How to best hand out money issues in the design and structure of intergovernmental aid formulas
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How to Best Hand Out Money: Issues in the Design and Structure of Intergovernmental Aid Formulas. Thomas A. Downes Department of Economics Tufts University. Introduction. Importance of aid Federal aid 7.3% of revenues in 1999-2000 State aid 49.5%, largest source since 1978-79

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How to Best Hand Out Money: Issues in the Design and Structure of Intergovernmental Aid Formulas

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How to Best Hand Out Money: Issues in the Design and Structure of Intergovernmental Aid Formulas

Thomas A. Downes

Department of Economics

Tufts University


Introduction

  • Importance of aid

    • Federal aid 7.3% of revenues in 1999-2000

    • State aid 49.5%, largest source since 1978-79

  • Categorical v. general aid in the U.S. context

    • In 1999-2000, categorical aid provided 19% of revenues

    • Categorical share largest for districts with largest shares of “at-risk” students


Goals of this talk

  • Issues addressed in talk

    • What are objectives of aid?

    • How do objectives translate into aid formulae and aid programs?

    • What formula is implied by specific aid objective?

    • To what extent do actual formulas deviate from ideal?

    • What are implications of these deviations?


Objectives of Aid

  • Fiscal neutrality

    • Motivated by the existence of fiscal disparities – differences among localities in fiscal capacity and in cost of providing target level of public services

    • Has both efficiency and equity rationales

  • Equitable distribution of tax burdens

    • Motivated by desire to eliminate inequities

    • Definition of horizontal and vertical inequities

  • Correct for inefficiencies in provision

    • Result of mismatch of providers and beneficiaries

    • Need to change incentives of providers


Examples

  • State equalization aid to local school districts

    • Goal ‑ Reduce fiscal disparities

    • Dominant types ‑ Foundation and power‑equalizing

  • Title I Education grants

    • Goal – To provide districts serving significant populations of economically disadvantaged students with the resources to improve the teaching and learning of these students

    • Grants now go directly to most eligible school districts, with grant amounts based loosely on the number children in poverty and on state per pupil expenditures


Classes of Grants

  • Lump‑Sum grants

    • Aid does not depend on actions of recipient

    • Block grants are an example

    • Most categorical grants are lump sum

  • Matching grants

    • Increased spending by recipient increases aid

    • Open‑ended v. closed‑ended


Designing formulae: Common issues

  • Starting point: Closing need and effort gap

  • Basic formula ‑ Aj=F ‑ t*Vj (F is per‑capita spending to supply target service level, t* is formula tax rate, Vj is fiscal capacity)

  • Common issues

    • High capacity jurisdictions and recapture

    • Variation in services provided (equal access v. equal outcomes)

    • Multiple determinants of fiscal capacity

    • Cost adjustment ‑ Aj=CjF ‑ t*Vj (Cj is cost index)


Matching or Lump‑Sum?

  • Objective: Fiscal neutrality ‑ Appropriate formula: Lump‑sum

    • Conditions under which fiscal neutrality is achieved

    • Is result horizontally equitable?

  • Objective: Equitable distribution of tax burdens ‑ Appropriate formula: Lump‑sum

    • Operationalizing objective using average tax effort to establish measure of fiscal capacity

    • Will aid improve horizontal or vertical equity?


Matching or Lump‑Sum?

  • Objective: Correct for underprovision ‑ Appropriate formula: Matching

    • Determinants of the matching rate

    • Killing two birds with one stone ‑ Can matching aid also be used to mitigate locational nonneutralities?

  • Can aid be used to reduce vertical inequities?

  • Tension of objectives


Implementation Problems

  • Accounting for cost/need variation

    • Ad hoc nature of existing cost adjustments

    • Problem 1: No accepted methodology for estimating cost variation

    • Problem 2: Data issues

  • Measuring fiscal capacity

    • Choice of measure depends on objective

    • Preferred measure: Revenue that would be obtained from applying formula tax rate to available tax bases (Representative tax system)


Implementation Problems

  • Recapture

    • Tension ‑ Payments for services v. redistribution

    • Reality ‑ limited recapture

  • Local discretion

    • Local discretion as an impediment to achieving objectives

    • Should discretion be limited?

    • Can discretion really be limited? – The fungibility problem

    • Potential solution ‑ composite aid formulae


Implementation Problems

  • Limiting budgetary liability

    • Tools for controlling liability (lump‑sum) ‑ target spending level, formula tax rate

    • Tools for controlling liability (matching) ‑ matching rate, closed‑ended grants

    • Tensions between budgetary liability and objectives

  • Handling transitions

    • Case for hold‑harmless provisions (stability, fairness)

    • Costs of hold‑harmless provisions (failure to achieve objectives, lock‑in of inappropriate aid distribution)

  • Reasons for failure to achieve objectives


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