Advertisement

Testing the Quality and Smoothing of Demographic Data

  • Farhat Yusuf
  • Jo. M. Martins
  • David A. Swanson
Chapter
  • 3.1k Downloads

Abstract

This chapter is concerned with the testing of the accuracy of data and adjustments that might be required. It examines potential sources and types of errors such as sampling and non-sampling errors that include topics related to response, coverage and other types of errors. Methods of testing the accuracy of census and other types of demographic data are examined. Further, it considers the use of sample surveys in testing the quality and coverage of census data. The chapter discusses various indices such as the Myers’ index of digital preferences and age-sex ratio scores. The adjustment and smoothing of data is illustrated using methods such as moving averages and using interpolation multipliers.

Keywords

Response Error Ratio Score Parabolic Model Digital Preference Terminal Digit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Australia. (2012). Census of population and housing: Details of undercount, 2011. Catalogue No. 2940.0. Canberra: Australian Bureau of Statistics. http://www.abs.gov.au/ausstats/abs@.nsf/mf/2940.0. Accessed Feb 2013.
  2. Currie, I. D., Durban, M., & Eilers, P. H. C. (2004). Smoothing and forecasting mortality rates. Statistical Modelling, 4(4), 279–298.CrossRefGoogle Scholar
  3. De Beer, J. (2011). A new relational method for smoothing and projecting age specific fertility rates: TOPALS. Demographic Research, 24(18), 409–454. http://www.demographic-research.org/volumes/vol27/20/27-20.pdf. Accessed Feb 2013.
  4. Jaffe, A. J. (1951). Handbook of statistical methods for demographers. Washington, DC: Government Printing Office.Google Scholar
  5. McNeil, D. R., Trussell, T. J., & Turner, J. C. (1977). Spline interpolation of demographic data. Demography, 14(2), 245–252.CrossRefGoogle Scholar
  6. Myers, R. J. (1940). Errors and bias in the reporting of ages in census data. Transactions of the Actuarial Society of America, 41(104), 395–415.Google Scholar
  7. Oullette, N. & R. Bourbeau. (2011). Changes in the age-at-death distribution in four low mortality countries: A Non parametric approach. Demographic Research, 25(19), 595–628. http://www.demographic-research.org/volumes/vol25/19/25-19.pdf. Accessed Feb 2013.
  8. Spiegelman, M. (1969). Introduction to demography. Cambridge: Harvard University Press.Google Scholar
  9. Triola, M. F. (2007). Elementary statistics using excel (3rd ed.). Boston: Pearson Addison Wesley.Google Scholar
  10. United Nations. (1955). Manual II. Methods of appraisal of quality of basic data for population estimates. New York: Department of Economic and Social Affairs. http://www.un.org/esa/population/techcoop/DemEst/manual2/manual2.html. Accessed Feb 2013.
  11. United Nations. (2011). Demographic yearbook special census topics. New York: Department of Economic and Social Affairs. http://unstats.un.org/unsd/demographic/products/dyb/dybcens.htm. Accessed Feb 2013.
  12. Yusuf, F. (1967). On the extent of digital preference in reporting of ages in Pakistan. Pakistan Development Review, 4, 519–532.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht. 2014

Authors and Affiliations

  • Farhat Yusuf
    • 1
    • 2
  • Jo. M. Martins
    • 2
  • David A. Swanson
    • 3
  1. 1.Menzies Centre for Health Policy Sydney School of Public HealthThe University of SydneySydneyAustralia
  2. 2.Department of Marketing and Management Faculty of Business and EconomicsMacquarie UniversityNorth RydeAustralia
  3. 3.Department of Sociology College of Humanities, Arts and Social SciencesUniversity of California RiversideRiversideUSA

Personalised recommendations