Community Development Block Grant Formula: Targeting Assistance to High-Need Communities Could Be Enhanced
Published: 2005-04-26T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: Congress asked GAO to comment on the Department of Housing and Urban Development's (HUD) 2005 report on the Community Development Block Grant (CDBG), "CDBG Formula Targeting to Community Development Need." The CDBG program distributes funding to communities using two separate formulas that take into account poverty, older housing, community size, and other factors. That study evaluates the program's funding formula from two perspectives: (1) to what extent do communities with similar needs receive similar CDBG funding, and (2) to what extent are program funds directed to communities with greater community development needs. The HUD report is particularly salient in light of the administration's 2006 budget request which criticizes the program for not effectively targeting high-need communities. Congress asked us to provide our views on the HUD study based on our experience and past assistance to various congressional committees on a wide variety of federal formula funding issues.
section_title: What GAO Found
paragraphs: HUD's report on the CDBG formula provides a thoughtful and sophisticated analysis of those elements of the formula that impede effective and equitable targeting of limited federal resources. Central to HUD's analysis is an index of need that encompasses a wide variety of indicators related to poverty, housing infrastructure, and population growth and decline. While we would question some of the factors in their index, overall we believe it serves as a reasonable basis for evaluating CDBG targeting. The study identifies a number of causes that explain the poor performance of the current formula. The use of two formulas rather than one is an important reason communities with similar needs do not receive similar funding. The use of population size as a need indicator significantly reduces the extent to which funding is directed to high-need communities. Changing the poverty measure to one based on the poverty status of households rather than individuals would avoid large grants to communities with large student populations. An increasing number of communities have attained the minimum population size necessary to be eligible for formula funding and this has also reduced funding to communities with the highest needs. In addition to presenting formula options that address a number of these problems, HUD's study also presents an option that would include per capita income in the formula. The inclusion of per capita income could be justified on the grounds that it directs more funding to communities with weaker economic capacity to meet needs from local resources. However, some of the effect of this factor is offset by introducing an additional factor--metropolitan per capita income. The metropolitan per capita income factor directs more rather than less funding to communities located in high-income metropolitan areas. This works at cross purposes with the local per capita income factor. GAO suggests that Congress consider a needs-based criterion to determine eligibility and eliminate the grandfathering of eligibility into the formula before this approach is adopted as a means of improving the targeting performance of the program.

section_title: Letter
paragraphs: I am pleased to be here today to discuss policy considerations associated  with fashioning a grant targeting policy and provide our observations on  the Department of Housing and Urban Development’s (HUD) report titled:  “CDBG Formula Targeting to Community Development Need.” In our  recent report on 21st Century Challenges, we argue for the importance of  a thorough assessment of federal programs and policies across the board  due to long term fiscal challenges the nation currently faces. In that report  we specifically recommend that programs such as the Community  Development Block Grant (CDBG) be judged according to whether they  target assistance to those with the greatest needs and the least capacity to  meet them.
The CDBG program is a significant direct federal-to-local grant program. It  supports a wide array of local community development activities that are  primarily to benefit low- and moderate-income persons. Program funding  is allocated to local communities using two statutory formulas that take  into account various indicators of community development need. The  HUD report observes that this formula provides widely different payments  to recipients with similar needs and that funds going to the neediest  communities have decreased over time on a per capita basis. The study  then presents several alternative measures of community need that would  systematically focus support on those communities with the greatest need.  This subcommittee asked us to evaluate the HUD report.
The HUD study takes on even greater significance in light of the  administration’s proposal to consolidate 18 federal community and  economic development programs, including CDBG, into a single block  grant. The administration proposal would reduce overall funding by 30  percent. Such a cut raises issues regarding the need to more sharply focus  limited funding on those communities in greatest need. In this regard the  administration’s initiative criticizes the CDBG program as being poorly  targeted, indicating that 38 percent of the funds go to eligible communities  and states with poverty rates below the national average. To improve  targeting, the administration proposal cites both need, specifically poverty,  and economic capacity indicators such as unemployment and job loss as  important indicators of the need for development funding. Criticisms of  poor targeting raise fundamental questions about the relationship between  formula design choices and federal policy goals.
Over the years we have evaluated and provided technical assistance on a  number of formula grant programs. Consequently, we have a broad  perspective on formula design issues. Today I will draw on our past work  on a variety of grant programs to discuss several key issues that can  contribute to good formula design. I will then provide our observations on  HUD’s evaluation of the current formula and the alternative targeting  policies outlined in their report. Finally, I will offer some suggestions the  subcommittee may wish to consider to better account for differences in  local communities’ economic capacities to meet local needs with local  resources. We did not independently verify the reliability of the data used  in HUD’s report nor did we verify their analysis.
To briefly summarize our observations, I would first note that good  formula design and grant targeting depend on a number of important  policy choices. While the HUD study provides a thoughtful analysis of  grant targeting based on improved measurement of program need,  additional issues merit further consideration, including taking into account  not only the need for community infrastructure improvement but also  communities’ economic capacities to address those needs. In addition, the  subcommittee should consider revising eligibility criteria to encompass  both needs and economic capacity.
As agreed with the subcommittee, I will not be commenting on issues  related to the state program that provides funding for non-entitlement  communities. I would be happy to discuss these issues during our question  and answer period if time allows.
subsections: section_title: Grant Formula Design Embodies Several Policy Considerations
paragraphs: Over the years we have reported on a wide variety of grant formula issues.  During the 1970s and 1980s, we issued a number of reports on the funding  formulas used to direct Revenue Sharing funds to local communities based  on both their capacity and willingness to utilize local resources to address  local needs. In anticipation of the 2000 census, we examined the potential  effect of the decennial census population undercount on the distribution  of federal grant funds for 25 large formula grant programs, including  Medicaid. Over the years we have also assisted the Congress in revising  the funding formulas under the Ryan White CARE Act, the Older  Americans Act, Substance Abuse and Mental Health Block grants, and  Title I education grants so that program funding would be more responsive  to changes in program needs. This wide range of experience provides us  with an in-depth understanding of the issues associated with the equitable  and efficient targeting of federal grant dollars.
Based on our past experience, I would like to offer a number of  observations on the design of grant funding formulas. First, grant formulas  reflect an intergovernmental partnership that structures how costs are to  be shared among the various levels of government. When federal  resources represent a declining share of the cost of meeting national goals,  a greater effort to target high-need communities is necessary if federal  funding is to make a significant contribution to closing the fiscal gap  between high- and low-need communities.
Second, targeting grant funding involves two key decisions: 1) determining  which communities are eligible for assistance and 2) how to distribute  funding among eligible communities. A clear statement of policy goals and  objectives is essential as a guide for establishing grantee eligibility  standards and identifying a manageable number of statistical indicators  that can reliably direct formula funding to communities with the greatest  need. Because the CDBG program has a wide variety of policy goals — the  elimination of slums, historic preservation, and promoting more rational  land use, among others — identifying eligibility standards and a  reasonable set of indicators to represent program need is especially  challenging. For example, the CDBG program’s goal of improving the  physical infrastructure of economically distressed communities is  reflected in several of the need indicators used in the program’s formula,  such as poverty and older housing. However, there are no indicators for  historic preservation or rational land use.
In addition to program needs, consideration of fiscal equity or fairness  suggests additional targeting factors beyond need indicators. Here there  are two issues: 1) wide differences in communities’ ability to meet local  needs with local resources and 2) geographic differences in the cost of  financing local development projects. Regarding local resources, high  income communities generally have stronger tax bases from which to fund  program needs without relying on federal assistance compared to lower  income areas. Accordingly, the allocation of scarce resources might reflect  variations in local funding capacity. In addition, the cost issue arises for  areas faced with a high cost-of-living since they would need to pay more  for the workers who actually deliver services at the local level.
Performance indicators are sometimes considered as a targeting factor  though they present challenges as well. Ideally, performance indicators  would reflect only grantee performance and not program outcomes that  result from factors local officials have little ability to control. For example,  it makes little sense to reward a state that has substantially reduced  welfare dependence because it enjoyed a particularly strong economy but  did no better than other grantees in terms of efficiently managing its  welfare programs. Accurate performance indicators are particularly  difficult to develop, especially as they pertain to goals that may take  literally decades to realize. As a consequence, they require an even higher  degree of scrutiny than needs-based indicators before being incorporated  into funding formulas.
For this reason a more common approach to promoting accountability is  to require grantees to provide matching funds for projects funded under  the program. Grantees are likely to be more vigilant in screening and  funding individual projects if they must put a significant portion of their  own resources at risk. While often difficult to enforce, at a minimum, such  a requirement forces public discussion of how grant funds are to be  employed.
section_title: Two Formulas Are Used to Target Program Funding
paragraphs: Before I turn to discussing the HUD study and its findings, I would first  like to provide a brief description of the eligibility standards and funding  formulas now used to target CDBG funding. To obtain entitlement status, a  city must be the principal city of a metropolitan statistical area, as  designated by the Office of Management and Budget (OMB), or have a  population of at least 50,000 residents. An urban county must have a  population of at least 200,000 residents. The formulas used to distribute  funding among eligible communities reflect several broad dimensions of  need. Originally, CDBG funding was distributed to entitlement  communities based on a simple three-factor formula that took into  account:  the number of residents (population), the number of residents living in poverty, and the number of overcrowded housing units.
Beginning in fiscal year 1978, Congress added a second three-factor  formula that included the following need indicators:  the number of residents living in poverty, the number of older housing units, and    slow population growth or decline.
Under this dual formula approach, grantees receive the larger amount  allocated by either the first formula, commonly referred to as formula A,  or the second formula, commonly referred to as formula B. The use of two  formulas, each with three factors, results in allotments exceeding the  funds available for distribution. To avoid this outcome, all grantee  allotments are proportionally reduced to conform to the amount available  for distribution by formula.
section_title: Declining Budget Resources Underscore the Need for More Efficient Targeting of Available Funding
paragraphs: Since the advent of the entitlement portion of the program, the number of  participating communities has nearly doubled, increasing from 606 in  fiscal year 1975 to more than 1,100 in fiscal year 2004. This trend can be  expected to continue both because population will continue to grow and  because new standards for designating metropolitan areas, as promulgated  by OMB and utilized by the program, are also likely to increase the number  of eligible communities.
Since 1978 program funding has declined to roughly half its peak of   $10.2 billion when measured in purchasing power of today’s dollars. When  population growth is factored in, the decline in real per capita spending  has declined by two-thirds, as illustrated in the accompanying figure.
The policy implication of these trends is that with more limited resources,  narrowing the gap between high- and low-need communities can only be  realized by concentrating this more limited funding on high-need  communities. This requires a new look at the program’s eligibility  standards and funding formulas.
section_title: Given the Program’s Broadly Defined Purposes, HUD’s Evaluation Criteria for Grant Targeting Appear Reasonable
paragraphs: The HUD study relies on two generally accepted equity or fairness  principles to evaluate the targeting of CDBG funding: 1) equals should be  treated equally and 2) those with greater needs should receive more than  those with lesser needs. The first principle is based on the idea that  communities with similar needs should receive roughly similar per capita  funding amounts. The second standard is based on the idea that to reduce  the gap between high- and low-need communities, additional funding must  be targeted to communities with greater needs. This criterion is especially  pertinent because, as the HUD report observes, Congress designed a  formula intended to allocate CDBG funds according to variations in  community needs. However, determining the extent to which program  funding is disproportionately allocated to communities with the highest  needs involves value judgments that are the responsibility of policymakers  rather than technicians and administrators. The HUD study measures the  extent to which funding is targeted to high-need communities and leaves it  to policymakers to decide the appropriate degree of needs-based targeting.
Before I address the conclusions reached in the HUD study, I first want to  spend a couple of moments discussing the factors underlying the study’s  need criterion, since all conclusions rest upon its validity. One of the  criticisms directed at the CDBG program in the administration’s fiscal year  2006 budget proposal is that there is a “lack of clarity in the program’s  purpose,” a statement which is supported by the long list of specific  program objectives cited in HUD’s report. Given the broad and diffuse  goals established for the program, it is difficult to identify a few clear and  succinct indicators of program need appropriate for this program. Though  HUD’s need criterion is not immune from criticism, it is, in our view,  reasonable given the program’s diverse objectives. HUD’s criterion is  strongly related to poverty and older housing occupied by low-income  households and a number of other variables related to local poverty  conditions such as education, crime, and racial segregation. These  variables represent 80 percent of HUD’s overall index of need. This, I feel,  represents a reasonable approach for distinguishing between high- and  low-need communities.
Other indicators included in HUD’s need criterion may be more  questionable. For example, overcrowded housing, one of the elements in  the current formula, may be more indicative of a strong local economy  that reflects strong demand pressures in the local housing market rather  than economic decline. In addition, low population densities and strong  population growth, both reflected in HUD’s need criterion, may be more  indicative of strong rather than weak economic conditions. However, to  the extent that these indicators may be problematic, they represent a  comparatively small part of the overall need criterion. Consequently, even  if these factors were eliminated from the need index it is unlikely that they  would affect their main conclusions to any significant degree.
section_title: Many Features of CDBG Funding Formulas Limit Their Ability to Consistently Target High-Need Communities
paragraphs: The HUD study reaches a number of valid conclusions regarding the  targeting performance of the program’s funding formulas. I will just  mention their conclusions to echo the more detailed analysis presented in  the HUD report:    The primary reasons entitlement communities with similar community  development needs receive wide differences in funding are 1) using  two formulas rather than a single formula and 2) the factor that reflects  older housing in formula B results in especially large disparities in  funding among communities with similar needs because units occupied  by higher income residents typically are not in need of rehabilitation at  public expense.
Formula A is most responsible for reducing the extent to which funding  is targeted to high-need communities, because its reliance on general  population precludes greater targeting based on community  development needs.
Changing the poverty measure to one based on the poverty status of  households rather than individuals would avoid awarding large grants  to low-need college towns.
section_title: While HUD Formula Options Improve Needs Targeting, Additional Options Should Also Be Explored before Deciding on a Particular Reform Strategy
paragraphs: In our view, the HUD study has clearly identified the major elements that  limit the current formula’s ability to efficiently and effectively target  funding to high-need communities, and it puts forward a number of  formula alternatives that would strengthen the program in this regard.  Proposals range from a comparatively modest reform to options that result  in a more substantial redistribution of program funding.
The study describes two formula alternatives to improve grant targeting  among entitlement communities that incorporate new need indicators. The  first option, formula alternative one, introduces revised indicators of  poverty, older housing units and slow population growth and decline, and  places greater emphasis on the poverty indicators. It provides modest  improvements by narrowing wide differences in funding received by  communities with similar needs and it directs a larger portion of funding  to high-need communities. The second option, alternative two, takes a  somewhat more aggressive approach by eliminating the use of two  formulas and replacing them with a single formula that includes a range of  indicators related to need. It provides a substantial improvement in the  program’s ability to provide comparable funding for communities with  comparable needs.
However, it is important to point out that neither the poverty indicator  used in the current formula nor the alternative HUD proposes takes into  account geographic differences in the cost-of-living. As a consequence,  both the current formula and the two alternatives probably overstate  needs in communities with relatively low cost-of-living and understate  them in communities with a higher cost-of-living.
I would characterize the first two alternatives as making technical  improvements, in that they utilize better indicators of need and eliminate  the primary causes of wide differences in funding for communities with  similar needs. In contrast, a third option, formula alternative three,  introduces two additional factors—community per capita income and the  per capita income of the wider metropolitan area in which the grantee is  located. Community per capita income (PCI) is used to increase funding  for low-income communities and reduce funding for higher income  communities. The metropolitan PCI factor partly offsets the effect of  community PCI by increasing funding for communities in high-income  metropolitan areas. The net effect of both factors is that the two factors, to  some extent, work at cross purposes. For example, if two communities  located in different metropolitan areas had the same PCI, the community  located in the metropolitan area with a lower area-wide income would  receive less aid than the community located in the high-income  metropolitan area.
The HUD report suggests using the two per capita income factors because  they provide a means of directing more funding to high-need communities.  However, they really are much more than a technical means of producing  more targeting to high-need communities. And for that reason, I would like  to talk about their introduction into the formula in a little more detail.
While these two factors do direct more funding to high-need communities,  they also widen rather than narrow differences in funding among  communities with similar needs, in effect, increasing the error rate if  measured simply in terms of targeting need. The HUD report does not  provide any discussion that would justify allowing funding differences to  widen under this option. The policy question this raises is: Can these  differences be justified by differences in funding capacity or cost  differences?
Clearly, the introduction of per capita income can be justified on the  grounds that it provides a means of taking into account the underlying  economic strength of communities and their ability to fund local needs  from local resources. I would also observe that doing so is consistent with  the administration’s Strengthening America’s Community Initiative, which  emphasizes indicators of economic conditions such as job loss and  unemployment. However, introducing economic capacity also raises the  question of to what extent should low income places be targeted? For  example, should a community with half the average income be given a  grant that is twice the average, or possibly even more? The HUD study  provides one answer to this question. The subcommittee may wish to  consider possibilities with either a greater or lesser effect.
The inclusion of the metropolitan PCI introduces more controversial  issues as well. This factor, rather than targeting more funding to low- income areas, does the opposite. It actually targets more funding to  communities in higher income metropolitan areas. However, the rationale  for doing so is not discussed in HUD’s report. One possible reason for  introducing metropolitan PCI as a factor is that it would take account of  geographic differences in the cost-of-living. However, consensus within  the research community has not yet been achieved regarding the  magnitude of these cost differences. Technical experts are therefore  unable to provide guidance regarding how these cost differences may be  offset in a funding formula. As a consequence, there is no objective basis  to determine if HUD’s use of metropolitan per capita income is  appropriate.
section_title: Concluding Observations
paragraphs: In conclusion, the prospect of increasing budgetary stringency at the  federal level appropriately prompts a reexamination of programs that  respond to challenges faced by communities throughout the nation. The  administration’s proposal to restructure assistance for community  development opens up important issues regarding how to focus such aid  on the nation’s more hard pressed areas.
For the most part, the HUD study does a very effective job of identifying  the critical decisions regarding grant targeting for congressional  consideration. However, additional formula options are not explored as  part of the process of reaching a decision on how best to target CDBG  funding. If program funding continues to decline in inflation-adjusted  dollars, it may be appropriate to go beyond simply a needs-based targeting  policy and consider alternatives to also take into account the underlying  strength of local economies to meet those needs.
Finally, while the formula is a central instrument in targeting program  funding, the criteria used to establish entitlement status could also play an  important role in directing a larger share of program funding to  communities with the greatest need. Rather than the current program’s  reliance on population size as the primary criterion, the subcommittee  may also wish to consider either including a needs-based element in  eligibility standards or establishing a minimum threshold allotment in  order to qualify for entitlement status. Finally, the subcommittee may wish  to reconsider the grandfathering provisions that allow communities that  no longer meet eligibility standards to continue participating in the  entitlement program.
In closing, I would like to emphasize that the targeting issues raised by the  HUD report are important no matter what level of financial support  Congress provides for community development activities. The prospect of  reduced support for such efforts, as proposed by the administration,  would make consideration of these targeting issues particularly salient. I  would also note that GAO’s report on 21st Century Challenges calls for a  reexamination of federal policies and programs to respond to a growing  fiscal imbalance. Central to such a reexamination is assessing how to  better target federal assistance to those with the greatest need and the  least capacity to meet those needs.
Mr. Chairman, this concludes my statement. I would be happy to answer  any questions you or other members of the subcommittee may have. For  future comments or questions regarding this testimony, please contact  Paul L. Posner, Managing Director for Federal Budget Analysis and  Intergovernmental Relations, at (202) 512-9573. Individuals making key  contributions to this testimony included Jerry C. Fastrup, Michael  Springer, Robert Dinkelmeyer, and Michelle Sager.
This is a work of the U.S. government and is not subject to copyright protection in the  United States. It may be reproduced and distributed in its entirety without further  permission from GAO. However, because this work may contain copyrighted images or  other material, permission from the copyright holder may be necessary if you wish to  reproduce this material separately.