Abstract: In view of many countries using unmatched estimator in census omission estimation, which leads to underestimate omissions, the objective of this work is to replace it with the census omission synthetic estimator. In order to achieve the goal, a combination of mathematical model and sampling estimation is used to study the unmatched estimator, census omission synthetic estimator, and their sampling variance estimators. Theoretical and empirical research results show that compared with the unmatched estimator, the census omission synthetic estimator provides more omissions and higher estimation accuracy. For simplicity of calculation, the census omission synthetic estimator must be established in population strata of equal probability. The census omission synthetic estimator will be applied to China's 2020 census omission estimation to improve its estimation accuracy.

Key words: sample survey, census quality evaluation, census omissions, stratified jackknife