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Examining Equity in Texas Public School Funding

Module by: Wayne Bingham, Timothy B. Jones, Sherion H. Jackson. E-mail the authors

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Note:

This module has been peer-reviewed, accepted, and sanctioned by the National Council of the Professors of Educational Administration (NCPEA) as a scholarly contribution to the knowledge base in educational administration.

Abstract

This research examined the level of equity of the public school funding system in Texas that in September of 2004 was held to be unconstitutional by a state district judge. The study also introduces a mechanism, referred to as the Revenue-to-Population Index or RTP Index, which compares funding equity within the unconstitutional system among 1031 public school districts in Texas. The index utilizes the total funds available to the school district and the school districts’ weighted average daily attendance (WADA). Data suggest a level of inequity within the unconstitutional funding system with regards to accessibility of state funds for PK-12 schools within Texas, as measured by the Gini-coefficient and the coefficient of variation. Additionally, data indicates an extremely wide (0.85 to 2.91) differentiation within the RTP Index, further documenting a degree of inequity of the public school funding system. A graphical representation suggests a high correlation between property wealth per WADA and revenue per WADA. This condition indicates a violation of the central principal of fiscal neutrality. The processes cited in this paper provide a system that can be used to correct disproportionate funding levels for PK-12 students across Texas, in compliance with legislative objectives and in full-compliance with the directives of the courts.

Funding Public Schools in Texas: How Do We Quantify Inequity?

On Wednesday, September 15, 2004, State District Judge John K. Dietz in the West Orange Case, declared the Texas system for funding its public schools to be unconstitutional. Judge Deitz noted that the $30 billion-a-year system was both inequitable and inadequate. (Stutz, Sept. 16, 2004). A review of newspaper articles, press releases, and reports on meetings held around the state regarding public school finance would indicate that Texas is on the verge of “plowing new ground” in school finance. If, as Keller (2004) proposes, “. . . every Texas school will be accountable for closing achievement gaps among subpopulations of students as a result of The No Child Left Behind Act of 2001,”and “. . . nearly three-quarters of Texas public school students live in districts that levy property taxes at or near the statutory cap of $1.50 per $100 of valuation” (p. 93) then the challenge becomes reviewing every aspect of school financing and available resources in hopes that this review might yield an appropriate methodology to address equity and access issues.

Background of the Problem

Historically, the development of a funding system for Texas public schools has been characterized by a series of starts and stops, primarily driven by economic conditions and political considerations. Though this has largely been an evolutionary process, it became more revolutionary in nature with the filing in the federal court system of Rodriquez v. San Antonio ISD (1971)which challenged the constitutionality of the Texas public school funding system. This effort was unsuccessful and was followed by Edgewood v. Bynum (1984) which challenged the Texas system in state court. The case was filed again as Edgewood v. Kirby (1985) and in 1989 the Texas Supreme Court reversed the appeals court decision and affirmed the trial court's decision that found the Texas system of public school finance unconstitutional (Walker & Casey, 1996). The basis of the ruling was that the Constitution calls for an "efficient system" and the Court found "an implicit link between efficiency and equality" (Edgewood v. Kirby, 1989). Not unlike other states, this ruling was followed by a series of legislative attempts to remedy the problems within the system. These attempts lead to successful legal challenges to subsequent legislative proposals. Finally, in 1993 with the passage of Senate Bill 7, the legislature was able to pass a funding bill that met constitutional muster. Senate Bill 7 provided the framework for the revised Texas school funding system, but still carried the title of the previous Foundation School Program.

The method provided in Senate Bill 7 for funding maintenance and operations consisted of a two-tiered system. Tier I is a Minimum Foundation Program and Tier II is a Guaranteed Yield component. This system is built on a partnership between the local district and the state and it relies heavily on local property taxation. The unique and controversial feature of this system is the provision for recapture of all local property taxes collected above a legislatively determined cap, called the Equalized Wealth Level (Texas Education Code, Title 2, Chapter41, 42, and 46).This program is commonly referred to as a “Robin Hood” plan because, effectively, it recaptures funds from property wealthy districts and reroutes that funding indirectly to property poor districts.

Within the recent Foundation School Program, Tier I required that local districts levy a $0.86/$100 valuation tax rate to provide the local share of the total cost of Tier I and guaranteed that the district would be able to access funds of $295,000 of property wealth per weighted student. Tier II allowed districts to levy an enrichment tax rate of up to $0.64/$100 valuation since M&O rates are legislatively limited to $1.50/$100 valuation. This helps ensure access to a property wealth level of $271,400 per student in Weighted Average Daily Attendance (WADA). The Equalized Wealth Level was set at $305,000 property wealth per WADA. Also built into the Foundation School Program are adjustments for differing educational needs of students through a weighted pupil approach and for varying local economic conditions by way of a Cost of Education Index (CEI) and size and sparsity adjustments.

A major addition to the original Senate Bill 7, relating to state school finance, has been the addition of assistance for funding for instructional facilities. This assistance is comprised of two parts. The first is the Instructional Facilities Allotment (IFA), which requires applications for assistance in building proposed new facilities. These applications are approved based on greatest need (determined by per-pupil local property wealth) until allocated funds are expended. The second part consists of the Existing Debt Allotment (EDA) and is used to assist districts with debt retirement requirements on old debt. The allotment for both IFA and EDA is a guaranteed yield at $35 per ADA per penny on the debt service tax rate. The provision of recapture does not apply to local funds for building new facilities or to the retirement of current debt (Texas Statutes, Texas Education Code, Title 2, Chapter 46). Although not widely known, and thus not often discussed, this is seemingly a critical point in assessing equity across the current funding system.

Additionally, this version of the Foundation School Program has been a large step forward in the equalization of funding for public school students in Texas. However, areas of contention continue to surface. The most divisive area appears to be the concept of recapture, which is a plan specifically designed to address equity in funding among the 1031 state independent school districts. Districts that have property wealth above the cap send large amounts of local revenue back into the system to be accessed by districts with less local property wealth per student. The existence and degree of contention in regard to this matter is largely a matter of perspective. The less contentious, but more pervasive area is that of capacity. The maximum tax rate for Texas school districts for funding current year operations is $1.50 per $100 valuation. For fiscal year 2004, 60% of the districts had M&O tax rates of $1.46 to $1.50 (Thompson, 2004). At this point, under the above constraints, equity becomes an issue.

Judge Dietz’s ruling of September 15, 2004 gave the legislature one year to replace the system with one that is constitutionally acceptable. At that time, the Attorney General of the State of Texas noted that the state would appeal the ruling directly to the Texas Supreme Court in order to resolve the issues raised by the trial court. In the state of Texas, the issue of funding equity has been the driving force for many changes occurring in the way the state funds its schools. The recent standard tends to focus on providing equal access to funds at substantially equal tax effort in order to address these gaps (Thompson, 2003). The numbers would indicate that there still exist considerable differences in available revenue between property-rich and property-poor school districts. For example, the system has never closed the gap to the $600 promised in Edgewood IV. The gap has actually widened to over $1,000 (Equity Center Positions of the West Orange-Cove Case, 2003). Funding policies that continue to allow and/or exacerbate the ability for some districts to have access to needed funds include the following two issues.

  1. Adjusting for localized differences in the cost of providing educational services. The current Cost of Education Index (CEI) is dated and is in need of revision with more accurate and appropriate statistical measures for determining local differences in costs (Taylor, 2004).
  2. Accounting for individual differences in student educational needs. The current system of weighted pupils is generally accepted, but perhaps needs study in regard to the validity of the assigned weights. WADA is a statistical adjustment that is not exactly equal to the number of actual weighted students, a difference that is not generally understood.

Though equity is the focus of many studies, this study concentrates on accessibility to the funding. Accessibility, by definition, is not how much funding school districts have but how much funding districts have access to or how much is available to them. Districts unable to access the total amount of funding allotted, for one reason or another, have little recourse but to place themselves into the inequitable arena.

Purpose of the Study

The purpose of this study was to examine the degree of equity in funds available for access through the current funding system for public schools in Texas. More specifically, this study statistically addressed the accessibility of funding in the Texas Foundation School Program and then defined a new process, the Revenue-to-Population Index or RTP Index, to compare each school district based on this data.

Significance of the Study

This research is significant in three major areas. First and foremost, current literature on state formula funding in Texas has not used a normalized statistical technique in assessing the equity of the formula funding system, as measured by school district size and WADA access to funding, compared against the funds districts and students actually receive. Second, current literature does not provide a means of comparing equity or inequity among individual school districts across the state. This deficiency must be addressed in order to further reforms and to contribute substantively to the dialogue on restructuring the current system. With so much history of revision, legal challenges and the like, it is seemingly obvious that a fresh, new, critical look at the system is in order. Finally, as alternatives and changes to the Foundation School Program in Texas are contemplated, this study provides a vehicle, the RTP Index, for comparing the equity merits of new, existing, and/or emerging proposals.

Methodology

This project utilized a quasi causal-comparative research design. Specifically, the researchers, utilizing current data provided by the Texas Education Agency, set out to determine “consequences of differences that already exist between or among groups” (Fraenkel & Wallen, 2003). In the case of this research project, both school districts and WADA were considered as parts of the analysis. While this study does examine differences that have already occurred and were thus analyzed retrospectively, the term “quasi” was added to the design description because this research also attempts to formulate a method for analyzing future proposals of formula funding within the state. This final additional element takes this design out of the scope of Fraenkel and Wallen’s definition and moves it into the quasi-comparative arena.

Research Questions

This research was guided by the following research questions:

1.What is the degree of equity and fiscal neutrality in the methodology for providing access to funds in the current system of formula funding in the Texas Foundation School Program?

2.How do Texas School Districts compare in equity to other school districts as measured by percent of weighted student versus percent of available formula funding-generated dollars?

Population and Sample

In responding to the first research question, the total population was considered and a purposeful sample of the population was collected and utilized “to select unique cases that are especially informative” (Neuman, 2004). Since 82% of WADA in the state of Texas are consider to be in Tier II districts, our purposeful sample was designed to include the 18% of those outside Tier II. Therefore, the selected sample population consisted of the upper 18% and the lower 18% of WADA ranked by per WADA revenue. This sample was selected from the total population of public independent school districts in Texas (n=1031) that were eligible to access state formula-funding. All students within the State of Texas equate to

5, 336,535. Thus the purposeful sample utilizes the bottom 18% and the top 18% or approximately 1,923,083. The purposeful sample of 36% of the state’s total WADA equates to 774 public school districts (N=774). This sample was utilized in order to omit the repetition of districts falling within the Tier II funding system. The intent of drawing this purposeful sample of the population was to examine the true inequities within the system.

In order to address the second research question, the total population was analyzed. This total population consisted of all 1031 school districts in the State of Texas. Data from the total population were collected and utilized. Charter schools and private schools were intentionally omitted from this study due to a funding system that is not related to local property wealth.

Data Collection and Analysis

Data were collected from both online sources including the Texas Education Agency and the Equity Center in Austin, Texas. Specifically, data from the 2004 fiscal year were used as it represented the last completed year of state funding. The definition of state funding used in this report assumes that all districts are at $1.50 M&O and $.29 of existing debt allotment. In order to address the two research questions, the study then utilized three statistical treatments for equity analysis of this data and a graphical representation for fiscal neutrality. This study utilized three of the most commonly used measures of equity which have been associated with previous studies in school finance, i.e. the Gini coefficient, the coefficient of variation, the Verstegen Index, and a graphical representation of fiscal neutrality.

The Gini coefficient is used as a major indicator of the equity in the formula funding mechanism employed by the state of Texas. The decision to use this statistical procedure to demonstrate the relative equity in wealth access across schools districts is based on the definition of the Gini coefficient noting that this procedure takes into account the total range of data within the set. It is important to note that rather than pupil counts, such as ADA, this study used Weighted Average Daily Attendance (WADA) because this variable primarily drives funding in the Foundation School Program. The exception to this was in calculating the funding driven by Chapter 46 (facilities funding) where Average Daily Attendance (ADA) was noted as the metric to be used (pupil count).

The Gini coefficient is derived from the Lorenz curve, a cumulative frequency curve that compares the distribution of a specific variable with the uniform distribution that represents equality. A diagonal line represents perfect equality, and the greater the deviation of the Lorenz curves from this line, the greater the inequality. The Gini coefficient is double the area between the equality diagonal and the Lorenz curve, bounded below by zero (perfect equality) and above by one (the case when a single member of the population holds all of a particular resource.) The purest use of the Gini occurs when individual data are used. If only group data is available, the Lorenz curve will not be precise (Hale, 2001). This study used individual data as the revenue available to each WADA in the state as part of the sample; therefore the Gini coefficient analysis was utilized. The Verstegen Index was also utilized to measure the degree of concentration of resources in the top half of the distribution (Odden & Picus, 2004). This measurement calculates the ratio of the total amount of resources above the median and the amount that would be available to the same number of observations at the median per WADA revenue. The coefficient of variation among districts and WADA is shown to illustrate the percent variation about the mean (Odden & Picus, 2004). The coefficient of variation is simply the standard deviation divided by the mean. This study used a graphical treatment for illustration of fiscal neutrality in the Foundation School Program. Specifically, a graph was formulated to represent each school district’s available revenue per WADA plotted in relationship to the school property wealth per WADA.

Presentation of the Data

In this section, data are presented and discussed to address each of the research questions. The Lorenz curves, as explained in the previous section, are depicted in Figures 1 and 2. The results of the analysis are provided in Table 1 with benchmarks that are widely accepted in the research community. A graph illustrating Fiscal Neutrality is provided as Figure 3.

Research Question 1

What is the degree of equity and fiscal neutrality in the methodology for providing access to funds in the current system of formula funding in the Texas Foundation School Program?

The degree of equity and fiscal neutrality in the methodology for providing access to funds in the current formula funding in the Foundation School Program was analyzed. This analysis focused on the revenue available or accessible to districts rather than the amounts of revenue that districts actually receive. This approach allowed the focus to be placed on the system and not on the actions of the individual districts since revenue realized by individual school districts reflected local tax rates and tax collection procedures.

Figure 1. Population.

figure1texas.jpg

Portion of Population per 5,336,535 WADAPortion of Revenue

The analysis of Research Question 1 was completed on the total of revenue available in the Foundation School Program. This study presents two perspectives by which to apply the tests for equity in the system. The entire system (Figure 1) is evaluated which includes all WADA and districts and a sample population (Figure 2) was also analyzed using the Gini Coefficient and the Lorenz Curve.

Figure 2. Purposeful sample population (Top and Bottom 18% of the Population).

figure2texas.jpg

Portion of Purposeful Sample Population per 5,336,535 WADAPortion of Revenue

The purposeful sample included the 18% of WADA receiving the lowest per WADA revenue and the 18% of WADA receiving the largest portion per WADA revenue. The purposeful sample is presented as an alternative that would, perhaps, compensate for the potential masking of differences in per WADA funding due to the enormity of the system. As mentioned before, the 18% figure was arrived at because the system is, seemingly, equalized at the 82nd percentile.

The results of the statistical treatments are interesting even if somewhat contradictory. The Gini coefficient based on the total system is well within the benchmark for equity; however the Gini coefficient for the purposeful sample demonstrates the existence of considerable inequity. This mixed result, seemingly indicates that the magnitude of the numbers tend to mask the differences in funding levels.

Table 1

Results of Statistical Procedures on Both Population and Stratified Sample

Table 1
Statistical Treatment Participants Benchmark
  Population PurposefulSample  
Gini coefficient 0.03 0.06 * 0.05
Verstegen Index 1.06 * 1.13 * 1.00
Coefficient of Variation(WADA) 0.09 0.13* 0.10
Coefficient of Variation(District) 0.19 * 0.21* 0.10

* Exceeds Benchmark (Odden & Picus, 2004, pp. 64-67)

The coefficient of variation of 0.19 by district for the total system and 0.21 (Table 1) for the purposeful sample population (by district) are, in both cases, outside the benchmark of 0.10. These results would indicate that there are great differences in the amount of per WADA revenues available between those with the greatest access and those at the level of least access.The Verstegen Index (Table 1) of 1.06 for the total system and 1.12 for the sample population indicates by the range above 1.0 (1.0 indicating equal), that there is a considerable amount of per pupil revenues concentrated in the upper half of per pupil revenue access as compared to those at the median. The Verstegen Index is the actual revenue in the upper 50% of observation as compared to revenue available for the same observation at the median revenue.

Examination of the graph (Figure 3) illustrating fiscal neutrality in the system indicates that there continues to be a significant relationship between per WADA property value and per WADA revenue. This relationship is particularly strong at the extreme end of the per WADA property value scale (x-axis). The spikes in the per WADA revenue graph for those in the lower (approximately 80%) segment of property wealth are, seemingly, due to differences in leveling revenue such as CEI and district size adjustments.

Figure 3. Fiscal Neutrality.

figure3texas.jpg

Property Wealth per WADARevenue per WADA

Research Question 2

How do Texas School Districts compare in equity to other school districts as measured by percent of weighted student versus percent of available formula funding-generated dollars?

In order to compare equity in available funding access among the 1031 school districts in Texas, the “Revenue-to-Population” (RTP) Index was developed within this study for the purpose of creating a simplified method of comparison between available funding for districts. The index was calculated by dividing the percentage of school district funds which were available to each district by the total weighted average daily attendance within the district. The result was a number that could be easily understood and compared. The RTP Indexwas calculated as follows:

Percentage of Funds Available (PFA)

--------------------------------------------- = RTP Index

Percentage of Total WADA (PTW)

The RTP Index was calculated for each district based on its WADA and total access to funds in the Foundation School Program. This is a combined composite index representing the discrepancy, if it exists, in school funding equity at the individual district level. The RTP Index was then used to calculate available funding equity across the 1031 school districts in Texas. This index can be used to represent the funding which districts receive compared to that which is available to each district.

Data are presented in regard to the ratio of percent of revenue to the percent of population. A complete listing of RTP Indices for all Texas public schools can be found in the appendix A. The listing is compiled in ascending order by district number in Appendix A and in ascending order in Appendix B, by RTP Index Rank. The RTP Index is based on the assumption that in a totally equitable system (in terms of access to revenue) that every WADA and district would have an RTP Index of 1. Interestingly, the actual RTP Indexes for the 1031 school districts in Texas ranged from 0.85 to 2.91. That is, whatever percent of total population a student (WADA) represents, that individual would receive the same percent of available revenue so in a totally equitable system of 1% WADA would receive 1% of the available formula revenue.

In the case of the Foundation School Program, where the mean of per WADA revenue is $5428, a WADA in a district with an RTP Index of 0.85 would have access to 85% of $5428 or $4614, which would be $844 less than the district’s equitable entitlement per WADA. Conversely, a district with an RTP Index of 1.45 is receiving 145% of the equitable WADA. This equates to $7870 per WADA or $2442 more than the equitable amount of $5428. In this case, the district with the higher RTP Index is receiving $3256 more per WADA than the school district with the RTP Index of .85. Thus, the significant range of RTP values clearly suggests a marked difference in the amount of revenue available for school districts in the Foundation School Program.

Findings and Conclusions

The intent of this research was to provide some insights into the relative equity of the access to funds in the Texas Foundation School Program. Based on 2004 fiscal data and regulations in place at that time, the system was providing funding for more than five million WADA and access to funds nearing thirty billion dollars ($30 Billion). The analysis of the data reveals a system that is reasonably equitable in terms of the most widely accepted methods of analysis. Enthusiasm must be tempered for the degree of equity demonstrated by the Gini coefficient in light of the wide disparity in available funding within the system by the unacceptably high levels of variance as shown in the coefficients of variation by WADA and by District. There is also a concentration of per pupil revenue in the upper 50% of that hierarchy, along with a troubling relationship between per WADA property wealth and per WADA revenue.

The processes of performing these statistical tests are quite illuminating in regard to what issues drive these variations in available per pupil revenue. Seemingly, these disparities are exacerbated by the following factors:

  • Availability of revenue for property wealthy districts between the level of absolute equalization and the $305,000 property wealth per WADA cap on the system
  • Hold-harmless clauses that allow Chapter 41 districts access to property wealth far above the cap level
  • A percentage reduction in amounts of recapture for meeting certain criteria
  • The method of disbursement of the per capita allotment
  • No recapture on funds accessed for facilities

Any analysis of the data will reveal that the Foundation School Program is heavily reliant on local property taxes. Further examination indicates that in any school funding system that relies on property taxes to fund or supplement the system, equity and recapture are inseparable. It follows immediately that the greater the reliance on local property taxes, the more volatile the issue becomes between those who insist on equity and those who resent recapture.

The RTP Index values provided in Appendix A and Appendix B give voice to the equity and inequity of the system by providing a means of comparing and communicating the differences among districts. This index also gives key district leaders and policy-makers important data for identifying potential funding short-falls for their district in order to bring about dialog and subsequent actions for eliminating such short-falls. This index will also lead to examination of these short-falls in order to unmask issues surrounding funding availability.

Data in the study also give voice to the importance of accessing all funds available in the formula-funding system and thus the concern that some school districts may not be accessing the full funding available to them. It is a common factor for funding to be unavailable to districts due to some economic anomaly. It is of little use to districts to have available funding and not have the ability to obtain or access and use these funds. This anomaly widens the inequity gap and further complicates the problem of equitable funding for school districts. The RTP Index developed within this study can be used to simplify communications concerning the current funding system and to address its effects upon districts. It is important to note that districts not reaching equity of 1.0 on the RTP Index should seek to identify reasons for this short-fall whether it is current lack in Average Daily Attendance or disparities in taxes owed or taxes paid.

As Texas moves toward revisions in the public school funding system, the RTP Index can also be used to gauge the equity of any proposed funding systems before engagement. Further, the RTP Index gives individual school district leaders and school boards a means to compare their district’s equity position in comparison to the state funding system as well as other school districts in similar situations.

As discussed at the beginning of this article, the Texas public school finance system has been in and out of court for much of the last two decades. This reality clearly indicates the need for a new look at the funding equity questions across the system and the need for benchmarking the existing system in order to facilitate future system revisions. It is this benchmarking that becomes the major implication of this research. It is only when we completely understand the implications of changing funding formulas or continuing to use existing systems, that policy and lawmakers can chart a path for improvement. By using the RTP Index to pin-point funding availability we can vastly improve the tracking of these inequities. Hopefully the use of this technique can also reduce the likelihood that future funding systems will end up in the court system, as a result of challenges posed by individuals or districts that are perceived as not being treated fairly. Under a democratic system, fair and equitable treatment under the law is the expectation and the right of every citizen.

References

Equity center positions on the West Orange-Cove Case. (2003). Contained in Invitation to Tier II Districts to Join the Alvarado Intervenors in the West Orange-Cove Case. Alvarado Internevors Committee: Dr. Ernie Laurence, Chariman.

Edgewood V. Kirby 777 S.W.2d 391 (Tex. 1989).

Fraenkel, J. R., & Wallen, N. F. (2003). How to design and evaluate research in education (5th edition). Boston, MA: McGraw Hill.

Gronberg, T. J., Jansen, D. W., Taylor, L. L., & Booker, K. (2004). School outcomes and school costs: The cost function approach. Unpublished Report to The Texas Joint Select Committee on Public School Finance.

Keller, H. (2004). Confronting the constitutional challenges. Putting the Sides Together. Texas Public Policy Foundation. p. 93.

Hale, J. T. (2001). School finance and equity in Texas. Retrieved on January 14, 2005 from http://uts.cc.utexas.edu/~jthale/inequality.htm

Lavine, D. (2004). Show me the money. Putting the Sides Together. Texas Public Policy Foundation.

Neuman, W. L. (2004). Basics of social research. Boston: Allyn and Bacon/Pearson. pp. 138–139.

Odden, A. R., & Picus, L. O., (2004). School finance: A policy perspective, (3rd ed.). New York: McGraw Hill. pp. 64–67.

Picus, L. O., Odden, A., & Fermanich, M. (2004). Assessing the equity of Kentucky's SEEK formula: A 10-Year analysis. Journal of Education Finance,29(4), pp. 315–336.

Pierce, W. (September 16, 2004). Legal: Reaction to the ruling. Retrieved on September 17, 2004 from http://texasisd.com/

Schlomack, B. ( September 16, 2004). No matter who wins school finance lawsuit, taxpayers lose. Texas Public Policy Foundation. Retrieved on July 15, 2006 from http://www.texaspolicy.com/pdf/2004-08-25-southwestsun-suing.pdf

School Facts Sheet. Retrieved on April 3, 2004 from http://www.tgslc.org/tgslc/schlfs/

School Finance in Texas. Retrieved on April 3, 2004 from http://www.cppp.org/kidscount/education/finance.html

Stutz, Terence. (Sept. 16, 2004). Robin Hood’ system rejected. Dallas Morning News. Austin Bureau. Retrieved on November 13, 2004 from http://nieer.org/news/index.php?NewsID=925

Swanson, A. D. & King, R. A. (1997). School Finance: Its Economics and Politics. New York: Addison Wesley, Longman.

Taylor, L.L. (2004). Adjusting for geographic variations in teacher compensation: Updating the Texas CEI. Executive Summary. Unpublished Report to The Joint Select Committee on Public School Finance.

Texas Education Code: Chapter 41. (2002). Manual for districts subject to wealth equalization. Texas Education Agency: Austin.

Texas Education Code, Title 2, Chapter41-42. Texas Statutes. Retrieved on January 10, 2005 from http://www.capitol.state.tx.us/statutes/ed.toc.htm

Texas Education Code, Title 2, Chapter 46. Texas Statutes. Retrieved on January 10, 2005 from http://www.capitol.state.tx.us/statutes/ed.toc.htm

Texas school finance: Revenue generation for Texas public schools. Education Service Center, Region 20. Retrieved on April 3, 2004 from http://www.capitol.state.tx.us/psf/9_10_03/Smith-Stavinoha%20Presentation.pdf

Thompson, D. (2003). Texas public school finance: A look at where we have been-and where we are headed. Unpublished Document.

Thompson, D. (2004). The financing of Texas public schools: An update on the litigation. Featured strand on school finance summary: Texas Association of School Administrators.

Vedder, R., & Hall, J. (2004). Effective, efficient, fair: Paying for public education in Texas. Texas Public Policy Foundation.

Walker, B. D., & Casey, D. T. (1996). The Basics of Texas Public School Finance (6th ed). Texas Association of School Boards: Austin.

West Orange-Cove Consolidated Independent School District V. Alanis, 107 S.W.3d 558 (Tex. 2003).

Appendix A

Table 2
001902 CAYUGA ISD 0.95
001903 ELKHART ISD 0.95
001904 FRANKSTON ISD 0.94
001906 NECHES ISD 0.93
001907 PALESTINE ISD 0.97
001908 WESTWOOD ISD 0.95
001909 SLOCUM ISD 0.94
002901 ANDREWS ISD 1.20
003902 HUDSON ISD 0.97
003903 LUFKIN ISD 0.97
003904 HUNTINGTON ISD 0.96
003905 DIBOLL ISD 0.96
003906 ZAVALLA ISD 0.95
003907 CENTRAL ISD 0.96
004901 ARANSAS COUNTY ISD 0.98
005901 ARCHER CITY ISD 0.93
005902 HOLLIDAY ISD 0.96
005903 MEGARGEL ISD 0.90
005904 WINDTHORST ISD 0.95
006902 CLAUDE ISD 0.92
007901 CHARLOTTE ISD 0.94
007902 JOURDANTON ISD 0.95
007904 LYTLE ISD 0.96
007905 PLEASANTON ISD 0.96
007906 POTEET ISD 0.96
008901 BELLVILLE ISD 0.98
008902 SEALY ISD 0.97
008903 BRAZOS ISD 0.95
009901 MULESHOE ISD 0.95
010901 MEDINA ISD 0.91
010902 BANDERA ISD 0.98
011901 BASTROP ISD 0.99
011902 ELGIN ISD 0.97
011904 SMITHVILLE ISD 0.98
011905 MCDADE ISD 0.94
012901 SEYMOUR ISD 0.93
013901 BEEVILLE ISD 0.97
013902 PAWNEE ISD 1.17
013903 PETTUS ISD 0.93
013905 SKIDMORE-TYNAN ISD 0.95
014901 ACADEMY ISD 0.95
014902 BARTLETT ISD 0.93
014903 BELTON ISD 0.98
014905 HOLLAND ISD 0.94
014906 KILLEEN ISD 0.98
014907 ROGERS ISD 0.95
014908 SALADO ISD 0.96
014909 TEMPLE ISD 0.97
014910 TROY ISD 0.95
015901 ALAMO HEIGHTS ISD 1.29
015904 HARLANDALE ISD 0.97
015905 EDGEWOOD ISD 0.96
015907 SAN ANTONIO ISD 0.96
015908 SOUTH SAN ANTONIO ISD 0.97
015909 SOMERSET ISD 0.97
015910 NORTH EAST ISD 0.97
015911 EAST CENTRAL ISD 0.99
015912 SOUTHWEST ISD 0.98
015915 NORTHSIDE ISD 0.98
015916 JUDSON ISD 0.98
015917 SOUTHSIDE ISD 0.98
016901 JOHNSON CITY ISD 0.96
016902 BLANCO ISD 0.94
017901 BORDEN COUNTY ISD 2.37
018901 CLIFTON ISD 0.95
018902 MERIDIAN ISD 0.93
018903 MORGAN ISD 0.92
018904 VALLEY MILLS ISD 0.94
018905 WALNUT SPRINGS ISD 0.93
018906 IREDELL ISD 0.92
018907 KOPPERL ISD 0.94
018908 CRANFILLS GAP ISD 0.91
019901 DEKALB ISD 0.93
019902 HOOKS ISD 0.93
019903 MAUD ISD 0.93
019905 NEW BOSTON ISD 0.95
019906 REDWATER ISD 0.95
019907 TEXARKANA ISD 0.95
019908 LIBERTY-EYLAU ISD 0.95
019909 SIMMS ISD 0.92
019910 MALTA ISD 0.92
019911 RED LICK ISD 0.94
019912 PLEASANT GROVE ISD 0.96
019913 HUBBARD ISD 0.92
019914 LEARY ISD 0.92
020901 ALVIN ISD 0.98
020902 ANGLETON ISD 0.98
020904 DANBURY ISD 0.95
020905 BRAZOSPORT ISD 1.14
020906 SWEENY ISD 1.26
020907 COLUMBIA-BRAZORIA ISD 0.98
020908 PEARLAND ISD 1.00
020910 DAMON ISD 0.95
021901 COLLEGE STATION ISD 1.18
021902 BRYAN ISD 0.98
022004 TERLINGUA CSD 0.97
022901 ALPINE ISD 0.94
022902 MARATHON ISD 0.92
022903 SAN VICENTE ISD 0.85
023902 SILVERTON ISD 0.92
024901 BROOKS COUNTY ISD 0.95
025901 BANGS ISD 0.95
025902 BROWNWOOD ISD 0.95
025904 BLANKET ISD 0.92
025905 MAY ISD 0.93
025906 ZEPHYR ISD 0.93
025908 BROOKESMITH ISD 0.94
025909 EARLY ISD 0.95
026901 CALDWELL ISD 0.97
026902 SOMERVILLE ISD 0.94
026903 SNOOK ISD 0.94
027903 BURNET CONS ISD 0.98
027904 MARBLE FALLS ISD 1.04
028902 LOCKHART ISD 0.97
028903 LULING ISD 0.96
028906 PRAIRIE LEA ISD 0.93
029901 CALHOUN CO ISD 1.42
030901 CROSS PLAINS ISD 0.93
030902 CLYDE CONS ISD 0.96
030903 BAIRD ISD 0.91
030906 EULA ISD 0.93
031901 BROWNSVILLE ISD 0.97
031903 HARLINGEN CONS ISD 0.98
031905 LA FERIA ISD 0.98
031906 LOS FRESNOS CONS ISD 0.99
031909 POINT ISABEL ISD 1.31
031911 RIO HONDO ISD 0.97
031912 SAN BENITO CONS ISD 0.98
031913 SANTA MARIA ISD 0.95
031914 SANTA ROSA ISD 0.96
032902 PITTSBURG ISD 0.96
033901 GROOM ISD 0.96
033902 PANHANDLE ISD 0.96
033904 WHITE DEER ISD 1.17
034901 ATLANTA ISD 0.96
034902 AVINGER ISD 0.92
034903 HUGHES SPRINGS ISD 0.94
034905 LINDEN-KILDARE CONS ISD 0.95
034906 MCLEOD ISD 0.94
034907 QUEEN CITY ISD 0.95
034908 MARIETTA ISD 0.91
034909 BLOOMBURG ISD 0.92
035901 DIMMITT ISD 0.94
035902 HART ISD 0.93
035903 NAZARETH ISD 0.95
036901 ANAHUAC ISD 0.97
036902 BARBERS HILL ISD 1.41
036903 EAST CHAMBERS ISD 0.96
037901 ALTO ISD 0.94
037904 JACKSONVILLE ISD 0.98
037907 RUSK ISD 0.98
037908 NEW SUMMERFIELD ISD 0.93
037909 WELLS ISD 0.93
038901 CHILDRESS ISD 0.93
039901 BYERS ISD 0.91
039902 HENRIETTA ISD 0.94
039903 PETROLIA ISD 0.94
039904 BELLEVUE ISD 0.94
039905 MIDWAY ISD 0.93
040901 MORTON ISD 0.93
040902 WHITEFACE CONS ISD 1.49
041901 BRONTE ISD 0.90
041902 ROBERT LEE ISD 0.91
042901 COLEMAN ISD 0.94
042903 SANTA ANNA ISD 0.93
042905 PANTHER CREEK CONS ISD 0.94
042906 NOVICE ISD 0.96
043901 ALLEN ISD 0.98
043902 ANNA ISD 0.96
043903 CELINA ISD 0.98
043904 FARMERSVILLE ISD 0.97
043905 FRISCO ISD 1.32
043907 MCKINNEY ISD 0.97
043908 MELISSA ISD 0.95
043910 PLANO ISD 1.19
043911 PRINCETON ISD 0.97
043912 PROSPER ISD 0.97
043914 WYLIE ISD 0.99
043917 BLUE RIDGE ISD 0.95
043918 COMMUNITY ISD 0.97
043919 LOVEJOY ISD 1.95
044902 WELLINGTON ISD 0.92
044904 SAMNORWOOD ISD 0.90
045902 COLUMBUS ISD 0.96
045903 RICE CONS ISD 0.95
045905 WEIMAR ISD 0.93
046901 NEW BRAUNFELS ISD 0.98
046902 COMAL ISD 1.06
047901 COMANCHE ISD 0.95
047902 DE LEON ISD 0.94
047903 GUSTINE ISD 0.93
047905 SIDNEY ISD 0.91
048901 EDEN C I S D 0.93
048903 PAINT ROCK ISD 0.93
049901 GAINESVILLE ISD 0.96
049902 MUENSTER ISD 0.94
049903 VALLEY VIEW ISD 0.96
049905 CALLISBURG ISD 0.97
049906 ERA ISD 0.95
049907 LINDSAY ISD 0.95
049908 WALNUT BEND ISD 0.93
049909 SIVELLS BEND ISD 1.11
050901 EVANT ISD 0.94
050902 GATESVILLE ISD 0.97
050904 OGLESBY ISD 0.93
050909 JONESBORO ISD 0.95
050910 COPPERAS COVE ISD 0.98
051901 PADUCAH ISD 0.92
052901 CRANE ISD 1.38
053001 CROCKETT CO CONS CSD 2.41
054901 CROSBYTON ISD 0.91
054902 LORENZO ISD 0.94
054903 RALLS ISD 0.93
055901 CULBERSON COUNTY-ALLAMOORE ISD 0.92
056901 DALHART ISD 0.95
056902 TEXLINE ISD 0.98
057903 CARROLLTON-FARMERS BRANCH ISD 1.14
057904 CEDAR HILL ISD 0.97
057905 DALLAS ISD 1.01
057906 DESOTO ISD 0.98
057907 DUNCANVILLE ISD 0.97
057909 GARLAND ISD 0.98
057910 GRAND PRAIRIE ISD 0.97
057911 HIGHLAND PARK ISD (Dallas County) 1.54
057912 IRVING ISD 0.96
057913 LANCASTER ISD 0.96
057914 MESQUITE ISD 0.98
057916 RICHARDSON ISD 1.08
057919 SUNNYVALE ISD 1.44
057920 WILMER-HUTCHINS ISD 0.96
057922 COPPELL ISD 1.20
058902 DAWSON ISD 1.32
058905 KLONDIKE ISD 1.22
058906 LAMESA ISD 0.96
058909 SANDS CISD 0.97
059901 HEREFORD ISD 0.96
059902 WALCOTT ISD 1.01
060902 COOPER ISD 0.95
060914 FANNINDEL ISD 0.95
061901 DENTON ISD 0.98
061902 LEWISVILLE ISD 1.04
061903 PILOT POINT ISD 0.97
061905 KRUM ISD 0.96
061906 PONDER ISD 0.96
061907 AUBREY ISD 0.97
061908 SANGER ISD 0.96
061910 ARGYLE ISD 1.22
061911 NORTHWEST ISD 1.31
061912 LAKE DALLAS ISD 0.97
061914 LITTLE ELM ISD 0.98
062901 CUERO ISD 0.97
062902 NORDHEIM ISD 0.89
062903 YOAKUM ISD 0.96
062904 YORKTOWN ISD 0.95
062905 WESTHOFF ISD 0.91
062906 MEYERSVILLE ISD 0.95
063903 SPUR ISD 0.92
063906 PATTON SPRINGS ISD 0.92
064903 CARRIZO SPRINGS CONS ISD 0.98
065901 CLARENDON ISD 0.92
065902 HEDLEY ISD 0.93
066005 RAMIREZ CSD 0.98
066901 BENAVIDES ISD 0.92
066902 SAN DIEGO ISD 0.96
066903 FREER ISD 0.93
067902 CISCO ISD 0.93
067903 EASTLAND ISD 0.95
067904 GORMAN ISD 0.92
067907 RANGER ISD 0.93
067908 RISING STAR ISD 0.92
068901 ECTOR COUNTY ISD 0.98
069901 ROCKSPRINGS ISD 0.97
069902 NUECES CANYON CISD 0.91
070901 AVALON ISD 0.93
070903 ENNIS ISD 0.97
070905 FERRIS ISD 0.98
070907 ITALY ISD 0.94
070908 MIDLOTHIAN ISD 0.98
070909 MILFORD ISD 0.93
070910 PALMER ISD 0.95
070911 RED OAK ISD 0.98
070912 WAXAHACHIE ISD 0.97
070915 MAYPEARL ISD 0.95
071901 CLINT ISD 0.98
071902 EL PASO ISD 0.98
071903 FABENS ISD 0.96
071904 SAN ELIZARIO ISD 0.96
071905 YSLETA ISD 0.97
071906 ANTHONY 0.93
071907 CANUTILLO ISD 0.97
071908 TORNILLO ISD 0.96
071909 SOCORRO ISD 0.98
072901 THREE WAY ISD 0.96
072902 DUBLIN ISD 0.95
072903 STEPHENVILLE 0.97
072904 BLUFF DALE ISD 1.38
072908 HUCKABAY ISD 0.93
072909 LINGLEVILLE ISD 0.93
072910 MORGAN MILL ISD 0.94
073901 CHILTON ISD 0.93
073903 MARLIN ISD 0.95
073904 WESTPHALIA ISD 0.94
073905 ROSEBUD-LOTT ISD 0.94
074903 BONHAM ISD 0.96
074904 DODD CITY ISD 0.94
074905 ECTOR ISD 0.93
074907 HONEY GROVE ISD 0.94
074909 LEONARD ISD 0.95
074911 SAVOY ISD 0.93
074912 TRENTON ISD 0.95
074917 SAM RAYBURN ISD 0.95
075901 FLATONIA ISD 0.95
075902 LA GRANGE ISD 0.97
075903 SCHULENBURG ISD 0.94
075906 FAYETTEVILLE ISD 1.05
075908 ROUND TOP-CARMINE ISD 1.28
076903 ROBY CONS ISD 0.92
076904 ROTAN ISD 0.91
077901 FLOYDADA ISD 0.94
077902 LOCKNEY ISD 0.94
078901 CROWELL ISD 0.91
079901 LAMAR CONSOLIDATED ISD 0.99
079906 NEEDVILLE ISD 0.98
079907 FORT BEND ISD 0.99
079908 KENDLETON ISD 0.96
079910 STAFFORD MUNICIPAL SCHOOL DISTRICT 1.19
080901 MOUNT VERNON ISD 0.99
081902 FAIRFIELD ISD 1.34
081904 TEAGUE ISD 1.30
081905 WORTHAM ISD 0.94
081906 DEW ISD 2.34
082902 DILLEY ISD 0.93
082903 PEARSALL ISD 0.96
083901 SEAGRAVES ISD 0.94
083902 LOOP ISD 1.78
083903 SEMINOLE ISD 1.49
084901 DICKINSON ISD 0.98
084902 GALVESTON ISD 0.97
084903 HIGH ISLAND ISD 0.94
084904 LA MARQUE ISD 0.96
084906 TEXAS CITY ISD 1.05
084908 HITCHCOCK ISD 0.95
084909 SANTA FE ISD 0.99
084910 CLEAR CREEK ISD 0.99
084911 FRIENDSWOOD ISD 0.99
085902 POST ISD 0.93
085903 SOUTHLAND ISD 0.94
086024 DOSS CONS CSD 1.25
086901 FREDERICKSBURG ISD 1.03
086902 HARPER ISD 0.93
087901 GLASSCOCK COUNTY ISD 1.29
088902 GOLIAD ISD 0.96
089901 GONZALES ISD 0.96
089903 NIXON-SMILEY CONS ISD 0.95
089905 WAELDER ISD 0.93
090902 LEFORS ISD 0.96
090903 MCLEAN ISD 1.02
090904 PAMPA ISD 0.96
090905 GRANDVIEW-HOPKINS ISD 2.10
091901 BELLS ISD 0.95
091902 COLLINSVILLE ISD 0.94
091903 DENISON ISD 0.96
091905 HOWE ISD 0.95
091906 SHERMAN ISD 0.97
091907 TIOGA ISD 0.94
091908 VAN ALSTYNE ISD 0.98
091909 WHITESBORO ISD 0.96
091910 WHITEWRIGHT ISD 0.95
091913 POTTSBORO ISD 0.96
091914 S AND S CONS ISD 0.96
091917 GUNTER ISD 0.97
091918 TOM BEAN ISD 0.96
092901 GLADEWATER ISD 0.96
092902 KILGORE ISD 0.97
092903 LONGVIEW ISD 0.96
092904 PINE TREE ISD 0.97
092906 SABINE ISD 0.96
092907 SPRING HILL ISD 0.97
092908 WHITE OAK ISD 0.96
093901 ANDERSON-SHIRO CONS ISD 1.13
093903 IOLA ISD 0.95
093904 NAVASOTA ISD 0.98
093905 RICHARDS ISD 0.93
094901 SEGUIN ISD 0.97
094902 SCHERTZ-CIBOLO-U CITY ISD 0.99
094903 NAVARRO ISD 0.97
094904 MARION ISD 0.96
095901 ABERNATHY ISD 0.94
095902 COTTON CENTER ISD 0.93
095903 HALE CENTER ISD 0.93
095904 PETERSBURG ISD 0.93
095905 PLAINVIEW ISD 0.97
096904 MEMPHIS ISD 0.91
096905 TURKEY-QUITAQUE ISD 0.92
097902 HAMILTON ISD 0.93
097903 HICO ISD 0.94
098901 GRUVER ISD 0.92
098903 PRINGLE-MORSE CONS ISD 1.27
098904 SPEARMAN ISD 0.94
099902 CHILLICOTHE ISD 0.93
099903 QUANAH ISD 0.91
100903 KOUNTZE ISD 0.97
100904 SILSBEE ISD 0.97
100905 HARDIN-JEFFERSON ISD 0.98
100907 LUMBERTON ISD 0.98
100908 WEST HARDIN COUNTY CONS ISD 0.96
101902 ALDINE ISD 0.99
101903 ALIEF ISD 0.98
101905 CHANNELVIEW ISD 0.97
101906 CROSBY ISD 0.99
101907 CYPRESS-FAIRBANKS ISD 0.99
101908 DEER PARK ISD 1.21
101909 NORTH FOREST ISD 0.98
101910 GALENA PARK ISD 0.97
101911 GOOSE CREEK CISD 1.04
101912 HOUSTON ISD 0.97
101913 HUMBLE ISD 0.99
101914 KATY ISD 0.99
101915 KLEIN ISD 0.99
101916 LA PORTE ISD 1.18
101917 PASADENA ISD 0.98
101919 SPRING ISD 0.99
101920 SPRING BRANCH ISD 1.08
101921 TOMBALL ISD 1.00
101924 SHELDON ISD 1.05
101925 HUFFMAN ISD 0.99
102901 KARNACK ISD 0.93
102902 MARSHALL ISD 0.97
102903 WASKOM ISD 0.93
102904 HALLSVILLE ISD 1.05
102905 HARLETON ISD 0.95
102906 ELYSIAN FIELDS ISD 0.95
103901 CHANNING ISD 1.08
103902 HARTLEY ISD 0.92
104901 HASKELL CISD 0.91
104902 ROCHESTER COUNTY LINE ISD 0.90
104903 RULE ISD 0.94
104907 PAINT CREEK ISD 0.92
105902 SAN MARCOS CONS ISD 0.98
105904 DRIPPING SPRINGS ISD 1.03
105905 WIMBERLEY ISD 1.17
105906 HAYS CONS ISD 1.00
106901 CANADIAN ISD 1.15
107901 ATHENS ISD 0.97
107902 BROWNSBORO ISD 0.97
107904 CROSS ROADS ISD 0.94
107905 EUSTACE ISD 0.95
107906 MALAKOFF ISD 1.14
107907 TRINIDAD ISD 0.92
107908 MURCHISON ISD 0.92
107910 LAPOYNOR ISD 1.08
108902 DONNA ISD 0.98
108903 EDCOUCH-ELSA ISD 0.97
108904 EDINBURG CONSOLIDATED 0.98
108905 HIDALGO ISD 0.97
108906 MCALLEN ISD 0.98
108907 MERCEDES ISD 0.98
108908 MISSION CONS ISD 0.99
108909 PHARR-SAN JUAN-ALAMO ISD 0.98
108910 PROGRESO ISD 0.96
108911 SHARYLAND ISD 0.99
108912 LA JOYA ISD 0.99
108913 WESLACO ISD 0.98
108914 LA VILLA ISD 0.94
108915 MONTE ALTO ISD 0.95
108916 VALLEY VIEW ISD 0.97
109901 ABBOTT ISD 0.94
109902 BYNUM ISD 0.94
109903 COVINGTON ISD 0.95
109904 HILLSBORO ISD 0.95
109905 HUBBARD ISD 0.94
109907 ITASCA ISD 0.93
109908 MALONE ISD 0.92
109910 MOUNT CALM ISD 0.95
109911 WHITNEY ISD 0.96
109912 AQUILLA ISD 0.94
109913 BLUM ISD 0.94
109914 PENELOPE ISD 0.95
110901 ANTON ISD 0.93
110902 LEVELLAND ISD 0.96
110905 ROPES ISD 0.94
110906 SMYER ISD 0.93
110907 SUNDOWN ISD 2.13
110908 WHITHARRAL ISD 0.94
111901 GRANBURY ISD 0.98
111902 LIPAN ISD 0.94
111903 TOLAR ISD 0.95
112901 SULPHUR SPRINGS ISD 0.97
112905 CUMBY ISD 0.92
112906 NORTH HOPKINS ISD 0.93
112907 MILLER GROVE ISD 0.95
112908 COMO-PICKTON CISD 0.95
112909 SALTILLO ISD 0.93
112910 SULPHUR BLUFF ISD 0.94
113901 CROCKETT ISD 0.95
113902 GRAPELAND ISD 0.94
113903 LOVELADY ISD 0.94
113905 LATEXO ISD 0.94
113906 KENNARD ISD 0.92
114901 BIG SPRING ISD 0.97
114902 COAHOMA ISD 0.94
114904 FORSAN ISD 0.95
115901 FT HANCOCK ISD 0.94
115902 SIERRA BLANCA ISD 0.91
115903 DELL CITY ISD 0.93
116901 CADDO MILLS ISD 0.96
116902 CELESTE ISD 0.94
116903 COMMERCE ISD 0.95
116905 GREENVILLE ISD 0.97
116906 LONE OAK ISD 0.94
116908 QUINLAN ISD 0.97
116909 WOLFE CITY ISD 0.94
116910 CAMPBELL ISD 0.94
116915 BLAND ISD 0.95
116916 BOLES ISD 0.93
117901 BORGER ISD 0.96
117903 SANFORD ISD 0.95
117904 PLEMONS-STINNETT-PHILLIPS CONS ISD 1.28
117907 SPRING CREEK ISD 0.93
118902 IRION CO ISD 1.08
119901 BRYSON ISD 0.93
119902 JACKSBORO ISD 0.93
119903 PERRIN-WHITT CONS ISD 0.95
120901 EDNA ISD 0.96
120902 GANADO ISD 0.95
120905 INDUSTRIAL ISD 0.97
121902 BROOKELAND ISD 0.95
121903 BUNA ISD 0.98
121904 JASPER ISD 0.97
121905 KIRBYVILLE CISD 0.96
121906 EVADALE ISD 1.29
122901 FT DAVIS ISD 0.89
122902 VALENTINE ISD 0.90
123905 NEDERLAND ISD 0.97
123907 PORT ARTHUR ISD 0.97
123908 PORT NECHES-GROVES ISD 1.20
123910 BEAUMONT ISD 0.98
123913 SABINE PASS ISD 1.49
123914 HAMSHIRE-FANNETT ISD 0.98
124901 JIM HOGG COUNTY ISD 0.94
125901 ALICE ISD 0.98
125902 BEN BOLT-PALITO BLANCO ISD 0.95
125903 ORANGE GROVE ISD 0.97
125905 PREMONT ISD 0.94
125906 LA GLORIA ISD 0.94
126901 ALVARADO ISD 0.98
126902 BURLESON ISD 0.98
126903 CLEBURNE ISD 0.98
126904 GRANDVIEW ISD 0.99
126905 JOSHUA ISD 0.98
126906 KEENE ISD 0.93
126907 RIO VISTA ISD 0.95
126908 VENUS ISD 0.97
126911 GODLEY ISD 0.95
127901 ANSON ISD 0.93
127903 HAMLIN ISD 0.92
127904 HAWLEY ISD 0.94
127905 LUEDERS-AVOCA ISD 0.92
127906 STAMFORD ISD 0.93
128901 KARNES CITY ISD 0.93
128902 KENEDY ISD 0.95
128903 RUNGE ISD 0.92
128904 FALLS CITY ISD 0.95
129901 CRANDALL ISD 0.97
129902 FORNEY ISD 0.99
129903 KAUFMAN ISD 0.98
129904 KEMP ISD 0.98
129905 MABANK ISD 0.97
129906 TERRELL ISD 0.97
129910 SCURRY-ROSSER ISD 0.95
130901 BOERNE ISD 1.14
130902 COMFORT ISD 0.95
131001 KENEDY COUNTY WIDE CSD 2.91
132902 JAYTON-GIRARD ISD 1.99
133901 CENTER POINT ISD 0.95
133902 HUNT ISD 1.80
133903 KERRVILLE ISD 0.97
133904 INGRAM ISD 0.95
133905 DIVIDE ISD 1.01
134901 JUNCTION ISD 0.93
135001 GUTHRIE CSD 2.00
136901 BRACKETT ISD 0.93
137901 KINGSVILLE ISD 0.96
137902 RICARDO ISD 0.97
137903 RIVIERA ISD 0.92
137904 SANTA GERTRUDIS ISD 1.09
138902 KNOX CITY-O'BRIEN CISD 0.93
138903 MUNDAY CISD 0.94
138904 BENJAMIN ISD 0.92
139905 CHISUM ISD 1.11
139908 ROXTON ISD 0.93
139909 PARIS ISD 0.96
139911 NORTH LAMAR ISD 0.98
139912 PRAIRILAND ISD 0.95
140901 AMHERST ISD 0.93
140904 LITTLEFIELD ISD 0.96
140905 OLTON ISD 0.94
140906 SPADE ISD 0.92
140907 SPRINGLAKE-EARTH ISD 0.94
140908 SUDAN ISD 1.54
141901 LAMPASAS ISD 0.98
141902 LOMETA ISD 0.92
142901 COTULLA ISD 0.96
143901 HALLETTSVILLE ISD 1.03
143902 MOULTON ISD 0.94
143903 SHINER ISD 0.94
143904 VYSEHRAD ISD 0.93
143905 SWEET HOME ISD 0.95
143906 EZZELL ISD 1.59
144901 GIDDINGS ISD 0.96
144902 LEXINGTON ISD 0.96
144903 DIME BOX ISD 0.93
145901 BUFFALO ISD 0.94
145902 CENTERVILLE ISD 0.94
145906 NORMANGEE ISD 0.95
145907 OAKWOOD ISD 0.94
145911 LEON ISD 1.05
146901 CLEVELAND ISD 0.98
146902 DAYTON ISD 0.99
146903 DEVERS ISD 1.88
146904 HARDIN ISD 0.98
146905 HULL-DAISETTA ISD 0.95
146906 LIBERTY ISD 0.97
146907 TARKINGTON ISD 0.99
147901 COOLIDGE ISD 0.92
147902 GROESBECK ISD 1.14
147903 MEXIA ISD 0.95
148901 BOOKER ISD 0.93
148902 FOLLETT ISD 1.04
148903 HIGGINS ISD 1.00
148905 DARROUZETT ISD 1.88
149901 GEORGE WEST ISD 0.95
149902 THREE RIVERS ISD 1.00
150901 LLANO ISD 1.25
152901 LUBBOCK ISD 0.97
152902 NEW DEAL ISD 0.94
152903 SLATON ISD 0.95
152906 LUBBOCK-COOPER ISD 0.96
152907 FRENSHIP ISD 0.98
152908 ROOSEVELT ISD 0.95
152909 SHALLOWATER ISD 0.96
152910 IDALOU ISD 0.94
153903 O'DONNELL ISD 0.92
153904 TAHOKA ISD 0.92
153905 NEW HOME ISD 0.94
153907 WILSON ISD 0.94
154901 MADISONVILLE CONS ISD 0.96
154903 NORTH ZULCH ISD 0.94
155901 JEFFERSON ISD 0.95
156902 STANTON ISD 0.93
156905 GRADY ISD 1.16
157901 MASON ISD 0.93
158901 BAY CITY ISD 0.97
158902 TIDEHAVEN ISD 0.95
158904 MATAGORDA ISD 2.01
158905 PALACIOS ISD 1.13
158906 VAN VLECK ISD 0.95
159901 EAGLE PASS ISD 0.97
160901 BRADY ISD 0.94
160904 ROCHELLE ISD 0.91
160905 LOHN ISD 0.90
161901 CRAWFORD ISD 0.95
161903 MIDWAY ISD 1.12
161906 LA VEGA ISD 0.96
161907 LORENA ISD 0.95
161908 MART ISD 0.94
161909 MCGREGOR ISD 0.96
161910 MOODY ISD 0.94
161912 RIESEL ISD 0.94
161914 WACO ISD 0.96
161916 WEST ISD 0.94
161918 AXTELL ISD 0.90
161919 BRUCEVILLE-EDDY ISD 1.08
161920 CHINA SPRING ISD 0.95
161921 CONNALLY ISD 0.96
161922 ROBINSON ISD 0.97
161923 BOSQUEVILLE ISD 0.93
161924 HALLSBURG ISD 1.25
161925 GHOLSON ISD 0.96
162904 MCMULLEN COUNTY ISD 1.61
163901 DEVINE ISD 0.96
163902 D'HANIS ISD 0.92
163903 NATALIA ISD 0.96
163904 HONDO ISD 0.97
163908 MEDINA VALLEY ISD 0.98
164901 MENARD ISD 0.92
165901 MIDLAND ISD 0.98
165902 GREENWOOD ISD 0.97
166901 CAMERON ISD 0.96
166902 GAUSE ISD 0.94
166903 MILANO ISD 0.95
166904 ROCKDALE ISD 0.95
166905 THORNDALE ISD 0.94
166907 BUCKHOLTS ISD 0.92
167901 GOLDTHWAITE ISD 0.92
167902 MULLIN ISD 0.89
167903 STAR ISD 0.87
167904 PRIDDY ISD 0.90
168901 COLORADO ISD 0.93
168902 LORAINE ISD 0.94
168903 WESTBROOK ISD 1.74
169901 BOWIE ISD 0.97
169902 NOCONA ISD 0.94
169906 GOLD BURG ISD 0.91
169908 MONTAGUE ISD 0.91
169909 PRAIRIE VALLEY ISD 0.93
169910 FORESTBURG ISD 0.94
169911 SAINT JO ISD 0.93
170902 CONROE ISD 1.00
170903 MONTGOMERY ISD 1.18
170904 WILLIS ISD 0.99
170906 MAGNOLIA ISD 1.00
170907 SPLENDORA ISD 0.99
170908 NEW CANEY ISD 0.99
171901 DUMAS ISD 0.96
171902 SUNRAY ISD 0.96
172902 DAINGERFIELD-LONE STAR ISD 1.03
172905 PEWITT ISD 0.95
173901 MOTLEY COUNTY ISD 0.92
174901 CHIRENO ISD 0.94
174902 CUSHING ISD 0.93
174903 GARRISON ISD 0.95
174904 NACOGDOCHES ISD 0.98
174906 WODEN ISD 0.96
174908 CENTRAL HEIGHTS ISD 0.94
174909 MARTINSVILLE ISD 0.94
174910 ETOILE ISD 0.94
174911 DOUGLASS ISD 0.94
175902 BLOOMING GROVE ISD 0.95
175903 CORSICANA ISD 0.97
175904 DAWSON ISD 0.94
175905 FROST ISD 0.94
175907 KERENS ISD 0.94
175910 MILDRED ISD 0.94
175911 RICE ISD 0.93
176901 BURKEVILLE ISD 0.90
176902 NEWTON ISD 0.96
176903 DEWEYVILLE ISD 0.94
177901 ROSCOE ISD 0.93
177902 SWEETWATER ISD 0.95
177903 BLACKWELL CONS ISD 1.09
177905 HIGHLAND ISD 0.95
178901 AGUA DULCE ISD 0.94
178902 BISHOP CONS ISD 0.97
178903 CALALLEN ISD 0.97
178904 CORPUS CHRISTI ISD 0.97
178905 DRISCOLL ISD 0.95
178906 LONDON ISD 0.94
178908 PORT ARANSAS ISD 1.44
178909 ROBSTOWN ISD 0.96
178912 TULOSO-MIDWAY ISD 0.96
178913 BANQUETE ISD 0.93
178914 FLOUR BLUFF ISD 0.98
178915 WEST OSO ISD 0.95
179901 PERRYTON ISD 0.96
180902 VEGA ISD 0.93
180903 ADRIAN ISD 0.93
180904 WILDORADO ISD 0.95
181901 BRIDGE CITY ISD 0.97
181905 ORANGEFIELD ISD 0.97
181906 WEST ORANGE-COVE CONS ISD 1.06
181907 VIDOR ISD 0.97
181908 LITTLE CYPRESS-MAURICEVILLE CISD 0.98
182901 GORDON ISD 0.94
182902 GRAFORD ISD 1.19
182903 MINERAL WELLS ISD 0.96
182904 SANTO ISD 0.95
182905 STRAWN ISD 0.92
182906 PALO PINTO ISD 2.15
183901 BECKVILLE ISD 1.63
183902 CARTHAGE ISD 1.41
183904 GARY ISD 0.94
184901 POOLVILLE ISD 0.95
184902 SPRINGTOWN ISD 0.98
184903 WEATHERFORD ISD 0.99
184904 MILLSAP ISD 0.94
184907 ALEDO ISD 1.00
184908 PEASTER ISD 0.96
184909 BROCK ISD 0.96
184911 GARNER ISD 0.99
185901 BOVINA ISD 0.93
185902 FARWELL ISD 0.94
185903 FRIONA ISD 0.94
185904 LAZBUDDIE ISD 0.93
186901 BUENA VISTA ISD 1.36
186902 FT STOCKTON ISD 1.20
186903 IRAAN-SHEFFIELD ISD 1.36
187901 BIG SANDY ISD 1.03
187903 GOODRICH ISD 0.92
187904 CORRIGAN-CAMDEN ISD 0.95
187906 LEGGETT ISD 0.93
187907 LIVINGSTON ISD 0.97
187910 ONALASKA ISD 0.94
188901 AMARILLO ISD 0.97
188902 RIVER ROAD ISD 0.97
188903 HIGHLAND PARK ISD (Potter County) 1.28
188904 BUSHLAND ISD 1.55
189901 MARFA ISD 0.91
189902 PRESIDIO ISD 0.96
190903 RAINS ISD 0.96
191901 CANYON ISD 0.98
192901 REAGAN COUNTY ISD 1.04
193902 LEAKEY ISD 0.93
194902 AVERY ISD 0.94
194903 RIVERCREST ISD 0.96
194904 CLARKSVILLE ISD 0.94
194905 DETROIT ISD 0.94
195901 PECOS-BARSTOW-TOYAH ISD 0.96
195902 BALMORHEA ISD 0.92
196901 AUSTWELL-TIVOLI ISD 1.50
196902 WOODSBORO ISD 0.93
196903 REFUGIO ISD 0.92
197902 MIAMI ISD 1.33
198901 BREMOND ISD 1.17
198902 CALVERT ISD 0.92
198903 FRANKLIN ISD 0.95
198905 HEARNE ISD 0.94
198906 MUMFORD ISD 0.94
199901 ROCKWALL ISD 1.01
199902 ROYSE CITY ISD 0.98
200901 BALLINGER ISD 0.94
200902 MILES ISD 0.93
200904 WINTERS ISD 0.92
200906 OLFEN ISD 0.92
201902 HENDERSON ISD 0.96
201903 LANEVILLE ISD 0.93
201904 LEVERETTS CHAPEL ISD 0.93
201907 MOUNT ENTERPRISE ISD 0.94
201908 OVERTON ISD 0.93
201910 TATUM ISD 1.34
201913 CARLISLE ISD 0.94
201914 WEST RUSK ISD 0.95
202903 HEMPHILL ISD 0.94
202905 WEST SABINE ISD 0.93
203901 SAN AUGUSTINE ISD 0.95
203902 BROADDUS ISD 0.94
204901 COLDSPRING-OAKHURST CONS ISD 0.98
204904 SHEPHERD ISD 0.97
205901 ARANSAS PASS ISD 0.96
205902 GREGORY-PORTLAND ISD 0.97
205903 INGLESIDE ISD 1.10
205904 MATHIS ISD 0.96
205905 ODEM-EDROY ISD 0.96
205906 SINTON ISD 0.97
205907 TAFT ISD 0.95
206901 SAN SABA ISD 0.92
206902 RICHLAND SPRINGS ISD 0.92
206903 CHEROKEE ISD 0.91
207901 SCHLEICHER ISD 0.93
208901 HERMLEIGH ISD 0.94
208902 SNYDER ISD 0.96
208903 IRA ISD 0.96
209901 ALBANY ISD 0.92
209902 MORAN ISD 0.89
210901 CENTER ISD 0.97
210902 JOAQUIN ISD 0.94
210903 SHELBYVILLE ISD 0.95
210904 TENAHA ISD 0.93
210905 TIMPSON ISD 0.94
210906 EXCELSIOR ISD 0.90
211901 TEXHOMA ISD 1.02
211902 STRATFORD ISD 1.01
212901 ARP ISD 0.95
212902 BULLARD ISD 0.96
212903 LINDALE ISD 0.96
212904 TROUP ISD 0.96
212905 TYLER ISD 0.97
212906 WHITEHOUSE ISD 0.98
212909 CHAPEL HILL ISD 0.98
212910 WINONA ISD 0.96
213901 GLEN ROSE ISD 2.06
214901 RIO GRANDE CITY CISD 0.98
214902 SAN ISIDRO ISD 1.00
214903 ROMA ISD 0.99
215901 BRECKENRIDGE ISD 0.95
216901 STERLING CITY ISD 1.22
217901 ASPERMONT ISD 0.93
218901 SONORA ISD 1.10
219901 HAPPY ISD 0.93
219903 TULIA ISD 0.94
219905 KRESS ISD 0.94
220901 ARLINGTON ISD 0.98
220902 BIRDVILLE ISD 0.97
220904 EVERMAN ISD 0.96
220905 FORT WORTH ISD 0.98
220906 GRAPEVINE-COLLEYVILLE ISD 1.22
220907 KELLER ISD 0.99
220908 MANSFIELD ISD 0.99
220910 LAKE WORTH ISD 0.96
220912 CROWLEY ISD 0.99
220914 KENNEDALE ISD 0.97
220915 AZLE ISD 0.98
220916 HURST-EULESS-BEDFORD ISD 1.04
220917 CASTLEBERRY ISD 0.96
220918 EAGLE MT-SAGINAW ISD 1.02
220919 CARROLL ISD 1.20
220920 WHITE SETTLEMENT ISD 0.98
221901 ABILENE ISD 0.96
221904 MERKEL ISD 0.94
221905 TRENT ISD 1.36
221911 JIM NED CONS ISD 0.95
221912 WYLIE ISD 0.97
222901 TERRELL COUNTY ISD 1.45
223901 BROWNFIELD ISD 0.95
223902 MEADOW ISD 0.93
223904 WELLMAN-UNION CONS ISD 0.93
224901 THROCKMORTON ISD 0.94
224902 WOODSON ISD 0.92
225902 MOUNT PLEASANT ISD 0.97
225905 WINFIELD ISD 0.95
225906 CHAPEL HILL ISD 0.95
225907 HARTS BLUFF ISD 0.93
226901 CHRISTOVAL ISD 0.93
226903 SAN ANGELO ISD 0.97
226905 WATER VALLEY ISD 0.92
226906 WALL ISD 0.97
226907 GRAPE CREEK ISD 0.96
226908 VERIBEST ISD 0.94
227901 AUSTIN ISD 1.14
227904 PFLUGERVILLE ISD 0.98
227907 MANOR ISD 1.09
227909 EANES ISD 1.33
227910