1. An Empirical Framework for Large-Scale Policy Analysis, with an Application to School Finance Reform in Michigan
Maria Marta Ferreyra
Tepper School of Business
Carnegie Mellon University

2. Motivation How should we empirically analyze large-scale policies?
This paper:
Empirical framework for the analysis of large-scale policies
Applies framework to study the Michigan school finance reform

3. K-12 Public School Finance
Funding for K-12 schools comes from:
Local districts (property taxes)
State (income or sales tax)
School finance reform since the early 70s
Greater equity in funding across districts

4. Michigan School Finance Reform (Proposal A)
Implemented in 1994
Local control  centralized state control
Tax Reform
Reduced property taxes
Increased sales and use taxes
Revenue Reform
State guarantees revenue = foundation allowance
Revenue increases to low-revenue districts; revenue caps for high revenue districts

5. Proposal A (cont.) Goals: But other effects are also possible:
Lower property tax burdens
Lower revenue variation across districts
But other effects are also possible:
General equilibrium effects
… and they can magnify the improvement

6. Empirical Framework for Large-Scale Policy Analysis
Large-scale policies  general equilibrium model
Empirical content estimate model; fit in-sample data
Serve to analyze actual policies
Serve to analyze counterfactual policies
 model must fit out of sample data

7. Empirical Framework for Large-Scale Policy Analysis (cont.)
Focus on Detroit metropolitan area
Estimate a general equilibrium model for the Detroit metropolitan area using 1990 data
Use parameter estimates to predict the effects of the actual reform in 2000
Compare predictions with 2000 data
Simulate counterfactual school finance reforms

8. Contributions To literature on large-scale policy analysis
Estimate and validate model
Estimation rather than calibration
Model validation: need a regime shift
first validation of a Tiebout model
Are counterfactuals plausible?
In my counterfactuals, public good adjusts endogenously

9. Contributions (cont.) To the analysis of school finance reform
General rather than partial equilibrium
Structural estimation
Current analysis consistent with reduced form studies for MI
Study counterfactuals in school finance reform
Analysis applicable to other metro areas (18 states currently litigating) and other types of policies

10. Model Builds upon Ferreyra (2007) and Nechyba (1999)
Community Structure for Metro area:
A continuum of houses and households
D districts; one public school per district
Each district has neighborhoods (housing qualities)
A house gives entrance into the district’s school

11. Model (cont.) Households:
One child per household; child goes to school
Households vary in endowment and idiosyncratic preferences for locations

12. Model (cont.) Household preferences: c = consumption
S = school quality
K = neighborhood quality
Households pay taxes:
Local property tax
State income tax

13. Model (cont.) Schools: School Funding:
Vary in quality across districts
Quality (achievement) is a function of:
Spending per student x
Peer quality q ( = avg. income)
School Funding:
Property taxes:
Chosen by majority voting per district
Paid by residential and non-residential owners
Income taxes

14. Model (cont.) Households choose: Equilibrium: Location (and school)
Property taxes
Equilibrium:
Who lives where  district demographic compositions
Rental Values
School spending
School peer qualities
School qualities
… such that nobody wishes to move or vote differently

15. Estimation Match 1990 data at the district level 83 school districts
4 parameters

16. Detroit Metropolitan Area in 1990

17. Detroit Metropolitan Area in 1990 (cont.)

18. Estimation (cont.)
Challenge of estimating general equilibrium models: all equilibrium conditions must hold
My approach: full solution estimation (Ferreyra 2007)
Compute the equilibrium given 1990 exogenous variables
Metro area income distribution
Housing stock: quantity and quality across districts
School finance regime
Fit in-sample (1990) data well
According to estimates, higher role for peer quality (household income) than for spending (0.87 out of 1)

19. Model Validation Compute equilibrium given 2000 exogenous data
Model fits 2000 data reasonably well
2000 levels
Changes between 90 and 00
Confidence in model for policy analysis and counterfactuals

20. Policy Analysis: Proposal A
Recall: tax reform, and revenue reform
Some revenue equalization
Capitalization of tax and revenue reform
Greater gains for low-income and urban districts
Very little effect on district demographics
Revenues do no affect school quality much
Low housing quality in favored districts
Achievement gap across districts shrinks little

21. Alternative Policies District Power Equalization:
Property tax revenue per child = tax rate * property tax base per child
To equalize effectively, set a very high guaranteed tax base  fiscally very costly
… yet tax rates differ across districts!
Affects high-income districts
… but it preserves local autonomy
Not very effective to close the achievement gap

22. Alternative Policies (cont.)
Uniform Foundation (full equalization)
low foundation ($6,000)
Very little effect
High foundation ($15,000)
Hurts high income districts and property values more
No more effective than low foundation for achievement gap

23. Alternative Policies (cont.)
Adequacy
Costing-out studies
Answer depends on achievement target
for target = 30% of highest-achieving district:
Income tax rate = 10%
Partial-equilibrium estimate is 65%
For target = 30%:
City of Detroit gets $30,000 per student; other districts get funding b/w $20,000 and $100,000 per student
Relocations are still limited
Rental values fall in most places
Most effective in achievement; also most costly

24. Alternative Policies (cont.)
For target = 40%:
Income tax rate = 45%
No Child Left Behind targets a 100% proficiency rate by 2013/14
Prohibitively costly IF no other tools were used

25. Policy Analysis (cont.)
Little room for revenue-based policies
Extra money is not very effective under the current conditions
Accountability
Seemingly effective for low-income districts; low cost
Raise peer quality
Interdistrict open enrollment
What peer quality measures
Parental inputs and early childhood
Non-cognitive skills

26. Concluding Remarks Empirical framework for large-scale policy analysis
use the policy shift for out-of-sample prediction
Here: estimate model with 1990 data; predict 2000.
Ability to quantify g.e. effects
Large-scale policies are very costly and may have unintended effects bring rigor to the policy analysis