Finding and Using Data to Advocate for Children and Families - - PowerPoint PPT Presentation

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Finding and Using Data to Advocate for Children and Families - - PowerPoint PPT Presentation

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Finding and Using Data to Advocate for Children and Families Stephanie Schmit, Senior Policy Analyst Child Care and Early Education Christine Johnson-Staub, Senior Policy Analyst Child Care and Early Education Smart Start May 3, 2017

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www.clasp.org

Finding and Using Data to Advocate for Children and Families

Smart Start May 3, 2017

Stephanie Schmit, Senior Policy Analyst Child Care and Early Education Christine Johnson-Staub, Senior Policy Analyst Child Care and Early Education

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www.clasp.org

  • Who are the Young Children in the United

States?

  • Poverty
  • Race/Ethnicity
  • Immigration Status
  • Where are the Children in Child Care and Early

Education?

  • Utilization and Access
  • Disparate Access
  • How Can the Data be Used to Advocate?

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Who Are the Young Children in the United States?

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www.clasp.org

Poor (under 100% of poverty) 22.8% Low-income (100-200% of poverty) 22.8%

Above 200%

  • f poverty

54.4%

Children Under Age 6 by Family Income, 2015

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Source: CLASP calculations of American Community Survey data, Table B17001, http://www.census.gov/acs/. CLASP calculations of American Community Survey data, Table B17024, http://www.census.gov/acs/. Extreme Poverty is defined as living below 50 percent of the federal poverty level. CLASP calculations of American Community Survey data, Table B17024, http://www.census.gov/acs/. Low-income is defined as living below 200 percent of the federal poverty level.

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www.clasp.org

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Children Living in Low-income and Poor Families in the U.S. by Age Group, 2015

Yang Jiang, Maribel R. Granja and Heather Koball, Basic Facts about Low-Income Children, National Center for Children in Poverty, 2015

Birth - 2 3-5 6-11 12-17 23% 22% 21% 18% 45% 45% 44% 39% Poor Low-Income

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Research shows:

  • Poverty is a strong predictor of…
  • Children’s success in school
  • Adult employment and earnings.
  • Children growing up in poverty experience…
  • Poorer health
  • Higher incidence of developmental delays and learning

disabilities

  • More hunger

Greg J. Duncan and Katherine MaGnuson, The Long Reach of Early Childhood Poverty, 2011; and Caroline Ratcliffe and Signe-Mary McKernan, Child Poverty and Its Lasting Consequence, Urban Institute, 2012.

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0 risks 40% 1-2 risks 43% 3+ risks 17% Exposure to Multiple Risk Factors Among Young Children, 2014

Young Child Risk Calculator, National Center for Children in Poverty 2014 American Community Survey

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These risk factors include: poor, single parent , teen mother, low parental education, non-employed parents, residential mobility, households with non-English speakers, and large family size.

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8 Source: CLASP calculations of American Community Survey data, U.S Census Bureau, Table PEPASR6H, Annual Estimates of the Resident Population by Sex, Age, Race, and Hispanic Origin for the United States and States: April 1, 2010 to July 1, 2013 (Release Date: June 2014), http://www.census.gov/acs/www/.

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9 Source: CLASP calculations of 2015 American Community Survey data, Tables B17001A-I, http://www.census.gov/acs/. 40% 36% 33% 30% 30% 23% 22% 19% 14% 12%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

Black or African American alone Some Other race alone American Indian and Alaska Native alone Hispanic or Latino alone Native Hawaiian and Other Pacific Islander Alone All Children Under Age 6 Two or more Races White alone White Alone not Hispanic

  • r Latino

Asian alone

Children Under Age 6 Living at or Below the Federal Poverty Level

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Source: Donald Hernandez, Center for Social & Demographic Analysis, from Population Projections Program, Population Division, U.S. Census Bureau, Issued January 13, 2000.

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  • Children of immigrants are a growing share of

the U.S. population

  • One in four children between ages 0 to 5 had at least
  • ne immigrant parent, and the majority are U.S.

citizens

  • Children of immigrants are increasingly diverse
  • Country of origin
  • LEP status
  • Immigration status

11 Sources: Migration Policy Institute, DataHub, 2013 data, accessed March 2015; Hannah Matthews and Deeana Jang, The challenges of change: Learning from the child care and early education experiences of immigrant families, 2007.

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Source: Source: Migration Policy Institute tabulation of data from the U.S. Census Bureau's 2012 American Community Survey, http://www.migrationinformation.org/datahub. More than 60% Change 40-60% Change 20-39% Change 0-19% Change Negative Change

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Damage to child’s health, education, development Child/ parent stress Less family income Less access to education & services

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Where Are the Children in Child Care and Early Education?

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Source: National Center for Education Statistics, 2012 National Household Education Survey. 50 100 Under 1 year 1-2 years 3-5 years 46 54 76

Percent of Children with a Weekly Non-parental Care Arrangement, 2012 by Age

15

Percent

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Source: Who’s Minding the Kids? Child Care Arrangements Spring 2011, U.S. Census Bureau, 2013 and U.S. Census Bureau, Survey of Income and Program Participation (SIPP), 2008 Panel Wave 8

36 33 32 23 24 25 25 21 25 18 15 12 16 11

Any Arrangement Day Care Center Family Day Care Grandparent Nonrelative in child's home Nursery/Preschool Other Nonrelative

Mother Employed Mother Not Employed

Average Time Preschoolers Spent in Selected Child Care Arrangements by Employment Status of Mother

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Primary Child Care Arrangements for Children 0-5 With Employed Mothers

Source: Urban Institute, 2002 National Survey of America’s Families.

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10 20 30 40 50

Below Poverty 100-199% of Poverty 200% of Poverty and Above

30 18 7 Percent of Household Income

Monthly Child Care Expenditures of Families with Employed Mothers as a Percent of Household Income

Source: U.S. Census Bureau, Who’s Minding the Kids? Child Care Arrangements: Spring 2011. 2012.

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Access to Early Childhood Programs by Race & Ethnicity

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  • High-quality child care and early education can build a

strong foundation for young children's healthy development; yet, current federal and state child care and early education investments are not sufficient to meet the great need among young children.

  • While these gaps in access to

child care and early education are widely recognized, less is understood about how access differs by race and ethnicity.

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To download the full report visit: http://www.clasp.org/issues/child-care-and-early-education/pages/disparate-access

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  • Head Start and

Early Head Start

  • Child Care and

Development Block Grant (CCDBG)

  • Preschool
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  • Head Start serves 43 percent of

eligible preschoolers and about 5 percent of eligible infants and toddlers in Early Head Start.

  • CCDBG serves 13 percent of

eligible children.

Source: CLASP anaylsis.

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Head Start Preschool and Early Head Start Findings

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  • Federal to local funding stream.
  • Early Head Start serves children birth through

age 2.

  • Head Start Preschool serves children ages 3

and 4.

  • Eligibility parameters were based on children

living at 100% FPL or below.

  • This analysis does not include the Migrant and

Seasonal or American Indian/Alaskan Native Program.

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Source: CLASP analysis of Head Start Program Information Report (PIR) Data. U.S. totals include territories. 38% 4% 2% 29% 1% 43% 9% 12%

Hispanic/Latino, regardless of race AIAN Asian Black Native Hawaiian/Pacific Islander White Bi- or Multi-racial Other/Unspecified

Percent of Children Served in All Head Start Programs, by Race/Ethnicity

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43% 54% 38% 36% All Children Black Hispanic/Latino Asian

Percent of Poor Children Ages 3 & 4 Served by Head Start Preschool, by Race/Ethnicity

Source: CLASP Analysis of 2011-2013 Head Start PIR data and 2011-2013 ACS data.

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Percent Eligible Children Served in Head Start Preschool by Race/Ethnicity Black Preschoolers Hispanic/Latino Preschoolers Asian Preschoolers Top 10 States Bottom 10 States Top 10 States Bottom 10 States All States Calculated Mississippi (108%) Arizona (28%) Minnesota (84%) South Carolina (13%) California (41%) District of Columbia (83%) Nevada (33%) Oregon (60%) Georgia (15%) New York (33%) Kansas (71%) Colorado (34%) Wisconsin (60%) Nevada (21%) Minnesota (27%) Michigan (68%) Texas (35%) Mississippi (59%) North Carolina (23%) Texas (11%) Illinois (67%) Virginia (39%) Illinois (58%) Tennessee (24%) Louisiana (67%) North Carolina (40%) Michigan (58%) Florida (26%) Minnesota (67%) Indiana (40%) Rhode Island (57%) Alabama (27%) Ohio (67%) Georgia (43%) Ohio (54%) Indiana (29%) Oklahoma (67%) Kentucky (44%) Connecticut (53%) Washington (29%) Pennsylvania (64%) Massachusetts (45%) Massachusetts (53%) Delaware (30%)

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5% 6% 5% 4% All Children Black Hispanic/Latino Asian

Source: CLASP analysis of 2011-2013 Head Start PIR data and 2011-2013 ACS data.

Percent of Poor Children Ages 0-3 Served in Early Head Start, by Race/Ethnicity

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Child Care and Development Block Grant Findings

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  • Federal to State with significant state flexibility
  • Eligibility
  • Income
  • Work/Education
  • Serves Children Age 0-13
  • In 2014, 1.4 million children were served

nationally.

  • This analysis includes only CCDBG funded child

care.

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www.clasp.org 21% 1% 1% 42% 2% 41% 3% 10% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Hispanic/Latino, regardless of race American indian/Alaska Native Asian African American Native Hawaiian/Pacific Islander White Multiracial Invalid/Not reported

Percent of Children Served in CCDBG, by Race/Ethnicity

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Source: CLASP analysis of 2014 Office of Child Care administrative data.

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www.clasp.org Source: CLASP analysis of 2011-2013 CCDBG administrative data and 2011-2013 ACS data

13% 21% 8% 6% 11% All Children Black Hispanic/Latino AIAN Asian

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CCDBG Eligible Children Served by Race/Ethnicity Top 5 States Black Hispanic/Latino AIAN Asian Pennsylvania (42%) New Jersey (12%) Arizona (43%) New York (73%) Delaware (39%) Iowa (10%) North Carolina (24%) California (29%) Missouri (38%) Hawaii (9%) Virginia (13%) Washington (24%) New York (37%) Connecticut (9%) Washington (10%) Minnesota (16%) Kansas (35%) Wisconsin (8%) Oregon (9%) Wisconsin (13%) CCDBG Eligible Children Served by Race/Ethnicity Bottom 5 States Black Hispanic/Latino AIAN Asian Maine (3%) Mississippi (1%) Hawaii (0%) Arizona (<1%) South Carolina (4%) Oregon (1%) Florida (1%) Montana (<1%) Rhode Island (6%) South Carolina (1%) Georgia (1%) North Dakota (<1%) District of Columbia (7%) Alabama (2%) Illinois (1%) South Dakota (<1%) South Dakota (9%) Arkansas (2%) Massachusetts (1%) Multiple States (NM, OK) (1%)

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Share of Eligible Latino Children Served by CCDBG by State

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36 To Read the full report visit: http://www.clasp.org/resources-and-publications/publication-1/CloserLookAtLatinoAccess.pdf

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Maryland:

  • 53 percent of all Latino 4-year-olds were enrolled in the public preschool

program, while 49 percent of Black 4-year-olds, 25 percent of Asian 4-year-

  • lds, and 22 percent of White 4-year-olds were enrolled.

Michigan:

  • 35 percent of all Black 4-year-olds in the state are enrolled in the state-

funded preschool program, while only 21 percent of White 4-year-olds are enrolled.

  • Black children in Michigan comprised 37 percent of the state’s Head Start

population in 2012, which is 8 percent higher than the number of Black children in the U.S. Head Start population for the same year.

Sources: http://www.education.umd.edu/TLPL/centers/MEP/Research/earlyeducation/MEP_Early_Educ_Data_Brief_2014_rv2.pd f; and http://www.nbcdi.org/sites/default/files/uploads/SOBC%20Michigan.FINAL__0.pdf. 37

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62% 62% 56% 66% 40% 44% 62% 65% 49%

0% 10% 20% 30% 40% 50% 60% 70% White Alone Black or African American Alone American Indian and Alaskan Native Alone Asian Alone Native Hawaiian and Other Pacific Islander Alone Some other Race Two or More Races White alone, not hispanic

  • r latino

Hispanic or Latino

Figure 10. Percentage of U.S. Children Ages 3 & 4 by Race/Ethnicity in Nursery School

Source: CLASP Analysis of U.S. Census American Community Survey 3-year estimates (2010-2012). Analysis is preliminary.

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Immigrant status not tracked in data - primary language is often used as a proxy for analysis.

  • Research shows that children of immigrants are less likely to

access all types of child care and early education programs.

  • In 2013, 29 percent of children in all Head Start programs

came from households where the primary spoken language was not English.

  • In 2013, LEP children made up 11 percent of the public

school preschool population.

  • A 2006 GAO report found that after controlling for other

factors, children with LEP parents are about half as likely to receive financial assistance for child care.

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How Can Data Be Used to Advocate?

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  • To advocate
  • To help others advocate
  • To support our analyses
  • To make the case
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  • What is the state of young children in your

community?

  • Where are the unmet needs and gaps in

services for particular age groups; racial/ethnic groups; programs and services?

  • What are the differences in access to early

childhood programs for different racial and ethnic groups in your community?

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www.clasp.org

  • www.clasp.org/data
  • Offers State Level and National Level Data
  • Poverty
  • Young Child Demographics
  • Race, ethnicity, immigrant family

status

  • Child Care spending/participation
  • Head Start/Early Head Start

participation

  • TANF spending

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www.clasp.org

  • www.clasp.org/in_the_states/
  • Find fact sheets on:
  • Head Start
  • Child Care assistance
  • TANF spending
  • Infant/toddler initiatives

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  • Improve data collection for both access and the

quality of programs.

  • Consider using new sources of data to make the

case for your advocacy goals

  • To advocate for sounder policy, use data

analysis that considers racial equity, immigration status, and other characteristics that may change the impacts of policy for particular and vulnerable populations.

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  • Disparate Access
  • A Closer Look at Latino Access to Child Care

Subsidies

  • DataFinder
  • CLASP in the States
  • 2014 Head Start and Early Head Start Profiles

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  • Stephanie Schmit, Senior Policy Analyst,

sschmit@clasp.org, (202) 906-8008

  • Christine Johnson-Staub, Senior Policy Analyst,

cjohnsonstaub@clasp.org, (202) 906-8005

  • Follow CLASP on Twitter @CLASP_DC
  • Receive our email updates by visiting

www.clasp.org and signing up in the bottom right corner!

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