IDEAS home Printed from https://ideas.repec.org/a/kap/poprpr/v32y2013i6p919-942.html
   My bibliography  Save this article

A Comparative Evaluation of Error and Bias in Census Tract-Level Age/Sex-Specific Population Estimates: Component I (Net-Migration) vs Component III (Hamilton–Perry)

Author

Listed:
  • Jack Baker
  • Adelamar Alcantara
  • Xiaomin Ruan
  • Kendra Watkins
  • Srini Vasan

Abstract

While the housing-unit method continues to be the preferred method nationwide for producing small-area population estimates, this procedures lacks a method for making age/sex-specific estimates. This paper reports evaluation research on implementation of component-based methods for estimating census tract populations with age/sex detail. Two alternatives are explored: (1) the Component I method relying upon estimates of births, deaths, and net-migration and (2) the Component III method relying solely upon 1990 and 2000 Census counts. From an April 1, 2000 base, each method is used to make estimates moving forward to an April 1, 2010 estimate that is compared to the results of the 2010 Census. The two methods are compared in terms of accuracy and bias using both absolute and algebraic mean and median percentage errors. Results are reviewed and discussed in light of their implications for applied demographers tasked with making small-area demographic estimates. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Jack Baker & Adelamar Alcantara & Xiaomin Ruan & Kendra Watkins & Srini Vasan, 2013. "A Comparative Evaluation of Error and Bias in Census Tract-Level Age/Sex-Specific Population Estimates: Component I (Net-Migration) vs Component III (Hamilton–Perry)," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 32(6), pages 919-942, December.
  • Handle: RePEc:kap:poprpr:v:32:y:2013:i:6:p:919-942
    DOI: 10.1007/s11113-013-9295-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11113-013-9295-4
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11113-013-9295-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Donald Starsinic & Meyer Zitter, 1968. "Accuracy of the housing unit method in preparing population estimates for cities," Demography, Springer;Population Association of America (PAA), vol. 5(1), pages 475-484, March.
    2. Pflaumer, Peter, 1992. "Forecasting US population totals with the Box-Jenkins approach," International Journal of Forecasting, Elsevier, vol. 8(3), pages 329-338, November.
    3. Flowerdew, Robin & Green, Mick, 1992. "Developments in Areal Interpolation Methods and GIS," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 67-78, April.
    4. David Swanson & Jerome McKibben, 2010. "New Directions in the Development of Population Estimates in the United States?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 29(6), pages 797-818, December.
    5. Robert C. Schmitt & Albert H. Crosetti, 1954. "Accuracy of the Ratio-Correlation Method for Estimating Postcensal Population," Land Economics, University of Wisconsin Press, vol. 30(3), pages 279-281.
    6. Jack Baker & Adélamar Alcantara & Xiaomin Ruan, 2011. "A Stochastic Version of the Brass PF Ratio Adjustment of Age-Specific Fertility Schedules," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-13, August.
    7. Stanley Smith & Bart Lewis, 1983. "Some New Techniques for Applying the Housing Unit Method of Local Population Estimation: Further Evidence," Demography, Springer;Population Association of America (PAA), vol. 20(3), pages 407-413, August.
    8. David Swanson & Alan Schlottmann & Bob Schmidt, 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, Springer;Southern Demographic Association (SDA), vol. 29(1), pages 47-63, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jack Baker & David Swanson & Jeff Tayman, 2021. "The Accuracy of Hamilton–Perry Population Projections for Census Tracts in the United States," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(6), pages 1341-1354, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qian Cai, 2007. "New techniques in small area population estimates by demographic characteristics," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(2), pages 203-218, April.
    2. Stanley Smith & Scott Cody, 2013. "Making the Housing Unit Method Work: An Evaluation of 2010 Population Estimates in Florida," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 32(2), pages 221-242, April.
    3. Thomas M. Fullerton JR., 2001. "Specification of a Borderplex Econometric Forecasting Model," International Regional Science Review, , vol. 24(2), pages 245-260, April.
    4. Annette Jacoby & Peter Lobo & Joseph J. Salvo, 2021. "Estimating Postcensal Household Size for NYC’s Neighborhoods," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(3), pages 459-474, June.
    5. Tom Wilson & Irina Grossman & Monica Alexander & Phil Rees & Jeromey Temple, 2022. "Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 865-898, June.
    6. Thomas M. Fullerton & Patricia Arellano-Olague, 2022. "Short-Term Household Economic Stress Effects on Retail Activity in El Paso, Texas," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 50(1), pages 27-35, June.
    7. A. Chaudhuri, 1994. "Small domain statistics: a review," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 48(3), pages 215-236, November.
    8. Pflaumer, Peter, 1993. "Measuring the accuracy of population projections: An application of exploratory data analysis," Discussion Papers, Series II 199, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    9. David A. Swanson, 2022. "Forecasting a Tribal Population Using the Cohort-Component Method: A Case Study of the Hopi," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(4), pages 1831-1852, August.
    10. Wasantha Athukorala & Clevo Wilson & Prasad Neelawela & Evonne Miller & Tony Sahama & Peter Grace & Mike Hefferan & Premawansa Dissanayake & Oshan Manawadu, 2010. "Forecasting Population Changes and Service Requirements in the Regions: A Study of Two Regional Councils in Queensland, Australia," Economic Analysis and Policy, Elsevier, vol. 40(3), pages 327-349, December.
    11. Stanley Smith & June Nogle & Scott Cody, 2002. "A regression approach to estimating the average number of persons per household," Demography, Springer;Population Association of America (PAA), vol. 39(4), pages 697-712, November.
    12. David A. Swanson & Jack Baker, 2019. "Estimating the underlying infant mortality rates for small populations: an historical study of US counties in 1970," Journal of Population Research, Springer, vol. 36(3), pages 233-244, September.
    13. Tom Wilson, 2022. "Preparing local area population forecasts using a bi-regional cohort-component model without the need for local migration data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 46(32), pages 919-956.
    14. John Quiggin, 2010. "Agriculture and global climate stabilization: a public good analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 41(s1), pages 121-132, November.
    15. Mangirdas Morkunas & Elzė Rudienė & Lukas Giriūnas & Laura Daučiūnienė, 2020. "Assessment of Factors Causing Bias in Marketing- Related Publications," Publications, MDPI, vol. 8(4), pages 1-16, October.
    16. N. Namboodiri, 1972. "On the ratio-correlation and related methods of subnational population estimation," Demography, Springer;Population Association of America (PAA), vol. 9(3), pages 443-453, August.
    17. Jeff Tayman & David A. Swanson & Jack Baker, 2021. "Using Synthetic Adjustments and Controlling to Improve County Population Forecasts from the Hamilton–Perry Method," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 40(6), pages 1355-1383, December.
    18. Jeff Tayman & David A. Swanson, 2017. "Using modified cohort change and child-woman ratios in the Hamilton–Perry forecasting method," Journal of Population Research, Springer, vol. 34(3), pages 209-231, September.
    19. Dempwolff, Nelly & Schulze, Peter M., 2009. "ARIMA: Bevölkerungsprognosen für Deutschland und Rheinland-Pfalz," Arbeitspapiere des Instituts für Statistik und Ökonometrie 43, Johannes Gutenberg-Universität Mainz, Institut für Statistik und Ökonometrie.
    20. John Quiggin & David Adamson & Sarah Chambers & Peggy Schrobback, 2010. "Climate Change, Uncertainty, and Adaptation: The Case of Irrigated Agriculture in the Murray–Darling Basin in Australia," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(4), pages 531-554, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:poprpr:v:32:y:2013:i:6:p:919-942. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.