The Gender Pay Gap Methodology

Overview
PayScale's Inside the Gender Pay Gap report examines the difference in median earnings of men and women overall, as well as by marital and family status, across industry, job family, degree level, generation, management status, job level, state, and metropolitan statistical area. Using our proprietary compensation algorithm, we are able to estimate a controlled median pay for females by adjusting for outside compensable factors across gender (years of experience, education, company size, management responsibilities, skills, and more), and calculate the difference in pay between similar men and women working the same jobs. All data is collected from ~1.4 million full-time employees who successfully completed the PayScale Survey between July 2013 and July 2015.

Definitions

Gender:

  • Male: Respondents who identify as male.
  • Female: Respondents who identify as female.

Marital and Family Status Personas:

  • Male, Married w/ Kids: Respondents who identify as male, have kids, and are married or in a domestic relationship.
  • Female, Married w/ Kids: Respondents who identify as female, have kids, and are married or in a domestic relationship.
  • Male, Single w/ Kids: Respondents who identify as male, have kids, and are single, divorced, or widowed.
  • Female, Single w/ Kids: Respondents who identify as female, have kids, and are single, divorced, or widowed.
  • Male, Single w/o Kids: Respondents who identify as male, do not have kids, and are single, divorced, or widowed.
  • Female, Single w/o Kids: Respondents who identify as female, do not have kids, and are single, divorced, or widowed.
  • Male, Married w/o Kids: Respondents who identify as male, do not have kids, and are married or in a domestic relationship.
  • Female, Married w/o Kids: Respondents who identify as female, do not have kids, and are married or in a domestic relationship.

Total Cash Compensation: TCC combines base annual salary or hourly wage, bonuses, profit sharing, tips, commissions, and other forms of cash earnings, as applicable. It does not include equity (stock) compensation, cash value of retirement benefits, or value of other non-cash benefits (e.g., healthcare).

Uncontrolled Median Pay: The median pay is the national median (50th Percentile) annual TCC. Half the people doing the job earn more than the median, while half earn less. The median pay for men and women are examined separately. Variables such as years of experience and education are not controlled for. This provides a picture of the differences in wages earned by men and women in an absolute sense.

Controlled Female Median Pay: Using our unique database and compensation algorithm, we estimate the controlled median pay by adjusting for outside compensable factors across genders. These factors include years of experience, education, company size, management responsibilities, skills and more. In order to provide an apples-to-apples comparison, we determine the characteristics of the typical man within a job and then adjust the characteristics of the typical woman in the same job to match those of the average man. The result is the median pay calculated for the average woman if they had the exact same breakdown of measured compensable factors as the average man.

Controlled Pay Gap: This is the difference in male median pay and controlled female median pay. That is, this is the pay difference that exists between the genders after we control for all measured compensable factors.

  • Note on how to read the "Controlled Pay Gap": For Controlled Pay Gap "x":
    • If negative, Persona B makes "x" percent less than Persona A after we control for all other measured compensable factors.
    • If positive, Persona B makes "x" percent more than Persona A after we control for all other measured compensable factors.

% Male: This is the percentage of respondents that are male.
% Female: This is the percentage of respondents that are female.
Percent of Total: This is the percent of all respondents (male or female).

Industry: This is the product or service of the respondent's organization as classified in the North American Industry Classification System (NAICS). NAICS is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy (http://www.census.gov/eos/www/naics/).

NAICS Code: This is the specific code associated with the respondent's industry assigned from the North American Industry Classification System (NAICS).

Tech Industry: The "Tech Industry" contains all workers classified in one of the following industries in the NAICS taxonomy (http://www.census.gov/eos/www/naics/):

  • Computer Systems Design and Related Services (NAICS Code 5415)
  • Computer and Electronic Product Manufacturing (NAICS Code 334)
  • Other Scientific and Technical Consulting Services (NAICS Code 54169)
  • Software Publishers (NAICS Code 5112)
  • Telecommunications (NAICS Code 517)
  • Data Processing, Hosting, and Related Services (NAICS Code 518)
  • Internet Publishing and Broadcasting and Web Search Portals (NAICS Code 51913)

Major Job Group: The Major Job Group is the highest level of the O*NET-SOC Taxonomy (http://www.onetcenter.org/taxonomy.html) that encompasses the respondent's occupation. Major Job Groups are the most general groupings of related occupations. All jobs are classified into one of the 23 Major Groups.

SOC Code: This is the specific code associated with the respondent's job from the Standard Occupational Classification (SOC) system. The Standard Occupational Classification (SOC) system is used by Federal statistical agencies to classify workers into occupational categories for the purpose of collecting, calculating, or disseminating data (http://www.bls.gov/soc/).

Relative Commonness by State:

  • Relative Commonness (For Females): This is the relative commonness for female workers in the given state compared to all workers in the state. For example, the relative commonness for female social workers in Connecticut is 1.94, therefore, it is nearly twice as likely for a female worker in Connecticut to be a social worker than all workers in Connecticut.
  • Most Relatively Common Job for Females: This is the job with the highest relative commonness for females in the given state.
  • Relative Commonness (For Males): This is the relative commonness for male workers in the given state compared to all workers in the state. For example, the relative commonness for male mechanical engineers in Connecticut is 2.02, therefore, it is just over twice as likely for a male worker in Connecticut to be a mechanical engineer than all workers in Connecticut.
  • Most Relatively Common Job for Males: This is the job with the highest relative commonness for males in the given state.

Degree Level: This is the highest degree level earned by the respondent.

School Category:

  • Public Schools: Schools identified by IPEDS as being publicly funded.
  • Private Not-For-Profit Schools: Schools identified by IPEDS as Private Not-for-Profit.
  • Private For-Profit Schools: Schools identified by IPEDS as Private For-Profit.
  • Research Universities: Schools categorized by the Carnegie basic higher education classification system in one of three categories:
    • RU/VH: Research Universities (very high research activity)
    • RU/H: Research Universities (high research activity)
    • DRU: Doctoral/Research Universities
  • Ivy League School: The eight schools in the Ivy League.
  • Party Schools: The 20 schools on the 2015 Princeton Review "Party Schools" list.
  • Sober Schools: The 20 schools on the 2015 Princeton Review "Sobers Schools" list.
  • Liberal Arts Schools: Schools with a Carnegie basic classification of "BAC/A&S Baccalaureate – Arts and Sciences". These generally are non-pre-professional, undergraduate-focused institutions, and usually have smaller enrollments.
  • Engineering Schools: Schools which grant more than 50 percent of their undergraduate degrees in math, sciences, computer science, engineering and engineering technology majors based on completions data from IPEDS. The idea is to identify science, engineering and technology-focused schools.
  • Business Schools: Schools which grant more than 50 percent of their undergraduate degrees in business management, marketing and related support services majors based on completions data from IPEDS.
  • Art / Design Schools: Schools which grant more than 50 percent of their undergraduate degrees in visual and performing arts majors based on completions data from IPEDS.
  • Religious Schools: Schools with a religious affiliation based on data from IPEDS.
  • For Sports Fans Schools: Schools with a Division 1 Football or Division 1 Basketball team.

Generation:

  • Generation Y: People who were born between 1982 and 2002.
  • Generation X: People who were born between 1965 and 1981.
  • Baby Boomers: People who were born between 1946 and 1964.

People Management Role: This is determined based off the yes/no response to the question "Do you supervise people?"

Job Level:

  • Executive Level: Workers with a Chief Executive title (CEO, CFO, etc.) or Vice Presidential title or a title with a comparable level or responsibility, years of experience, and management scope.
  • Director Level: Workers with a Director title or a title with a comparable level or responsibility, years of experience, and management scope.
  • Manager or Supervisor Level: Workers who supervise people and do not have a higher level title.
  • Individual Contributor Level: Workers who do not supervise people and do not have a higher level title.

State: This is the U.S. state in which the respondent works.

Metropolitan Statistical Areas (MSAs): These are the geographic areas in which the respondent works and are defined by the U.S. Office of Management and Budget (OMB) (December 2003 Definition).  To be considered an MSA, the area must contain a core urban population of 50,000 or more.  Each MSA consists of one or more counties, including the county containing the core urban area and any adjacent counties that have a high degree of social or economic integration with the urban core.  The latter is measured by commuting to work. (http://www.whitehouse.gov/sites/default/files/omb/assets/bulletins/b10-02.pdf). Note: Only the top 20 MSAs by population are included in this analysis.

% High Job Meaning: This is the percentage of respondents who answered "Very much so" or "Yes" to the question, "Does your work make the world a better place?"

% High Job Satisfaction: This is the percentage of respondents who answered "Extremely satisfied" or "Fairly satisfied" to the question, "How satisfied are you in your job?"

% High Job Stress: This is the percentage of respondents who answered "Fairly stressful" or "Extremely stressful" when asked "How stressful is your job/work environment?"

% Underemployed: This is the percentage of respondents who answered "Yes" to the question "Do you consider yourself underemployed?" or answered "I'm not sure" and did not answer "I am happily employed" when further prompted "Tell us more about your employment situation."

% Have Strong Professional Role Model Within Organization: This is the percentage of respondents who said "Yes" when asked "Do you have strong professional role models within your organization?"

% Have Been Recommended for Leadership/Management Training by Manager: This is the percentage of respondents who said "Yes" when asked "Has your manager ever recommended you for leadership or management training?"

Home/Family Prioritization:

  • % Never Prioritize Family Obligations Over Professional Obligations: This is the percentage of respondents who said "Never" when asked "How often do you prioritize home or family obligations over professional obligations or opportunities?"
  • % Prioritize Family Obligations Over Professional Obligations 1-4x a Year: This is the percentage of respondents who said "1-4x a year" when asked "How often do you prioritize home or family obligations over professional obligations or opportunities?"
  • % Prioritize Family Obligations Over Professional Obligations 1-2x a Month: This is the percentage of respondents who said "1-2x a month" when asked "How often do you prioritize home or family obligations over professional obligations or opportunities?"
  • % Prioritize Family Obligations Over Professional Obligations 1x or More a Week: This is the percentage of respondents who said "1x or more a week" when asked "How often do you prioritize home or family obligations over professional obligations or opportunities?"
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