B99201. Imputation of Earnings in the Past 12 Months For the Population 16 Years and Over - Percent of Earnings Imputed [8] - American Community Survey Tables: 2005 -- 2007 (3-Year Estimates) (ACS07_3yr) - ACS 2007 (3-Year Estimates)

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ACS 2007 (3-Year Estimates)

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Survey: ACS 2007 (3-Year Estimates)

Data Source:

U.S. Census Bureau

Data set: American Community Survey Tables: 2005 -- 2007 (3-Year Estimates) (ACS07_3yr)

Table:

B99201. Imputation of Earnings in the Past 12 Months For the Population 16 Years and Over - Percent of Earnings Imputed [8]

Universe: Universe: Population 16 years and Over

Table Details

B99201.

Imputation of Earnings in the Past 12 Months For the Population 16 Years and Over - Percent of Earnings Imputed

Universe: Universe: Population 16 years and Over

Variable	Label
B99201001	Total
B99201002	No earnings imputed
B99201003	Dollar value of zero imputed
B99201004	More than 0 to less than 10 percent of total earnings for individual imputed
B99201005	10 to less than 25 percent of total earnings for individual imputed
B99201006	25 to less than 50 percent of total earnings for individual imputed
B99201007	50 to less than 100 percent of total earnings for individual imputed
B99201008	100 percent of total earnings for individual imputed

Relevant Documentation:

Excerpt from:	Social Explorer; U.S. Census Bureau; 2005-2007 American Community Survey 3-Year Summary File: Technical Documentation.
	ACS 2007-3yr Summary File: Technical Documentation -> Appendix B. Subject Definitions -> Quality Measures -> Imputation Rates

Imputation Rates

Missing data for a particular question or item is called item nonresponse. It occurs when a respondent fails to provide an answer to a required item. The ACS also considers invalid answers as item nonresponse. The Census Bureau uses imputation methods that either use rules to determine acceptable answers or use answers from similar housing units or people who provided the item information. One type of imputation, allocation, involves using statistical procedures, such as within-household or nearest neighbor matrices populated by donors, to impute for missing values.

Overall Person Characteristic Imputation Rate

This rate is calculated by adding together the weighted number of allocated items across a set of person characteristics, and dividing by the total weighted number of responses across the same set of characteristics.

Overall Housing Characteristic Imputation Rate

This rate is calculated by adding together the weighted number of allocated items across a set of household and housing unit characteristics, and dividing by the total weighted number of responses across the same set of characteristics. These rates give an overall picture of the rate of item nonresponse for a geographic area.

Excerpt from:	Social Explorer; U.S. Census Bureau; 2005-2007 American Community Survey 3-Year Summary File: Technical Documentation.
	ACS 2007-3yr Summary File: Technical Documentation -> Appendix B. Subject Definitions -> Population Variables -> Income in the Past 12 Months -> Earnings

Earnings

Earnings are defined as the sum of wage or salary income and net income from self-employment. Earnings represent the amount of income received regularly for people 16 years old and over before deductions for personal income taxes, Social Security, bond purchases, union dues, Medicare deductions, etc. An individual with earnings is one who has either wage/salary income or self-employment income, or both. Respondents who "break even" in self-employment income and therefore have zero self-employment earnings also are considered "individuals with earnings."

Excerpt from:	Social Explorer; U.S. Census Bureau; 2005-2007 American Community Survey 3-Year Summary File: Technical Documentation.
	ACS 2007-3yr Summary File: Technical Documentation -> Appendix B. Subject Definitions -> Population Variables -> Age

Age

The data on age were derived from answers to Question 2. The age classification is based on the age of the person in complete years at the time of interview. Both age and date of birth are used in combination to calculate the most accurate age at the time of the interview. Inconsistently reported and missing values are assigned or imputed based on the values of other variables for that person, from other people in the household, or from people in other households ("hot deck" imputation). Data on age are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. Age data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. Therefore, age data are tabulated by many different age groupings, such as 5-year age groups.

Median Age

The median age is the age that divides the population into two equal-size groups. Half of the population is older than the median age and half is younger. Median age is based on a standard distribution of the population by single years of age and is shown to the nearest tenth of a year. (See the sections on "Standard Distributions" and "Medians" under "Derived Measures.")

Age Dependency Ratio

The age dependency ratio is derived by dividing the combined under-18 and 65-and-over populations by the 18-to-64 population and multiplying by 100.

Old-Age Dependency Ratio

The old-age dependency ratio is derived by dividing the population 65 years and over by the 18-to-64 population and multiplying by 100.

Child Dependency Ratio

The child dependency ratio is derived by dividing the population under 18 years by the 18-to-64 population, and multiplying by 100.

Limitation of the Data

Caution should be taken when comparing population in age groups across time. The entire population continually ages into older age groups over time and babies fill in the youngest age group. Therefore, the population of a certain age is made up of a completely different group of people in 2000 and 2007. Since populations occasionally experience booms/increases and busts/decreases in births, deaths, or migration (for example, the postwar Baby Boom from 1946-1964), one should not necessarily expect that the population in an age group in Census 2000 should be similar in size or proportion to the population in the same age group in the 2007 ACS. For example, Baby Boomers were age 36 to 54 in Census 2000 while they were age 44 to 62 in the 2007 ACS. Therefore, the age group 55 to 59 would show a considerable increase in population when comparing Census 2000 data with the 2007 ACS data.
Beginning in 2006, the population in group quarters (GQ) is included in the ACS. Some types of GQ populations have age distributions that are very different from the household population. The inclusion of the GQ population could therefore have a noticeable impact on the age distribution. This is particularly true for areas with a substantial GQ population.

Question/Concept History

The 1996-2002 American Community Survey question asked for month, day, and year of birth before age. Since 2003, the American Community Survey question asked for age, followed by month, day, and year of birth. In 2007, an additional instruction was provided with the age and date of birth question on the American Community Survey questionnaire to report babies as age 0 when the child was less than 1 year old. The addition of this instruction occurred after 2005 National Census Test results indicated increased accuracy of age reporting for babies less than one year old.

Excerpt from:	Social Explorer; U.S. Census Bureau; 2005-2007 American Community Survey 3-Year Summary File: Technical Documentation.
	ACS 2007-3yr Summary File: Technical Documentation -> Appendix B. Subject Definitions -> Derived Measures -> Percentage

Percentage

This measure is calculated by taking the number of questions in a group possessing a characteristic of interest and dividing by the total number of questions in that group, and then multiplying by 100.