Restricted calibration and weight trimming approaches for estimation of the population total in business statistics


Metin C. B., ŞAHİN TEKİN S. T., ÖZDEMİR Y. A.

Journal of Applied Statistics, cilt.48, ss.2658-2672, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 48
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/02664763.2020.1869703
  • Dergi Adı: Journal of Applied Statistics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Veterinary Science Database, zbMATH
  • Sayfa Sayıları: ss.2658-2672
  • Anahtar Kelimeler: Weighting, calibration, weight trimming, minimum distance method, restricted calibration estimators
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2021 Informa UK Limited, trading as Taylor & Francis Group.Some adjustments are made to design weights to reduce the negative effects of non-response and out-of-scope problems. The calibration approach is a weighting process that agrees with the known population values by using auxiliary information. In this study, alternative calibration approaches and weight trimming process that can be used in large data sets with extreme weights and different correlation structures were analysed. In addition, the effect of the correlation structure of auxiliary variables on the efficiency of the calibration estimators was investigated by a simulation study. The 2017 Annual Industry and Service Statistics data were used in the simulation study and it was seen that restricted calibration estimators were more efficient than the generalized regression estimator in estimating the variables with a high variance such as turnover. Especially in small sample fractions, we recommend the application of restricted calibration estimators, as they are more efficient than the weight trimming in solving the negative and less than one weights problem encountered after the calibration process.