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1315 E 10th St

Bloomington, IN 47405

Email: wp2@iu.edu

Indiana University Bloomington
Last Update: October 30, 2024

Wooserk Park
Indiana University Bloomington
Last Update: October 30, 2024

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State vs. Local Management of the Fiscal Commons in Educational Equity: Evidence from California Tax Increment Financing

State vs. Local Management of the Fiscal Commons in Educational Equity: Evidence from California Tax Increment Financing

Journal (TBA)

Work-in-progress

Abstract (Last Update: August 06, 2024)

Abstract (Last Update: August 06, 2024)

Abstract (Last Update: Aug. 06, 2024)

This paper evaluates the effectiveness of higher-level government intervention in internalizing externalities, as opposed to lower-level administrative action. We analyze California's 2011 legislative and Supreme Court decision to shift control of property tax use and related redevelopment initiatives from local to state control. We use this natural experiment to examine how this policy change affects the provision of equitable education. To estimate the effects, we use California state education finance data between FY2004 and FY2022, along with state legislative and administrative documents that describe the timing and magnitude of property asset transfers and their uses. Using a propensity score-weighted difference-in-differences approach, our preliminary results indicate that school districts that took control of Tax Increment Financing (TIF) assets increased per-pupil spending allocations by 3.5 percent annually compared to similar districts without TIF assets. However, this increase is primarily driven by a reduction in direct state aid, possibly related to Equalization Act mandates. The following investigation plans to document the causal mechanisms behind state mandates designed to reduce residential sorting, as well as local governments' conflicting roles in promoting residents' welfare.

This paper evaluates the effectiveness of higher-level government intervention in internalizing externalities, as opposed to lower-level administrative action. We analyze California's 2011 legislative and Supreme Court decision to shift control of property tax use and related redevelopment initiatives from local to state control. We use this natural experiment to examine how this policy change affects the provision of equitable education. To estimate the effects, we use California state education finance data between FY2004 and FY2022, along with state legislative and administrative documents that describe the timing and magnitude of property asset transfers and their uses. Using a propensity score-weighted difference-in-differences approach, our preliminary results indicate that school districts that took control of Tax Increment Financing (TIF) assets increased per-pupil spending allocations by 3.5 percent annually compared to similar districts without TIF assets. However, this increase is primarily driven by a reduction in direct state aid, possibly related to Equalization Act mandates. The following investigation plans to document the causal mechanisms behind state mandates designed to reduce residential sorting, as well as local governments' conflicting roles in promoting residents' welfare.

This paper evaluates the effectiveness of higher-level government intervention in internalizing externalities, as opposed to lower-level administrative action. We analyze California's 2011 legislative and Supreme Court decision to shift control of property tax use and related redevelopment initiatives from local to state control. We use this natural experiment to examine how this policy change affects the provision of equitable education. To estimate the effects, we use California state education finance data between FY2004 and FY2022, along with state legislative and administrative documents that describe the timing and magnitude of property asset transfers and their uses. Using a propensity score-weighted difference-in-differences approach, our preliminary results indicate that school districts that took control of Tax Increment Financing (TIF) assets increased per-pupil spending allocations by 3.5 percent annually compared to similar districts without TIF assets. However, this increase is primarily driven by a reduction in direct state aid, possibly related to Equalization Act mandates. The following investigation plans to document the causal mechanisms behind state mandates designed to reduce residential sorting, as well as local governments' conflicting roles in promoting residents' welfare.

Selected Figures & Tables

Selected Figures & Tables

Selected Figures & Tables

Figures 1a & 1b.
California School Districts and Tax Increment Financing Districts Maps

Figures 1a & 1b.
California School Districts and Tax Increment Financing Districts Maps

Figures 1a & 1b.
California School Districts and Tax Increment Financing Districts Maps

California Tax Increment Financing

Figure 1a. Census Unified and Elementary School Districts

Figure 1a. Census Unified and Elementary School Districts

California Tax Increment Financing

Figure 1a. Census Unified and Elementary School Districts

California Tax Increment Financing

Figure 1b. Tax Increment Financing Districts

Figure 1b. Tax Increment Financing Districts

Figure 1b. Tax Increment Financing Districts

Figure 1a shows a map of California school districts using geocoordinate data from the California Geoportal. The map uses pink to represent unified school districts and blue to represent elementary school categories. As of the 2022-2023 academic year, this dataset includes records for 939 school districts. Figure 1b shows whether school districts used tax increment financing (pink shaded) or not (none).

Figure 1a shows a map of California school districts using geocoordinate data from the California Geoportal. The map uses pink to represent unified school districts and blue to represent elementary school categories. As of the 2022-2023 academic year, this dataset includes records for 939 school districts. Figure 1b shows whether school districts used tax increment financing (pink shaded) or not (none).

Figure 1a shows a map of California school districts using geocoordinate data from the California Geoportal. The map uses pink to represent unified school districts and blue to represent elementary school categories. As of the 2022-2023 academic year, this dataset includes records for 939 school districts. Figure 1b shows whether school districts used tax increment financing (pink shaded) or not (none).

Figures 2a & 2b.
California Students Information

Figures 2a & 2b.
California Students Information

Figures 2a & 2b.
California Students Information

California Tax Increment Financing

Figure 2a. Total Students

Figure 2a. Total Students

Figure 2a. Total Students

California Tax Increment Financing

Figure 2a. Students (Economically Disadvantaged)

Figure 2a. Students (Economically Disadvantaged)

Figure 2a. Students (Economically Disadvantaged)

Note: Figures 2a and 2b show the proportions of total number of students (Figure 2a) and the subset of economically disadvantaged students (Figure 2b).

Note: Figures 2a and 2b show the proportions of total number of students (Figure 2a) and the subset of economically disadvantaged students (Figure 2b).

Note: Figures 2a and 2b show the proportions of total number of students (Figure 2a) and the subset of economically disadvantaged students (Figure 2b).

Figures 3a & 3b.
California Land Use Classification and Development

Figures 3a & 3b.
California Land Use Classification and Development

Figures 3a & 3b.
California Land Use Classification and Development

California Tax Increment Financing

Figure 3a. Land Use

Figure 3a. Land Use

Figure 3a. Land Use

California Tax Increment Financing

Figure 3b. Modestly Developed Parcels

Figure 3b. Modestly Developed Parcels

Figure 3b. Modestly Developed Parcels

Note: Figures 3a and 3b show the land use classifications (Figure 3a) and the parcels extracted specifically for moderately developed areas (Figure 3b).

Note: Figures 3a and 3b show the land use classifications (Figure 3a) and the parcels extracted specifically for moderately developed areas (Figure 3b).

Note: Figures 3a and 3b show the land use classifications (Figure 3a) and the parcels extracted specifically for moderately developed areas (Figure 3b).

Figures 4a & 4b.
State Education Expenditure by Categories

Figures 4a & 4b.
State Education Expenditure by Categories

Figures 4a & 4b.
State Education Expenditure by Categories

California Tax Increment Financing

Figure 4a. Tax Increment Financing School Districts

Figure 4a. Tax Increment Financing School Districts

Figure 4a. Tax Increment Financing School Districts

California Tax Increment Financing

Figure 4b. Non-Tax Increment Financing School Districts

Figure 4b. Non-Tax Increment Financing School Districts

Figure 4b. Non-Tax Increment Financing School Districts

Note: Figures 4a and 4b show state-level education expenditures for school districts that used tax increment financing (Figure 4a) and those that did not (Figure 4b).

Note: Figures 4a and 4b show state-level education expenditures for school districts that used tax increment financing (Figure 4a) and those that did not (Figure 4b).

Note: Figures 4a and 4b show state-level education expenditures for school districts that used tax increment financing (Figure 4a) and those that did not (Figure 4b).

Figures 5a, 5b, & 5c.
Empirical Identification Strategy (Preliminary Results)

Figures 5a, 5b, & 5c.
Empirical Identification Strategy (Preliminary Results)

Figures 5a, 5b, & 5c.
Empirical Identification Strategy (Preliminary Results)

California Tax Increment Financing

Figure 5a. Two-way Fixed Effect

Figure 5a. Two-way Fixed Effect

Figure 5a. Two-way Fixed Effect

California Tax Increment Financing

Figure 5b. Sensitivity Analysis

Figure 5b. Sensitivity Analysis

Figure 5b. Sensitivity Analysis

Opportunity Zone Designation

Figure 5c. Bound Test (Rambachan & Roth, 2022)

Figure 5c. Bound Test (Rambachan & Roth, 2022)

Figure 5c. Bound Test (Rambachan & Roth, 2022)

Note: Figure 5a evaluates the impact of the dissolution of California's redevelopment agencies using a two-way fixed effects model. Figure 5b conducts a sensitivity analysis with various identification strategies for difference-in-differences (DiD) analysis. This part includes the approach of Callaway and Sant'Anna (2021), which uses propensity score-weighted DiD to match treatment and control groups with similar characteristics. Note that this analysis uses a code developed by Borusyak (2023). Figure 5c examines the violation of the pre-trend using the methodology of Rambachan and Roth (2022).

Note: Figure 5a evaluates the impact of the dissolution of California's redevelopment agencies using a two-way fixed effects model. Figure 5b conducts a sensitivity analysis with various identification strategies for difference-in-differences (DiD) analysis. This part includes the approach of Callaway and Sant'Anna (2021), which uses propensity score-weighted DiD to match treatment and control groups with similar characteristics. Note that this analysis uses a code developed by Borusyak (2023). Figure 5c examines the violation of the pre-trend using the methodology of Rambachan and Roth (2022).

Note: Figure 5a evaluates the impact of the dissolution of California's redevelopment agencies using a two-way fixed effects model. Figure 5b conducts a sensitivity analysis with various identification strategies for difference-in-differences (DiD) analysis. This part includes the approach of Callaway and Sant'Anna (2021), which uses propensity score-weighted DiD to match treatment and control groups with similar characteristics. Note that this analysis uses a code developed by Borusyak (2023). Figure 5c examines the violation of the pre-trend using the methodology of Rambachan and Roth (2022).

Table 1.
Summary Statistics

Table 1.
Summary Statistics

Table 1.
Summary Statistics

National Flood Insurance

Note: This table present the summary table of selected variables at the school district level for the education expenditure per pupil. "Count," "Mean," "SD," "Min," and "Max" are the number of observations, the sample mean, the standard deviation, and the minimum and maximum values, respectively.

Note: This table present the summary table of selected variables at the school district level for the education expenditure per pupil. "Count," "Mean," "SD," "Min," and "Max" are the number of observations, the sample mean, the standard deviation, and the minimum and maximum values, respectively.

Note: This table present the summary table of selected variables at the school district level for the education expenditure per pupil. "Count," "Mean," "SD," "Min," and "Max" are the number of observations, the sample mean, the standard deviation, and the minimum and maximum values, respectively.

Conclusion

Conclusion

Conclusion

Work-in-progress.

Work-in-progress.

Work-in-progress.

National Flood Insurance

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