An Application of Adaptive Cluster Sampling to Surveying Informal Businesses

Autor:	Gemechu Aga, David C Francis, Filip Jolevski, Jorge Rodriguez Meza, Joshua Seth Wimpey
Rok vydání:	2023
Předmět:	Statistics and Probability Applied Mathematics Statistics Probability and Uncertainty Social Sciences (miscellaneous)
Zdroj:	Journal of Survey Statistics and Methodology.
ISSN:	2325-0992 2325-0984
DOI:	10.1093/jssam/smac037
Popis:	Informal business activity is ubiquitous around the world, but it is nearly always uncaptured by administrative data, registries, or commercial sources. For this reason, there are rarely adequate sampling frames available for survey implementers wishing to measure the activity and characteristics of the sector. This article applies a well-established sampling method for rare and/or clustered populations, Adaptive Cluster Sampling (ACS), to a novel population of informal businesses. Generally, it shows that efficiency gains through the application of ACS, when compared to Simple Random Sampling (SRS), are large, particularly at higher levels of fieldwork effort. In particular, ACS efficiency gains over SRS remain sizable at higher values of initial starting samples, but with comparatively high expansion thresholds, which can reduce the fieldwork effort.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b169f106af2c50f71f9bafaa4ad60029 https://doi.org/10.1093/jssam/smac037 Zobrazit plný text záznamu