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Estimates based on preliminary data from a specific subsample and from respondents not included in the subsample

Author

Listed:
  • Piero Demetrio Falorsi

    (University of Rome “La Spapienza”)

  • Giorgio Alleva

    (University of Rome “La Spapienza”)

  • Fabio Bacchini

    (University of Rome “La Spapienza”)

  • Roberto Iannaccone

    (University of Rome “La Spapienza”)

Abstract

Various approaches to obtaining estimates based on preliminary data are outlined. A case is then considered which frequently arises when selecting a subsample of units, the information for which is collected within a deadline that allows preliminary estimates to be produced. At the moment when these estimates have to be produced it often occurs that, although the collection of data on subsample units is still not complete, information is available on a set of units which does not belong to the sample selected for the production of the preliminary estimates. An estimation method is proposed which allows all the data available on a given date to be used to the full-and the expression of the expectation and variance are derived. The proposal is based on two-phase sampling theory and on the hypothesis that the response mechanism is the result of random processes whose parameters can be suitably estimated. An empirical analysis of the performance of the estimator on the Italian Survey on building permits concludes the work.

Suggested Citation

  • Piero Demetrio Falorsi & Giorgio Alleva & Fabio Bacchini & Roberto Iannaccone, 2005. "Estimates based on preliminary data from a specific subsample and from respondents not included in the subsample," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(1), pages 83-99, February.
    • Handle: RePEc:spr:stmapp:v:14:y:2005:i:1:d:10.1007_bf02511576
    DOI: 10.1007/BF02511576
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    References listed on IDEAS

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    4. Francesco Battaglia & Livio Fenga, 2003. "Forecasting composite indicators with anticipated information: an application to the industrial production index," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(3), pages 279-290, July.
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