U.S. charter schools are publicly funded through state school finance formulas that often mirror the traditional public school finance systems. While charter school advocates and critics disagree over whether charters receive an equitable share of funding, few discussions are based on rigorous analyses of funding and expenditures. Most prior analyses, especially those presented in policy briefs or white papers, examine average funding differences without exploring underlying cost factors between the two sectors. Our purpose is to demonstrate how careful analysis of charter school funding with appropriate methodological approaches can shed light on disagreements about charter school finance policy. Using detailed school finance data from Texas as a case study, we find that after accounting for differences in accounting structures and cost factors, charter schools receive significantly more state and local funding compared to traditional public schools with similar structural characteristics and student demographics. However, many small charter schools are actually underfunded relative to their traditional public school counterparts. Policy simulations demonstrate that on average, each student who transfers to a charter school increases the cost to the state by $1,500. We discuss the implications of these findings for both school finance policy in Texas and nationally.

As workforce participation increasingly requires a college degree, ensuring that more students from traditionally underrepresented populations have the opportunity to enter and complete college is an equity imperative. To that end, high school reforms have promoted college-going cultures in low-performing high schools through interventions such as rigorous course offerings and college counseling. College access research has focused on issues specific to academics and college-going processes. Yet this research has tended to ignore broader school climate factors such as school safety and extracurricular programming, which may play a critical role in postsecondary opportunity, especially for historically underserved students. The current study applies hierarchical generalized linear modeling to the Educational Longitudinal Study of 2002 to 2006 to examine the role of college-going culture and high school climate characteristics on college enrollment and persistence. We find that while some components of college-going culture are associated with the likelihood of college enrollment and persistence, that relationship is moderated by school climate factors. We conclude that efforts to implement a college-going culture may struggle if extracurricular opportunities, school safety, and overall school climate issues are ignored.

Educational data offer a powerful tool for supporting equity. In this article, the authors call for a shift toward greater use of data in educator preparation programs. The authors motivate their proposal by highlighting findings from the Department of Education report released January 2018, which found that the Texas Education Agency systematically denied students special education services. The article outlines three basic metrics that stakeholders can use to identify potential noncompliance with the Individuals With Disabilities Education Act. The authors describe other ways data can be used to promote equity and close with recommendations for educator preparation policy and practice.

Price differentials, among other factors, persuade many residents of Northern Mexico to shop in the Southwestern United States border region. Employment patterns in the latter region are studied using a set of control variables and two indicators that are likely to influence cross-border shopping patterns. The first is a real exchange rate index, which captures changes in relative prices in the United States and Mexico. The second is real per capita gross state product in Mexican states adjacent to the international boundary. Both of these variables are found to impact retail and restaurant employment in the United States border zone, confirming that cross-border shopping influences labor market conditions in that region. Furthermore, the estimated elasticities vary across retail sub-sectors in ways that are generally consistent with prior research. Overall, the results suggest that economic setbacks in Northern Mexico and real peso depreciations are likely to have adverse consequences for important sectors of border economies in the United States.

State accountability systems have been a primary school reform initiative in the US for the past 20 years, but often produce unintended negative consequences. In 2004, the Texas Education Agency (TEA) implemented the Performance Based Monitoring and Analysis System (PBMAS), which included an accountability indicator focused on the percentage of students found eligible for special education under the Individuals with Disabilities Education Act (IDEA), the nation’s special education law. From 2004 through 2016, the percentage of students found eligible for special education in Texas declined significantly, while the national rate held constant. Eventually, the U.S. Department of Education (ED) investigated TEA and the statewide implementation of IDEA. The purpose of this study is two-fold: (a) to evaluate the potential impact of the the PBMAS indicator on manipulation of special education identification practices; and (b) to describe how the indicator may have influenced school and district personnel. We highlight several concerning trends in state and district data and, through an analysis of publicly available reports from the ED, show how district and school personnel knowingly and unknowingly acted in ways that delayed and denied special education to potentially eligible students. We conclude with recommendations for TEA and implications for future research and policy. © 2019, Arizona State University. All rights reserved.

Scholars have not reached consensus on the best approach to measure state school finance equity. The regression-based approach estimates the relationship between district poverty rate and funding level, controlling for other district cost factors. A second commonly used approach involves estimating the weighted average funding level for low-income students or other subgroups. Meanwhile, policymakers have preferences for their own data systems and poverty indicators when reading reports and assessing progress. We constructed parallel, district-level panel data sets using data from the California Department of Education and the U.S. Census. We estimated changes over time in district-level school finance equity under California's Local Control Funding Formula, using multiple school finance measurement approaches, with each of the two data sets. Our results show that different methods and analytic choices result in policy-relevant differences in findings. We discuss the implications for policy and future research.

We evaluate the cost-effectiveness of two early childhood interventions that use instructional coaching and parent coaching as levers for improvement. The study design allows us to compare the individual effects of each intervention as well as their combined effect on student outcomes. We find that teachers receiving instructional coaching improve their use of evidence-based instructional practices, while families receiving parent coaching show increases in numerous responsive parenting behaviors associated with positive child outcomes. Both interventions demonstrate positive impacts on students, but only parent coaching shows statistically significant effects across a range of student outcomes. Instructional coaching alone is substantially less costly and may therefore be the most cost-effective of the three treatment conditions; however, small sample sizes limit our ability to reach definitive conclusions. Policy simulations suggest that implementing these interventions could raise the overall cost-effectiveness of Head Start by at least 16 percent. © 2019 by the Association for Public Policy Analysis and Management

Links between electricity consumption and economic growth are fairly well documented for national economies, but less so for urban economies. The analysis of such relationships at the sub-national level of aggregation can potentially offer a useful complement to national-level research. This study examines the electricity-growth nexus in El Paso, Texas, while also considering the roles of capital stocks and employment. Testing suggests the presence of cointegrating relationships and a vector error correction model is estimated. Granger causality tests reveal the absence of causality between electricity consumption and personal income, implying that energy conservation efforts will have a neutral effect on economic growth. Furthermore, the results indicate that causality runs from the capital stock and employment to both personal income and electricity consumption. This echoes previous research regarding the importance of accounting for capital and labour factors of production in studies of aggregate electricity utilization and economic performance. The methodology used in this analysis to develop a broad synthetic measure of the urban capital stock, including various categories of public infrastructure, can also be applied to other regions and urban economies.

This study evaluates the accuracy of previously published econometric forecasts for seven lodging sector variables that measure hotel activity in El Paso, Texas. The hotel forecasts have been generated annually using an econometric model of the El Paso metropolitan economy from 2006 forward. Predictive accuracy is evaluated relative to random walk benchmarks. Assessment is completed using both descriptive forecast error summary statistics as well as formal statistical tests. The econometric model outperforms the random walk benchmarks for a majority of the variables analyzed. However, statistical tests of forecast error differentials do not yield conclusive evidence in favor of the econometric historical track record. Tests of directional forecast accuracy also produce mixed results. Although the structural econometric model of hotel business conditions appears to provide useful predictive information, analysts and planners should also monitor recent history closely.