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South Dakota
Statistics on children, youth and families in South Dakota from the Annie E. Casey Foundation and South Dakota KIDS COUNT
Children in poverty (1-year estimates)
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Why This Indicator Matters
Growing up poor has wide-ranging and long-lasting repercussions.
Poverty elevates a child's risk of experiencing behavioral, social and emotional and health challenges. Child poverty also reduces skill-building opportunities and academic outcomes, undercutting a young student's capacity to learn, graduate high school and more.
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Poverty elevates a child's risk of experiencing behavioral, social and emotional and health challenges. Child poverty also reduces skill-building opportunities and academic outcomes, undercutting a young student's capacity to learn, graduate high school and more.
Definition and Source
PROVIDER
Definition
The number and percent of children age birth to 4 (statewide only), 5 to 17, and total birth to 17 who are living in families with incomes below 100% of the federal poverty threshold.
Data Source
U.S. Census Bureau, Small Area Income and Poverty Estimates (SAIPE), https://www.census.gov/programs-surveys/saipe.html
Notes
The federal poverty thresholds are updated each year by the U.S. Census Bureau and were established in 1964 using guidelines set by the Social Security Administration. Current poverty thresholds can be found here.
SAIPE uses statistical models to create estimates. The models relate state and county estimates of income and poverty from the American Community Survey (ACS) to other indicators of income and poverty, including federal income tax returns, SNAP benefits data, the most recent decennial census, intercensal population estimates, Supplemental Security Income data, and economic data from the Bureau of Economic Analysis. These estimates are then combined with direct estimates from the ACS sample to provide figures which are more precise than either data set alone, thus providing consistent and reliable single-year estimates. These model-based single-year estimates are more reflective of current conditions than multi-year survey estimates.
LIMITATIONS - Measures of uncertainty for the poverty estimates are provided in SAIPE in the form of 90% confidence intervals. These intervals were constructed from estimated standard errors. For the model-based estimates, the standard error depends mainly on the uncertainty about the model and the ACS sampling variance. Estimates are considered unreliable if the relative standard error is greater than 30%, and unreliable estimates are reported as NA. The 90% confidence intervals for each estimate are available here Children in poverty (1-year estimates).
SAIPE uses statistical models to create estimates. The models relate state and county estimates of income and poverty from the American Community Survey (ACS) to other indicators of income and poverty, including federal income tax returns, SNAP benefits data, the most recent decennial census, intercensal population estimates, Supplemental Security Income data, and economic data from the Bureau of Economic Analysis. These estimates are then combined with direct estimates from the ACS sample to provide figures which are more precise than either data set alone, thus providing consistent and reliable single-year estimates. These model-based single-year estimates are more reflective of current conditions than multi-year survey estimates.
LIMITATIONS - Measures of uncertainty for the poverty estimates are provided in SAIPE in the form of 90% confidence intervals. These intervals were constructed from estimated standard errors. For the model-based estimates, the standard error depends mainly on the uncertainty about the model and the ACS sampling variance. Estimates are considered unreliable if the relative standard error is greater than 30%, and unreliable estimates are reported as NA. The 90% confidence intervals for each estimate are available here Children in poverty (1-year estimates).
Last Updated
December 2023