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Erschienen in: Empirical Economics 4/2014

01.06.2014

State politics, tuition, and the dynamics of a political budget cycle

verfasst von: C. Lockwood Reynolds

Erschienen in: Empirical Economics | Ausgabe 4/2014

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Abstract

This paper attempts to improve the understanding of political budget cycles by first identifying a previously undocumented cycle in tuition and required fees at public four-year institutions of higher education in the United States. I find that tuition and fees are 1.5 % lower during gubernatorial election years than in non-election years. No similar cycle is found in private tuition and fees. Using a newly constructed dataset, I then explore the variation in electoral competition in gubernatorial and state legislative elections within states over time to uncover the underlying electoral incentives creating the cycle. The results suggest that the tuition cycle is not designed to increase the reelection prospects of governors as standard theories would predict. I find that tuition decreases during gubernatorial election years as the reelection prospects of the incumbent governor increases. Instead, the evidence suggests that popular governors use lower tuition as political pork to expand party power in the state by capturing swing districts in concurrent state legislative elections. I find that the magnitude of the cycle increases with the level of competition in state house elections and that the effect is concentrated among those districts held by the opposition party, particularly if those opposition districts are populated with voters likely to be responsive to tuition as a policy lever. These results reveal important dynamics about party competition within states in the United States and suggest that the electoral incentives driving political budget cycles can be complex.

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Fußnoten
1
Henceforth, unless otherwise noted, “election year” refers to a gubernatorial election year and “tuition” refers to in-state tuition and required fees at public four-year institutions. In-state (or resident) tuition is the rate charged to students who reside in the state. Students whose permanent residence is in another state are typically charged a separate and higher non-resident (or out-of-state) rate.
 
2
Parents and students are not the only voters who care about tuition. College costs are listed as an important concern for all voters (Immerwahr et al. 2009) and tuition is linked to the state budget, the handling of which is an important indicator for the governor (Gray et al. 1999). Finally, higher education is an effective lobbying force in many states, particularly when connected through faculty and lecturers to unions (Gray et al. 1999).
 
3
State general fund appropriation was listed as the most influential factor by 36 states and was listed as one of the top three factors by 47 states. In comparison, the prior year’s tuition was listed as the most influential by two states, tuition at peer institutions was listed as the most influential by one state, and inflation was listed as the most influential factor by three states. These factors were only listed in the top three factors by 16, 19, and 6 states, respectively.
 
4
In the survey, 18 states reported having such caps sometime in the previous three years.
 
5
See “Granholm Wants Limit on Tuition Increases” by Amy F. Bailey (Associated Press, Feb. 10, 2005), “Tuition Freezes on Thin Ice; Public, Private Colleges Mull Rate Hikes Amid Rising Operating Costs, State Funding Uncertainty” by Shannon Mortland (Crain’s Cleveland Business, January 19, 2009), and “Tuition Increases and Audits” by Wendy Ginsberg (The New York Times, May 12, 2002).
 
6
While the HEGIS files do provide some tuition data before 1972, they are collected intermittently and have a significant degree of item non-response. Therefore, I begin the sample in 1972, the earliest year where consistent data are available.
 
7
An alternative dataset of tuition and fees constructed by the Washington Higher Education Coordinating Board (HECB) has no years of missing data. However, it only includes a sample of institutions within each state and is not enrollment-weighted. Thus, I prefer the IPEDS dataset for this project. However, I repeated the analysis using the HECB data and the results were quantitatively and qualitatively similar, suggesting that neither the enrollment weighting nor the gaps in annual tuition data are driving the estimates.
 
8
An alternative approach would be to use state linear time trends to control for slow-moving covariates which are not captured by state fixed effects. I prefer the approach that I use, which is similar to that used frequently in the literature (see Besley and Case 1995; Persico et al. 2011), because the state linear time trends take up much of the variation with only 48 states over 29 years. All results have been estimated using state-specific time trends and the substantive results are unchanged as I later demonstrate.
 
9
The log specification is for ease of interpretation as \(\beta \) represents the deviation during election years in percentage terms. Results of a specification using levels of real tuition instead were similar in relative magnitude.
 
10
The governance structure of higher education has been found to affect the level of tuition in the cross section by Lowry (2001). To the extent that these governance structures are constant over time, the differences will be picked up by the state fixed effect. Unfortunately, consistent data on governance structures over time are not available. However, I have estimated regressions across states by governance structure in the later years of the sample when such data are available and have found that while the governance structure may affect the level of tuition across states, it has no effect on the existence or magnitude of the tuition cycle within states.
 
11
Nebraska has a non-partisan, unicameral state legislature and while margins can be constructed for districts, party competition at the district level cannot be determined. Vermont, Alaska, and Hawaii are excluded because of missing data in the early years of the sample period.
 
12
Throughout the paper, all dollar values are inflated to real 2008 dollars using the CPI-U.
 
13
One might also consider using non-resident or out-of-state tuition as an alternative falsification test as this is tuition charged to students from other states and therefore would not impact voters within the state. However, over half of states specifically index non-resident tuition to resident tuition, and individual institutions may choose to do so as well.
 
14
Wyoming has no private four-year institutions and therefore is not included in the regressions using private tuition. Removing Wyoming from the regressions using public tuition does not substantively change the results, so the exclusion of this state does not explain the difference between public and private tuition.
 
15
Throughout the paper, I use the margins of victory in general elections. Some gubernatorial and state legislative elections go to a runoff election if no candidate wins a majority of votes. As discussed previously, the decisions about tuition and state budgets are made before the general election in each state. Additionally, only the top candidates in the general election qualify for the runoff election, so incumbents still have an incentive to maximize their vote share in the general election. For both these reasons, the margin of victory in the general election would seem to be the appropriate measure. Regardless, the relatively infrequent runoff elections do not appear to be driving the results.
 
16
A majority of states (31) have four-year terms of office for state senators and two-year terms of office for house members. However, roughly half of states stagger the elections of senate members such that in any given gubernatorial election year, only some senate districts experience an election. With rare exceptions, all house members are elected concurrently with governors in all states.
 
17
Note that the margin calculated in single-member districts can also be thought of as a measure of competition between political parties because each party can only have one candidate in the election. A candidate from a major party may run as an independent which would split the vote of that party, though it is relatively rare. Given that there are over 5,000 state house districts, the occasional independent candidate is not driving the results.
 
18
I use the state house margin distribution to define competitive and tight elections because the state house distribution is more skewed than the gubernatorial margin distribution. The results are not driven by how competitive and tight elections are defined and are robust to other definitions of close elections. For example, the substantive results are unchanged if I use the median and 20th percentiles of the gubernatorial margin distribution, 0.119 and 0.044, respectively, instead of the state house distribution to define competitive and tight elections (see Table 7 in the Appendix).
 
19
It is also possible that governors are thinking about their future political careers and thus still inducing a cycle for their own purposes. However, some states have lifetime instead of consecutive term limits, so future reelection is not an option for many governors. Additionally, it is not clear why holding tuition low during the last year of office as opposed to the entire term is optimal for increasing reelection chances in some future election many years away. Finally, while it is possible for governors to move up in their party from holding state to holding federal offices, either elected or appointed, the instances of this happening are relatively rare in the data. Also, it is not immediately clear why electoral manipulation of tuition at the state level would increase their prospects for federal positions.
 
20
While the results also appear to suggest that the cycle disappears during the terms of independent governors, which would be consistent with the story that partisan competition for state legislative districts drives the tuition cycle, care must be taken when interpreting this result because there are few independent governors during the sample. Therefore, I interpret the effect as possibly suggestive, but not definitive evidence of partisan competition.
 
21
This creates a final panel of approximately 86,000 state house districts over time. Though I do not investigate state senate elections, the same methodology can be used to construct a panel of approximately 20,000 state senate districts as well. To my knowledge, this is the first panel of all state legislative district characteristics over a substantial time horizon and through periodic redistricting. Excellent data from Barone et al. (1998) and Lilley et al. (2008) have been created, but are limited to the 1990s and 2000s, respectively, and do not account for mid-decade redistricting.
 
22
I use the proportion aged 0–24 to capture the possibility that tuition is viewed as a proxy for educational issues and therefore parents with younger children may also respond to lower tuition. Results using the proportion of the population aged 18–24 were similar.
 
23
Dividing districts into young and old is fairly broad, but the substantive results hold if I use a finer gradation of ages. For example, if I instead divide districts into terciles based on the 0–24 age distribution of districts, I find that the interaction of average house margin and the election year indicator is 0.561** (0.232) for the youngest districts, 0.421** (0.238) for the middle districts, and \(-0.149\) (0.249) for the oldest districts).
 
24
The existence of gubernatorial coattails also serves to explain why the cycle in tuition occurs during gubernatorial elections. In off-year state house elections, there are no coattails and thus fewer competitive opposition districts to be targeted. Consistent with this explanation, estimates of the existence and magnitude of a cycle associated with state house elections, which are more frequent than gubernatorial elections in most states, are presented in Table 9 in the Appendix. The results for all estimates have the same signs as those reported for gubernatorial election years, but the magnitudes are much smaller and are never statistically significant. These results suggest that the underlying motivation associated with state house elections may exist in all state house elections, but the effects are concentrated among gubernatorial election years.
 
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Metadaten
Titel
State politics, tuition, and the dynamics of a political budget cycle
verfasst von
C. Lockwood Reynolds
Publikationsdatum
01.06.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 4/2014
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-013-0723-4

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