Page 61
6
Anticipated Panel Activities
In the past 30 years, there has been considerable research related to formula-based fund allocation programs. Findings and recommendations made two decades ago remain timely and relevant (see Box 6-1 for a summary). To make additional progress, the Panel on Formula Allocations will address both broad and focused issues relevant to developing, implementing, and evaluating federal and state programs.
A broad view will be provided by the panel's already initiated summary of goals, inputs, and formula features for the universe of federal funds allocation programs listed in the General Services Administration's Catalogue of Federal Domestic Assistance. Similar summaries will be considered for selected state programs.
To increase understanding of formula allocation processes and of the role of Congress and federal or state agencies in developing and administering formula-based fund allocation programs, the panel plans to commission a series of papers on some or all of the following topics:
1. Retrospective case studies of the evolution of formula allocations for specific programs. The universe for these studies would be formula allocation programs which have been in operation for a substantial period of time. The focus of each study will be on how the formula and the allocation process have changed over time, the reasons that changes were made, and evaluation of their effects on equity, efficiency, or other appropriate measures of program effectiveness. See the list of relevant program features
Page 62
BOX 6-1Previous Recommendations on Allocation Formula Design
|
below for additional details. A commissioned paper may cover a single program or more than one program. Programs that might be covered fall into three groups:
(a) U.S. federal formula allocation programs. Some good candidates might include Elementary and Secondary Education Act Title I, the Special Supplemental Nutrition Program for Women, Infants, and Chil-
Page 63
dren (WIC), the State Children's Health Insurance Program, the Substance Abuse and Mental Health Services Administration (SAMHSA) Block Grants, Medicaid, Highway Planning and Construction, Employment and Training Assistance, and Special Education Grants to States under the Individuals with Disabilities Education Act.
(b) State programs, i.e., programs in which state governments use formulas to allocate state funds to counties, municipalities, and other jurisdictions. A case study might focus on a particular state or cover similar programs in two or more states. State aid to education is an area of considerable current interest.
(c) Foreign and international formula allocation programs. Examples of foreign programs would be Canada's system for fiscal equalization among its provinces or for allocating revenues from “harmonized sales taxes” among the federal and three participating provincial governments. At the international level, several agencies, such as the United Nations, the International Monetary Fund, and the U.N. Development Programme, use formulas to allocate aid funds.
2. Prospective case studies of specific programs or groups of programs. These studies would cover areas in which significant developments are expected to occur during the projected life of the Panel on Formula Allocations. Possible examples are:
(a) The reauthorization process for the Temporary Assistance for Needy Families block grant program. The program will be coming up for reauthorization soon, providing an opportunity for a sort of anthropological/organizational study, tracking and analyzing the roles of congressional staff, federal, and state agency staff and other players in the process. The paper would describe the initial allocation procedures established under the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 and subsequent changes, including any that may be included in the reauthorization legislation. High-performance bonuses are a special feature that may merit attention. (b) Revision of New York state's formula for the allocation of state education funds. A recent court decision has declared the current formula to be unconstitutional and has given the legislature until September 2001 to revise it (the case may be appealed). This paper might be expanded to cover similar recent developments in other states. (c) A study of several continuing programs whose allocation for-
Page 64
mulas rely on decennial census data. Describe in detail how the transition from 1990 to 2000 census data takes place. Are new legislation or regulations needed? Which year's allocations are the first to be affected? How is the transition affected by hold-harmless provisions? What can be learned about how to improve future transitions when new decennial census data are released (or are replaced by American Community Survey data)?
3. A quantitative analysis of historical trends in U.S. formula allocation programs: 19xx to 2000. Using data from the Federal Assistance Awards Data System (FAADS) and other sources, develop annual time series data for the amounts of federal funds distributed to states and other recipients through formula allocation programs. To the extent possible, provide data classified by type of program, type of recipient, and other salient characteristics. An initial conceptual analysis will be needed to determine the scope of programs to be included and define appropriate classification variables. The FAADS data go back only to 1981; other sources will be needed to extend the series farther back, and there may be problems in achieving comparability among different sources.
4. An analysis of long-term effects of formula allocations on the legislative process. A historical analysis of how the introduction and increasingly widespread use of formula allocation processes has helped national and state legislatures in their functioning, for example, by shifting the language of the debate.
5. Alternative measures of fiscal capacity. Measures of fiscal capacity or capability are often used in allocation formulas to represent the possibility of a recipient area meeting its needs from state, local, or private funds. The most commonly used measure has been and still is per capita income. In 1989, in response to a congressional requirement, an alternative measure, total taxable resources, was developed by the U.S. Treasury Department's Office of Economic Policy for use in the allocation formula for the SAMHSA block grants. This study would evaluate these two alternative measures, comparing their suitability from a conceptual point of view, the quality and timeliness of the data sources used, and other relevant features. The evaluation might include comparisons of the effects of using the two measures in specific formula allocation programs, such as Medicaid.
Page 65
6. An empirical analysis of the effects of hold-harmless provisions. Building on the work of Zaslavsky and Schirm (2000), describe the various kinds of hold-harmless provisions that have been used and how they interact over time with changes in the total amounts appropriated for the program and with other formula features, such as thresholds. Include some real examples showing what the allocations would have been with and without hold-harmless provisions.
7. The rationale for hold-harmless and threshold provisions in formulas. For the most part, allocation formulas are based on measures of need, capacity, effort, and cost that are more or less directly related to program goals. Other formula features, such as hold-harmless provisions and thresholds, are often added on the grounds that they are needed for reasons of administrative efficiency, for example, to avoid disruptions caused by large changes in the amounts received from one year to the next. The purpose of this study would be to undertake a detailed analysis of the rationale for such formula provisions, examine how they vary among programs, and, if possible, gather empirical evidence about how effectively they are meeting their stated objectives. As part of the study, the experiences and views of local program administrators should be sought.
8. Procedures for combining different components of allocation formulas. Many formulas incorporate different components representing need, capacity, effort, and costs, although it is challenging to determine how best to combine these components in a single allocation formula. Examine a large number of allocation formulas with multiple components to identify methods used to combine them. Develop a typology of alternative methods and identify their advantages and disadvantages.
9. The role of the public comment process in the development of allocation formulas. In those instances in which some features of the allocation process are determined by regulation rather than legislation, the proposed regulations have to be published in the Federal Register for public comment. Identify some instances in which this has occurred, analyze the volume, nature, and sources of comments received, and analyze changes to the proposed regulations as a result of the public comment process.
10. Measuring the effects of the statistical properties of input data on the achievement of program goals. Several studies have examined the effects of
Page 66
the statistical properties of input data, such as sampling variance, persistent bias, and lack of conceptual fit, on formula allocations and on the degree of equity achieved by the process. However, very little is known about how such errors affect the achievement of program goals. The purpose of this paper would be to develop prospectuses for one or more experimental or quasi-experimental studies designed to measure gains in efficiency that might result from investment in the development of more accurate input data. Specific programs would be identified for the proposed experiments and design protocols proposed.
11. Facilitating analysis and interpretation of simulations of alternative allocation formulas. Simulations of alternative formulas and processes are frequently used in the development of new programs and the revision of existing allocation formulas. Given the complexity of many formulas and the sometimes unexpected ways in which formula elements and features interact, it may be difficult, even for statisticians, to evaluate the outputs of simulations. This paper would attempt to identify summary measures and graphical outputs that would make it easier for interested parties to understand the properties of alternative formulas and make choices among them.
Each of the case studies (topic 1 above) will describe the establishment and subsequent development of one or more formula allocation programs. If more than one program is included, the programs will be selected either because they have similar objectives and target populations or because they illustrate significant contrasts in approaches to formula allocation.
The relevant program features include:
-
program goals;
-
target population, if applicable;
-
a brief description of services provided by the program;
-
first-level recipient units, e.g., states, counties, metropolitan areas;
-
the formula and its elements, including need, capacity, effort, and cost;
-
information, from legislative history and other sources, about considerations that affected the formula's initial development;
-
sources of input data used to estimate formula elements;
-
other formula features, such as thresholds, minimums, and hold-harmless provisions;
Page 67
research studies designed to measure and suggest possible improvements in the equity or efficiency of the allocation process;
studies designed to evaluate impacts of the program; and
the relationships between legislators, program agencies, recipient units, and other interested parties in the operation of the program.
The primary focus of each case study will be on changes in these program features during the life of the program. What specific changes occurred, why were they made, and how did they affect the achievement of program goals? Other commissioned papers will address topics such as alternative measures of fiscal capacity, the rationale for and effects of hold-harmless and threshold provisions in formulas, and procedures for combining different components of formulas. For a selected set of programs, the panel intends to study statistical properties involving formula inputs, features, and outputs, and to compare actual allocations to those that would have resulted from using alternative formulas or processes.
The panel anticipates developing examples of good and poor practice, including consideration of allocation programs that do not use formulas and programs that have changed after an evaluation (e.g., WIC). To provide background for possible changes in the properties or types of input data as new data sources become available in the next few years, the panel will document the principal data sources currently used in the major formula based allocation programs. The panel will also identify information gaps and potential new information sources.
Fund allocation programs are extremely complicated systems. Their design, implementation, and evaluation are very specialized activities and require understanding of diverse fields. Not surprisingly, there is a knowledge gap. To help bridge this gap, increase public understanding, and increase the effectiveness of formula-based fund allocation programs, the panel plans to develop a handbook that addresses issues in formula program development, implementation, and evaluation ( Box 6-2). The target audience includes members of Congress and their staffs, federal and state policy makers and program administrators, and other interested parties, such as advocacy groups. Principal topics include explaining the complex interrelations between inputs and formula features, necessary a priori and ongoing evaluations, and the properties of the most common data sources. The handbook will aid in developing new allocation formulas and evaluating existing formulas. Issues related to appreciating, accommodating, and communicating uncertainty will receive substantial attention in the handbook.
Page 68
Box 6-2A Handbook on Fund Allocation Formulas: Preliminary Table of Contents
1. Introduction
1.1 Fund allocation formulas: an overview 1.1.1 An early example: the Morrill Act 1.1.2 General Revenue Sharing 1.1.3 A statistical summary of current programs 1.2 The parties involved 1.2.1 The Congress 1.2.2 Program agencies 1.2.3 First-level recipients 1.2.4 Individual beneficiaries 1.3 Alternative approaches 1.3.1 Amounts specified in legislation 1.3.2 Specific formula in legislation 1.3.3 Goals in legislation; formula developed by program agency with public comment 1.4 Types of formula allocations 1.4.1 Closed mathematical statements 1.4.2 Iterative procedures 1.4.3 Matching and cost-sharing provisions 1.5 Purpose of the Handbook 1.6 Intended audience 1.7 Uses of the Handbook 1.7.1 Developing a new formula 1.7.2 Periodic allocations 1.7.3 Analyzing an existing formula 2. Program goals
2.1 Target population 2.2 Services provided 2.3 Desired outcomes 3. Basic formula features
3.1 Target allocation units 3.3.1 Multilevel allocations 3.2 Frequency and timing of disbursements 3.3 Provisions for administrative costs 3.4 Program rules |
Page 69
|
4. Components of formulas
4.1 Measures of need/workload 4.2 Measures of funding capacity 4.3 Cost differentials 4.4 Effort 4.5 Interactions among components 5. Special features of formula allocations
5.1 Thresholds and other eligibility criteria 5.2 Minimum and maximum values 5.3 Hold-harmless provisions 5.4 Interaction of special features with size of and changes in program appropriations 6. Data sources for estimating formula components
6.1 Decennial censuses 6.2 Household surveys 6.3 Other statistical programs 6.4 Administrative records 6.5 Factors to consider in choosing data sources 6.5.1 Conceptual fit 6.5.2 Level of geographic detail available 6.5.3 Timeliness 6.5.4 Quality 6.5.5 Costs of collecting new data or processing existing data 6.6 Combining data sources to produce model-based estimates 6.7 Updating estimates 7. Special topics
7.1 Step functions v. continuous functions 7.2 Hold-harmless provisions v. moving averages 8. Operational considerations
8.1 Steps in developing a new formula 8.2 Quality assurance procedures 8.2.1 Replication 8.2.2 Analysis of change from prior years 8.3 Evaluating a formula 8.3.1 The use of simulation techniques 8.3.2 Exploratory data analysis |
