This data collection contains the basic information about all counties in the coterminous United States needed for mapping county-based data. It provides an interface between ICPSR datasets and the mapping programs SAS/GRAPH, SURFACE II, and SYMAP. Cloropleth and isopleth maps can be produced by match-merging this dataset with any other dataset (special facilities exist for ICPSR datasets) and running the merged data against a cartographic program. Isopleth mapping programs, using the latitude and longitude coordinates provided for each county seat, can produce maps of ICPSR data. Cloropleth mapping of county-level data can be accomplished after merging by running the merged dataset through SAS/GRAPH. The variables provide state Federal Information Processing (FIPS) codes, county FIPS codes, county names/county seat names, the month, day, and year in which each county was created, the latitude and longitude of county seats, as well as the ICPSR state and county codes.

The County Longitudinal Template is a tool that enables researchers to allow for temporal changes in the geographic boundaries of counties in the United States. These data provide a decade-by-decade account of the administrative status of each county, starting in 1990 and tracing each census period back through 1840. The first four variables are the county name, ICPSR state code, FIPS code, and ICPSR county code. These four variables allow the researcher to select the counties for the state in question. The next 16 variables are ID variables for each census year, 1990 back to 1840. The last 13 variables are boundary change flags for each census year from 1960 to 1840.

This dataset was created to facilitate the conversion of Uniform Crime Reporting (UCR) Program state and county codes to Federal Information Processing Standards (FIPS) state and county codes. The four UCR agency-level data files archived at ICPSR in Uniform Crime Reporting Program Data: United States contain UCR state and county codes as geographic identifiers. Researchers who wish to use these data with other sources, such as Census data, may want to convert these UCR codes to FIPS codes in order to link the different data sources. This file was created to facilitate this linkage. It contains state abbreviations, UCR state and county codes, FIPS state and county codes, and county names for all counties present in the UCR data files since 1990. These same FIPS codes were used to create the UCR County-Level Detailed Arrest and Offense files from 1990-1996.

The U.S. Census Bureau TIGER/Line® files in this data collection were originally distributed by the Inter-university Consortium for Political and Social Research (ICPSR) through its TIGER/Line file web site, which was decommissioned in 2018 (archived version: https://web.archive.org/web/20090924181858/http://www.icpsr.umich.edu/TIGER/index.html). There, users could download various versions of the U.S. Census Bureau's TIGER (Topologically Integrated Geographic Encoding and Referencing) database. The TIGER/Line files do not include demographic data, but they do contain geographic information that can be linked to the Census Bureau’s demographic data. Due to file number limitations in openICPSR, the original data collections have been bundled into single zip packages. A single TIGER_directory.txt file listing the original files and the original directory structure is included with the root directory. Documentation files are also included as standalone subdirectories in each collection so users do not need to download entire zip bundles to view documentation. The TIGER/Line data are stored in compressed format in subdirectories by state name. There is one TIGER/Line file (in a compressed format) for each county or county equivalent. The file names consist of TGR + the 2-digit state FIPS (Federal Information Processing Standards) code + the 3-digit county FIPS code (i.e. TGR01031.ZIP for Coffee County, Alabama). Each state folder contains individual county files.The individual county files include one file for each record type included for that county with the following name convention: tgr01031.rt1. The convention follows the order described above with each file having a suffix which includes 'rt' (record type) followed by its designation (in this case record type 1). Each county file also contains its own metadata record.If present, documentation files for the TIGER/Line data are stored in a directory named '0docs' which is located in the 'Parent Directory'. This directory appears at the top of the index of state subdirectories for each edition of the TIGER/Line files. The documentation includes a complete list of FIPS state and county codes.

This study contains data retrieved from the CENSUS OF POPULATION AND HOUSING, 1970: FOURTH COUNT summary files on selected items that were not included in the COUNTY AND CITY DATA BOOK, 1972 (ICPSR 0061). Data on age, sex, ethnicity, place of birth, level of education, employment status, occupation, and family income are reported for the population of each county and county equivalent in the United States as well as the District of Columbia. County equivalents are parishes in Louisiana, census divisions in Alaska, and independent cities in Virginia and Missouri. Identification variables such as names of counties, Standard Metropolitan Statistical Areas codes, and both the Census Bureau and ICPSR state and county codes are also provided. The data were originally compiled from the 1970 Census summary tapes by John McAdams of Harvard University. ICPSR added identification codes and county names, reformatted some substantive variables, and corrected some SMSA code values. (Source: downloaded from ICPSR 7/13/10)

This data collection relates ZIP codes to counties, to standard metropolitan statistical areas (SMSAs), and, in New England, to minor civil divisions (MCDs). The relationships between ZIP codes and other geographical units are based on 1979 boundaries, and changes since that time are not reflected. The Census Bureau used various sources to determine ZIP code-county or ZIP code-MCD relationships. In the cases where the sources were confusing or contradictory as to the geographical boundaries of a ZIP code, multiple ZIP-code records (each representing the territory contained in that ZIP-code area) were included in the data file. As a result, the file tends to overstate the ZIP code-county or ZIP code-MCD crossovers. The file is organized by ZIP code and is a byproduct of data used to administer the 1980 Census. Variables include ZIP codes, post office names, FIPS state and county codes, county or MCD names, and SMSA codes. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08051.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Abstract (en): This data collection contains FIPS codes for state, county, county subdivision, and place, along with the 1990 Census tract number for each side of the street for the urban cores of 550 counties in the United States. Street names, including prefix and/or suffix direction (north, southeast, etc.) and street type (avenue, lane, etc.) are provided, as well as the address range for that portion of the street located within a particular Census tract and the corresponding Census tract number. The FIPS county subdivision and place codes can be used to determine the correct Census tract number when streets with identical names and ranges exist in different parts of the same county. Contiguous block segments that have consecutive address ranges along a street and that have the same geographic codes (state, county, Census tract, county subdivision, and place) have been collapsed together and are represented by a single record with a single address range. 2006-01-12 All files were removed from dataset 551 and flagged as study-level files, so that they will accompany all downloads. (1) Due to the number of files in this collection, parts have been eliminated here. For a complete list of individual part names designated by state and county, consult the ICPSR Website. (2) There are two types of records in this collection, distinguished by the first character of each record. A "0" indicates a street name/address range record that can be used to find the Census tract number and other geographic codes from a street name and address number. A "2" indicates a geographic code/name record that can be used to find the name of the state, county, county subdivision, and/or place from the FIPS code. The "0" records contain 18 variables and the "2" records contain 10 variables.

The State Legislative District Summary File Supplement contains geographic identification codes that relate each 2000 Census block to pre-2010 Census state legislative districts. Both upper and lower chamber districts are identified. In addition, these block-level data contain variables on land area, water area, latitude, longitude, total population size, and number of housing units, as well as geographic identification variables for other levels of observation such as states, metropolitan statistical areas, urban areas, congressional districts, counties, county subdivisions, places, census tracts, block groups, and ZIP code tabulation areas. There is one data file for each state, the District of Columbia, and Puerto Rico which are bundled together in a single ZIP archive. A second ZIP archive contains the codebook and other documentation.

The Geographic Names Information System (GNIS) was developed by the United States Geological Survey (USGS) to meet major national needs regarding geographic names and their standardization and dissemination. This dataset consists of standard report files written from the National Geographic Names Data Base, one of five data bases maintained in the GNIS. A standard format data file for each of the fifty States, the District of Columbia and the four Insular Territories of the United States is included, as well as a file that provides a Cross-Reference to USGS 7.5 x 7.5 minute quadrangle maps. The records in the data files are organized in an alphabetized listing of all of the names in a particular state or territory. The other variables available in the dataset include: Federal Information Processing Standard (FIPS) state/county codes, Geographic Coordinates-- latitude and longitude to degrees, minutes, and seconds followed by a single digit alpha directional character, and a GNIS Map Code that can be used with the Cross-Reference file to provide the name of the 7.5 x 7.5 minute quadrangle map that contains that geographic feature.

Version 5 release notes:Adds 2016 dataStandardizes the "group" column which categorizes cities and counties by population.Arrange rows in descending order by year and ascending order by ORI. Version 4 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. Version 3 Release Notes:Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Change column names for relationship variables from offender_n_relation_to_victim_1 to victim_1_relation_to_offender_n to better indicate that all relationship are victim 1's relationship to each offender. Reorder columns.This is a single file containing all data from the Supplementary Homicide Reports from 1976 to 2015. The Supplementary Homicide Report provides detailed information about the victim, offender, and circumstances of the murder. Details include victim and offender age, sex, race, ethnicity (Hispanic/not Hispanic), the weapon used, circumstances of the incident, and the number of both offenders and victims. All the data was downloaded from NACJD as ASCII+SPSS Setup files and cleaned using R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors, have terminology be the same across years). The following is the summary of the Supplementary Homicide Report copied from ICPSR's 2015 page for the data.The Uniform Crime Reporting Program Data: Supplementary Homicide Reports (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

Abstract (en): This collection presents in computer-readable form the data items used to produce the corresponding printed volume of the COUNTY AND CITY DATA BOOK, 1988. Included is a broad range of statistical information, made available by federal agencies and national associations, for counties, cities, and places. Information also is provided for the 50 states, the District of Columbia, and for the United States as a whole. The dataset is comprised of seven files: a county file, a city file, and a place file, with footnote files and data dictionaries for both the county and the city files. The county data file contains information on areas such as age, agriculture, banking, construction, crime, education, federal expenditures, personal income, population, and vital statistics. The city data file includes variables such as city government, climate, crime, housing, labor force and employment, manufactures, retail trade, and service industries. Included in the place data file are items on population and money income. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. The universe varies from item to item within the files, e.g., all persons, all housing units, all local governments, etc. 2009-05-26 SAS, SPSS, and Stata setups have been added to this data collection.2006-03-30 File CB9251.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. Users are advised that the codebook that the Census Bureau has issued for use with this dataset is a preliminary one and does not include codes and definitions for states, counties, and cities. The codes and definitions may be listed off the tape or users may refer to other sources such as the printed version of the COUNTY AND CITY DATA BOOK, 1988. For each case in the Counties Data file, there are two 1,239-character records.

These migration data come from the Census 2000 long-form questions about residence in 1995 and provide the number of people who moved between counties. There are two files, one for inflows from every county in the United States and another re-sorted by outflows to every county. Each file contains data for all 50 states and the District of Columbia, sorted by FIPS state and county codes.

Abstract (en): This data collection is a compendium of data for all counties in the United States for the period 1944 to 1977. The data provide diverse information such as local government activities, population estimates and characteristics, and housing unit descriptors. Also included is information on local government revenues, property taxes, capital outlay, debts, expenditures on education, highways, public welfare, health and hospitals, and police, as well as information on births, deaths, schooling, labor force, employment, family income, family characteristics, electoral votes, and housing characteristics. Additional variables provide information on manufacturing, retail and wholesale trade, banking, mineral industries, farm population, agriculture, crime, and weather. Users may also be interested in the related data collection, COUNTY AND CITY DATA BOOK [UNITED STATES] CONSOLIDATED FILE: CITY DATA, 1944-1977 (ICPSR 7735). ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Checked for undocumented or out-of-range codes.. Individual states, the District of Columbia, and counties or county equivalents for which data were published in the County and City Data Books, in the entire United States in the period 1947-1977. Smallest Geographic Unit: county 2012-09-18 The data have been checked and corrected for inconsistencies, and have been reformatted to one record per case. SAS, SPSS, and Stata setup files have been updated. SPSS and Stata system files and a SAS transport (CPORT) file have been added to the collection. The codebook has been updated.2008-04-01 SAS, SPSS, and Stata setup files have been added to this data collection. record abstractsThis data file includes both state and county records. Records for counties in each state are listed immediately following the state record. All records have the same structure, and the identifier for each record includes both state and the county codes. In the state records, the county code is listed as 000.

Researchers have long been able to analyze crime and law enforcement data at the individual agency level (see UNIFORM CRIME REPORTING PROGRAM DATA: [UNITED STATES] [ICPSR 9028]) and at the county level (see, for example, UNIFORM CRIME REPORTING PROGRAM DATA [UNITED STATES]: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1997 [ICPSR 2764]). However, analyzing crime data at the intermediate level, the city or place, has been difficult. To facilitate the creation and analysis of place-level data, the Bureau of Justice Statistics (BJS) and the National Archive of Criminal Justice Data (NACJD) created the Law Enforcement Agency Identifiers Crosswalk. The crosswalk file was designed to provide geographic and other identification information for each record included in either the Federal Bureau of Investigation's Uniform Crime Reports (UCR) files or BJS's Directory of Law Enforcement Agencies. The main variables for each record are the UCR originating agency identifier number, agency name, mailing address, Census Bureau's government identification number, UCR state and county codes, and Federal Information Processing Standards (FIPS) state, county, and place codes. These variables make it possible for researchers to take police agency-level data, combine them with Bureau of the Census and BJS data, and perform place-level, jurisdiction-level, and government-level analyses.

Abstract (en): This data collection contains population and per capita income estimates for over 39,000 governmental entities in the United States, recorded for selected years from 1969 to 1975. These estimates were developed to provide updates of the data elements in federal revenue sharing allocations under the state and local Fiscal Assistance Act of 1972. Estimates recorded in the data file are for July 1 of the respective years, while per capita income refers to the entire year. Data items included are population in 1970 as recorded in the decennial census of that year, population estimates for 1973 and 1975, and per capita money income estimates for 1969, 1972, and 1974. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. The county and county-equivalent population of the United States. (1) The methodology used to derive the estimates contained in this data collection is described in detail in Appendix B of the codebook. (2) The codebook is provided by ICPSR as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

Version 4 release notes:I am retiring this dataset - please do not use it. The reason that I made this dataset is that I had seen a lot of recent articles using the NACJD version of the data and had several requests that I make a concatenated version myself. This data is heavily flawed as noted in the excellent Maltz & Targonski's (2002) paper (see PDF available to download here and important paragraph from that article below) and I was worried that people were using the data without considering these flaws. So the data available here had the warning below this section (originally at the top of these notes so it was the most prominent thing) and had the Maltz & Targonski PDF included in the zip file so people were aware of it. There are two reasons that I am retiring it. First, I see papers and other non-peer reviewed reports still published using this data without addressing the main flaws noted by Maltz and Targonski. I don't want to have my work contribute to research that I think is fundamentally flawed. Second, this data is actually more flawed that I originally understood. The imputation process to replace missing data is based off of a bad design, and Maltz and Targonski talk about this in detail so I won't discuss it too much. The additional problem is that the variable that determines whether an agency has missing data is fatally flawed. That variable is the "number_of_months_reported" variable which is actually just the last month reported. So if you only report in December it'll have 12 months reported instead of 1. So even a good imputation process will be based on such a flawed measure of missingness that it will be wrong. How big of an issue is this? At the moment I haven't looked into it in enough detail to be sure but it's enough of a problem that I no longer want to release this kind of data (within the UCR data there are variables that you can use to try to determine the actual number of months reported but that stopped being useful due to a change in the data in 2018 by the FBI. And even that measure is not always accurate for years before 2018.).!!! Important Note: There are a number of flaws in the imputation process to make these county-level files. Included as one of the files to download (and also in every zip file) is Maltz & Targonski's 2002 paper on these flaws and why they are such an issue. I very strongly recommend that you read this paper in its entirety before working on this data. I am only publishing this data because people do use county-level data anyways and I want them to know of the risks. Important Note !!!The following paragraph is the abstract to Maltz & Targonski's paper: County-level crime data have major gaps, and the imputation schemes for filling in the gaps are inadequate and inconsistent. Such data were used in a recent study of guns and crime without considering the errors resulting from imputation. This note describes the errors and how they may have affected this study. Until improved methods of imputing county-level crime data are developed, tested, and implemented, they should not be used, especially in policy studies.Version 3 release notes: Adds a variable to all data sets indicating the "coverage" which is the proportion of the agencies in that county-year that report complete data (i.e. that aren't imputed, 100 = no imputation, 0 = all agencies imputed for all months in that year.). Thanks to Dr. Monica Deza for the suggestion. The following is directly from NACJD's codebook for county data and is an excellent explainer of this variable.The Coverage Indicator variable represents the proportion of county data that is reported for a given year. The indicator ranges from 0 to 100. A value of 0 indicates that no data for the county were reported and all data have been imputed. A value of 100 indicates that all ORIs in the county reported for all 12 months in the year. Coverage Indicator is calculated as follows: CI_x = 100 * ( 1 - SUM_i { [ORIPOP_i/COUNTYPOP] * [ (12 - MONTHSREPORTED_i)/12 ] } ) where CI = Coverage Indicator x = county i = ORI within countyReorders data so it's sorted by year then county rather than vice versa as before.Version 2 release notes: Fixes bug where Butler University (ORI = IN04940) had wrong FIPS state and FIPS state+county codes from the LEAIC crosswa

We study trends in income inequality across U.S. states and counties 1960-2019 using a mix of administrative and survey data sources. Both states and counties have diverged in terms of per-capita pre-tax incomes since the late 1990s, with transfers serving to dampen this divergence. County incomes have been diverging since the late 1970s. These trends in mean income mask opposing patterns among top and bottom income quantiles. Top incomes have diverged markedly across states since the late 1970s. In contrast, bottom income quantiles and poverty rates have converged across areas in recent decades.

This dataset contains records for each public elementary and secondary education agency in the 50 states, the District of Columbia, United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), and Department of Defense schools outside of the United States for 1991-1992. Data were reported to the Bureau of the Census for the National Center for Education Statistics by the state coordinators. Each record provides state and federal identification numbers, agency address, name, and telephone number, county name and FIPS code, agency type code, student counts, graduates and other completers counts, and other codes for selected characteristics of the agency. Information on grade span and the number of schools, classroom teachers, and staff is also included in most cases.

This metadata report documents tabular data sets consisting of items from the Census of Agriculture. These data are a subset of items from county-level data (including state totals) for the conterminous United States covering the census reporting years (every five years, with adjustments for 1978 and 1982) beginning with the 1950 Census of Agriculture and ending with the 2012 Census of Agriculture. Historical (1950-1997) data were extracted from digital files obtained through the Intra-university Consortium on Political and Social Research (ICPSR). More current (1997-2012) data were extracted from the National Agriculture Statistical Service (NASS) Census Query Tool for the census years of 1997, 2002, 2007, and 2012. Most census reports contain item values from the prior census for comparison. At times these values are updated or reweighted by the reporting agency; the Census Bureau prior to 1997 or NASS from 1997 on. Where available, the updated or reweighted data were used; otherwise, the original reported values were used. Changes in census item definitions and reporting as well as changes to county areas and names over the time span required a degree of manipulation on the data and county codes to make the data as comparable as possible over time. Not all of the census items are present for the entire 1950-2012 time span as certain items have been added since 1950 and when possible the items were derived from other items by subtracting or combining sub items. Specific changes and calculations are documented in the processing steps sections of this report. Other missing data occurs at the state and (or) county level due to census non-disclosure rules where small numbers of farms reporting an item have acres and (or) production values withheld to prevent identification of individual farms. In general, caution should be exercised when comparing current (2012) data with values reported in earlier censuses. While the 1974-2012 data are comparable, data prior to 1974 will have inflated farm counts and slightly inflated production amounts due to the differences in collection methods, primarily, the definition of a farm. Further discussion on comparability can be found the comparability section of the Supplemental Information element of this metadata report. Excluded from the tabular data are the District of Columbia, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the three county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. Data for independent cities of Virginia prior to 1959 have been included with their surrounding or adjacent county. Please refer to the Supplemental Information element for information on terminology, the Census of Agriculture, the Inter-university Consortium for Political and Social Research (ICPSR), table and variable structure, data comparability, all farms and economic class 1-5 farms, item calculations, increase of farms from 1974 to 1978, missing data and exclusion explanations, 1978 crop irregularities, pastureland irregularities, county alignment, definitions, and references. In addition to the metadata is an excel workbook (VariableKey.xlsx) with spreadsheets containing key spreadsheets for items and variables by category and a spreadsheet noting the presence or absence of entire variable data by year. Note: this dataset was updated on 2016-02-10 to populate omitted irrigation values for Miami-Dade County, Florida in 1997.

Abstract (en): This dataset contains records for each public secondary and elementary education agency in the United States and its outlying areas (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) for 1985-1986. Reporting agencies serve instructional levels from pre-kindergarten through grade 12, or the equivalent span of instruction in ungraded or special education districts. Regional Educational Service Agencies, supervisory unions, and county superintendents are also represented. Variables include state and federal ID numbers, agency name, address, city, and ZIP code, FIPS county and out-of-state indicators, instructional operating status, agency type, grade span, metropolitan statistical area (MSA) ID and status, and board of control selection code. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. All public elementary and secondary education agencies in operation during 1985-1986 in the 50 states, the District of Columbia, and United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands). The codebook is provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.