2015 Equality Index: State of Black Kansas City

2015 Equality Index: State of Kansas City developed for The Urban League of Greater Kansas City by University of Missouri - Kansas City UMKC Institute for Human Development Kathryn L. Fuger, Ph.D. Ryan L. Gee, M.A. in partnership with UMKC Center for Economic Information Lead Researchers: Peter J. Eaton, Ph.D. Michael Kelsay, Ph.D. Douglas H. Bowles, Ph.D. with support from UMKC Office of Research and Economic Development Lawrence Dreyfus, Ph.D., Vice Chancellor for Research & Economic Development UMKC is an equal opportunity affirmative action institution. The contents are solely the responsibility of the authors and do not represent the official views or policies of the funding agency. Neither do the points of view or opinions represent official positions of the Curators of the University of Missouri. 1

OVERVIEW By Peter J. Eaton, Ph.D. Director of Center for Economic Information Department of Economics University of Missouri-Kansas City And Kathryn L. Fuger, Ph.D. Director of Early Childhood and Youth Programs Institute for Human Development University of Missouri-Kansas City The Equality Index The 2015 Kansas City Equality Index is the fourth expansion of research comparing and white Kansas City residents, which began with the 2006 State of Kansas City Equality Index. Additionally, for the first time an Equality Index for Hispanic Kansas City is added. This is reported in a separate section following the Equality Index and Appendix. Both indices follow a methodology used by the National Urban League in its most recent Equality Index publication. 1 This method compares the value of indicators in several categories for residents of Kansas City with the value of the same indicators for white residents of Kansas City, when calculating the Equality Index. The comparison made for the Hispanic Equality Index is between Hispanic residents and non-hispanic white residents of Kansas City. Both indices use data from the five most populous counties of the Kansas City Metro Area (Clay, Jackson and Platte in Missouri, and Johnson and Wyandotte in Kansas). The basic idea for the index is to examine variables that indicate the conditions of minority populations relative to the values of their white counterparts. If the numbers for minority residents are the same as those for their white counterparts, then the Equality Index equals 100. When minority residents fare worse than white residents, the Equality Index is less than 100, and when minority residents fare better than white residents, the index is greater than 100. There are five major categories of indicators, each of which is assigned a Figure 1. Components of the Equality Index relative importance to be used in 1 calculating the overall Index of Equality. The relative importance is reflected in a Economics 1 3 weight. The five major categories and Health their respective weights are displayed in Figure 1. Education For each of these major categories, a sub-index is calculated. The same Social Justice method is used to calculate each subindex, with a value of 100 meaning that Civic Engagement 3 the minority population has the same value as the white population. 1 National Urban League. (2014). State of America 2014 One Nation Underemployed: Jobs Rebuild America. Author. www.nul.org/#jobs4all 2

Each of the five sub-indices is in turn based on several sub-categories. For example, there are six sub-categories used to arrive at the Economics Sub-Index (Median Income, Poverty, Employment Issues, Housing and Wealth, the Digital Divide, and Transportation). Finally, each of these sub-categories is based on one or more individual variables. This overview of the components of the Equality Index is displayed in Figure 2. Several changes occurred over time in the design of the national index. Weights given to some categories were changed, and some variables were added and subtracted. These adjustments have not seemed to change the end result in the national index. Corresponding changes were also made to the Kansas City Equality Index. Figure 2. Overview of the Components of the Equality Index 3

The Data Collection Area Additionally, the geographic coverage of the Kansas City Equality Index expanded. The first index (2006) used data from only Jackson County, Missouri and Wyandotte County, Kansas. The current index uses data from the five most populous counties of the Kansas City Metropolitan Area: Clay, Jackson and Platte in Missouri, and Johnson and Wyandotte in Kansas. The county population numbers are used to calculate a weighted average for each indicator used in the analysis, with the weights consisting of the percentage of the (or the Hispanic) population living in each county. The Kansas City Metropolitan Statistical Area (KCMSA) consists of 15 counties (6 in Kansas and 9 in Missouri). According to the Census Bureau, the total population in 2013 was 2,035,334. Overall, 83% of the KCMSA population is concentrated in the five largest counties (Clay, Jackson and Platte in Missouri, and Johnson and Wyandotte in Kansas). An even larger percentage of the, non-hispanic population (95%) and the Hispanic population (93%) is concentrated in these five counties. Virtually all of the population growth in the MSA since 2000 is due to growth in the Hispanic population. Because the great majority of minority populations live in the five most populous counties, we have restricted ourselves to data from these counties in the calculation of both the Equality Index and the Hispanic Equality Index. In addition, since these counties have larger populations, the American Community Survey data about residents of these counties will be timelier. Table 1 presents a tabulation of the Kansas City population by county and by racial/ethnic combinations. The shaded cells signify the populations that are included in the calculation of most of the Equality Indices, Sub-Indices, and components. Please refer to Appendix C for detailed maps of the Kansas City region. Table 1. Fifteen-County Kansas City Population by Race/Ethnicity County Non- Hispanic Non- Hispanic Hispanic 5-County Area Other* All Races/ Ethnicities Jackson (MO) 427,304 159,914 56,434 643,652 30,506 674,158 Clay (MO) 186,850 11,387 13,101 211,338 10,601 221,939 Platte (MO) 75,249 5,183 4,424 84,856 4,466 89,322 Wyandotte (KS) 68,318 39,172 41,633 149,123 8,382 157,505 Johnson (KS) 446,885 23,227 38,949 509,061 35,118 544,179 5-County Area 1,204,606 238,883 154,541 1,598,030 89,073 1,687,103 Other 10 KCMSA Counties 312,631 12,758 12,142 337,531 10,700 348,231 15-County Area 1,517,237 251,641 166,683 1,935,561 99,773 2,035,334 Source: Census Bureau 2013 Population Estimates * Other includes Asian, American Indian and Pacific Islander, and those who classified themselves in 2 or more races. Comparisons of Kansas City and National Equality Indices Both the and Hispanic Equality Indices for Kansas City can be compared to the National Equality Indices. The Equality Indices in the left columns of Figure 3 depict the 2015 State of Kansas City and the 2014 State of America. Similarly, the Equality Indices in the right columns of Figure 3 show the comparison of the State of Hispanic Kansas City and the State of Hispanic America. According to the Equality Indices, and Hispanic populations of both Kansas City and the United States are only faring 71-75% as well as their white (or non-hispanic white) counterparts. 4

Index Value Index Value Figure 3. 2015 Kansas City Equality Indices and 2014 National Equality Indices Equality Index 100. 100. 10 8 71.9% 71.2% 6 2015 Kansas City Index 2014 National Index Hispanic Equality Index 100. 100. 10 75.9% 75.8% 8 6 2015 Kansas City Index 2014 National Index Hispanic Non-Hispanic The indices have changed only slightly since 2006. The National Equality Index value was 73. in 2006 and 71.2% in 2014. The Kansas City Equality Index value was 73. in 2006 and 71.9% in 2015. Clearly, no significant progress has been achieved by s nationally or locally over the past 8 years. For Hispanics, the National Equality Index value was 75.8% in 2014, and the Kansas City Equality Index value was 75.9% in 2015. The sub-indices provide more information about the areas that increase and decrease the Equality Index. Table 2 displays the Sub-Index values for both the and Hispanic populations of Kansas City and the nation. For the populations of both Kansas City and the United States, the Economic and Social Justice Sub-Indices are lowest (below 6), while the Civic Engagement Sub-Index values above 10 suggests that this area contributes the most to equality with white populations. For the Hispanic populations in Kansas City and the nation, the sub-index values are not as low. And yet, Economics, Education, Civic Engagement, and Social Justice Sub-Indices are all under 7, while the Health Sub-Index values above 10 suggests that health contributes the most to equality with non-hispanic white populations. Table 2. 2015 Kansas City Equality Indices and 2014 National Equality Indices for and Hispanic Populations Sub-Index 2015 Kansas City The Organization of This Report Equality Index 2014 United States Hispanic Equality Index 2015 Kansas City 2014 United States Economics 57.3% 55.5% 62.3% 60.6% Health 77.4% 76.8% 104.2% 102.3% Education 77.5% 76.8% 72.2% 73.2% Social Justice 52.4% 56.8% 70.3% 66.1% Civic Engagement 106.9% 104.1% 61.1% 71.2% TOTAL EQUALITY INDEX 71.9% 71.2% 75.9% 75.8% Part I 2015 Equality Index: State of Kansas City discusses the 2015 Kansas City Equality Index in more detail. It is followed by Appendix A, consisting of the data tables for the Kansas City Equality Index. In like manner, Part II 2015 Equality Index: State of Hispanic Kansas City discusses the 2015 Kansas City Hispanic Equality Index, and Appendix B presents the accompanying Hispanic Equality Index data tables. Appendix C consists of seven supplementary maps providing extensive information to supplement the indices of the Kansas City Metropolitan Core in describing the status of its residents. 5

Index Value PART I 2015 EQUALITY INDEX: STATE OF BLACK KANSAS CITY THE 2015 KANSAS CITY BLACK EQUALITY INDEX The Equality Index is developed as a compilation of information in five areas, as discussed in the Overview to this report. The importance and weight of each area was established by the National Urban League in their calculation of the National 2014 Equality Index, which we employed to calculate the 2015 Equality Index for both and Hispanic Kansas City populations. These are the areas of the subindices and their weights: Economics (3), Health (25%), Education (25%), Social Justice (1), and Civic Engagement (1). The 2015 Equality Index and five Sub-Indices are presented for the Kansas City population in Figure 4, based on information from the five most populous counties (Jackson, Clay and Platte Counties in Missouri, and Wyandotte and Johnson Counties in Kansas). As shown in the figure, the relative state of the population in Kansas City is much lower than the state of the white population, with the exception of the Sub-Index of Civic Engagement. Please note that the bar for the white population is 10 for each index, with the white condition serving as the control to which the condition is compared. Figure 4. The State of Kansas City: 2015 Equality Index and Sub-Indices 1 106.9% 10 8 6 57.3% 77.4% 77.5% 52.4% 71.9% Economics Health Education Social Justice Civic Engagement TOTAL EQUALITY INDEX Just as the Equality Index is composed of several areas, the Sub-Index for each of these areas is composed of multiple components. Again, the weights used by the National Urban League are applied to the Kansas City populations. Following is descriptive information about each sub-index of the 2015 Kansas City Equality Index and its contribution to the overall index. 6

Index Value ECONOMICS 3 OF THE EQUALITY INDEX The economics portion of the Equality Index has six components. Each component has a different weight used for the calculation of the overall Economics Sub-Index. Figure 5 displays the components of the Economics Sub-Index and their respective weights. Figure 5. Components of the Economics Sub-Index 5% 1% Median Income (25%) 25% Poverty (15%) 34% Employment Issues () Housing & Wealth (34%) 15% Digital Divide (5%) Transportation (1%) 1 3% 5% Figure 6. Distribution of Population in 5-County Kansas City Region 16% 66% Jackson County, MO Clay County, MO Platte County, MO Wyandotte County, KS Johnson County, KS Source: Census Bureau 2013 Population Estimates It is also important to remember that the population of Kansas City is concentrated in Jackson County. See the distribution of the population in Figure 6. When calculating regional values, the county value is given the weight of the proportion of the population in the county. In the Kansas City region, the Economics Sub-Index of the Equality Index for 2015 has a value of 57.3%. As presented in Figure 7, all components show economic conditions of s to be worse than the economic conditions of whites, particularly with regard to the Housing & Wealth and Poverty measures. Figure 7. Contributing Factors to the Economics Sub-Index 10 8 6 71% 43% 72% 41% 81% 69% 57% Median Income Poverty Employment Housing & Wealth Digital Divide Transportation OVERALL ECONOMICS 7

The value of the Economics Sub-Index has not Table 3. Economics Sub-Index Value over Time changed substantively between 2006 and 2015. Table 3 shows the values for this sub-index in past Index Year 2006 Kansas City 57% National 56% iterations for both the Kansas City region and 2007 57% 57% 2008 57% 57% nationally in the years that Kansas City results 2010 53% 57% were published region. Recognizing that some 2014 56% changes occurred in the index, it still seems clear 2015 57% that the Economics Sub-Index for Kansas City is varying within a small range, with no discernible trend. The variation is even smaller nationally. Key Economics Variables Each component of the Economics Sub-Index is informed by a number of individual variables that are also weighted. Prior to a discussion of the Economics Sub-Index components, it may be helpful to examine some of the actual data that contributed to the Economics portion of the Equality Index. The weight of these four variables influenced the Economics Sub-Index value the most: Median Household Income, Median Net Worth, Poverty Rate, and Rate of Home Ownership. Figure 8 displays the actual comparisons between the and white populations of the five-county Kansas City area for these variables. median household income is only 55% that of whites, and median net worth of s is less than Figure 8. Key Variables of the Economics Sub-Index $60,000 $50,000 $40,000 $30,000 $20,000 $10,000 $0 35% 3 25% 15% 1 5% Median Household Income $29,724 $54,044 6% that of whites. The poverty rate of s is more than double the poverty rate of whites, while the home ownership rate of s is 65% that of whites. Poverty Rate 29.8% 12.6% $120,000 $100,000 $80,000 $60,000 $40,000 $20,000 7 6 5 3 1 $0 Median Net Worth $6,314 $110,500 Home Ownership Rate 40.7% 62.7% 8

Components of the Economics Sub-Index The following sections examine each of the six components of the Economics Sub-Index in more detail. Each section explains the variables that are used to measure the component. Index Tables in Appendix A also display the county by county distribution of these variables. Median Income (25% of the Economics Sub-Index). There are three variables that contribute equally (are weighted equally) to the calculation of the Median Income component of the Economics Sub-Index: Median Household Income, Median Male Earnings, and Median Female Earnings. These three components measure substantially different concepts, as presented in Figure 9. For earnings, the Median Value is calculated only for those individuals with earnings, that is, only for those who are working. For both men and women, Median Earnings are over 77% of that of their white counterparts. Median Household Income includes income from all sources and is calculated for all households, not just households with earnings. Unemployment is very high for both men and women, which translates into Median Household Income that is only 55% of Median Household Income. The overall value for the Median Income Index in the Economics Sub-Index is 70.5%. The Median Income Index is substantially higher than the overall Economics Sub-Index (57.3%), so it acts to raise the Economics Sub-Index. Figure 9. Index Values for Median Income Variables 6 8 10 Median Household Income Median Male Earnings Median Female Earnings Median Income Component 55% 71% 77% 8 Poverty (15% of the Economics Sub-Index). There are four variables that enter into the calculation of the Poverty component of the Economics Sub-Index. The Overall Poverty Rate (percentage of households below the poverty line) of white households relative to that of households accounts for 6 of the value of the Poverty element. The remaining comes from the ratio of percentage of white to percentage of households in the three lowest categories of income relative to the poverty line (each of these gets one-third of the ). Because higher poverty numbers reflect a worse economic condition, we look at the percentage of white households in poverty divided by the percentage of households in poverty to get a number that grows when things become more equal. Figure 10 shows the results of the poverty calculations. The Poverty Index is 43.01%. In comparing this to the Median Income Index of 70.5%, the negative contribution of the poverty component becomes clear. The Poverty Index brings the Economics Sub-Index down. Especially alarming is the value of 33.95 for the Extreme Poverty component. This means that the percentage of households in extreme poverty is almost 3 times (2.95) as high as the percentage of white households in extreme poverty. Figure 10. Index Values for Poverty Variables 6 8 10 Households in Poverty Households in Extreme Poverty Households Slightly Below Poverty Households Slightly Above Poverty Poverty Component 34% 42% 43% 47% 54% 9

Employment Issues ( of the Economics Sub-Index). There are five variables that enter into the calculation of the employment issues element of the Economics Sub-Index. Each of these five variables is designed to capture a specific employment issue. The first two speak to availability of jobs, and so capture both macroeconomic effects and the suitability of the skill set of s relative to the skill set of whites. Labor Force Participation speaks to engagement in the economy. A person who is either working or looking for work is a labor force participant. The Percentage of the Population Not in the Workforce speaks to heath and the age distribution of the population over 16, relative to the white population over 16. The Employment to Population Ratio is a measure of the degree of dependence on the workers of the versus white populations. For the first three of these variables, higher numbers imply worse economic conditions, so the variables enter as the ratio of white to. For the last two variables, higher numbers imply better economic conditions (higher engagement or lower dependence), so the variables enter as the ratio of to white. Figure 11 summarizes the results for employment issues. There are substantial differences between the values for the different variables that enter into the overall Employment Issues component index of 72.2%. For both men and women, the Civilian Unemployment Rates for s are over double the rate for whites. However, the Labor Force Participation rate for s is over 95% of the Labor Force Participation rate for whites. Clearly, the major difference between employment issues of whites and s in the high unemployment rate of s. Figure 11. Index Values for Employment Issues Variables 6 8 10 Male Unemployment Rate Female Unemployment Rate Percent of Population 16+ Not in Workforce Labor Force Participation Rate Employment to Population Ratio Employment Issues Component 44% 46% 72% 9 96% 89% Housing and Wealth (34% of the Economics Sub-Index). Each of eight variables in the Housing and Wealth element is designed to capture a specific housing or wealth issue. Since the single most important source of wealth is the value of the home, housing and wealth are combined into one element of the Economics Sub-Index. Four variables are deemed less important, with a total weight of approximately 8%, whereas the other four are each accorded a weight of over. The overall value for the Housing and Wealth component is 41.3%. Among the six components of the Economics Sub-Index, this is the lowest value. It also has the highest weight of the six components. The Housing and Wealth indicator is therefore the biggest contributor to poor performance in the Economics Sub-Index for residents of Kansas City. One factor stands out in Figure 12. The Median Net Worth variable has a value of 5.71%. This is an order of magnitude smaller than any other economic indicator. Among the eight variables used to compute the Housing and Wealth Index, the Median Net Worth has the highest weight. The reason for the low value of this indicator goes back to the fact that the main source of wealth for Americans is the value of the home. The median household does not own a home (less than 5 of households own their home), and therefore, there is zero wealth from the home for the median 10

household. Almost 7 of white households own their home in the Kansas City region, and therefore, have wealth from the home in the form of home equity. 2 Figure 12. Index Values for Housing and Wealth Variables 6 8 10 Home Ownership Rate Percent of Housing Units Mortgaged Percent of Housing Units Owned Outright Percent of Housing Units Renter Occupied Mortgage Denial Rate Home improvement Loan Denial Rate Percent of High Interest Loans Denied Median Household Net Worth Housing and Wealth Component 6% 58% 63% 44% 51% 56% 5 49% 41% The Digital Divide (5% of the Economics Sub-Index). The Digital Divide Index is based on a single variable, and is therefore the most straightforward component of the Economics Sub-Index. The variable is the ratio of the percentage of individuals living in households with access to the Internet to the percentage of individuals in white households with access to the Internet. Because data for the Kansas City region were not available, we used the national value as a proxy. The national value of the Digital Divide Index is 81.3%. Nationally, the Percentage of Individuals Living in Households with Access to the Internet is 68. for individuals and 83.6% for white individuals. The Digital Divide Index is the highest of the six Economics Sub-Index components, and thus, makes the Economics Sub-Index larger than it would otherwise be. There is no variation in our measure across the five counties because we used this national value. Transportation (1% of the Economics Sub-Index). The three variables that enter into the calculation of the Transportation element of the Economics Sub-Index are shown in Figure 13. Because of the view that use of public transport for work is a negative transportation variable in the Economics Sub-Index, and riding alone to work is a positive transportation variable, the index value of the Transportation component is 69.. The variable with the clearest interpretation in the Transportation category is Car Ownership, although this variable might be more appropriate to use in the Wealth Index. The value for this variable is over 88%. Figure 13. Index Values for Transportation Component Variables 6 8 10 Car Ownership Rate Percent Transportation to Work Driving Alone Percent Transportation to Work Using Public Transportation Transportation Component 24% 69% 89% 94% 2 For the national study (State of America, 2014) the survey of income and program participation was the source for the median household net worth. The sample is not large enough to be used for any one region. We therefore use the national number as a proxy for the regional number. The same reasoning (low home ownership among households) is relevant regionally, as it was used nationally for expecting the net worth of households to be extremely low, relative to the net worth of white households. 11

Index Value HEALTH 3 OF THE EQUALITY INDEX The health portion of the Equality Index has ten components. Each component has a different weight used for the calculation of the overall Equality Index. Figure 14 displays the components of the Health Sub-Index and their respective weights. 1% 4% 3% 1 5% 2% 1 Figure 14. Components of the Health Sub-Index 1 Death Rates & Life Expectancy Physical Condition Substance Abuse Mental Health 45% Access to Care Elderly Health Care Pregnancy Issues Reproduction Issues Delivery Issues Children's Health 1 In past reports there have been only three components of the Health Sub-Index: Death Rates and Life Expectancy (45%), Lifetime Health Issues (3), and Neonatal and Pediatric Care (25%). The latter two contained some of the other nine elements listed above. In the Kansas City region, the Health Sub-Index for the Equality Index for 2015 is 77.4%. Figure 15 displays the index values of the components of the 2015 Health Sub-Index. Figure 15. Contributing Factors to the Health Sub-Index 1 103% 10 91% 8 6 63% 71% 59% 54% 64% 47% 46% 61% 77% 12

Years Table 4 shows the values for this sub-index in past Table 4. Health Sub-Index Value over Time iterations for both the Kansas City region and nationally in the years that Kansas City results were published Index Year 2006 Kansas City 8 National 76% 2007 82% 78% region. Keeping in mind that changes in the indices 2008 83% 76% themselves prevent strict comparability over time, the 2010 78% 77% Health Sub-Index is relatively stable. It is consistently an 2014 77% order of magnitude higher than the Economics Sub- 2015 77% Index. The Health Sub-Index in the Kansas City region is also consistently slightly above the Health Sub-Index for the nation. Key Health Variables Before examining the components of the Health Sub-Index in detail, it is helpful to note four individual variables measured in the Health Sub- Index that contributed the most to the Health Sub-Index value: Age-Adjusted Death Rate, Life Expectancy at Birth, Percentage of Adults Who Are Overweight or Obese, and Fetal Deaths. Figure 16 displays the comparisons of and white populations in the five-county Kansas City area for these variables. The Death Rate is somewhat worse than the Death Rate for whites, with the index value of 86% suggesting that s are faring 86% as well as whites. Life Expectancy at Birth, however, is almost identical (index value of 99%). The Incidence of Obesity is almost one-third higher for s than whites (index value of 71%). The Fetal Death Rate for s is more than double the rate for whites (index value of 39%). Components of the Health Sub-Index Figure 16. Key Variables of the Health Sub-Index Age-Adjusted Death Rate per 100,000 800 750 700 650 600 550 500 872 The following sections examine each of the components of the Health Sub-Index in more detail. Each section explains the variables that are used to measure the component. Death Rates and Life Expectancy (45% of the Health Sub-Index). Two variables contribute to the calculation of the Death Rates and Life Expectancy component of the Health Sub-Index: Life Expectancy 750 Life Expectancy at Birth 80 75 70 65 75.0 76.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 Fetal Deaths Per 1,000 7.4 2.9 Percent Adults Who Are Overweight or Obese 5 39.9% 3 1 28.1% 13

at Birth, and Age-Adjusted Death Rate per 100,000 from All Causes. Life Expectancy accounts for onethird of this component, and Age-Adjusted Death Rate accounts for two-thirds of this component. Figure 17 shows that both of the variables in this component of the Health Sub-Index are above the total Health Sub-Index score, indicating that this set of variables tends to raise the Health Sub-Index. The index value of the Death Rates and Life Expectancy component for residents of Kansas City is 91.2%. Figure 17. Index Values for Death Rates and Life Expectancy Variables 6 8 10 Life Expectancy at Birth Age-Adjusted Death Rates per 100,000 Death Rates and Life Expectancy Component 94% 9 91% Physical Condition (1 of the Health Sub-Index). There are four variables that contribute to the calculation of the Physical Condition component of the Health Sub-Index. Figure 18 shows that there is substantial variation in the values for these variables measured for s, relative to those measured for whites. The Incidence of HIV/AIDS among s is over 26 higher than that that of whites, while the Incidence of Being Slightly Overweight is 9.5% higher among s than among whites. Among these variables, only the Incidence of Being Slightly Overweight increases the Health Sub-Index. The Physical Condition Index for residents of Kansas City is 62.6%. Therefore, the Physical Condition variables serve to reduce both the Health Sub-Index and the overall Equality Index. Figure 18. Index Values for Physical Condition Variables 6 8 10 Overweight/Obese Adults (BMI=25.0-29.9) Overweight/Obese Adults (BMI>=30) Diabetes Rate per 100,000 HIV/AIDS Rate per 100,000 Physical Condition Component 38% 63% 71% 72% 91% Substance Abuse (1 of the Health Sub-Index). There are three variables that contribute to the calculation of the Substance Abuse component of the Health Sub-Index. Figure 19 shows that, with the exception of Illicit Drug Use, Substance Abuse does not contribute to inequality. The Substance Abuse Index is 102.7%, indicating virtual equality between s and whites for these variables. The Incidence of Illicit Drug Use is about higher among s than among whites. The other two measures of substance abuse have higher incidence among whites than among s. The data that were used for these three variables are only available by race at the state level. There may be substantial differences in variables measured at the state level from those same variables measured at the metropolitan area level, so we should view these results very cautiously. For example, in both the states of Kansas and Missouri, the Incidence of Tobacco Use is higher in rural counties than in urban counties. If there are rural to urban behavioral differences, then using the state numbers would tend to bias the estimate for the Kansas City Region. Figure 19. Index Values for Substance Abuse Variables 6 8 10 1 Incidence of Binge Drinking Incidence of Illicit Drug Use Incidence of Tobacco Use Substance Abuse Component 81% 103% 103% 124% 14

Mental Health (2% of Health Sub-Index). The variables used to measure Mental Health are all from a survey of youth behavioral risk done in 2013. For this reason, they should be considered, at best, as indicators of the mental health of youths. All three variables are tallies of Students Who Considered Suicide, classified by sex, as displayed in Figure 20. There is more variation by sex than there is by race. The percentage of white females who considered suicide is higher than the percent of males. Still, for both genders, a substantially higher percentage of the student population considered suicide than the corresponding white population. The data for this component are available only at the five-county Kansas City region level, so a county breakdown was not possible. The Mental Health Component Index is 71.1%. Figure 20. Index Values for Mental Health Variables 6 8 10 Students Who Considered Suicide - Total Students Who Considered Suicide - Male Students Who Considered Suicide - Female Mental Health Component 62% 72% 71% 79% Access to Care (5% of Health Sub-Index). Figure 21 shows that the Access to Care variables overall contribute negatively to both the Health Sub-Index and the overall Equality Index for residents of Kansas City. The Quality of Health variables listed here are self-reported, reflecting how individuals feel about their own health; they are not based on an assessment of health by health professionals. For those two variables (the Percent of the Population that Felt that They Were in Poor to Fair Health and the Percent of the Population that Felt that They Were in Excellent Health), there is more equality than for the two Access to Insurance variables. The percentage of s without health insurance is roughly twice that of whites. The percentage of adults (18-64) with health care is roughly twice as high for whites as it is for s. These data are only available at the state level, so no county breakdowns are possible. All Access to Care indices are lower in Kansas than in Missouri. There is a substantial difference in the Excellent Health variable between Missouri (which has an index of slightly over 10) and Kansas (which has an index of slightly below 5). The index value for the Access to Care component for s is 59.2%. Figure 21. Index Values for Access to Care Variables 1 3 5 6 7 8 9 10 Fair or Poor Health People without Health Insurance Adults 18-64 with Health Insurance Excellent Health Access to Care Component 52% 57% 59% 82% 87% Elderly Health Care (3% of Health Sub-Index). Figure 22 shows that Elderly Care contributes negatively to both the Health Sub-Index and the overall Equality Index for residents of Kansas City. The percentage of residents of the Kansas City region covered by Medicaid (15.1%) is almost three times that of whites (5.6%). Average Medicare expenditures were higher for s ($23,047) than for whites ($16,474). Both of these data were available at the five-county regional level, so a county breakdown is impossible. The Elderly Care Index is 54.3%. 15

Figure 22. Index Values for Elderly Health Care Variables 6 8 10 Population over 65 Covered by Medicaid Medicare Expenditures per Beneficiary Elderly Health Care Component 37% 54% 71% Pregnancy Issues (4% of Health Sub-Index). Figure 23 shows that Pregnancy Issues also contributed negatively to both the Health Sub-Index and the overall Equality Index for residents of Kansas City. Among these eight indicators, six have index values below 6. Only the Smoking during Pregnancy indicator has a value over 10, indicating that the incidence of smoking during pregnancy is higher among white women than among women in the five-county region. Recall that Infant and Maternal Mortality also have very low index values. These is an obvious connection between these two elements. The Pregnancy Issues Component Index is 63.95%. The Pregnancy Issues data are available by county. However, there is some variation in the set of variables that were used. Only the six variables that were measured in all five counties are included in Table 16 below, plus the overall score. 3 Recall that the population of Platte and Clay Counties is very small, and therefore there is high sampling error associated with the data. In the county with the highest population (Jackson), the overall Pregnancy Issues Index is the lowest. The finding of a high index value for mothers who smoked during pregnancy is consistent across counties. Other common variables have roughly the same outcome across counties. Figure 23. Index Values for Pregnancy Issues Variables 6 8 10 1 Prenatal Care Begins in First Trimester Inadequate Prenatal Care Prior Live Births (Mother Under 20) Percent of Live Births to Unmarried Mothers Cause of Death Due to Pregnancy Complications Mothers Smoked During Pregnancy Low Birth Weights (<2500 g) Very Low Birth Weights (<1500 g) Pregnancy Issues Component 38% 54% 53% 58% 58% 53% 64% 8 118% Reproduction Issues (1% of Health Sub-Index). The indicator of Reproduction Issues is represented by one variable, Frequency of Abortion. We use this variable because the national index uses this variable. It is unclear why this variable is chosen to represent Reproduction Issues. Since there is only one variable, a figure is unnecessary. The index value for the Reproduction Issues component is 47.3%, indicating that abortions are twice as frequent among the population as among the white population. These data are available for the five counties of the Kansas City Region. For Jackson County, Missouri, the county with the highest population, the index is 51%. The smallest value for the index is for Johnson County, Kansas, which has a value of 26%. 3 For Missouri the additional two variables were Prior Live Births to Mothers over 20, and Percent of Live Births to Unmarried Mothers. For Kansas, the two additional variables were Spacing of Children less than 18 Months Apart and Percent of Mothers with Weight Gain over 44 Pounds. 16

Delivery Issues (1 of the Health Sub-Index). There are two variables that contribute to the calculation of the Delivery Issues component of the Health Sub-Index. Infant Mortality and Maternal Mortality are weighted equally within this component. Figure 24 shows that Delivery Issues contribute negatively to the Health Sub-Index and to the overall Equality Index. The index value of the Delivery Issues component is 46.4%. Both infant and maternal mortality have indices below the Health Sub-Index and below the overall Equality Index. It is possible that there is a downward bias to our regional estimate. For Maternal Mortality, there were no data available for Missouri or Kansas, so we used national data to estimate the index. There is reason to expect that the national data overstate Maternal Mortality. We have access to county level Infant Mortality data, and those numbers result in a higher index for the five-county Kansas City region than for the nation (55.9% versus 43.3%). A high correlation is expected between infant mortality and maternal mortality. If infant mortality for the population is smaller in the five-county Kansas City region than in the nation, then it would be expected that Maternal Mortality would be lower in the region than in the nation. By using the national data, we therefore may be biasing the index downward. The national index value for the Delivery Issues component is 38.5%. There is no excuse in a country that spends one-sixth of its Gross Domestic Product on health care, for the extremely high values of Infant and Maternal Mortality observed in the nation and in the five-county Kansas City Region. The extremely high values of Infant and Maternal Mortality justify a public health policy aimed at reducing these high numbers. Figure 24. Index Values for Delivery Issues Variables 1 3 5 6 7 8 9 10 Infant Mortality Maternal Mortality Delivery Issues Component 37% 46% 56% Children s Health (1 of the Health Sub-Index). There are five variables that contribute to the calculation of the Children s Health component of the Health Sub-Index. Figure 25 shows that Children s Health contributes negatively to the Health Sub-Index and to the overall Equality Index. The Children s Health Index is 59.51%. For the variables with the two lowest index values the Incidence of Uninsured Children and Obesity among Adolescent Girls the incidence is twice as high for s as it is for whites. These two variables make up almost half (47.5%) of the Children s Health component. Adolescent Obesity among Boys is much less prevalent (19.8%) than it is among girls (39.2%). Among the Children s Health variables, Obesity among boys is the only index that is higher than the Health Sub-Index and the overall Equality Index. Figure 25. Index Values for Children's Health Component Variables 6 8 10 Uninsured Children Medicaid Insurance among Children Private Health Insurance Coverage for Children Obesity Incidence among Boys 12-19 Obesity Incidence among Girls 12-19 Children's Health Component 5 5 57% 6 64% 84% 17

Index Value EDUCATION 25% OF THE EQUALITY INDEX The Education portion of the Equality Index has five components. Each of the components has a different weight used for the calculation of the overall Education Sub-Index. Figure 26 presents the five components of the Education Sub-Index and their respective weights. Figure 26. Components of the Education Sub-Index 1 1 25% Education Quality Attainment Scores Enrollment 25% Student Status & Risk Factors 3 In 2009, the National Equality Index lowered the weight for the Education Sub-Index from 3 to 25%. Additionally, weights of the Education components changed in 2008, giving lower weight for the Education Quality component, while increasing the Attainment and Scores components. As a result of these changes, the indices are not strictly comparable over time. In the Kansas City region, the Education Sub-Index for the 2015 Equality Index is 77.5%, compared to the 2014 National Education Sub-Index for the Equality Index of 76.8%. The index means that s in Kansas City are performing worse educationally than whites in Kansas City, but marginally better that their national counterparts. Figure 27 presents a summary of the Education Sub-Index and its components, along with their respective index values. An examination of key contributing variables and the components of the Education Sub-Indices reveals why this is the case. Figure 27. Contributing Factors to the Education Sub-Index 1 136% 1 10 8 6 83% 83% 56% 42% 78% Education Quality Attainment Scores Enrollment Student Status & Risk Factors OVERALL EDUCATION 18

% of 25+ Population % of 25+ Population Points Key Education Variables Prior to discussing the strategy for collecting data for the Education Sub-Index in the Kansas City Region, it is important to note these individual variables that had substantial weight within the Education area: Percentage of Classes Taught by Highly Qualified Teachers, Composite ACT Score, Percentage of Adults (25 and Older) Who Are High School Graduates, and Percentage of Adults (25 and Older) with More Education than a High School Diploma. Figure 28 shows these comparisons between the and white populations of the five-county Kansas City area. A slightly lower percentage of classes are taught by highly qualified teachers for than white students, with students faring approximately 95% as well as white students. ACT Composite scores for s had about one-third fewer points than scores for whites. Highest educational attainment of high school graduation (which is 5% higher for s than whites) and education beyond high school (which is almost 1 lower for s than whites) are two of the education variables in the range of all categories that are combined into the Attainment component for the Kansas City region. Education Sampling Design Figure 28. Key Variables of the Education Sub-Index 10 95% 9 85% 8 45% 35% 3 25% 15% 1 5% Classes Taught by Highly Qualified Teachers 93.8% The strategies for gathering the information needed to determine the Kansas City Education Sub- Index were unique to Kansas City, creating a need for different solutions in the five counties and their many school districts. State level and school district level data were available for some of the components needed to calculate the Kansas City Education Sub-Index. But collecting some data elements was challenging because of differences in their enrollment of both and white students and in their collection of different types of education data. We employed the following sampling strategy to collect some of the Education data from each county to construct the Education Sub-Index. 99.2% High School Diploma 33.9% 28.6% 25.0 20.0 15.0 10.0 5.0 0.0 7 6 5 3 1 Composite ACT Score 14.5 50.2% 22.8 More Education than High School Diploma 59.7% 19

Jackson County, Missouri. To facilitate a comparison between a education and a white education in Jackson County, we chose (a) an elementary school and a high school that were predominantly and (b) an elementary school and a high school in Jackson County that were predominantly white. We selected Troost Elementary (96% ) and Greenwood Elementary (93% white) for comparison of educational performance at the elementary school level. At the high school level, we selected Central Academy of Excellence High School (94% ) and Blue Springs South High School (79% white). Clay and Platte Counties, Missouri. Data were not available to select schools that were predominantly, as a result of a small population of students in these counties. For comparison, we accessed summary statistics on education benchmarks and scores for an elementary school and high school in each county. In Clay County we selected Nashua Elementary (78% white) and Staley High School (77% white). In Platte County, we selected Central Elementary (85% white) and Platte High School (81% white). Wyandotte County, Kansas. We chose (a) an elementary school and a high school in Wyandotte County that were predominantly and (b) an elementary school and a high school in Wyandotte County that were predominantly white to analyze the quality of education received across some of the Education components. We selected JFK Elementary (69% ) and Edwardsville Elementary (71% white) for comparison of educational performance at the elementary school level. At the high school level, we selected Washington High School (61% ) and Bonner Springs High School (68% white). Washington High School is 61., and Bonner Springs High School is 67.5% white. Johnson County, Kansas. Data were not available to select any predominantly elementary or high school for comparison to predominantly white schools, due to the small population of students at the individual school level. However, the State of Kansas does provide elementary and high school performance measures of and white students at the school district level. We accessed performance benchmarks at the district level for USD 512, Shawnee Mission Public Schools. Components of the Education Sub-Index Education Quality (25% of Education). There are two important components of the Education Quality Index. They are the Quality of Teaching and the Quality of Course Offerings. These data were gathered from the Missouri Comprehensive Data System and the Kansas Department of Education and utilized according to the sampling design described above. The Education Quality component is summarized in Figure 29. The index value of the Education Quality component (82.7%) is higher than both the Education Sub-Index (77.5%) and the Equality Index (71.9%), therefore making both higher than they would be in the absence of this measure. Figure 29. Index Values for Education Quality Variables 6 8 10 Teacher Quality Course Quality Education Quality Component 56% 81% 85% Education Attainment (3 of Education.) In order to measure Attainment, we examined the Highest Educational Level of Individuals Ages 25 and Over. At the lower end of the educational spectrum, we calculated the percentage of the population aged 25 and over with Less than a Ninth Grade Education. At the upper end of the educational spectrum, we calculated the percentages of the population aged 25 and over with a Bachelor s Degree, and with a Graduate or Professional Degree. The data for these variables 20

are from the American Community Survey. Each index compares the attainment of the population over 25 to that of the white population over 25. We also calculated High School Graduation Rates and Dropout Rates. The data for these rates are from the respective State Departments of Education. Once again, these rate compare the population to the white population. The Education Attainment component is summarized in Figure 30. Figure 30. Index Values for Education Attainment Variables 6 8 10 1 Less than 9th Grade 9th-12th Grade, No Diploma High School Graduate Some College, No Degree Associate's Degree Bachelor's Degree Graduate or Professional Degree High School Graduation Rate Dropout Rate Education Attainment Component 59% 57% 59% 68% 64% 91% 125% 1 114% 11 The index for the first two categories is the ratio of the percent of the population over 25 to that of the white population over 25. The index for the next five categories is the ratio of the percent of the white population over 25 to that of the population over 25. The index value of the Education Attainment component (82.9%) is higher than both the Education Sub- Index and the Equality Index. Overall, this component contributes to more equality than there would be without this component. There are variables within Education Attainment that contribute to more inequality, however. In particular, the percentage of the population over 25 with a Bachelor s Degree or Higher is only a little over half that of the white population over 25. Education Scores (25% of Education). For the Education Scores component, we once again were faced with inadequate data, and so resorted to comparing predominantly schools with predominantly white schools in Jackson and Wyandotte Counties, while comparing students to white students in Johnson County USD 512. (See the previous section, entitled Education Sampling Design, for more details.) For this component, Elementary Readiness was weighted at 1, Elementary Test Scores were weighted at, and High School Test Scores were weighted at 5. Proficiency test scores at the elementary and secondary school level were the most readily available data. Data were not available in Clay County or Platte County, Missouri. The Missouri Department of Elementary and Secondary Education reports a Missouri School Improvement Program (MSIP5) Achievement Level Report at the school level on a variety of subject matters at a variety of grade levels. The MSIP5 program is Missouri s accountability system for reviewing and accrediting public school districts, outlining the expectations for student achievement with the ultimate goal of each student graduating ready for success in college and careers. The overall score is comprised of scores for each Local Education Agency (LEA) and school. The overall score includes scores for each of MSIP5 performance standards: (1) Academic Achievement, (2) Subgroup Achievement, (3) High School Readiness (K-8 Districts) or College and Career Readiness (K-12 Districts), (4) Attendance Rates, and (5) Graduation Rates (K-12 Districts). Information about this system can be found at this website: http://dese.mo.gov/sites/default/files/msip-5-comprehensive-guide-3-13_1.pdf. 21

The Education Scores component is summarized in Figure 31. While there are slight differences in the variables that are used to measure achievement in reading, math, science and social science in the two states, we feel that they are sufficiently comparable to be grouped together. This figure paints a negative picture for the ability of the region s educational system to educate children. From Preschool Scores that are nearly equal, the relative scores of s get worse with more years of education. The index of the Education Scores component (56.4%) is much lower than both the Education Sub-Index and the Equality Index. Thus, this component contributes to more inequality and points to disadvantages s may have in high schools, in colleges, and ultimately in the labor market. Figure 31. Index Values for Education Scores Variables 6 8 10 Preschool Score Elementary Scores High School Scores Education Scores Component 51% 57% 56% 94% School Enrollment (1 of Education). The School Enrollment component should be viewed with caution. The variables measure the percentage of the population enrolled in high school, the percentage enrolled in college, and the percentage of the population between 3 and 34 that is enrolled in any level of schooling. Recall that in the Health Sub-Index, we found that life expectancy is lower and that death rates are higher for the population than for the white population. Because the population is likely to have shorter lives, finding the percentage of the population that is enrolled in school give a biased result may be biased because there is a higher percentage of the population that is of school age. It may also be true that it takes more years to graduate for the population. Figure 32 summarizes the School Enrollment component. The value for this component (136.2%) is much higher than the Education Sub-Index or the Equality Index. Figure 32. Index Values for School Enrollment Variables 6 8 10 1 1 16 School Enrollment Ages 3-34, % of Population Percent Enrolled in High School Percent Enrolled in College (Undergraduate or Graduate) School Enrollment Component 136% 149% 124% 136% Student Status and Risk Factors (1 of Education). All of the variables included in this category indicate students who have a high probability of leaving school, and thus, do not obtain the reward of an education. Because the performance of children at school is linked to conditions in their households, these variables were selected: (1) Poverty, (2) Children with No Parent in the Labor Force, (3) Attendance, and (4) Students Eligible for Free Lunches. Discipline variables that are indicative of the high probability of children being removed from mainstream classrooms were also included: (1) Discipline Offenses, (2) Suspensions, (3) Felonies, and (4) Misdemeanors. Different variables are available for different counties, so it is not possible to produce a meaningful graphic portrayal of this component. The index value for this component is 42.2%. This value is well below the Education Sub-Index and the Equality Index, thereby contributing to more inequality. 22

Index Value SOCIAL JUSTICE 1 OF THE EQUALITY INDEX The Social Justice portion of the Equality Index has two components. Each of the components has a different weight used for the calculation of the overall Social Justice Index. Figure 33 presents the components of the Social Justice Sub-Index and their respective weights. Figure 33. Components of the Social Justice Sub-Index 3 Equality before the Law Victimization & Mental Anguish 7 These weights are the same weights that have been used by the National Urban League since 2010. 4 While the weights are the same, there have been some changes in the selected variables, as well as the weights of certain variables that have been used to calculate the values. For example, the Average Prison Sentence was weighted at of the Equality before the Law component in 2014; in 2010, it was weighted at only 3% of the component. As a result of these changes, the indices are not strictly comparable over time. In the Kansas City region, the Social Justice Sub-Index for the 2015 Equality Index was 52.4%. At the national level, the Social Justice Sub-Index for the 2014 Equality Index was 56.8%. In part, this lower sub-index value means that s in the Kansas City region are not only faring markedly worse than whites; they are also doing more poorly than s across the United States, as measured by the national Social Justice Sub-Index. Figure 34 presents the components of the Social Justice Sub-Index and their respective index values. The relative experience of the white population is represented by the horizontal grey bar. Figure 34. Contributing Factors to the Social Justice Sub-Index 10 8 6 56% 44% 52% Equality before the Law Victimization & Mental Anguish OVERALL SOCIAL JUSTICE 4 The National Urban League prepared an alternative estimate for the Social Justice Sub-Index although it is not contained in their written report. In the alternative index, they changed the overall weights of the components. In their alternative, they weighted Equality before the Law at 55%, rather than 7, and they weighted Victimization and Mental Anguish at 45%, rather than at 3. The national Social Justice Sub-Index in the National Urban League report under this alternative weighting was 47.1%. We calculated the Kansas City Social Justice Sub-Index under this alternative weight to have the value of 45.6%. 23

% of Victims Years Key Social Justice Variables Two important variables carried the greatest weight in the calculation of the Social Justice Sub-Index. These variables are the Average Prison Sentence for All Offenses and the Murder Victimization Rate. Figure 35 shows the difference in years between the average length of prison sentences for s and for whites. The average for s is 7.2 years, and the average for whites is 5.5 years. The index value for this variable is 76.4%, documenting s having noticeably longer prison sentences, compared to those of whites. Even more dramatic differences are apparent in the Murder Victimization Rate, with 77% of victims from the population, compared to of the victims from the white population. The index value of 26. for this variable shows that s are only doing 26% as well as whites with regard to this gravely serious condition. Social Justice Sampling Design Figure 35. Key Variables of the Social Justice Sub-Index 8 6 Murder Victimization Rate 77. Jackson, Clay, and Platte Counties of Missouri. The sources of our crime statistics for the three Missouri counties Jackson, Clay, and Platte were various data from the Police Department, the State of Missouri, the Missouri Sentencing Advisory Commission, and other criminal justice related sources. Thanks to the availability of unique local data from local law enforcement agencies that are compiled and published by the Missouri Attorney General s Office, we have reviewed and compiled statistics by local law enforcement agencies that allowed us to partially answer the question of Equal Treatment under the Law for s and whites in Kansas City. We aggregated the vehicle stops reports for 2013 up to the county level for Jackson, Clay, and Platte Counties in Missouri. In Jackson County, 18 law enforcement agencies provided vehicle stops data to the Attorney General Office, while 17 and 12 law enforcement agencies provided vehicle stops data for Clay County and Platte County, respectively. Four variables were aggregated that address the issue of Racial Profiling as it pertains to traffic stops by law enforcement: Search Rate Arrest Rate Contraband Hit Rate Disparity Index Wyandotte and Johnson Counties of Kansas. Data were not available from Wyandotte County, Kansas, and Johnson County, Kansas. 20. Average Prison Sentence for All Offenses 8.0 6.0 4.0 2.0 0.0 7.2 5.5 24

Components of the Social Justice Sub-Index Equality before the Law (7 of Social Justice). The largest category in the Social Justice Sub-Index addresses Equal Treatment before the Law in our region. A value of 10 for the Equality before the Law component index would mean that we live in a colorblind region. Figure 36 summarizes the Equality before the Law component, with an index value of 56.1%. The region is, therefore, far from a colorblind region. This component is about the same as the Social Justice Sub-Index and is well below the Equality Index. It therefore contributes strongly to the inequality of the region. There are major differences in the index values for the variables that make up the Equality before the Law component. In particular, the Incarceration Rate for whites is less than 25% of the Incarceration Rate for s in both Missouri and Kansas. In general, the indicators for Kansas have much lower index values than do the indicators for Missouri. More information about these differences is available in Appendix A. Figure 36. Index Values for Equality before the Law Component Variables 6 8 10 Racial Profiling (Jackson, Clay, Platte) Traffic Stops (Jackson, Clay, Platte) Probably Cause/Search Authority (Jackson, Clay, Platte) Incarceration Rate (MO) Prison Sentencing (KCMO) Offense Rate (KS) Probation Sentences (KS) Incarceration Rate (KS) Prisoners as % of Arrests (KS) Equality before the Law Component 22% 21% 27% 14% 21% 56% 81% 8 96% 96% Victimization and Mental Anguish (3 of Social Justice). Figure 37 summarizes the Victimization and Mental Anguish component of the Social Justice Sub-Index. The component index value is 44.2%, indicating that this component contributes strongly to inequality. The Homicide Rate in the region is almost five times as great among the population as it is among the white population. The Homicide Victimization Rate is four times as large for the population as it is for the white population. This component is among the lowest of all components, even though the two elements pertaining to Students Carrying Weapons are over 10. Figure 37. Index Values for Victimization & Mental Anguish Component Variables 6 8 10 1 Homicide Rate Murder Victims (Jackson County Only) Prisoners Under Sentence of Death High School Students Carrying Weapon on School Property High School Students Carrying Weapon Victimization & Mental Anguish Component 22% 26% 18% 44% 111% 1 25

Index Value CIVIC ENGAGEMENT 1 OF THE EQUALITY INDEX The Civic Engagement component of the Equality Index has four components. Each of the components has a different weight used for the calculation of the overall Civic Engagement Index. Figure 38 displays the Civic Engagement Sub-Index components and their respective weights. Figure 38. Components of the Civic Engagement Sub-Index 1 Democratic Process Community Participation Collective Bargaining Government Employment 3 These weights are slightly different weights from those used by the National Urban League in previous publications. In 2010, Democratic Process was weighted at 5, and Collective Bargaining was weighted at 3. Community Participation and Government Employment have remained the same. As a result of these changes, the indices are not strictly comparable over time. In the Kansas City region, the Civic Engagement Sub-Index for the Equality Index for 2015 was 106.9%. At the national level, the Civic Engagement Sub-Index for the Equality Index for 2014 was 104.7%. This index value illustrates that s are slightly more civically engaged than whites locally, as well as being slightly more civically engaged than their national counterparts. The Civic Engagement Sub-Index and each of its components contribute to more equality for the population in the Kansas City region. Figure 39 summarizes the index values of the Sub-Index and each of its components, with the horizontal grey bar giving a point of reference how the white population is faring on the same components. Figure 39. Contributing Factors to the Civic Engagement Sub-Index 1 1 10 98% 98% 123% 135% 107% 8 6 Democratic Process Community Participation Collective Bargaining Government Employment OVERALL CIVIC ENGAGEMENT 26

% of U.S. Citizens 18+ Years Old % of Workers 16+ Years Old Key Civic Engagement Variables Two variables that serve as major indicators of Civic Engagement are the Percentage of U.S. Citizens 18 and Older Who Voted and the Percentage of Workers 16 and Older Who Work in the Private Nonprofit Sector. Figure 40 displays the relative equality of voting (by 63% of s and 64% of whites) and the Figure 40. Key Variables of the Civic Engagement Sub-Index Percentage of U.S. Citizens 18 Years and Older Who Voted 8 63.4% 64.3% 6 Private Nonprofit Wage and Salary Workers 1 8% 6% 4% 2% 8.7% 8.2% relative equality of participation in the workforce within the private nonprofit sector (9% of s, compared to 8% of whites). The index values of 99% and 107% indicate that s are functioning in these aspects of Civic Engagement about 99% as well as their white counterparts on voting and 7% better than whites in their employment in the private nonprofit sector. Components of the Civic Engagement Sub-Index Democratic Process ( of Civic Engagement). The Democratic process component is calculated from two variables: Registered Voters from the Population of U.S. Citizens 18 and Over Voters in the 2012 Election from the Population of U.S. Citizens 18 and Over The index value for this component is 98.3%. This value suggests relative equality in the overall experiences related to voting. In actuality, there are differences between Missouri and Kansas, with regard to the Democratic Process component. In Missouri, s were more involved in the democratic process than whites, while the opposite was true in Kansas. According to Missouri data from the 2012 election, 77% of U.S. citizens over 18 were registered to vote, compared to 75% of whites. In Kansas, 61% of s U.S. citizens over 18 were registered to vote, compared to a white voter registration percentage of 72%. Index values of 103. in Missouri and 85. in Kansas indicate that great inequality is occurring in Democratic Process in Kansas. Community Participation (3 of Civic Engagement). These two variables were used to calculate the index value for the Community Participation component: Persons Who Are Veterans of the Armed Forces, 18 and Over Private Not-For-Profit Wage and Salary Workers, 16 and Over The Community Participation component has an index value of 98.2%, suggesting that s and whites are doing as well in this component overall. It therefore contributes to equality. Across all counties in the five-county Kansas City region, more differences were seen in the status of being a Veteran of the Armed Forces. See Appendix A for comparisons across counties. 27