The paper sketches a proper statistical setting necessary to define the sampling design for Small Area Estimation (SAE). Since SAE techniques are commonly used in official statistics, relying on appropriate sampling designs to improve the quality of estimates becomes crucial. The sampling design is based on both allocation and sampling selection. The allocation step solves a non-standard problem necessary for finding the minimum-cost solution that controls the accuracy of the model-based small area estimator. The sampling selection ensures the planned sample sizes for each level of random effects affecting the variables of interest.
Falorsi, P. D., Falorsi, S., Nardelli, V., Righi, P., Defining Ad-Hoc Sampling Designs for Small Area Estimation, <<JOURNAL OF OFFICIAL STATISTICS>>, 2025; (N/A): N/A-N/A. [doi:10.1177/0282423x251388201] [https://hdl.handle.net/10807/327877]
Defining Ad-Hoc Sampling Designs for Small Area Estimation
Nardelli, Vincenzo
;
2025
Abstract
The paper sketches a proper statistical setting necessary to define the sampling design for Small Area Estimation (SAE). Since SAE techniques are commonly used in official statistics, relying on appropriate sampling designs to improve the quality of estimates becomes crucial. The sampling design is based on both allocation and sampling selection. The allocation step solves a non-standard problem necessary for finding the minimum-cost solution that controls the accuracy of the model-based small area estimator. The sampling selection ensures the planned sample sizes for each level of random effects affecting the variables of interest.| File | Dimensione | Formato | |
|---|---|---|---|
|
falorsi-et-al-2025-defining-ad-hoc-sampling-designs-for-small-area-estimation.pdf
accesso aperto
Licenza:
Creative commons
Dimensione
1.29 MB
Formato
Adobe PDF
|
1.29 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



