THE STATE OF THE NATION'S CITIES DATABASE AND MACHINE-READABLE FILE DOCUMENTATION VERSION 2.2A Norman J. Glickman, Michael Lahr, and Elvin Wyly Released on January 19, 1998 CENTER FOR URBAN POLICY RESEARCH RUTGERS, THE STATE UNIVERSITY OF NEW JERSEY 33 LIVINGSTON AVENUE, SUITE 400 NEW BRUNSWICK NJ 08901-1982 DATABASE OVERVIEW Introduction: Despite the proliferation of high-quality data sets 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 grew out of data needs of the United Nations' Habitat II Conference 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 policy-makers, planners, and scholars. Database Description: The 3,000+ variables in Version 2.2a of the database present a comprehensive description of social and economic conditions in America's urban centers. Highlights of version 2.2a include: the addition of 1970 census variables; updates of the REIS/BEA employment and income data to 1995; permit data for central cities and MSAs for 1990 to 1995 including number, type, and value of units; number of employed residents, labor force participation, and unemployment rates for cities and MSAs from 1990 to 1996 from the Bureau of Labor Statistics, Local Area Unemployment Statistics; and, measures of family income inequality and per capita income ratios between cities and suburbs. completed variable labels for the SPSS portable version. See the new data dictionary (DCT_22a.xls) for a complete list of variables and definitions. In order to balance data-set coverage (number and diversity of variables and sources) with geographic coverage (number of cities), we narrowed our focus to a hybrid list of seventy-seven cities and their surrounding 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; household expenditures; 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 the 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. If you have downloaded SNC_211a in the SPSS portable format or in the SAS format, the file will contain 77 cases and approximately 2,400 variables. However the Excel version of the data set has been transposed in order to fit within Excel's limit on columns. The Excel file contains 77 columns corresponding to the 77 central cities and approximately 2,570 rows corresponding to the variables. The first row contains the FIPS number--the only unique identification number in the data set--preceded by a "v". Thus Birmingham, AL has the column header " V107000" where "107000" is the unique FIPS number. The first column contains the variable name. 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 of the constant MSA2. Generated by subtracting the central city from the metropolitan area. In the case of the three MSAs with two central cities both central cities are subtracted from the metropolitan total. VAR Other 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. For example, data from the Bureau of the Census measuring residential employment for the city and metropolitan scales may not exactly match residential employment as measured by the Bureau of Labor. For 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. As a general rule, we issue updated versions of the database and documentation on a quarterly basis. The most recent version of the database is available in several different file formats via world wide web at http://www.policy.rutgers.edu/cupr/sonc.htm 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 MSAPMSA 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 MSAPMSA 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 Database Overview, Page Version 2.2a January 19, 1998