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Assessing post-census state poverty estimates

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Abstract

While the decennial census provides poverty figures for states and other subnational geographic units every ten years, their utility declines over the course of a decade. Consequently, there is growing interest in producing post-census estimates for a variety of indicators. This study extends recent efforts to estimate post-census poverty figures for states by producing such estimates using a multiple regression approach. The accuracy of the multiple regression estimates along with recently produced estimates from the Current Population Survey (CPS) are evaluated relative to the decennial census. The mean absolute percentage point error (MAPPE) using the ratio-correlation technique (1.56 percentage points) was somewhat higher than the MAPPE of 1989 CPS (1.37 percentage points) and an average of 1988–1990 CPS data (1.15 percentage points). However, a simple regression technique using data from 1979 to estimate poverty in 1989 produced a set of estimates where the MAPPE (1.37 percentage points) is nearly as accurate as the single-year CPS estimates. Estimates which average regression estimates and CPS-based estimates are more accurate than either regression or CPS estimates used alone. Several suggestions are offered for improving regression estimates.

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References

  • Bousfield, M.V. (1977). Intercensal estimation using a current sample and census data,Review of Public Data Use 5: 6–15.

    Google Scholar 

  • Center for the Study of Social Policy (1992).Kids count data book: State profiles of child well-being. Washington, DC.

  • Children's Defense Fund (1990). Children 1990: A report card, briefing book, and action primer. Washington, DC: Children's Defense Fund.

    Google Scholar 

  • Committee on National Statistics (1993). Planning the decennial census: Interim report. Washington, DC: National Research Council.

    Google Scholar 

  • Dunton, N. & Leon, S. (1988). Experimental estimates of poverty in New York State Counties. Paper presented at the National Conference on Applied Demography, Bowling Green State University, Bowling Green, OH, 19 September 1988.

    Google Scholar 

  • Ericksen, E. P. (1973). A method for combining sample survey data and symptomatic indicators to obtain population estimates for local areas,Demography 10: 137–160.

    Google Scholar 

  • Ewing, F.J. & McIntyre, J.H. (no date).Intercensal county level poverty estimates. North Carolina State Data Center, North Carolina Office of State Budget and Management.

  • Farley, R., Peek, C. & Danziger, S. (1991). Proceedings of the social statistic's section of the American Statistical Association, meeting August 1991.

  • Goldberg, D., Rao, V.R. & Namboodiri, N.K. (1964). A test of accuracy of ratio-correlation population estimates,Land Economics 40: 100–102.

    Google Scholar 

  • Herriot, R.A. & Schneider, P. (1990) Improved intercensal demographic estimates for small areas: An interim approach. Paper presented at the American Statistical Association Meeting, August 1990, Anaheim CA.

  • Haveman, J.D., Danziger, S. & Plotnick, R.D. (1991). State poverty rates for whites, blacks, and hispanics in the late 1980s,Focus 13(1), University of Wisconsin, Madison.

  • Koebel, C.T. & Price, M.L. (1988). Annual estimates of poverty for counties in Kentucky: 1979–86. Urban Studies Center, College of Urban and Public Affairs, University of Louisville.

  • Larrick, D. (1988). Poverty project: Report on methods. Ohio Department of Development, Office of Research, Ohio Data Users Center.

  • Mandell, M. & Tayman, J. (1979). A test of the accuracy of the ratio-correlation and difference correlation method in a high-growth state. Paper delivered at the Southern Regional Demographic Group's annual meeting, 17–19 October 1979, Myrtle Beach, SC.

  • Martin, J. & Serow, W. (1978). Estimating demographic characteristics using the ratio-correlation method,Demography 15: 223–233.

    Google Scholar 

  • McMurry, M. (1986). Substate estimates of income and poverty. Paper presented at the University of Wisconsin Workshop on Poverty, Madison, WI.

  • Namboodiri, N.K. (1972). On the ratio-correlation and related methods of subnational population estimation,Demography 9: 443–453.

    Google Scholar 

  • Namboodiri, N.K. & Lalu, N.M. (1971). The average of several simple regression estimates as an alternative to the multiple regression estimate in post censal and intercensal population estimation: A case study,Rural Sociology 36: 187–194.

    Google Scholar 

  • O'Hare, W.P. (1976). Report on a multiple regression method for making population estimates,Demography 13: 369–379.

    Google Scholar 

  • O'Hare, W.P. (1980). A note on the use of regression methods in population estimates,Demography 17: 341–343.

    Google Scholar 

  • O'Hare, W.P. (1983). Analyzing the difference in poverty estimates from the decennial census and the current population survey. Paper delivered at the annual meeting of the Southern Regional Demographic Group, 19–21 October 1983, Chattanooga, TN.

  • O'Hare, W.P. (1989). Post-census state poverty estimates. Paper delivered at the annual meeting of the American Statistical Association, 8 August 1989, Washington, DC.

  • O'Hare, W.P. (1993). Post-census state poverty estimates. Paper delivered at the Population Association of America meeting, 2 April 1993, Cincinnati.

  • O'Hare, W.P., Mann, T., Porter, K. & Greenstein, R. (1990). Real life poverty in America: Where the American public would set the poverty line. Washington, DC: Center on Budget and Policy Priorities.

    Google Scholar 

  • Plotnick, R.D. & Danziger, S. (1988). Poverty rates by state in the mid-1980s: An update,Focus 11(3): 12–14.

    Google Scholar 

  • Pollard, K.M. (1989). The dilemma in estimating post-census state poverty rates,Population Today (Population Reference Bureau) 17(10): 6–7.

    Google Scholar 

  • Pursell, D.E. (1970). Improving-population estimates with the use of dummy variables,Demography 7: 87–91.

    Google Scholar 

  • Rosenberg, H. (1968). Improving current population estimates through stratification,Land Economics 44: 331–338.

    Google Scholar 

  • Ross, C. & Danziger, S. (1987). Poverty rates by state, 1979 and 1985: A research note,Focus 10(3): 1–5.

    Google Scholar 

  • Ruggles, P. (1990).Drawing the line: Alternative poverty measures and their implications for public policy. Washington DC: The Urban Institute Press.

    Google Scholar 

  • Sawyer, T.C. (1993). Poverty data improvement Act of 1993), H.R. 1645),Congressional Record, 139(50).

  • Serow, W. & Martin, J. (1977). Estimating demographic characteristics using the ratio-correlation method,Demography 15: 223–233.

    Google Scholar 

  • Schmitt, R.C. & Crosetti, A.H. (1954). Accuracy of the ratio-correlation method for estimating postcensal population,Land Economics 30: 279–281.

    Google Scholar 

  • Schmitt, R.C. & Grier, J.M. (1966). A method of estimating the population of minor civil division,Rural Sociology 31: 355–361.

    Google Scholar 

  • Schirm, A.L., Swearingen, G.D. & Hendricks, C.S. (1992). Development and evaluation of alternative state estimates of poverty, food stamp program eligibility, and food stamp program participation. Paper prepared by Mathematica Policy Research, Inc., for the Food and Nutrition Service, US Department of Agriculture.

  • Spar, M. & Martin, J. (1979). Refinements to regression-based estimates of postcensal population characteristics,Review of Public Data Use 7(5/6).

  • Swanson, D. (1978). An evaluation of ‘Ratio’ and ‘Difference’ regression models for estimating small, highly concentrated populations: The case of ethnic groups,Review of Public Data Use 6: 18–27.

    Google Scholar 

  • Swanson, D. (1980). Improving accuracy in multiple regression estimates of population using principles from causal modeling,Demography 17: 413–427.

    Google Scholar 

  • Swanson, D. (1989). A state-based regression model for estimating substate life expectancy,Demography 26: 161–170.

    Google Scholar 

  • Texas Department of Health (1988). County poverty population model and estimates. Bureau of State Health Data and Policy Analysis and Budget, Texas State Department of Health, and Data Analysis Division, Texas State Department of Human Services.

  • US Bureau of the Census (1973). Federal-state cooperative program for local population estimates — 1 April 1970,Current Population Reports, Series P-26, No. 21.

  • US Bureau of the Census (1985). Evaluation of 1980 subcounty population estimates,Current Population Reports, Series P-25, No. 963.

  • US Bureau of the Census (1987a). Receipt of selected noncash benefits: 1985,Current Population Reports, Series P-60, No. 155.

  • US Bureau of the Census (1987b). Poverty in the United States: 1985,Current Population Reports, Series P-60, No. 158.

  • US Bureau of the Census (1991a). Major research and development components for the year 2000 census and census-related activities for 2000–2009, Version 1.0, prepared by the Year 2000 Research and Development Staff.

  • US Bureau of the Census (1991b). Poverty in the United States: 1990,Current Population Reports, Series P-60 No. 175.

  • US Bureau of the Census (1992). Poverty in the United States: 1991,Current Population Reports, Series P-60 No. 181.

  • US General Accounting Office (1990). Decennial census: Preliminary 1990 lessons learned indicates need to rethink census approach. Testimony of L. Nye Stevens before the Subcommittee on Census and Population, Committee on Post Office and Civil Service, House of Representatives.

  • Zeller, G. (1986). Ohio poverty indicators: Trends 1980–1986. Council for Economic Opportunities in Greater Cleveland, Cleveland.

    Google Scholar 

  • Zitter, M. & Shryock, H.S. (1964). Accuracy of methods of preparing postcensal population estimates for states and local areas,Demography 1: 227–241.

    Google Scholar 

Download references

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  1. Center for Urban and Economic Research, University of Louisville, 40292, Louisville, KY, USA

    William P. O'Hare

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O'Hare, W.P. Assessing post-census state poverty estimates. Popul Res Policy Rev 12, 261–275 (1993). https://doi.org/10.1007/BF01074388

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