In 2000, the federal government distributed over $260 billion of funding to state and local governments via 180 formula programs. These programs promote a wide spectrum of economic and social objectives, such as improving educational outcomes and increasing accessibility to medical care, and many are designed to compensate for differences in fiscal capacity that affect governments' abilities to address identified needs. Large amounts of state revenues are also distributed through formula allocation programs to counties, cities, and other jurisdictions. Statistical Issues in Allocating Funds by Formula identifies key issues concerning the design and use of these formulas and advances recommendations for improving the process. In addition to the more narrow issues relating to formula design and input data, the book discusses broader issues created by the interaction of the political process and the use of formulas to allocate funds. Statistical Issues in Allocating Funds by Formula is only up-to-date guide for policymakers who design fund allocation programs. Congress members who are crafting legislation for these programs and federal employees who are in charge of distributing the funds will find this book indispensable.

The use of formulae has become widespread in recent years across most developed countries. In the UK, a conservative estimate is that annually £150 billion of public service expenditure is distributed using formulae, in services such as health care, local government, social security and higher education. This book offers a comprehensive introduction to the theory and practice underlying the use of such formulae as a basis for funding public services. The philosophy, design and economic consequences of funding formulae have become key policy issues worldwide. However, till now, there has been no text which brings together the economic, statistical and political issues underlying formula funding. This key book fills that gap. Written by a leading international expert on the design of funding formulae, this important book includes empirical evidence from a range of countries and will be a valuable resource for all those involved in this field.

Many federal assistance programs are funded by formula grants that have historically relied at least in part on population data from the decennial census and related data to allocate funds. In June 2009, the Census Bureau reported that in FY 2007 the fed. gov¿t. (FG) obligated over $446 billion through funding formulas that rely at least in part on census and related data. This report determined: (1) how much the FG obligates to the largest fed. assistance programs based on the decennial census and related data, and how the Recovery Act changed that amount; and (2) what factors could affect the role of population in grant funding formulas. The report identified the 10 largest fed. assistance programs in FY 2008 and 2009. Charts and tables.

The workshop was a direct outgrowth of a previous study by the CNSTAT Panel on Estimates of Poverty for Small Geographic Areas. That panel, established under a 1994 act of Congress, began its work with a very specific mission: to evaluate the suitability of the U.S. Census Bureau's small-area estimates of poor school-age children for use in the allocation of funds to counties and school districts under Title I of the Elementary and Secondary Education Act. In carrying out their assignment, panel members came to realize that the properties of data sources and statistical procedures used to produce formula estimates, interacting with formula features such as thresholds and hold-harmless provisions, can produce consequences that may not have been anticipated or intended. It also became evident that there is a trade-off between the goals of providing a reasonable amount of stability in funding from one year to the next and redirecting funds to different jurisdictions as true needs change. In one instance, for example, the annual appropriation included a 100 percent hold-harmless provision, ensuring that no recipient would receive less than the year before. However, there was no increase in the total appropriation, with the result that new estimates showing changes in the distribution of program needs across areas had no effect on the allocations. Choosing the Right Formula provides an account of the presentations and discussions at the workshop. The first three chapters cover the overview, case studies, and methodological sessions, respectively. Chapter 4 summarizes the issues discussed in the roundtable and concluding sessions, with emphasis on the identification of questions that might be addressed in a panel study.

Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens. In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit. Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence. Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they've been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years.