THE STATE OF THE NATION'S CITIES DATABASE AND MACHINE-READABLE FILE DOCUMENTATION VERSION 1.5A Norman J. Glickman, Michael Lahr, and Elvin Wyly August, 1996 CENTER FOR URBAN POLICY RESEARCH RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY 33 LIVINGSTON AVENUE, SUITE 400 NEW BRUNSWICK NJ 08901-1982 Introduction: Despite a proliferation of high-quality datasets from public and private sources over the past generation, the changing nature of the American city often eludes precise measurement. Incomparable variables, inconsistent definitions, and the inexorable expansion of metropolitan regions all present challenges in describing and analyzing recent transformations in American urban life. This database grows out of data needs of the United Nations' Habitat II Conference, to be held in Istanbul in June, 1996. As part of the United States' country report for the conference, the U.S. Department of Housing and Urban Development (HUD) contracted with the Center for Urban Policy Research (CUPR) to assemble a comprehensive database on American cities. This database presents information consistent with the needs of the Habitat II Conference, but also includes a wide array of additional variables of interest to policymakers, planners, and scholars. Database Description: Version 1.5A of the database includes approximately 2,000 variables, together presenting a comprehensive description of social and economic conditions in America's urban centers. In order to balance dataset coverage (number and diversity of variables and sources) with geographic coverage (number of cities), we narrow our focus to a hybrid list of seventy- seven cities and their sorrounding metropolitan areas. This group was defined to include the nation's fifty largest cities, along with additional cities to ensure at least one reporting unit in each state. The full array of variables is divided into six categories: 1. Employment and Economic Development (listed as "Employment" in Data Dictionary sections below): Total employment; employment growth; employment by sector; gross metropolitan product; retail sales; cost of living; unemployment. 2. Demographic Factors ("Demographic"): Population; population growth; population by race, gender, and ethnicity; number and growth of households; migration by type; age structure; 3. Housing and Land Use ("Housing"): Housing stock; housing production; crowded housing; homeownership rates; tenure; age of housing; housing segregation; housing affordability; land use. 4. Income and Poverty ("Income"): Poverty rates by race, gender, and family type; income distribution; underclass status; per capita income. 5. Fiscal Conditions and the Public Sector ("Fiscal"): Overall fiscal conditions; revenues; expenditures; transfer payments; infrastructure, transportation, and utilities; debt; voting patterns. 6. Social, Health, and Environment ("Social"): Birth and death rates; cause of death; illness, including AIDS; literacy; crime; energy costs; air and water pollution. Individual variables are defined in the Data Dictionary sections below. The first Data Dictionary section lists the variables grouped by subject; the second section lists the variables alphabetically by name. Notes and references are listed in the final portions of this document. Geographic Coverage: Associated with each city are four geographic codes: FIPS (seven-digit state and place Federal Information Processing Standard) and MSAPMSA (metropolitan statistical area and primary metropolitan statistical area) codes are based on the U.S. Census Bureau's areal definitions as of June 30, 1993. NECMAs are used in New England. To ensure at least one reporting unit in New Hampshire, we excluded Hillsboro County from the Boston NECMA and designated it as a separate unit encompassing Manchester, New Hampshire's largest city. For some variables reported at the MSA level, we combined data for Manchester, NH, and Nashua, NH for better comparability to NECMA tabulations. For comparability, two codes are taken from Kasarda's (1993) database: ST_PLAC8 (a five-digit state and place code for each central city) and KMSA (1980 SMSA designations). For thirteen cities in our database not included in Kasarda's files, the ST_PLAC8 and KMSA codes are set to negative values. The database should always be sorted and indexed on FIPS, since this is the only unambiguous and unique code for all observations. Three pairs of cities in the database share the same MSAPMSA and KMSA codes (Los Angeles and Long Beach; Minneapolis and St. Paul; Kansas City, KS, and Kansas City, MO.) Any additional adjustments or substitutions are described in the notes for each variable. Each variable is associated with one and only one code signifying the areal aggregation of the data. Extreme caution should be exercised when comparing variables with different area codes: CC: Incorporated central city, unadjusted for boundary changes. Three cities in the database are recognized by the U.S. Census Bureau as consolidated with county governments: Jacksonville, FL (Duval County); Indianapolis, IN (Marion County); Nashville-Davidson, TN (Davidson County); data for these areas refer only to the part of the central city not in the surrounding county. MSA1: Metropolitan Statistical Area, unadjusted for boundary changes. Variables using this measurement scheme refer to areas defined at particular points in time: some decennial 1980 census figures, for example, are not comparable to later tabulations using revised metropolitan area boundaries. MSA2: Metropolitan Statistical Area boundaries defined as of June 30, 1993. Where data were not collected or reported according to these criteria, we aggregated data to the 1993 MSA definitions to ensure that boundaries remain consistent across all years. Most of the metropolitan-level data drawn from the Census of Population and Housing are aggregated to the 1993 MSA definitions. CCY: Central county encompassing all or most of the respective central city. Applies only to Bureau of Economic Analysis data reported by Kasarda (1993). CBD: Central business district, the functional core of the historic central city housing its most dense agglomeration of office and retail functions. Applies only to data reported by the Society of Industrial and Office Realtors (SIOR). SUB: Suburban ring. Designates area of (unadjusted) metropolitan statistical area exclusive of central city. Applies only to data reported by the Society of Industrial and Office Realtors (SIOR). VAR Other areal reporting unit, specific to the agency or institution reporting the data. Examples include consolidated school districts, public transit jurisdictional areas, water and sewer authorities, etc. Consult source of original data for specific boundary definitions and comparability. Cautionary Notes and Request for Feedback: Any large data collection and analysis project necessarily introduces a certain amount of error, and users should be aware of the limitations of this database. First, all variables suffer from a certain degree of sampling error, which varies widely for different agencies or institutions collecting the original information; particularly serious are comparisons between decennial U.S. Census sources (which have relatively large sample sizes) and the annual Current Population Survey (which suffers from a much smaller sampling frame). For more detailed information on sampling error, consult the documentation of original sources. Second, data collected from different sources often refer to different populations; users should examine the "measurement unit (denominator or universe)" column to ensure comparability. Finally, variables collected at different levels of aggregation (central city vs. metropolitan area) are not comparable, except in the case of prior methodological grounding (e.g. multilevel modeling). Users should be aware that this database remains preliminary, and continues to undergo substantial revision and enhancements. As a general rule, we will be issuing updated versions of the database and documentation at least twice per year. The most recent version of the database is available in several different file formats at CUPR's home page on the World Wide Web (point your browser to http://www.policy.rutgers.edu/cupr, and choose "projects" from the initial menu). We would appreciate being informed of any major errors encountered by users, and we also appreciate any comments or suggestions for future improvements to this database. Send electronic mail to wyly@rci.rutgers.edu. GEOGRAPHIC CODES FOR CITIES IN THE DATABASE (Total 77 cities, 74 metropolitan areas) City FIPS ST_PLAC8 MSAPMS A KMSA Birmingham city AL 0107000 010185 1000 1000 Anchorage city AK 0203000 020140 0380 0380 Phoenix city AZ 0455000 040260 6200 6200 Tucson city AZ 0477000 040380 8520 8520 Little Rock city AR 0541000 051195 4400 4400 Fresno city CA 0627000 061090 2840 2840 Long Beach city CA 0643000 061610 4480 4480 Los Angeles city CA 0644000 061630 4480 4480 Oakland city CA 0653000 061970 5775 7360 Sacramento city CA 0664000 062420 6920 6920 San Diego city CA 0666000 062475 7320 7320 San Francisco city CA 0667000 062485 7360 7360 San Jose city CA 0668000 062510 7400 7400 Santa Ana city CA 0669000 062570 5945 0360 Denver city CO 0820000 080320 2080 2080 Hartford city CT 0937000 090970 3283 Wilmington city DE 1077580 100255 9160 Washington DC city 1150000 110005 8840 8840 Jacksonville city FL 1235005 121000 3600 3600 Miami city FL 1245000 121370 5000 5000 Tampa city FL 1271000 122075 8280 8280 Atlanta city GA 1304000 130150 0520 0520 Honolulu CDP HI 1517000 150110 3320 3320 Boise City city ID 1608830 160090 1080 Chicago city IL 1714000 171051 1600 1600 Indianapolis city IN 1836010 181145 3480 3480 Des Moines city IA 1921000 191130 2120 2120 Kansas City city KS 2036000 201430 3760 Wichita city KS 2079000 203040 9040 9040 Louisville city KY 2148000 211230 4520 4520 New Orleans city LA 2255000 220956 5560 5560 Portland city ME 2360545 233750 6403 Baltimore city MD 2404000 240025 0720 0720 Boston city MA 2507000 250440 1123 1120 Detroit city MI 2622000 260680 2160 2160 Minneapolis city MN 2743000 272585 5120 5120 St. Paul city MN 2758000 273425 5120 5120 Jackson city MS 2836000 280615 3560 3560 Kansas City city MO 2938000 292220 3760 3760 St. Louis city MO 2965000 293875 7040 7040 Billings city MT 3006550 300050 0880 Omaha city NE 3137000 311825 5920 5920 Las Vegas city NV 3240000 320065 4120 4120 Manchester city NH 3345140 331610 33011 Newark city NJ 3451000 342895 5640 5640 City FIPS ST_PLAC8 MSAPMS A KMSA Albuquerque city NM 3502000 350015 0200 0200 Buffalo city NY 3611000 360450 1280 1280 New York city NY 3651000 362505 5600 5600 Charlotte city NC 3712000 370480 1520 1520 Fargo city ND 3825700 380545 2520 Cincinnati city OH 3915000 390865 1640 1640 Cleveland city OH 3916000 390900 1680 1680 Columbus city OH 3918000 390960 1840 1840 Toledo city OH 3977000 394265 8400 8400 Oklahoma City city OK 4055000 401815 5880 5880 Tulsa city OK 4075000 402465 8560 8560 Portland city OR 4159000 410905 6440 6440 Philadelphia city PA 4260000 427180 6160 6160 Pittsburgh city PA 4261000 427234 6280 6280 Providence city RI 4459000 440400 6483 6480 Columbia city SC 4516000 450305 1760 Sioux Falls city SD 4659020 461225 7760 Memphis city TN 4748000 470940 4920 4920 Nashville-Davidson TN 4752006 471016 5360 5360 Austin city TX 4805000 480210 0640 0640 Dallas city TX 4819000 481085 1920 1920 El Paso city TX 4824000 481340 2320 2320 Fort Worth city TX 4827000 481500 2800 1920 Houston city TX 4835000 481975 3360 3360 San Antonio city TX 4865000 483745 7240 7240 Salt Lake City city UT 4967000 490870 7160 7160 Burlington city VT 5010675 500460 1303 Virginia Beach city VA 5182000 511280 5720 5720 Seattle city WA 5363000 531140 7600 7600 Charleston city WV 5414600 540280 1480 Milwaukee city WI 5553000 551645 5080 5080 Cheyenne city WY 5613900 560050 1580 Data Dictionary NOTES 1. The underclass population as defined by Kasarda (1993) is the total number of persons having all five of the following characteristics: both householder and spouse (if present) did not complete high school; householder is either single, divorced, widowed, or separated, and householder's family includes persons under 18; both householder and spouse (if present) worked less than 26 weeks or usually worked less than 20 hours per week during the previous year; at least one member of the household received public assistance income in the previous year; and householder's income was below the poverty line in the previous year. As opposed to Ricketts and Sawhill's (1988) definitions, these figures are for persons in households with the specified characteristics, rather than all persons living in "underclass" census tracts. 2. Includes covered deposits in commercial and savings banks and branches. 3. PUMA boundaries do not match central city boundaries precisely in all cases. See Kasarda (1993), p. 3-41. 4. Actual fiscal health provides a measure of the central city's access to tax revenue compared to the services to which it is committed. The measure is defined as an index equal to zero for the average central city in 1972; deviations from this value are expressed as a percentage of the city's revenue-raising capacity. Values for Washington, D.C. reflect federal assistance through institutions and grants; 1972 index for Cincinnati may understate that city's fiscal health, due to certain biases in the way education responsibilities were defined. 5. Identical to actual fiscal health, except for the standardization assuming a single, market- basket of city fiscal institutions and service-providing responsibilities. Defined as an index equal to zero for the average central city in 1972; deviations from this value are expressed as a percentage of the city's revenue-raising capacity. Values for Washington, D.C. reflect federal assistance through institutions and grants. 6. The dissimilarity index provides a measure of the residential segregation between two different racial or ethnic groups. Given two populations A and B, the index is defined as: D = ( 0.5 Si | Ai - Bi | ) where Ai and Bi represent the respective proportion of members of A and B groups living in each census tract i. The index ranges from zero to 1 (although in the preliminary database 1980 and 1990 figures range from 0 to 100), with 1 (or 100) signifying perfect and complete segregation. The value of the index may be interpreted as the proportion of the minority population that would have to move in order to achieve perfect integration. 7. Wilger's index of dissimilarity ranges from 0 to 100. 8. Excludes federal government physicians. 9. Data derived from the REIS, which is reported only at the county level. For each central city, the county encompassing all or a majority of the city was selected for reporting purposes. Variables derived from Kasarda's database require adjustment for Los Angeles, Santa Ana, Long Beach, and Santa Ana. ST_PLAC8 is columns 351-357, 7.0, and is 69991 for Orange County, 69992 for Los Angeles County. See Kasarda, p. 2.3-7. 13. Carbon monoxide measured as the highest second (non-overlapping) eight-hour concentration. 14. Lead measured as the highest quarterly concentration. 15. Nitrogen Dioxide and Sulfur Dioxide are measured as the highest mean concentration. 16. Ozone is measured as the highest second daily maximum one-hour concentration. 17. Particulate matter (that exceeding 10 micrometers in diameter) is defined as the highest weighted annual mean concentration. 18. Daily particulate matter and sulfur dioxide measurements are defined as the highest second maximum 24-hour concentration. 19. Areal definitions do not correspond with MSA or central city boundaries in most cases. Single metropolitan-wide agency data are reported for several pairs of cities: Minneapolis/St. Paul; Los Angeles/Long Beach; and Boston/Manchester. For details on the areal definitions, see AMSA (1990). 20. Full-time workers only. 21. Operation and maintenance revenues; excludes capital and debt-related items. 22. Percentage of total flow treated at primary (best), secondary, and tertiary levels, respectively. These three items sum to 100 percent in all cases except for plants (or parts of facilities) in which level of service is not specified. 23. Percentage of total flow comprised of residential and industrial wastewater, respectively. Differences between the sum of these two items and 100 percent reflect the proportion of flow comprised of infiltration/inflow. 24. Total annual service cost per one-family residential user. 25. Excessive housing expenditure refers to total housing costs (contract rent for renters, specifed owner costs for owners) that equal or exceed 35 percent of gross household income. 26. Data refer to urbanized areas, and may not correspond to Metropolitan Statistical Area (MSA) definitions. Data for urbanized area used for both twin cities for Kansas City, KS/Kansas City, MO, San Francisco/Oakland, Minneapolis/St. Paul. Data for Norfolk substituted for Virginia Beach. 27. Vehicle kilometers of travel per lane kilometer of the specified roadway type; provides an estimate of traffic flow relative to capacity. 28. The roadway congestion index (RCI) compares existing traffic flow characteristics with specified threshold values identified with congested conditions. The index includes separate components for each roadway type (freeway and principal arterial). Index values exceeding 1.0 signify congested conditions areawide, while values below 1.0 indicate no systemic congestion. The RCI value is based on flow values aggregated across each urban area; thus the index is an overall measure, an urban area with an index less than 1.0 may have congested sections of road. 29. Represents the percentage of daily vehicle-kilometers of travel on each roadway type during the peak period operating on congested conditions. 32. The limiting factor in estimating gross metro product (GMP) is the availability of data on output. In the U.S., the smallest areal unit for officially released data on output is at the state level (gross state product or GSP). We derive GMP by assuming that sector- specific productivity levels are constant across all parts of each respective state -- i.e., that the GSP-to-earnings ratio for a state prevails within each of the state's metropolitan areas. We calculate GMP estimates by multiplying metropolitan earnings by sector- specific productivity levels at the state level and summing across sectors. Both GSP and earnings data are available at approximately the two-digit SIC level. We adjusted these datasets for comparability, yielding a total of 60 industrial sectors for which productivity estimates were calculated. Consequently, the GMP figures not only account for state differences in productivity, but also for differences in the industrial mix between the metro and non-metro portions of each state. 33. Area in acres devoted to agricultural, business/commercial, residential, and transportation uses, based on aggregations of prime-use categories in the U.S.D.A. database. These categories do not sum to the total Metropolitan acreage, the difference reflects land devoted to recreation, reservation and dedication, waste land, and unspecified uses. 34. Excludes undeveloped rural areas. 35. Excludes water-based transportation. 36. Total pounds of pollution released into the environment (air, land, water, underground) by facilities in 1987 Standard Industrial Classification codes 20 to 39 with 10 or more full- time employees. These variables exclude establishments releasing less than 50,000 pounds in each respective reporting year; these smaller releases comprise about 11 percent of the national total reported in 1992 (1.57 million tons). Data cover more than 300 chemicals; thus figures on total pollution conceal wide variations in type of pollution and degree of threat to health or environment. 37. Data refer to urbanized area. 38. Consist of Medicare payments, medical vendor payments, and CHAMPUS payments. 39. Includes general assistance, emergency assistance, refugee assistance, foster home care payments, earned income tax credits, and energy assistance. 40. Monthly bill assuming 500 c.f. use, with a 5/8" meter. 41. Monthly bill assuming 50,000 c.f. use, with a 2" meter. 42. Labor force and unemployment data reported for MSAs in New England; exercise extreme caution when comparing unemployment rates with metropolitan variables reported by NECMA for Hartford, CT, Portland, ME, Boston, MA, Manchester, NH, Providence, RI, and Burlington, VT. 43. Average annual unemployment, weighted by total labor force in each respective year. 44. Deflated to constant 1987 dollars, using the GDP price deflator. 45. This index was calculated by CUPR using data from the REIS CD ROM published by the U.S. Department of Commerce's Bureau of Economic Analysis. For each year, from the CD we extracted both earnings and employment data at the division level (one-digit SIC designation) for each pertinent metropolitan statistical area and the nation. Subsequently, for the metropolitan areas we calculated the average earnings per job for each division. Then, we calculated the average earnings for each metro area assuming that its industry mix was the same as the nation's. Finally, we took these average earnings and divided them by the national average earnings per job and multiplied by 100. 46. These totals do not distinguish Hispanic/non-Hispanic origin within each racial category (e.g., 'White' includes both non-Hispanic Whites and Hispanic Whites. 47. Dependency ratio is defined as the percentage of all persons aged under 18 or over 64. 48. Income inequality is measured by: I = ( 0.5 Si | Ai - Bi | ) where Ai is the percentage of all households in income category i and Bi is the percentage of total income garnered by households in income category I. For 1980, calculations based on mean of each of 17 household income ranges; $1,500 assumed average for bottom category; $125,000 average assumed for top category. For 1990, calculations based on mean of each of 25 household income ranges; $3,000 assumed average for bottom category; $175,000 average assumed for top category. I ranges from zero to one, with higher values indicative of greater income inequality. 49. Calculations based on mean of each of 25 household income ranges; $3,000 average assumed for bottom category; $175,000 average assumed for top category. 50. Includes families of each respective type with related children under 18. 51. All civilian labor force figures exclude persons in armed forces; participation rate denotes percentage of persons aged 16 and over in the labor force. 52. Exercise extreme caution when comparing educational attainment across census years. Data are not strictly comparable, for two reasons. First, decennial census tabulations of CC9HSCH, CM9HSCH, CC8HSCH, and CM8HSCH report high school educational attainment of persons aged 18 and over, while the corresponding figures derived from the Current Population Surveys for 1992 and 1993 cover only those aged 25 and over. Second, 1980 and 1990 decennial census figures reflect changes to the census questionnaire in 1990. For 1980, "high school graduates" refers to those persons completing four years of high school (as well as those completing one or more years of college); for 1990, tabulations distinguish between persons earning a degree (or equivalency) and those completing grades 9 to 12 without receiving a degree. CC9HSCH and CM9HSCH report the percentage of all persons aged 18 and over who earned a high school diploma or equivalency (including all persons attaining higher levels of education). For 1980, "college graduates" refers to those persons completing four or more years of college; for 1990, the tabulations distinguish between persons who earned a bachelor's degree and those completing one or more years of college without receiving a degree. CC9COLL and CM9COLL report the percentage of all persons aged 18 and over who earned bachelor's degrees (including those completing graduate or professional degrees). 53. Excludes workers working at home. 54. Single-family housing excludes attached units; medium-density housing includes attached single-family units, and housing in structures with 2, 3, or 4 units; high-density housing includes units in structures with 5 or more units. 55. Figures for Indianapolis, Jacksonville, and Nashville refer to the respective counties with which these cities have been consolidated. 56. Total population living within a 500-mile radus of each respective central city. 57. Payments and number of participants during December of each respective reporting year. 58. Geographical coverage of permits data varies for several cities. Anchorage permit system covers all of the Aleutians East Borough, Aleutians West Census Area, Bethel Census Area, Dillingham Census Area, Kenai Peninsula Borough, Lake and Peninsula Borough, Matanuska-Susitna Borough, Nome Census Area, Northwest Arctic Borough, Valdez- Cordova Census Area, and Wade Hampton Census Area. Miami city permits are measured using Dade County data. Indianapolis permit system covers the entire county of Marion except Beech Grove, Lawrence, and Southport cities; and Speedway town. Kansas City, KS permit system also covers the portion of the unincorporated area of Wyandotte County, KS not covered by Bonner Springs city. New Orleans is coextensive with Orleans parish. Detroit permit system also covers property owned by the city outside the corporate limits of Detroit. Billings permit system also covers a 4 - 1/2 mile radius beyond the city limits. Omaha permit system also covers a 3-mile radius beyond the city limits. Portland, OR, permit system also covers permits issued for the portion of the unincorporated area of Multnomah County not covered by the Gresham and Troutdale offices (1994). Memphis permit system also covers Germantown and Lakeland cities, Arlington town; and unincorporated areas of Shelby County. Cheyenne city permit system covers the flood-prone area within a 5-mile radius around the city. 59. All variables drawn from the Current Population Survey files (U.S.BOC 1993, 1994c) are subject to several limitations; users should exercise extreme caution interpreting these figures. The CPS files suffer from three main limitations. First, the CPS is based on a small sample (approximately 1 in 1,000), and sampling variability may fluctuate between surveys or across different cities. In order to eliminate variables with unacceptable levels of sampling error, we have set to missing all values or ratios in which the denominator falls short of 25,000 (persons or families). Second, the CPS reports characteristics of families, but does not refer to "family households" as does the decennial census; in some cases this difference yields high estimates of family-related variables drawn from the CPS. Third, metropolitan areas for the 1992 and 1993 surveys are based on the 1980 MSA definitions; thus metropolitan CPS tabulations are not comparable to 1990 Census figures. 60. Users should exercise caution when comparing employment figures drawn from BEA and U.S. Census sources. All BEA employment figures describe workers by place of work, while census figures describe workers by place of residence. 61. Defined as the number of occupied housing units in which there are more than 1.01 persons per room. 62. Exercise extreme caution when examining metropolitan-level migration measures for 1980; all such measures are based on SMSA boundaries in force for the 1980 census enumeration (hence the "MSA1" designation). Metropolitan-level migration measures for 1980 are based on SMSAs in New England, rather than NECMAS; therefore, metropolitan migration totals for 1980 are incomparable to most other metropolitan area measures. 63. Workers 16 years and over does not includethose who worked at home. 64. The degree day normals are used to determine relative estimates of heating and cooling requirements for the buildings. Each degree that the average temperature for a day is below 65 degrees F produces one heating degree day. For example, if the maximum temperature is 70 degrees F and the minumum temperature is 52 degree F, the average temperature for the day is 61 degrees, resulting in four heating degreee days. Cooloing degree days are calculated in a similar fashion for each degree that the average temperature is above 65 degree F. 65. Figures for Buffalo refer to the Buffalo-Niagara Falls, NY Consolidated Metropolitan Statistical Area (CMSA). 66. Users should exercise extreme caution when comparing government financial information across central cities. These figures refer only to city government operations, and exclude other units of local government such as school districts or water management districts. Variations in state and local government organization and jurisdiction, therefore, may be responsible for variations in city financial information reported here. For detailed information, see U.S.B.O.C. (1993b). 68. Governmental administration expenditures include expenditures on financial administration, general control and general public buildings; expenditures on environment and housing include parks and recreation, housing and community development, and natural resources; expenditures on health services include hospital and health expenditures; expenditures on transportation include highways and other, but exclude capital outlays; expenditures on sewerage and sanitation exclude capital outlays. 69. 70. Data excludes teachers reported as having working in school district offices rather than individual schools. 71. Includes all categories of high school completions, such as GEDs. 72. Denotes the total amount of revenue transfers from federal government to each respective school district. 73. Expenditures by local school districts only. Excludes expenditures by state educational agencies made for local school districts. 74. 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