Join us on social media for Asian American and Pacific Islander (AAPI) Women’s Equal Pay Day, March 9, 2021. The Twitterstorm will take place 11 a.m. – 12 p.m. Pacific / 2-3 p.m. Eastern.
We will raise awareness of how AAPI women and girls experience the wage gap and increase visibility of work and wealth disparities in our communities that are often rendered invisible in mainstream conversations about the wage gap.
Use hashtags #AAPIEqualPay and #NotYourModelMinority.
Sample tweets and graphics available in the following toolkit: bit.ly/AAPIEPD2021
About AAPI Equal Pay Day
For every $1 earned by white, non-Hispanic men working full time, year-round in 2019, AAPI women working full time, year-round earned 85 cents, on average. Even when controlling for factors such as education and experience, the pay gaps persist and start early in women’s careers and contribute to a wealth gap that follows them throughout their lifetimes.
When we look past the average, some AAPI ethnic subgroups, particularly Southeast Asian and Pacific Islander women, have much bigger wage gaps. Between 2015 and 2019, Burmese women working full time, year-round earned, on average, $0.52 cents for every $1 earned by their white, non-Hispanic male counterparts. The “model minority myth,” or the idea that AAPI women are all well off and don’t need support, furthers the misconception that we don’t need additional resources or support.
Our wages touch every part of our lives, from our ability to get the health care we need, to make decisions about if and when to start a family, and support the people who depend on us. The impact of the pandemic has been even more devastating for women making low and unequal wages, who have little to no safety net in a time of unprecedented long-term unemployment.
**A note about data from the Center for American Progress: This year we adjusted our methodology for calculating the AAPI wage gap to be more inclusive of PI women. In addition, we have updated how we calculate wage gaps for disaggregated AAPI subpopulations to ensure better data reliability by looking at a 5-year range rather than a single year. For more detail, messaging guidance, and a full index of disaggregated data please refer to this resource.