View monthly updates and historical trends for Seattle, WA Unemployment Rate. Source: Bureau of Labor Statistics. Track economic data with YCharts analyti…

Graph and download economic data for Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) (SEAT653URN) from Jan 1994 to Aug 2025 about Seattle, WA, unemployment, rate, and USA.

Graph and download economic data for Unemployment Rate in King County, WA from Jan 1990 to Aug 2025 about King County, WA; Seattle; WA; unemployment; rate; and USA.

Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) was 4.60% in August of 2025, according to the United States Federal Reserve. Historically, Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) reached a record high of 17.60 in April of 2020 and a record low of 2.40 in February of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) - last updated from the United States Federal Reserve on December of 2025.

Graph and download economic data for Unemployment Rate in Pierce County, WA (WAPIER6URN) from Jan 1990 to Aug 2025 about Pierce County, WA; Seattle; WA; unemployment; rate; and USA.

View monthly updates and historical trends for Seattle-Tacoma-Bellevue, WA Unemployment Rate. Source: Bureau of Labor Statistics. Track economic data with…

In 2023, the unemployment rate in Washington was at *** percent. While no change from the previous year, the rate follows a steep decrease from 2020, when the unemployment rate stood at *** percent. The state's highest rate of employment since 1992 was *** percent in 2010.

Graph and download economic data for Unemployment Rate in King County, WA (LAUCN530330000000003A) from 1990 to 2024 about King County, WA; Seattle; WA; unemployment; rate; and USA.

Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) was 4.30% in August of 2025, according to the United States Federal Reserve. Historically, Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) reached a record high of 17.50 in April of 2020 and a record low of 2.70 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) - last updated from the United States Federal Reserve on November of 2025.

Graph and download economic data for Unemployment Rate in Snohomish County, WA (WASNOH0URN) from Jan 1990 to Aug 2025 about Snohomish County, WA; Seattle; WA; unemployment; rate; and USA.

Graph and download economic data for Unemployment Rate in Pierce County, WA (LAUCN530530000000003A) from 1990 to 2024 about Pierce County, WA; Seattle; WA; unemployment; rate; and USA.

Graph and download economic data for Unemployment Rate in Washington (WAUR) from Jan 1976 to Aug 2025 about WA, unemployment, rate, and USA.

All Employees: Professional and Business Services: Employment Services in Seattle-Bellevue-Everett, WA (MD) was 24.30000 Thous. of Persons in March of 2025, according to the United States Federal Reserve. Historically, All Employees: Professional and Business Services: Employment Services in Seattle-Bellevue-Everett, WA (MD) reached a record high of 48.00000 in December of 1999 and a record low of 14.60000 in January of 1993. Trading Economics provides the current actual value, an historical data chart and related indicators for All Employees: Professional and Business Services: Employment Services in Seattle-Bellevue-Everett, WA (MD) - last updated from the United States Federal Reserve on October of 2025.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Seattle. The dataset can be utilized to gain insights into gender-based income distribution within the Seattle population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Seattle, among individuals aged 15 years and older with income, there were 312.52 thousand men and 289.09 thousand women in the workforce. Among them, 189,091 men were engaged in full-time, year-round employment, while 140,215 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 2.74% fell within the income range of under $24,999, while 3.56% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 57.49% of men in full-time roles earned incomes exceeding $100,000, while 45.01% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Seattle median household income by race. You can refer the same here

Table from the American Community Survey (ACS) 5-year series on poverty and employment status related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B23025 Employment Status for the Population 16 years and over, B23024 Poverty Status by Disability Status by Employment Status for the Population 20 to 64 years, B17010 Poverty Status of Families by Family Type by Presence of Related Children under 18 years, C17002 Ratio of Income to Poverty Level in the Past 12 Months. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B23025, B23024, B17010, C17002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Graph and download economic data for Unemployment Rate in Seattle-Tacoma-Bellevue, WA (MSA) from Jan 1994 to Aug 2025 about Seattle, WA, unemployment, rate, and USA.

Graph and download economic data for All Employees: Service-Providing in Seattle-Tacoma-Bellevue, WA (MSA) (SMU53426600700000001SA) from Jan 1990 to Aug 2025 about Seattle, WA, services, employment, and USA.

Graph and download economic data for Unemployed Persons in Seattle-Tacoma-Bellevue, WA (MSA) (LAUMT534266000000004) from Jan 1994 to Aug 2025 about Seattle, WA, household survey, persons, unemployment, and USA.

Graph and download economic data for Employment in Seattle-Tacoma-Bellevue, WA (MSA) (LASMT534266000000005) from Jan 1994 to Aug 2025 about Seattle, WA, employment, and USA.

Graph and download economic data for Employed Persons in Seattle-Tacoma-Bellevue, WA (MSA) (LAUMT534266000000005) from Jan 1994 to Aug 2025 about Seattle, WA, household survey, persons, employment, and USA.