Using American Community Survey Data to Expand Access to the School Meals Programs (2012) / Chapter Skim
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4 Data Analysis and Results
4 Data Analysis and Results
Pages 93-150
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From page 93... ...
for universal free school meals, the panel implemented the technical approach described in Chapter 3 and conducted extensive analyses of the ACS direct and model-based estimates produced by the U.S. Census Bureau.
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From page 94... ...
Even if the data obtained by the ACS and by program applications are fully accurate, eligibility based on annual income can be different from eligibility and certification based on monthly income. Yet another difference is that the ACS records where students live, while school meals program certification data are based on where students attend school.
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From page 95... ...
In Chapter 5, we propose an approach to implementing the AEO that incorporates into the AEO claiming percentages not only the ACS eligibility estimates but also the participation rates of students when all are offered free meals. DIFFERENCES BETWEEN ACS AND ADMINISTRATIVE ESTIMATES The panel compared ACS estimates of students eligible for school meals by category (free, reduced price, full price)
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From page 96... ...
Systematic Differences Between ACS and Administrative Estimates The panel's analyses revealed that ACS estimates differ systematically from administrative estimates for districts that might be most interested in the AEO. Figure 4-1 plots ACS and CCD estimates of the percentage of students eligible for free meals in very high FRPL districts.
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From page 97... ...
and CCD (2009-2010) estimates for very high FRPL districts: Percentage of students eligible for free meals.
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From page 98... ...
Many districts are clustered around the line of equality between the ACS and administrative estimates for the reduced-price category. The scatter plots in Figures 4-1 and 4-2 suggest that for the typical very high FRPL district, the ACS substantially underestimates the percentage eligible for free meals and slightly overestimates the percentage eligible for reduced-price meals.
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From page 99... ...
and CCD (2009-2010) esti mates for very high FRPL districts: Percentage of students eligible for reduced price meals.
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From page 100... ...
and CCD (2009-2010) es timates for very high FRPL districts: Percentage of students eligible for free or reduced-price meals.
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From page 101... ...
ACS = American Community Survey; BRR = blended reimbursement rate; CCD = Common Core of Data; FRPL = free or reduced-price lunch. SOURCE: Prepared by the panel.
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From page 102... ...
SOURCE: Prepared by the panel. For very high FRPL districts, several consistent patterns emerge from these tables of average ACS-CCD differences: · The average ACS estimate of the percentage of students eligible for free meals is typically 15 to 22 percentage points lower than the average CCD estimate.
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From page 103... ...
(227) Percentage free 17.1 18.6 20.1 15.5 18.2 19.5 17.9 18.8 20.4 Percentage reduced price 3.6 3.1 3.9 3.7 2.9 3.7 3.5 3.2 4.1 Percentage free or reduced price 13.5 15.5 16.2 11.8 15.3 15.7 14.5 15.6 16.4 BRR, $ 0.33 0.37 0.39 0.29 0.37 0.38 0.35 0.38 0.40 High FRPL Districts (972)
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From page 104... ...
SOURCE: Prepared by the panel. TABLE 4-4 Average Across Years of Average Differences Between ACS Estimates and CCD Estimates for Very High FRPL and High FRPL Districts 3-Year Estimates for 1-Year 5-Year All Medium Estimates Estimates for and Large for All Large Estimand All Districts Districts Districts Very High FRPL Districts (1,641)
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From page 105... ...
Furthermore, as shown in Table 4-5 and in more detailed tables in Appendix F, average BRR differences are even smaller -- $0.05 to $0.13 -- for low and moderate FRPL districts, that is, districts with FRPL percentages below 50 percent in all school years from 2004-2005 through 2009-2010.8 These results demonstrate a challenge entailed in using ACS data to obtain school meals program eligibility estimates with which to implement the AEO. Specifically, the differences between ACS and administrative estimates are greatest, on average, for those districts for which the AEO might otherwise be most attractive (because they have higher fractions of students certified for free or reduced-price meals under traditional operating procedures)
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From page 106... ...
Errors in the ACS estimates can also contribute to the differences between those estimates and administrative estimates. The panel's review of the literature, consultation with experts during our meetings and workshop, and analyses revealed four major potential sources of systematic error in ACS estimates that may contribute to the average differences between the ACS and CCD estimates: · underreporting of SNAP participation in the ACS; · determination of eligibility from annual income in the ACS rather than monthly income as in the application process for the school meals programs; · limitations of using ACS data to count homeless students, stu dents in families of migrant or seasonal workers, and other students who do not live in traditional housing; and · the effects of families' exercising school choice opportunities, such as attending charter, magnet, and other nonneighborhood schools.
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From page 107... ...
Each is assumed to have 10 percent of its students certified for reduced-price meals. The percentages certified for free meals are 65 percent, 75 percent, and 85 percent to illustrate the effects of certification error on administrative estimates for districts with very high levels of free or reduced-price students.
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To derive the estimates of eligible students denoted "(2) ," we assumed that among those students who must pay full price because they were not approved for free or reduced-price meals, 25 percent applied for but were denied free or reduced-price certification.
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From page 109... ...
What do the illustrative results in Table 4-6 suggest about the potential effects of certification error on the differences between ACS eligibility estimates and administrative certification estimates? For very high FRPL districts, we found that BRRs based on ACS eligibility estimates are, on average, about $0.30 to $0.40 less than BRRs based on certification estimates from the CCD.
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From page 110... ...
. ." To evaluate underreporting of SNAP benefits in the ACS and its potential impact on school meals eligibility estimates, the panel compared the estimated number of individuals aged 5-17 in households reporting SNAP benefits on the ACS with the estimated number of individuals aged 5-17 receiving SNAP benefits according to the SNAP Quality Control (SNAP QC)
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From page 111... ...
According to the SNAP QC data, however, fewer than 0.1 percent of individuals aged 5 to 17 in SNAP households live in a household with gross income that exceeds 185 percent of the poverty line.11 Eligibility Determined from Annual Rather Than Monthly Income The ACS collects data on annual income and annual receipt of program benefits. However, eligibility for the school meals programs is based on current monthly income and current participation.
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From page 112... ...
With the collection of earnings data being tied specifically to spells of employment, a change in income -- attributable, for example, to the loss of a job -- that is sufficiently large to affect eligibility status for the school meals programs is likely to be captured in the SIPP even if the timing of the change is not exactly correct because of "seam bias." (Seam bias occurs when changes are more likely to be reported between rather than within waves.) Thus, we expect that our analysis of SIPP data provides a reasonably accurate basis for assessing the effect of using annual rather than monthly income to determine eligibility for the school meals programs, although the effect could be understated if there is still a propensity among SIPP respondents to misreport the timing of changes in income.
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From page 113... ...
monotonically from 0.96 for households in which the householder has no college degree to 0.80 for households with a college-educated house holder.12 Across census regions, the difference due to using annual rather than monthly income varies from $0.11 to $0.16. Although using annual rather than monthly income surely contributes to the ACS's underestimation of BRRs, it probably does not explain all of the average differences observed between ACS and administrative estimates.
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From page 114... ...
Furthermore, any misreporting of monthly changes in income probably varies across households of different types and thus across districts with different populations, strengthening our conclusion that a simple global correction, especially one based on SIPP data, would be of limited effectiveness. Limitations of Using ACS Data to Count Students Who Do Not Live in Traditional Housing Some of the differences observed between ACS and administrative estimates may be attributable to the challenges that arise in counting homeless students, students living in migrant labor camps, and other students who do not live in traditional housing and are categorically eligible for free meals.
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From page 115... ...
However, the October certification numbers from the district will include all migrant students, contributing to the large observed undercount of students eligible for free 15Assume that the district establishes that k categorically eligible children do not live in traditional housing units and the total enrollment is E If the ACS estimate for percentage free-eligible is pf and for percentage reduced-price-eligible is pr, then the estimate for the total number of students eligible for free meals is pf *
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From page 116... ...
As a result, school choice will not pose a problem for ACS eligibility estimates. However, if students leave the district, for example, to attend an independent charter school or are part of another interdistrict choice plan, and if students eligible for free or reduced-price meals differentially choose these options, ACS estimates will misrepresent the percentage of students eligible for free or reduced-price meals attending district schools.
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; and (3) administrative estimates based on actual enrollment versus ACS estimates (errors in the latter reflect ACS sampling and other errors, as well as errors due to the inability to take open enrollment into account)
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Use of a Statistical Model to Adjust for Differences Between ACS and Administrative Estimates The panel's analyses suggest that there are at least several potentially important sources of differences between ACS and administrative estimates, and the contributions of these sources are likely to vary substantially among districts. The effects of school choice and of students living in nontraditional housing, for example, will tend to be highly localized and variable, with many districts having no effects at all and others having moderate to large effects.
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From page 119... ...
Thus, the predictors could not be used to derive an adjustment for ACS estimates on an ongoing basis.18 As discussed in Chapter 5, however, an adjustment could be determined when the district first adopted the AEO and used thereafter without updating. In light of this issue, the panel estimated models that included predictors based on school meals certification data in the CCD ("FRPL predictors")
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From page 120... ...
Although a simple model with FRPL predictors explains only about three-fifths of the variability in ACS-CCD differences, a model with many interaction and quadratic terms has an adjusted R2 of nearly 0.75.20 Although even a well-developed predictive model might not be able to account for almost all of the variability in the differences between ACS and administrative estimates across districts, our exploratory results suggest that such a model might still be able to play a useful role in adjusting ACS estimates. This potential role of a predictive model is addressed in Chapter 6.
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From page 121... ...
As noted earlier, administrative estimates have no sampling variation, but they do vary from year to year because of real changes in socioeconomic conditions that affect eligibility and participation rates (as well as variation in nonsampling error, such as certification error)
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From page 122... ...
These results suggest that, relative to the intertemporal changes normally experienced by a district as reflected in administrative data, the typical large district would likely experience less variability if it used 3- or 5-year ACS estimates but greater variability if it used 1-year ACS estimates.23 The typical medium district would experience about the same variability as is normal if it used 3-year ACS estimates and less variability than is normal if it used 5-year ACS estimates. The typical small district would experience somewhat less than normal variability if it used 5-year ACS estimates.
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From page 123... ...
(relative to BRR of $1.65) 100 0.34 20.5 200 0.25 15.1 400 0.18 11.2 800 0.14 8.3 1,600 0.10 6.3 3,200 0.08 4.8 6,400 0.06 3.8 12,800 0.05 3.2 NOTE: ACS = American Community Survey; BRR = blended reimbursement rate.
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From page 124... ...
data. In addition to the direct estimates, however, the Census Bureau derived and provided ACS model-based estimates of the percentages of students eligible for free and reducedprice meals using an adaptation of the Small Area Income and Poverty Estimates (SAIPE)
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From page 125... ...
For the very high FRPL districts, however, the average of the average differences for the model-based BRR estimates is $0.54, 20 to 25 percent greater than the average difference for the ACS 5-year estimates. Examination of the first two rows of estimates in Table 4-9 suggests that the performance of the model used in deriving estimates of the percentage of students eligible for free meals needs further assessment and improvement.
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From page 126... ...
ACS = American Community Survey; BRR = blended reimbursement rate; CCD = Common Core of Data; FRPL = free or reduced-price lunch. SOURCE: Prepared by the panel.
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From page 127... ...
During this particular period, the trend was sufficiently strong that the 5-year estimates have a higher RMSE than the 3-year estimates, and the RMSE for the 5-year estimates is nearly as high 28Nonetheless, as noted above, BRRs based on ACS 5-year estimates are likely to be more stable than BRRs based on administrative certification percentages for many small districts. 29Mean squared error (MSE)
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From page 128... ...
Another consideration in evaluating estimates is the time lag between their reference period and when they would be used to determine reimbursements under the AEO. Although most of our analyses compare, for example, ACS estimates that include 2009 in the reference period -- i.e., the 2009, 2007-2009, and 2005-2009 estimates -- with SY 2009-2010 administrative estimates, AEO claiming percentages based on those particular ACS estimates would be used 2 years later -- for SY 2011-2012.31 Because no such lag is associated with administrative estimates, the lag in the ACS estimates is an additional source of error, specifically, a timeliness bias.
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From page 129... ...
The ACS provides estimates of eligible students based on the data on income and SNAP and welfare program participation collected by the survey, although as documented earlier in this chapter, the ACS eligibility estimates are substantially different, on average, from administrative certification estimates. The ACS does not collect data on participation by students in the school meals programs, yet it is participation that is the basis for reimbursement of districts for the meals they serve under traditional operating procedures or Provisions 2 and 3.
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From page 130... ...
In addition, the availability of free school meals for all students might increase participation among those previously eligible for free meals -- as well as those previously paying a reduced price or full price -- because it would reduce the family's burden of applying for benefits and remove any perceived stigma associated with participating in the program. Furthermore, participation might increase if eliminating the need to ascertain the eligibility status of students as they received or purchased meals allowed cafeteria lines to move more quickly so that it was easier to eat a meal during the allotted time for lunch.35 Thus, we would expect participation rates and the distribution of meals served under the AEO to be different from participation rates and the distribution of meals served under traditional operating procedures.
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From page 131... ...
An advantage of using administrative data for not only meals served but also certified students is that the role of participation is highlighted more clearly than it would be if we used ACS eligibility estimates. The latter are subject to sampling error, and as demonstrated earlier in this chapter, are systematically different from the administrative estimates of certified students.
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From page 132... ...
Participation Rates (%) Certified Students Meals Served Reduced Reduced Reduced District Free Price Full Price Free Price Full Price Free Price Full Price Austin, Texas 86 72 34 56 8 37 73 8 19 Chatham County, Georgia 75 72 48 59 9 32 67 10 23 Norfolk, Virginia 77 71 43 48 11 41 59 12 29 Omaha, Nebraska 92 84 61 50 11 39 58 12 30 Pajaro Valley, California 68 52 23 59 9 32 77 9 14 BRRs District Certified Students ($)
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From page 133... ...
To supplement results for the case study districts, Table 4-14 presents state-level BRRs based on the distribution of certified students, national participation rates applied to each state's distribution of certified students, and each state's actual participation rates applied to its distribution of certified students (which equals the BRR derived from the actual distribution of meals served)
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From page 134... ...
Reduced Full Reduced Full District Free Price Price Free Price Price Austin, Texas 86 72 34 75 67 43 Chatham County, Georgia 75 72 48 75 67 43 Norfolk, Virginia 77 71 43 75 67 43 Omaha, Nebraska 92 84 61 75 67 43 Pajaro Valley, California 68 52 23 75 67 43 Claiming Percentages (based on meals served) District Participation National Participation Rates (%)
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From page 135... ...
Reduced Full Reduced Full District Free Price Price Free Price Price Austin, Texas 86 72 34 68 66 54 Chatham County, Georgia 75 72 48 84 75 58 Norfolk, Virginia 77 71 43 83 74 45 Omaha, Nebraska 92 84 61 88 78 67 Pajaro Valley, California 68 52 23 66 60 25 Claiming Percentages (based on meals served) District Participation State Participation Rates (%)
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From page 136... ...
and could use them in combination with ACS eligibility estimates to develop AEO claiming percentages. Although such participation rates have the advantage of being specific to each district, a potentially important limitation is that they would not reflect the effects on participation of offering free meals to all students.
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From page 137... ...
Another way to examine these results is to consider whether the changes in participation rates induced by offering free meals to all students under the AEO might bring the distribution of meals served close to the distribution of certified/eligible students. If that were to occur, claiming percentages could be based on the distribution of certified/eligible students, and it would not be necessary to take participation into account.
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From page 138... ...
Adjusted Actual Adjusted Reduced Full Certified Using National Meals Certified Using National State Free Price Price Students Participation Rates Served Students Participation Rates Alabama 84 75 57 1.49 1.79 1.69 0.20 0.09 Alaska 66 66 25 1.22 1.53 1.76 0.54 0.23 Arizona 86 74 35 1.37 1.67 1.83 0.47 0.16 Arkansas 84 74 49 1.53 1.82 1.80 0.28 0.01 California 66 60 25 1.51 1.80 1.99 0.48 0.19 Colorado 75 64 26 0.97 1.26 1.53 0.56 0.27 Connecticut 83 73 40 0.96 1.24 1.34 0.38 0.10 Delaware 70 73 61 1.38 1.69 1.46 0.08 0.22 District of Columbia 72 61 41 1.74 2.00 2.00 0.26 0.00 Florida 78 65 31 1.41 1.71 1.89 0.48 0.18 Georgia 84 75 58 1.50 1.80 1.70 0.20 0.09 Hawaii 62 56 48 1.24 1.54 1.37 0.13 0.17 Idaho 80 71 54 1.31 1.61 1.51 0.20 0.10 Illinois 76 63 39 1.37 1.68 1.73 0.36 0.06 Indiana 67 58 65 1.40 1.70 1.41 0.01 0.29 Iowa 80 77 63 1.02 1.31 1.14 0.12 0.17 Kansas 81 74 55 1.16 1.46 1.37 0.21 0.09 Kentucky 76 79 79 1.64 1.91 1.62 0.02 0.29 Louisiana 76 67 61 1.67 1.94 1.78 0.11 0.16 Maine 72 62 40 1.14 1.44 1.46 0.32 0.02 Maryland 77 67 31 1.04 1.33 1.52 0.48 0.19 Massachusetts 78 65 40 0.99 1.28 1.34 0.35 0.05 138 Michigan 75 67 34 1.19 1.50 1.63 0.44 0.13 Minnesota 73 84 57 1.00 1.28 1.13 0.14 0.15
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Mississippi 85 75 51 1.77 2.03 2.00 0.23 0.02 Missouri 80 73 55 1.27 1.58 1.48 0.21 0.10 Montana 77 67 43 1.09 1.39 1.40 0.31 0.01 Nebraska 88 78 67 1.10 1.40 1.24 0.14 0.16 Nevada 65 51 23 1.25 1.55 1.79 0.54 0.23 New Hampshire 79 67 45 0.76 0.99 1.00 0.24 0.00 New Jersey 80 67 36 1.06 1.35 1.48 0.42 0.13 New Mexico 74 67 49 1.77 2.02 1.96 0.19 0.06 New York 74 66 40 1.37 1.68 1.70 0.32 0.02 North Carolina 78 68 43 1.40 1.70 1.72 0.32 0.02 North Dakota 100 80 66 0.86 1.13 1.04 0.18 0.09 Ohio 79 71 40 1.13 1.44 1.50 0.37 0.07 Oklahoma 72 69 50 1.53 1.82 1.73 0.20 0.09 Oregon 72 61 31 1.30 1.60 1.74 0.45 0.14 Pennsylvania 78 72 47 1.08 1.38 1.35 0.27 0.03 Rhode Island 76 65 28 1.17 1.47 1.71 0.54 0.23 South Carolina 81 70 45 1.48 1.78 1.79 0.31 0.01 South Dakota 82 78 65 1.11 1.41 1.23 0.12 0.18 Tennessee 71 64 50 1.53 1.82 1.72 0.19 0.11 Texas 68 66 54 1.77 2.02 1.88 0.11 0.14 Utah 75 72 50 1.03 1.32 1.24 0.21 0.08 Vermont 78 67 43 0.99 1.27 1.28 0.29 0.01 Virginia 83 74 45 1.04 1.33 1.36 0.32 0.03 Washington 76 65 31 1.15 1.45 1.63 0.48 0.18 West Virginia 70 63 60 1.46 1.76 1.54 0.08 0.22 Wisconsin 76 73 53 1.04 1.34 1.24 0.20 0.10 Wyoming 80 71 53 0.98 1.26 1.19 0.20 0.08 United States 75 67 43 1.35 1.66 1.66 0.30 0.00 NOTE: BRRs = blended reimbursement rates. 139 SOURCE: Prepared by the panel.
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From page 140... ...
140 USING ACS DATA TO EXPAND ACCESS TO THE SCHOOL MEALS PROGRAMS TABLE 4-15 BRRs Based on Certified Students Versus BRRs Based on Meals Served: Illustration with Case Study District Schools Claiming Percentages Participation Rates (%) Certified Students Reduced Full Reduced Full School Free Price Price Free Price Price 1 98 94 23 65 7 27 2 96 9 85 63 11 26 3 85 64 35 65 9 26 4 96 91 71 59 16 25 5 96 79 44 68 8 24 6 91 82 59 57 20 23 7 63 55 18 67 10 23 8 74 71 71 68 9 23 9 93 94 83 64 14 22 10 45 31 6 72 7 21 11 57 44 16 74 6 20 12 96 86 66 76 6 18 13 89 95 27 75 6 18 14 89 87 74 68 15 17 15 77 67 33 77 9 15 16 99 93 33 80 7 14 17 97 98 55 83 4 13 18 90 89 82 83 5 12 19 82 67 35 78 11 11 20 96 90 90 84 5 10 21 62 41 28 77 13 10 22 70 47 22 82 8 10 23 95 93 60 88 3 9 24 92 92 68 84 8 8 25 86 80 40 87 7 6 26 95 95 95 89 6 5 27 94 67 60 88 7 5 28 90 84 78 86 10 4 29 84 77 78 89 7 4 30 90 83 60 87 9 4 NOTE: BRRs = blended reimbursement rates.
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DATA ANALYSIS AND RESULTS 141 Claiming Percentages Meals Served BRRs Certified Reduced Full Students Meals Difference Percentage Free Price Price ($) Served ($)
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From page 142... ...
Reduced Full Reduced Full District Free Price Price Free Price Price Austin, Texas 86 72 34 91 88 44 Chatham County, Georgia 75 72 48 80 77 58 Norfolk, Virginia 77 71 43 82 79 53 Omaha, Nebraska 92 84 61 97 94 71 Pajaro Valley, California 68 52 23 73 70 33 Claiming Percentages (based on meals served) Actual, Pre-AEO (%)
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From page 143... ...
· BRRs based on ACS estimates of eligible students are substan tially less than BRRs based on CCD estimates of certified students for high and very high FRPL districts, on average. · Average ACS-CCD differences are larger for very high FRPL dis tricts than for high FRPL districts.
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From page 144... ...
(%) Actual, Pre-AEO Reduced Full Reduced Full Reduced Full School Free Price Price Free Price Price Free Price Price 1 98 94 23 100 97 33 83 9 8 2 96 9 85 100 97 94 72 1 27 3 85 64 35 90 87 45 79 8 13 4 96 91 71 100 97 81 64 17 20 5 96 79 44 100 97 54 80 8 13 6 91 82 59 96 93 69 64 20 17 7 63 55 18 68 65 28 82 10 8 8 74 71 71 79 76 73 69 9 22 9 93 94 83 98 95 92 66 15 20 10 45 31 6 50 47 16 90 6 3 11 57 44 16 62 59 26 87 6 7 12 96 86 66 100 97 76 81 5 14 13 89 95 27 94 91 37 86 8 6 14 89 87 74 94 91 84 70 15 14 15 77 67 33 82 79 43 85 8 7 16 99 93 33 100 97 43 88 7 5 17 97 98 55 100 97 65 88 4 8 18 90 89 82 95 92 89 84 5 11 19 82 67 35 87 84 45 85 10 5 20 96 90 90 100 97 94 85 5 10 21 62 41 28 67 64 38 85 10 5 22 70 47 22 75 72 32 91 6 3 23 95 93 60 100 97 70 91 3 6 24 92 92 68 97 94 78 86 8 6 25 86 80 40 91 88 50 90 7 3 26 95 95 95 100 97 94 89 6 5 27 94 67 60 99 96 70 91 6 3 28 90 84 78 95 92 88 87 9 4 29 84 77 78 89 86 83 90 7 4 30 90 83 60 95 92 70 89 8 3 NOTE: AEO = American Community Survey (ACS)
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DATA ANALYSIS AND RESULTS 145 Illustrative, Post-AEO BRR Reduced Full Actual Pre- Illustrative Percentage Free Price Price AEO ($)
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From page 146... ...
Difference Austin, Texas 1.71 2.12 2.05 0.41 24 0.34 20 Chatham County, Georgia 1.80 2.01 1.96 0.21 11 0.15 9 Norfolk, Virginia 1.59 1.87 1.81 0.29 18 0.22 14 Omaha, Nebraska 1.64 1.84 1.80 0.20 12 0.16 10 Pajaro Valley, California 1.81 2.22 2.13 0.41 23 0.33 18 NOTE: AEO = American Community Survey (ACS) Eligibility Option; BRR = blended reimbursement rate.
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From page 147... ...
Based on the panel's empirical analyses, as well as consultations with experts and reviews of relevant documents, the panel reached the following conclusions: Conclusion 4-1: A one-size-fits-all approach for benchmarking ACS estimates of students eligible for school meals to administrative estimates to minimize the differences caused by such factors as underreporting of SNAP participation is not possible at present. Further research will be required to determine whether a techni cally sound and operationally feasible set of procedures for estimat ing the necessary adjustments to the ACS estimates can be devel oped.
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From page 148... ...
Eligibility Option; BRR = blended reimbursement rate. SOURCE: Prepared by the panel.
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From page 149... ...
DATA ANALYSIS AND RESULTS 149 Difference from Certified Students BRR Actual Meals Served, Pre-AEO Illustrative Meals Served, Post-AEO Percentage Percentage Difference ($) Difference Difference ($)
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From page 150... ...
For all but the smallest districts, however, reimbursements based on ACS estimates might be equally stable over time and often more so than reimbursements based on administrative estimates, and this feature of the AEO might be attractive to districts along with its other benefits. Although a one-size-fits-all approach for benchmarking ACS estimates to administrative estimates is not feasible at present, a tailored approach to using ACS estimates could possibly allow more districts to offer free meals to all students under the AEO.
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