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Synthetic and composite estimators for small area estimation under Lahiri – Midzuno sampling scheme


  • Pandey, Krishan
  • Tikkiwal, G.C.


This paper studies performance of synthetic ratio estimator and composite estimator, which is a weighted sum of direct and synthetic ratio estimators, under Lahiri – Midzuno (L-M) sampling scheme. The synthetic estimator under L-M scheme is unbiased and consistent if the assumption of synthetic estimator is satisfied. Further, this paper compares performance of the synthetic and composite estimators empirically under L-M and SRSWOR schemes for estimating crop acreage for small domains. The study shows that both the estimators perform better under L-M scheme as having comparatively smaller absolute relative biases and relative standard errors.

Suggested Citation

  • Pandey, Krishan & Tikkiwal, G.C., 2006. "Synthetic and composite estimators for small area estimation under Lahiri – Midzuno sampling scheme," MPRA Paper 22783, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:22783

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    Cited by:

    1. PANDEY, KRISHAN & Tikkiwal, G.C., 2010. "Generalized class of synthetic estimators for small areas under systematic sampling scheme," MPRA Paper 37161, University Library of Munich, Germany.

    More about this item


    Composite estimators; Synthetic ratio estimators; Small domains; Lahiri – Midzuno sampling design; SICURE model;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics


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