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
Albany
36,454
Allegany
23,030
Broome
27,744
Cattaraugus
24,628
Cayuga
29,022
Chautauqua
24,825
Chemung
28,115
Chenango
26,717
Clinton
26,772
Columbia
35,581
Cortland
26,979
Delaware
26,629
Dutchess
38,048
Erie
32,347
Essex
30,273
Franklin
25,491
Fulton
26,875
Genesee
29,465
Greene
27,271
Hamilton
25,918
Herkimer
26,151
Jefferson
25,884
Lewis
26,169
Livingston
27,073
Madison
28,925
Monroe
32,502
Montgomery
25,427
Nassau
49,211
Niagara
29,824
Oneida
28,548
Onondaga
32,678
Ontario
35,121
Orange
33,472
Orleans
25,261
Oswego
27,217
Otsego
27,680
Putnam
45,905
Rensselaer
34,280
Rockland
38,076
Saratoga
41,709
Schenectady
31,412
Schoharie
28,712
Schuyler
26,484
Seneca
27,366
St. Lawrence
24,473
Steuben
28,600
Suffolk
42,204
Sullivan
29,292
Tioga
31,330
Tompkins
31,464
Ulster
33,879
Warren
33,605
Washington
27,156
Wayne
29,028
Westchester
54,572
Wyoming
27,150
Yates
27,512
Value for New York (US Dollars): $37,470
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.