Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California

Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Executive Summary This Issue Brief surveys 11 data tools that measure and analyze how people and places are doing across California based on various indicators for economic, social, physical, and environmental well-being. Commission staff developed this resource to support state leaders, who will need to utilize objective metrics and data tools as they implement the Community Economic Resilience Fund (CERF), a statewide initiative to encourage inclusive regional economic planning and development, and address broad issues of regional equity. The data tools identified and compiled in the Brief include the Governor’s Office of Business and Economic Development’s Community and Place-Based Data Tool, the Economic Innovation Group’s Distressed Communities Index, and the Office of Environmental Health Hazard Assessment’s CalEnviroScreen. In addition to identifying existing data tools that provide insight into the health of regional economies, this Brief also discusses how these tools can shape perceptions of regions’ economic well-being and how they can offer different—even contrasting—depictions of how places are faring. Although the tools discussed in this Brief all provide thorough information about the well- being of California’s regions, they also vary in key ways, including the number of individual metrics used (ranging from four to 37), the specificity of geographic areas covered (ranging from census tracts to large regions), whether they focus on a single topic or compile data on multiple topics, and whether they ultimately produce an overall score or simply a compilation of individual metrics. In analyzing these tools, the Commission illustrates five ways in which data tools can shape how we perceive regional economic well-being: ◊ How regions are defined: Perception of the overall well-being of regions can vary significantly based on how regions are delineated. An example is the state’s southern border, which is sometimes viewed as one region, or is sometimes bifurcated into a coastal region focused on San Diego County and an inland region consisting of Imperial County. The Southern Border region performs relatively well when viewed as a single area. However, when viewed independently, San Diego and Imperial Counties perform notably differently than each other, sometimes even on opposite ends of the spectrum. Similar differences can be found elsewhere in the state, depending on regional definitions. Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 ◊ Which metrics are used: Which metrics are used and differences in how similar metrics are calculated can play a big role in changing our perception of areas. For example, the federal poverty rate, California Poverty Measure, and Real Cost Measure all seek to capture similar concepts, but the outputs of these metrics vary considerably across tools. ◊ Number of metrics used: While single metrics can offer a simple and standardized way to compare progress over time, they lack nuance and only account for one of the many aspects that contribute to the well-being of individuals and societies. Alternatively, data tools that combine a wide range of metrics have the potential to provide a more comprehensive picture of the well-being of an area. However, when pulling metrics from a variety of domains—such as environmental quality and economic prosperity—differences in how regions perform across domains can be masked. ◊ Granularity of the geography covered: Analyzing well-being across wider geographies can obscure disparities that exist within communities in the same region. Data tools that allow users to compare and contrast based on census tract, zip code, and city level open up the opportunity to explore some of the variations in well-being that exist among communities within the same region. ◊ Time of data collection: Accuracy-related concerns arise when pulling data from anomalous time periods, such as the COVID-pandemic. When comparing regional performance in anomalous eras it can be helpful to examine changes over time (looking at whether the trajectory of disparities is widening or narrowing), as opposed to focusing solely on snapshot comparisons. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 2 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Introduction This Issue Brief is part of the Little Hoover Commission’s study on equitable regional economic development, which launched earlier this year and focuses on California’s efforts to close regional disparities and promote greater prosperity across the state. In recent years, California has expanded its efforts to support regional economic development. Notably, in 2021, the state invested $600 million into the Community Economic Resilience Fund (CERF), a statewide initiative to encourage inclusive regional economic planning and development. Objective metrics and data tools will play a key role in helping state leaders and policymakers measure regional disparities, formulate plans to best target resources to address regional challenges, and track efforts to lift up regional economies. With this in mind, this Issue Brief offers a compilation of existing tools that measure and analyze how people and places are doing across California based on various indicators for economic, social, physical, and environmental well-being. It also utilizes examples from across the state to illustrate five ways in which data tools can shape our understanding of an area’s well-being. There are legitimate reasons why indices use different measures. This Issue Brief does not offer commentary as to which tools are preferential to others. Rather, it aims to illustrate the ways in which these differences can impact how we view regional disparities. How Data Tools Can Shape our Understanding of Well- Being Data tools can play an important role in helping policy- and change-makers address regional economic development. They provide informed, objective data on what issues exist and where, thus helping better direct resources or efforts. They can allow for easy comparison between geographical areas and across time. But they also have the power to shape how well—or how poorly—we think a region is performing overall or based on a specific policy area. In this Issue Brief, the Commission highlights 11 data tools that provide information on the well-being of regions and places in California. Utilizing examples from across the state, this Brief underscores five ways in which these tools can shape how we understand and subsequently address regional disparities. Data Tools Overview While the 11 data tools the Commission identified all attempt to gauge the well-being of areas within California, the tools vary in several key ways. See Appendix 1 for more information on the differences between the data tools identified in this Brief. First, the tools cover differing geographic areas, ranging from census tracts to variously delineated regions that cover large swaths of the state. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 3 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Well-Being Data Health Outcomes Rankings: Compares the physical and mental well-being of county Tools residents through measures that represent the length and quality of life typically experienced in the community. CalEnviroScreen (California Office of Environmental Health Hazard Assessment): Healthy Places Index (Public Health Alliance Mapping tool that helps identify California of Southern California): Combines 23 communities that are most affected by many community characteristics linked to health sources of pollution, and where people are often outcomes across eight domains (economic, especially vulnerable to pollution’s effects. social, etc.) to compare the relative performance of different geographies of the state. California Dream Index (California Forward): Measures 10 indicators for economic mobility, Human Development Index (Measure of security, and inclusion to track progress towards America of the Social Science Research the “California Dream.” Council): Measures social and economic development by focusing on three key Community & Place-Based Data Tool dimensions of well-being: health, education, and (Governor’s Office of Business and Economic income. Development): Interactive map that provides economic development, business, workforce, and Metro Monitor (Brookings Institution): Tracks demographic data for California cities, counties, the economic performance of the nation’s and economic regions. metropolitan areas along three dimensions critical to successful economic development: Distressed Communities Index (Economic growth, prosperity, and inclusion. Innovation Group): Examines the economic well- being of U.S. ZIP codes and counties and sorts Opportunity Atlas (Opportunity Insights): them into five quintiles of well-being: prosperous, Allows users to explore outcomes (e.g., earnings comfortable, mid-tier, at risk, and distressed. or educational attainment) for individuals based on the neighborhoods (census tracts) in which County Health Rankings and Roadmaps they grew up. (University of Wisconsin Population Health Institute)a Vitality Index (Hamilton Project): A composite Health Factors Rankings: Compares measure of several different indicators of California counties by a variety of modifiable economic activity and well-being used to community conditions in four factor areas determine the economic vitality of states and (health behaviors, clinical care, economic and counties. social factors, and physical environment) to gauge how healthy communities can be in the a We have included the Health Factors Rankings and Health future. Outcomes Rankings as separate tools as they utilize unique metrics and seek to measure different concepts. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 4 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Second, some tools provide a sense of how well areas of the state are doing in specific domains— Geographic Designations or categories—such as health (Health Outcomes and Data Tools Rankings) or the economy (Metro Monitor). Other tools include metrics from a variety of domains GEOGRAPHIC DESIGNATIONS to capture a more holistic sense of how well Community Economic Resilience Fund (CERF) Region: A county or collection of counties that geographies are performing. have been grouped based on economic and related factors for inclusive regional economic development But even when tools incorporate the same domains, planning under the CERF program. There are 13 they often vary in the type of metrics they utilize to CERF-designated regions.1 evaluate each domain. For example, the California Dream and Vitality Indices both include housing- Metropolitan Statistical Area (MSA) and Core related metrics, but the Dream Index uses the Based Statistical Area (CBSA): A county or collection affordable rent rate and homeownership rate while of counties that surround an urbanized area (with at least 50,000 people for MSAs and 10,000 people for the Vitality Index uses the housing vacancy rate. CBSAs) and that have a high degree of economic or social integration.2 MSAs and CBSAs are defined by The tools also include differing numbers of metrics, the U.S. Office of Management and Budget. ranging from four (Human Development Index) to 37 (Opportunity Atlas). County: A political and administrative division of a state. In California, there are 58 counties. Finally, the tools offer varying outputs, including a compilation of individual metrics or an overall score. Census Tract: A relatively small subdivision of a county with around 2,500 to 8,000 residents. See Appendix 3 for those tools that include an overall ZIP Code Tabulation Area (ZIP Code): An score or index ranking and Appendix 4 for those tools approximate area representation of U.S. Postal that include data compilations. Service Zip Codes, used by the U.S. Census Bureau for tabulating census data. ZIP Codes can cross How Regions are Defined county and state lines. How we delineate regions impacts our perception of GEOGRAPHIC DESIGNATIONS AND the well-being of areas. REGIONAL INDICES Sometimes multiple geographic designations For example, several state programs and initiatives— cover the same area. For instance, Kern County, such as the Community Economic Resilience Fund the Bakersfield MSA (metro area), and the Kern County CERF region all have the same geographic (CERF), Strong Workforce Program, and the K-16 boundaries. While regional delineations can include Education Collaboratives—group together San just a single county or metro area, more often, they Diego and Imperial Counties into a single, “Southern include multiple counties and metro areas. Regional Border” region. boundaries generally respect the boundaries of metro areas. However, one metro area—San Jose- The California Dream Index, which does so, gives the Sunnyvale-Santa Clara (comprised of San Benito and San Diego-Imperial region an overall well-being score Santa Clara Counties) is divided into two regions in that is slightly above the median score for California the CERF program. regions in 2019. The Community & Place Based-Data See additional details on which indices use which Tool—which allows users to explore demographic, designations in Appendix 1. economic, and workforce data for California’s cities, LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 5 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 counties, and economic regions—shows that the Southern Border Region ranks third highest for bachelor’s degrees and seventh highest for median household income (out of the 13 CERF regions). However, independently, San Diego and Imperial Counties perform notably differently than each other. The Health Factors Rankings and Healthy Places Index rank San Diego County among the top twenty counties for community well-being. Meanwhile, these tools place Imperial County on the opposite end of the spectrum. The Healthy Places Index finds that Imperial County scores second lowest among California counties with regard to measures of community well-being (across eight domains including economic, social, and physical health) while the Health Factors Rankings finds that Imperial County displays the lowest measures for community well-being (across four factor areas: health behaviors, clinical care, economic and social factors, and physical environment) among California counties. Graphic A: Regional Groupings Can Overshadow County Differences How San Diego and Imperial Counties Fare on Different Data Tools Range and San Diego Imperial Orientation Index Output County County (higher ranking/score to lower ranking/score) California Dream Index 63 58 California county score 78 to 51 Distressed Communities Index Prosperous Distressed Well-being quartile Prosperous to distressed Health Outcomes Ranking 15 33 California county rank 1 to 58 Health Factors Ranking 16 58 California county rank 1 to 58 Healthy Places Index 19 56 California county rank 1 to 57 Human Development Index 11 30 California county rank 1 to 48 Vitality Index 0.52 -1.27 Nationwide county score 3.07 to -4.33 Perception of the overall well-being of California’s Southern Border can thus vary significantly based on whether San Diego and Imperial Counties are grouped into a single region, or understood as constituting distinct regions. Which Metrics are Used Our perception of the well-being of an area is also impacted by which type of metrics analysts include in their data tools. Data tools differ in the domains—or categories—they include as well as the metrics used to evaluate those domains. Differences in how similar metrics are calculated can also play a big role in changing our perception of an area. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 6 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 For example, multiple tools rely on a cost of living or poverty metric to help express the economic well-being of areas. However, not all tools rely on the same definition of “poverty.” Here are three different metrics used by data tools to measure cost of living and poverty: Graphic B: Measuring Cost of Living and Poverty FEDERAL POVERTY CALIFORNIA POVERTY INCOME ABOVE COST RATE MEASURE OF LIVING Three times the cost of Considers changes in costs Factors in the costs of the economy food plan and standards of living and housing, health care, child published by the U.S. factors in resources from care, transportation, and social safety net programs. other basic needs to capture Department of Agriculture. what it costs to live in Note: This metric is not used California. Tools using this metric: by the data tools surveyed Healthy Places Index, in this brief, but is included Tools using this metric: Distressed Communities here to further illustrate how California Dream Indexb Index, and the Opportunity different ways of calculating Atlas. metrics can impact analysis Developed by: California of area’s well-being. Forward utilizing United Developed by: Economists Ways of California’s Real at the Social Security Developed by: Stanford Cost Measure. Administration in 1963. University and the Public Policy Institute of California. Despite aiming to capture similar concepts—the share of individuals or households in an area that do not have enough money to cover basic needs—the outputs of these metrics vary considerably across tools. As a result, our perception of the relative affluence of areas can differ based on how we calculate poverty levels. For instance, the poverty rate for Merced County—which the Distressed Communities Index shows to be “mid-tier”—ranges from 13 to 47 percent across tools. Santa Barbara County—which the Distressed Communities Index shows to be “comfortable”—has a poverty rate that ranges from 15 to 38 percent. See graphic C. b The California Dream Index also uses the official poverty rate to develop its “Prosperous Neighborhoods” indicator, which captures the percent of residents that live in census tracts with less than 20 percent in poverty. Since this metric offers a slightly different perspective on poverty, it is not included in the comparison in this section. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 7 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 The question of whether poverty is higher in Merced or Santa Barbara depends on the metric used. For example, according to the federal poverty measure, which the Distressed Communities Index employed in its evaluation of county economic well-being, the 2020 poverty rate was 19 percent in Merced County and 13 percent in Santa Barbara County. Conversely, the California Poverty Measure (CPM) essentially reverses the poverty rates for the two counties; according to the CPM, the average poverty rate in 2017-2019 was 21 percent in Santa Barbara County and 13 percent in Merced County. Graphic C: Poverty Rates Vary Considerably Across Data Tools Estimated poverty rates for Merced and Santa Barbara Counties 2017 California California Healthy Places Distressed Dream Index Poverty Measure Index Communities Households with Poverty rate, as Earning less than Index incomes below cost of calculated by PPIC and 200% of the federal Federal poverty rate living, as calculated by Stanford University poverty rate (ACS 2016 - 2020) United Way's Real Cost (2017–2019 average) (ACS 2015-2019) Measure Merced County 13% 19% 46% 47% Santa Barbara 21% 13% 33% 38% County Note: The Healthy Places Index and California Dream Index both include metrics that reflect the percentage of people and households living above the respective cost of living/poverty levels. For the sake of comparison between metrics, we have reversed this number to get the percentage of individuals and households living below the respective cost of living/poverty levels. ACS = American Community Survey. The Number of Metrics Used Another way that data tools can shape our perception of the well-being of an area is in the number of metrics used. SINGLE METRIC Using a single metric to gauge the well-being or relative prosperity of an area has its advantages. For instance, it can offer a simple and standardized way to compare progress over time and across areas. Using a single metric, however, also has its limitations. It lacks nuance and a single factor only accounts for one of the many aspects that contribute to the well-being of individuals and societies. We can explore the impact of using a single metric versus multiple metrics by comparing how counties rank by median household income, a frequent indicator of economic well-being, against their Health Factors Ranking (which includes measures related to health behaviors, clinical care, social factors, and physical environment). As noted in graphic D below, there is a positive correlation between a county’s median household income and its Health Factors Rank. Counties with higher median incomes—notably, counties located in the Bay Area region—also received relatively better Health Factors Rankings. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 8 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 However, the graph also highlights clear differences. For example, many counties in the San Joaquin Valley region have higher median incomes but received relatively worse Health Factors Ranks. Conversely, many of the North State and Redwood Coast region counties have lower median incomes but received relatively better Health Factors Ranks. This suggests that considering multiple metrics can provide a more holistic and nuanced picture of an area’s well-being. Graphic D: Health Factors Rank vs. Median Household Income Rank 70 60 Imperial Kern Merced Tulare Kings Del Norte Colusa Fresno Glenn Madera 50 Lake Modoc Tehama San Bernardino San Joaquin Alpine Stanislaus Trinity Yuba Mendocino 40 Monterey Mariposa Lassen Los Angeles Siskiyou Riverside Butte Sierra Sutter Plumas 30 Humboldt Shasta Calaveras Tuolumne Inyo Sacramento San Benito Amador Mono Solano 20 Santa Barbara Ventura San Diego Napa Santa Cruz Yolo El Dorado Sonoma Orange Contra Costa 10 Nevada San Luis Obispo Alameda San Francisco Placer Santa Clara San Mateo Marin 0 0 10 20 30 40 50 60 70 MULTIPLE METRICS Regional indices that combine a wide range of indicators into a single, aggregate score have the potential to provide a more comprehensive picture of the well-being of an area. However, when indices include metrics from a variety of domains—such as environment, economic, and social— differences in how regions perform across domains can be masked. For instance, the Healthy Places Index—which aims to measure community well-being using 23 different metrics spanning eight domains—ranks the Eureka-Arcata-Fortuna (Eureka) and Redding Core-Based Statistical Areas (CBSAs) relatively similarly overall. Eureka has healthier community conditions than 61 percent of the state’s CBSAs while Redding is healthier than 55 percent. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 9 knaR srotcaF htlaeH Median Household Income Rank Note: The rankings in this chart range from 1 to 58, with 1 being both the highest median household income rank and the highest health factors rank. Source: U.S. Census Bureau. “2016-2020 American Community Survey (5-year estimates).” Retrieved from the California Department of Finance. https://dof.ca.gov/reports/demographic-reports/american-community-survey/. Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 However, upon closer examination, we can see that these areas possess different strengths and face varying challenges. Based on the identified metrics, Eureka scores much better than Redding in the education, transportation, neighborhood, and clean environment domains. Conversely, Redding scores relatively higher in the economic, social, housing, and healthcare access domains. Graphic E: The Healthy Places Index Ranks Eureka-Arcata-Fortuna and Redding Similarly Overall but Differences Emerge in the Details EUREKA-ARCATA-FORTUNA: REDDING: 61ST PERCENTILE 55TH PERCENTILE Policy Action Areas: Policy Action Areas: Economic Economic Education Education Social Social Transportation Transportation Neighborhood Neighborhood Housing Housing Clean Environment Clean Environment Healthcare Access Healthcare Access Less More Healthy 0 25 50 75 100 By focusing on the overall score, the differences between domains can get lost and we can make incorrect assumptions about conditions within regions. Further, as state and regional leaders look at where to invest funding to boost regional development, it is important they understand the interplay between domains beneath the overall score of a region. This will help ensure a better understanding of the problems facing regions and inform decisions about where to concentrate efforts and investments. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 10 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 The Granularity of the Geography Covered Our perception of the well-being of an area is further influenced by how narrow or broad the geography of the area under analysis is. Data tools that allow users to compare and contrast based on census tract, zip code, or metro area opens up the opportunity to explore some of the variations in well-being that exists among communities within the same region. For example, the San Joaquin Valley, a large swath of Central California that accounts for around 10 percent of the state’s population, consistently receives low scores with respect to economic, social, and physical well-being across multiple indices. The California Dream Index gave the San Joaquin Valley regionc the lowest overall score among its 13 regions in 2020. The Healthy Places Index (which uses the same regional definition) found that over half of census tracts in the San Joaquin Valley rank in the least healthy quartile, compared to other regions in the state.3 Recognizing the size and diversity of the San Joaquin Valley—and with a desire to provide greater investment to the underserved area—the CERF leaders divided the region into three separate subregions: NORTHERN SAN CENTRAL SAN JOAQUIN VALLEY JOAQUIN VALLEY KERN COUNTY San Joaquin County Fresno County Kern County Stanislaus County Kings County Merced County Madera County Tulare County Breaking up the San Joaquin Valley into three regions helps to recognize the existing support networks within each subregion as well as their respective economic ties and industries.4 However, there are still significant differences in prosperity and well-being that exist among neighborhoods and communities within each subregion.a For instance, the Healthy Places Index—which combines 23 community characteristics linked to health outcomes across eight domains (economic, social, etc.) to compare the relative performance of different geographies of the state—illustrates these differences within the Northern San Joaquin Valley region. The Index ranks San Joaquin County in the second lowest quartile of counties with respect to health outcomes, but at the census tract level, we see that neighborhoods in Stockton rank in the bottom quartile of neighborhoods while surrounding communities may rank in third highest quartile. A similar pattern holds for Stanislaus and Merced Counties. c The California Dream Index refers to the San Joaquin Valley region as the Central Valley region. For consistency in our analysis, we are labeling the region as the San Joaquin Valley, but both labels refer to the same set of counties (Fresno, Kern, Kings, Madera, Merced, San Joaquin, Stanislaus, and Tulare). LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 11 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Graphic F: Wider Geographies Can Hide Local Disparities DISTRESSED OPPORTUNITY ATLAS HEALTHY PLACES INDEX COMMUNITIES INDEX (Median Household (Overall Ranking) (Overall Ranking) Income at 35) As seen in Graphic F, other data tools, like the Distressed Communities Index and Opportunity Atlas, also show how more granular analysis reveals significant local disparities below higher-level regional measures. The CalEnviroScreen similarly reveals a local patchwork of varying levels of pollution burden and vulnerabilities among neighborhoods. When characterizing the well-being of regions, it is important to have an understanding of the disparities that exist within those regions. The wider the geography, the more differences between communities are reduced. This is a significant point as the state government prepares to invest in regional economic development: supporting economic development in a distressed or disadvantaged regional area does not necessarily guarantee that investment and jobs will flow to distressed or disadvantaged communities within the region. CERF guidelines accordingly direct collaboratives to identify how planned initiatives will support disinvested communities at the census tract and neighborhood level. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 12 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Time of Data Collection Finally, perception of the well-being of an area is impacted by the time in which the data used in the analysis was collected. The COVID-19 pandemic has had a tremendous impact on Californians’ lives. This period of great social and economic upheaval also illuminates the challenges that arise when pulling data during and surrounding anomalous periods. Similar concerns relate to data from other anomalous periods in the state’s history, such as the Great Recession, the tech boom of the late 1990s, or the post-Cold War decline of the aerospace industry. Pre-pandemic data may no longer provide an accurate basis for comparing regional performance or evaluating the current scale of regional disparities. At the same time, more recent data may reflect severe but ultimately temporary impacts from the COVID-19 pandemic and accompanying recession. For example, the unemployment rate in the Inland Empire stood at about four percent immediately prior to the outbreak of COVID, peaked at 16 percent in Spring 2020, declined to eight percent in Spring 2021, and again stood at about four percent in Summer 2022.5 By comparison, in Fresno, the pre-pandemic unemployment rate was slightly higher at seven percent, reached a similar peak in Spring 2020 at 17 percent, declined to 10 percent in Spring 2021, and finally reached its pre-pandemic unemployment rate slightly earlier in February 2022. Graphic G: Unemployment Rate in the Inland Empire and Fresno Metro Area 18 17 16 16 14 13 12 10 10 9 8 8 7 7 6 6 6 4 4 4 2 0 Source: U.S. Bureau of Labor Statistics. “Unemployment Rate in Riverside-San Bernardino-Ontario, CA (MSA).” Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/RIVE106UR. Also, U.S. Bureau of Labor Statistics. “Unemployment Rate in Fresno, CA (MSA).” Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/FRES406UR. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 13 4102/1/1 4102/1/4 4102/1/7 4102/1/01 5102/1/1 5102/1/4 5102/1/7 5102/1/01 6102/1/1 6102/1/4 6102/1/7 6102/1/01 7102/1/1 7102/1/4 7102/1/7 7102/1/01 8102/1/1 8102/1/4 8102/1/7 8102/1/01 9102/1/1 9102/1/4 9102/1/7 9102/1/01 0202/1/1 0202/1/4 0202/1/7 0202/1/01 1202/1/1 1202/1/4 1202/1/7 1202/1/01 2202/1/1 2202/1/4 2202/1/7 Fresno Inland Empire Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 However, while the Inland Empire’s unemployment rate in Summer 2022 is similar to its pre- pandemic rate (four percent), Fresno’s unemployment rate has dipped slightly lower than its pre- pandemic unemployment rate to six percent.6 It may be some years before it is clear where apparent changes in relative regional performance reflect actual adjustments in regional trajectories or are simply temporary effects from the pandemic that will disappear as pre-pandemic trends reassert themselves. These challenges relative to comparing regional performance in the COVID-era suggest that it may be helpful when evaluating regional disparities to examine changes over time (looking at whether the trajectory of disparities is widening or narrowing), as opposed to focusing solely on snapshot comparisons. Some data tools, like the Brookings Metro Monitor, track key metrics over a period of time, allowing users to follow and compare regional trajectories based on indicators like regional income, productivity, and job creation. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 14 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Appendix 1: Overview of Data Tools The Commission identified 11 data tools that provide thorough information about California’s regional well-being. These tools differ in several ways: DOMAINS AND METRICS One way that the data tools vary is in the kinds of data they include. Some tools focus on providing a sense of how well areas in California are doing in specific domains or categories. For instance, the Health Outcomes Rankings seek to reflect the physical and mental well-being of counties. Alternatively, the Metro Monitor tracks economic growth performance metrics for the nation’s largest metro areas. However, most of the data tools that the Commission identified include metrics from a variety of domains. For the purpose of this Brief, these metrics have been divided into the following domains: economics, education, social, environment, health, transportation, housing, physical environment, and demographic characteristics. In addition to differing domains, these tools also utilize disparate metrics within those domains. For example, the California Dream, Vitality, and Distressed Communities Indices all include metrics that fall within the housing domain. However, they utilize different metrics to depict these domains. The California Dream Index uses affordable rent rate (percent of people paying more than 30 percent of their income on rent) and homeownership rate (percent of people who own their own home). Conversely, the Vitality Index and the Distressed Communities Index both use the housing vacancy rate (percent of habitable housing that is unoccupied). Finally, these tools also vary in the number of metrics utilized, ranging from four (Human Development Index) to 37 (Opportunity Atlas). GEOGRAPHIC AREA The tools cover differing geographic areas, ranging from census tracts to independently-defined regions that cover large swaths of the state. Counties are the most frequently-used geographic area among the tools, with eight of 11 data tools utilizing this level of geography. OUTPUT The tools vary in the outputs that they offer. Some tools, such as the Community and Place-Based Data Tool, provide a compilation of individual metrics. Others, such as the Vitality Index, use statistical methods to combine metrics (or domain scores) into an overall score. Some, including the Human Development Index, provide a combination of these outputs and offer both an overall score as well as individual metrics. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 15 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Appendix 2: Chart with Broad Overview of the Data Tools Health Rankings and Roadmaps* California Community and Distressed Health Health Human Healthy Metro Opportunity Vitality CalEnviroScreen Dream Place-Based Data Communities Factors Outcomes Development Places Index Monitor Atlas Index Index Tool Index Rankings Rankings Index Geographies Covered Census Tract X X X Zip Code X X Metro Areas or X X X X Cities Counties X X X X X X X X Region X X State X X X X X Other X X Domains and Metrics Economic X X X X X X X X X X Education X X X X X X X X Social X X X X Environment X X X X Health X X X X X X X X Transportation X X X X X X Housing X X X X X X X X Physical X X X Environment Demographic X X Characteristics Total Metrics: 21 10 34 7 30 5 23 4 15 37 6 Output Score(s) and/ X X X X X X X or Ranking(s) Data X X X X X X X X X X X Compilation Data Time Frame Time Frame 2009-21 2010–20 2013-21 2016–20 2014-20 2010-20 2011–19 2014-19 2009–19 1990-2016 2013-17 *The County Health Rankings and Roadmaps also provides related metrics outside of those utilized in the Health Factors and Outcomes Rankings. LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 16 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Appendix 3: Chart Comparing Data Tool Metrics (Indices and Rankings) County Health Rankings and Roadmaps California Dream Distressed Health Factors Health Outcomes Human Healthy Places Index Vitality Index Index Communities Index Rankings Rankings Development Index Economic % households with Federal poverty rate Unemployment rate (ages 16 Above poverty (% with Median earnings Median household income incomes above the "real and older) income >200% of federal cost of living" measure Unemployment rate (ages poverty level) Federal poverty rate (United Way) 25 to 54) % children in poverty Employment rate (ages Employment rate (ages 25 % of residents living in Median household income Income inequality (ratio of 25-64) to 54) census tracts with less than ratio (median household household income in the 80th 20% in poverty income as a % of metro area percentile to income at the Per capita income Unemployment rate median household income, 20th percentile) or state median household income, for non-metro areas) % change in number of jobs (2016 to 2020) % change in businesses (2016 to 2020) Education In pre-school (% ages 3 to 4) No high school diploma (% Have high school diploma or Bachelor's education or Educational degree ages 25+) equivalent (% ages 25+) higher (% adults 25+) attainment (% of adults % population with an 25+) Associate’s degree or Some post-secondary In high school (% ages 15 higher, or a career education (% ages 25-44) to 17) School enrollment (% technical education ages 3 to 24) certificate In pre-school (% ages 3 to 4) Housing Affordable rent (% paying Housing vacancy rate Severe housing problems Homeownership rate Housing vacancy rate >30% of their income on (% households with at least rent) 1 of 4 housing problems: % households with basic overcrowding, housing costs kitchen facilities and Homeownership rate that >50% of income, lack of plumbing kitchen facilities, or lack of plumbing facilities) Low-income homeowner severe housing cost burden (% paying >50% of income on housing) Low-income renter severe housing cost burden (% paying >50% of income on housing) Uncrowded housing (% households with ≤1 occupant per room) Social % of children in single- Voting in 2020 (% parent households registered voters voting in the 2020 general election) Membership social associations Census response rate (% responding to the 2020 Violent crime offenses census, short form) Deaths due to injury LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 17 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 County Health Rankings and Roadmaps California Distressed Health Outcomes Human Development Health Factors Rankings Healthy Places Index Vitality Index Dream Index Communities Index Rankings Index Health % adult smoking Premature death (years of po- % adults insured (ages 18 to 64) Life expectancy Life expectancy tential life lost before age 75 per Adult obesity (% age ≥18 with BMI 100,000 population, age-adjusted) ≥30 kg/m2) Poor or fair health (self-reported) Food environment index Poor physical health days Physical inactivity (self-reported) Access to exercise opportunities Poor mental health days (self-re- ported) Excessive drinking % of live births with low birth- Alcohol-impaired driving deaths weight (<2,500 gm) STIs Teen births % uninsured Primary care physicians to population ratio Dentists to population ratio Mental health providers to population ratio Preventable hospital stays Mammography screenings Flu vaccinations Environment Median air quality Air pollution (PM2.5) Diesel PM % of population Presence of health-related Drinking water contaminants served by water drinking water violations districts with no Air Quality: Ozone water quality violations Air Quality: PM 2.5 Transportation Census tract mean Driving alone to work % with automobile access commute time to work Long (30 min+) commute – Active commuting (% of driving alone workers ages ≥16 commuting by walking, cycling, or transit, excluding working from home) Physical Broadband access Park access (% living within ½ Environment -mile of a park, beach, or open space >1 acre) Tree canopy (population- weighted % of the census tract area with tree canopy) Retail density (combined employment density for retail, entertainment, supermarkets, and educational uses - jobs/ acre) LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 18 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Appendix 4: Chart Comparing Data Tool Metrics (Data Compilations) CalEnviroScreen Community & Place Based Data Tool Metro Monitor Opportunity Atlas Economic Poverty (% of population living below two times Labor force status 2009 to 2019: Children’s outcomes in adulthood: the federal poverty level) % change in the number of jobs Household income (HHI) at age 35 Unemployment rate Unemployment rate (age 16+) % change in gross metropolitan product (GMP) Indiv. income (excluding spouse) at age 35 Unemployment rate change (1 year) % change in the number of jobs at young firms Spouse's income at age 35 Largest job counts by occupation % change in productivity (GMP divided by number Employment rate at age 35 # of employees of jobs) Hours worked per week at age 35 Workforce distribution (blue collar vs white collar) % change in the average annual wage Hourly wage ($/hour) at age 35 # of businesses % change in standard of living (GMP divided by total metro population) Fraction in top 20% based on HHI # and share of business by type % point change in the employment rate Fraction in top 1% based on HHI # of jobs and businesses by NAICS % change in median earnings Fraction in top 20% based on indiv.income # and share of businesses by # of employees % point change in the relative poverty rate Fraction in top 1% based on indiv. income Median household income % point change in white/people of color employ- HHI (stayed in commuting zone) Median annual and hourly wages by occupation ment rate gap Indiv. income (stayed in commuting zone) Household income distribution Change in white/people of color median earn- ings gap HHI for U.S. natives Median household expenditures % point change in the white/people of color HHI for immigrants Consumer expenditures by type relative poverty rate gap Indiv. income for U.S. natives Tax rate by type 2005-09 to 2015-19: % point change in top/bottom neighborhoods Indiv. income for immigrants employment rate gap Neighborhood characteristics: Change in top/bottom neighborhoods median Job growth rate (2004 to 2013) household income gap Median HHI of residents (2012-16) % point change in top/bottom neighborhoods relative earnings poverty rate Median HHI of residents (1990) Poverty rate Density of jobs Education % with less than high school degree (age 25+) Educational attainment Children’s outcomes in adulthood: High school graduation rate Number of colleges College graduation rate Number of universities Neighborhood characteristics: Top 5 universities and # of graduates Fraction college graduates in 2012-16 Top college programs and # of graduates Housing Housing-burdened (paying >50 percent of Homeowners vs. renters rate Neighborhood characteristics: income on housing costs) low-income (income Median rent <80 percent of county’s median family income) Total households vs. families households Number of housing units by type Households by size LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 19 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 CalEnviroScreen Community & Place Based Data Tool Metro Monitor Opportunity Atlas Social Linguistic isolation (limited English speaking households) Children’s outcomes in adulthood: Incarceration rate Fraction married at age 35 Neighborhood characteristics: Fraction single parents Census response rate Health Asthma emergency department visits Children’s outcomes in adulthood: Teenage birth rate (women only) Cardiovascular disease (emergency department visits for heart attacks) Low birth-weight infants Environment Ozone concentrations in air PM2.5 concentrations in air Diesel particulate matter emissions Drinking water contaminants Children’s lead risk from housing Use of certain high-hazard, high-volatility pesticides Toxic releases from facilities Toxic cleanup sites Groundwater threats from leaking underground storage sites and cleanups Hazardous waste facilities and generators Impaired water bodies Solid waste sites and facilities Transportation Traffic impacts Means of transportation to work Neighborhood characteristics: Fraction with short work commutes Mean commute travel time Number of airports Physical Children’s outcomes in adulthood: Environment % staying in same census tracts as adults % staying in same commuting zone as adults Demographic Median age Children’s outcomes in adulthood: Characteristics Number of children Age distribution Neighborhood characteristics: Total population Fraction non-white Sex distribution Foreign-born share Population density Ethnicity distribution Race distribution LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 20 Issue Brief: Using Data Tools to Compare Regional Economic Well-Being in California November 2022 Notes 1. Governor’s Office of Planning and Research, Labor and Workforce Development Agency, Governor’s Office of Business and Economic Development. “Finalized CERF Regions and Responses to Frequently Asked Questions.” https://opr.ca.gov/economic- development/cerf/docs/20211217-CERF_Final_Regions_FAQ.pdf. 2. Find the current list of California MSA’s here: https://www. labormarketinfo.edd.ca.gov/definitions/metropolitan-statistical- areas.html. Also, U.S. Census Bureau. “Glossary.” https://www. census.gov/programs-surveys/metro-micro/about/glossary.html. 3. Coline Bodenreider, MPH, et al. Public Health Alliance of Southern California. “Health Places Index 3.0.” Page 32. March 31, 2022. https://www.assets.website-files. com/613a633a3add5db901277f96/624a02bba72d6628b96ae461_ HPI3TechnicalReport2022-03-31.pdf. 4. Governor’s Office of Planning and Research, Labor and Workforce Development Agency, Governor’s Office of Business and Economic Development. “Community Economic Resilience Fund Program (CERF) Proposed Economic Regions for High Road Transition Planning Grants: Released for Public Comment.” https://www.edd. ca.gov/siteassets/files/Jobs_and_Training/pubs/wsin21-20att1.pdf. 5. U.S. Bureau of Labor Statistics. “Unemployment Rate in Riverside- San Bernardino-Ontario, CA (MSA).” Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/ RIVE106URN. 6. U.S. Bureau of Labor Statistics. “Unemployment Rate in Fresno, CA (MSA).” Retrieved from FRED, Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/FRES406UR. Issue Brief: Using Data Tools to Compare Regional Economic Well-Being November 2022 (916) 445-2125 | LittleHoover@lhc.ca.gov 925 L Street, Suite 805, Sacramento, CA 95814 LITTLE HOOVER COMMISSION WWW.LHC.CA.GOV | 21