Tuition-Setting Authority and Broad-Based Merit Aid: The Effect of Policy Intersection on Pricing Strategies

Abstract

The notion of merit-aid is not a new development in higher education. Although previous researchers have demonstrated the impact of state-adopted merit-aid funding on student decision-making, fewer studies have examined institutional pricing responses to broad-based merit-aid policies. Using a generalized difference-in-difference approach, we extend previous empirical work by examining the impact of merit-aid on institutional pricing strategies while considering both the institution’s tuition-setting authority and the relative strength of the merit-aid program. In this study, we find that colleges and universities with the authority to set their own tuition increased their in-state tuition and fees following broad-based merit-aid policy adoption; however, institutions with state-controlled tuition-setting authority respond to broad-based merit-aid policies by lowering their in-state tuition and fees. Our findings suggest that the incentives and dynamics of each state’s policy environment are significant determinants of institutional responses to state-level policy adoptions.

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Fig. 1
Fig. 2

Notes

  1. 1.

    Between 1993 and 2005, 14 states have offered merit aid to high-achieving resident students.

  2. 2.

    Long (2004) found that four-year institutions throughout Georgia increased their costs for attendance after the adoption of Georgia’s state-level merit-aid policy and effectively diluted the benefit of merit-aid. This study extends Long’s work in several substantive ways, as outlined in this paper.

  3. 3.

    Zhang (2011) and Zhang et al. (2013) include Florida in their analyses of the effect of merit-aid policies in higher education.

  4. 4.

    As we discuss later, we define broad-based merit-aid as merit-aid policies that have large per-FTE subsidies and cover a substantial proportion of students enrolled at public 4-year institutions.

  5. 5.

    We follow the prior work of Delaney and Ness (2013) and Sjoquist and Winters (2015) to identify the broad-based merit-aid policies for this study. A more detailed description of how policies were identified can be found in the methods section of this manuscript.

  6. 6.

    The majority of institutions removed were community colleges that were reclassified as public 4-year institutions due to their awarding of bachelor’s degrees. See Fulton (2015) for information on states implementing community college baccalaureate policies during our analytical period.

  7. 7.

    Missing data were concentrated primarily in institutions that have zero tuition reliance (i.e., service academies) and public 4-year institutions that reported no state appropriation revenue or FTE enrollment in a given year.

  8. 8.

    We omitted private institutions from our analysis because not all state merit-aid programs provide incentives for enrollment at private 4-year institutions. All state-adopted merit-aid programs provide financial support to qualified in-state students attending a public 4-year institution.

  9. 9.

    The practice of using the NASSGAP Survey to identify merit-aid policy adopters is rooted within the academic literature. Specifically, Doyle (2006) used it to classify adopters for his event history analysis as well as Fitzpatrick and Jones (2012) in their analysis of multi-state merit-aid adoption on student migration. Additionally, none of these states met the criteria for broad-based merit-aid policies, and thus would not impact our point estimates.

  10. 10.

    Figure 1 provides the pre- and post-adoption trends for each of our identified broad-based merit-aid states. Across each of our identified adopters, institutions within merit-aid states followed similar pre-adoption trends compared to institutions in non-adopting states.

  11. 11.

    See our methodological discussion on how we used the prior work of Delaney and Ness (2013) and Sjoquist and Winters (2014) to classify the identified merit-aid policies.

  12. 12.

    We borrow from Hillman et al. (2014) when discussing robustness across multiple comparison groups: (a) one comparison group yields a statistically significant result and equals “limited” evidence, (b) two or three groups equals stronger evidence, and (c) all four comparison groups yield statistically significant results, which is the strongest evidence possible. Alternatively, if our estimates have no significant patterns across all four comparison groups, then we conclude that the policy had null effects on that particular outcome.

  13. 13.

    Over the course of our analytical sample, 82 institutions were under a broad-based merit-aid program, 195 institutions were afforded the authority to set their own tuition, and 38 institutions operated both under a broad-based merit-aid policy and decentralized tuition-setting authority.

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Correspondence to Dennis A. Kramer II.

Appendix

Appendix

See Tables 6 and 7.

Table 6 In-state published tuition and fees (logged) with covariate point estimates
Table 7 Out-of-state published tuition and fees (logged) with covariate point estimates

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Kramer, D.A., Ortagus, J.C. & Lacy, T.A. Tuition-Setting Authority and Broad-Based Merit Aid: The Effect of Policy Intersection on Pricing Strategies. Res High Educ 59, 489–518 (2018). https://doi.org/10.1007/s11162-017-9475-x

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Keywords

  • Merit aid
  • Tuition decentralization
  • Pricing strategy
  • Policy interaction
  • Higher education finance
  • Financial aid