Abstract
State support of public higher education has rapidly declined relative to total state spending. Much of this decline in support is due to the rapid growth in spending on such things as Medicaid. However, relative support of public higher education varies significantly between states. This study applies Tandberg’s (2009) fiscal policy framework created to explain state support of public higher education in order to evaluate the relationship between various factors and states’ relative support of higher education. While Tandberg’s fiscal policy framework accounts for traditional economic and demographic factors in explaining state support for higher education, it also draws attention to political influences as well including the impact of state-level interest groups. Using cross-sectional time-series analysis these relationships are explored over a 19-year period. The findings provide evidence of the significant impact of interest groups and politics on state fiscal policy in regard to higher education.
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Notes
Tandberg’s (2007) original model included a lagged dependent variable. Because of concerns over correlation between the error terms it was dropped in favor of the percent change in the dependent variable (Tandberg 2009). However, percent change in the dependent variable does not fully capture the impact of previous years funding level nor does it carry much theoretical importance. Therefore, for this model percent change in the dependent variable has been replaced by percent change in total state expenditures.
Similar to Tandberg (2007) I found that interest group density and the higher education interest group ratio used in Tandberg’s analysis were highly correlated. The interest group density measure was the only significant variable of the two in this analysis and therefore it was the only one used in the final model.
It shows a systematic decrease in governors’ budgetary powers across almost every state in 1994 and the decrease is not corrected for in subsequent years (change of 1.8 on a 5 point scale). A review of the source data used by Beyle (e.g., Council of State Governments’ Book of the States) reveals that governors’ powers did not decrease in that manner, nor did state legislatures’ powers increase in that manner. The fifty state average before 1994 was between 4 and 4.8 (it had been steadily increasing until 1994). From 1994 until 2001 the average was between 3 and 3.1. The largest change before 1994 was .4 and after 1994 the largest change was .1. Because of this error the data may not be useable.
Generally researchers use Beyle’s overall index of gubernatorial powers and not his measure of budgetary powers alone which may be why this error has gone undetected until now. Beyle’s budget power data can be viewed here: http://www.unc.edu/~beyle/E-Budget-501.doc
When the average increase in the explained variance for each category of variables is taken (loaded forward, as they appear in Table 3, and in reverse with the political variables loaded second) the political variables add 8%, the higher education variables add 4%, and the economic and demographic variables add 14%.
As indicated this result is unexpected. Several other approaches were attempted including removing the unemployment variable, running the model with the unemployment variable but not the recessionary year variable, and using recessionary year variable that was not lagged. None of this approaches changed the results in any substantive way for either the unemployment variable (which returned the hypothesized results) or the recessionary year variable. While not particularly strongly correlated (−0.18) the direction of the correlation coefficient for the recessionary year variable and unemployment is in the expected direction.
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Tandberg, D.A. Politics, Interest Groups and State Funding of Public Higher Education. Res High Educ 51, 416–450 (2010). https://doi.org/10.1007/s11162-010-9164-5
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DOI: https://doi.org/10.1007/s11162-010-9164-5