Effects of Income Imputation on Traditional Poverty Estimates 1987-2007

transcript

Effects of Income Imputation on Traditional

Poverty Estimates1987-2007

The views expressed here are the authors and do not represent the official positions of their organizations.

Authors

• Joan Turek, Brian Sinclair James and Bula Ghose, Department of Health and Human Services

• Charles Nelson and Edward Welniak, Bureau of the Census

• Fritz Scheuren, NORC

Outline of Talk

• Handling nonresponse on the CPS• Effects of imputation on income

and poverty estimates• Official poverty vs. first quintile

measure -- demographic characteristics

• Summary of findings • Implications for new measure?

Upward Trend in Nonresponse

0.00%5.00%

10.00%15.00%20.00%25.00%30.00%35.00%40.00%

Trend in the Percent of Total Dollar Income Imputed, All People With Positive Income

Handling CPS Nonresponse

• Uses “Hot Deck” procedures• Imputation occurs at the person

level by income source• Assigns amounts from reporters

with similar characteristics• Imputation method consistent

over time

Types of Imputation

Two types of non-response in ASEC: item and whole imputes

• Item impute: sample person or other household member fails to respond to a specific question

• Item imputes are based on responses to both the basic monthly survey and on the ASEC supplement 6

Types of Imputes (Con.)

• Whole impute: Sample persons only responded to the basic labor force questions in the monthly survey -- entire supplement is imputed using the monthly survey

• More limited data on monthly survey—have labor force experience for last month and not last year 7

Income Per PersonComparisons

What Comparisons Tell Us

• Imputation has greatest effect at lower per person income levels

• Predictable consequences for poverty rates

• Shown for 2007, but generally true over time

Poverty Trends: 1987-2007

Trends in Poverty Rates for People with Positive Income -- Item, Whole or No Imputes

10.00%

12.00%

No Imputes

Poverty Trends Summary

• No imputes -- highest poverty rates• Item imputes -- lowest poverty

rates• Growth in imputation rates has not

really changed the poverty distribution

Income Type and Poverty Status

Next look at the percent of the total population with positive income:

• below the official poverty line by type of imputation at five year intervals and for 5-year average

• Compares this 5 year average to those not in poverty and to all persons with positive income

Imputation Type and Poverty Status

Year None Item Whole Total Imputes

Impute types sum to 100%

100% Poverty

2007 63.0% 28.3% 9.7% 38.0%

2002 56.5% 31.9% 11.6% 43.5%

1997 66.3% 24.4% 9.3% 33.7%

1992 73.7% 14.4% 11.9% 26.3%

1987 77.4% 13.4% 9.2% 22.6%

5 year average 67.3% 22.3% 10.4% 32.7%

Not in Poverty

5 year average 58.2% 31.8% 10.0% 41.8%

All Persons

5 year average 59.1% 30.9% 10.0 40.9%

Percents are for number of persons with positive income

Income Type and Poverty Status (Con.)

Percentage of all persons with positive income who are item imputed falling below the poverty line grew, but trend seemed to reverse in recent years

• Whole imputes are relatively stable -- ranging between 9 and 12 percent.

• Overall trend has been toward more imputing –

• On average, less imputation for poverty population

• Not sure what recent reversal between 2002 and 2007 means for the long term.

Income Type and Poverty Status (Con.)

Role of Imputes on Poverty Rates in 2007

• No imputes only 9.8%• Item Imputes only 6.1%• Whole imputes only 8.4%• All of Above 8.3%• Whole plus no imputes 9.6%• Item plus no imputes 8.3%• All, item imputes set to 0 35.1%• Item imputes only set to 0 51.7%

What Imputation Does?

• In 2007, the poverty rate including no, item and whole imputes is 8.26%

• Without whole imputes the poverty rate is 8.25%

• When all item imputed amounts are set to zero, the poverty rate increases from 8.3% to 35.1%%

What Imputation Does?

• When looking only at persons with item imputes and setting these imputes equal to zero, the poverty rate increases from 6.1% to 51.7%

• Most persons with item imputes are workers

• O’Hara finds more persons have item imputed rather than reported or whole imputed earnings up to approx. $30,000

Official Poverty vs. Lowest Quintile

• Approximately 50% of the worst off 20% of the population are in official poverty estimate

• Only 2% of the population in the next quintile are in the official poverty estimate

• Family income is used in putting persons into a quintile – but counts are number of persons

Official Poverty vs Lowest Quintile (Con.)

• How are the demographics of the poor affected by the poverty measure selected

• Averages were constructed for selected demographic characteristics from annual estimates at five year intervals for: 2007, 2002, 1997, 1992 and 1987

Official Poverty vs. Lowest Quintile (cont.)

• Comparisons made by gender, race, family type, age, and education

• First chart shows poverty rates for males and females separately by official poverty measure and by lowest quintile

Gender

Demographic category

Official Poverty

Lowest Quintile Standardized Official Poverty

Standardized Lowest Quintile

Not Imputed

Male 8.2% 15.6% 64.3% 68.0%

Female 12.7% 22.9% 100.0% 100.0%

Item Imputed

Male 5.3% 11.4% 66.5% 64.2%

Female 8.0% 17.7% 100.0% 100.0%

Whole Imputed

Male 7.6% 14.9% 66.8% 67.6%

Female 11.4% 22.1% 100.0% 100.0%

Males 7.2% 14.2% 64.9% 67.0%

Females 11.1% 21.2% 100.0% 100.0%

Official Poverty

Not Imputed White 8.6% 17.2% 36.4% 49.5% Black 23.7% 34.7% 100.0% 100.0%

Item Imputed White 5.8% 13.7% 44.2% 60.9% Black 13.1% 22.5% 100.0% 100.0%

Whole Imputed White 8.3% 17.2% 50.1% 65.6% Black 16.6% 26.2% 100.0% 100.0%

All White 7.7% 16.1% 38.9% 53.2% Black 19.8% 30.2% 100.0% 100.0%

AgeDemographic

category Official Poverty

Lowest Quintile Standardized Official Poverty Ratio

Ratio Not Imputed

18-44 11.2% 17.5% 137.9% 119.9% 45-64 8.1% 14.6% 100.0% 100.0%

65 and over 12.3% 35.8% 152.0% 245.6% Item Imputed

18-44 7.3% 12.6% 149.0% 135.5% 45-64 4.9% 9.3% 100.0% 100.0%

65 and over 7.8% 28.5% 157.5% 305.6% Whole Imputed

18-44 10.5% 17.5% 147.0% 134.6% 45-64 7.2% 13.0% 100.0% 100.0%

65 and over 10.8% 32.2% 151.5% 247.9% All

18-44 10.1% 16.2% 146.4% 128.6% 45-64 6.9% 12.6% 100.0% 100.0%

65 and over 10.3% 32.8% 150.1% 260.8%

Single and Two Parent

Official Poverty

Not Imputed

Two Parent 7.3% 7.0% 19.7% 13.8%

Single Parent 36.9% 50.7% 100.0% 100.0%

Item Imputed

Two Parent 3.8% 3.6% 16.4% 9.7%

Single Parent 23.4% 37.4% 100.0% 100.0%

Whole Imputed

Two Parent 5.9% 6.0% 18.5% 13.1%

Single Parent 32.1% 46.0% 100.0% 100.0%

Two Parent 6.2% 5.9% 18.4% 12.5%

Single Parent 33.4% 47.2% 100.0% 100.0%

EducationDemographic

category Official Poverty

Not Imputed Less HS 27.1% 46.5% 269.5% 235.1% Some HS 20.2% 31.3% 200.1% 158.4%

HS Graduate 10.1% 19.8% 100.0% 100.0% Some College 7.0% 14.5% 69.4% 73.5% College Grad 2.8% 6.5% 28.0% 32.9

Item Imputed

Less HS 17.2% 36.7% 238.5% 215.3% Some HS 14.0% 26.1% 193.4% 153.4%

HS Graduate 7.2% 17.0% 100.0% 100.0% Some College 5.4% 12.4% 75.1% 72.8% College Grad 2.6% 5.9% 36.3% 34.7%

Education (cont.)

Official Poverty

Whole Imputed Less HS 19.8% 37.8% 206.8% 196.0% Some HS 16.6% 27.9% 173.6% 144.4%

All Less HS 24.2% 43.4% 263.7% 229.6% Some HS 18.2% 29.7% 199.3% 157.2%

Summary of Findings

Who are viewed as poor, is influenced by measure used:

• In one instance (Gender) no difference in impact of non-response

• In another instance (Race) large differences are found

Summary of Findings

• In still other cases, (age, family type, education) results are mixed:– More poor elderly in poverty when use

lowest quintile– fewer two parent families in poverty using

lowest quintile– more persons with education below high

school graduate in poverty using official poverty

The Supplemental Measures??

• Money income, with many additional adjustments, will also be used to construct supplemental poverty measures

• How does the addition of these new elements, such as near money income, expenditure and tax estimates affect the overall pattern of nonresponse

• Will poverty trends remain stable over a long period of time? 30

Next Steps• ASPE and Census are jointly

sponsoring a project that will match SSA, TANF and SSI records to the 2008 ASEC

• We will compare the incomes reported on these files to those on the ASEC by imputation type and other characteristics

• This will add an additional dimension to the retooling of CPS Poverty measures 31

Sources

• Amy O’Hara, Allocated Values in Linked Files, Housing and Household Economic Statistics Division, U.S. Census Bureau. amy.b.ohara@census.gov

• Joan Turek, Fritz Scheuren, Charles Nelson, Edward Welniak Jr., Brian Sinclair-James, and Bula Ghose,

- Effects of Imputation on CPS Income and Poverty Series: 1981-2007, Papers and Proceedings of the American Statistical Association, August 2009

- Effects of Imputation on CPS Poverty Series: 1987 – 2007, Papers and Proceedings of the Federal Committee on Statistical Methodology, November 2009.

Thank You!!

Contact

Dr. Joan Turek

Joan.Turek@HHS.GOV

Effects of Income Imputation on Traditional Poverty Estimates 1987-2007

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