Federal, state, and local governments share the financing of our nation’s public schools. The federal share is the smallest, averaging about 7 percent of public school funding in the 1991-92 school year. Nationwide, the other 93 percent of funding was about evenly split between state and local funding (see fig. 2). However, the state share of total public funding varied by state from about 9 percent in New Hampshire to about 76 percent in New Mexico in the 1991-92 school year. Localities raise revenue for education mainly through property taxes, and the amount of local funds depends on both property values and local tax rates. This has produced local funding disparities because school districts’ property tax bases vary widely. Localities with high property values can generally raise large amounts of local revenue per pupil even with relatively low tax rates; localities with low property values usually raise less local revenue per pupil even with higher tax rates. In an earlier report, we found that poorer districts in 35 states tended to make a greater tax effort than wealthier districts in school year 1991-92, but this effort was not sufficient to eliminate the funding gaps between poor and wealthy districts in 23 of these states. When allocating revenue to districts, states typically consider these tax base differences as well as educational need factors. States use various equalization strategies to address the funding gaps that arise from tax base differences. Such strategies include targeting more funds to districts with lower tax bases and increasing the state’s share of total education funds. Meanwhile, states typically consider districts’ educational needs, including the number of pupils in a district, the cost of educating different types of pupils (for example, students with disabilities), and other educational cost factors beyond the districts’ control such as costs related to sparsity or enrollment growth. The educational needs of poor students are one of the states’ considerations when making funding decisions. Poor students risk academic failure because their homes or communities lack the resources to prepare them academically and because, among other factors, they have considerable health and nutrition problems. Children living below the poverty level are more likely than nonpoor children to have learning disabilities and developmental delays. As a result, poor students’ academic achievement tends to be low, and they have high rates of dropping out of high school. To help low-achieving poor students, 28 states funded compensatory programs in school year 1993-94, according to a national study on school finance programs. States may have funded such programs by directly allocating funds for this purpose, incorporating the funding into other programs, or including weights in their basic support formulas that provide funds for school districts’ daily operations. Funding for state compensatory programs that directly targeted poor students represented up to 11 percent of total state school aid. The total spent for compensatory programs ranged from about $1 million in Wyoming to about $785 million in Texas in school year 1993-94. The lawsuits filed since the early 1970s challenging the constitutionality of state school finance systems based on the inequitable distribution of education revenues between districts within states demonstrate that ensuring a fair distribution of funds is a complex and difficult undertaking. States are under constant pressure from both poor and wealthy districts, education interest groups, and anti-tax groups to modify their state school finance systems. For example, in our 1995 study of three states involved in equity lawsuits, we found that the state remedies for improving the equity of their school finance systems had to respond to citizens’ concerns about increased taxes and to concerns of wealthy districts that want to maintain spending levels. In fiscal year 1997, the federal government spent about $37 billion on elementary and secondary education. The Department of Education provides most of these funds. The states’ education agencies receive most of the funds and then allocate them to local districts. Programs funded this way include those for disadvantaged children, children with disabilities, drug-free schools, math and science, vocational education, and migratory education. Department of Education funding provided directly to districts included impact aid, bilingual education, and Indian education. Among other federal agencies that spend substantial amounts on elementary and secondary education are USDA through its child nutrition programs and HHS through its Head Start and other programs. Most federal funding for elementary and secondary education is targeted to disadvantaged and poor children. For example, the Department of Education’s title I grants that provide compensatory services for disadvantaged students accounted for about $7.2 billion of the federal funding for education in fiscal year 1997, and USDA’s child nutrition programs for low-income students accounted for about $8.3 billion. Title I has anchored the Elementary and Secondary Education Act since it was first enacted in 1965. USDA began providing child nutrition programs with the enactment of the National School Lunch Act of 1946 and later expanded its effort under the Child Nutrition Act of 1966. Members of the Congress have recently considered more flexible approaches for funding federal education programs as a way to possibly consolidate duplicative programs and eliminate regulations seen as unnecessarily limiting local flexibility. Education programs serving disadvantaged students, including title I, are possible candidates for this approach. The Congressional Research Service recently noted that among the unresolved issues concerning such approaches are the amount of flexibility that would be allowed states or localities in using these federal funds and the extent to which recipients would be held accountable for achieving certain outcomes. Most states targeted more funds to districts with large numbers of poor students, although the amount of such funding varied widely. In most states, federal funds were more targeted than state funds, which resulted in increasing the overall amount of additional funding for each poor student. Regardless of whether a state’s school finance system explicitly targeted poor students, the effect was to target more state funds to poor students in 43 of the 47 states in our analysis. State school finance systems may have targeted poor students either directly through compensatory programs or indirectly through other programs, such as bilingual education, which may serve a high proportion of poor students. The amount of extra state funding districts received for each poor student varied widely. On average, for every $1 a state provided in education aid for each student in a district, the state provided an additional $.62 per poor student. At the high end, New Hampshire provided an extra $6.69 per poor student; at the low end, four states provided no additional funding per poor student. Federal funding was more targeted to poor students than state funding in 45 of the 47 states. On average, for every $1 of federal funding districts received for each student, they received an additional $4.73 in federal funding per poor student. The amount of additional federal funding districts received for each poor student varied widely. At the high end, districts in Alaska received an additional $9.04 in federal funding; at the low end, districts in West Virginia received an additional $2.59. In general, the greater federal targeting had the effect of raising the additional funding for poor students from the state-only average of $.62 to a combined state and federal average of $1.10, a 77-percent increase. This increase reflects that most states’ relatively small share of federal funds was highly targeted. Again, states varied widely in the amount of combined targeting that occurred, ranging from an additional $7.41 for poor students in Missouri to an additional $.27 in West Virginia. In three states, the addition of federal funding increased funding for poor students but did not enhance the state targeting effort. In one state (New Hampshire), the addition of federal funding yielded less combined targeting for a poor student. The other two states (Nevada and New York) did not target poor students, and the addition of the relatively small amount of targeted federal funding did not raise the combined targeting effort above zero. Table 1 shows each state’s amount of state and federal targeting and the amount of targeting when state and federal funding are combined. The addition of state and federal funds had the effect of reducing or eliminating the local funding gap between high- and low-poverty districts in most states. In 37 states, high-poverty districts had less local funding per weighted pupil than low-poverty districts. State funding eliminated this funding gap in 7 states and reduced it in the remaining 30 states. The addition of the more targeted federal funds eliminated the funding gap in another 9 states and further reduced it in the 21 states that still had funding gaps. A substantial number of poor students lived in these 21 states, however. Although targeting poor students helped reduce the total funding gap, the percentage of total education funding provided by state and federal governments was more important in reducing the gap. States with a greater state and federal share of education funding had smaller total funding gaps. High-poverty districts had less local funding per weighted pupil than low-poverty districts in 37 states. Separating all school districts into five groups on the basis of increasing poverty rates reveals the size of the gaps (see fig. 3). The average local funding per weighted pupil in the lowest poverty districts was $3,739 compared with $1,751 in the highest poverty districts. The lowest poverty districts nationwide had about 114 percent more local funding than the highest poverty districts. This gap occurred even though the highest poverty districts in 30 states made a greater tax effort than the lowest poverty districts. Combined state and federal funding had the effect of eliminating the funding gap in 16 of the 37 states where the local funding per weighted pupil was less in high- than low-poverty districts. Combined state and federal funding reduced the funding gap in the remaining 21 states. The arrows in figure 4 show the effects of combined state and federal funding on closing the local funding gap between high- and low-poverty districts. The light arrow indicates the effect of state funding on closing the funding gap; the dark arrow indicates the effect of federal funding. The zero line (0) of the figure indicates no funding gap between high- and low-poverty districts. States whose funding gaps are represented by negative values are those where higher poverty districts had less funding per weighted pupil; states whose funding gaps are represented by positive values are those where higher poverty districts had more funding per weighted pupil. The further the value is from the zero line, the greater the funding gap. The legend in figure 4 describes three points that mark the progress of state and federal funds in closing the funding gap. The tail end of the state arrow represents the size of the local funding gap. The second and third points measure the size of the gap that remains after state funds and then federal funds are added. For example, New York’s local funding gap of about –.65 indicates that local funding levels were less in high-poverty than in low-poverty districts. Moving to the zero line, the addition of state funds reduced the gap to –.40. The addition of federal funds reduced the gap further to about –.35. (See app. V for more information on each state’s points and the statistical significance of each.) Figure 4 shows that most states had a funding pattern like New York’s, with state funding favoring high-poverty districts. In some cases, state funds favored high-poverty districts so much that the resulting distribution of funds favored high-poverty districts (it passed the zero line). In some states, the local funding levels in high-poverty districts already exceeded those in the low-poverty districts. In these states, state funding offset or reduced this imbalance. Finally, in all states, federal funding favored the high-poverty districts regardless of the distribution of state and local funds. The national distribution of education resources shown in figure 5 provides another perspective on the size of the gaps nationwide and the effect of state and federal funding in closing them. (See also table 2.) When we compared the distribution of local funds of the lowest and highest poverty districts (see fig. 3), the lowest poverty districts had about 114 percent more local funding per weighted pupil than the highest poverty districts nationwide. States helped considerably in closing this funding gap, reducing it to 25 percent. The addition of federal funds had the greatest effect on the highest poverty districts and reduced the gap to about 15 percent. A relatively high combined state and federal share of total funding enhanced state and federal targeting efforts to close the funding gap. Figures 6 and 7 illustrate this point. Both California and Virginia had about the same average total funding per weighted pupil and the same combined state and federal targeting rate per poor student. However, California’s state and federal share was much larger (about 71 percent) than Virginia’s (about 39 percent). This difference reduced California’s funding gap to one smaller than Virginia’s. The highest poverty districts in California received $237 less in total funding per weighted pupil than the lowest poverty districts; in Virginia, the highest poverty districts received $970 less than the lowest poverty districts. The size of the combined state and federal share of total funding was more important in closing the funding gap than the extent to which these funds were targeted to poor students. This proved to be the case in an analysis we conducted to assess the effect of factors that influence the size of the funding gap. Many states eliminated their funding gaps even though they had relatively low targeting efforts in part because they had higher than average state and federal shares of total funding. Conversely, many states did not close their funding gaps even though they had relatively high targeting efforts in part because they had relatively low state and federal shares of total funding. Despite state and federal efforts to close the funding gap, the most important factor determining the size of the gap was the tax effort of high-poverty districts compared with low-poverty districts. Although state and federal funding closed or eliminated the funding gaps between high- and low-poverty districts, the gaps that remained in the 21 states affected a significant portion of the nation’s poor students. Nearly two-thirds of the students in our study were in these 21 states, and about 64 percent of the nation’s poor students attended public schools in these states. Information on the state and federal targeting amounts and the effect of state and federal funding on the funding gaps in school year 1991-92 appears in the state profiles in this report (see apps. VI through LIII). Each profile also provides the amount of local, state, and federal funding available for districts in five groups of approximately equal numbers of students arranged in increasing proportions of poor students as well as other demographic information. We contacted state school finance officials in the 47 states to determine whether school finance systems had changed in ways that would affect the funding patterns of school year 1991-92. By school year 1995-96, only 16 states reported making changes that would target more funds to high- poverty districts. Ten states reported no change in targeting, 19 states reported no targeting of high-poverty districts, and 2 states reported targeting less funding to high-poverty districts. Eight of the 47 states reported increasing their state share of education funding by 6 percentage points or more. Appendix LIV summarizes the changes states made between school years 1991-92 and 1995-96. Although greater targeting has been limited to a minority of states since school year 1991-92, federal funding formulas have changed, which would result in a continued pattern of greater targeting. Federal education officials have reported increased targeting to high-poverty districts resulting from changes in title I legislation and regulations that went into effect in July 1995. Title I, the largest federal education program, provides funding for disadvantaged students. In addition, other federal programs allocate funds on the basis of title I formulas. The changes in title I would increase the relative funding for high-poverty districts from these other programs. Appendix LV discusses changes in federal funding to the states since school year 1991-92 in greater detail. Federal funding for education, which primarily serves the needs of poor and disadvantaged students, is generally more highly targeted to poor students than more multipurpose state funding. In allocating funds to districts, state officials must balance the needs of poor students with those of many other high-cost student groups such as special education students. States also generally try to offset differences in localities’ ability to raise education revenues. The states’ wide range in targeting to poor students indicates that different states balance the needs of poor students with all other needs in different ways. Furthermore, the many lawsuits alleging inequities in state school finance systems illustrate that states are under constant pressure to meet the needs of many and often conflicting interest groups. In this context, any proposal to consolidate federal education funding into grants that give more discretion to states would need to consider that the targeting of those federal funds might become more like that of the state funds. That is, the federal funds—and the combination of federal and state funds—might become less targeted to poor students. In assessing states’ performance in financing the education needs of poor students, policymakers need to look beyond state efforts to target poor students and consider the combined state and federal share of total education funds. A low state targeting effort does not necessarily mean that a large funding gap exists between a state’s high- and low-poverty districts, according to our analysis. Rather, a relatively high overall share of state and federal funding can reduce the gap. The Department of Education reviewed a draft of this report and agreed with our finding that federal funding was generally more targeted to poor students than either state funding or combined state and federal funding. As suggested by the Department, we clarified the wording used to describe federal targeting and incorporated technical comments as appropriate. As agreed with your office, unless you publicly announce its contents earlier, we plan no further distribution of this report until 30 days from the date of this letter. At that time, we will send copies to appropriate congressional committees and members of the Congress, the Secretary of Education, and other interested parties. Please contact me on (202) 512-7014 or Eleanor L. Johnson, Assistant Director, on (202) 512-7209 if you or your staff have any questions. GAO contacts and staff acknowledgments appear in appendix LVI. The objectives of this study were to determine (1) the extent to which state and federal funding is targeted to poor students and (2) the effect of state and federal funding on the amount of funds available to high-poverty compared with low-poverty districts. To help answer these questions, we used school year 1991-92 district-level data from the Department of Education, the most recent available, supplemented by data from the 1990 census and directly from states. We used standard school finance measures and accounted for geographic differences in education costs and student need among school districts. We supplemented our analysis by contacting federal and state education officials to determine the extent to which federal funding patterns and the states’ school finance systems had changed since 1991-92. We conducted our work between March and December 1997 in accordance with generally accepted government auditing standards. For this study, we conducted a district-level analysis of all states except Hawaii, Vermont, and Wyoming. We wanted our analysis to examine state funding for regular school districts with students in kindergarten through twelfth grade, so we excluded from the analysis administrative districts and districts serving unique student populations, such as vocational or special education schools. We also excluded from our analysis a number of small districts that had extreme outlying values of income per pupil. Finally, we excluded districts that lacked data for critical variables such as poverty level. The final database used in our analysis of the 47 states contained 14,140 districts with a total of 41,011,102 students, representing 99.2 percent of the public school students in the 47 states. We based this study mainly on revenue and demographic data obtained from the Department of Education’s Common Core of Data (CCD) for the 1991-92 school year, the most current data available for a national set of districts. Data for the CCD were submitted by state education agencies and edited by the Education Department. We obtained district per capita income and population data directly from the 1990 census because they were not available in the CCD. We used revenue data from all sources in the analysis, including funding for capital expenditures and debt service. Federal revenue included funding from all Department of Education sources, although we considered federal impact aid to be local revenue in our analysis because states typically consider funding from this program as part of a district’s local education resources. We also included federal revenue from other departments that had revenue reported in the CCD, including funding for Head Start from HHS and for USDA’s child nutrition programs. For variables in our analysis that had missing or incomplete data, we obtained the data directly from state education offices. For example, we obtained district-level data for students with disabilities for school year 1991-92 directly from the state education offices for nine states because the CCD either did not report the number of these students in the states or reported a number substantially different from another Education Department source. We also obtained district-level data on federal revenue from seven states for similar reasons. We made further edits on the basis of consultations with Department of Education experts. In some cases, we imputed critical data when they were missing and not available from other sources. We imputed income per pupil data for 199 districts in California because the per capita income data needed to compute this control variable were not reported by these districts. We also imputed cost index data for 310 districts, including 18 in Alaska and 72 in New York (mainly Suffolk County). The imputation method we used to impute cost index data was based on the recommendation of the school finance expert who developed the cost index. We conducted structured telephone interviews with state school finance officials to determine the extent to which states had changed their school finance systems since school year 1991-92. We did not, however, verify the accuracy of the officials’ statements. We also interviewed federal officials and reviewed supporting documentation about changes in federal funding programs since school year 1991-92. Education costs vary by school district in a state (and nationwide) because of geographic differences in the cost of educational resources. For example, some districts have a lower cost of living, which may reduce the cost of their education resources. As a result, we used a district-level teacher cost index developed for the National Center for Education Statistics to develop a method to adjust for statewide geographic differences in resource costs. Districts with high proportions of students with special needs, such as those with disabilities and the poor, generally have higher education costs than average because such students require additional educational services. When adjusting our analysis for statewide differences in student need, we made adjustments that weighted students with disabilities and poor students according to their need for additional services. We gave students with disabilities a weight of 2.3 because the cost of educating these children is generally 2.3 times the cost of educating children who do not need such services. We gave poor students a weight of 1.6 because this was the median state weight in our analysis. Using these weights, we developed a district-level need index adjusted for statewide differences. To measure the extent to which state funding was targeted to districts on the basis of the number of poor students, we estimated the additional state funding per poor student a district received for every dollar of state funding received for each student. To estimate the additional funding per poor student, we developed a statistical model of the distribution of state funding to local school districts. The model describes the distribution of state funds as if a fixed percentage of the funds was allocated to districts on the basis of the number of poor students and the remaining percentage was allocated on the basis of the total number of students. The model also describes the targeting of state funds to districts with low tax bases. Thus, the model accounts for both student needs-based targeting related to the number of poor students and targeting to low tax base districts. By modeling the distribution of state funds this way, we measured the additional state funds that districts received per poor student compared with every dollar received for each student, while statistically removing any additional funding districts may have received due to the size of their local tax base. In addition, the model allowed us to measure state targeting policies that either directly targeted funding to districts on the basis of the number of poor students or indirectly targeted funding on the basis of other student needs such as limited-English proficiency programs that may serve poor students. We used the same general model to determine the extent to which federal funding and combined state and federal funding were targeted to districts on the basis of the number of poor students. However, when determining the targeting of just federal funding, we did not control for differences in local tax bases because none of the federal funds included in our analysis were allocated on the basis of local tax bases. In appendix II, we describe the statistical model used to estimate state and federal targeting based on the number of poor students. In appendix III, we use the model to estimate the additional funding districts received that was targeted directly or indirectly to poor students but controlling for the additional funding districts may have received as a result of tax base targeting. Appendix IV analyzes how each state’s estimate of poor student targeting would change if we controlled for funding that indirectly targeted poor students as in states that target students with disabilities. Throughout these analyses we adjusted state and federal funding for statewide differences in geographic costs and used income per student to measure local tax bases, also adjusted for geographic costs. In estimating these targeting amounts, we weighted each observation by the district’s size to allow districts with larger enrollments to have more effect on the results. To measure the effect of state and federal funding on closing the funding gap between high- and low-poverty districts, we estimated the elasticity of each state’s districts’ per pupil funding with respect to districts’ poverty rate, that is, the proportion of a district’s total enrollment that is poor.We estimated separate elasticities for local funding only; local and state funding combined; and local, state, and federal funding combined. Observing the change in the elasticity as state funding and then federal funding were added to local funds quantitatively measures the effect of state and federal funding on funding gaps between high- and low-poverty districts. We adjusted these analyses for differences in statewide geographic costs and student need. In estimating these elasticities, we weighted each observation by the district’s size to allow districts with larger enrollments to have more effect on the results. Appendix V details this process. To determine the factors most closely associated with the nationwide differences in states’ funding gaps between high- and low-poverty districts, we used multiple regression techniques. We estimated several models that used each state’s elasticity of districts’ pupil funding to districts’ poverty rate as the dependent variable. We included the following state-level variables as possible explanatory variables (see app. V): the combined additional state and federal funding targeted to districts on the basis of the district’s number of poor students, the extent to which state funding is targeted to low tax base districts, combined state and federal funding as a percentage of total funding, the tax effort of low-poverty compared with high-poverty districts in a state, and the tax base of low-poverty compared with high-poverty districts in a state (as measured by income per pupil). Whenever we included more than one independent variable in a regression routine, all the variables were entered into the analysis at the same time. Appendixes VII through LIII provide profiles of each state’s school finances in school year 1991-92. The profiles provide information on state and federal funding, the targeting of additional state and federal funding for poor students, differences in the tax effort of high- and low-poverty districts, and the effect of funding on closing the funding gap. Appendix VI is a detailed guide to the state profiles. Because we relied on funding data from the 1991-92 school year, we telephoned states’ school finance officials to determine how state school finance systems had changed from school years 1991-92 through 1995-96. We specifically asked about changes that would affect the amount of funding provided to districts with high proportions of poor students. We also telephoned federal officials responsible for the major education programs and reviewed program documents to determine how changes in regulations or legislation may have changed federal funding to poor students. Appendixes LIV and LV present the results of these efforts. State school finance systems typically provide funds to school districts to account for differences in student needs and ability to raise education revenues. Because poor students are generally recognized as having special education needs that increase the cost of their education, many states try to offset these costs by targeting additional funds to districts with high numbers of poor students. Meanwhile, states try to compensate for the limited ability of districts with low tax bases to raise education revenues by targeting additional state funds to such districts. Poor students reside in poor and wealthy districts alike. Therefore, when estimating a state’s effort to target poor students, accounting for state policies that target additional funds to low tax base districts is also important. This appendix describes the statistical model we used to estimate state efforts to target additional funding to poor students, while controlling for targeting to low tax base districts. In the first section, we describe how we modeled a district’s total student need on the basis of the number of all students and poor students. In the second section, we incorporate the total student need of districts into a more general model of state funding that also compensates for differences in districts’ tax bases. This general model assumes that states target additional funds to low tax base districts to equalize the funding among poor and wealthy school districts. States typically distribute state funds to school districts on the basis of school district enrollment. To allow for policies that provide additional funding to districts on the basis of the number of poor students, we introduce an implicit cost weight (w ) that reflects the additional state funding provided to each poor student in the district. A district’s total student need (total enrollment with additional weight given to the number of poor students) is represented by the following equation: N = a district’s student enrollment count P = a district’s count of poor students = the state’s implicit cost weight associated with a poor student. The implicit cost weight (w ) can be interpreted as follows: If the state expense for educating an average student were normalized to $1, then w represents the additional state expense for educating a poor student. For example, if a poor student were 50 percent more expensive for the state to educate than an average student, then w would equal $.50. Our research objective was to estimate the implicit cost weight associated with poor students. We refer to this cost weight as an implicit weight because it must be inferred from data on the actual distribution of state funds to local districts. In addition, it should be noted that poor students represent the model’s only student need factor other than total enrollment. By not controlling for other student need factors (for example, limited-English proficiency or gifted students), our estimate of the implicit cost weight reflects any additional state funding systematically related to the number of poor students in local school districts. To estimate the implicit cost weight from data on the distribution of state funding to local school districts, we first express student needs as a grant formula. If state funds were distributed simply on the basis of enrollment with additional funding for poor students, then a district’s share of total state funding (Grant Share) could be expressed as its share of the state’s total student need (Need Share) as in equation II.2: To estimate w district’s share of the state’s total student need (Need Share) as a linear function of enrollment and the number of poor students. We accomplished this by first expanding equation II.2 to equation II.3: using linear regression methods, we had to express a Multiplying the first term in equation II.3 by S N/S N and the second by S P/S P does not change the value of the expression and allows us to express a district’s share of total student need as a weighted sum of the district’s share of enrollment (N/S N) and its share of poor children (P/S P): Note that the terms in parentheses sum to one and can be interpreted as formula weights applied to a district’s share of total enrollment and its share of poor students. Equation II.4 can now be written more simply as follows: where w = the formula weight relative to the district’s share of total state enrollment, and w = the formula weight relative to the district’s share of the state’s total number of poor students, and Dividing both sides of equation II.5 by each district’s share of total enrollment (N/S N) yields an expression for each district’s relative per pupil grant that also serves as an index of student needs. The following equation demonstrates that, in our simple model of student needs, a district’s per pupil grant would be linearly related to the proportion of poor students in the districts: g = a district’s per pupil grant (g = the state average per pupil grant) n = a district’s student need index (an index value of 1.0 would indicate that the district’s proportion of poor students equals the state’s average proportion of poor students) r = a district’s proportion of poor students (P/N); (r = the state average proportion of poor students (S P/S N)). Because the implicit cost weight (w ) depends on the formula weights w in equation II.6 for the implicit cost weight w r = the state average proportion of poor students (S P/S N). The implicit cost weight associated with poor students (w ) could be estimated by applying linear regression techniques to the model in equation II.6. However, this would not account for state targeting to poor students that may also offset differences in local tax bases. Consequently, the model in equation II.6 could bias the estimate of the implicit cost weight because it would not control for the effects of tax base targeting that coincide with poor student-based targeting. To obtain an unbiased estimate of the implicit cost weight, we modeled the distribution of state funding using a foundation equalization model like that used in our earlier report. With foundation equalizing grants, states seek to enable all school districts to finance a minimum amount of total funding per pupil (the foundation funding level) with a uniform minimum tax effort. An important implication of this standard is that state funding must be targeted to school districts with low tax bases per student. States can adjust the foundation level to account for differences in geographic and student need-related costs. Our modeling approach is to use the state’s average total funding per pupil as a benchmark against which to estimate the foundation funding level that a state’s school finance policies can implicitly support. A state’s average total funding level represents the highest level of total funding per pupil that a state can support with the amount of both state and local resources it devotes to education (it is impossible to guarantee all districts an above average funding level). Under a foundation equalizing system that supports an implicit foundation level equal to the average total funding per pupil (e), districts would receive a total state equalizing grant (G) according to the following: G = total state funding in a district g = a scalar that ensures that the total sum of state funding equals the total amount of state funds available for distribution N = a district’s enrollment count c = a district’s input cost index that reflects geographic differences in, for example, the cost of teachers n = a district’s student need index defined in equation II.6 e = a state’s average total funding per pupil (the maximum funding level that can be attained by equalizing all available state and local funding) = the locally financed share of total funding = equalization factor (b =1 signifies maximum equalization and b =0 implies none) v = a district’s tax base per pupil. The state average total funding per pupil serves as a benchmark funding level. Given this benchmark, the quantity represented by (Ncne) is the dollar amount of total funding a school district needs to finance this benchmark level. The implicit foundation level, that is, the minimum total funding per pupil (expressed in real dollars), is given by g e. Note that this level is a fraction (g ) of the state average total funding level. In our earlier report, we showed that the scalar g depends on the state financing share (1-a ) and the equalization factor b through the following relationship:Notice that the scalar equals 1 if the equalization factor b also equals 1. Thus, the implicit foundation level equals the state average funding level when b =1 and falls below the state average when b is less than 1. The equalization model can be expressed as a linear regression model by substituting the expression for n in equation II.6 and the expression for g in equation II.9 into equation II.8. Dividing both sides of the resulting equation by an expression for the average state grant per pupil (g = (1-a )e) and rearranging some terms yields the following regression model: g = a district’s state grant per pupil (g = average state grant per pupil) r = a district’s proportion of poor students (r = the proportion of all students in a state who are poor students) v = a district’s tax base per pupil (v = state average) c = a district’s input cost index that reflects geographic differences in, for example, the cost of teachers unrelated to poor students and tax bases. Our goal was to estimate states’ and federal targeting of additional funding to districts on the basis of the number of poor students. This appendix presents the statistical results of estimating the grant targeting model described in appendix II. It presents estimates of grant targeting on the basis of the number of poor students for (1) state funding alone, (2) federal funding alone, and (3) combined state and federal funding. We estimated the grant targeting by including the additional funds that districts received for each poor student from programs that target poor students directly through compensatory programs, or indirectly, through, for example, programs that target limited-English proficiency students. Appendix IV shows how the grant targeting estimates would change after controlling for some indirect targeting based on other student needs. As described in appendix II, we began by estimating the model summarized in equation II.10, reproduced here as equation III.1, for each of the 47 states included in our analysis: g = a district’s state grant per pupil (g = average state grant per pupil) r = a district’s proportion of poor students (r = the proportion of all students in the state who are poor) v = a district’s tax base per pupil (v = state average) c = a district’s input cost index that reflects geographic differences in, for example, the cost of teachers unrelated to poor students and tax bases. Given the estimated tax base coefficients in equation III.1, we then solved . From this, we derived the formula weight w from the estimated regression coefficient on poor students. We then calculated the implicit cost weight using equation II.7. The results of these calculations appear in table III.2. Implicit cost weight for state funding(continued) The formula weights reported in table III.2 show a wide range of variation in the proportion of state funding allocated on the basis of the number of poor students. In Alabama, for example, state funding was distributed as if 6 percent of the targeting based on student need was allocated on the basis of the number of poor students in a district and 94 percent on the basis of a district’s total enrollment. This formula weight is equivalent to providing Alabama school districts with an additional $.27 per poor student for every $1 allocated per student in a district. Overall, 43 of the 47 states in our analysis targeted additional funding either directly or indirectly to districts with poor students to some degree. The amount of extra funding that districts received varied substantially by state. On average, districts received an additional $.62 in state funding for each poor student. At the high end, for every $1 of state aid provided for each student, New Hampshire provided an extra $6.69 per poor student; at the low end, four states (Montana, Nevada, New Mexico, and New York) provided no additional funding on the basis of the number of poor students. Figure III.1 shows each state’s additional funding per poor student in ranked order. Figure III.1: Targeting of State Funds to Poor Students, School Year 1991-92 Extra Funding per Poor Pupil (Dollars) To estimate the targeting of federal funds per poor student, we modeled the distribution of federal funding on the basis of total enrollment and the number of poor students as shown in equation II.10. However, a tax base variable was not included in the model because federal programs do not allocate funding on the basis of this factor. Therefore, b resulting in equation III.2. The dependent variable was the district’s federal funding per pupil adjusted for statewide differences in teacher cost. The independent variable was the district’s proportion of poor students. Each variable was expressed in index form relative to their respective state averages. The regressions were weighted for a district’s enrollment size: The regression coefficients and their associated standard errors and the R squares from our analysis, along with the implicit cost weight associated with federal funding for poor students, appear in table III.3. Implicit cost weight for federal funding(continued) Implicit cost weight for federal funding(Table notes on next page) Federal funding was more targeted to poor students than state funds in 45 of the 47 states. On average, districts received an additional $4.73 in federal funding per poor student for every $1 of funding received by each student. This amount compares with an additional $0.62 in state funding.The amount of additional federal funding varied widely. At the high end, Alaska provided an additional $9.04 in federal funding; at the low end, West Virginia provided an additional $2.59. In the two states with the highest state targeting effort (Missouri and New Hampshire), federal funds were targeted to poor students but to a lesser extent than state funds. Figure III.2 shows federal targeting in ranked order. Figure III.2: Targeting of Federal Funding to Poor Students, School Year 1991-92 Extra Funding per Poor Pupil (Dollars) To estimate the targeting of combined state and federal funds, we estimated the model in equation III.1 using combined state and federal funding per pupil adjusted for statewide differences in the cost of teachers’ salaries as the dependent variable. The two independent variables were a district’s proportion of poor students and a district’s income per pupil adjusted for statewide differences in the cost of teachers. Because federal funding is not targeted on the basis of income per pupil, we constrained the coefficient of the income per pupil variable to be the same as that in the regression for state funding alone. As before, each variable was expressed in index form relative to its respective state averages. All regressions were weighted on the basis of a district’s enrollment. The regression coefficients and their associated standard errors from our analysis appear in table III.4 along with the R squares of the model. The formula weight and implicit cost weight associated with combined state and federal funding for poor students appear in table III.5. Table III.4: Regression Results Used to Determine Implicit Cost Weight of Combined State and Federal Funding (continued) (Table notes on next page) Implicit cost weight for combined state and federal funding(continued) Greater federal targeting had the effect of raising the average state targeting from $.62 to an average combined state and federal targeting of $1.10, a 77-percent increase. This increase reflects the fact that the relatively small share of federal funds was highly targeted in most states. Again, states’ amounts of combined targeting varied widely, ranging from $7.41 in Missouri to $.27 in West Virginia. The addition of federal funding increased state targeting most in North Dakota ($1.75) and least in Florida ($.13). In three states, the addition of federal funding did not enhance the state’s targeting effort. In New Hampshire, the addition of federal funding yielded less combined targeting for a poor student. The other two states (Nevada and New York) did not target poor students, and the addition of the relatively small amount of targeted federal funding did not raise the combined targeting effort above zero. Figure III.3 shows these results in ranked order. A comparison of the implicit cost weights of state funding alone and combined state and federal funding appears in table III.6. Figure III.3: Targeting of Combined State and Federal Funding to Poor Students, School Year 1991-92 Extra Funding per Poor Pupil (Dollars) Implicit cost weight for combined state and federal funding(continued) Our primary concern was to measure the extent to which states target additional funds to school districts to compensate for the higher cost of educating poor students, while controlling for state policies that target more funds to low tax base districts. In measuring state targeting to poor students, we wanted to measure the state’s targeting effort regardless of whether it was an explicit state policy or the result of targeting other types of student needs that may be correlated with poor students. However, estimating the extent to which states target more funds to districts on the basis of the number of poor students could also be done by holding other types of student needs constant. To measure this type of targeting, we expanded our modeling of student need by including additional student need factors. To account for additional student need factors, we modified equation II.5 to include each district’s share of (1) high school students, (2) students with an Individual Education Plan (a measure of pupils with special education needs), (3) the square of student enrollment, and (4) the land area of the school district. Adding these factors, each district’s share of total student need (Need Share) would be expressed in the following equation: Dividing both sides of equation IV.1 by each district’s share of total enrollment would produce the following expanded student need index: n = a district’s student need index PI = a district’s percentage of poor students expressed as a percentage of the state average HSI = a district’s percentage of high school students expressed as a percentage of the state average IEPI = a district’s percentage of students with an individual education plans expressed as a percentage of the state average NIits share of total enrollment = a district’s share of enrollment squared expressed as a percentage of LAI = a district’s land area per student expressed as a percentage of the state average. Substituting equations IV.2 and II.9 for equation II.8 and rearranging terms allows us to express the foundation equalization model with additional student need indicators as follows: We have estimated the model summarized in equation IV.3 for the 47 states included in our analysis using state and combined state and federal funding. Both dependent variables were expressed on a per pupil basis adjusted for statewide differences in teacher costs. The regression coefficients and standard errors for the two variables of interest—the poor student variable and the tax base variable—as well as the R squared and standard error of the model appear in table IV.1 for the state funding model. Regression results for the combined state and federal funding model appear in table IV.2. (continued) The analysis excluded the land area variable because of missing land area data. (continued) The analysis excluded the land area variable because of missing land area data. (continued) Implicit cost weight for state (continued) Implicit cost weight for state (continued) As table IV.4 shows, the results of the expanded model differ dramatically from those of the model used in appendix III for a number of states. Overall, the implicit weight of state funding in the expanded model increased in 16 states and decreased in 26 states. States with the largest increases in the implicit weight of state funding were Connecticut, Illinois, Massachusetts, New Hampshire, and New York; states with the largest decreases were Alaska, Michigan, Missouri, and New Jersey. Kansas, Maryland, Rhode Island, Tennessee, Texas, and West Virginia also had noteworthy increases; Delaware, Idaho, Iowa, North Dakota, and South Carolina had noteworthy decreases. Five states had the same implicit weight. The median implicit weight declined slightly, from $.62 to $.61. A comparison of the combined state and federal weights reveals a similar pattern. The same five states had the largest increases in the implicit weight of combined state and federal funding: Connecticut, Illinois, Massachusetts, New Hampshire, and New York; the same four states had the largest decreases: Alaska, Michigan, Missouri, and New Jersey. Kansas, Maryland, Texas, and West Virginia also had noteworthy increases; Iowa and Utah had noteworthy decreases. Overall, the implicit combined weight in the expanded model increased in 17 states and decreased in 28 states. Two states had the same implicit weight. The median implicit weight decreased slightly, from $1.10 to $1.06. One goal of this study was to determine the variability of local funding levels in high- and low-poverty districts and the changes in these funding levels as state and federal funds were added. Because high-poverty districts tend to have low tax bases, such districts typically have lower local funding levels compared with low-poverty districts. States generally distribute state funds on the basis of a district’s educational need and ability to raise local revenue for education, while federal funds are targeted largely to poor and other disadvantaged students. Given these policy features, we expected high-poverty districts to benefit from both state and federal funding and that total funding levels in high- and low-poverty districts would be more equal with the addition of state and then federal funds. This appendix presents the method we used to estimate the size of the local funding gap and the effect that state funds and then federal funds had on closing this gap in each state. It also presents results of the distribution of total funding to districts with the highest and lowest poverty levels. Finally, it discusses factors that affect poverty-related funding gaps. We measured the size of the funding gap by determining the extent to which funding varied in high- and low-poverty districts using the poverty elasticity of funding per weighted pupil. The elasticity measures the percentage change in a district’s funding level for every 1-percent change in a district’s poverty rate, where the district’s change in a variable is measured relative to its state average. We determined the poverty elasticity of local funding per weighted pupil and then the changes in poverty elasticity with the addition of state funds and then with the addition of federal funds. A negative poverty elasticity score indicates that high-poverty districts tended to have less funding per weighted pupil than low-poverty districts; a positive elasticity score indicates that high-poverty districts tended to have more funding per weighted pupil than low-poverty districts; and 0 score indicates that no systematic differences occurred in funding levels among all districts. We used a linear regression model to estimate the elasticity of a district’s funding relative to a district’s proportion of poor students. To assess the incremental effects of state funds and then federal funds, we estimated the poverty elasticity relative to a district’s funding in three ways. First, we determined the poverty elasticity to local funding per weighted pupil. We then added state funds and determined the poverty elasticity of the combined state and local funding per weighted pupil. Finally, we added the federal funds to determine the poverty elasticity of total (federal, state, and local) funding per weighted pupil. The dependent variable was one of the three measures of district funding per weighted pupil, and each was adjusted for statewide differences in geographic cost and student need (see app. I). The independent variable was a district’s poverty rate. For each regression, the dependent and the independent variables were placed in index form, that is, they were expressed as a percentage of their respective state averages. We estimated the three poverty elasticities by weighting each observation for membership size to better reflect the distribution of state funding to students rather than to districts; thus, school districts with larger enrollments had a greater effect in determining the estimated coefficients of the model. With these adjustments, a general model for all three regressions took the following form: Because both variables are measured relative to their respective state averages, the regression coefficient (b score. The error term (e ) in the equation reflects the variation in the ) represents the poverty elasticity funding per weighted pupil that could not be accounted for by the poverty index variable. In 37 states, high-poverty districts had less local funding per weighted pupil than low-poverty districts (the poverty elasticity was negative).Florida had the largest local funding gap and South Dakota the smallest. In two states (New Mexico and Utah), high-poverty districts had more local funding per weighted pupil (the poverty elasticity was positive). In both of these states, high-poverty districts made a greater tax effort than low-poverty districts. In the remaining eight states, local funding per weighted pupil was not statistically different as poverty rates increased. The addition of state funds reduced the number of states with a funding gap (negative elasticity) from 37 to 30 and the size of the funding gap in the remaining 30 states. Of the states where funding gaps remained, state funding in Florida reduced the gap most, and state funding in New Hampshire reduced it the least. Three states had a positive elasticity, that is, the combined local and state funding per weighted pupil increased as a district’s poverty rate increased. The addition of federal funds further reduced the number of states with a funding gap (negative elasticity) from 30 to 21 and the size of the funding gap in the remaining 21 states. Of the states where funding gaps remained, federal funding in Alabama reduced the gap the most, and federal funding in New Hampshire reduced it least. In six states, high-poverty districts had more total (local, state, and federal) funding per weighted pupil than low-poverty districts (positive elasticity). Table V.1 shows the elasticities of local, local and state, and total funding to district poverty rates and the adjusted R square for each state. Figure 4 (shown earlier in the report) provides the table information in graphic form. Local, state, and federal funding (continued) Local, state, and federal funding (Table notes on next page) Another way to analyze the size of the poverty-related funding gaps is to examine the amount of funding available to districts with the highest and lowest poverty rates. To do this, we grouped each state’s student population into five groups. These groups were determined by ranking a state’s districts according to increasing proportions of poor students and then dividing these districts into five groups, each with about the same number of students. We defined lowest poverty districts as those districts in the first group and highest poverty districts as those in the fifth group. Normally, each group consisted of about 20 percent of each state’s students. Nationwide, the lowest poverty districts had about 114 percent more local funding per weighted pupil than the highest poverty districts. The addition of state funds greatly reduced this funding gap to 25 percent. The addition of federal funding reduced the total funding gap to about 15 percent. Table V.2 summarizes the gaps in total funding per weighted pupil between each state’s highest and lowest poverty districts. Lowest poverty group funding compared with the highest poverty group funding(continued) Lowest poverty group funding compared with the highest poverty group funding(continued) Several factors affect the size of the gaps in total funding between high- and low-poverty districts. These include differences in the tax base of high- and low-poverty districts, differences in the tax effort of high- and low-poverty districts, the state and federal shares of total funding, the extent to which state and federal funding is targeted to districts with high-poverty rates, and the extent to which state funding is targeted to districts with low tax bases. To estimate the extent to which these factors accounted for the variation in the total funding gap between high and low-poverty districts, we constructed a regression model that used these factors to explain differences among states’ funding gaps. We used the elasticity of local, state, and federal funding reported in table V.1 as the measure of the total funding gap between high- and low-poverty districts. We used the elasticity of local tax bases relative to district poverty rates as the measure of tax base differences and the elasticity of local tax effort relative to districts’ poverty rates as the measure of tax effort differences. We also used the combined state and federal share of total funding, the combined state and federal targeting to poor students, and the states’ tax base targeting in the model. These factors appear in table V.3. We estimated several versions of the model with state and federal funding shares and poor student targeting entered separately and combined into one variable. The model described in table V.4, which has four variables, all of which were statistically significant, accounted for 57 percent of the variation in funding gaps among states. The model includes only four variables because when we included all five variables in the analysis, the fifth variable, differences in state tax base targeting, was insignificant. Table V.3: Factors Affecting Poverty-Related Funding Gaps, School Year 1991-92 Share of funding (percent) Elasticity of local tax effort(continued) Share of funding (percent) Elasticity of local tax effort(Table notes on next page) This is the amount of extra state funding per poor student a district received for every dollar of state funding received for each student. As the beta coefficients in table V.4 show, differences in tax efforts had the greatest effect on reducing the total funding gap—the greater the tax effort of high-poverty districts compared with low-poverty districts, the lower the funding gap. Combined state and federal share of total funding had the second greatest effect on reducing the funding gap: the larger the combined share, the less the funding gap. Differences in tax bases between high- and low-poverty districts had the third greatest effect: the greater the tax base of high-poverty districts compared with low-poverty districts, the lower the gap. Combined state and federal targeting to poor students also had the effect of reducing the gap, although to a lesser extent than the other three variables. Appendixes VII through LIII contain profiles for 47 states. Each profile provides the critical data resulting from our analysis of state and federal targeting to poor students and the effect that state and federal funds had on the funding levels among high- and low-poverty districts. In addition, each profile provides information in tabular and graphic form on the distribution of local, state, and federal funding to regular school districts in school year 1991-92. The profiles show state averages for districts in five groups according to increasing proportions of poor students. For example, the highest poverty group typically contains about 20 percent of a state’s students and has the highest proportion of poor students. All funding data in the profiles were adjusted for statewide differences in geographic cost and student need. Data used in the profiles were based mainly on the Department of Education’s Common Core of Data (CCD) for school districts for the 1991-92 school year. In some cases, we obtained data directly from state education offices, and we imputed data for a district when the source lacked data. For example, we imputed cost index data for 310 districts, including 18 in Alaska and 72 in New York (see app. I). Funding data included all local, state, and federal revenue for all purposes, including maintenance and operations, transportation, and capital expenditures and debt service. Federal impact aid was considered part of local revenue because states consider federal funding from this program as part of a district’s local education resources. The numbers in the profiles’ tables may not add due to rounding. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table VII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Alabama averaged $3,696. The localities provided about 27 percent of total funding for education; the state provided about 62 percent; federal funds provided about 11 percent. Alabama’s state funding had the effect of providing districts with an additional $.27 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.92 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Alabama’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 66 percent to about 19 percent. The addition of federal funding further reduced the funding gap between these groups to about 6 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Alabama, districts with the highest proportions of poor students made a slightly greater effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 101 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table VII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table VII.3 presents data on how local, state, and federal funds were distributed among the five groups of Alabama districts. (Fig. VII.1 provides table information in graphic form.) Table VII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table VIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Alaska averaged $9,054. The localities provided about 27 percent of total funding for education; the state provided about 68 percent; federal funds provided about 5 percent. Alaska’s state funding had the effect of providing districts with an additional $1.81 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $2.42 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Alaska’s targeting efforts and state share of total funding more than eliminated the 2-percent local funding gap between the lowest and highest poverty groups. Consequently, the lowest poverty group had about 19 percent less funding than the highest poverty group. The lowest poverty group had about 22 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Alaska, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 240 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table VIII.2 presents demographic data for school year 1991-92 for five groups with districts of increasing proportions of poor students. Table VIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Alaska districts. (Fig. VIII.1 provides table information in graphic form.) Table VIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Alaska education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Alaska’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Alaska appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table IX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Arizona averaged $4,959. The localities provided about 51 percent of total funding for education; the state provided about 43 percent; federal funds provided about 7 percent. Arizona’s state funding had the effect of providing districts with an additional $0.50 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.10 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Arizona’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 55 percent to about 16 percent. The addition of federal funding further reduced the funding gap between these groups to about 5 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Arizona, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 159 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table IX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table IX.3 presents data on how local, state, and federal funds were distributed among the five groups of Arizona districts. (Fig. IX.1 provides table information in graphic form.) Table IX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Arizona education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Arizona’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Arizona appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table X.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Arkansas averaged $4,164. The localities provided about 32 percent of total funding for education; the state provided about 59 percent; federal funds provided about 9 percent. Arkansas’s state funding had the effect of providing districts with an additional $.29 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.76 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Arkansas’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 34 percent to about 8 percent. The addition of federal funding further reduced the funding gap between these groups to the extent that the lowest poverty group had 2 percent less funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Arkansas, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 106 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table X.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table X.3 presents data on how local, state, and federal funds were distributed among the five groups of Arkansas districts. (Fig. X.1 provides table information in graphic form.) Table X.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Arkansas education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Arkansas’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Arkansas appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in California averaged $4,902. The localities provided about 29 percent of total funding for education; the state provided about 64 percent; federal funds provided about 7 percent. California’s state funding had the effect of providing districts with an additional $1.15 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.59 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) California’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 177 percent to about 14 percent. The addition of federal funding further reduced the funding gap between these groups to about 5 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 94 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XI.3 presents data on how local, state, and federal funds were distributed among the five groups of California districts. (Fig. XI.1 provides table information in graphic form.) Table XI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A California education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in California’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about California appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Colorado averaged $5,288. The localities provided about 54 percent of total funding for education; the state provided about 42 percent; federal funds provided about 4 percent. Colorado’s state funding had the effect of providing districts with an additional $.27 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.57 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Colorado’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 24 percent to about 9 percent. The addition of federal funding further reduced the funding gap between these groups to about 3 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 103 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XII.3 presents data on how local, state, and federal funds were distributed among the five groups of Colorado districts. (Fig. XII.1 provides table information in graphic form.) Table XII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Colorado education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Colorado’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Colorado appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Connecticut averaged $8,531. The localities provided about 59 percent of total funding for education; the state provided about 37 percent; federal funds provided about 4 percent. Connecticut’s state funding had the effect of providing districts with an additional $1.53 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.89 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Connecticut’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 172 percent to about 27 percent. The addition of federal funding further reduced the funding gap between these groups to about 17 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 81 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Connecticut districts. (Fig. XIII.1 provides table information in graphic form.) Table XIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Connecticut education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Connecticut’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Connecticut appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XIV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Delaware averaged $6,008. The localities provided about 28 percent of total funding for education; the state provided about 65 percent; federal funds provided about 7 percent. Delaware’s state funding had the effect of providing districts with an additional $.38 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.56 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Delaware’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 65 percent to about 7 percent. The addition of federal funding further reduced the funding gap between these groups to about 4 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 130 percent of the effort made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XIV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XIV.3 presents data on how local, state, and federal funds were distributed among the five groups of Delaware districts. (Fig. XIV.1 provides table information in graphic form.) Table XIV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Delaware education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Delaware’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Delaware appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Florida averaged $5,964. The localities provided about 44 percent of total funding for education; the state provided about 49 percent; federal funds provided about 7 percent. Florida’s state funding had the effect of providing districts with an additional $.62 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.75 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Florida’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 58 percent to about 7 percent. The addition of federal funding further reduced the funding gap between these groups to about 3 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 99 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XV.3 presents data on how local, state, and federal funds were distributed among the five groups of Florida districts. (Fig. XV.1 provides table information in graphic form.) Table XV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Florida education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Florida’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Florida appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XVI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Georgia averaged $4,688. The localities provided about 42 percent of total funding for education; the state provided about 50 percent; federal funds provided about 8 percent. Georgia’s state funding had the effect of providing districts with an additional $.40 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.81 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Georgia’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 32 percent to about 7 percent. The addition of federal funding eliminated the funding gap between these groups to the extent that the lowest poverty group had about 3 percent less funding than the highest poverty group. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Georgia, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 122 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XVI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XVI.3 presents data on how local, state, and federal funds were distributed among the five groups of Georgia districts. (Fig. XVI.1 provides table information in graphic form.) Table XVI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Georgia education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Georgia’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Georgia appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XVII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Idaho averaged $3,805. The localities provided about 31 percent of total funding for education; the state provided about 62 percent; federal funds provided about 7 percent. Idaho’s state funding had the effect of providing districts with an additional $.66 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.10 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Idaho’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 32 percent to about 7 percent. The addition of federal funding further reduced the funding gap between these groups to about 2 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 90 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XVII.2 presents demographic data for school year 1991-92 for five groups with districts of increasing proportions of poor students. Table XVII.3 presents data on how local, state, and federal funds were distributed among the five groups of Idaho districts. (Fig. XVII.1 provides table information in graphic form.) Table XVII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Idaho education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Idaho’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Idaho appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XVIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Illinois averaged $5,295. The localities provided about 63 percent of total funding for education; the state provided about 31 percent; federal funds provided about 6 percent. Illinois’s state funding had the effect of providing districts with an additional $2.01 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $3.08 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Illinois’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 158 percent to about 63 percent. The addition of federal funding further reduced the funding gap between these groups to about 42 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 131 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XVIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XVIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Illinois districts. (Fig. XVIII.1 provides table information in graphic form.) Table XVIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Illinois education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Illinois’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Illinois appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XIX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Indiana averaged $5,248. The localities provided about 44 percent of total funding for education; the state provided about 52 percent; federal funds provided about 5 percent. Indiana’s state funding had the effect of providing districts with an additional $.78 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.19 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Indiana’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 43 percent to about 14 percent. The addition of federal funding further reduced the funding gap between these groups to about 7 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 110 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XIX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XIX.3 presents data on how local, state, and federal funds were distributed among the five groups of Indiana districts. (Fig. XIX.1 provides table information in graphic form.) Table XIX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Indiana education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Indiana’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Indiana appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Iowa averaged $5,051. The localities provided about 49 percent of total funding for education; the state provided about 47 percent; federal funds provided about 4 percent. Iowa’s state funding had the effect of providing districts with an additional $.91 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.27 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Iowa’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 34 percent to about 15 percent. The addition of federal funding further reduced the funding gap between these groups to about 11 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 92 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XX.3 presents data on how local, state, and federal funds were distributed among the five groups of Iowa districts. (Fig. XX.1 provides table information in graphic form.) Table XX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Iowa education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Iowa’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Iowa appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Kansas averaged $5,240. The localities provided about 54 percent of total funding for education; the state provided about 42 percent; federal funds provided about 5 percent. Kansas’ state funding had the effect of providing districts with an additional $.18 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.52 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Kansas’ targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 39 percent to about 10 percent. The addition of federal funding further reduced the funding gap between these groups to about 4 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 122 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXI.3 presents data on how local, state, and federal funds were distributed among the five groups of Kansas districts. (Fig. XXI.1 provides table information in graphic form.) Table XXI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Kansas education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Kansas’ school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Kansas appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Kentucky averaged $4,174. The localities provided about 27 percent of total funding for education; the state provided about 63 percent; federal funds provided about 11 percent. Kentucky’s state funding had the effect of providing districts with an additional $.59 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.87 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Kentucky’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 104 percent to about 6 percent. The addition of federal funding eliminated the funding gap between these groups to the extent that the lowest poverty group had about 3 percent less funding than the highest poverty group. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Kentucky, districts with the highest proportions of poor students made slightly less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 99 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXII.3 presents data on how local, state, and federal funds were distributed among the five groups of Kentucky districts. (Fig. XXII.1 provides table information in graphic form.) Table XXII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Kentucky education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Kentucky’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Kentucky appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Louisiana averaged $4,397. The localities provided about 34 percent of total funding for education; the state provided about 55 percent; federal funds provided about 11 percent. Louisiana’s state funding had the effect of providing districts with an additional $.14 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.70 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Louisiana’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 15 percent to about 11 percent. The addition of federal funding further reduced the funding gap between these groups to about 2 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 126 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Louisiana districts. (Fig. XXIII.1 provides table information in graphic form.) Table XXIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to this analysis. A Louisiana education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Louisiana’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Louisiana appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXIV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Maine averaged $6,017. The localities provided about 48 percent of total funding for education; the state provided about 47 percent; federal funds provided about 5 percent. Maine’s state funding had the effect of providing districts with an additional $.86 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.43 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Maine’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 31 percent to about 10 percent. The addition of federal funding further reduced the funding gap between these groups to about 4 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made slightly less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 99 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXIV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXIV.3 presents data on how local, state, and federal funds were distributed among the five groups of Maine districts. (Fig. XXIV.1 provides table information in graphic form.) Table XXIV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to this analysis. A Maine education official reported that the state had targeted less funding to high-poverty districts since school year 1991-92. More information on changes in Maine’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Maine appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Maryland averaged $6,349. The localities provided about 57 percent of total funding for education; the state provided about 38 percent; federal funds provided about 5 percent. Maryland’s state funding had the effect of providing districts with an additional $.04 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.38 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Maryland’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 262 percent to about 80 percent. The addition of federal funding further reduced the funding gap between these groups to about 63 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 65 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXV.3 presents data on how local, state, and federal funds were distributed among the five groups of Maryland districts. (Fig. XXV.1 provides table information in graphic form.) Table XXV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Maryland education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Maryland’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Maryland appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXVI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Massachusetts averaged $6,601. The localities provided about 66 percent of total funding for education; the state provided about 29 percent; federal funds provided about 5 percent. Massachusetts’s state funding had the effect of providing districts with an additional $2.98 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $3.60 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Massachusetts’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 99 percent to about 25 percent. The addition of federal funding further reduced the funding gap between these groups to about 14 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 88 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXVI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXVI.3 presents data on how local, state, and federal funds were distributed among the five groups of Massachusetts districts. (Fig. XXVI.1 provides table information in graphic form.) Table XXVI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Massachusetts education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Massachusetts’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Massachusetts appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXVII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Michigan averaged $6,110. The localities provided about 64 percent of total funding for education; the state provided about 32 percent; federal funds provided about 4 percent. Michigan’s state funding had the effect of providing districts with an additional $2.71 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $3.11 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Michigan’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 193 percent to about 37 percent. The addition of federal funding further reduced the funding gap between these groups to about 26 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 82 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXVII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXVII.3 presents data on how local, state, and federal funds were distributed among the five groups of Michigan districts. (Fig. XXVII.1 provides table information in graphic form.) Table XXVII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Michigan education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Michigan’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Michigan appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXVIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Minnesota averaged $5,872. The localities provided about 45 percent of total funding for education; the state provided about 51 percent; federal funds provided about 4 percent. Minnesota’s state funding had the effect of providing districts with an additional $.96 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.25 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Minnesota’s targeting efforts and state share of total funding more than eliminated the 25-percent local funding gap between the lowest and highest poverty groups. Consequently, the lowest poverty group had about 5 percent less funding than the highest poverty group. The low-poverty group had about 9 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Minnesota, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 111 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXVIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXVIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Minnesota districts. (Fig. XXVIII.1 provides table information in graphic form.) Table XXVIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Minnesota education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Minnesota’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Minnesota appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXIX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Mississippi averaged $3,386. The localities provided about 30 percent of total funding for education; the state provided about 54 percent; federal funds provided about 16 percent. Mississippi’s state funding had the effect of providing districts with an additional $.22 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.03 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Mississippi’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 34 percent to about 18 percent. The addition of federal funding further reduced the funding gap between these groups to about 1 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 126 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXIX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXIX.3 presents data on how local, state, and federal funds were distributed among the five groups of Mississippi districts. (Fig. XXIX.1 provides table information in graphic form.) Table XXIX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Mississippi education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Mississippi’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Mississippi appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Missouri averaged $4,272. The localities provided about 52 percent of total funding for education; the state provided about 41 percent; federal funds provided about 7 percent. Missouri’s state funding had the effect of providing districts with an additional $5.97 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $7.41 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Missouri’s targeting efforts and state share of total funding more than eliminated the 44-percent local funding gap between the lowest and highest poverty groups. Consequently, the lowest poverty group had about 7 percent less funding than the highest poverty group. The lowest poverty group had about 14 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Missouri, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 137 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXX.3 presents data on how local, state, and federal funds were distributed among the five groups of Missouri districts. (Fig. XXX.1 provides table information in graphic form.) Table XXX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Missouri education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Missouri’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Missouri appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Montana averaged $5,260. The localities provided about 54 percent of total funding for education; the state provided about 41 percent; federal funds provided about 5 percent. Montana’s state funding had the effect of providing districts with no additional funding per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.54 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) State funding in Montana had no effect on the 13-percent local funding gap between the lowest and highest poverty groups. The addition of federal funding reduced the funding gap between these groups to about 8 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 155 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXI.3 presents data on how local, state, and federal funds were distributed among the five groups of Montana districts. (Fig. XXXI.1 provides table information in graphic form.) Table XXXI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Montana education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Montana’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Montana appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Nebraska averaged $5,448. The localities provided about 63 percent of total funding for education; the state provided about 33 percent; federal funds provided about 4 percent. Nebraska’s state funding had the effect of providing districts with an additional $.39 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.70 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Nebraska’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 8 percent to about 7 percent. The addition of federal funding further reduced the funding gap between these groups to about 3 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made slightly less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 99 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXII.3 presents data on how local, state, and federal funds were distributed among the five groups of Nebraska districts. (Fig. XXXII.1 provides table information in graphic form.) Table XXXII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Nebraska education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Nebraska’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Nebraska appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Nevada averaged $3,810. The localities provided about 41 percent of total funding for education; the state provided about 54 percent; federal funds provided about 5 percent. Nevada’s state funding had the effect of providing districts with no additional funding per poor student for every $1 provided to each student. The addition of federal funding had no effect on the amount of additional funding per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) State funding in Nevada more than eliminated the 43-percent local funding gap between the lowest and highest poverty groups. Consequently, the lowest poverty group had about 13 percent less funding than the highest poverty group. The lowest poverty group had about 14 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 104 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXIII.2 presents demographic data for school year 1991-92 for four groups of districts with increasing proportions of poor students. Table XXXIII.3 presents data on how local, state, and federal funds were distributed among the four groups of Nevada districts. (Fig. XXXIII.1 provides table information in graphic form.) Poverty rate (percent) Percent difference (group 1 compared with group 4) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Nevada education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Nevada’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Nevada appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXIV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in New Hampshire averaged $6,028. The localities provided about 89 percent of total funding for education; the state provided about 8 percent; federal funds provided about 3 percent. New Hampshire’s state funding had the effect of providing districts with an additional $6.69 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $5.50 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) New Hampshire’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 49 percent to about 35 percent. The addition of federal funding further reduced the funding gap between these groups to about 32 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made a slightly greater effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 101 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXIV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXIV.3 presents data on how local, state, and federal funds were distributed among the five groups of New Hampshire districts. (Fig. XXXIV.1 provides table information in graphic form.) Table XXXIV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A New Hampshire education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in New Hampshire’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about New Hampshire appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in New Jersey averaged $9,605. The localities provided about 55 percent of total funding for education; the state provided about 41 percent; federal funds provided about 4 percent. New Jersey’s state funding had the effect of providing districts with an additional $3.45 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $4.03 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) New Jersey’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 194 percent to about 22 percent. The addition of federal funding further reduced the funding gap between these groups to about 13 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 116 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXV.3 presents data on how local, state, and federal funds were distributed among the five groups of New Jersey districts. (Fig. XXXV.1 provides table information in graphic form.) Table XXXV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A New Jersey education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in New Jersey’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about New Jersey appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXVI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in New Mexico averaged $4,353. The localities provided about 15 percent of total funding for education; the state provided about 75 percent; federal funds provided about 10 percent. New Mexico’s state funding had the effect of providing districts no additional funding per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.28 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) State funding in New Mexico increased the local funding gap between the lowest and highest poverty groups from about 1 percent to about 9 percent. The addition of federal funding reduced the funding gap between these groups to about 2 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 333 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXVI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXVI.3 presents data on how local, state, and federal funds were distributed among the five groups of New Mexico districts. (Fig. XXXVI.1 provides table information in graphic form.) Table XXXVI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A New Mexico education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in New Mexico’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about New Mexico appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXVII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in New York averaged $8,233. The localities provided about 54 percent of total funding for education; the state provided about 40 percent; federal funds provided about 5 percent. New York’s state funding had the effect of providing districts with no additional funding per poor student for every $1 provided to each student. The addition of federal funding had no effect on the amount of additional funding per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) State funding in New York reduced the local funding gap between the lowest and highest poverty groups from about 213 percent to about 44 percent. The addition of federal funding further reduced the funding gap between these groups to about 34 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 72 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXVII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXVII.3 presents data on how local, state, and federal funds were distributed among the five groups of New York districts. (Fig. XXXVII.1 provides table information in graphic form.) Table XXXVII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A New York education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in New York’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about New York appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXVIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in North Carolina averaged $4,780. The localities provided about 30 percent of total funding for education; the state provided about 63 percent; federal funds provided about 7 percent. North Carolina’s state funding had the effect of providing districts with an additional $.53 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.05 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) North Carolina’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 81 percent to about 16 percent. The addition of federal funding further reduced the funding gap between these groups to about 7 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 93 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXVIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXVIII.3 presents data on how local, state, and federal funds were distributed among the five groups of North Carolina districts. (Fig. XXXVIII.1 provides table information in graphic form.) Table XXXVIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A North Carolina education official reported that the state targeted more funding to high-poverty districts as of school year 1996-97. More information on changes in North Carolina’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about North Carolina appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XXXIX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in North Dakota averaged $4,467. The localities provided about 48 percent of total funding for education; the state provided about 44 percent; federal funds provided about 8 percent. North Dakota’s state funding had the effect of providing districts with an additional $.78 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $2.53 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) North Dakota’s targeting efforts and state share of total funding more than eliminated the 2-percent local funding gap between the lowest and highest poverty groups. Consequently, the lowest poverty group had about 5 percent less funding than the highest poverty group. The lowest poverty group had about 12 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In North Dakota, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 153 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XXXIX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XXXIX.3 presents data on how local, state, and federal funds were distributed among the five groups of North Dakota districts. (Fig. XXXIX.1 provides table information in graphic form.) Table XXXIX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A North Dakota education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in North Dakota’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about North Dakota appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XL.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Ohio averaged $4,984. The localities provided about 55 percent of total funding for education; the state provided about 40 percent; federal funds provided about 5 percent. Ohio’s state funding had the effect of providing districts with an additional $1.48 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $2.19 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Ohio’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 96 percent to about 27 percent. The addition of federal funding further reduced the funding gap between these groups to about 15 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 98 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XL.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XL.3 presents data on how local, state, and federal funds were distributed among the five groups of Ohio districts. (Fig. XL.1 provides table information in graphic form.) Table XL.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Ohio education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Ohio’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Ohio appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Oklahoma averaged $3,929. The localities provided about 28 percent of total funding for education; the state provided about 66 percent; federal funds provided about 7 percent. Oklahoma’s state funding had the effect of providing districts with an additional $.76 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.09 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Oklahoma’s targeting efforts and state share of total funding more than eliminated the 19-percent local funding gap between the lowest and highest poverty groups. Consequently, the lowest poverty group had about 2 percent less funding than the highest poverty group. The lowest poverty group had about 8 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Oklahoma, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 112 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLI.3 presents data on how local, state, and federal funds were distributed among the five groups of Oklahoma districts. (Fig. XLI.1 provides table information in graphic form.) Table XLI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Oklahoma education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Oklahoma’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Oklahoma appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Oregon averaged $5,411. The localities provided about 65 percent of total funding for education; the state provided about 29 percent; federal funds provided about 6 percent. Oregon’s state funding had the effect of providing districts with an additional $1.57 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $2.32 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Oregon’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 43 percent to about 17 percent. The addition of federal funding further reduced the funding gap between these groups to about 12 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 119 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLII.3 presents data on how local, state, and federal funds were distributed among the five groups of Oregon districts. (Fig. XLII.1 provides table information in graphic form.) Table XLII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. An Oregon education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Oregon’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Oregon appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Pennsylvania averaged $6,709. The localities provided 54.5 percent of total funding for education; the state provided 41 percent; federal funds provided 4.5 percent. Pennsylvania’s state funding had the effect of providing districts with an additional $1.31 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.89 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Pennsylvania’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 110 percent to about 32 percent. The addition of federal funding further reduced the funding gap between these groups to about 20 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 86 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Pennsylvania districts. (Fig. XLIII.1 provides table information in graphic form.) Table XLIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Pennsylvania education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Pennsylvania’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Pennsylvania appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLIV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Rhode Island averaged $6,244. The localities provided about 58 percent of total funding for education; the state provided about 37 percent; federal funds provided about 4 percent. Rhode Island’s state funding had the effect of providing districts with an additional $.23 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.42 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Rhode Island’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 87 percent to about 28 percent. The addition of federal funding further reduced the funding gap between these groups to about 21 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 84 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLIV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLIV.3 presents data on how local, state, and federal funds were distributed among the five groups of Rhode Island districts. (Fig. XLIV.1 provides table information in graphic form.) Table XLIV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Rhode Island education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Rhode Island’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Rhode Island appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLV.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in South Carolina averaged $4,509. The localities provided about 44 percent of total funding for education; the state provided about 48 percent; federal funds provided about 9 percent. South Carolina’s state funding had the effect of providing districts with an additional $.21 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.66 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) South Carolina’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 52 percent to about 17 percent. The addition of federal funding further reduced the funding gap between these groups to about 6 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 106 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLV.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLV.3 presents data on how local, state, and federal funds were distributed among the five groups of South Carolina districts. (Fig. XLV.1 provides table information in graphic form.) Table XLV.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A South Carolina education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in South Carolina’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about South Carolina appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLVI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in South Dakota averaged $4,217. The localities provided about 66 percent of total funding for education; the state provided about 26 percent; federal funds provided about 8 percent. South Dakota’s state funding had the effect of providing districts with an additional $1.30 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $2.51 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) South Dakota’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 28 percent to about 9 percent. The addition of federal funding further reduced the funding gap between these groups to about 1 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 140 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLVI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLVI.3 presents data on how local, state, and federal funds were distributed among the five groups of South Dakota districts. (Fig. XLVI.1 provides table information in graphic form.) Table XLVI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A South Dakota education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in South Dakota’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about South Dakota appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLVII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Tennessee averaged $3,699. The localities provided about 48 percent of total funding for education; the state provided about 42 percent; federal funds provided about 10 percent. Tennessee’s state funding had the effect of providing districts with an additional $.31 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.16 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Tennessee’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 5 percent to about 3 percent. The addition of federal funding eliminated the funding gap between these groups, resulting in the lowest poverty group having about 7 percent less funding than the highest poverty group. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Tennessee, districts with the highest proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 125 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLVII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLVII.3 presents data on how local, state, and federal funds were distributed among the five groups of Tennessee districts. (Fig. XLVII.1 provides table information in graphic form.) Table XLVII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Tennessee education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Tennessee’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Tennessee appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLVIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Texas averaged $4,946. The localities provided about 49 percent of total funding for education; the state provided about 44 percent; federal funds provided about 7 percent. Texas’ state funding had the effect of providing districts with an additional $.39 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.58 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.). Texas’ targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 140 percent to about 11 percent. The addition of federal funding further reduced the funding gap between these groups to about 1 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 115 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLVIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLVIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Texas districts. (Fig. XLVIII.1 provides table information in graphic form.) Table XLVIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Texas education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Texas’ school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Texas appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table XLIX.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Utah averaged $3,408. The localities provided about 38 percent of total funding for education; the state provided about 56 percent; federal funds provided about 6 percent. Utah’s state funding had the effect of providing districts with an additional $.02 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.59 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) The lowest poverty group in Utah had about 29 percent less local funding than the highest poverty group. State funding reduced this funding gap to about 8 percent. The lowest poverty group had about 11 percent less funding after the addition of federal funding. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 123 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table XLIX.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table XLIX.3 presents data on how local, state, and federal funds were distributed among the five groups of Utah districts. (Fig. XLIX.1 provides table information in graphic form.) Table XLIX.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Utah education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Utah’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Utah appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table L.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Virginia averaged $5,021. The localities provided about 61 percent of total funding for education; the state provided about 34 percent; federal funds provided about 5 percent. Virginia’s state funding had the effect of providing districts with an additional $.93 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.29 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Virginia’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 98 percent to about 30 percent. The addition of federal funding further reduced the funding gap between these groups to about 20 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) The size of the local funding gap is partly determined by differences in districts’ local tax efforts. In Virginia, districts with the highest proportions of poor students made less effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 91 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table L.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table L.3 presents data on how local, state, and federal funds were distributed among the five groups of Virginia districts. (Fig. L.1 provides table information in graphic form.) Table L.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Virginia education official reported that the state had targeted much more funding to high-poverty districts since school year 1991-92. More information on changes in Virginia’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Virginia appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table LI.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Washington averaged $5,604. The localities provided about 24 percent of total funding for education; the state provided about 71 percent; federal funds provided about 5 percent. Washington’s state funding had the effect of providing districts with an additional $.70 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.11 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Washington’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 46 percent to about 7 percent. The addition of federal funding further reduced the funding gap between these groups to about 1 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 123 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table LI.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table LI.3 presents data on how local, state, and federal funds were distributed among the five groups of Washington districts. (Fig. LI.1 provides table information in graphic form.) Table LI.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Washington education official reported that the state had targeted more funding to high-poverty districts since school year 1991-92. More information on changes in Washington’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Washington appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table LII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in West Virginia averaged $5,332. The localities provided about 25 percent of total funding for education; the state provided about 67 percent; federal funds provided about 8 percent. West Virginia’s state funding had the effect of providing districts with an additional $.09 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $.27 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) West Virginia’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 68 percent to about 13 percent. The addition of federal funding further reduced the funding gap between these groups to about 9 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 114 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table LII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table LII.3 presents data on how local, state, and federal funds were distributed among the five groups of West Virginia districts. (Fig. LII.1 provides table information in graphic form.) Table LII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A West Virginia education official reported that the state had not targeted more funding to high-poverty districts since school year 1991-92. More information on changes in West Virginia’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about West Virginia appears in appendixes III and IV. Average total funding per weighted pupil Targeting to poor students (added amount allocated per poor student for every dollar allocated for each student) Total funding weight (effect of combined state and federal funding) As table LIII.1 shows, in school year 1991-92, total funding (local, state, and federal funding combined) per weighted pupil in Wisconsin averaged $6,124. The localities provided about 52 percent of total funding for education; the state provided about 44 percent; federal funds provided about 4 percent. Wisconsin’s state funding had the effect of providing districts with an additional $1.20 per poor student for every $1 provided to each student. When federal funding was added to the state funding, the combined effect provided an additional $1.55 per poor student. (To compare these amounts with those of other states, see table III.6 in app. III.) Wisconsin’s targeting efforts and state share of total funding reduced the local funding gap between the lowest and highest poverty groups from about 75 percent to about 17 percent. The addition of federal funding further reduced the funding gap between these groups to about 11 percent. (To compare the total funding gap with those of other states, see table V.2 in app. V. For the funding gap results using a regression analysis, see table V.1.) proportions of poor students made more effort to raise local revenue than districts with the lowest proportions of poor students. Specifically, districts in the highest poverty group made a tax effort that was 102 percent of that made in districts in the lowest poverty group. To put the state’s school finance system in perspective, table LIII.2 presents demographic data for school year 1991-92 for five groups of districts with increasing proportions of poor students. Table LIII.3 presents data on how local, state, and federal funds were distributed among the five groups of Wisconsin districts. (Fig. LIII.1 provides table information in graphic form.) Table LIII.2: Demographic Information for Districts of Increasing Proportions of Poor Students, School Year 1991-92 Local funding raised for every $1,000 of district income. Percent difference (group 1 compared with group 5) Federal impact aid is considered part of local funding. Not applicable to our analysis. A Wisconsin education official reported that the state had targeted less funding to high-poverty districts since school year 1991-92. More information on changes in Wisconsin’s school finance system made between 1991-92 and 1995-96 and such changes in other states appears in table LIV.1. Information on changes in federal funding between 1991-92 and 1994-95 appears in table LV.1. Additional technical information about Wisconsin appears in appendixes III and IV. In this report, we relied on funding data from the 1991-92 school year. However, many states have subsequently changed their school finance systems in response to legal challenges or to equity concerns. We telephoned officials in the 47 states to determine what changes had taken place in the school finance systems from school years 1991-92 through 1995-96. We specifically asked about changes in targeting that would affect districts with high proportions of poor students and changes in a state’s share of education funding. These two factors affect the size of the funding gap between low- and high-poverty districts—in general, the greater the targeting to high-poverty districts or the greater the state share, or both, the lower the funding gap. We did not verify the state officials’ statements. Relatively few states reported increased targeting to high-poverty districts. Education officials in 19 states reported not targeting high-poverty districts at all, 10 states reported no change in targeting to high-poverty districts, and 2 states reported changes that would result in high-poverty districts receiving less state funding. The remaining 16 states reported making changes that would provide more funds to high-poverty districts. Fewer states had increased the state share of total funding significantly. Officials in 36 states reported that their state’s share had a net increase or decrease of 5 percentage points or less, and 3 states reported a decrease of 6 percentage points or more. Officials in the remaining eight states reported an increase in the state share of 6 percentage points or more. Table LIV.1 summarizes our findings of the changes states have made. Change in state share (percentage points) Did not specifically target high-poverty districts in either school year (continued) Did not specifically target high-poverty districts in either school year (continued) Change in state share (percentage points) Change as of school year 1993-94. Change as of school year 1994-95. In this report, we relied on state, local, and federal funding data from the 1991-92 school year. Federal regulations or legislation since 1991-92, however, may have changed targeting to districts. We telephoned officials in the Departments of Education, Agriculture, Health and Human Services, and the Interior and reviewed relevant documents to determine what regulatory or legislative changes, if any, to the major federally funded elementary and secondary schools programs may have resulted in more or less federal funds being targeted to poor students. The federal government targeted more funding to poor students in the 1995-96 school year than in the 1991-92 school year, according to federal officials, due to changes in title I legislation and regulations. Title I, the largest federal education program, provides funding for disadvantaged students. Changes effective as of July 1995 were expected to provide more title I funding to high-poverty districts through increased targeting. In addition, other federal education programs allocate funds on the basis of title I formulas. For example, vocational education grants are partially based on title I funding formulas. Consequently, vocational education funding has also increased in high-poverty districts. Federal government programs supporting children with disabilities under the Individuals With Disabilities Education Act made changes in 1997 that are expected to result in targeting more funding to poor students. Funding patterns remained relatively unchanged in many other federal programs. Federal officials for the Head Start, bilingual education, Indian education, and child nutrition programs cited no regulatory or legislative changes since 1991-92 that would affect targeting to poor students. Table LV.I summarizes the federal funding provided to the states in school years 1991-92 and 1994-95. These figures include impact aid as part of the totals (we excluded federal impact aid in our analysis of federal targeting). The federal percentages in the table are based on total funding amounts from public sources (private funding is excluded from total funding). Total federal funding (thousands) Total federal funding (thousands) (continued) Total federal funding (thousands) In addition to those named above, the following individuals made important contributions to this report: Jerry Fastrup (202-512-7211) conceived the model for determining the poor student cost weights and helped write the report; Barbara A. Billinghurst (206-287-4867) helped develop and apply the model and write the report; Nancy Purvine and Virginia Vanderlinde contacted state officials about changes in funding patterns; and Alicia Moos researched changes in federal funding patterns. The first copy of each GAO report and testimony is free. Additional copies are $2 each. Orders should be sent to the following address, accompanied by a check or money order made out to the Superintendent of Documents, when necessary. VISA and MasterCard credit cards are accepted, also. Orders for 100 or more copies to be mailed to a single address are discounted 25 percent. 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Summary: Pursuant to a congressional request, GAO reviewed state and federal efforts to target poor students and the funding gaps between districts with high and low proportions of poor students, focusing on: (1) the extent to which state and federal funding is targeted to districts on the basis of the number of poor students; and (2) the effect of state and federal funding on the amount of funds available to high-poverty compared with low-poverty districts. GAO noted that: (1) school finance systems in over 90 percent of the states had the effect targeting more state funds to districts with large numbers of poor students in school year 1991-92, regardless of whether the system explicitly intended to do so; (2) the extent of the targeting varied widely, however; (3) New Hampshire targeted poor students the most, providing an additional $6.69 per poor student for every $1 provided to each student; school finance systems in four states (Montana, Nevada, New Mexico, and New York) had the effect of targeting no additional funding per poor student; (4) the national average was $.62 in additional state funding; (5) federal funding was more targeted than state funding, providing an average of $4.73 in additional federal funding per poor student nationwide for every $1 provided for each student; (6) because federal funds were more targeted than state funds, the combination of federal and state funding increased the average additional funding per poor student from $.62 to $1.10 nationwide for every $1 provided for each student; (7) reported changes in federal education programs and state school finance systems since school year 1991-92 would probably result in federal funds being more targeted than state funds; (8) state and federal funding reduced but did not eliminate the local funding gap between high- and low-poverty districts in many states; (9) high-poverty districts had less local funding per weighted pupil in 37 of the 47 states GAO analyzed; (10) when GAO added state and federal funds to local funds for GAO's analysis, only 21 states still had such funding gaps, and these gaps were smaller in each state; (11) nevertheless, about 64 percent of the nation's poor students live in these 21 states; (12) nationwide, total funding levels in low-poverty districts were about 15 percent more than those in high-poverty districts; (13) although targeting helped close the funding gap, the percentage of total funding from state and federal sources was more important in reducing the gap; and (14) gaps were smaller in states whose combined state and federal share of total funding was relatively high.