This is a presentation given at the International Public Finance Institute Annual Congress in 2019 at Tampere, Finland.

1. Political Economy of Parcel Tax
in California School Districts
Soomi Lee
Associate Professor
University of La Verne (USA)
August 23, 2018
International Institute of Public Finance Annual Congress
Tampere, Finland

2. Parcel Tax in California
• A lump-sum property tax per unit of parcel
• “A non-ad valorem tax imposed as an incidence
of property ownership” (CA State Controller’s
Office)
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3. 2

4. 3

5. Parcel Tax in California
• Unique to the State of California
• Same amount for all property with no
classification
• Regressive with respect to property values
• Used by school districts, special districts,
cities, and counties. They must obtain a 2/3
supermajority of votes.
• This paper is on parcel taxes in school
districts.
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6. Background of a School Parcel
Tax
• Serrano v. Priest (1971, 1976, 1977)
– School finance equalization.
– Transferred local control over school finance
to the state.
• Proposition 13 (1978)
– One percent rule.
– Resulted in significant budget constraints in
local governments.
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7. California K-12 public school per pupil spending relative to
the national average, 1970-2000 (RAND 2005)
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Prop 13.

8. Additional Local Revenue
Sources?
• Donation?
• More taxes? How?
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9. Parcel Tax as a Special Tax
• Proposition 13 requires taxes raised by local
governments for a designated or special
purpose to be approved by a 2/3 of the voters.
(CA Constitution Article 13A Section 4)
• Parcel tax: not an ad valorem tax, which can be
raised by a 2/3 supermajority for specific
purposes (e.g. STEM education)
• A way to circumvent the limitations of
Proposition 13 to extract revenue from real
estate
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10. School Parcel Tax in California
• First school parcel tax in 1983.
• 625 parcel tax measures (1983-2015)
– Approval rate: 57.76%
– 23% have held at least one parcel tax election.
– 13% have passed at least one parcel tax
measure.
• Usually specifies purposes, restrictions,
exemptions, etc.
• Current school parcel tax: $470 million per year
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11. Literature
1. Brunner (2001): marginal price for residential
property owners.
2. Lang and Sonstelie (2015): tax price for per
pupil spending, district median income, the Bay
Area.
3. Hill and Kiewiet (2015): political ideology,
election strategies, district median income, the
Bay Area.
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12. 11

13. Goal
• How does regressivity of a parcel tax play
role in the process of adoption?
• Test a hypothesis: a larger variance of
home values within a school district
reduces the likelihood of parcel tax
adoption.
• Improve estimates in previous studies
– Need to understand parcel tax adoption better
by considering the two-step election process.
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14. Two-step Decision Making
Process
1. School board proposes a parcel tax
election.
2. Voters approve or reject the proposal.
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15. First Stage
• School board evaluates quality of
schooling, Q=𝑁−γ
(E,P,K), where
N=enrollment, γ=captures economies of
scale, E=current expenditure, P=local
supply price, K=capital expenditure.
• School board decides to increase Q by
increasing E.
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16. School Board considers…
• The income level of the district
• Tax price: tax amount to increase a one dollar of
current expenditure per pupil (for a parcel tax, it is
N/#parcels) (Lang and Sonstelie 2015).
• Different preferences for homeowners and renters
(Oates 2005; Brunner et al. 2015).
• Cost of election
– Administrative costs; campaigning costs; political
costs
• Social fractionalization
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17. Second Stage
• Voter j’s utility uj=uj (X,Q)
– X: bundle of private goods
– Q: quality of schools
• A parcel tax increases uj  Vote yes.
• Increase/decrease in uj depends on the
marginal rate of substitution for j.
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18. Voters consider…
• Their income
• Their tax burden: tj
– Under ad-valorem, tj=Vj/Vt, V=property value
– Under a parcel tax, tj=1/M, M=#of parcels
– For renters, V=0.
• Property owners with a lower value housing go
against a parcel tax for its regressivity.
– Pre-election polls reveal a strong opposition against a
lump-sum tax when different schemes are presented.
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19. At the Aggregate Level
• School boards place a parcel tax measure on
the ballot considering their district income level,
tax price, local price level, current operating
expenditures, cost of election, social
fractionalization.  first stage
• Voters make a yes-or-no decision based on
income and tax burden. At the aggregate level,
the distribution of home values determine the
adoption of a parcel tax.  second stage
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20. Empirical Model:
Heckman Selection Model
• High election costs, two-thirds supermajority vote
requirement, and risk of losing election  parcel tax
election is school boards’ deliberate choice. It is nor
randomly occur among 1000 school districts. To
account for the non-randomness, I use the
Heckman Selection Model.
• Follow Van de Ven and van Praag (1981).
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21. Empirical Model:
Heckman Selection Model
• Selection equation (probit mode)
– Latent variable 𝑦1𝑖
∗
= school boards’ propensity to call a parcel
tax election in district i
𝑦1𝑖
∗
= 𝑋𝑖 𝛽 + 𝜀𝑖, 𝑖 = 1, … , 𝑁,
• Outcome equation (probit model)
– 𝑦2𝑖
∗
= latent variable of parcel tax adoption
𝑦2𝑖
∗
= 𝑍𝑖 𝛾 + 𝑢𝑖,
𝑦2𝑖 =
1 𝑖𝑓 𝑦2𝑖
∗
> 0
0 𝑖𝑓 𝑦2𝑖
∗
≤ 0
𝑖𝑓 𝑦1𝑖 = 1
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22. Data
• 762 California school districts with 200 or more
students in 2014.
• Sources:
California Department of Education,
Ed-Data,
U.S. Census Bureau,
National Center of Education Statistics.
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23. Variables: Selection Equation
• Dependent variable: having held at least one parcel
tax election between 2008 and 2014 (binary)
• Independent variable
– Enrollment size, Enrollment size^2 (economies of scale)
– Current operation spending per pupil ($)
– Local price level: Comparable Wage Index
– Income bracket for a decisive voter
– Cost of election (city-school district congruence index)
– Social fractionalization (racial and ethnic heterogeneity)
– Cost of election X Social capital interaction term
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24. Variables: Outcome Equation
• Dependent variable: presence of parcel tax
revenue (binary)
• Independent variable
• Home value gap: upper 25% to lower 25% average
single family home value ratio (log)
• Social fractionalization (racial and ethnic
heterogeneity)
• Renters
• Income
• District size (quadratic function of enrollment)
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25. Selection Outcome
Home price gap -1.691**
Income .535*** -.044
ADA -.989*** .641
ADA^2 .065*** -.054**
Renters .507** .262
Social Fractionalization .661** .014
City-school district incongruence -3.080***
Social fractionalization X
Incongruence
-3.451***
Local cost of living 5.200***
Operating expenditure -.165
Tax price -.239**
Notes: N=751; Rho=-0.588***; * p<0.1; ** p<0.05; *** p<0.01
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Baseline Results

26. Effects of the Home Price Gap
• Coefficient = -1.691 (p<0.05)
• Difficult to interpret: -1.691=𝛽/𝜎 where 𝜎2
is the variance
of the error term (Kennedy 2003).
• Average marginal effect (AME) : -0.606, a 10% increase
in home price gap associated with a 6.06 pp decrease in
the probability of parcel tax adoption.
• Marginal effect at the average value: -0.775. A 10%
increase in home price gap associated with a 7.75 pp
decrease in the probability of parcel tax adoption.
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27. Average Marginal Effect of Home Price Gap on Likelihood of
Parcel Tax Adoption with 95% Confidence Intervals
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Home price gap more
than 1.5  unlikely to
adopt a parcel tax

28. Conditional Marginal Effect By the 33rd
Percentile Household Income Levels
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29. • Additional control variables for an
extended model
– Population of age 65 or older (%), log
– Political ideology (% County Obama supporter
in 2012 election), log
– Bay Area indicator (1=Bay Area, 0=Otherwise)
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30. Extensions
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DV: existence of parcel tax) Baseline (1) (2) (3)
Additional variables None
Only in
selection
Only in
outcome In both
Outcome equation
Home price gap -1.691** -1.759*** -1.610** -1.548**
Senior population -.699 -.550
Obama votes 1.554** .716
Bay Area .184 -.134
Selection equation
Senior population -.172 -.115
Obama votes 1.933*** 1.843***
Bay Area .719*** .738***
Notes: N=751. 1p<0.1; ** p<0.05; *** p<0.01. All variables in the
baseline estimate are included.

31. Conclusion
• A 10 percent increase in a home price gap leads
to a 6-7 pp decrease in the likelihood of parcel
tax adoption.
• Communities with a homogeneous housing
market are more likely to adopt taxes than more
heterogeneous districts serving a wider range of
incomes, which undermines state requirements
for equalized school funding. (Rolling back to
Serrano?)
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32. THANK YOU
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