labor_market_discrimination
Are Emily and Greg More Employable Than Lakisha and Jamal?
Description
Original data from the experiment run by Bertrand and Mullainathan (2004).
Usage
labor_market_discrimination
Format
A tibble with 4870 observations of 63 variables.
- education
Highest education, with levels of 0 = not reported; 1 = high school diploma; 2 = high school graduate; 3 = some college; 4 = college or more.
- n_jobs
Number of jobs listed on resume.
- years_exp
Number of years of work experience on the resume.
- honors
Indicator variable for which 1 = resume mentions some honors.
- volunteer
Indicator variable for which 1 = resume mentions some volunteering experience.
- military
Indicator variable for which 1 = resume mentions some military experience.
- emp_holes
Indicator variable for which 1 = resume mentions some employment holes.
- occup_specific
1990 Census Occupation Code. See sources for a key.
- occup_broad
Occupation broad with levels 1 = executives and managerial occupations, 2 = administrative supervisors, 3 = sales representatives, 4 = sales workers, 5 = secretaries and legal assistants, 6 = clerical occupations
- work_in_school
Indicator variable for which 1 = resume mentions some work experience while at school
Indicator variable for which 1 = email address on applicant's resume.
- computer_skills
Indicator variable for which 1 = resume mentions some computer skills.
- special_skills
Indicator variable for which 1 = resume mentions some special skills.
- first_name
Applicant's first name.
- sex
Sex, with levels of 'f' = female; 'm' = male.
- race
Race, with levels of 'b' = black; 'w' = white.
- h
Indicator variable for which 1 = high quality resume.
- l
Indicator variable for which 1 = low quality resume.
- call
Indicator variable for which 1 = applicant was called back.
- city
City, with levels of 'c' = chicago; 'b' = boston.
- kind
Kind, with levels of 'a' = administrative; 's' = sales.
- ad_id
Employment ad identifier.
- frac_black
Fraction of blacks in applicant's zip.
- frac_white
Fraction of whites in applicant's zip.
- l_med_hh_inc
Log median household income in applicant's zip.
- frac_dropout
Fraction of high-school dropouts in applicant's zip.
- frac_colp
Fraction of college degree or more in applicant's zip
- l_inc
Log per capita income in applicant's zip.
- col
Indicator variable for which 1 = applicant has college degree or more.
- expminreq
Minimum experience required, if any (in years when numeric).
- school_req
Specific education requirement, if any. 'hsg' = high school graduate, 'somcol' = some college, 'colp' = four year degree or higher
- eoe
Indicator variable for which 1 = ad mentions employer is 'Equal Opportunity Employer'.
- parent_sales
Sales of parent company (in millions of US $).
- parent_emp
Number of parent company employees.
- branch_sales
Sales of branch (in millions of US $).
- branch_emp
Number of branch employees.
- fed
Indicator variable for which 1 = employer is a federal contractor.
- frac_black_emp_zip
Fraction of blacks in employers's zipcode.
- frac_white_emp_zip
Fraction of whites in employer's zipcode.
- l_med_hh_inc_emp_zip
Log median household income in employer's zipcode.
- frac_dropout_emp_zip
Fraction of high-school dropouts in employer's zipcode.
- frac_colp_emp_zip
Fraction of college degree or more in employer's zipcode.
- l_inc_emp_zip
Log per capita income in employer's zipcode.
- manager
Indicator variable for which 1 = executives or managers wanted.
- supervisor
Indicator variable for which 1 = administrative supervisors wanted.
- secretary
Indicator variable for which 1 = secretaries or legal assistants wanted.
- off_support
Indicator variable for which 1 = clerical workers wanted.
- sales_rep
Indicator variable for which 1 = sales representative wanted.
- retail_sales
Indicator variable for which 1 = retail sales worker wanted.
- req
Indicator variable for which 1 = ad mentions any requirement for job.
- exp_req
Indicator variable for which 1 = ad mentions some experience requirement.
- com_req
Indicator variable for which 1 = ad mentions some communication skills requirement.
- educ_req
Indicator variable for which 1 = ad mentions some educational requirement.
- comp_req
Indicator variable for which 1 = ad mentions some computer skill requirement.
- org_req
Indicator variable for which 1 = ad mentions some organizational skills requirement.
- manuf
Indicator variable for which 1 = employer industry is manufacturing.
- trans_com
Indicator variable for which 1 = employer industry is transport or communication.
- bank_real
Indicator variable for which 1 = employer industry is finance, insurance or real estate.
- trade
Indicator variable for which 1 = employer industry is wholesale or retail trade.
- bus_service
Indicator variable for which 1 = employer industry is business or personal services.
- oth_service
Indicator variable for which 1 = employer industry is health, education or social services.
- miss_ind
Indicator variable for which 1 = employer industry is other or unknown.
- ownership
Ownership status of employer, with levels of 'non-profit'; 'private'; 'public'
Details
From the summary: "We study race in the labor market by sending fictitious resumes to help-wanted ads in Boston and Chicago newspapers. To manipulate perceived race, resumes are randomly assigned African-American- or White-sounding names. White names receive 50 percent more callbacks for interviews. Callbacks are also more responsive to resume quality for White names than for African-American ones. The racial gap is uniform across occupation, industry, and employer size. We also find little evidence that employers are inferring social class from the names. Differential treatment by race still appears to be prominent in the U. S. labor market."
Source
Bertrand, Marianne, and Mullainathan, Sendhil. Replication data for: Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. Nashville, TN: American Economic Association [publisher], 2004. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-12-06. \Sexpr[results=rd,stage=build]{tools:::Rd_expr_doi("10.3886/E116023V1")}.
Note: The description of the variables follows closely the labels provided in the original dataset, with small edits for clarity.