Commonly used techniques for estimating the effect of data error on fund allocations are
biased because they fail to account for numerous sources of data error and for
misspecification of the allocation formula itself. Alternative techniquesfor estimating the
effect of data error are presented and applied to estimate the effect of census undercount
on general revenue sharing allocations.
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References
1.
Grindley, W.C., D. Kaskowitz, B.J. Taylor, A.R. Wright, S. Levy, and J. Waksberg (1974) General Revenue Sharing Data Study (Vol. 3). Menlo Park, CA: Stanford Research Institute.
2.
Hill, R.B. and R. Steffes (1975) "Estimating the 1970 census undercount for states and local areas." Urban League Rev.1, 2: 36-45.
3.
Maurice, A.J. and R.P. Nathan (1982) "The census undercount: effects on federal aid to cities." Urban Affairs Q.17, 3: 251-285.
4.
Robinson, J.G. and J.S. Siegel (1979) "Illustrative assessment of the impact of census undernumeration and income underreporting on revenue sharing allocations at the local level." Proceedings of the Social Statistics Section, American Statistical Association. Washington, DC: 636-656.
5.
Savage, I.R., and B.M. Windham (1973) "The importance of bias removal in official use of United States census counts." Tallahassee: Florida State University, Department of Statistics.
6.
Siegel, J.S. (1975) "Coverage of population in the 1970 census and some implications for public programs." Current Population Reports, Series p-23, no. 56, Washington, DC: U.S. Bureau of the Census.
7.
Spencer, B.D. (forthcoming) "Optimal data quality." J. of the Amer. Statistical Assn.
8.
———( 1980) Benefit-Cost Analysis of Data Used to Allocate Funds. New York: Springer-Verlag.
9.
Strauss, R.P. and P.B. Harkins (1974) "The impact of population undercounts in general revenue sharing allocations in New Jersey and Virginia." National Tax J.27: 617-624.
