Until the 1800s, America’s schools were mainly private local entities. In the mid-1800s, several states rewrote their constitutions to create statewide public education systems and establish government responsibility for financing schools. Today, all states have constitutional provisions on free public education, and, based in part on these provisions, a number of state courts have ruled that education is a fundamental right subject to equal protection under the law. The largest single federal elementary and secondary education grant program is title I of the Elementary and Secondary Education Act. The program, which began in 1965, continues to focus on providing compensatory services to educationally disadvantaged children through categorical, program-specific grants. The fiscal year 1997 appropriations for title I compensatory education for the disadvantaged was $7.7 billion. Federal aid, however, only provides about 7 percent of the funding for elementary and secondary education. Nationwide, the other 93 percent is about evenly split between state and local funding, although the state share of total (state and local) funding for education varies by state. Although states have increased their control over schools, state contributions in the 1991-92 school year varied from 8 percent of total funding in New Hampshire to 85 percent of total funding in New Mexico. States’ ability to fund education also varies. States with higher income levels can provide more funding for their students. In the 1991-92 school year, states’ average income per weighted pupil ranged from $41,385 in Utah to $160,761 in New Jersey. States also vary in the number of students with additional educational needs, such as poor or disabled students, who tend to have education costs higher than average. For example, the student poverty rate among states in 1989 ranged from about 33 percent in Mississippi to under 8 percent in New Hampshire. In addition, localities’ ability to raise revenues varies widely. Localities raise revenues primarily through property taxes and, to a lesser extent, through local sales and income taxes. However, a heavy reliance on local property taxes as a major source of school revenue has produced funding disparities because school districts’ property tax bases vary widely. Localities with low property values usually have low funding per pupil even with high tax rates; localities with high property values have high funding per pupil even with low tax rates. Since the late 1960s, the funding gaps arising from the continued reliance on local tax revenues have led to litigation challenging the constitutionality of state school finance systems, with varying results. Researchers concerned about the equity of school finance systems—that is, the distribution of education funding—have focused on two important definitions of equity: vertical equity and fiscal neutrality. Vertical equity recognizes that legitimate differences occur among children and that some students, such as those who are disabled, have low academic achievement, or limited English proficiency, need additional educational services. After adjusting the pupil count to give greater weight to those pupils who need extra educational services and adjusting the funding for cost differences in educational resources, some experts would argue that funding per weighted pupil should be nearly equal among districts. Fiscal neutrality asserts that no relationship should exist between educational spending per pupil and local district property wealth per pupil (or some other measure of fiscal capacity). That is, the quality of education should be a function only of the entire state’s wealth, not of a locality’s. Unlike vertical equity, which calls for nearly equal funding per weighted pupil among districts after adjustments have been made, fiscal neutrality allows for differences in funding as long as they are not related to the districts’ taxable wealth. In addition to equity, researchers are also concerned about the adequacy of educational resources. Education funding is termed adequate if it enables each student to achieve some minimum level of academic performance. Not much is known, however, about the level of funding needed to achieve a certain level of performance. As a result, determining an adequate level of funding for a district is difficult. In response to legal and political pressures, states have sought to equalize—that is, compensate for the differences in—districts’ abilities to raise revenue for funding education. In general, states have used one or both of the following equalization strategies: added new state or local money to the school finance system to increase funding for poor districts or redistributed the available funding to poor districts by modifying school finance formulas. Redistributing education revenues may also include recapturing the local revenues raised above an established level in wealthy districts and giving them to poor districts. One of the more common funding formulas used to equalize the ability of districts to raise education revenues is the foundation program. A foundation program sets an expenditure per pupil—the minimum foundation—at a level that would provide at least a minimum-quality education for every pupil. Usually, districts must put forth a minimum local tax effort to receive state aid, which makes up the difference between what localities raise by the required local tax effort and the foundation amount. This funding formula results in states targeting more state education funds, on a per pupil basis, to those districts with low tax bases than to those with high tax bases. Despite the seeming simplicity of this funding formula, equalizing school finance systems is a complex and difficult undertaking. In a recent report, we reviewed the experiences of three states that had used one or both of the equalization strategies noted above. Although these states reported reduced funding gaps, their legislative solutions reflected citizens’ concerns about increased taxes to raise more state revenues and concerns of wealthy districts that wanted to maintain existing spending levels. Although most states pursued strategies to supplement the local funding in their poorest districts, the strategies generally did not offset the advantage of wealthy districts in raising local funds. These results occurred even after adjusting for the geographic differences in education costs and student needs within each state. In most states, the total funding per weighted pupil in districts was still largely determined by districts’ income per weighted pupil. In other words, these states had not achieved an income-based fiscal neutrality in their school finance system. On average, wealthy districts had about 24 percent more total funding per weighted pupil than poor districts. Figure 1 ranks states according to the extent to which total funding of school districts in school year 1991-92 was linked to district income. In this figure, the center line, which equals a fiscal neutrality score of 0, represents the goal of ensuring that education funding is unrelated to differences in district income per weighted pupil. The figure shows that the total funding of districts in 37 states favored wealthier districts; that is, the total funding increased as the income of the district increased. In three states the opposite occurred—the total funding decreased as district income increased. Among the 37 states whose school funding favored wealthier districts, the amount of funding available as district income increased varied widely. At the high end of the 37 states, students in Maryland had about $25 more in total funding for a $1,000 increase in income per weighted pupil above the state average. At the low end, students in Washington had only about $4 more for a $1,000 increase in income per weighted pupil above the state average. Three key factors affected the size of the funding gap between poor and wealthy districts. Two of these—targeting of state funds to poor districts and the state’s share of overall education funding—represent states’ school equalization policies. The third factor—the relative local tax effortof poor districts to wealthy districts—stems mainly from choices made at the local level. In general, increases in any one of these decreases the funding gap between poor and wealthy districts. Nationwide, the three factors accounted for 61 percent of the variation in the income-related funding gap. Of the three factors, targeting was the least important in explaining the variation in funding gaps between wealthy and poor districts. The state’s share of total funding accounted for more of the variation in the income-related funding gap than targeting. The relative local tax effort of poor districts to wealthy districts accounted for most of the variation (see app. III). State targeting efforts typically helped to reduce but did not eliminate the gap in total funding between wealthy and poor districts. These results occurred even after adjusting for geographic differences in education costs and student need. For example, Connecticut’s wealthy districts had over three times the amount of local funding as its poor districts in school year 1991-92 (see table 1). In contrast, the state funding was over three times higher in poor districts compared with wealthy districts; the wealthy districts still had, however, about 34 percent more total funding per weighted pupil than the poor districts. In Connecticut, the gap in total funding between the poor and wealthy districts was $2,559. Appendix III provides similar data for all states. Like Connecticut, most states (33 of 49) targeted more state funds to poor districts to some degree on the basis of district income. Of the remaining 16 states, 14 provided approximately equal state funding to poor and wealthy districts. Two states—Louisiana and North Dakota—provided more state funding to wealthy districts than to poor districts. Among the states that targeted more funds to poor districts, the additional amount of state funding varied widely. For example, for a $1,000 decrease in district income below the state average, Nevada provided about $42 more in state funding per weighted pupil; Indiana provided about $6 more in state funding per weighted pupil. Appendix V provides information on all the states’ targeting efforts. A high state share of total education funding offsets income-related funding gaps, even if the targeting effort is low. For example, Washington had virtually no targeting effort but funded about 75 percent of the total funding for education. The poorest districts in Washington had only 4 percent less ($229) to spend per weighted pupil than the wealthiest districts. In contrast, Michigan had a relatively high targeting effort but funded only about 33 percent of the total education funding in the state, which was relatively low. As a result, the poorest districts in Michigan had 36 percent ($1,923) less to spend per weighted pupil than the wealthiest districts (see figs. 2 and 3). Appendix V provides information on the state share for all states. The willingness of poor districts to tax themselves at a higher rate than wealthy districts helped reduce the funding gap between poor and wealthy districts. In 35 states, poor districts made a higher tax effort than wealthy districts. The tax effort is defined as the ratio of district local funding to district income. Poor districts must make a higher level of tax effort to finance comparable education programs because the same tax effort generates less revenue in poor districts than in wealthy districts. For example, Kansas and Pennsylvania each targeted additional funds to poor districts to about the same extent and funded about the same share of total education funding. Kansas’ poor districts, however, taxed themselves about 24 percent more than the state’s wealthy districts, while Pennsylvania’s poor districts had about the same tax effort as its wealthy districts. As a result, the gap in total funding between poor and wealthy districts was smaller in Kansas than in Pennsylvania (see fig. 1). To determine the effects of state school finance policies on the funding gap between poor and wealthy districts, we analyzed states’ school finance data. We developed a new equity measure, implicit foundation level, which indicates the extent to which these policies enable districts to finance a minimum quality education for each student with an equal tax effort. Then we compared this level to the state average to determine states’ equalization efforts. This section describes how we developed these two measures. We determined the combined effects of state equalization policies (targeting and state share), while excluding the effects of local tax effort. To accomplish this, we viewed each state as if it were distributing state funds according to a foundation program. In such a program, the state ensures all districts the ability to finance a foundation or a minimum amount of funding per pupil, provided that the districts make a minimum local tax effort. Using a foundation funding model and assuming all districts made an equal local tax effort, we estimated the implicit foundation level that each state’s equalization policies in school year 1991-92 could have supported. This implicit foundation level is an estimate of the minimum amount of total funding that states’ districts could spend per student if districts were to make an equal minimum local tax effort.This new measure, for the first time, allows analysts to examine the extent to which the funding gap between poor and wealthy districts is due to state equalization policies (state share and state targeting) and the extent to which it is due to local policies (relative differences in local tax efforts). Appendix IV explains how we developed the implicit foundation level. Figure 4 illustrates the implicit foundation level using a hypothetical example of two districts in a state, one poor and one wealthy. For each district, we graphed how much total funding per weighted pupil is associated with a given level of tax effort. Since poor districts generally receive more state funding per weighted pupil than wealthy districts, in this example we assigned the poor district $2,500 in state funding per weighted pupil, twice the amount the wealthy district was assigned. Therefore, the line for the poor district starts out higher (the district has more state money) on the graph than the line for the wealthy district (which has less state money). As figure 4 shows, as both districts increase their local tax effort, the wealthy district raises more local revenue than the poor district for a given level of tax effort. For any given tax effort past a certain point (where the lines cross on fig. 4), the wealthy district’s local revenue more than offsets the additional state money that poor districts receive—therefore, the total funding in wealthy districts exceeds total funding in poor districts. The point at which the total funding lines cross is the implicit foundation level and is the only point at which the two districts have the same amount of total funding for the same tax effort. We compared states’ implicit foundation levels with the maximum foundation levels that would be possible given each state’s amount of total funding devoted to education. We call this ratio a state’s equalization effort. State average funding per weighted pupil is actually the maximum foundation level (see app. IV for a mathematical explanation of this). A state’s equalization effort is a measure of the extent to which districts in a state can finance the state average with an average tax effort. To achieve the maximum foundation level without changing the total funding for education, a state could increase its effort to target funds to poor districts or increase the state’s share of education funding or both. States’ implicit foundation levels varied widely, averaging $3,134 per weighted pupil, with levels ranging as low as $721 in New Hampshire to as high as $5,415 in Alaska in school year 1991-92. In line with the purpose of foundation programs, these implicit levels indicate the extent to which states’ school finance policies ensure a level of funding assumed adequate for districts to finance at least a minimum quality education for every student with an equal local tax effort. Appendix V provides information on the implicit foundation levels in each state. States’ equalization efforts also varied. Only one state—Nevada—made the maximum equalization effort given the total funding available for education in the state. As a result, Nevada’s state school policies in school year 1991-92 enabled each district to spend the state average on each student with an average tax effort. The implicit foundation levels in the other 48 states were less than their state averages, with equalization efforts ranging from about 87 percent (Arkansas and Kentucky) to about 13 percent (New Hampshire). In 14 states, the implicit foundation level was less than half the state average. Figure 5 summarizes the states’ equalization efforts in school year 1991-92. State equalization efforts, representing the combined effects of state targeting and state share, have an important effect on reducing the funding gap between poor and wealthy districts. When we controlled for the differences in the tax effort of wealthy and poor districts in each state, we found that states with higher equalization efforts tended to have smaller funding gaps between poor and wealthy districts, as measured by their fiscal neutrality scores (see app. V). However, differences in the tax effort of wealthy and poor districts still accounted for more of the variation in income-related funding gaps than did states’ equalization efforts. That is, states’ finance policies, as measured by their equalization efforts, helped to reduce the funding gap between poor and wealthy districts, but differences in the tax effort of these districts continued to be the more important determinant of the funding gap. For example, Maryland had an above average equalization effort (about 63 percent), yet it also had the largest income-related funding gap (see fig. 1). This large gap can be explained in part by the relative local tax effort: wealthy districts in Maryland made a tax effort that was about 53 percent higher than the tax effort of poor districts, the highest such ratio in the nation. Thus, despite Maryland’s substantial efforts to equalize funding, the effort did not overcome the differences in local funding by district that were due, in part, to the relatively high tax effort of wealthy districts (see app. III). To further reduce the funding gap between poor and wealthy districts, states would need to increase their equalization effort by either increasing their share of total funding, increasing their targeting effort to poor districts, or increasing both. To illustrate the extent of the change that would be needed to maximize a state’s equalization effort without any increase in state funding, we analyzed state targeting in school year 1991-92, while holding the state share constant and assuming all districts made an equal tax effort. Under this scenario, 48 states would have had to reduce their funding of wealthy districts to increase their funding of poor or middle-income districts or both. In many states, the magnitude of the targeting change would have had to be significant to enable districts to spend the state average with an average tax effort. Relative to the distribution needed to attain the state average for all students, 29 states would have had to significantly shift their funding from wealthy districts to poor or middle-income districts or both (see table 2). Detailed information on state equalization policies and changes in state funding needed to enable districts to spend the state average for each student with an average tax effort appears in the state profiles in this report (see apps. VII through LV). Each profile provides information on (1) the actual state and local funding distribution to districts in school year 1991-92 for districts in five groups of approximately equal student population, according to increasing district income, and (2) how funding would have been distributed among these groups if each district could have financed the state’s average total funding per weighted pupil with an average tax effort. We contacted state education officials to determine the extent to which the states had changed their targeting effort and state share between school years 1991-92 and 1995-96. Twenty-five states reported making little or no changes to their targeting effort or state share. The remaining 24 states reported making targeting changes that may have increased their implicit foundation levels. For example, education officials in Missouri said that changes implemented in 1993 had increased targeting to low-wealth districts and that the state’s new formula provides more state funding to districts with both lower property wealth and higher tax efforts. Six of the 24 states also reported making increases of 10 percentage points or more in their state share of education funding: Tennessee (10), Colorado (11), Kansas (18), Utah (24), Oregon (30), and Michigan (45). In some cases, lawsuits challenging the constitutionality of a state’s school finance system have prompted changes in targeting or state share. For example, one lawsuit alleged that Tennessee’s school finance system resulted in inequalities that violated the state constitution, and the state has since significantly revised its system. Appendix LVI summarizes the changes states have made between school years 1991-92 and 1995-96. Of the 10 states noted in table 2 requiring the largest shifts in state funding to poor districts, 5 reported making changes that provided more or much more state funding to low-wealth districts than in school year 1991-92. The other five states reported making little or no changes to their school finance system by school year 1995-96. Recognizing the struggle of poor districts to adequately fund the education needs of their students, states have used several strategies to reduce the funding gap between poor and wealthy districts. States that want to further reduce the funding gap between poor and wealthy districts would have to continue to increase the state share of total funding, increase their targeting effort to poor districts, or increase both. If targeting is increased, poor and middle-income districts would receive more state funding, while wealthy districts would receive less state funding. States may also increase their state share of education funding. A higher state share can offset income-related gaps even if the targeting effort is low, according to our analysis. However, making such changes may be difficult because of taxpayer concerns. Decisionmakers and others can use the measures in this report— particularly the fiscal neutrality score, implicit foundation level, and equalization effort—to assess the equity effects of current and proposed changes in state school finance policies. In addition, the implicit foundation level, when compared to a standard like the state average, can be used as a measure of the adequacy of funding provided by a state’s school finance system. Moreover, these measures can be used to assess progress over time in achieving more equity in school finance systems within states. The Department of Education reviewed a draft of this report and had no comments. 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 all 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 LVII. The objectives of this study were to determine (1) the size of the gap in total (state and local combined) funding between poor and wealthy school districts for each state, (2) the key factors that affect the size of states’ funding gaps, and (3) the effect of states’ school finance policies on the funding gaps. To help answer these questions, we used school year 1991-92 district-level data from the Department of Education, the most recent available, and supplemented these data when key data were missing. We used standard school finance measures and developed a new method to measure the effect of state policies on the funding levels of school districts. We supplemented our analysis by contacting education officials in the states to determine the extent to which a state’s school finance system had changed since school year 1991-92. For this study, we conducted a district-level analysis of all states except Hawaii. We wanted our analysis to examine state funding for regular school districts with students in grades kindergarten to 12, so the analysis excluded administrative districts and districts serving unique student populations, such as vocational or special education schools. Our analysis also excluded 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 2,235 districts excluded from the analysis had a total enrollment of 335,558. The final database used in our analysis of the 49 states contained 14,425 districts with a total of 41,204,610 students, representing 99.2 percent of the students in 49 states. This study was based 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. 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 disabled students for school year 1991-92 directly from the state education offices for nine states because the CCD either did not report the number of disabled students in the states or reported a number substantially different from one reported by another Education Department source. 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 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. To measure the size of the gap in total funding between poor and wealthy districts, we used the elasticity of total (state and local) funding in a district relative to district income, a measure of a district’s ability to raise revenue for education. In a regression model, we used dependent and independent variables that were adjusted for differences in geographic cost and student need within the state and put into index form (see app. II). A district’s total funding per weighted pupil was the dependent variable; a district’s income per weighted pupil was the independent variable. Each observation was weighted by the district size to allow districts with larger enrollments to have a greater effect on the results. Appendix III describes this process in detail. To determine the relationship between the total funding gaps and the key factors affecting the size of the gaps, we conducted a regression analysis using a state’s fiscal neutrality score (the elasticity of total funding to district income) as the dependent variable and the following as independent variables: a state’s share of total funding, a state’s targeting effort (described in this app.), and a state’s relative local tax effort (the elasticity of local tax effort relative to district income—see app. III). To measure the extent to which states targeted their education funds to poor districts, we estimated the elasticity of state funding in a district relative to district income. Using a regression model, we defined the dependent variable as a district’s state funding per pupil and the key independent variable as a district’s income per pupil. Both variables were adjusted for differences in geographic cost within the state (see app. II). To control for student need and economies of scale, we included four additional independent variables: poor students, disabled students, high school students, and district size. All variables in the analysis were put into index form and were included in the regression. Each observation was weighted by the district size to allow districts with larger enrollments to have a greater effect on the results. We set certain constraints on the regression coefficients. The resulting regression coefficient of the income per pupil variable is our measure of a state’s targeting effort and measures the elasticity of state funding relative to district income. Appendix V describes this methodology in greater detail. We developed an equity measure—implicit foundation level—to assess the state policies (targeting and state share) that affect the funding gap between wealthy and poor districts. We calculated this measure using a formula involving a state’s share of total funding, a state’s targeting effort, and a state’s average total funding per weighted pupil. To calculate the targeting effort in this formula, we used the same multivariate linear regression as the one already described, except we imposed the restriction that the income per pupil variable have a nonpositive coefficient. Appendix IV explains the theory behind the equity measure we developed, and appendix V explains the regression. Appendixes VII through LV provide profiles of each state’s school finances in school year 1991-92. The profiles provide summary information on the total funding per weighted pupil, states’ share of education funding, states’ targeting effort, implicit foundation level, equalization effort, and fiscal neutrality score. To report the state profiles for school year 1991-92, we ranked each state’s districts according to increasing district income and then divided the districts into five groups, each with about the same number of students. We then calculated the mean state, local, and total funding per weighted pupil for each group. These funding figures were also adjusted for differences in geographic costs within the state (see app. II). Appendix VI provides an overview of the state profiles. Because we relied on state and local funding data from the 1991-92 school year, we telephoned state school finance officials to determine what changes had occurred in the school finance systems from school years 1991-92 through 1995-96. We specifically asked about changes in targeting that would affect low-wealth districts and changes in the state’s share of total funding. Appendix LVI presents interview results. Education costs vary by school district in a state (and nationwide) because of geographic differences in the cost of educational resources and in the number of students with special needs. The cost of educational resources may vary across districts for several reasons. For example, a district may be able to hire a teacher of a given quality at a lower rate than other districts because the district may have a lower cost of living or offer certain amenities or working conditions that are more attractive to teachers than the other districts. Also, districts with either large or small student populations may face higher costs than other districts because of the diseconomies of scale that can occur in providing services at these levels. The cost of educating students also varies for a number of other reasons. Districts with high proportions of students with special needs, such as the disabled, the poor, and those with limited English proficiency, generally have higher education costs than average because such students require additional educational services. Furthermore, districts that largely serve high school students tend to have higher per pupil education costs than those that largely serve elementary students. As discussed in our previous report on equity measures, when estimating comparable measures of funding levels or disparities among districts, accounting for districts’ differences in educational resource costs and student needs is useful. This appendix discusses how we made these adjustments in our study. To adjust for geographic differences in resource costs by district, we used a national district-level teacher cost index recently developed for the National Center for Education Statistics (NCES). Although an index that examines differences in the cost of living is available by district, the NCES teacher cost index is better suited to comparing districts by considering the purchasing power of districts in determining personnel-related costs, a major cost to school districts. Our focus is on a district’s ability to provide comparable educational services to its students, rather than on whether teachers’ salaries are adequate given the cost of living in their area. Not all costs, however, vary within a state. For example, the cost of books, instructional materials, and other supplies and equipment tends to vary little within a state or, for some items, the nation. Therefore, we used the teacher cost index only to adjust the 84.8 percent of current expenditures estimated to relate to personnel costs, including salaries, fringe benefits, and some purchased services. Finally, we rescaled the NCES teacher cost index to create district-level indexes for each state that reflect the education resource cost differences in just one state rather than the differences nationwide. To rescale the teacher cost index, we determined the average teacher cost index for the state, then divided each district’s teacher cost index by the state average to obtain the district-level teacher cost index adjusted for within-state differences. A teacher cost index equal to 1.0 indicates a district with average resource costs for the state. Table II.1 provides the average cost index for each of the five income groups of districts in a state. In all states except four (Alaska, Nevada, New York, and North Carolina), the range in the average cost indexes across groups in the table was less than twice the standard deviation of the district-level cost index. This suggests that states may have had more variation in cost differences among individual districts than across the income groups shown in the table. To account for the differences in student need by district, we made adjustments that weighted poor students and disabled students according to their need for additional services. Our analysis did not account for limited English proficient students, generally recognized as a third group of high-cost students, because we could not obtain accurate district-level data on the number of such students. To account for differences in student needs by district, students with disabilities were given a weight of 2.3 because the cost of educating such children is generally 2.3 times the cost of educating children who do not need special educational services, although the cost of educating children with specific types of disabilities varies widely. We also assigned a weight of 1.2 for children from poor families. This additional .2 weighting for poor students stems from an estimate based on the average title I allocation per student divided by average funding per student. We used a set of weights developed for an NCES report. Using these weights, we developed a district-level need index adjusted for differences within the state. We used the following equation to calculate the need index for each district: where AdjMem = adjusted membership; a district’s fall membership + (1.3 x students with Individual Education Plans) + (.2 x students below the poverty line) AdjStMem = adjusted membership in a state; the sum of AdjMem for all districts in a state Member = membership; a district’s fall membership StMem = state membership; the sum of Member for all districts in a state. Table II.2 provides the average need index for each of the five income groups of districts in a state. In all states except three (Alaska, Maryland, and New Mexico), the range in the average need indexes across groups in the table was less than twice the standard deviation of the district-level need index. This suggests that states may have had more variation in need differences among individual districts than across the income groups shown in the table. Group 1 Group 2 Group 3 Group 4 (continued) Group 1 Group 2 Group 3 Group 4 Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Group 1 Group 2 Group 3 Group 4 (continued) Group 1 Group 2 Group 3 Group 4 Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. In our study, the goal of fiscal neutrality is achieved in a state when total (state and local) funding per weighted pupil does not depend on differences in districts’ income per weighted pupil. We measured the extent of this dependency using the income elasticity of total funding per weighted pupil and defined this elasticity as a state’s fiscal neutrality score. A positive fiscal neutrality score would indicate that per pupil funding rises with income; a fiscal neutrality score of 0 would indicate that fiscal neutrality has been achieved (that is, no relationship exists between per pupil funding and per pupil income); and a negative score would indicate higher funding in low-income districts. The first section of this appendix presents the method we used to estimate each state’s fiscal neutrality score and the results of our analysis. The second section shows how the variation in fiscal neutrality scores among states is explained by differences in state equalization policies (state share and state targeting) and by differences in the relative local tax effort of wealthy and poor districts. We used a linear regression model to estimate the elasticity of total funding in a district relative to district income. Both the dependent and independent variables were adjusted for differences in geographic cost and student need within the state and expressed as a percent of their respective state averages. By expressing each variable as a percent of its state average value, both the dependent and independent variables can be interpreted as index numbers. A value below 1.00 signifies that a district was below the state average for that variable; a value above 1.00 signifies that a district was above the state average. With these adjustments the regression model took the following form: Because both variables are measured relative to their respective state averages, the regression coefficient (b ) represents the percent difference, from the state average, in total funding relative to a percent difference, from the state average, in district income. This is precisely the elasticity we wanted to estimate and use as our fiscal neutrality score. A positive coefficient implies that total funding per weighted pupil is higher in wealthy districts, and a negative coefficient, the opposite. A coefficient that is not statistically different from 0 implies that fiscal neutrality has been achieved because no systematic differences exist in per pupil funding between wealthy and poor districts. We used a district’s total funding per weighted pupil as the dependent variable. This variable included state and local funding for all purposes, including maintenance and operations, transportation, and capital expenditures and debt service. We divided the district’s total funding by its fall membership to put the variable in per pupil form. We used district income per weighted pupil as the independent variable, our measure of a district’s ability to raise revenue for education. Because we could not develop income per pupil data from the Common Core of Data (CCD), we used district-level per capita income from the 1990 census to construct the variable. We multiplied per capita income in a district by district population, resulting in the total income in the district. We then divided this amount by the total number of students in the district, resulting in income per pupil. Most school finance studies measure a district’s ability to raise revenue for education as district wealth defined as property value per pupil. However, we chose to use district income defined as resident income per pupil because we could not construct a property-value-per-pupil measure at the district level from the national databases that were available. Furthermore, beyond the field of school finance, income—as opposed to wealth—is the most commonly accepted measure of the ability to raise revenue. A good income measure of a district’s ability to raise revenue for education should be as comprehensive as possible. For example, the Department of Treasury defines and compiles the total taxable resources (TTR) for each state. TTR takes into account all income either received by state residents or produced in a state. Either income measure, by itself, is incomplete. Income received by state residents does not include business income earned by nonresidents (undistributed corporate profits, for example). Alternatively, income produced does not include income earned by residents from out-of-state sources (residents who work out of state, for example). Consequently, TTR includes both income received and income produced to gauge a state’s total taxable resources. Unfortunately, a comprehensive income measure such as the TTR is not available at the school district level. Our income measure is money income reported in the 1990 census. Its major weakness is that it does not include commercial or nonresident income that local school districts may be able to tax. It may therefore understate the ability of districts with high concentrations of this type of income to raise revenues for education. However, our measure does include the largest income category—resident income—represented in TTR. Although we would expect some differences in the results of our analyses if all income from commercial and industrial property had been included in the income variable, the general trends from our analyses would still have held true. Finally, the regression model in equation III.1 was estimated 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. In most states, total funding per weighted pupil increased as district income increased (the elasticity was positive). On average, wealthy districts had about 24 percent more total funding per weighted pupil than poor districts. In 37 states, the income elasticity of total funding per weighted pupil was positive. This means that as the districts’ income increased, the level of total funding increased. However, the range in elasticity varied among the states, with a high of .469 in Maryland and a low of .055 in Washington. In three states—Alaska, Nevada, and Oklahoma—the elasticity was negative, that is, total funding decreased as district income increased. Elasticities for these three states ranged from –.556 in Nevada to –.053 in Oklahoma. The elasticity was not statistically different from 0 in the remaining nine states. Table III.1 shows the elasticities of total funding to district income and the R square for each state. Elasticity of total funding to income (continued) In most states, the amount of total funding (state and local funding combined) per weighted pupil available to wealthy districts exceeded such funding available to poor districts. However, states varied widely in the degree to which funding available for wealthy districts exceeded that of poor districts. Table III.2 summarizes the gaps in total funding per weighted pupil between wealthy and poor districts. Tables III.3 and III.4 show the state averages for total funding per weighted pupil and income per weighted pupil as well as the average index numbers of these two variables for each of the five income groups of districts in a state. Wealthy group funding compared with poor group funding(continued) Average total funding per weighted pupil(continued) Average total funding per weighted pupil(continued) Average total funding per weighted pupilNevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Average income per weighted pupil(continued) Average income per weighted pupilNevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. We identified state share, state targeting, and relative local tax effort as the three key factors affecting the size of school funding gaps between poor and wealthy districts using the following rationale. First, we set aside the effects of state share and state targeting by assuming that states do not fund schools and that funding per pupil depends entirely on the revenue from local tax bases. Under this assumption, the funding gap occurs because wealthy districts can generate more local funding than poor districts when the tax effort for all districts is equal. However, the gap in funding between wealthy and poor districts would grow smaller as poor districts increase their local tax effort relative to wealthy districts. Therefore, in the absence of any state funding for education, the funding gap between poor and wealthy districts would be completely determined by the relative local tax effort of poor and wealthy districts. A state can help offset the funding gap by providing a portion of the total funding and targeting more state funds to poor districts. Consequently, the size of the funding gap between wealthy and poor districts should depend on both state equalization policies (state share and state targeting) and the relative local tax effort of poor districts and wealthy districts. To measure a state’s relative local tax effort, we estimated the income elasticity of local tax effort. For each state, this elasticity measures the percent change in local tax effort associated with a 1-percent increase in district income per weighted pupil. As measured this way, the greater the elasticity, the greater the tax effort in wealthy districts as compared with poor districts. This elasticity is represented by the regression coefficient ) in the following equation: local tax effort index = the ratio of a district’s local funding to its income expressed as a percent of the average tax effort of all districts, represented by the dependent variable above elasticity of local tax effort = a state’s elasticity of local tax effort to income per weighted pupil, represented by b = an error term that reflects the variation in the local tax effort that cannot be accounted for by the other variables in the model. To estimate the extent to which the three factors—elasticity of local tax effort, state share, and state targeting (see table III.6)—accounted for the variation in the funding gap between wealthy and poor districts, we constructed a regression model that used these three factors to explain cross-state differences in fiscal neutrality scores: fiscal neutrality score = a state’s elasticity of total funding per weighted pupil relative to income per weighted pupil state funding percentage = state funding as a percentage of total (state and local) funding state targeting effort = a state’s elasticity of state funding per weighted pupil relative to income per weighted pupil elasticity of local tax effort = a state’s elasticity of local tax effort relative to income per weighted pupil = an error term that reflects the variation in funding gaps that cannot be accounted for by the other variables in the model. The results of this analysis showed that the three factors accounted for about 61 percent of the variation in the income-related funding gaps.Although increases in both state targeting and state share led to decreases in states’ fiscal neutrality scores, state share had a relatively greater impact on reducing income-related funding gaps than did states’ targeting efforts. Increases in the elasticity of local tax effort were associated with increases in the funding gap, meaning that as the wealthy districts’ tax effort increased relative to the poor districts’ tax effort, the income-related funding gap also increased. The elasticity of local tax effort factor of the three factors in this equation accounted for most of the variation in the fiscal neutrality scores (see table III.5). Table III.6 shows the state data used in the regression analysis. State share of total funding (percent) Elasticity of local tax effort(continued) State share of total funding (percent) Another way to illustrate that state equalization policies (state share and state targeting) reduced but did not eliminate the funding gap between wealthy and poor districts is shown in table III.7. In most cases, the addition of state funding to local funding caused total funding to be less sensitive to district income than local funding. This is illustrated by the fact that states’ income elasticities of total funding are usually less than those of local funding. The elasticity of local tax effort accounted for most of the variation in the fiscal neutrality scores. We compared the local tax efforts of poor and wealthy districts in table III.8. In 35 states, poor districts made a higher tax effort than wealthy districts. (continued) –.196 Poor group tax effort compared with wealthy group tax effort(continued) In this study, we developed a new equity measure to assess a state’s equalization policies (state share and state targeting) that excludes the effects of the local tax effort. To accomplish this, we viewed each state as if it were distributing state funds according to a foundation program in which the state ensures a foundation or minimum amount of funding per pupil for a minimum local tax effort. Using a foundation formula and assuming all districts made an equal minimum tax effort, we determined each state’s implicit foundation level given the state’s equalization policies in school year 1991-92. This implicit foundation level is an estimate of the minimum amount of total funds (including both state and local funds) that districts could spend per student given the state’s equalization policies and provided all districts made an equal tax effort. The implicit foundation level identifies a funding level per pupil at which an equal local tax effort would produce equal funding per pupil among all districts in a state. This appendix describes how foundation formulas work and how we calculated three important summary measures for each state: targeting effort, implicit foundation level, and equalization effort. As mentioned, to calculate these three summary measures, we assumed states behaved as if they used a foundation formula to distribute state funds to districts. As will be shown in this appendix, foundation equalization policy can result in states targeting more funds to districts with lower tax bases. Because nearly all states do target more funds to districts with low tax bases, it is reasonable to evaluate school finance policies as if they followed an implicit foundation equalization policy. To model the state targeting needed to enable districts to spend the implicit foundation amount on each student with a minimum tax effort, we used a derivation of the following foundation formula:g = state funding per pupil in a school district e* = the implicit foundation level (including both state and local funds) that results when all districts make an equal minimum tax effort given the state’s equalization policies t* = the minimum tax effort, a ratio of district’s local revenue to district’s tax base value v = the tax base per pupil in a school district. In our study, we used income per pupil. One implication from the above equation is that if a state chose not to target additional funding to poor districts and instead provided the same funding per pupil to all students with no minimum required local tax effort (t*= 0), then the implicit foundation level for the state (e*) would equal the average state funding per pupil. That is, each district’s state funding per pupil (g) would equal the average state funding per pupil (g). Another implication of the equation is that if states require a minimum tax effort (t*) greater than 0, states will have to target more funding to poor districts than to wealthy districts to achieve the same implicit foundation level (e*) for all districts. The implicit foundation level in this instance would be greater than the average state funding per pupil (g) where, without a required local tax effort, no extra state funding is targeted to poor districts. From our analysis of school year 1991-92 school finance data, we know that states do, in fact, vary in the extent to which they target additional funding to poor districts. Consequently, our purpose was to estimate the implicit foundation level that was possible in each state given the degree to which a state targets more funds to poor districts. We have divided the explanation into two parts. First, we explain how state funding would have to be targeted to ensure that all students received the state’s average total funding per pupil, provided that all local districts made an average tax effort. Second, we modify our explanation to allow for state targeting that results in an implicit foundation level that is below the state average with districts making a minimum local tax effort. On the basis of equations developed in this second part, we then describe how we estimated state targeting efforts, implicit foundation levels, and equalization efforts. Given the total amount of funding for education in a state, the maximum foundation level possible in a state is the state’s average total funding per pupil. This means that, in principle, if all districts were to make the average tax effort to finance their local school programs, the state could target its funds to ensure that all districts could fund the average total funding per pupil. To demonstrate this, we began with an equation in which the implicit foundation level equals the state’s average total funding per pupil, and then we modified this equation to show how state funds would have to be distributed. where g = state funding per pupil in a school district e = the state’s average total funding per pupil, which is also the implicit foundation level in the state t = the average tax effort of local school districts v = the tax base per pupil in a school district. The local share of total funding per pupil, by definition, is local funding expressed as a percent of total funding. This is expressed by the following equation: = the local share of the total funding for education in the state v = the average tax base per pupil in the state. Rearranging terms in equation IV.3, we found that the equation for average tax effort of local districts is t=(a e/v). Substituting this equation for t in equation IV.2 and rearranging terms results in the following equation: Equation IV.4 represents how state funding would have to be distributed if all school districts were to finance the state average funding level, provided that districts made an average tax effort to finance their local schools. We chose to measure state targeting by the income elasticity of state funding, where district income represents the tax base per pupil. The income elasticity is the percent difference in state funding that results from a 1-percent difference in district income. We can use the relationship in equation IV.4 to measure this elasticity by dividing both sides of the equation by the average state funding, that is, g=e(1-(a v/v))=(1-a )e. This yields the following equation: g = the average state funding per pupil, (1-a )e. We note that a school district’s relative state funding per pupil (g/g) depends on (1) the relative size of its tax base per pupil (measured as v/v) and (2) the share of education funding financed at the local level (a ) and by implication the share of education funding financed with state funds (1-a ). The slope parameter of equation IV.5 (a /1-a ) can be interpreted as the income elasticity of state funding and represents the state’s targeting effort to achieve the maximum foundation level (providing all districts the capacity to fund the state average funding level with an average tax effort). The relationship also implies that the greater the local share of total funding, and therefore the smaller the state share, the greater the state’s targeting effort must be if it is to achieve the maximum foundation level for all students. Other important implications derive from this relationship: A linear relationship must exist between a school district’s relative state funding per pupil and the relative tax base per pupil. The intercept is the inverse of the state funding percentage (that is, 1/(1-a )). The slope and intercept will always sum to 1 (that is, (1/(1-a ) + (-a /(1-a ))) = 1). Although the state average represents the maximum foundation level possible in a state if all districts were to make an average tax effort, most states’ implicit foundation levels are likely less than the maximum. In this section we develop the state targeting implications that produce an implicit foundation level that is less than the maximum. We assume that all districts make the same minimum tax effort and that the state still funds the same share of total education funding. If the implicit foundation level is less than the state average, it is because the state targets its funds to low tax base districts to a lesser degree than is required to achieve the maximum foundation level. To model this condition, we introduced a new term—the equalizing factor (b )—into equation IV.2. The value of the equalizing factor ranges from 0 to 1. When the equalizing factor equals 1, the state’s targeting effort is at its maximum level. When the equalizing factor equals 0, the state is not targeting funds to poor districts, and every district receives the same state funding per pupil. In this instance, the implicit foundation level is simply the average state funding per pupil. An equalizing factor between 0 and 1 means the state’s effort to target funds to poor districts is less than the maximum. Introducing just the equalizing factor to the equation increases the size of state funding to each district. However, since the total amount of state funding has not changed, we had to introduce a scalar (g ) to ensure that the sum of the state funding is still the same percentage of total funding. The result of introducing these two new variables is shown in equation IV.6: = the equalizing factor, that is, the fraction of the maximum targeting effort that the state undertakes g = a scalar that ensures that the total sum of state funding equals the total amount of state funds available for distribution. The next few equations show that the scalar (g ) depends on the state share of education funding (1-a ) and the equalizing factor (b ). As stated earlier, the total amount of state funding equals the sum of all the districts’ state funding. By multiplying both sides of equation IV.2 by the total number of pupils in a district (P) and summing both sides, we created an equation for the total amount of state funding (G). G = the total sum of state funding available for distribution P = the number of pupils in a district. Because the total amount of state funding (G) available has not changed, it must be true that the sum of total state funding under maximum targeting efforts is the same as when targeting efforts are less than the maximum. This is represented in the following equation: Solving for the scalar (g ) yields equation IV.9: By definition, the sum of (Pe) equals total funding and the sum of (Ptv) equals the total amount of local funding from all school districts. Dividing both numerator and denominator by total funding yields the following equation for the scalar (g ): When the state’s targeting is at its maximum level, then the equalizing factor (b ) equals 1, and the scalar (g ) equals 1. If the state were to provide flat funding per pupil to all districts, no targeting to poor districts would occur, and the equalizing factor (b ) would equal 0 and the scalar (g ) would equal (1-a ), the state’s share of total funding. As discussed earlier, we used the slope of equation IV.5 to determine how much the state would have to target state funding to low tax base districts to achieve an implicit foundation level equal to the state average. Revising equation IV.6 produced a similar equation that shows how much state funding would have to be targeted to low tax base districts to achieve an implicit foundation level below the state average. We modified equation IV.6 by substituting (1-a )/(1-b ) for the scalar (g ) and substituting (a e/v) for the average tax effort (t). Making these substitutions in equation IV.6 and rearranging terms yielded the following equation analogous to equation IV.5: This equation is the basis for running regressions, using actual district data for state funding per pupil (g) and the tax base per pupil (v). The slope (b )) represents the state’s targeting effort. When estimating this/(1-b equation, the slope and the intercept (1/(1-b )) must be constrained so that they sum to 1. After obtaining the regression coefficient for the tax base per pupil, we can solve for the equalizing factor (b ) because the local share of funding (a ) is known. When the state’s implicit foundation level is less than the state average, the state’s equalizing factor (b ) is less than 1 and the state’s targeting effort ((b maximum value (a )) is less than it would be at its /(1-a )). The term representing the implicit foundation level in equation IV.6 equals the scalar (g ) times the state’s average total funding per pupil (e) or the maximum foundation level. Substituting the expression in equation IV.10 for the scalar (g ) in equation IV.6, we expressed the implicit foundation level in terms of the state’s average total funding per pupil, the local share of school funding, and the equalizing factor as follows: Using equation IV.12 and knowing the local funding percentage (a ), the equalizing factor (b ), and the state average funding level (e), we solved for the state’s implicit foundation level. A state’s equalization effort is a ratio of the state’s implicit foundation level to the maximum or average funding level. By rearranging terms in equation IV.12, we showed that a state’s equalization effort, the ratio of the implicit foundation level (e*) to the average funding level (e), equals the ). Therefore, a state’s equalization effort reflects scalar (g ) or (1-a )/(1-b the state’s share of education funding and a state’s targeting effort. Appendix V describes how we used these equations to estimate each state’s targeting effort, implicit foundation level, and equalization effort. This appendix describes the statistical models we used to estimate each state’s targeting effort, implicit foundation level, and equalization effort. It also presents the model results and the index data for some of the model variables. In addition, it explains how the implicit foundation level for each state can be adjusted to facilitate cross-state comparisons. Finally, it describes how states’ estimated equalization efforts and relative local tax efforts can explain the variation in state fiscal neutrality scores. ) can be interpreted as the percent difference in state funding per pupil associated with a 1-percent difference in district income from the state average per pupil income. This, by definition, is the elasticity of total per pupil funding relative to a district’s per pupil income, evaluated at the mean of these variables. = the equalizing factor, that is, the fraction of the maximum targeting effort that the state undertakes v = the tax base per pupil in a school district (in our study, we used income per pupil) v = the average per pupil tax base in the state. In the regression, both the dependent and independent variables were adjusted for differences in geographic cost within the state by applying a district-level teacher cost index to the dollar figures (see app. II). The dependent variable was a district’s state funding per pupil, and the key independent variable was a district’s income per pupil. Our analyses included four other independent variables that controlled for student-need factors that contribute to the cost of education. The first three of these variables relate to the presence of high-cost student groups in a district, and the fourth variable relates to cost differences due to economies of scale. The four variables are the percent of district students who are poor (based on the percentage of children who live in households that were below the poverty level in 1989);the percent of district students who are disabled designated as special education students under the Individuals With Disabilities Education Act (part B) who have an Individual Education Plan; the percent of district students who are high school students (grades 9 to 12); and the total square of district enrollment (membership) on October 1, 1991. We included these control variables in our model rather than use the student need index developed in appendix II because we wanted to account for actual state targeting policies to the extent possible rather than use a uniform measure of student need that may not reflect actual state policy. All variables in the analysis were put into index form. Including all four control variables yielded the following model of state targeting policies: c = a district’s teacher cost index adjusted for statewide differences MEMSQI=a district’s student membership squared as a percent of the district student membership (as a percent of the state average) PovI = the percent of district students below the poverty level (as a percent of the state average) SNI = the percent of district students with an Individual Education Plan (a measure of pupils with special education needs) also measured as a percent of the state average HSI = the percent of district students who are high school students (as a percent of the state average) = error term measuring all other factors affecting the distribution of state funding. Each of the regression coefficients in the model depends on the equalization factor and the local share of education funding (b additional coefficient (b ). An ), unique to each variable, was added so that the regression coefficients added to 1.0, as required by the equalization model (see app. IV). The regression coefficients in the model )) in the )) to (b model, in effect, serves as a control for the membership size of the district. The model in equation V.2 was estimated by weighting each observation for membership size to allow school districts with larger enrollments to have a greater effect on determining the coefficients of the equation. This prevents one or a few small school districts from unduly influencing the estimated coefficients. The results are then more representative of the effect that state funding targeting policies had on students in the state. Because we were estimating the extent to which each state’s funding targeting policy was consistent with providing an implicit foundation level with a minimum tax effort, we also imposed the restriction that the three student-need variables would have non-negative coefficients. We did not specify the direction of the coefficient for the membership squared variable because we did not have an expectation of how a state’s funding targeting policy might reflect economies or diseconomies of size. Because we wanted to determine the actual targeting efforts of states compared with district income, we did not restrict the coefficient for the income per pupil variable, allowing the coefficient to be any sign. We reported state targeting efforts using the income per pupil coefficient obtained from this effort. Table V.1 shows the targeting effort for state funds compared with district income per pupil, the sampling error, and the overall R square. Negative targeting efforts represent more targeting to poor than to wealthy districts; positive targeting efforts represent more targeting to wealthy than to poor districts. A targeting effort of 0 signifies no targeting of state funds to either poor or wealthy districts. Our analysis shows that 33 states targeted more state funds to districts as district income declined. However, the degree of the targeting varied widely, ranging from a high of –1.007 in Nevada to a low of –.099 in Indiana. Fourteen states did not target state funds on the basis of district income—the targeting effort was not statistically different from 0. Two states—Louisiana and North Dakota—provided more state funding to districts as district income increased. The degree to which states targeted state funds on the basis of differences in district income and student need also varied widely. In only 19 states, district income and student need accounted for more than 50 percent of the variation in state funding per pupil as noted by the R squared results. In 3 of the 19 states—Kentucky, Maryland, and Virginia—more than 80 percent of the variation in state funding was explained. In the remaining 30 states, less than half of the variation in state funding per pupil was due to differences in district income and student need. Tables V.2 and V.3 provide the average income per pupil and average state funding per pupil as well as the average index numbers of these two variables according to groups of increasing district income. Tables V.4 to V.7 provide the average index numbers for the four control variables associated with student poverty, disabled students, high school students, and district size according to groups of increasing district income. Sampling error Overall R squared (continued) Average income per pupil index numbers (continued) Average income per pupil index numbers Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Average state funding per pupil (continued) Average state funding per pupil (continued) Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Average poverty rate (percent) (continued) Average poverty rate (percent) Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Average disabled rate (percent) (continued) Average disabled rate (percent) Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Average high school student index numbers Group 1 Group 2 Group 3 Group 4 (continued) Average high school student index numbers Group 1 Group 2 Group 3 Group 4 (continued) Average high school student index numbers Group 1 Group 2 Group 3 Group 4 Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. Average membership squared index numbers Group 1 Group 2 Group 3 Group 4 (continued) Average membership squared index numbers Group 1 Group 2 Group 3 Group 4 Nevada was divided into only four groups because of the distribution of the student population. The wealthiest group is group 4. In appendix IV we demonstrated that to calculate the implicit foundation level we must know the state’s targeting effort, the local share of total funding, the state’s average total funding per weighted pupil, and the equalizing factor. Because the equalization theory underlying the implicit foundation level implies state funding is targeted to poor districts, when we determined the targeting effort for calculating the implicit foundation level, we constrained the coefficient of the tax base variable to be less than or equal to 0. Then, having calculated the state’s targeting effort (that is, the coefficient of the tax base variable, b local share of education funding (a ) and average total funding per weighted pupil (e), we can solve for the equalizing factor (b ). Finally, )) and knowing the knowing the equalizing factor, we can calculate the state’s implicit foundation level using equation IV.12 from appendix IV (reproduced here as equation V.3). The results for each state are reported in table V.8. e = the state’s average total funding per weighted pupil. The implicit foundation level available to all students in a state depends upon the state’s average total funding per weighted pupil, targeting effort, and share of total funding. Two states with the same average total funding per weighted pupil can have very different implicit foundation levels depending on their state equalization policies. For example, Alaska and Connecticut had about the same average funding level. However, Alaska’s state share was about twice that of Connecticut’s. Consequently, Alaska’s implicit foundation level ($6,137) was much more than Connecticut’s ($4,556), even though Connecticut’s targeting effort was greater than Alaska’s effort. Once we know the implicit foundation level, we can calculate the state’s equalization effort. This is a measure of the implicit foundation level as a percent of the state average. Since the state average is the maximum foundation level that is possible in a state given the total funding devoted to education, the equalization effort is a measure of how close a state comes to reaching the maximum level. States’ implicit foundation levels varied widely. The average implicit foundation level was $3,090 per weighted pupil in school year 1991-92, with levels ranging as low as $764 in New Hampshire to as high as $6,137 in Alaska. States’ equalization efforts also varied widely. Only one state—Nevada— reached the state average for each student. The equalization effort in the other 48 states was less than the state average, ranging from 87 percent (Arkansas and Kentucky) to 13 percent (New Hampshire) of their state average. In 14 states, districts could finance less than half the state average with a minimum local tax effort. Table V.8 summarizes the critical data used to determine the implicit foundation level and equalization effort for all states. Table V.8: State Targeting, State Share, and Funding Levels State targeting )) State’s share as a percent of total funding (1-a ) State average funding level (e) Implicit foundation level (e*) Equalization effort (e*/e) (continued) State targeting )) State’s share as a percent of total funding (1-a ) State average funding level (e) Implicit foundation level (e*) Equalization effort (e*/e) (Table notes on next page) Nevada targeted more state funds to poor districts than was necessary for districts to finance the state average with all districts making the same tax effort. As a result, poor districts in Nevada were able to finance the state average funding level with a lower tax effort than wealthy districts. In addition to targeting additional funds to poor districts, some states provided the same minimum amount of state funding to all districts, regardless of district income. Unlike funding for lower income districts, such funding for wealthy districts in some states was not part of the state’s targeting effort because it was not sensitive to district income. Consequently, we also estimated the state implicit foundation level and equalization effort, assuming the goal was to have all students except for the 15 percent of students in the wealthiest districts receive the implicit foundation level. Using this analysis, we found that 16 states had a net increase of 10 percentage points or more in their equalization effort, that is, in the extent to which they achieved the state average. Table V.9 provides the results of this analysis. Equalization effort for all students(continued) Equalization effort for all students(Table notes on next page) To facilitate cross-state comparisons of the implicit foundation levels, we adjusted the implicit foundation levels reported in table V.8 for interstate differences in costs and student needs. We used a teacher cost index available from the National Center for Education Statistics (NCES) for the states to adjust funding data for national differences in cost, and we created a nationwide need index for the states in the same way we created other indexes (see app. II). To compare states, we divided the funding data from a state by the product of the nationwide cost and need indexes of that state. Using this method, we calculated the nationally adjusted implicit foundation level for each state (see table V.10 and fig. V.1). Table V.11 lists the original nationwide teacher cost index we obtained from NCES, an adjusted nationwide index that applies only to teacher costs, and the nationwide need index for each state. Figure V.1: Nationally Adjusted Implicit Foundation Levels (Ranked) Funding per Weighted Pupil (Dollars) Adjusted state teacher cost index(continued) After calculating the state equalization effort, a measure that accounts for the combined effects of state targeting and state share in state equalization policies, we used it together with relative local tax effort to explain cross-state variation in funding gaps. In equation V.4, the dependent variable was the state fiscal neutrality scores reported in table III.1; the two independent variables were the state equalization efforts, reported in table V.8 and the elasticity of local tax effort reported in table III.6. The results of this analysis showed that the two factors accounted for 63 percent of the variation in the funding gaps. The elasticity of local tax effort accounted for more of the variation in funding gaps than did state equalization efforts (see table V.12). Appendixes VII through LV contain profiles for 49 states. Each profile provides the critical data resulting from our analysis of state school finance policies. In addition, each profile provides information in tabular and graphic form on (1) the actual distribution of state and local funding to regular school districts in school year 1991-92 and (2) how the funding would have been distributed if the state share of total funding had remained the same and the targeting of state funding had been changed so that districts could spend the state average of total funding on each student with an average tax effort. All funding data in the profiles were adjusted for differences in geographic cost and student need within the state. The profiles show averages for districts within the state in five groups according to increasing income per pupil based on student population. For example, the poorest group of districts typically contains about 20 percent of a state’s student population and has the lowest incomes per pupil. In the stacked bar graphs (the first two figures in each profile), the height of the bars shows how state funding that has been adjusted for cost and need is equalized among districts. If the state fully equalized funding, all the bars are the same height. To assess the targeting of state funds, examine the shaded area within each bar, which represents the state’s share of total funding. Where state funding was targeted to poor districts, the shaded portion is highest for the poorest districts and becomes smaller as the per pupil income of a district increases. The first figure in each profile shows how total funding per weighted pupil changed as district income per pupil increased. Typically, the local funding increased with increasing per pupil income, often at a faster rate than the decline in state funding. Thus, total funding typically was greatest for the wealthiest districts. The second figure in each profile shows how state and local funding would have been distributed if all districts could have spent the average total funding per weighted pupil (the total funding level is the same across all groups) with an average tax effort. This figure assumes that the state optimized its targeting effort without changing the state share or the total funding for education. The third figure in each profile compares the state funding in the first figure with the state funding in the second figure. The third figure illustrates which groups of districts would have received more or less than what they needed if the state had targeted its funds so that each district could have spent the state average of total funding on each student with an average tax effort. The data used in each of the figures appear in tables in each profile. The numbers in the tables may not add due to rounding. 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 income and cost data for a district when the data were missing from the source. Income per pupil data were adjusted for differences in cost within a state. Funding per pupil data were adjusted for differences in student need and geographic costs within a state. Funding data included all state and local revenue for all purposes, including maintenance and operations, transportation, and capital expenditures and debt service. As table VII.1 shows, in school year 1991-92, the state provided about 70 percent of the total funding to Alabama’s school districts. Total funding (state and local funds combined) per weighted pupil in Alabama averaged $3,277 with an implicit foundation level of $2,287 for each student, which is about 70 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .290, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) An Alabama education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table VII.3 presents data on how state and local funding was distributed among the five groups of Alabama districts. Alabama’s equalization policies reduced the funding disparity between the poor and wealthy groups from about 93 percent to about 18 percent. Figure VII.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table VII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure VII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure VII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table VIII.1 shows, in school year 1991-92, the state provided about 76 percent of the total funding to Alaska’s school districts. Total funding (state and local funds combined) per weighted pupil in Alaska averaged $8,030 with an implicit foundation level of $6,137 for each student, which is about 76 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was –.272, indicating that total funding increased as district income decreased. (To compare this score with those of other states, see fig. 1.) To put the state’s school finance system in perspective, table VIII.2 presents demographic data for school year 1991-92 for five groups of districts of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table VIII.3 presents data on how state and local funding was distributed among the five groups of Alaska districts. Alaska’s equalization policies essentially eliminated the funding disparity between the poor and wealthy groups. Figure VIII.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table VIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure VIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure VIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table IX.1 shows, in school year 1991-92, the state provided about 47 percent of the total funding to Arizona’s school districts. Total funding (state and local funds combined) per weighted pupil in Arizona averaged $4,507 with an implicit foundation level of $2,598 for each student, which is about 58 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.232, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .141, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table IX.3 presents data on how state and local funding was distributed among the five groups of Arizona districts. Arizona’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 144 percent to about 32 percent. Figure IX.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table IX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure IX.2 provides information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure IX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (1,000) (2,000) State Funding Funding per Weighted Pupil (Dollars) (1,000) (2,000) As table X.1 shows, in school year 1991-92, the state provided about 65 percent of the total funding to Arkansas’s school districts. Total funding (state and local funds combined) per weighted pupil in Arkansas averaged $3,784 with an implicit foundation level of $3,289 for each student, which is about 87 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.328, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .220, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table X.3 presents data on how state and local funding was distributed among the five groups of Arkansas districts. Arkansas’ equalization policies reduced the funding disparity between the wealthy and poor groups from about 111 percent to about 14 percent. Figure X.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table X.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure X.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure X.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XI.1 shows, in school year 1991-92, the state provided about 69 percent of the total funding to California’s school districts. Total funding (state and local funds combined) per weighted pupil in California averaged $4,543 with an implicit foundation level of $3,504 for each student, which is about 77 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.119, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .073, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XI.3 presents data on how state and local funding was distributed among the five groups of California districts. California’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 166 percent to about 13 percent. Figure XI.1 provides table information in graphic form. Appendix XI State Profile: California Funding per Weighted Pupil (Dollars) Table XI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XI State Profile: California Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XII.1 shows, in school year 1991-92, the state provided about 44 percent of the total funding to Colorado’s school districts. Total funding (state and local funds combined) per weighted pupil in Colorado averaged $5,047 with an implicit foundation level of $3,847 for each student, which is about 76 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.753, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .154, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Colorado education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XII.3 presents data on how state and local funding was distributed among the five groups of Colorado districts. Colorado’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 63 percent to about 8 percent. Figure XII.1 provides table information in graphic form. Appendix XII State Profile: Colorado Funding per Weighted Pupil (Dollars) Table XII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XIII.1 shows, in school year 1991-92, the state provided about 39 percent of the total funding to Connecticut’s school districts. Total funding (state and local funds combined) per weighted pupil in Connecticut averaged $8,221 with an implicit foundation level of $4,556 for each student, which is about 55 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.430, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .241, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Connecticut education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XIII.3 presents data on how state and local funding was distributed among the five groups of Connecticut districts. Connecticut’s equalization policies reduced the funding disparity between the wealthy and poor groups from 234 percent to about 34 percent. Figure XIII.1 provides table information in graphic form. Appendix XIII State Profile: Connecticut Funding per Weighted Pupil (Dollars) Table XIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) State Funding Appendix XIII State Profile: Connecticut Funding per Weighted Pupil (Dollars) (1,000) As table XIV.1 shows, in school year 1991-92, the state provided about 70 percent of the total funding to Delaware’s school districts. Total funding (state and local funds combined) per weighted pupil in Delaware averaged $5,576 with an implicit foundation level of $4,190 for each student, which is about 75 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.070, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .072, indicating that total funding increased as district income increased.(To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XIV.3 presents data on how state and local funding was distributed among the five groups of Delaware districts. Delaware’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 156 percent to about 9 percent. Figure XIV.1 provides table information in graphic form. Appendix XIV State Profile: Delaware Funding per Weighted Pupil (Dollars) Table XIV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XIV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XIV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XV.1 shows, in school year 1991-92, the state provided 53 percent of the total funding to Florida’s school districts. Total funding (state and local funds combined) per weighted pupil in Florida averaged $5,555 with an implicit foundation level of $4,759 for each student, which is about 86 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.615, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .239, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XV.3 presents data on how state and local funding was distributed among the five groups of Florida districts. Florida’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 181 percent to about 18 percent. Figure XV.1 provides table information in graphic form. Appendix XV State Profile: Florida Funding per Weighted Pupil (Dollars) Table XV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XV State Profile: Florida Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XVI.1 shows, in school year 1991-92, the state provided about 55 percent of the total funding to Georgia’s school districts. Total funding (state and local funds combined) per weighted pupil in Georgia averaged $4,324 with an implicit foundation level of $2,932 for each student, which is about 68 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.242, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .323, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XVI.3 presents data on how state and local funding was distributed among the five groups of Georgia districts. Georgia’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 189 percent to about 30 percent. Figure XVI.1 provides table information in graphic form. Appendix XVI State Profile: Georgia Funding per Weighted Pupil (Dollars) Table XVI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XVI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XVI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XVI State Profile: Georgia Funding Per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XVII.1 shows, in school year 1991-92, the state provided about 67 percent of the total funding to Idaho’s school districts. Total funding (state and local funds combined) per weighted pupil in Idaho averaged $3,504 with an implicit foundation level of $2,654 for each student, which is about 76 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.130, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .247, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) An Idaho education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). To put the state’s school finance system in perspective, table XVII.2 presents demographic data for school year 1991-92 for five groups of districts of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XVII.3 presents data on how state and local funding was distributed among the five groups of Idaho districts. Idaho’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 177 percent to about 26 percent. Figure XVII.1 provides table information in graphic form. Appendix XVII State Profile: Idaho Funding per Weighted Pupil (Dollars) Table XVII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XVII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XVII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XVII State Profile: Idaho Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XVIII.1 shows, in school year 1991-92, the state provided about 33 percent of the total funding to Illinois’ school districts. Total funding (state and local funds combined) per weighted pupil in Illinois averaged $4,970 with an implicit foundation level of $2,031 for each student, which is about 41 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.230, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .338, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XVIII.3 presents data on how state and local funding was distributed among the five groups of Illinois districts. Illinois’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 215 percent to about 67 percent. Figure XVIII.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table XVIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XVIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XVIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) (4,000) State Funding Appendix XVIII State Profile: Illinois Funding per Weighted Pupil (Dollars) (1,000) (2,000) (3,000) As table XIX.1 shows, in school year 1991-92, the state provided about 54 percent of the total funding to Indiana’s school districts. Total funding (state and local funds combined) per weighted pupil in Indiana averaged $4,993 with an implicit foundation level of $2,970 for each student, which is about 60 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.099, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .153, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) An Indiana education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XIX.3 presents data on how state and local funding was distributed among the five groups of Indiana districts. Indiana’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 40 percent to about 10 percent. Figure XIX.1 provides table information in graphic form. Appendix XIX State Profile: Indiana Funding per Weighted Pupil (Dollars) Table XIX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XIX.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XIX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XIX State Profile: Indiana Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XX.1 shows, in school year 1991-92, the state provided 49 percent of the total funding to Iowa’s school districts. Total funding (state and local funds combined) per weighted pupil in Iowa averaged $4,849 with an implicit foundation level of $2,622 for each student, which is about 54 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.104, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .031, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XX.3 presents data on how state and local funding was distributed among the five groups of Iowa districts. Iowa’s equalization policies increased the funding that poor districts had compared with wealthy districts from 2 percent to about 4 percent. Figure XX.1 provides table information in graphic form. Appendix XX State Profile: Iowa Funding per Weighted Pupil (Dollars) Table XX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XX.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XX State Profile: Iowa Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXI.1 shows, in school year 1991-92, the state provided about 44 percent of the total funding to Kansas’ school districts. Total funding (state and local funds combined) per weighted pupil in Kansas averaged $4,973 with an implicit foundation level of $2,706 for each student, which is about 54 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.241, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .014, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Kansas education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXI.3 presents data on how state and local funding was distributed among the five groups of Kansas districts. Kansas’ equalization policies reduced the funding disparity between the wealthy and poor groups from about 68 percent to about 9 percent. Figure XXI.1 provides table information in graphic form. Appendix XXI State Profile: Kansas Funding per Weighted Pupil (Dollars) Table XXI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XXI State Profile: Kansas Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXII.1 shows, in school year 1991-92, the state provided 70 percent of the total funding to Kentucky’s school districts. Total funding (state and local funds combined) per weighted pupil in Kentucky averaged $3,728 with an implicit foundation level of $3,232 for each student, which is about 87 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.239, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .126, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXII.3 presents data on how state and local funding was distributed among the five groups of Kentucky districts. Kentucky’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 283 percent to about 15 percent. Figure XXII.1 provides table information in graphic form. Appendix XXII State Profile: Kentucky Funding per Weighted Pupil (Dollars) Table XXII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XXII State Profile: Kentucky Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXIII.1 shows, in school year 1991-92, the state provided about 62 percent of the total funding to Louisiana’s school districts. Total funding (state and local funds combined) per weighted pupil in Louisiana averaged $3,912 with an implicit foundation level of $2,433 for each student, which is about 62 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .216, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Louisiana education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXIII.3 presents data on how state and local funding was distributed among the five groups Louisiana districts. Louisiana’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 80 percent to about 21 percent. Figure XXIII.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table XXIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XXIII State Profile: Louisiana Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXIV.1 shows, in school year 1991-92, the state provided about 50 percent of the total funding to Maine’s school districts. Total funding (state and local funds combined) per weighted pupil in Maine averaged $5,681 with an implicit foundation level of $3,612 for each student, which is about 64 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.287, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .176, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXIV.3 presents data on how state and local funding was distributed among the five groups of Maine districts. Maine’s equalization policies reduced the total funding disparity between the wealthy and poor groups from about 100 percent to about 17 percent. Figure XXIV.1 provides table information in graphic form. Appendix XXIV State Profile: Maine Funding per Weighted Pupil (Dollars) Table XXIV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXIV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXIV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XXIV State Profile: Maine Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXV.1 shows, in school year 1991-92, the state provided about 40 percent of the total funding to Maryland’s school districts. Total funding (state and local funds combined) per weighted pupil in Maryland averaged $6,039 with an implicit foundation level of $3,819 for each student, which is about 63 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.566, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .469, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Maryland education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXV.3 presents data on how state and local funding was distributed among the five groups of Maryland districts. Maryland’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 217 percent to about 65 percent. Figure XXV.1 provides table information in graphic form. Appendix XXV State Profile: Maryland Funding per Weighted Pupil (Dollars) Table XXV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXVI.1 shows, in school year 1991-92, the state provided about 31 percent of the total funding to Massachusetts’ school districts. Total funding (state and local funds combined) per weighted pupil in Massachusetts averaged $6,264 with an implicit foundation level of $2,542 for each student, which is about 41 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.316, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .447, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Massachusetts education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXVI.3 presents data on how state and local funding was distributed among the five groups of Massachusetts districts. Massachusetts’ equalization policies reduced the funding disparity between the wealthy and poor groups from about 228 percent to about 54 percent. Figure XXVI.1 provides table information in graphic form. Appendix XXVI State Profile: Massachusetts Funding per Weighted Pupil (Dollars) Table XXVI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXVI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXVI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) State Funding Appendix XXVI State Profile: Massachusetts Funding per Weighted Pupil (Dollars) (1,000) As table XXVII.1 shows, in school year 1991-92, the state provided about 33 percent of the total funding to Michigan’s school districts. Total funding (state and local funds combined) per weighted pupil in Michigan averaged $5,851 with an implicit foundation level of $2,839 for each student, which is about 49 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.475, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .290, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Michigan education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXVII.3 presents data on how state and local funding was distributed among the five groups of Michigan districts. Michigan’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 208 percent to about 36 percent. Figure XXVII.1 provides table information in graphic form. Appendix XXVII State Profile: Michigan Funding per Weighted Pupil (Dollars) Table XXVII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXVII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXVII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) State Funding Appendix XXVII State Profile: Michigan Funding per Weighted Pupil (Dollars) (1,000) As table XXVIII.1 shows, in school year 1991-92, the state provided about 54 percent of the total funding to Minnesota’s school districts. Total funding (state and local funds combined) per weighted pupil in Minnesota averaged $5,646 with an implicit foundation level of $4,524 for each student, which is about 80 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.499, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .113, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Minnesota education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXVIII.3 presents data on how state and local funding was distributed among the five groups of Minnesota districts. Minnesota’s equalization policies reduced the funding disparity between the wealthy and poor groups from 133 percent to about 11 percent. Figure XXVIII.1 provides table information in graphic form. Appendix XXVIII State Profile: Minnesota Funding per Weighted Pupil (Dollars) Table XXVIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXVIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXVIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXVIII State Profile: Minnesota Funding per Weighted Pupil (Dollars) As table XXIX.1 shows, in school year 1991-92, the state provided about 64 percent of the total funding to Mississippi’s school districts. Total funding (state and local funds combined) per weighted pupil in Mississippi averaged $2,831 with an implicit foundation level of $1,860 for each student, which is about 66 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.020, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .007, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Mississippi education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXIX.3 presents data on how state and local funding was distributed among the five groups of Mississippi districts. Mississippi’s equalization policies eliminated the funding disparity between the wealthy and poor groups, with poor districts receiving about 2 percent more total funding than wealthy districts. Figure XXIX.1 provides table information in graphic form. Appendix XXIX State Profile: Mississippi Funding per Weighted Pupil (Dollars) Table XXIX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXIX.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXIX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XXIX State Profile: Mississippi Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXX.1 shows, in school year 1991-92, the state provided about 45 percent of the total funding to Missouri’s school districts. Total funding (state and local funds combined) per weighted pupil in Missouri averaged $3,972 with an implicit foundation level of $1,802 for each student, which is about 45 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.017, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .362, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Missouri education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXX.3 presents data on how state and local funding was distributed among the five groups of Missouri districts. Missouri’s equalization policies reduced the funding disparity between the wealthy and poor groups from 181 percent to about 70 percent. Figure XXX.1 provides table information in graphic form. Appendix XXX State Profile: Missouri Funding per Weighted Pupil (Dollars) Table XXX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXX.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XXX State Profile: Missouri Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XXXI.1 shows, in school year 1991-92, the state provided about 44 percent of the total funding to Montana’s school districts. Total funding (state and local funds combined) per weighted pupil in Montana averaged $4,835 with an implicit foundation level of $2,406 for each student, which is about 50 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.126, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .393, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Montana education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXI.3 presents data on how state and local funding was distributed among the five groups of Montana districts. Although Montana provided more state funding to wealthy districts than to poor districts, Montana’s equalization policies moderated the funding disparity between the wealthy and poor groups from about 104 percent to about 73 percent. Figure XXXI.1 provides table information in graphic form. Appendix XXXI State Profile: Montana Funding per Weighted Pupil (Dollars) Table XXXI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (1,000) State Funding Appendix XXXI State Profile: Montana Funding per Weighted Pupil (Dollars) (1,000) As table XXXII.1 shows, in school year 1991-92, the state provided about 34 percent of the total funding to Nebraska’s school districts. Total funding (state and local funds combined) per weighted pupil in Nebraska averaged $5,148 with an implicit foundation level of $2,203 for each student, which is about 43 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.246, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .154, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Nebraska education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXII.3 presents data on how state and local funding was distributed among the five groups of Nebraska districts. Nebraska’s equalization policies reduced the total funding disparity between the wealthy and poor groups from about 27 percent to about 5 percent. Figure XXXII.1 provides table information in graphic form. Appendix XXXII State Profile: Nebraska Funding per Weighted Pupil (Dollars) Table XXXII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXXII State Profile: Nebraska Funding per Weighted Pupil (Dollars) As table XXXIII.1 shows, in school year 1991-92, the state provided about 57 percent of the total funding to Nevada’s school districts. Total funding (state and local funds combined) per weighted pupil in Nevada averaged $3,597 with the same implicit foundation level, achieving an equalization effort of 100 percent. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –1.007, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was –.556, indicating that total funding increased as district income decreased. (To compare this score with those of other states, see fig. 1.) To put the state’s school finance system in perspective, table XXXIII.2 presents demographic data for 1991-92 for four groups of districts of increasing district income. Nevada was divided into four groups rather than five because of its student population distribution. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXIII.3 presents data on how state and local funding was distributed among the four groups of districts. Nevada’s equalization policies increased the funding that poor districts had compared with wealthy districts, resulting in wealthy districts having 31 percent less funding than poor districts. Figure XXXIII.1 provides table information in graphic form. Appendix XXXIII State Profile: Nevada Funding per Weighted Pupil (Dollars) Table XXXIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXXIII State Profile: Nevada Funding per Weighted Pupil (Dollars) As table XXXIV.1 shows, in school year 1991-92, the state provided about 8 percent of the total funding to New Hampshire’s school districts. Total funding (state and local funds combined) per weighted pupil in New Hampshire averaged $5,850 with an implicit foundation level of $764 for each student, which is about 13 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.571, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .238, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXIV.3 presents data on how state and local funding was distributed among the five groups of New Hampshire districts. New Hampshire’s equalization policies reduced the funding disparity between the wealthy and poor groups from 48 percent to about 30 percent. Figure XXXIV.1 provides table information in graphic form. Appendix XXXIV State Profile: New Hampshire Funding per Weighted Pupil (Dollars) Table XXXIV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXIV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXIV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) (4,000) State Funding Appendix XXXIV State Profile: New Hampshire Funding per Weighted Pupil (Dollars) (1,000) (2,000) (3,000) As table XXXV.1 shows, in school year 1991-92, the state provided about 43 percent of the total funding to New Jersey’s school districts. Total funding (state and local funds combined) per weighted pupil in New Jersey averaged $9,239 with an implicit foundation level of $4,399 for each student, which is about 48 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.104, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .168, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A New Jersey education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXV.3 presents data on how state and local funding was distributed among the five groups of New Jersey districts. New Jersey’s equalization policies reduced the funding disparity between the wealthy and poor groups from 247 percent to about 31 percent. Figure XXXV.1 provides table information in graphic form. Appendix XXXV State Profile: New Jersey Funding per Weighted Pupil (Dollars) Table XXXV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) State Funding Appendix XXXV State Profile: New Jersey Funding per Weighted Pupil (Dollars) (2,000) As table XXXVI.1 shows, in school year 1991-92, the state provided 85 percent of the total funding to New Mexico’s school districts. Total funding (state and local funds combined) per weighted pupil in New Mexico averaged $3,830 with an implicit foundation level of $3,254 for each student, which is 85 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .004, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXVI.3 presents data on how state and local funding was distributed among the five groups of New Mexico districts. New Mexico’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 33 percent to about 5 percent. Figure XXXVI.1 provides table information in graphic form. Appendix XXXVI State Profile: New Mexico Funding per Weighted Pupil (Dollars) Table XXXVI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXVI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXVI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXXVI State Profile: New Mexico Funding per Weighted Pupil (Dollars) As table XXXVII.1 shows, in school year 1991-92, the state provided about 43 percent of the total funding to New York’s school districts. Total funding (state and local funds combined) per weighted pupil in New York averaged $7,787 with an implicit foundation level of $5,240 for each student, which is about 67 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.578, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .370, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXVII.3 presents data on how state and local funding was distributed among the five groups of New York districts. New York’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 189 percent to 32 percent. Figure XXXVII.1 provides table information in graphic form. Appendix XXXVII State Profile: New York Funding per Weighted Pupil (Dollars) Table XXXVII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXVII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXVII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXXVII State Profile: New York Funding per Weighted Pupil (Dollars) As table XXXVIII.1 shows, in school year 1991-92, the state provided about 68 percent of the total funding to North Carolina’s school districts. Total funding (state and local funds combined) per weighted pupil in North Carolina averaged $4,424 with an implicit foundation level of $3,043 for each student, which is about 69 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.016, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) A North Carolina education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). The fiscal neutrality score was .250, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXVIII.3 presents data on how state and local funding was distributed among the five groups of North Carolina districts. North Carolina’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 110 percent to about 18 percent. Figure XXXVIII.1 provides table information in graphic form. Appendix XXXVIII State Profile: North Carolina Funding per Weighted Pupil (Dollars) Table XXXVIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXVIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXVIII.3. Funding of wealthiest group compared with poorest group(percent) This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXXVIII State Profile: North Carolina Funding per Weighted Pupil (Dollars) As table XXXIX.1 shows, in school year 1991-92, the state provided 48 percent of the total funding to North Dakota’s school districts. Total funding (state and local funds combined) per weighted pupil in North Dakota averaged $4,079 with an implicit foundation level of $1,957 for each student, which is 48 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .236, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A North Dakota education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XXXIX.3 presents data on how state and local funding was distributed among the five groups of North Dakota districts. North Dakota’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 48 percent to about 18 percent. Figure XXXIX.1 provides table information in graphic form. Appendix XXXIX State Profile: North Dakota Funding per Weighted Pupil (Dollars) Table XXXIX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XXXIX.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XXXIX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) State Funding Appendix XXXIX State Profile: North Dakota Funding per Weighted Pupil (Dollars) As table XL.1 shows, in school year 1991-92, the state provided about 42 percent of the total funding to Ohio’s school districts. Total funding (state and local funds combined) per weighted pupil in Ohio averaged $4,709 with an implicit foundation level of $2,325 for each student, which is about 49 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.180, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .315, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) An Ohio education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XL.3 presents data on how state and local funding was distributed among the five groups of Ohio districts. Ohio’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 110 to 32 percent. Figure XL.1 provides table information in graphic form. Appendix XL State Profile: Ohio Funding per Weighted Pupil (Dollars) Table XL.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XL.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XL.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XL State Profile: Ohio Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLI.1 shows, in school year 1991-92, the state provided about 71 percent of the total funding to Oklahoma’s school districts. Total funding (state and local funds combined) per weighted pupil in Oklahoma averaged $3,623 with an implicit foundation level of $2,838 for each student, which is about 78 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.102, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was –.053, indicating that total funding increased as district income decreased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLI.3 presents data on how state and local funding was distributed among the five groups of Oklahoma districts. Oklahoma’s equalization policies eliminated the 69 percent funding disparity between the wealthy and poor groups, resulting in poor districts having about 6 percent more funding than wealthy districts. Figure XLI.1 provides table information in graphic form. Appendix XLI State Profile: Oklahoma Funding per Weighted Pupil (Dollars) Table XLI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLI State Profile: Oklahoma Funding per Weighted Pupil (Dollars) Funding Per Weighted Pupil (Dollars) As table XLII.1 shows, in school year 1991-92, the state provided about 31 percent of the total funding to Oregon’s school districts. Total funding (state and local funds combined) per weighted pupil in Oregon averaged $5,087 with an implicit foundation level of $1,652 for each student, which is about 33 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.043, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .166, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) An Oregon education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLII.3 presents data on how state and local funding was distributed among the five groups of Oregon districts. Oregon’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 46 to 22 percent. Figure XLII.1 provides table information in graphic form. Appendix XLII State Profile: Oregon Funding per Weighted Pupil (Dollars) Table XLII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (1,000) State Funding Appendix XLII State Profile: Oregon Funding per Weighted Pupil (Dollars) (1,000) As table XLIII.1 shows, in school year 1991-92, the state provided 43 percent of the total funding to Pennsylvania’s school districts. Total funding (state and local funds combined) per weighted pupil in Pennsylvania averaged $6,406 with an implicit foundation level of $3,455 for each student, which is about 54 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.255, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .300, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLIII.3 presents data on how state and local funding was distributed among the five groups of Pennsylvania districts. Pennsylvania’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 142 to 32 percent. Figure XLIII.1 provides table information in graphic form. Appendix XLIII State Profile: Pennsylvania Funding per Weighted Pupil (Dollars) Table XLIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLIII State Profile: Pennsylvania Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLIV.1 shows, in school year 1991-92, the state provided about 39 percent of the total funding to Rhode Island’s school districts. Total funding (state and local funds combined) per weighted pupil in Rhode Island averaged $5,939 with an implicit foundation level of $3,953 for each student, which is about 67 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.694, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .274, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Rhode Island education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLIV.3 presents data on how state and local funding was distributed among the five groups of Rhode Island districts. Rhode Island’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 85 to 19 percent. Figure XLIV.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table XLIV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLIV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLIV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLIV State Profile: Rhode Island Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLV.1 shows, in school year 1991-92, the state provided about 52 percent of the total funding to South Carolina’s school districts. Total funding (state and local funds combined) per weighted pupil in South Carolina averaged $4,112 with an implicit foundation level of $3,239 for each student, which is about 79 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.505, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .150, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLV.3 presents data on how state and local funding was distributed among the five groups of South Carolina districts. South Carolina’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 69 to 8 percent. Figure XLV.1 provides table information in graphic form. Appendix XLV State Profile: South Carolina Funding per Weighted Pupil (Dollars) Table XLV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLV State Profile: South Carolina Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLVI.1 shows, in school year 1991-92, the state provided about 30 percent of the total funding to South Dakota’s school districts. Total funding (state and local funds combined) per weighted pupil in South Dakota averaged $3,756 with an implicit foundation level of $1,109 for each student, which is about 30 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .367, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLVI.3 presents data on how state and local funding was distributed among the five groups of South Dakota districts. South Dakota’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 66 to 28 percent. Figure XLVI.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table XLVI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLVI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLVI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLVI State Profile: South Dakota Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLVII.1 shows, in school year 1991-92, the state provided 47 percent of the total funding to Tennessee’s school districts. Total funding (state and local funds combined) per weighted pupil in Tennessee averaged $3,329 with an implicit foundation level of $1,566 for each student, which is 47 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .242, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Tennessee education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLVII.3 presents data on how state and local funding was distributed among the five groups of Tennessee districts. Tennessee’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 59 to 21 percent. Figure XLVII.1 provides table information in graphic form. Appendix XLVII State Profile: Tennessee Funding per Weighted Pupil (Dollars) Table XLVII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLVII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLVII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLVII State Profile: Tennessee Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLVIII.1 shows, in school year 1991-92, the state provided about 47 percent of the total funding to Texas’ school districts. Total funding (state and local funds combined) per weighted pupil in Texas averaged $4,603 with an implicit foundation level of $3,318 for each student, which is about 72 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.522, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .003, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Texas education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLVIII.3 presents data on how state and local funding was distributed among the five groups of Texas districts. Texas’ equalization policies eliminated the funding disparity between the wealthy and poor groups. Figure XLVIII.1 provides table information in graphic form. Appendix XLVIII State Profile: Texas Funding per Weighted Pupil (Dollars) Table XLVIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLVIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLVIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table XLIX.1 shows, in school year 1991-92, the state provided about 60 percent of the total funding to Utah’s school districts. Total funding (state and local funds combined) per weighted pupil in Utah averaged $3,177 with an implicit foundation level of $2,240 for each student, which is about 71 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.172, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .036, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) A Utah education official reported that the state had changed its school finance system since school year 1991-92 to increase funding to poor districts compared with wealthy districts (see app. LVI). 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table XLIX.3 presents data on how state and local funding was distributed among the five groups of Utah districts. Utah’s equalization policies eliminated the funding disparity between the wealthy and poor groups, resulting in poor districts having 1 percent more funding than wealthy districts. Figure XLIX.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table XLIX.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure XLIX.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure XLIX.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix XLIX State Profile: Utah Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table L.1 shows, in school year 1991-92, the state provided 29 percent of the total funding to Vermont’s school districts. Total funding (state and local funds combined) per weighted pupil in Vermont averaged $7,722 with an implicit foundation level of $3,453 for each student, which is about 45 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.539, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .176, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table L.3 presents data on how state and local funding was distributed among the five groups of Vermont districts. Vermont’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 91 to 31 percent. Figure L.1 provides table information in graphic form. Funding per Weighted Pupil (Dollars) Table L.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure L.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure L.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (2,000) State Funding Funding per Weighted Pupil (Dollars) (2,000) As table LI.1 shows, in school year 1991-92, the state provided 36 percent of the total funding to Virginia’s school districts. Total funding (state and local funds combined) per weighted pupil in Virginia averaged $4,713 with an implicit foundation level of $2,541 for each student, which is about 54 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.499, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .377, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table LI.3 presents data on how state and local funding was distributed among the five groups of Virginia districts. Virginia’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 168 to 38 percent. Figure LI.1 provides table information in graphic form. Appendix LI State Profile: Virginia Funding per Weighted Pupil (Dollars) Table LI.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure LI.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure LI.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Funding per Weighted Pupil (Dollars) (1,000) State Funding Appendix LI State Profile: Virginia Funding per Weighted Pupil (Dollars) (500) As table LII.1 shows, in school year 1991-92, the state provided about 75 percent of the total funding to Washington’s school districts. Total funding (state and local funds combined) per weighted pupil in Washington averaged $5,302 with an implicit foundation level of $4,025 for each student, which is about 76 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.009, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .055, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table LII.3 presents data on how state and local funding was distributed among the five groups of Washington districts. Washington’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 99 to 4 percent. Figure LII.1 provides table information in graphic form. Appendix LII State Profile: Washington Funding per Weighted Pupil (Dollars) Table LII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure LII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure LII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix LII State Profile: Washington Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table LIII.1 shows, in school year 1991-92, the state provided about 73 percent of the total funding to West Virginia’s school districts. Total funding (state and local funds combined) per weighted pupil in West Virginia averaged $4,927 with an implicit foundation level of $4,028 for each student, which is about 82 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.127, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .071, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) 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 of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table LIII.3 presents data on how state and local funding was distributed among the five groups of West Virginia districts. West Virginia’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 70 to 4 percent. Figure LIII.1 provides table information in graphic form. Appendix LIII State Profile: West Virginia Funding per Weighted Pupil (Dollars) Table LIII.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure LIII.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure LIII.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix LIII State Profile: West Virginia Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table LIV.1 shows, in school year 1991-92, the state provided about 46 percent of the total funding to Wisconsin’s school districts. Total funding (state and local funds combined) per weighted pupil in Wisconsin averaged $5,865 with an implicit foundation level of $3,439 for each student, which is about 59 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was –.270, indicating that state education funds were targeted to poor districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was .129, indicating that total funding increased as district income increased. (To compare this score with those of other states, see fig. 1.) To put the state’s school finance system in perspective, table LIV.2 presents demographic data for school year 1991-92 for five groups of districts of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table LIV.3 presents data on how state and local funding was distributed among the five groups of Wisconsin districts. Wisconsin’s equalization policies reduced the funding disparity between the wealthy and poor groups from about 74 to about 8 percent. Figure LIV.1 provides table information in graphic form. Appendix LIV State Profile: Wisconsin Funding per Weighted Pupil (Dollars) Table LIV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure LIV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure LIV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix LIV State Profile: Wisconsin Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) As table LV.1 shows, in school year 1991-92, the state provided about 53 percent of the total funding to Wyoming’s school districts. Total funding (state and local funds combined) per weighted pupil in Wyoming averaged $5,920 with an implicit foundation level of $3,111 for each student, which is about 53 percent of the average and represents the state’s equalization effort. (To compare this effort with those of other states, see fig. 5.) The targeting score for state funding was .000, indicating that state education funds were not targeted to poor or wealthy districts. (To compare this score with those of other states, see table V.1 in app. V.) The fiscal neutrality score was –.196, indicating that total funding increased as district income decreased. (To compare this score with those of other states, see fig. 1.) To put the state’s school finance system in perspective, table LV.2 presents demographic data for school year 1991-92 for five groups of districts of increasing district income. Average total funding per weighted pupilState share of total funding (percent) Targeting score (state funds) Local funding raised for every $1,000 of district income. Table LV.3 presents data on how state and local funding was distributed among the five groups of Wyoming districts. Wyoming’s equalization policies resulted in wealthy districts having 16 percent less funding than poor districts. Figure LV.1 provides table information in graphic form. Appendix LV State Profile: Wyoming Funding per Weighted Pupil (Dollars) Table LV.4 provides data on the distribution of state and local funding if all districts could have spent the average total funding per weighted pupil with an average tax effort. This assumes the state optimized its targeting effort without changing the state share or the total funding for education. Under this scenario, the implicit foundation level equals the maximum possible foundation level (the state average). Figure LV.2 provides this information in graphic form. The difference between how state funding was actually distributed and how it would have been distributed if districts could have financed the average is shown in figure LV.3. This is the local funding that could have been raised assuming all districts had made the same average tax effort. The average is the maximum foundation level possible in a state. Appendix LV State Profile: Wyoming Funding per Weighted Pupil (Dollars) Funding per Weighted Pupil (Dollars) In this report, we relied on state and local funding data from the 1991-92 school year. However, many states have made subsequent changes to their school finance system in response to legal changes or to concerns about equity. We telephoned officials in the 49 states to determine what changes had been implemented in the school finance system from school years 1991-92 through 1995-96. We specifically asked about changes in targeting that would affect low-wealth districts and changes in a state’s share of total funding. These two factors affect the implicit foundation level that all districts in a state can finance with the same minimum tax effort—the greater the targeting effort to low-wealth districts or the greater the state share, or both, the greater the implicit foundation level. Education officials in over half the states (25) said their state had not increased the targeting of state funds to low-wealth districts since school year 1991-92. Officials in the other 24 states reported that their state was targeting more or many more state funds to low-wealth districts. We did not verify the statements of the state officials. Fewer states had increased the state share of total funding significantly. Officials in eight states reported an increase of 6 percentage points or more in the state share. Officials in 38 states reported that their state’s share of total funding had a net increase or decrease of 5 percentage points or less, and 3 states reported a decrease of 6 percentage points or more. their local property taxes to maintain former spending levels. Table LVI.1 summarizes our findings of the changes states have made. Change in state share (percentage points) (continued) Change as of school year 1993-94. Change as of school year 1994-95. The percent change in one variable relative to a 1-percent change in another variable. In the context of this report, a state’s effort to compensate for differences in districts’ abilities to raise education revenues. The ratio of a state’s implicit foundation level to the maximum foundation level (the state average). Equity in school finances is concerned with the distribution of education funding or resources. To determine the equity of school finance systems, experts recommend considering the following four issues: (1) who is to benefit (taxpayers or public school students); (2) what objects are to be equally distributed, such as revenues or key resources (for example, curriculum and instruction), or outcomes (for example, student achievement); (3) what principle is to be used for determining whether distribution is equitable (such as vertical equity or fiscal neutrality); and (4) the statistic used to measure the degree of equity. A definition of equity that asserts that no relationship should exist between educational spending per pupil and local district income per pupil (or some other measure of fiscal capacity). In this study, a fiscal neutrality score of 0 indicates that no relationship exists between district funding and district income. The elasticity of total (state and local) funding relative to district income. The minimum amount of total funding per weighted pupil that a state’s equalization policies implicitly enable districts to spend with the same minimum local tax effort. The average amount of total funding per weighted pupil in a state. In this study, the tax effort is a ratio of a district’s local education revenue to its income. 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. U.S. General Accounting Office P.O. Box 6015 Gaithersburg, MD 20884-6015 Room 1100 700 4th St. NW (corner of 4th and G Sts. NW) U.S. General Accounting Office Washington, DC Orders may also be placed by calling (202) 512-6000 or by using fax number (301) 258-4066, or TDD (301) 413-0006. 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Summary: Pursuant to a congressional request, GAO reviewed funding gaps between poor and wealthy school districts, focusing on the: (1) size of the gap in total (state and local combined) funding between poor and wealthy school districts for each state; (2) key factors that affect the size of states' funding gaps; (3) effect of states' school finance policies on the funding gap; and (4) implications of this information for state policies. GAO found that: (1) although most states pursued strategies to supplement the local funding of poor school districts, wealthier districts in 37 states had more total (state and local combined) funding than poor districts in the 1991-92 school year; (2) this disparity existed even after adjusting for differences in geographic and student need-related education costs; (3) on average, wealthy districts had about 24 percent more total funding per weighted pupil than poor districts; (4) three factors affected the funding gap between a state's poor and wealthy districts; (5) first, the extent to which a state targeted funding to poor districts affected the funding gap; (6) although targeting efforts typically reduced funding gaps, they did not eliminate them; (7) second, a state's share of total funding can reduce the funding gap, even when the targeting effort is low; (8) finally, the local tax effort to raise education funding affected the funding gap; (9) at the local level, the greater the tax effort that poor districts were willing to make compared with wealthy districts, the smaller the gap in funding between these two types of districts; (10) poor districts in 35 states made a greater tax effort than wealthy districts; (11) because all three of these factors can affect the funding gap, analyzing the effects of state school finance policies required excluding the effects of the local tax effort; (12) to do this, GAO estimated the foundation level each state's school finance policies implicitly supported, which estimates the minimum total funding per pupil that districts could finance if they were to make the same local tax effort; (13) GAO's resulting analysis showed wide variations in the implicit foundation level that state school finance policies supported in school year 1991-92; (14) the implicit foundation levels of almost all states were less than their state average funding levels; (15) in 14 states, the implicit foundation level was less than half the state average funding level; (16) although the relative tax effort of poor and wealthy districts greatly affects the funding gaps between these districts, higher implicit foundation levels can help reduce the gaps; (17) therefore, states can further reduce the funding gaps by increasing their targeting effort to poor districts, increasing the state share of total funding, or increasing both; and (18) officials in a number of states reported making such changes between school years 1991-92 and 1995-96, although 25 states reported making little or no changes in their targeting of poor districts or state share.