The annual personal income of Kansas City Metro Area (MO-KS) was $44,336 in 2009.

Annual Personal Income in US$

Per capita personal income was computed using Census Bureau midyear population estimates. Estimates for 2010-2014 reflect county population estimates available as of March 2015. All dollar estimates are in current dollars (not adjusted for inflation).

Above charts are based on data from the U.S. Bureau of Economic Analysis | Data Source | ODN Dataset | API - Notes:

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Economy and Personal Income Datasets Involving Kansas City Metro Area (MO-KS)

  • API

    Quarterly Census of Employment and Wages (QCEW)

    data.edd.ca.gov | Last Updated 2019-10-04T21:41:21.000Z

    The Quarterly Census of Employment and Wages (QCEW) Program is a Federal-State cooperative program between the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the California EDD’s Labor Market Information Division (LMID). The QCEW program produces a comprehensive tabulation of employment and wage information for workers covered by California Unemployment Insurance (UI) laws and Federal workers covered by the Unemployment Compensation for Federal Employees (UCFE) program. The QCEW program serves as a near census of monthly employment and quarterly wage information by 6-digit industry codes from the North American Industry Classification System (NAICS) at the national, state, and county levels. At the national level, the QCEW program publishes employment and wage data for nearly every NAICS industry. At the state and local area level, the QCEW program publishes employment and wage data down to the 6-digit NAICS industry level, if disclosure restrictions are met. In accordance with the BLS policy, data provided to the Bureau in confidence are used only for specified statistical purposes and are not published. The BLS withholds publication of Unemployment Insurance law-covered employment and wage data for any industry level when necessary to protect the identity of cooperating employers. Data from the QCEW program serve as an important input to many BLS programs. The Current Employment Statistics and the Occupational Employment Statistics programs use the QCEW data as the benchmark source for employment. The UI administrative records collected under the QCEW program serve as a sampling frame for the BLS establishment surveys. In addition, the data serve as an input to other federal and state programs. The Bureau of Economic Analysis (BEA) of the Department of Commerce uses the QCEW data as the base for developing the wage and salary component of personal income. The U.S. Department of Labor’s Employment and Training Administration (ETA) and California's EDD use the QCEW data to administer the Unemployment Insurance program. The QCEW data accurately reflect the extent of coverage of California’s UI laws and are used to measure UI revenues; national, state and local area employment; and total and UI taxable wage trends. The U.S. Department of Labor’s Bureau of Labor Statistics publishes new QCEW data in its County Employment and Wages news release on a quarterly basis. The BLS also publishes a subset of its quarterly data through the Create Customized Tables system, and full quarterly industry detail data at all geographic levels.

  • API

    Annual Income - Median and Per Capita

    data.mesaaz.gov | Last Updated 2019-02-11T20:21:44.000Z

    The Annual Income - Median and Per Capita dataset shows Median Household Income and Per Capita Income for the City of Mesa, and some comparative numbers from other neighboring communities as well as Maricopa County. Census money income is defined as income received on a regular basis (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive part of their income in the form of noncash benefits, such as food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents which may take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, users should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries much better than other sources of income and that the reported wage and salary income is nearly equal to independent estimates of aggregate income. Census also derives alternative income measures that systematically remove or add various income components such as deducting payroll taxes and federal and state income taxes and including the value of specific noncash benefits, food stamps, school lunches, housing subsidies, health insurance programs, and return on home equity. These alternative measures are derived from information collected in Census surveys along with information from other agencies such as the Centers for Medicare and Medicaid Services (CMS), the U.S. Bureau of Labor Statistics, the U.S. Department of Agriculture, the U.S. Internal Revenue Service, and the U.S. Office of Personnel Management (OPM). What does Income Include? http://www.census.gov/cps/data/incdef.html

  • API

    Medicare Hospital Cost Report PUF 2014

    data.cms.gov | Last Updated 2019-12-06T14:54:38.000Z

    The Hospital Cost Report Public Use File (Hospital Cost Report PUF) presents select measures provided by hospitals through their annual cost report, and is organized at the hospital level. The Hospital Cost Report PUF is available in a downloadable, user-friendly Excel format. The PUF does not contain all measures reported in the cost reports, but rather includes a subset of commonly used measures. Any hospital that submitted a cost report in a given year will be included in the PUF. For a full list of variables included in this PUF and their descriptions, please see the attachments. The variables in the Hospital Cost Report PUF have not been edited or changed and will be identical to what is available in the online HCRIS system in the 2014 SAS dataset as of July 15, 2018. Please note however that the HCRIS datasets are updated quarterly, while the PUF is created annually, and therefore the data may not match if compared to later versions of the HCRIS files.

  • API

    Annual Income

    data.mesaaz.gov | Last Updated 2019-02-11T18:03:34.000Z

    The Annual Income dataset shows Household Income ranges for the City of Mesa, and some comparative numbers from other neighboring communities as well as Maricopa County. Source is American FactFinder at census.gov. See source link below. Saved query is found in attachments. Change file name from *.txt to *.aff and retrieve using the "Load Search or Query" button on the main page at http://factfinder.census.gov. Census money income is defined as income received on a regular basis (exclusive of certain money receipts such as capital gains) before payments for personal income taxes, social security, union dues, medicare deductions, etc. Therefore, money income does not reflect the fact that some families receive part of their income in the form of noncash benefits, such as food stamps, health benefits, subsidized housing, and goods produced and consumed on the farm. In addition, money income does not reflect the fact that noncash benefits are also received by some nonfarm residents which may take the form of the use of business transportation and facilities, full or partial payments by business for retirement programs, medical and educational expenses, etc. Data users should consider these elements when comparing income levels. Moreover, users should be aware that for many different reasons there is a tendency in household surveys for respondents to underreport their income. Based on an analysis of independently derived income estimates, the Census Bureau determined that respondents report income earned from wages or salaries much better than other sources of income and that the reported wage and salary income is nearly equal to independent estimates of aggregate income. Census also derives alternative income measures that systematically remove or add various income components such as deducting payroll taxes and federal and state income taxes and including the value of specific noncash benefits, food stamps, school lunches, housing subsidies, health insurance programs, and return on home equity. These alternative measures are derived from information collected in Census surveys along with information from other agencies such as the Centers for Medicare and Medicaid Services (CMS), the U.S. Bureau of Labor Statistics, the U.S. Department of Agriculture, the U.S. Internal Revenue Service, and the U.S. Office of Personnel Management (OPM). What does Income Include? http://www.census.gov/cps/data/incdef.html

  • API

    2011 National Household Survey (NHS) - Income by Census Tracts, Dissemination Areas, Wards and Urban Service Areas

    data.strathcona.ca | Last Updated 2016-12-16T16:03:17.000Z

    The data shows income frequency distribution for individuals and households in four different boundary types. The data was provided by Statistics Canada but it has been sectioned and transposed. The fields come from NHS profile reports of Statistics Canada and some information may not be available for all the boundaries. The fields have been arranged in the same order as NHS profile reports. To see a more complete description of the fields click on this link: http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/details/Page.cfm?Lang=E&Geo1=CSD&Code1=4811052&Data=Count&SearchText=Strathcona%20County&SearchType=Begins&SearchPR=01&A1=All&B1=All&GeoLevel=PR&GeoCode=10#tabs1 The field “Household income in 2010 of private households” in the Income of Households in 2010 section is not included in the data to avoid redundancy.

  • API

    LACERS Key Facts and Figures from Year End Financial Reports

    data.lacity.org | Last Updated 2019-09-12T19:20:10.000Z

    This is a collection of data reported in LACERS Comprehensive Annual Financial Report (CAFR) since Fiscal Year End 2003, including data from the annual Actuarial Valuations generated after the end of each Fiscal Year. Actuarial Valuations and CAFR documents, in electronic form, can be found on the LACERS.org website at https://www.lacers.org/aboutlacers/reports/index.html.

  • API

    Medicare Hospital Cost Report PUF 2015

    data.cms.gov | Last Updated 2019-12-06T14:40:48.000Z

    The Hospital Cost Report Public Use File (Hospital Cost Report PUF) presents select measures provided by hospitals through their annual cost report, and is organized at the hospital level. The Hospital Cost Report PUF is available in a downloadable, user-friendly Excel format. The PUF does not contain all measures reported in the cost reports, but rather includes a subset of commonly used measures. Any hospital that submitted a cost report in a given year will be included in the PUF. For a full list of variables included in this PUF and their descriptions, please see the attachments. The variables in the Hospital Cost Report PUF have not been edited or changed and will be identical to what is available in the online HCRIS system in the 2015 SAS dataset as of December 2nd, 2019. Please note however that the HCRIS datasets are updated quarterly, while the PUF is created annually, and therefore the data may not match if compared to later versions of the HCRIS files.

  • API

    Michigan Dashboard

    midashboard.michigan.gov | Last Updated 2018-01-18T19:19:48.000Z

    Open Michigan (OpenMichigan@michigan.gov) is the official State of Michigan account. Any items created by other user accounts are not endorsed by the State of Michigan.

  • API

    Vital Signs: Jobs by Wage Level - Metro

    data.bayareametro.gov | Last Updated 2019-10-25T20:41:01.000Z

    VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1) FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations LAST UPDATED January 2019 DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage. DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html American Community Survey (2001-2017) http://api.census.gov CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour. Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average. Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017. Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases. In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling c

  • API

    Vital Signs: Jobs by Wage Level - Region

    data.bayareametro.gov | Last Updated 2019-10-25T20:41:27.000Z

    VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1) FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations LAST UPDATED January 2019 DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage. DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html American Community Survey (2001-2017) http://api.census.gov CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour. Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average. Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017. Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases. In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling c