2021 State of Pre-K: Poverty and Pre-K Access in Mississippi, 2017-2018

STATE OF PRE-K SERIES: BRIEF SEPTEMBER 2021

Poverty and Pre-K Access in Mississippi, 2017-2018 Research Brief by Rachel Canter, Micayla Tatum, and Andrew Van Horn

BACKGROUND Research consistently shows that children living in poverty receive the greatest benefit from pre-K.1 For this reason, each version of our pre-K report has analyzed whether children in poverty in Mississippi have access to public pre-K, which is generally low or no cost. “Public pre-K” includes programs with publicly funded seats, such as those in Head Start, blended Head Start, school districts, and collaborative programs (including private childcare seats within collaborative programs, which we refer to as “public childcare”).

HEAD START programs include all programs operated by grantees of the federal Office of Head Start. At least 90% of enrollees in Head Start centers must come from families whose incomes fall below 100% of federal poverty guidelines.

We do not include blended Head Start programs within Head Start figures.

1

BLENDED HEAD START programs blend Head Start and school district dollars, usually from the federal Title I program. These programs may be located either on campus at one or more elementary schools in a given district or at a local Head Start agency. We ensured that we did not double-count blended Head Start seats by separating them from other types of public school district seats.

SCHOOL DISTRICT PRE-K

programs are operated by public school districts regardless of funding source, including blended Head Start programs.

PUBLIC CHILDCARE PROGRAMS are licensed childcare centers that participate in the state-funded collaborative pre-K program.

COLLABORATIVE PROGRAMS participate in the statefunded early learning collaborative program.

These programs are comprised of all types of providers—Head Start, public school district (including blended Head Start), and licensed childcare. As a result, we count collaborative seats within the provider type to avoid duplication.

Brookings Institute. 2017. The Current State of Scientific Knowledge on Pre-Kindergarten Effects. Research report, Washington, D.C.: Brookings Institute. Accessed August 23, 2021. https://www.brookings.edu/wp-content/uploads/2017/04/duke_prekstudy_final_4-4-17_hires.pdf.

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EXECUTIVE SUMMARY AND LONG-TERM TRENDS In this brief, we find that a strong, positive association persists between poverty and public pre-K access on both the county and district levels. This association was similar despite different measures of poverty for each geographic unit: every one percentage point increase in the poverty rate was associated with a 1.38 percentage point increase in public access on the county level and a 1.21 percentage point increase in public access on the district level.

The association between poverty and access to publicly funded pre-K is one of the strongest long-term trends arising from this report series. Since funding to Head Start, the largest provider of publicly funded seats, is based on the poverty rates of an area, the association is expected; however, it has persisted over time despite a dramatic decrease in the number of Head Start seats since the first iteration of this report. Between the first two reports (2011-2012 to 2014-2015), Head Start lost approximately 5,000 seats. Between the 2014-2015 report and the current 2017-2018 report, Head Start lost 2,092 seats. Only ongoing population loss in the state prevented access rates from declining along with Head Start seats. However, such a profound, ongoing loss of seats threatens to reduce access over time. To combat this potential loss in access, we recommend an expansion of state-funded pre-K programs coupled with an expansion of blended Head Start, especially in high-poverty districts and counties across the state. This expansion will enable federal dollars to remain in the most underserved communities while ensuring that gold standard quality pre-K is accessible to children living in poverty.

Further discussions of these recommendations can be found in our community access report.

DATA & LIMITATIONS This analysis uses the same access data—and has the same limitations—as our research brief on community access to pre-K. Please see that brief for more information about how we estimate pre-K enrollment. In this brief, we add the dimension of child poverty to evaluate the relationship between public pre-K access and poverty. As a reminder, in this report, county access rates represent access that all four-year-old children had to public pre-K in the same year (i.e., 2017-2018 access for 2017-2018 four-year-olds) whereas district access rates represent access that entering public school kindergarteners had to public pre-K the prior year (i.e., 2017-2018 access for 2018-2019 kindergarteners).

ESTIMATING POVERTY IN SCHOOL DISTRICTS AND COUNTIES Estimating poverty in school districts has become more complicated in recent years. In the past, we have used free and reduced-price lunch rates from the National School Lunch Program (NSLP) to estimate district poverty. School districts participating in this program (which includes every traditional school district in Mississippi) previously collected income forms from every family in the district to determine each child’s eligibility for the program. Children with family incomes at or below 130% of poverty qualified for free lunch, while children with family incomes between 131-185% qualified for reduced-price lunch. Because these data were the most direct evidence of child poverty in school districts, education researchers, including Mississippi First, came to rely on these statistics, readily available by district, for estimating poverty.

In recent years, the National School Lunch Program, in order to reduce paperwork barriers to feeding children in need, has moved aggressively to increase the number of districts who can participate in the Community

Eligibility Program (CEP). CEP allows districts to serve free lunch to 100% of children in a district without collecting paper forms from all of them if at least 40% of the students in the district are identified as being either in poverty or “at risk” through other federal programs. This combined rate, called the Identified Student Percentage (ISP), uses family participation in the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF) program, or Food Distribution Program on Indian Reservations (FPDIR); child eligibility for Head Start; classification of students as homeless, migrant, or runaway; or child participation in foster care to measure the student eligibility rate for CEP. Each of these programs have different poverty eligibility guidelines (up to 185% of poverty) and may include children based on non-income factors.

As more and more districts have moved to CEP, rates of poverty based on the NSLP are no longer a reliable indicator of actual student poverty, as districts under CEP will report 100% of children on free lunch, even though as few as 40% may qualify for free lunch under the old guidelines.

STATE OF PRE-K SERIES: Poverty and Pre-K Access in Mississippi, 2017-2018

As a result, researchers have struggled to find comparable alternatives to NSLP’s formerly direct measure of poverty. Other options—using ISP or census-based school district poverty rates—have downsides. ISP, though it directly classifies individual students as being either in poverty or at risk, will exclude children whose parents could not navigate signing up for federal assistance programs or who do not qualify based on state guidelines that may be stricter than federal allowances. This is why the federal government recommends states multiply ISP by 1.6 to account for the universe of children who are likely to be eligible for free or reducedprice lunch under the old guidelines (Mississippi uses this practice). Since ISP is also based on federal programs of differing income eligibility as well as programs that admit participants based on non-income factors, it also does not exactly match the free lunch rate that we used as our measure of poverty in our previous reports.

Census poverty rates, which report the percentage of households at or below 100% of poverty in an area, most closely measure rates of the neediest families. These rates, however, are based on only a sample of people in years between official census counts (which frequently

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underreport people in poor or rural areas). These census-based estimates have high error rates for low population geographies, such as rural school districts, of which Mississippi has many. This makes census school district poverty rates too unreliable for our purposes.

Based on the above reasons, we decided to perform our two analyses in this brief—one by county and one by school district—with different measures of poverty. For our county analysis, we use poverty rates by county from the U.S. Census’s Small Area Income and Poverty Estimates (SAIPE) for 2017. SAIPE is an estimate of all households at or below 100% of the federal poverty line. These rates have their own error estimates as described in the Definitions and Sources appendix. For school districts, we use ISP. Since we understand the limitations of ISP, we recommend that readers view these poverty rates as relative—a school district with a higher ISP has a higher percentage of students in poverty, even if the exact percentages in the comparison may not be precise. County poverty rates will be more conservative than district rates since ISP includes households up to 185% of poverty. As a result, school district poverty rates will not add up to county poverty rates.

ESTIMATING TOTAL POPULATION County and district access rates also use different measures for the total eligible population of children. For counties, we use annual bridged racepopulation single-year estimates from the Centers for Disease Control and Prevention (based on census data) to find the number of four-year-old

As a result, the district access rates only represent the access public school children had to public pre-K, while the county access rates show the access that all four-year-olds had to public pre-K. children who could have enrolled in pre-K programs in 2017-2018. However, this measure is not available for school districts. Instead, we calculate district access rates by comparing the number of 2017-2018 public pre-K seats to the number of enrolled public school kindergarteners the following school year, 2018-2019. As a result, the district access rates only represent the access public school children had to public pre-K, while the county access rates show the access that all four-year-olds had to public pre-K.

ESTIMATING CHILDREN SERVED Again, we use the same data for children served (by county and by district) as we do in our report on community access. See that report for more information.

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CATEGORIZATION OF TERMS In this report, we use the terms “above average,”“average high,”“average,”“average low,” and “below average” to describe both access and poverty. We define these terms as follows:

“Above average” means greater than or equal to one standard deviation above the mean.

“Average” means within one standard deviation above and below of the mean. As one may expect, many

districts fall in the “average” categories. For a more nuanced view, we subdivide the “average” category into two: “Average high”

“Average low”

which means districts that are more than half of one standard deviation above the absolute average but not yet to the “above-average” mark.

which means districts that are more than half of one standard deviation below average but not yet to the “below-average” mark.

“Below average” means less than or equal to one standard deviation below the mean.

THE RELATIONSHIP BETWEEN COUNTY POVERTY AND PUBLIC PRE-K ACCESS FOR FOUR-YEAR-OLD CHILDREN In this section, we analyze the relationship between county poverty and county public pre-K access for four-year-old children in the 2017-2018 school year. In this analysis, measures of poverty across years are consistent, with the measure used being census-based poverty estimates. See Appendix A for rates of poverty and public access by county used in this section.

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WHAT RELATIONSHIP DOES POVERTY HAVE TO PUBLIC PRE-K ACCESS AT THE COUNTY LEVEL? For 2017-2018, we find a statistically significant, strong, and positive association between overall public pre-K access and poverty rates at the county level. Every one percentage point increase in county poverty was associated with an access increase of 1.38 percentage points. However, this relationship only explains about 41% of the variation across counties.

Percentage of Children with Publicly Funded Pre-K Percentage of Children with Publicly Funded Pre-K Access RateAccess

by Percentage

by Percentage of Children in Poverty

by County of Children in Poverty

by County y = 0.0138x + 0.068 R² = 0.4116

% of Children Living in Poverty

100.00%

75.00%

50.00%

25.00%

0.00% 0

10

20

30

40

50

60

70

% of Children with Access to Public Pre-K Seats

This association is not unexpected, as funding to Head Start is based on the poverty rates of an area and Head Start is the single largest provider of public seats. Title I funding, which is a primary funding source for district seats, is also based on poverty rates. Furthermore, the association between access and poverty mostly fits a normal curve. As evidenced by the graph below, most The Number of Counties Meeting Each Poverty and counties fall close to the center of Accessibility Classification both access and poverty distributions, 57 60 meaning they meet the criteria for “average” poverty and “average” 48 50 public access. There are no counties with the highest poverty and lowest 40 access nor are there counties with the 30 lowest poverty and highest access.

Increases in poverty are generally 17 20 16 13 associated with an increase in access.

11 10 0 Below Average

Average Poverty

Access

Above Average

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Counts of Counties by Level of Poverty and Level of Public Access ACCESS

POVERTY

Below Average Below Average Average Low Average High Above Average

6 8 3 0

Average Low 4 13 10 2

High 1 8 5 5

Above Average 0 10 0 7

This table summarizes the distribution of counties across our two variables of access and poverty.

Below, we list the counties contained within the categories above, as well as any major changes in the type of publicly funded seats located within those counties.

Counties with Below-Average Poverty, Below-Average Access There are six counties that fall at least one standard deviation below the average rates of poverty and access. Four of the six are in the southern half of the state, with the exceptions being DeSoto and Pontotoc. Though they feature the lowest rates of public access in the state, public pre-K access in two of the six counties—Lamar and Rankin—increased from 2015. Madison’s public access was stable. District seats increased in each of these three counties while Lamar and Rankin also experienced increases in Head Start. However, Madison saw a decline in both Head Start and blended seats as district seats grew. Conversely, DeSoto, Jackson, and Pontotoc County experienced decreases in their public access rates, dropping by 1.72, 6.62, and 21.87 percentage points, respectively, from 2015. In alphabetical order, the below-average poverty, below-average access counties are 1.

2.

DeSoto Jackson

3.

4.

Lamar Madison

5.

6.

Pontotoc Rankin

Counties with Below-Average Poverty, Average Access Of the five counties with below-average poverty and average access, four counties—Itawamba, Lafayette, Lee, and Tishomingo—had averagelow access rates (below the mean but above one standard deviation below the mean). One striking commonality is these average-low counties— every county in this category but Union—experienced declines in Head Start. In Lee County, Head Start decreases were offset by a growth in blended seats whereas lost Head Start and blended seats in Lafayette were replaced with a smaller number of district seats. Both Tishomingo and Itawamba experienced declines in Head Start with no increases in other types of seats. Overall, all but two counties—Lee and Union—saw decreases in their overall public access rate. Below-average poverty, average access rate counties in alphabetical order are the following: 1.

2.

Itawamba Lafayette

3.

4.

Lee Tishomingo

Counties with Below-Average Poverty, Above-Average Access No counties met these criteria.

5.

Union

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Counties with Average Poverty, Below-Average Access Like counties with below-average poverty and average access, all but three counties—Newton, Stone, and Webster—of the 11 with average poverty and below-average access saw decreases in Head Start seats. Lost Head Start seats were offset at least partially by increases in blended seats in two of these counties. District seats also rose in Hancock and Harrison to replace some of the lost Head Start seats. Nonetheless, most of these counties (with the exceptions of Hancock, Harrison, and Stone) saw a decrease in public access, with Greene, Marion, Perry, and Smith’s public access rates falling steeply—31.45, 36.86, 33.92, and 20.14 percentage points, respectively. These counties, in alphabetical order, are as follows: 5.

Marion 9.

Smith 1.

Greene 6.

Newton 10.

Stone 2.

Hancock 7.

Pearl River 11.

Webster 3.

Harrison 8.

Perry 4.

Leake Counties with Average Poverty, Average Access Average poverty, average access counties make up the largest group of our analysis. Of these 36 counties, only four (Jones, Kemper, Simpson, and Walthall) did not have a classroom-sized change in at least one of the publicly funded types of pre-kindergarten. Half of these counties saw declines in Head Start seats, which were not always offset by blended or district seat growth. Conversely, most of these counties (30 of 36) showed growth or stability in district seats. The following counties fall within one standard deviation of the state average of both measures: 1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

Alcorn Amite Bolivar Carroll Chickasaw Clay Copiah Forrest George Grenada Hinds Jasper Jones

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

Kemper Lauderdale Lawrence Lincoln Lowndes Marshall Monroe Montgomery Neshoba Oktibbeha Panola Pike Prentiss

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

Scott Simpson Tate Tippah Walthall Warren Wayne Winston Yalobusha Yazoo

Counties with Average Poverty, Above-Average Access Public access rates were stable or grew from 2015 in eight of the 10 counties with average poverty, above-average access. The two exceptions were Clarke County, which declined by 6.68 percentage points, and Wilkinson County, which declined by nearly 20 percentage points (19.80). Three counties—Attala, Jefferson Davis, and Covington—each saw public access grow by more than 20 percentage points. Every county except Benton and Franklin saw at least one type of publicly funded seat grow (these counties had no changes); however, growth in some types of public seats in Clarke and Wilkinson did not fully offset losses in other types of public seats in these counties, leading to the contraction of access. Average poverty, above-average access seats are as follows alphabetically: 1.

2.

3.

4.

Attala Benton Calhoun Choctaw

5.

6.

7.

Clarke Covington Franklin

8.

9.

10.

Jefferson Davis Tallahatchie Wilkinson

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Counties with Above-Average Poverty, Below-Average Access No counties met these criteria.

Counties with Above-Average Poverty, Average Access While none of the poorest counties are significantly below average for access, seven are at the average. These counties have the greatest need for affordable seats but are at best on par with the typical county in the state.

The first and most striking trend is that the counties with the highest poverty but average access are almost exclusively located in or near the Mississippi Delta or Mississippi’s poor southwest corner, with the exception of Noxubee. Five of the seven (Adams, Coahoma, Holmes, Tunica, and Washington) qualify as “average-high access.” Nonetheless, only three of these seven counties (Adams, Noxubee, and Tunica) did not experience an overall decline in access, with only two experiencing growth (Adams and Noxubee). The counties with the highest poverty and average access are the following: 1.

2.

3.

Adams Coahoma Holmes

4.

5.

6.

Leflore Noxubee Tunica

7.

Washington

Counties with Above-Average Poverty, Above-Average Access Counting Sharkey and Issaquena separately, seven counties qualified as having the highest poverty but also the highest public access. Sharkey and Issaquena together had the highest public access rate (95.24%). Interestingly, four of these six counties (Claiborne, Humphreys, Jefferson, and Quitman) saw declines in their public access rate, but because access was so high in 2015, these declines were not enough to knock them to a lower category of access. These counties, in alphabetical order, are as follows: 1.

2.

3.

Claiborne Humphreys Jefferson

4.

Quitman 5.&6. Sharkey-Issaquena 7.

Sunflower

HOW HAS THE RELATIONSHIP BETWEEN PUBLIC ACCESS AND POVERTY IN COUNTIES CHANGED OVER TIME? The strong, positive relationship between access and poverty endures from our last report. In 2017-2018, each one percentage point increase in poverty is associated with a 1.38 percentage point increase in the public access rate. We quantified a nearly identical relationship for the 2014-15 school year—a 1.39 percentage point increase. The difference between the two relationships is small and not statistically significant. In other words, the association between poverty and access at the county level is unchanged since our last report.

THE RELATIONSHIP BETWEEN DISTRICT POVERTY AND DISTRICT PRE-K ACCESS FOR ENTERING KINDERGARTENERS In this section, we analyze the relationship between district poverty and district publicly funded pre-K access in 2017-2018 for 2018-2019 entering kindergartners. In this analysis, measures of poverty across years are different, with the measure used in this report being ISP and the measure used in the 2014-2015 being free and reduced-price lunch rates. These measures are also different from county poverty measures. See Appendix B for the rates of poverty and public access by district used in this section.

WHAT IS THE RELATIONSHIP BETWEEN PUBLIC ACCESS AND POVERTY AT THE SCHOOL DISTRICT LEVEL? On the district level, we find a strong, positive association between poverty and public access, but this association is not quite as large as that of poverty and county access. For every one percentage point increase in the poverty rate, public access increased by 1.21 percentage points. About half of the variation—.497—is explained by the poverty rate, in this case ISP.2 This is similar to what we found in the county analysis, and again, the districts fall along a normal curve for poverty and access.

2018-2019 K Access to Public Pre-K (%)

Despite a different measure for poverty, 2018-2019 Kindergarten Access to Public Pre-K by District our categorization of districts by access Poverty and poverty largely tracks with our county 100.00% findings for a district’s county of residence, 90.00% especially for counties with only one school 80.00% district. Like the county analysis, our district 70.00% 60.00% analysis does not find any districts with 50.00% below-average poverty and above-average 40.00% public access or vice versa. Additionally, 30.00% 20.00% above-average poverty and average access y = 1.2069x - 0.0612 10.00% districts primarily cluster in the Delta and R² = 0.4958 0.00% southwest of the state like in the county 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% analysis, although there are more exceptions.

Identified Student Percentage by District Please note that because we did not have ISP information for the two newly established charter schools, we do not include them in this analysis. A summary table of findings is below, followed by lists of districts in each category. See Appendix B for the rates of poverty and public access by district used in this section.

The district-level poverty analysis uses each district’s Identified Student Percentage (ISP) instead of the census poverty rates we use for counties. ISP has a higher threshold for poverty, as explained in the Data and Limitations section, meaning that the percentage of families in poverty according to the ISP is consistently higher than those identified by the census using the traditional poverty line. Remember also that this analysis is not directly comparable to our previous analysis using lunch rates. See “How has the relationship between public access and poverty in districts changed over time?” for more discussion on trends over time.

2

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Public Access and Poverty at the School District Level ACCESS

POVERTY

Below Average Below Average Average Low Average High Above Average

12 14 0 0

Average Low 11 22 11 1

High 2 12 13 13

Above Average 0 1 14 13

Below-Average Poverty, Below-Average Access 1.

2.

3.

4.

5.

6.

Clinton Public School District Desoto County School District Jackson County School District Lamar County School District* Lee County School District Lincoln County School District

7.

8.

9.

10.

11.

12.

Long Beach School District Madison County School District Newton County School District Ocean Springs School District Pearl River County School District Rankin County School District

*Lamar County School District’s access rate includes Lumberton School District’s seats from the 2017-2018 school year because Lumberton consolidated into Lamar at the end of the 2017-2018 school year.

Below-Average Poverty, Average Access 1.

2.

3.

4.

5.

6.

7.

8.

Alcorn School District Booneville School District Enterprise School District Itawamba County School District Lafayette County School District Lowndes County School District Monroe School District New Albany Public Schools

Below-Average Poverty, Above-Average Access No districts meet these criteria.

9.

10.

11.

12.

13.

Oxford School District Petal School District South Tippah School District Tishomingo County Schools Union County School District

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Average Poverty, Below-Average Access 1.

2.

3.

4.

5.

6.

7.

Greene County School District Hancock County School District Houston School District Jones County School District Lauderdale County School District Nettleton School District North Pike School District

8.

9.

10.

11.

12.

13.

14.

Perry County Schools Pontotoc City School District Pontotoc County School District Poplarville School District Smith County School District Stone County School District Webster County School District

Average Poverty, Average Access 1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

Aberdeen School District Amory School District Baldwyn School District Bay-Waveland School District Biloxi Public School District Brookhaven School District Calhoun County School District Canton Public School District Carroll County School District Chickasaw County School District Cleveland School District Columbia School District Copiah County School District Corinth School District Forest Municipal School District Forrest County School District Franklin County School District George County School District Grenada School District Gulfport School District Harrison County School District Hinds County School District Holly Springs School District Kosciusko School District Lawrence County School District Leake County School District Louisville Municipal School District Marion County School District Marshall County School District Neshoba County School District

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

54.

55.

56.

57.

58.

North Tippah School District Okolona School District* Pascagoula Separate School District Pass Christian Public School District Pearl Public School District Picayune School District Prentiss County School District Quitman School District Quitman County School District Richton School District Scott County School District Senatobia Municipal School District Simpson County School District South Panola School District South Pike School District Starkville Oktibbeha Consolidated School District Tate County School District Tupelo Public School District Union Public School District Vicksburg Warren School District Walthall County School District Water Valley School District Wayne County School District West Jasper School District West Tallahatchie School District Western Line School District Winona-Montgomery Consolidated School District Yazoo County School District

*Oddly, Okolona’s kindergarten enrollment data was suppressed for 2018-2019. We used the number of fall 2018 test-takers on the kindergarten-entry exam, 35, to impute an enrollment. After considering other years (2014-2015 had 49 kindergarten students, 2015-2016 had 54, 2016-2017 had 44, 2017-2018 had 35, and 2019-20 had 42) as well as the spring 2019 test-taker number of 39, we felt 35 was a fair estimate.

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Average Poverty, Above-Average Access 1.

2.

3.

4.

5.

6.

7.

8.

Attala County School District Benton County School District Choctaw County School District Coffeeville School District Covington County School District East Jasper School District East Tallahatchie School District Hazlehurst School District

9.

10.

11.

12.

13.

14.

15.

Jefferson County School District Jefferson Davis County School District Kemper County School District Newton Municipal School District Philadelphia Public School District West Point Consolidated School District Wilkinson County School District

Above-Average Poverty, Below-Average Access No districts met these criteria, which is a significant change from 2015 when multiple school districts fell into this category. This change means that the most impoverished children had at least average access to pre-K in 2018, a positive development.

Above-Average Poverty, Average Access 1.

Clarksdale Municipal School District 2.

Coahoma County School District 3.

Columbus Municipal School District 4.

Hattiesburg Public School District 5.

Hollandale School District 6.

Jackson Public School District 7.

Laurel School District 8.

Leflore County School District 9.

McComb School District

10.

11.

12.

13.

14.

Meridian Public School District Moss Point School District North Bolivar Consolidated School District North Panola School District Noxubee County School District

Above-Average Poverty, Above-Average Access 1.

2.

3.

4.

5.

6.

Amite County School District Claiborne County School District Greenville Public School District Greenwood Public School District Holmes County Consolidated School District Humphreys County School District

7.

8.

9.

10.

11.

12.

Leland School District Natchez-Adams School District South Delta School District Sunflower County Consolidated School District West Bolivar School District Yazoo City School District

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2018-2019 Consolidated Districts Between 2017-2018 and 2018-2019, the state experienced five school district consolidations.

As a result, the access rates for these districts use as their numerator pre-K enrollment across public provider types from the former districts and use as their denominator the 2018-2019 kindergarten enrollment for the consolidated district. We also use a weighted ISP for the consolidated district that is based on the ISPs of each former district. The affected districts are 1. Holmes County Consolidated School District—This district is comprised of the former Holmes County and Durant school districts.

2. Lamar County School District—In July 2018, the Lumberton Public School District merged into the existing Lamar County School District.

3. Winona-Montgomery Consolidated School District—This district is comprised of the former Winona and Montgomery County school districts.

HOW HAS THE RELATIONSHIP BETWEEN PUBLIC ACCESS AND POVERTY IN DISTRICTS CHANGED OVER TIME? Though we use a different measure of poverty than in our 2014-2015 report, the association between public access and district poverty is essentially unchanged since 2014-2015. Every one percentage point increase in the poverty rate was associated with an increase of 1.2 percentage points in 20172018 compared to 1.1 percentage points in 2014-2015. The difference between the two numbers is small and not statistically significant. Furthermore, poverty explains a similar amount of the variation—approximately half (.495)—as in our previous report, which found that poverty explained slightly less than half (.48) of the variation. This finding indicates that factors in addition to poverty influence whether kindergarteners in a particular school district had access to publicly funded pre-K, though poverty plays a large role.

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Appendix A: Rates of Poverty and Public Pre-K Access by County County Adams Alcorn Amite Attala Benton Bolivar Calhoun Carroll Chickasaw Choctaw Claiborne Clarke Clay Coahoma Copiah Covington DeSoto Forrest Franklin George Greene Grenada Hancock Harrison Hinds Holmes Humphreys Itawamba Jackson Jasper Jefferson Jefferson Davis Jones Kemper Lafayette Lamar Lauderdale Lawrence

Percentage of Children Living in Poverty 44.4% 25.2% 31.6% 31.8% 33.9% 41.5% 30.4% 24.4% 29.6% 32.6% 53.5% 32.1% 37.7% 50.4% 34.6% 34.7% 12.8% 27.5% 28.5% 22.5% 24.4% 29.6% 24.4% 30.5% 28.6% 52.5% 56.2% 19.7% 21.6% 32.5% 45.6% 40.1% 27.6% 40.6% 18.4% 18.6% 30% 28.9%

Percentage of Children with Access to Public Pre-K Seats 65.18% 64.14% 60.68% 86.80% 100.00% 65.09% 81.77% 44.09% 36.17% 91.11% 85.29% 75.29% 66.52% 70.60% 49.47% 76.28% 15.81% 33.07% 78.35% 33.92% 13.49% 66.42% 23.20% 27.97% 51.49% 67.73% 82.68% 40.08% 22.78% 58.41% 84.43% 88.74% 29.81% 70.59% 39.85% 24.45% 38.27% 54.55%

STATE OF PRE-K SERIES: Poverty and Pre-K Access in Mississippi, 2017-2018

County Leake Lee Leflore Lincoln Lowndes Madison Marion Marshall Monroe Montgomery Neshoba Newton Noxubee Oktibbeha Panola Pearl River Perry Pike Pontotoc Prentiss Quitman Rankin Scott Sharkey-Issaquena Simpson Smith Stone Sunflower Tallahatchie Tate Tippah Tishomingo Tunica Union Walthall Warren Washington Wayne Webster

Percentage of Children Living in Poverty 33.5% 20.4% 60.2% 24.1% 32.6% 14.3% 33% 34.2% 25.6% 33.7% 31% 27.2% 45.8% 26.2% 34% 24.9% 31.3% 37.8% 21% 24.3% 57.5% 11.9% 29% 50.9% 33.6% 24% 24.3% 47.8% 41.7% 24% 23.1% 21% 44.6% 19.4% 37.2% 31.7% 45.3% 33.8% 33%

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Percentage of Children with Access to Public Pre-K Seats 27.97% 39.96% 52.87% 41.11% 45.66% 16.63% 27.70% 49.07% 51.43% 47.22% 46.28% 29.20% 53.50% 33.14% 55.33% 23.64% 15.03% 48.25% 8.64% 49.83% 73.91% 14.15% 55.38% 95.24% 37.54% 27.18% 26.49% 77.78% 77.04% 34.27% 60.22% 38.71% 69.95% 52.13% 41.76% 64.16% 66.38% 69.09% 23.26%

STATE OF PRE-K SERIES: Poverty and Pre-K Access in Mississippi, 2017-2018

County Wilkinson Winston Yalobusha Yazoo

Percentage of Children Living in Poverty 40.5% 33.3% 30.7% 41.7%

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Percentage of Children with Access to Public Pre-K Seats 80.20% 50.83% 55.71% 58.19%

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Appendix B: Rates of Poverty and Public Pre-K Access by District School District

Identified Student Percentage (ISP)

Aberdeen School District Alcorn School District Amite County School District Amory School District Attala County School District Baldwyn School District Bay St. Louis School District Benton County School District Biloxi Public School District Booneville School District Brookhaven School District Calhoun County School District Canton Public School District Carroll County School District Chickasaw County School District Choctaw County School District Claiborne County School District Clarksdale Collegiate Clarksdale Municipal School District Cleveland School District Clinton Public School District Coahoma County School District Coffeeville School District Columbia School District Columbus Municipal School District Copiah County School District Corinth School District Covington County School District Desoto County School District East Jasper School District East Tallahatchie School District Enterprise School District Forest Municipal School District Forrest County Schools Franklin County School District George County School District Greene County School District Greenville Public School District

57.65% 33.60% 66.43% 34.53% 53.41% 36.06% 47.42% 50.45% 44.51% 28.50% 49.62% 42.04% 64.04% 51.01% 49.00% 45.16% 70.45% -75.10% 52.47% 23.19% 74.49% 59.70% 46.04% 67.96% 52.02% 42.81% 50.47% 25.90% 53.04% 63.03% 24.35% 51.08% 47.77% 42.74% 39.36% 45.74% 85.75%

Percentage of Kindergarteners with Access to Public Pre-K 64.84% 43.72% 100.00% 48.91% 100.00% 52.54% 31.58% 100.00% 36.68% 35.58% 68.56% 74.00% 53.90% 61.19% 68.89% 82.83% 95.60% 56.60% 79.43% 75.61% 18.26% 55.45% 100.00% 26.96% 70.98% 42.55% 72.73% 84.27% 14.81% 100.00% 93.24% 54.67% 74.84% 31.50% 65.52% 36.14% 12.59% 95.33%

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School District

Identified Student Percentage (ISP)

Greenwood Public School District Grenada School District Gulfport School District Hancock County School District Harrison County School District Hattiesburg Public School District Hazlehurst City School District Hinds County School District Hollandale School District Holly Springs School District Holmes County Consolidated School District Houston School District Humphreys County School District Itawamba County School District Jackson County School District Jackson Public School District Jefferson County School District Jefferson Davis County School District Joel E. Smilow (Republic) Jones County School District Kemper County School District Kosciusko School District Lafayette County School District Lamar County School District Lauderdale County School District Laurel School District Lawrence County School District Leake County School District Lee County School District Leflore County School District Leland School District Lincoln County School District Long Beach School District Louisville Municipal School District Lowndes County School District Lumberton Public School District Madison County School District Marion County School District Marshall County School District

75.68% 44.03% 59.85% 38.25% 48.21% 72.34% 63.13% 40.02% 78.64% 60.76%

Percentage of Kindergarteners with Access to Public Pre-K 88.51% 54.15% 36.06% 22.76% 26.62% 50.28% 87.50% 60.24% 70.18% 66.36%

70.64%

82.93%

43.74% 76.39% 31.59% 29.78% 70.70% 61.94% 53.28% -36.39% 59.38% 43.82% 24.74% 30.53% 34.82% 65.89% 45.11% 51.23% 32.89% 77.21% 76.90% 30.63% 32.22% 52.87% 33.56% 67.96% 16.30% 50.05% 45.46%

21.85% 92.92% 36.59% 13.43% 71.13% 100.00% 100.00% 33.33% 14.21% 85.71% 80.34% 26.90% 24.75% 10.54% 61.20% 52.00% 34.19% 20.47% 56.30% 90.48% 9.42% 14.54% 57.86% 34.56% -6.80% 31.29% 57.68%

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School District

Identified Student Percentage (ISP)

McComb School District Meridian Public School District Monroe School District Moss Point School District Natchez-Adams School District Neshoba County School District Nettleton School District New Albany Public Schools Newton County School District Newton Municipal School District North Bolivar Consolidated School District North Panola School District North Pike School District North Tippah School District Noxubee County School District Ocean Springs School District Okolona Separate School District Oxford School District Pascagoula Separate School District Pass Christian Public School District Pearl Public School District Pearl River County School District Perry County Schools Petal School District Philadelphia Public School District Picayune School District Pontotoc City Schools Pontotoc County Schools Poplarville Separate School District Prentiss County School District Quitman County School District Quitman School District Rankin County School District Richton School District Scott County School District Senatobia Municipal School District Simpson County School District Smith County School District South Delta School District

70.41% 73.94% 27.41% 68.43% 66.61% 46.36% 34.95% 30.24% 33.58% 57.88%

Percentage of Kindergarteners with Access to Public Pre-K 69.83% 78.01% 55.67% 64.71% 85.00% 44.89% 17.48% 43.00% 14.52% 86.44%

77.53%

72.41%

72.04% 42.33% 34.14% 70.30% 22.08% 51.93% 22.19% 53.93% 36.54% 38.23% 31.45% 49.47% 30.09% 59.98% 57.78% 35.69% 36.20% 40.39% 35.33% 63.23% 56.14% 21.02% 45.26% 43.95% 43.91% 49.90% 36.91% 79.76%

70.49% 26.09% 50.53% 71.79% 9.34% 60.00% 46.15% 41.45% 33.11% 34.93% 0.00% 0.00% 27.79% 100.00% 49.01% 14.13% 3.88% 22.22% 61.14% 80.00% 70.16% 11.50% 41.82% 32.39% 33.05% 39.29% 26.37% 100.00%

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School District

Identified Student Percentage (ISP)

South Panola School District South Pike School District South Tippah School District Starkville Oktibbeha Consolidated School District Stone County School District Sunflower County Consolidated School District Tate County School District Tishomingo County Schools Tunica County School District Tupelo Public School District Union County School District Union Public School District Vicksburg Warren School District Walthall County School District Water Valley School District Wayne County School District Webster County School District West Bolivar Consolidated School District West Jasper School District West Point Consolidated School District West Tallahatchie School District Western Line School District Wilkinson County School District Winona-Montgomery Consolidated School District Yazoo City Municipal School District Yazoo County School District

48.91% 62.77% 33.13%

Percentage of Kindergarteners with Access to Public Pre-K 50.31% 72.32% 48.72%

48.00%

42.39%

40.86%

23.67%

74.89%

89.81%

49.60% 27.00% 80.11% 34.98% 26.17% 38.51% 54.74% 53.06% 45.94% 57.60% 37.53%

34.30% 33.73% 94.04% 51.97% 48.55% 42.03% 70.13% 49.65% 62.03% 70.37% 22.73%

75.06%

86.05%

42.71% 59.35% 65.13% 65.12% 59.81%

44.44% 82.26% 72.92% 49.26% 100.00%

52.15%

69.39%

80.51% 55.54%

85.20% 36.36%

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Appendix C: DEFINITIONS AND SOURCES 2017-2018

COUNTY DATA DEFINITIONS Percentage of Kids Living in Poverty (County) This data is reported by the U.S. Census Bureau Small Area Income and Poverty Estimates (SAIPE) for the year 2017. The percentage of kids living in poverty is the estimated number of individuals under the age of 18 living at or below 100% of the federal poverty line, as defined by the U.S. Office of Management and Budget, in 2017. The 90% confidence intervals for the state of Mississippi are 26.7% to 28.5%, with the average poverty rate for the state at 27.6%. The 90% confidence intervals would vary on a county-by-county basis but are not available for each county. The data was provided by the Mississippi KIDS COUNT through the KIDS COUNT online data center.

Estimated Number of Four-Year-Olds (County) For the estimated number of four-year-olds in each county regardless of year, we use bridged-race population data generated by the U.S. Census Bureau and reported by the National Center for Health Statistics at the Centers for Disease Control and Prevention. The U.S. Census normally reports unbridged age data by age spans (e.g., under five) on a county level. These single-year estimates by age and by county are statistical estimates created from intercensal (between census) data and reflect estimated populations as of July 1 of a year. For this report, we used the 1990-2017 online database with bridged-race estimates of the July 1 resident population from the Vintage 2017 postcensal series, the revised 2000-2009 intercensal series, and the 1990-1999 intercensal series. We use the year leading into a child’s pre-K year, e.g., 2017 for the 2017-2018 school year, etc., for the estimate. The Census does not report error estimates for this data though they caution that “any small population group…has the most potential for error.”

Public Pre-K Access Rate for Four-Year-Olds (County) The public pre-K access rate for four-year-olds in 2017-2018 uses as its numerator the sum of the data points described below and as the denominator the estimated number of four-year-olds in the county, as explained above. Because collaborative programs contain multiple types of providers, their seats are included by provider type instead of separately, below. For more information about the sources of these numbers as well as their limitations, please read the more extensive Definition and Sources appendix in our community accessibility brief. ●

Number Children in District Pre-K (2017-2018). The number of children in district pre-K is calculated by combining data from every school district program in the county. This data does not include children in school district programs exclusively designed to serve children with disabilities; however, these counts do include children with disabilities enrolled in general education programs. In most cases, the number of seats in district(s) is constructed from the number of children who took the spring 2018 state pre-K assessment in each school district, with adjustments for blended Head Start (see below) and special education-only enrollments taken from MDE enrollment data.

Please note that unlike 2014-2015, this number reflects enrollment in school district programs, not the maximum capacity a school district could serve.

●

Number of Children in Blended Head Start (2017-2018). The number of children in blended Head Start counts children served in programs jointly funded by a school district and a Head Start partner in each county. Mississippi First constructed this data by comparing the addresses and names of Head Start centers to the addresses of public schools in Mississippi. Where we found Head Start sites that overlapped (either by site name or by address), we removed these numbers from both the district counts and the Head Start counts and placed them in their own category—blended Head Start. We also referenced our previous report to see if any previously identified blended programs did not appear in our new data set so that we could double-check program locations. For these cases, we called federal program coordinators and checked with the Mississippi Head Start Collaboration Director. If we could not confirm these definitively (usually because staff had changed and had no historic knowledge or because we could not get responses), we made our best guess based on all available evidence.

●

Number of Children in Head Start (2017-2018). The number of children in Head Start includes the total enrollment of four-year-olds at all Head Start centers in each county. This data came from a variety of sources. Our primary source was a survey administered by the state Office of Head Start Collaboration and completed by directors of Head Start grantees. At times, we found the survey numbers to be

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inflated when compared to licensure data from MSDH, actual inspection reports, or the parent survey. If licensure data captured all the Head Start centers in a county and matched parent survey data, we gave second priority to MSDH licensure data. However, if we still found varying information, we looked for actual inspection reports and used those numbers when they clearly identified four-year-old pre-K enrollments. In a few cases, MSDH licensure numbers conflicted significantly with parent survey data, and there were no clear inspection reports. In these cases, we used parent survey data, especially if public school pre-K data from the parent survey was comparable to our district figures. For the centers that changed grantees, parent survey data was often the only available data. For one county—Attala— we imputed a figure from parent surveys because we had no other source. The parent surveys indicated that fewer than 10 students attended Head Start in Attala in 2017-2018. To be conservative, we imputed a figure of 9. ●

Number of Children in Public Childcare (2017-2018). The number of children in public childcare represents the total number of four-year-olds enrolled in childcare programs that participated in the state collaborative program in 2017-2018. We obtained this data from a Mississippi Department of Education report on the number of children in a childcare center participating in the 2018 spring pre-K assessment.

SCHOOL DISTRICT DATA DEFINITIONS Percent of Students Living in Poverty (2017-2018) The percent of students living in poverty is defined as the district’s “identified student percentage (ISP),” which is a federal rate combining the percentage of children who either qualify as “at risk” through federal support programs or whose families participate in federal poverty programs. The ISP uses family participation in the Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF) program, or Food Distribution Program on Indian Reservations (FPDIR); child eligibility for Head Start; classification of students as homeless, migrant, or runaway; or child participation in foster care. Each of these programs have different poverty eligibility guidelines (up to 185% of poverty) and may include children based on non-income factors. However, this is the most reliable source of poverty data by school district currently. (See the discussion in the Poverty and Access brief for why.) Since we understand the limitations of ISP, we recommend that readers understand district poverty rates as relative—a school district with a higher ISP has a higher percentage of students in poverty than another, even if the exact percentage of both may not be precise.

Public Pre-K Access for 2018-2019 Kindergarteners by School District Access to public pre-K for 2018-2019 kindergarteners by school district is represented in a bar graph on the school district dashboard. This graphic shows districtwide data, and because some of the component data points are estimates, this bar graph is an estimate. The data include students served in fullweek, classroom-based programs that are not exclusively for students with disabilities. ●

Total Number of Children in District Pre-K (2017-2018). This data reflects the number of children in each district enrolled in that district’s pre-K program in 2017-2018. This data does not include children in school district programs exclusively designed to serve children with disabilities;17 however, these counts do include children with disabilities enrolled in general education programs. In most cases, the number of seats in district(s) is constructed from the number of children who took the spring 2018 state pre-K assessment in each school district, with adjustments for blended Head Start (see below) and special education-only enrollments taken from MDE enrollment data. Please note that unlike 2014-2015, this percentage reflects enrollment in school district programs, not the maximum capacity a school district could serve. We assume that the same number of children who were enrolled in a district’s pre-K program in 2017-2018 matriculated to that district’s kindergarten class in 2018-2019, unless otherwise noted.

●

Total Number of Blended Head Start Seats (2017-2018). This data reflects the number of children served in programs jointly funded by that school district and a Head Start partner. Mississippi First constructed this data by comparing the addresses and names of Head Start centers to the addresses of public schools in Mississippi. Where we found Head Start sites that overlapped (either by site name or by address), we removed these numbers from both the district counts and the Head Start counts and placed them in their own category— blended Head Start. We also referenced our previous report to see if any previously identified blended programs did not appear in our new data set so that we could double-check program locations. For these cases, we called federal program coordinators and checked with the Mississippi Head Start Collaboration Director. If we could not confirm these definitively (usually because staff had changed and had no historic knowledge or because we could not get responses), we made our best guess based on all available evidence. We assume that

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the same number of children who were enrolled in a district’s blended Head Start program in 2017-2018 matriculated to that district’s kindergarten class in 2018-2019, unless otherwise noted. ●

Total Number of Children Who Transitioned to District from Head Start (2018-2019). This data reflects the number of 20182019 kindergarteners in each school district that we estimate attended Head Start in 2017-2018. The data was constructed by Mississippi First using a combination of the Head Start Survey, the Parent Survey, and the Blended Head Start data. Because the areas that Head Start centers serve are determined by county, not school district, lines, allocating Head Start seats to school districts can be complicated in counties with multiple school districts. In 2014-2015, we had exact transition data from Head Start centers (data documenting where children matriculated after Head Start), and we found that nearly all students transitioned to the public kindergarten in the district where their Head Start center was located. As a result, for single-district counties, we use Head Start seat counts from 2017-2018 to estimate how many Head Start seats were available to 2018-2019 kindergarteners from those districts. For multiple-district counties, we rely on a combination of parent survey data, Head Start data, and blended Head Start data to impute transition figures as best as possible. The parent survey data can sometimes be unreliable as parents may only report the program where their child started or finished the year but not where their child spent the majority of the school year. If a seat is blended, there is no separate category on the survey and the fact that a seat is blended also might not be obvious to parents, leading them to assign the child either to Head Start or the school district. This can lead to over- or undercounting of enrollment, which is why we used the parent survey only when no other sources were available. In general, though, parent survey data aligns to our Head Start and school district data sources, so we can be reasonably sure that it is an accurate reflection of transition data, except where noted in specific instances. However, we urge you to view these numbers as estimates and interpret them with caution, especially on an individual school district level.

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Total Number of Children Enrolled in Kindergarten (2018-2019). This data was obtained from the District and School Data tool on the Mississippi Department of Education’s website. The number represents all the students by district (traditional and charter) enrolled in kindergarten in 2018-2019 who were not in self-contained special education classrooms. We used 2018-2019 kindergarten enrollment data because it captures information about the 2017-2018 pre-K cohort.

SOURCES This section provides further information about poverty sources. For more information about how we constructed enrollment numbers by pre-K provider type, please see the more extensive Definition and Sources appendix in our community accessibility brief.

Identified Student Percentage This data was collected from a report titled “CEP Annual Notification of Local Educational Agencies (LEA)” available on the Mississippi Department of Education’s website. We use the 2018-2019 version of this report, which is based on 2017-2018 data. For the districts that consolidated between 20172018 and 2018-2019, we use a weighted average of each of the former districts’ ISPs as reported in this document. We use enrollment as reported in the document or on the MDE Office of Public Reporting’s School and District Data website in the case of Lamar County School District.

Census Data on the Population of Four-Year-Old Children The US Census Bureau normally reports age data in age groups (e.g., under five). To verify the number of four-year-olds in the state, we requested single-year estimates by county. The US Census Bureau provided us with a spreadsheet titled “Bridged - Race Population Estimates 1990 - 2017” from the Center for Disease Control and Prevention’s National Center for Health Statistics. When we discovered this information could be generated from an online tool for prior years, we updated all of our estimates for four-year-olds in previous years as well. The exact data set used is the 1990-2017 online database with bridged-race estimates of the July 1 resident population from the Vintage 2017 postcensal series, the revised 2000-2009 intercensal series, and the 1990-1999 intercensal series. Please note that using data on the county level, or any small population group, has the most potential for error. However, the margins of error for the data were not reported by the Census.

For the online tool, see the CDC WONDER Online Database: http://wonder.cdc.gov/bridged-race-v2017.html.