Return on Investment: An Examination of the "Spillover Effect" of State Funding For Higher Education On State Economic Performance, A Spatial Analysis

dc.contributor.advisorTitus, Marvin A.en_US
dc.contributor.authorWilliams II, David S.en_US
dc.contributor.departmentEducation Policy, and Leadershipen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2017-06-22T06:19:53Z
dc.date.available2017-06-22T06:19:53Z
dc.date.issued2017en_US
dc.description.abstractUtilizing a conceptual framework that includes the endogenous growth theory and principal agent theory, this study investigates the relationship between state economic performance and state appropriations for public higher education, both within and across states. This examination is conducted utilizing advanced statistical modeling and data from the 48 contiguous United States over a period of ten years. The analytic model utilized in this study is a dynamic fixed effects panel (DFEP) which is estimated utilizing a Generalized Method of Moments (GMM) technique. Combining the DFEP model with GMM techniques facilitates an ability to account for issues such as unobservable state characteristics, endogeneity, serial correlation, heteroscedasticity, and time-specific effects. This technique utilizes lags of the dependent variable and independent variables to address the aforementioned issues. This study adds to the literature surrounding the relationship between state economic performance and state appropriations for public higher education, by not only examining this relationship in the economic performance of neighboring states but also utilizing advanced statistical methodology. The results discussed herein indicate that while using simpler statistical methods e.g. ordinary least squares regression, there is a positive statistically significant relationship between state economic performance and state appropriations for public higher education. However, this relationship becomes insignificant when utilizing the DFEP model estimated with GMM techniques. Furthermore while the results of this inquiry indicate that there was no statistically significant relationship between state appropriations and neighboring state economic performance, there is spatial correlation of state appropriations and gross state product across neighboring states. There were several implications as a result of this study. One implication is that though the relationship between state appropriations for public higher education and state economic performance was insignificant this research provides a foundation for further research in this area. By introducing advanced methodology and suggesting a redefinition of how one measures the relationship between higher education funding and economic performance this study may inspire new research. Another implication is utilizing two disparate theories to develop a conceptual framework. Scholars who wish to examine relationships between other forms of state funding and state economic performance might also consider employing these theories as a foundation for their study. Lastly, spatial correlation was discovered in both state appropriations and state economic performance. The discovery of spatial correlation indicates that further research is needed regarding the influence of higher education institutions and policy beyond state and regional borders.en_US
dc.identifierhttps://doi.org/10.13016/M26G57
dc.identifier.urihttp://hdl.handle.net/1903/19467
dc.language.isoenen_US
dc.subject.pqcontrolledHigher education administrationen_US
dc.subject.pquncontrolledDynamic fixed-effects panelen_US
dc.subject.pquncontrolledEconomic performanceen_US
dc.subject.pquncontrolledPanel dataen_US
dc.subject.pquncontrolledSpatial autocorrelationen_US
dc.subject.pquncontrolledState appropriationsen_US
dc.titleReturn on Investment: An Examination of the "Spillover Effect" of State Funding For Higher Education On State Economic Performance, A Spatial Analysisen_US
dc.typeDissertationen_US

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