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Overview of Estimation Methods

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Subnational Population Estimates

Part of the book series: The Springer Series on Demographic Methods and Population Analysis ((PSDE,volume 31))

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Abstract

Our purpose in this chapter is to provide a general roadmap of subnational population estimation methods, which are covered in detail in subsequent chapters. We set the stage for this overview by differentiating between pre-censal, inter-censal, and post-censal estimates and classifying population estimation methods. Finally we describe the variety of methods currently used to estimate population. This focus of this chapter is on population estimates based on usual residence or de jure. We cover de facto (physically present) population estimates in Chapter 16.

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References

  • Bogue, D. J. (1950). A technique for making extensive population estimates. Journal of the American Statistical Association, 45, 149–163.

    Article  Google Scholar 

  • Bogue, D. J., & Duncan, B. B. (1959). A composite method for estimating post-censal population for small areas by age, sex, and color (Vol. Vital Statistics Special Report, 47). Washington, DC: National Office of Vital Statistics.

    Google Scholar 

  • Bryan, T. (2004b). Population estimates. In J. S. Siegel, & D. A. Swanson (Eds.), The Methods and Materials of Demography, Second Edition (pp. 523–560). New York: Elsevier Academic Press.

    Google Scholar 

  • Causey, B. D. (1984). Dual system estimation based on iterative proportional fitting. SRD Research Report Number: CENSUS/SRD/RR-84/03. Washington, DC: Bureau of the Census.

    Google Scholar 

  • Chambers, R., & Feeney, G. (1977). Log linear models for small area estimation. Belconnen, ACT: Australian Bureau of Statistics.

    Google Scholar 

  • Deming, W. E. (1943). Statistical adjustment of data. New York: Dover Publications.

    Google Scholar 

  • Espenshade, T. J., & Tayman, J. (1982). Confidence intervals for post-censal population estimates. Demography, 19(2), 191–210.

    Article  Google Scholar 

  • Forrester, J. W. (1958). Industrial dynamics: A major breakthrough for decision makers. Harvard Business Review, 36(4), 37–66.

    Google Scholar 

  • Hamilton, C. H, & Perry, J. (1962). A short method for projecting population by age from one decennial census to another. Social Forces, 41, 163–170.

    Article  Google Scholar 

  • Jarosz, B. (2008). Using assessor parcel data to maintain housing unit counts for small area population estimates. In S. H. Murdock, & D. A. Swanson (Eds.), Applied Demography in the 21st Century (pp. 89–101). Dordrecht, Heidelberg, London, and New York: Springer.

    Google Scholar 

  • Judson, D. H., & Popoff, C. L. (2004). Selected general methods. In J. S. Siegel, & D. A. Swanson (Eds.), The Methods and Materials of Demography, Second Edition (pp. 677–732). New York: Elsevier Academic Press.

    Google Scholar 

  • Judson, D. H., & Swanson, D. A. (2011). Estimating characteristics of the foreign-born by legal status: An evaluation of data and method. Springer Briefs in Population Studies. Dordrecht, Heidelberg, London, and New York: Springer.

    Google Scholar 

  • Killworth, P. D., Johnsen, E. C., Bernard, R. H., Shelley, G. A., & McCarty, C. (1990). Estimating the size of personal networks. Social Networks, 12(4), 289–312.

    Article  Google Scholar 

  • Long, J. F. (1993). Post-censal population estimates: States, counties, and places. Technical Working Paper No. 3. Washington, DC: US Bureau of the Census.

    Google Scholar 

  • Lowe, T. J., Myers, W. R., & Weisser, L. M. (1984). A special consideration in improving housing unit estimates: The interaction effect. Paper presented at the annual meeting of the Population Association of America, Minneapolis, MN.

    Google Scholar 

  • Mandell, M., & Tayman, J. (1982). Measuring temporal stability in regression models of population estimation. Demography, 19(1), 135–146.

    Article  Google Scholar 

  • Martin, J. M., & Serow, W. J. (1978). Estimating demographic characteristics using the ratio-correlation method. Demography, 15(2), 223–234.

    Article  Google Scholar 

  • Murdock, S. H., & Ellis, D. R. (1991). Applied demography: An introduction to basic concepts, methods, and data. Boulder: Westview Press.

    Google Scholar 

  • Murdock, S. H., Hwang, S., & Hamm, R. R. (1995). Component methods. In N. W. Rives, W. J. Serow, A. S. Lee, H. F. Goldsmith, & P. R. Voss (Eds.), Basic methods for preparing small-area estimates (pp. 10–53). Madison: Applied Population Laboratory, University of Wisconsin.

    Google Scholar 

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

    Google Scholar 

  • O'Hare, W. (1976). Report on a multiple regression method for making population estimates. Demography, 13(3), 369–380.

    Article  Google Scholar 

  • Purcell, D. E. (1970). Improving population estimates with the use of dummy variables. Demography, 7(1), 87–92.

    Article  Google Scholar 

  • Purcell, N. J., & Kish, L. J. (1980). Post-censal estimates for local areas (or domains). International Statistical Review, 48, 3–18.

    Article  Google Scholar 

  • Raymondo, J. C. (1992). Population estimation and projections. New York: Quorum Books.

    Google Scholar 

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

    Google Scholar 

  • Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: John Wiley & Sons.

    Book  Google Scholar 

  • Schmitt, R. C., & Crosetti, A. H. (1954). Accuracy of ratio-correlation method for estimating post-censal population. Land Economics, 30(3), 279–280.

    Article  Google Scholar 

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

    Google Scholar 

  • Smith, S. K. (1986). A review and evaluation of the housing unit method of population estimation. Journal of the American Statistical Association, 81, 287–296.

    Article  Google Scholar 

  • Smith, S. K., & Cody, S. (2004). An evaluation of population estimates in Florida: April 1, 2000. Population Research and Policy Review, 23, 1–24.

    Article  Google Scholar 

  • Smith, S. K., & Tayman, J. (2003). An evaluation of population projections by age. Demography, 40(4), 741–757.

    Article  Google Scholar 

  • Smith, S. K., Tayman, J., & Swanson, D. A. (2001). State and local population projections: Methodology and analysis. New York: Kluwer Academic/Plenum Publishers.

    Google Scholar 

  • Starsinic, D. E., Lee, A. S., Goldsmith, H. F., & Spar, M. A. (1995). The Census Bureau's administrative records method. In N. W. Rives, W. J. Serow, A. S. Lee, H. F. Goldsmith, & P. R. Voss (Eds.), Basic methods for preparing small-area estimates (pp. 54–70). Madison: Applied Population Laboratory, University of Wisconsin.

    Google Scholar 

  • Swanson, D. A. (1978). An evaluation of the ratio and difference regression methods for estimating small, highly concentrated populations. Review of Public Data Use, 6, 18–27.

    Google Scholar 

  • Swanson, D. A., Schlottmann, A., & Schmidt, B. (2010). Forecasting the population of census tracts by age and sex: An example of the Hamilton-Perry method in action. Population Research and Policy Review, 29(1), 47–63.

    Article  Google Scholar 

  • Swanson, D. A., & Tedrow, L. M. (1984). Improving the measurement of temporal change in regression models used for county population estimates. Demography, 21(3), 373–382.

    Article  Google Scholar 

  • Swanson, D. A., & Walashek, P. J. (2011). CEMAF as a census method: A proposal for a redesigned census and independent US Census Bureau. Springer Briefs in Population Studies. Dordrecht, Heidelberg, London, and New York: Springer.

    Google Scholar 

  • Tayman, J., & Schafer, E. (1985). The impact of coefficient drift and measurement error on the accuracy of ratio correlation population estimates. The Review of Regional Studies, 15(2), 3–10.

    Google Scholar 

  • US Census Bureau. (1998). Subcounty population estimates methodology. (http://www.census.gov/population/methods/e98scdoc.txt).

  • Voss, P. R., Palit, C. D., Kale, B. D., & Krebs, H. J. (1995). Censal ratio methods. In N. W. Rives, W. J. Serow, A. S. Lee, H. F. Goldsmith, & P. R. Voss (Eds.), Basic methods for preparing small-area estimates (pp.70–89). Madison: Applied Population Laboratory, University of Wisconsin.

    Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

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Swanson, D.A., Tayman, J. (2012). Overview of Estimation Methods. In: Subnational Population Estimates. The Springer Series on Demographic Methods and Population Analysis, vol 31. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8954-0_5

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