Model-assisted estimation using panel data and data from independent samples for the Philippine Family Income and Expenditure survey

Erniel B. Barrios, Divina Gracia L. Del Prado, Mae Abigail C. Oberos, Desiree Robles, Jo Louise Buhay

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther


The domains for the Philippine Family Income and Expenditure Survey (FIES) are the regions. Design-unbiased estimation for the provinces (smaller areas) would necessitate an increase the sample size to about four times. Considering further that FIES is conducted semi-annually (at the end of reference semester), using the same sample households for the survey year and administered with a lengthy questionnaire, response burden and refusals increases along with problems with willingness of interviewers to complete the task for the entire survey duration. This problem is addressed by keeping the regions as survey domains but partially rotating the samples in the two rounds of data collection. This study then proposes a model-assisted estimation procedure in combining panel data and data from independent samples to generate annual estimates at the provincial level. Simulation studies indicate the advantages of model-assisted estimation procedure over design-unbiased method in generating estimates at the provincial level. Furthermore, sample size requirement using model-assisted approach is only about half of the required sample size for the design-unbiased method for reliable provincial level estimates.
Original languageEnglish
Title of host publicationProceeding of the 62nd ISI World Statistics Congress 2019
Subtitle of host publicationInvited Paper Session
EditorsRozita Talha
Place of PublicationPutrajaya Malaysia
PublisherDepartment of Statistics Malaysia
Number of pages6
Publication statusPublished - 2019
Externally publishedYes
EventISI World Statistics Congress 2019 - Kuala Lumpur, Malaysia
Duration: 18 Aug 201923 Aug 2019
Conference number: 62nd (Proceedings)


ConferenceISI World Statistics Congress 2019
Abbreviated titleISI 2019
CityKuala Lumpur
Internet address

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