About this application: This application provides summary profiles showing frequently requested data items from various US Census Bureau programs. Profiles are available for the nation, states, and counties.
Per capita income in past 12 months (in 2018 dollars), 2014-2018 - (US Dollars)
County
Value
Ada
33,352
Adams
25,143
Bannock
24,555
Bear Lake
24,654
Benewah
23,502
Bingham
21,322
Blaine
32,861
Boise
30,660
Bonner
27,590
Bonneville
27,272
Boundary
25,401
Butte
25,941
Camas
30,803
Canyon
20,807
Caribou
26,908
Cassia
21,547
Clark
16,181
Clearwater
22,844
Custer
24,545
Elmore
23,547
Franklin
22,367
Fremont
21,782
Gem
20,776
Gooding
22,542
Idaho
21,584
Jefferson
22,934
Jerome
20,820
Kootenai
29,429
Latah
25,623
Lemhi
23,042
Lewis
24,052
Lincoln
20,188
Madison
15,626
Minidoka
23,578
Nez Perce
27,753
Oneida
21,575
Owyhee
21,935
Payette
25,002
Power
22,199
Shoshone
24,204
Teton
30,554
Twin Falls
24,222
Valley
30,838
Washington
21,414
Value for Idaho (US Dollars): $26,772
Sources: U.S. Census Bureau, American Community Survey (ACS) and Puerto Rico Community Survey (PRCS), 5-Year Estimates. The PRCS is part of the Census Bureau's ACS, customized for Puerto Rico. Both Surveys are updated every year.
Definition
Per capita income is the mean income computed for every man, woman, and child in a particular group including those living in group quarters. It is derived by dividing the aggregate income of a particular group by the total population in that group. This measure is rounded to the nearest whole dollar. For the complete definition, go to ACS subject definitions "Income in the Past 12 Months, Per Capita Income."
Source and Accuracy
This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12 month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.
Statistics from all surveys are subject to sampling and nonsampling error. Sampling error is the uncertainty between an estimate based on a sample and the corresponding value that would be obtained if the estimate were based on the entire population (as from a census). Measures of sampling error are provided in the form of margins of error for all estimates included with ACS and PRCS published products. The Census Bureau recommends that data users incorporate this information into their analyses, as sampling error in survey estimates could impact the conclusions drawn from the results. The data for each geographic area are presented together with margins of error at Using margins of error. A more detailed explanation of margins of error and a demonstration of how to use them is provided below.
For more information on sampling and estimation methodology, confidentiality, and sampling and nonsampling errors, please see the Multiyear Accuracy (US) and the Multiyear Accuracy (Puerto Rico) documents at "Documentation - Accuracy of the data."
Margin of Error
As mentioned above, ACS estimates are based on a sample and are subject to sampling error. The margin of error measures the degree of uncertainty caused by sampling error. The margin of error is used with an ACS estimate to construct a confidence interval about the estimate. The interval is formed by adding the margin of error to the estimate (the upper bound) and subtracting the margin of error from the estimate (the lower bound). It is expected with 90 percent confidence that the interval will contain the full population value of the estimate. The following example is for demonstrating purposes only. Suppose the ACS reported that the percentage of people in a state who were 25 years and older with a bachelor's degree was 21.3 percent and that the margin of error associated with this estimate was 0.7 percent. By adding and subtracting the margin of error from the estimate, we calculate the 90-percent confidence interval for this estimate:
Therefore, we can be 90 percent confident that the percent of the population 25 years and older having a bachelor's degree in a state falls somewhere between 20.6 percent and 22.0 percent.