Review of how the generalized regression estimators contribute to estimating the financial and economic data with missing observations under unequal probability sampling

Purpose - Knowing financial and economic information beforehand benefits in planning and developing policies for every country especially for a developing country like Thailand and for other Asian countries. Unfortunately, missing data or non-response plays an essential role in many areas of studies including finance and economics. Eradication of missing data in a proper way before further analysis can gain remarkable outcomes and can be effective for planning policies. This review on the generalized regression estimators for population total can be applied to financial, economic and other data when missing data are present. Design/methodology/approach - The generalized regression estimators for estimating population total, including the variance estimators under unequal probability sampling without replacement with missing data are explored under the reverse framework. Applications to financial and economic data in Thailand are also reviewed. Findings - The review of literatures related to the proposed estimator shows the best performance, giving smaller variances in all scenarios. Originality/value - The generalized regression estimators can assist in estimating financial and economic data that contain missing values with different missing mechanisms and can be used in other applications which help gain more superior estimators.