Medous, Estelle, Goga, Camelia, Ruiz-Gazen, Anne, Beaumont, Jean-François, Dessertaine, Alain and Puech, Pauline (2021) Many-to-One indirect sampling with application to the French postal traffic estimation. TSE Working Paper, n. 21-1269, Toulouse

[thumbnail of wp_tse_1269.pdf]
Download (1MB) | Preview


In social and economic surveys, it can be difficult to directly reach units of the target population, and indirect sampling is often advocated to solve this issue. In indirect sampling, the sample is drawn from a frame population that is linked to the target population, and estimation of tar-get population parameters is typically achieved through the Generalized Weight Share Method (GWSM). This method provides a weight, for every unit of the target population, that depends on the one hand, on the sampling weights in the frame population and, on the other hand, on the link weights between the frame population and the target population. In the present study, we focus on the situation in which the units from the frame population are linked to one and only one unit from the target population (Many-to-One case). This situation is encountered at the French postal service where addresses are sampled instead of postman rounds. We aim at understanding of the impact of the link weights on the efficiency of the GWSM estimators. We derive variance expressions and optimality results for a large class of sampling designs. Moreover, we note that the Many-to-One case can lead to too many links to observe. We alleviate the problem by introducing an intermediate population and double indirect sampling. The question of the loss of precision in this situation is discussed in detail through theoretical results and simulations. These findings help to explain the loss of precision of double GWSM estimators observed recently at the French postal service.

Item Type: Monograph (Working Paper)
Language: English
Date: November 2021
Place of Publication: Toulouse
Uncontrolled Keywords: Generalized Weight Share Method, Optimal link weights, Stratified sampling, Variance estimation
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 25 Nov 2021 15:37
Last Modified: 13 Jan 2023 12:28
OAI Identifier:
View Item


Downloads per month over past year