Multi-City Study of Urban Inequality, 1992-1994: [Atlanta, Boston, Detroit, and Los Angeles] (ICPSR 2535)
Principal Investigator(s): Bobo, Lawrence, Harvard University; Johnson, James , University of North Carolina; Oliver, Melvin, Ford Foundation; Farley, Reynolds, Russell Sage Foundation; Bluestone, Barry, University of Massachusetts-Boston; Browne, Irene, Emory University; Danziger, Sheldon, University of Michigan; Green, Gary, University of Wisconsin; Holzer, Harry, Michigan State University; Krysan, Maria, Pennsylvania State University; Massagli, Michael, University of Massachusetts-Boston; Charles, Camille Zubrinsky, University of Pennsylvania; Kirschenman, Joleen; Moss, Philip; Tilly, Chris
Summary:
The Multi-City Study of Urban Inequality was designed to broaden the understanding of how changing labor market dynamics, racial attitudes and stereotypes, and racial residential segregation act singly and in concert to foster contemporary urban inequality. This data collection comprises data for two surveys: a survey of households and a survey of employers. Multistage area probability sampling of adult residents took place in four metropolitan areas: Atlanta (April 1992-September 1992), Boston (May 1993-November 1994), Detroit (April-September 1992), and Los Angeles (September 1993-August 1994). The combined four-city data file in Part 1 contains data on survey questions that were asked in households in at least two of the four survey cities. Questions on labor market dynamics included industry, hours worked per week, length of time on job, earnings before taxes, size of employer, benefits provided, instances of harassment and discrimination, and searching for work within particular areas of the metropolis in which the respondent resided. Questions covering racial attitudes and attitudes about inequality centered on the attitudes and beliefs that whites, Blacks, Latinos, and Asians hold about one another, including amount of discrimination, perceptions about wealth and intelligence, ability to be self-supporting, ability to speak English, involvement with drugs and gangs, the fairness of job training and educational assistance policies, and the fairness of hiring and promotion preferences. Residential segregation issues were studied through measures of neighborhood quality and satisfaction, and preferences regarding the racial/ethnic mix of neighborhoods. Other topics included residence and housing, neighborhood characteristics, family income structure, networks and social functioning, and interviewer observations. Demographic information on household respondents was also elicited, including length of residence, education, housing status, monthly rent or mortgage payment, marital status, gender, age, race, household composition, citizenship status, language spoken in the home, ability to read and speak English, political affiliation, and religion. The data in Part 2 represent a telephone survey of current business establishments in Atlanta, Boston, Detroit, and Los Angeles carried out between spring 1992 and spring 1995 to learn about hiring and vacancies, particularly for jobs requiring just a high school education. An employer size-weighted, stratified, probability sample (approximately two-thirds of the cases) was drawn from regional employment directories, and a probability sample (the other third of the cases) was drawn from the current or most recent employer reported by respondents to the household survey in Part 1. Employers were queried about characteristics of their firms, including composition of the firm's labor force, vacant positions, the person most recently hired and his or her salary, hours worked per week, educational qualifications, promotions, the firm's recruiting and hiring methods, and demographic information for the respondent, job applicants, the firm's customers, and the firm's labor force, including age, education, race, and gender.
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Dataset(s)
Study Description
Citation
Bobo, Lawrence, James Johnson, Melvin Oliver, Reynolds Farley, Barry Bluestone, Irene Browne, Sheldon Danziger, Gary Green, Harry Holzer, Maria Krysan, Michael Massagli, Camille Zubrinsky Charles, Joleen Kirschenman, Philip Moss, and Chris Tilly. Multi-City Study of Urban Inequality, 1992-1994: [Atlanta, Boston, Detroit, and Los Angeles]. ICPSR02535-v3. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2000. doi:10.3886/ICPSR02535.v3
Persistent URL: http://dx.doi.org/10.3886/ICPSR02535.v3
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Funding
This survey was funded by:
- Russell Sage Foundation
- Ford Foundation
Scope of Study
Subject Terms: demographic characteristics, discrimination, employers, household income, households, labor markets, neighborhoods, race relations, racial attitudes, racial discrimination, racial segregation, residential segregation, urban areas
Geographic Coverage: Atlanta, Boston, California, Detroit, Georgia, Los Angeles, Massachusetts, Michigan, United States
Time Period:
- 1992--1994
Date of Collection:
- 1992--1994
Universe: Part 1: Adult residents in four selected metropolitan areas in the United States (Atlanta, Boston, Detroit, Los Angeles), Part 2: Active business establishments in the same four areas.
Data Types: survey data
Data Collection Notes:
Two weights are provided in Part 1: a post-stratified nonresponse adjusted household weight and a person weight. Four weights are provided in Part 2.
The data files in Parts 1 and 2 can be linked.
This collection has not been processed by ICPSR staff. ICPSR is distributing the data and documentation for this collection in essentially the same form in which they were received. When appropriate, hardcopy documentation has been converted to machine-readable form and variables have been recoded to ensure respondents' anonymity.
Methodology
Sample: Part 1: Multistage area probability sample. Part 2: Size-weighted, stratified, probability sample.
Data Source:
personal interviews
Extent of Processing: 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 online analysis version with question text.
Version(s)
Original ICPSR Release: 1998-08-28
Version History:
- 2000-03-21 Logical record length versions of both datasets are now available, in addition to the SPSS portable files previously released. In addition, a STATA version of Part 1, Household Survey, is provided. Also, SAS and SPSS data definition statements for both datasets have been created.
- 1998-10-15 Part 1 data have been revised to correct rounding errors in integer variables, and Part 2 has been added to the collection.
Related Publications
- List all ~76 citations associated with this study
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Variables
Instructional Resources
ICPSR has created the following instructional guides that utilize data from this study:
Additional materials can be found on our Resources for Instructors site.
Instructional guides that utilize this dataset are available:
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Gender and Occupation: A Data-Driven Learning Guide - Inter-university Consortium for Political and Social Research
The term sex is typically used to refer to a person's biological maleness or femaleness, whereas gender refers to the psychological, social, and cultural aspects of masculinity or femininity.
A large increase in women's labor force participation has occurred since World War II in the United States. Despite gains women have made, significant gender differences in occupational attainment remain. Women tend to be concentrated in office and administrative support and service occupations. In comparison, men tend to be concentrated in "blue collar" jobs, including skilled production, craft and repair work as well semi-skilled and unskilled manual jobs. Studies have found that women and men are equally likely to work in sales occupations.
The goal of this exercise is to explore gender differences in occupation. Summary statistics, including the mean, median, mode, and standard deviation will be used.
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Utilities
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