The annual personal income of Davenport Metro Area (IA-IL) was $43,971 in 2014. The annual personal income of Peoria Metro Area (IL) was $43,974 in 2014.

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 Peoria Metro Area (IL) or Davenport Metro Area (IA-IL)

  • API

    Quarterly Personal Income for State of Iowa

    mydata.iowa.gov | Last Updated 2020-10-04T01:30:26.000Z

    This dataset provides quarterly personal income estimates for State of Iowa produced by the U.S. Bureau of Economic Analysis . Data includes the following estimates: personal income, per capita personal income, proprietors' income, farm proprietors' income, compensation of employees and private nonfarm earnings, compensation, and wages and salaries for wholesale trade. Personal income, proprietors' income, and farm proprietors' income available beginning 1997; per capita personal income available beginning 2010; and all other data beginning 1998. Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income for Iowa is the income received by, or on behalf of all persons residing in Iowa, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s midquarter population estimates. Proprietors' income is the current-production income (including income in kind) of sole proprietorships, partnerships, and tax-exempt cooperatives. Corporate directors' fees are included in proprietors' income. Proprietors' income includes the interest income received by financial partnerships and the net rental real estate income of those partnerships primarily engaged in the real estate business. Farm proprietors’ income as measured for personal income reflects returns from current production; it does not measure current cash flows. Sales out of inventories are included in current gross farm income, but they are excluded from net farm income because they represent income from a previous year’s production. Compensation to employees is the total remuneration, both monetary and in kind, payable by employers to employees in return for their work during the period. It consists of wages and salaries and of supplements to wages and salaries. Compensation is presented on an accrual basis - that is, it reflects compensation liabilities incurred by the employer in a given period regardless of when the compensation is actually received by the employee. Private nonfarm earnings is the sum of wages and salaries, supplements to wages and salaries, and nonfarm proprietors' income, excluding farm and government. Private nonfarm wages and salaries is wages and salaries excluding farm and government. Wages and salaries is the remuneration receivable by employees (including corporate officers) from employers for the provision of labor services. It includes commissions, tips, and bonuses; employee gains from exercising stock options; and pay-in-kind. Judicial fees paid to jurors and witnesses are classified as wages and salaries. Wages and salaries are measured before deductions, such as social security contributions, union dues, and voluntary employee contributions to defined contribution pension plans. More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

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    Annual Personal Income for State of Iowa

    mydata.iowa.gov | Last Updated 2020-08-07T19:49:28.000Z

    This dataset provides annual personal income estimates for State of Iowa produced by the U.S. Bureau of Economic Analysis beginning in 1997. Data includes the following estimates: personal income, per capita personal income, wages and salaries, supplements to wages and salaries, private nonfarm earnings, compensation of employees, average compensation per job, and private nonfarm compensation. Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income for Iowa is the income received by, or on behalf of all persons residing in Iowa, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s annual midyear (July 1) population estimates. Wages and salaries is defined as the remuneration receivable by employees (including corporate officers) from employers for the provision of labor services. It includes commissions, tips, and bonuses; employee gains from exercising stock options; and pay-in-kind. Judicial fees paid to jurors and witnesses are classified as wages and salaries. Wages and salaries are measured before deductions, such as social security contributions, union dues, and voluntary employee contributions to defined contribution pension plans. Supplements to wages and salaries consists of employer contributions for government social insurance and employer contributions for employee pension and insurance funds. Private nonfarm earnings is the sum of wages and salaries, supplements to wages and salaries, and nonfarm proprietors' income, excluding farm and government. Compensation to employees is the total remuneration, both monetary and in kind, payable by employers to employees in return for their work during the period. It consists of wages and salaries and of supplements to wages and salaries. Compensation is presented on an accrual basis - that is, it reflects compensation liabilities incurred by the employer in a given period regardless of when the compensation is actually received by the employee. Average compensation per job is compensation of employees divided by total full-time and part-time wage and salary employment. Private nonfarm compensation is the sum of wages and salaries and supplements to wages and salaries, excluding farm and government. More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

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    Quarterly Census of Employment and Wages (QCEW)

    data.edd.ca.gov | Last Updated 2020-09-10T19:54:34.000Z

    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 Personal Income for State of Iowa by County

    mydata.iowa.gov | Last Updated 2020-08-07T21:44:03.000Z

    This dataset provides annual personal income estimates for State of Iowa counties produced by the U.S. Bureau of Economic Analysis beginning in 1997. Data includes the following estimates: personal income and per capita personal income. Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income is the income received by, or on behalf of all persons residing in the Iowa county, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s annual midyear (July 1) population estimates for the county. More terms and definitions are available on https://apps.bea.gov/regional/definitions/. Less

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    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.

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    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

  • 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

    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 - Subregion

    data.bayareametro.gov | Last Updated 2019-10-25T20:41:25.000Z

    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

    Feed The Future Uganda Population-Based Survey, Women's Empowerment in Agriculture Index-Household File

    data.usaid.gov | Last Updated 2018-11-11T02:38:29.000Z

    The Uganda Population-Based Survey (PBS) provides a comprehensive assessment of the current status of agriculture and food security in 38 districts across eight regions of the country. The PBS was conducted from October 25 to December 30, 2012. The overall objective of the survey is to provide baseline data on living standards, nutritional status, and women's empowerment in agriculture in the Zone Of Influence. This dataset is the second of two datasets needed to calculate the Women's Empowerment in Agriculture Index-related measures.