64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Small Area Estimation of teleworking indicators


Mahamat Hamit-Haggar


  • S
    Stanley Yu Su


64th ISI World Statistics Congress - Ottawa, Canada

Format: CPS Abstract

Keywords: covid-19, data, experiment


In a designed survey, sample sizes are usually not sufficient to generate reliable direct estimates for small domain. The use of valid statistical models can provide small area estimates with greater precision, that is, the Small Area Estimation (SAE) is an appropriate statistical models that link survey data to auxiliary data available for the entire population to produce reliable indirect estimates. In other words, SAE borrows strength through auxiliary information. In this study, we propose to estimate small area population parameters by using (Prasad and Rao (1986, 1990) for the Fay-Herriot model, the technique produces estimates of parameters for finer geographic detail. We focus on teleworking or working remotely as particular parameter of interest. Model performance is evaluated, and small area estimates are generated for almost a full coverage of domain defined as Self-contained Labour Area, for good producing and services providing industries.