction. In local communities with higher rates of immigrants, voter turnout can inaccurately reflect a community’s political participation. Communities with a population of immigrants who are not registered to vote could consider additional local data to better assess political participation and civic engagement.
DESCRIPTIVE REPRESENTATION
Having local elected officials whose demographic characteristics (i.e., gender, race, ethnicity, or sexual orientation) broadly reflect those of their constituents correlates with greater feelings of political influence and engagement among otherwise underrepresented demographic groups. Research demonstrates that Black individuals who are represented by Black elected officials in Congress are more likely to be interested in and to vote in a House election and to disagree with the notion that they do not have a say in what government does. Feeling represented by one’s local officials has a positive effect on their civic engagement and increases their sense of belonging and empowerment.
Metric: Ratio 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.
This metric measures the ratio of the share of the city council or county board from specific racial and ethnic groups to the share of city or county residents from those racial or ethnic groups.
Validity: Scholars of political science have used this metric in articles published in peer-reviewed journals.
Availability: Data on the racial or ethnic characteristics of city council or county boards can be collected locally. Communities themselves should ask local elected officials to self-report their racial or ethnic identity, and we recommend a process for collecting this information in the Boosting Upward Mobility Planning Guide (Fedorowicz et al. 2022). The racial and ethnic composition of residents in those districts can be calculated using data from the Census Bureau’s American Community Survey.
Frequency: This metric can be updated as frequently as elections occur.
Geography: This metric can be calculated at the city or county level.
Consistency: This metric can be calculated the same way over time.
Subgroups: This metric accounts for race within its definition, but it may also be calculated for other subgroups.
Limitations: Although the movement of people in and out of the jurisdiction can influence this metric, it is likely to be far more sensitive to shifts in the composition of elected officials in the short term. Collecting information on the demographic characteristics of a local official may be challenging if they do not reveal this information publicly and are unwilling to report it to local data collectors.
SAFETY FROM CRIME
Exposure to crime, even for those who are not direct victims, is associated with elevated levels of stress, depression, and anxiety in both youth and adults and lower test scores for students. Adolescents exposed to gang violence displayed increased anxiety and post-traumatic stress. Teens who are exposed to higher levels of violent crime are more likely to engage in criminal activity themselves.
Metric: Rates of reported violent crime and property crime (per 100,000 people).
The FBI’s Uniform Crime Reporting (UCR) Program provides a standard, well-defined measure of crime. Reported crimes are captured for four index violent felonies (murder or nonnegligent manslaughter, rape, robbery, and aggravated assault) and four index property felonies (burglary, larceny-theft, motor vehicle theft, and arson).
Validity: The UCR Program statistics are the most widely used way to measure and compare reported crime across jurisdictions. The FBI provides definitions for each of the criminal offenses in the index, and most police departments in the United States report the data on those offenses to the FBI through a standardized reporting system. The purpose of the FBI’s UCR Program is to provide a common language transcending the varying local and state laws. Although there are potential issues with how different departments might classify offenses, the UCR Program is considered the most standardized source.
Availability: The data are available for most jurisdictions across the United States. If a jurisdiction is not included in the UCR Program data, local officials may be able to obtain the relevant and comparable data directly from their law enforcement agencies.
Frequency: Data are reported annually.
Geography: The UCR Program data are available at the agency level and city level and can be aggregated to the county level, dependent on availably of relevant agency data.
Consistency: The FBI advises caution when using UCR Program data to rank or compare locales because many factors could cause the nature and type of crime to vary by place. Data may be accumulated and compiled differently at the local level.
Subgroups: The data include demographic information (age, race, and gender) for those arrested for all crimes in the index and for the victims and offenders of homicides only (not for the other crimes in the index).
Limitations: Reporting is not mandatory, and although most jurisdictions provide data, UCR does not capture the universe of reported index crimes across the United States. UCR data measure crime reported to the police, so unreported crime is not captured. An FBI analysis estimates that up to half of violent crime goes unreported to the local police, and research finds that some neighborhoods are less likely to report violent crime, especially where trust of police is low. As a place-based metric, reported crime is affected by mobility in and out of the jurisdiction. Crime rates are based on the number of incidents per 100,000 residents. If the number of residents increases, the crime rate could go down without any change in the number of reported incidents. Also, crime tends to be concentrated in certain areas. Similarly, if new residents are moving to places where crime rates are already low, the populations and areas experiencing the most crime may also not see any change even if citywide rates decrease. Relatedly, the UCR Program does not provide data on crime at the neighborhood level, so it cannot track changes in crime or compare different places within a jurisdiction.
JUST POLICING
Overly punitive policing can undermine a sense of control and belonging in a community, and a criminal conviction can limit future economic opportunities. Increased police visibility increases the fear of crime and decreases confidence that the police can control crime. Concentrated police presence, surveillance, and extensive enforcement of minor violations of the law are common in neighborhoods with higher levels of reported crime, and these in turn result in greater exposure to police contact and arrest for people living in those neighborhoods and a greater resultant possibility of their incarceration. These factors have also been shown to decrease engagement with surveilling institutions (e.g., schools and hospitals) and to lower civic engagement. This type of contact has immediate negative effects for youth. Juvenile arrests and police stops of juveniles are risk factors for criminal behavior and for further and deeper involvement in the justice system. Deeper involvement in the justice system in turn leads to increasingly negative effects on socioeconomic status and is a mechanism for downward mobility. At the community level, incarceration rates are associated with lower income mobility. This is in part because of intergenerational effects: parental incarceration adversely affects the transition to adulthood in several ways. Finally, many residents in heavily policed neighborhoods have low levels of trust in the police, believe that race and ethnicity affect the police’s treatment of people, and do not believe police are responsive to the concerns and most pressing issues facing their communities.
Metric: Rate of juvenile justice arrests.
The FBI’s UCR Program provides statistics on the number of arrests of people under age 18. Because individuals can be arrested several times, the data reports the number of arrests rather than the number of individuals arrested. The metric is for arrests of juveniles ages 10 to 17 for any crime, but the data can be broken down by offense type. Arrest rates can be calculated using population data from the Census Bureau’s American Community Survey.
Validity: Although arrest behavior of the total population may be confounded by many factors, arrests among juvenile offenders can be more closely tied to overly punitive policing behavior. Research finds that after controlling for suspect race, gender, seriousness of offense, and amount of evidence, juveniles are more likely to be arrested than adult suspects. Research also finds large and disruptive impacts on adult outcomes: juvenile detention is associated with lower educational attainment, lower rates of employment, and higher rates of criminal offending and incarceration as an adult.
Availability: Arrest data are available in jurisdictions that report to the UCR Program and are available through the FBI’s Crime Data Explorer tool. The data are available for most jurisdictions across the United States (see the exposure to crime metric for more detail).
Frequency: Juvenile arrest data are available annually through the FBI Crime Data Explorer. Arrest data before 2014 can be found on the Bureau of Justice Statistics Arrest Data tool.
Geography: The UCR data are available at the agency level and city level and can be aggregated to the county level, dependent on availability of relevant agency data.
Consistency: The FBI advises caution when using UCR data to rank or compare locales because many factors can cause the nature and type of crime to vary by place. The FBI consistently defines juveniles as under age 18 regardless of a state’s definition. Data may be accumulated and compiled differently at the local level.
Subgroups: This metric necessarily measures people within a particular age group but also provides data on age subgroups (e.g., 10–12, 13–15, and 16–17) as well as by race or ethnicity and gender.
Limitations: Reporting to the UCR Program is not mandatory, and although most jurisdictions do so, the program does not capture the universe of reported index crimes across the United States. These data also do not capture any punitive interactions with school resource officers that do not get elevated to the level of arrest (such as being temporarily detained or being removed or suspended from school). As a place-based metric, reported crime is affected by mobility in and out of the jurisdiction, and because the metric is a rate, large increases or declines in the number of juveniles in an area could also affect it.
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