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Black women make $0.48 for every $1.00 earned by Asian men, $0.57 for every $1.00 made by white men, $0.52 for every $1.00 made by white non-hispanic men, and $0.84 for every $1.00 made by Asian women, according to the US Census: https://www2.census.gov/programs-surveys/cps/tables/time-series/historical-income-people/p02.xls

So, why does Congressman Cummings’ office want to make a problem of white men vs black women in a tweet?

More generally males earn more than females, even with the same job, education, and experience.

However, the highest earning group is Asian males and the income of Asian females is actually very close to that of Black males.

For half a century, Asian immigrants have benefitted from the “minority” status, affirmative action, and minority contract set-asides meant for Black Americans, Native Americans, and women. Some Asian-Indians have gone as far as pretending to be Black Americans.

“Elijah E. Cummings @RepCummings
In 2017, Black women earned, on average, $0.61 for every $1.00 made by white, non-Hispanic male workers. Today, we must acknowledge that the pay gap is compounded by race. Men and women, regardless of race, deserve ‪#EqualPayForEqualWork‬.‪ #BlackWomenEqualPay‬ 4:32 PM · Aug 22, 2019” https://archive.li/I8tA2

White males make $0.85 for each $1.00 Asian males make; Black males make $0.62 cents for each $1.00 Asian males make; Hispanic females make $ 0.42 for each $1.00 Asian males make; Black females make $0.48; White females $0.53 cents; Asian females $0.58.

Updated: Asian-Indian households have the highest median income of all ethnic groups at $114,261; Median arnings of $148,019. https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmk

Pew had Asian-Indian households median income at $100,000: https://www.pewresearch.org/fact-tank/2017/09/08/key-facts-about-asian-americans

Asian-Indians are the wealthiest Asian group and mask the relative poverty of many southeast Asians, who needed to come to America as refugees.

The highest income group in the United States is ASIAN MALES, not white males. Asian females have the highest earnings among females. Clearly Asians do not need “minority” status. They do not need minority contract set-asides, nor affirmative action. Their economic position busts the myth of “people of color” as a persecuted group.

The lowest earning group is “hispanic females”. However, hispanic simply means someone from the Spanish or Portuguese speaking world of any race or ethnic origin. (Many of the indigenous peoples in Latin America do not even speak Spanish. The census classifies them as American Indian.) Thus, it seems that “white” hispanic and non-hispanic should really be lumped together.

Median income 2017 (half above and half below)
Asian males $48,842
Asian females $28,260
White males $41,578
White females $25,793
“Hispanic origin” males $30,691
“Hispanic origin” females $ 20,312
Black males $30,112
Black females $23,639
White non-hispanic males $45,836
White non-hispanic females $27,116
https://www2.census.gov/programs-surveys/cps/tables/time-series/historical-income-people/p02.xls

Median Value of Assets for US Households 2014
Net Worth
Asian alone: $ 156,500
White alone: $102,800
Hispanic origin (any race) $17,530
Black alone: $9,590
Net Worth (Excluding Equity in Own Home)
Asian alone $ 65,120
White alone $ 33,570
Hispanic origin (any race) $ 6,253
Black alone $ 3,339
https://www2.census.gov/programs-surveys/demo/tables/wealth/2014/wealth-asset-ownership/wealth_tables_cy2014.xlsx

The United States needs to reserve “minority” status for African Americans, Native Americans, and women, as originally intended. Upper caste Asian-Indians who cannot get affirmative action in India (called “reservation”) come to the United States to get affirmative action; minority status; minority contract set-asides. If you take away these “minority” perks for immigrants, a large part of immigration would dry up, almost overnight.

“A Minority Business Enterprise (MBE) is an American term which is defined as a business which is at least 51% owned, operated and controlled on a daily basis by one or more (in combination) American citizens of the following ethnic minorityand/or gender (e.g. woman-owned) and/or military veteran classifications:
1. African American
2. Asian American (includes West Asian Americans (India, etc.) and East Asian Americans (Japan, Korea, etc.))
3. Hispanic American – Persons with origins from Latin America, South America, Portugal and Spain.(SBA.gov)
4. Native American including Aleuts
5. Service-Disabled Veteran Owned aka SDVBE, aka DVBE* which became a federally certified classification in 1999, subsequent to the passage legislation by the United States Congress through the enactment of The Veterans Entrepreneurship and Small Business Act of 1999 (The Act); legislation that was further expanded by Congress in 2001.**
According to the U.S. Small Business Administration, minorities own more than 4.1 million firms, and account for nearly $700 billion in revenues.
MBE’s can be self-identified but are typically certified by a city, state or federal agency. DiversityBusiness.com is the primary organization for connecting businesses with Fortune 1000, Government Agencies and Educational organizations.
https://en.wikipedia.org/wiki/Minority_business_enterprise

“Some minority groups are presumed to be socially and economically disadvantaged and can qualify for the 8(a) program. These groups include: African Americans, Hispanic Americans, Native Americans, Asian Pacific Americans and Subcontinent Asian Americans. Individuals who are not members of one or more of these groups can be considered for the 8(a) program, but they must provide substantial evidence and documentation that demonstrates that they have been subjected to bias or discrimination and are economically disadvantaged. Firms owned by Alaska Native Corporations, Indian Tribes, Native Hawaiian Organizations and Community Development Corporations can also apply to the program.”
https://www.sba.gov/starting-business/how-start-business/business-types/minority-owned-businesses

Dr. King actually talked about the problem of new immigrants being favored over the descendants of slaves, historically, starting at ca 22 min http://youtu.be/RMLyhshxQc8

From the US Census:
“The U.S. Census Bureau must adhere to the 1997 Office of Management and Budget (OMB) standards on race and ethnicity which guide the Census Bureau in classifying written responses to the race question:
White – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.
Black or African American – A person having origins in any of the Black racial groups of Africa.
American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.
Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.

The 1997 OMB standards permit the reporting of more than one race. An individual’s response to the race question is based upon self-identification. 

An individual’s response to the race question is based upon self-identification. The Census Bureau does not tell individuals which boxes to mark or what heritage to write in. For the first time in Census 2000, individuals were presented with the option to self-identify with more than one race and this continued with the 2010 Census.

People who identify with more than one race may choose to provide multiple races in response to the race question. For example, if a respondent identifies as “Asian” and “White,” they may respond to the question on race by checking the appropriate boxes that describe their racial identities and/or writing in these identities on the spaces provided.

What is Race?

The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification.

The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race item include racial and national origin or sociocultural groups. People may choose to report more than one race to indicate their racial mixture, such as “American Indian” and “White.” People who identify their origin as Hispanic, Latino, or Spanish may be of any race.

OMB requires five minimum categories: White, Black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander.

Reasons for Collecting Information on Race

Information on race is required for many Federal programs and is critical in making policy decisions, particularly for civil rights. States use these data to meet legislative redistricting principles. Race data also are used to promote equal employment opportunities and to assess racial disparities in health and environmental risks.

Race and Ethnicity Research

The Census Bureau has a long history of conducting research to improve questions and data on race and ethnicity. Since the 1970s, the Census Bureau has conducted content tests to research and improve the design and function of different questions, including questions on race and ethnicity.”
https://archive.li/https://www.census.gov/topics/population/race/about.html

Disclaimer: The statistics in this post were either retyped from the census documents or calculations based on the census documents. If you need this for a school project or any other purpose, please go to the original link and double check the statistics. While we think it is accurate, it is always best to check our work and the work of anyone else. Errors can occur. We make no guarantees.