1. 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
Smart Start
May 3, 2017

2. Today’s Agenda 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?

3. Who Are the Young Children in the United States?

4. Many Young Children Are Poor or Low-Income…
Source: CLASP calculations of American Community Survey data, Table B17001,
CLASP calculations of American Community Survey data, Table B17024, Extreme Poverty is defined as living below 50 percent of the federal poverty level.
CLASP calculations of American Community Survey data, Table B17024, Low-income is defined as living below 200 percent of the federal poverty level.

5. …And the Youngest Children Are Most Likely to be Poor
Children Living in Low-income and Poor Families in the U.S. by Age Group, 2015
The official poverty measure is outdated
In 2010, poverty level is $18,310 for a family of 3 and $22,050 for a family of 4.
21% of America’s children—15.3million—live in poor families (2009).
Research shows that on average it takes an income of twice the poverty level to meet basic family needs
42% of America’s children—31.3 million—live in low-income families (below 200% of poverty) – 2009.
But depending on locality, it takes an income to 1.5 to 3.5 times the poverty level to meet basic needs.
Yang Jiang, Maribel R. Granja and Heather Koball, Basic Facts about Low-Income Children, National Center for Children in Poverty, 2015

6. Consequences of Poverty on Young Children
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.
Children with multiple risks are especially vulnerable.
Low-income children, especially young children, who are exposed to parental depression, substance abuse and/or domestic violence are at particularly high risk.
These risk factors have been linked to mental health disorders, acting out behavior, and learning problems.
Long term consequences may include dropping out of school and involvement with child welfare and juvenile justice.
A growing body of research documents the connection between adverse childhood experiences and poor health and development outcomes. The studies examine a variety of risks, document their association with poor outcomes, AND show that exposure to multiple risks has a compounding effect of increasing the odds of poor outcomes.
Stevens, Gregory D. "Gradients in the health status and developmental risks of young child ren: the combined influences of multiple social risk factors. " Maternal and Child Health Journal 10.2 (March 2006): 187(13).
Does not quantify costs or benefits, but produces odds ratios for poor health or developmental risk associated with any combination of four specific risks: race/ethnicity, social class (maternal education and family poverty status), child health insurance coverage, and maternal mental health. For example, a child with one risk factor has 1.7 higher odds of experiencing poor health or developmental delays than a child with no risk factors. The odds ratio for two risk factors is 3.28, for three risk factors 4.69, and for four risk factors Higher risk factors are also associated with poorer access to health care. These odds ratios may be helpful in quantifying potential costs or benefits.
Richards, M., and M.E.J. Wadsworth. "Long term effects of early adversity on cognitive function.” Archives of Disease in Childhood (October 2004):
Vincent J. Felitti, Robert F. Anda, Dale Nordenberg, David F. Williamson, Alison M. Spitz, Valerie Edwards, Mary P. Koss and James S. Marks “Relationship of Childhood Abuse and Household Dysfunction to Many of the Leading Causes of Death in Adults: The Adverse Childhood Experiences (ACE) Study” American Journal of Preventive Medicine, 14(4)/,

7. Young Children Face Multiple Risk Factors for Unhealthy Development
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.
Children with multiple risks are especially vulnerable.
Low-income children, especially young children, who are exposed to parental depression, substance abuse and/or domestic violence are at particularly high risk.
These risk factors have been linked to mental health disorders, acting out behavior, and learning problems.
Long term consequences may include dropping out of school and involvement with child welfare and juvenile justice.
A growing body of research documents the connection between adverse childhood experiences and poor health and development outcomes. The studies examine a variety of risks, document their association with poor outcomes, AND show that exposure to multiple risks has a compounding effect of increasing the odds of poor outcomes.
Stevens, Gregory D. "Gradients in the health status and developmental risks of young child ren: the combined influences of multiple social risk factors. " Maternal and Child Health Journal 10.2 (March 2006): 187(13).
Does not quantify costs or benefits, but produces odds ratios for poor health or developmental risk associated with any combination of four specific risks: race/ethnicity, social class (maternal education and family poverty status), child health insurance coverage, and maternal mental health. For example, a child with one risk factor has 1.7 higher odds of experiencing poor health or developmental delays than a child with no risk factors. The odds ratio for two risk factors is 3.28, for three risk factors 4.69, and for four risk factors Higher risk factors are also associated with poorer access to health care. These odds ratios may be helpful in quantifying potential costs or benefits.
Richards, M., and M.E.J. Wadsworth. "Long term effects of early adversity on cognitive function.” Archives of Disease in Childhood (October 2004):
Vincent J. Felitti, Robert F. Anda, Dale Nordenberg, David F. Williamson, Alison M. Spitz, Valerie Edwards, Mary P. Koss and James S. Marks “Relationship of Childhood Abuse and Household Dysfunction to Many of the Leading Causes of Death in Adults: The Adverse Childhood Experiences (ACE) Study” American Journal of Preventive Medicine, 14(4)/,
Young Child Risk Calculator, National Center for Children in Poverty
2014 American Community Survey

8. Young Children in the U.S. Are Increasingly Diverse
This graph needs replaced.
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),

9. Diversity Among Poor Young Children
The official poverty measure is outdated
In 2010, poverty level is $18,310 for a family of 3 and $22,050 for a family of 4.
21% of America’s children—15.3million—live in poor families (2009).
Research shows that on average it takes an income of twice the poverty level to meet basic family needs
42% of America’s children—31.3 million—live in low-income families (below 200% of poverty) – 2009.
But depending on locality, it takes an income to 1.5 to 3.5 times the poverty level to meet basic needs.
Source: CLASP calculations of American Community Survey data, Tables B17001A-I,

10. …And Children of Color Are an Emerging Majority
Source: Donald Hernandez, Center for Social & Demographic Analysis, from Population Projections Program, Population Division, U.S. Census Bureau, Issued January 13, 2000.

11. Children of Immigrants
Children of immigrants are a growing share of the U.S. population
One in four children between ages 0 to 5 had at least one immigrant parent, and the majority are U.S. citizens
Children of immigrants are increasingly diverse
Country of origin
LEP status
Immigration status
Challenges:
More likely to be poor
Low parental educational attainment
Limited English Proficiency
Less likely to access services/benefits, including high-quality ECE
Strengths
More likely to live in two-parent households
Potential for bilingualism
Strong community networks
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.

12. Percent Increase in Population of Children of Immigrants, Under Age 6, 2000-2012
North Carolina: 51% increase
More than 60% Change
40-60% Change
20-39% Change
0-19% Change
Source: Source: Migration Policy Institute tabulation of data from the U.S. Census Bureau's 2012 American Community Survey,
Negative Change

13. How a Parent’s Unauthorized Status Impacts Child Development
Damage to child’s health, education, development
Child/ parent stress
Less family income
Less access to education & services

14. Where Are the Children in Child Care and Early Education?

15. Many Young Children Are in Care…
Percent
Source: National Center for Education Statistics, 2012 National Household Education Survey.

16. …For Significant Portions of Time…
Average Time Preschoolers Spent in Selected Child Care Arrangements by Employment Status of Mother
Young children with employed mothers spend many hours in non-parental care each week
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

17. …And in Diverse Settings
Primary Child Care Arrangements for Children 0-5
With Employed Mothers
Source: Urban Institute, 2002 National Survey of America’s Families.

18. Child Care is Expensive, Particularly for Poor Families
$1,525 (monthly)
Source: U.S. Census Bureau, Who’s Minding the Kids? Child Care Arrangements:
Spring

19. Access to Early Childhood Programs by Race & Ethnicity

20. The Context
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.
Highlight CLASP’s previous racial equity/immigrant work.

21. To download the full report visit:
Disparate Access
In this first part of today’s webinar, we will be discussing the findings from CLASP’s Disparate Access brief regarding children’s access to Head Start Preschool, Early Head Start, and the Child Care and Development Block Grant – or CCDBG – as well as have a discussion on how to understand the data. You can access the full report, as well as view the state-by-state findings and our methodology at the link on the screen. Next slide.
To download the full report visit:

22. Programs Head Start and Early Head Start
Child Care and Development Block Grant (CCDBG)
Preschool

23. Federal Programs Serve Only a Fraction of Eligible Children
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.

24. Head Start Preschool and Early Head Start Findings
Now that we are grounded in some of the data on young children more generally, we will turn to the methodology and findings from this report.
This brief offers state-by-state estimates of racial and ethnic differences in the share of eligible children who participate in Head Start preschool, Early Head Start, and CCDBG. I’ll first be focusing on the Head Start findings.
Please note that we calculated participation rates by comparing the number of children in Head Start or CCDBG to the number of eligible children based on administrative data and data from the American Community Survey. The findings are based on three years of data from I also want to mention that this brief looks only at Black, Hispanic or Latino, Asian, and AIAN populations due to limitations in the data. Because the Head Start and CCDBG administrative data report race and ethnicity separately, it was not possible to identify which children were White, non-Hispanic or Latino. Therefore, White children are not included in this analysis. Further, because of sample size issues, some race categories had too few children to analyze in particular states. Next slide.

25. Context and Methodology
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.
In order to best understand the data we are about to present, it is important to understand the context in which Head Start programs are administered as well as the eligibility parameters for the programs. As many of you know, Head Start programs are administered through a federal to local grantee funding streams, except for in the instances that a few states are themselves Early Head Start grantees. Therefore, assessing the data on participation in Head Start in each state is not an indicator of state policy choices, but more provides a state-by-state look at federal investments. In this report, we looked specifically at access to Early Head Start and the Head Start preschool programs. Early Head Start serves children birth through age 2 and Head Start preschool serves children ages 3 and 4. Early Head Start also serves pregnant women, but this report is limited to the data on children. Head Start eligibility is based on poverty status – therefore, eligibility in this analysis was limited to young children living in households below the federal poverty line. Because we modeled eligibility based solely on the poverty level, these findings should be considered estimates and not exact. Programs are also allowed to enroll children above the poverty level and for categorical eligibility reasons. Our analysis does not include data on children served in the Migrant and Seasonal Programs or the American Indian/Alaskan Native programs, due to the complex eligibility criteria for these programs. Next slide.

26. Head Start Serves a Diverse Population
Furthermore, it is important to know that the overall make up of Head Start programs is diverse. 38% of all Head Start children are Hispanic, regardless of race. 29% are African-American or black. Almost 1 in ten children identify as biracial or multiracial, and 12% identify as an unspecified or other race. While 43% of children were White, again, it is important to remember that it is not possible to identify White, non-Hispanic or Latino children from the White, Hispanic or Latino children, due to the way the data was collected. Next slide.
Source: CLASP analysis of Head Start Program Information Report (PIR) Data. U.S. totals include territories.

27. Fewer than Half of Eligible Children were Served in Head Start Preschool
And now to the findings from the report. Fewer than half of all eligible children—those with incomes under federal poverty level—were served in Head Start preschool nationally. About 54 percent of eligible Black preschoolers were served in Head Start preschool, as were 38 percent of eligible Hispanic or Latino children and 36 percent of eligible Asian children. Please note that additional children birth to age 5 are also receiving Migrant and Seasonal Head Start services, the vast majority of which are Hispanic or Latino. Therefore, a greater share of poor Latino children have access to Head Start services than is shown here, which would narrow the gap in access between Black and Latino children. Next slide.
Source: CLASP Analysis of Head Start PIR data and ACS data.

28. Head Start Preschool State Findings
Percent Eligible Children Served in Head Start Preschool by Race/Ethnicity
Black Preschoolers
Hispanic/Latino Preschoolers
Asian Preschoolers
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%)
At the state level, the differences in access to the Head Start preschool program are striking. To see the state-by-state percentages for all children and each race and ethnicity, please consult Appendix II of the Disparate Access brief. Next slide.

29. Access to Early Head Start is Universally Low
Percent of Poor Children Ages 0-3 Served in Early Head Start, by Race/Ethnicity
Turning now to Early Head Start findings, according to our analysis, just 5 percent of eligible children were served in the Early Head Start program nationally. The percentages of eligible children served were low across the board for all races and ethnicities: 6 percent of Black infants and toddlers; 5 percent of Hispanic/Latino infants and toddlers, and 4 percent of Asian infants and toddlers. As with Head Start preschool, there are differences across states in the share of children served by race and ethnicity in Early Head Start. However, the main takeaway for Early Head Start is that access regardless of race and ethnicity is universally low. Six states served only 4 percent—the lowest percentage across all states—of the eligible Black infants and toddlers: Arizona, Indiana, Michigan, New Jersey, Tennessee, and Texas. Georgia and Louisiana served the smallest percentage of eligible Hispanic/Latino infants and toddlers at just 1 percent. Georgia served fewer than 1 percent of the eligible Asian infant and toddler population, while New Jersey served only 1 percent. To see the state-by-state percentages for all children and each race and ethnicity, please consult Appendix III of the Disparate Access brief. Next slide.
Source: CLASP analysis of Head Start PIR data and ACS data.

30. Child Care and Development Block Grant Findings
Now, let’s take a look at the access findings from CCDBG.

31. Context and Methodology
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.
As was mentioned earlier, in order to best understand the data we are about to present, it is important to understand the context in which CCDBG programs are administered as well as the eligibility parameters for the program. CCDBG is the largest source of federal funding for child care in the country. Unlike Head Start, CCDBG’s funding structure is Federal to State meaning that the dollars allocated for the program travel from the federal government to the state. The state then administers the program by designing the policies that the programs must follow with the federal parameters of the law. States have significant discretion in creating these policies and they vary significantly by state. One of those policies is eligibility. States can set the income eligibility limit at whatever they wish so long as it is below the federal parameter of 85 percent SMI. Many states set their eligibility far below that and there is a significant range. For purposes of this paper, 175 percent of the federal poverty level was used to determine who was eligible. This was chosen as it is the median income eligibility limit across all states. As such, the percentages of access you will see in the slides following this actually understate the need for child care assistance among all children that could be eligible according to the federal parameters.
Another policy that states have discretion over is the work and education requirements that parents must be doing in order to receive the subsidy for their children. For purposes of this paper and because of data limitations, only work requirements were considered. In order to be considered eligible for purposes of this analysis, both parents in a two parent family must be working or the only parent in a single parent family must be working.
Our analysis only looked at CCDBG-funded child care. This means that children receiving child care that is funded directly through TANF are not included in this analysis. In 2014, 1.4 million children were served through the CCDBG funds alone.
Next slide.

32. CCDBG serves a diverse population
So let’s take a quick look at the racial and ethnic make up of those 1.4 million children being served in CCDBG. 21% of all children served in CCDBG are Hispanic, regardless of race. 42% are African-American or black. While 41% of children were White, it was not possible to identify White, non-Hispanic or Latino children from the White, Hispanic or Latino children, due to the way the data was collected. Next slide.
Source: CLASP analysis of 2014 Office of Child Care administrative data.

33. Low-income Children 0-13 with Working Parents Served Through CCDBG by Race/Ethnicity
According to CLASP’s analysis, 13 percent of eligible children were served in CCDBG nationally, based on income eligibility at 175 percent of poverty. Access for most racial and ethnic groups is low, ranging from 6 to 21 percent of eligible children being served. Nationally, CCDBG served about 21 percent of eligible Black children, 11 percent of eligible Asian children, 8 percent of eligible Hispanic/Latino children, and 6 percent of eligible AIAN children. You will see that for all groups besides Black, the share of children served is below the national average. Additionally, the share of Hispanic/Latino and AIAN children served are nearly half that of all children and one third of the percent of black children served. Next Slide.
Source: CLASP analysis of CCDBG administrative data and ACS data

34. Access to CCDBG varies significantly by state
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%)
For CCDBG, there are considerable differences by state in the share of eligible children served by race and ethnicity. For Black children, the share served in CCDBG ranges from 3 percent in Maine to 42 percent in Pennsylvania. For Hispanic/Latino children, the share ranges from 1 percent in Mississippi to 12 percent in New Jersey. For AIAN children, less than 1 percent of eligible children are served in Hawaii compared to 43 percent in Arizona. And, for Asian children, the share ranges from less than 1 percent in Arizona, Montana, North Dakota, and South Dakota to 73 percent in New York. As a reminder, to see all states access by race, visit the appendices of the full paper.
Next slide.

35. Latino Children’s Access to CCDBG
Share of Eligible Latino Children Served by CCDBG by State
While 13 percent of all eligible children (ages 0-13, regardless of race/ethnicity) and 21 percent of eligible Black children receive child care assistance through CCDBG, only 8 percent of eligible Latino children get help. Access is even lower in many states including Alabama, Arkansas, Georgia, Mississippi, Oregon, South Carolina, and Tennessee Schmit and Walker, Disparate Access. Note: To qualify for assistance, a child’s parents must be working or in education or training programs or a child may be in protective services. Federal income eligibility is capped at 85 percent of State Median Income (SMI), but states may set income eligibility anywhere below that ceiling—and most do. In 2014, the median income eligibility for CCDBG children set by states and the District of Columbia was 175 percent FPL.
Latino children are served at rates below the national average in every state in the country, with the share ranging from 1 percent in Mississippi to 12 percent in New Jersey. In 18 states, fewer than 6 percent of eligible Latino children are served

36. To Read the full report visit:
Latino Access to CCDBG
To learn more about Latino access to CCDBG, you can read out new brief, A Closer Look at Latino Access to Child Care Subsidies, which was just released yesterday and can be accessed at the web link on the screen. This new brief is a companion piece to our original report discussed today. This brief elaborates on the low level of access Latino children have to child care assistance through CCDBG.
To Read the full report visit:

37. Access to Preschool 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-olds, 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: and
35 percent of 4-year-olds and only 4 percent of 3-year-olds attended the state preschool program in 2013.
Black children made up about 43 percent of attendees, in comparison to 27 percent White children, 20 percent Latino children, and 4 percent Asian children.
Almost 53 percent of all Latino 4-year-olds in the state were enrolled in the public preschool program, while 49 percent of all Black 4-year-olds, 25 percent of all Asian 4-year-olds, and 22 percent of all White 4-year-olds were enrolled in the state’s preschool program.
Black children and White children attend state-funded preschool at similar rates: 45 and 47 percent respectively.
Michigan’s Great Start Readiness Program (GSRP), the state-funded preschool program for at-risk 4-year-olds, serves more White children overall than Black children.
About 35 percent of all Black 4-year-olds in the state are enrolled in GSRP, while only 21 percent of all White 4-year-olds are enrolled in GSRP.
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.
Being Black Is Not a Risk Factor: Statistic and Strengths-Based Solutions in the State of Michigan, National Black Child Development Institute, 2014, pages 14-17, retrieved from

38. Access to Early Education
Source: CLASP Analysis of U.S. Census American Community Survey 3-year estimates ( ). Analysis is preliminary.

39. Access for Children of Immigrants
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.
Sources:
Hannah Matthews and Deeana Jang, The challenges of change: Learning from the child care and early education experiences of immigrant families, 2007.
CLASP analysis of Head Start PIR data for all programs, 2013.
CLASP analysis of the Department of Education Office of Civil Right Dataset,  
Child Care and Early Childhood Education: More Information Sharing and Program Review by HHS Could Enhance Access for Families with Limited English Proficiency, GAO , U.S. Government Accountability Office, 2006.

40. How Can Data Be Used to Advocate?

41. How does CLASP use data?
To advocate
To help others advocate
To support our analyses
To make the case

42. Tell Your Story 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?

43. CLASP DataFinder 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

44. CLASP In the States www.clasp.org/in_the_states/ Find fact sheets on:
Head Start
Child Care assistance
TANF spending
Infant/toddler initiatives

45. Recommendations
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.
Improved data collection for both access and the quality of programs would inform our understanding of how diverse groups of children experience differential access to child care and early education programs.

46. Resources 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

47. Contact Us
Stephanie Schmit, Senior Policy Analyst, (202)
Christine Johnson-Staub, Senior Policy Analyst, (202)
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