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Efficient survey sampling of households via Gaussian quadrature
Author(s) -
Arndt Channing,
Kozlitina Julia,
Preckel Paul V.
Publication year - 2006
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2006.00537.x
Subject(s) - sampling (signal processing) , survey data collection , gaussian , econometrics , data collection , statistics , gaussian quadrature , survey methodology , quadrature (astronomy) , survey research , mathematics , geography , nyström method , computer science , economics , engineering , physics , mathematical analysis , socioeconomics , integral equation , quantum mechanics , filter (signal processing) , electrical engineering , computer vision
Summary. The collection of data through surveys is a costly and time‐consuming process, particularly when complex economic data are involved. The paper presents an efficient approach, based on Gaussian quadrature, to survey sampling when some information is available about the target population. Using household data from Mozambique, we demonstrate that Gaussian quadrature subsamples, based on relatively easy to observe household characteristics such as size and educational attainment of members, generate better estimates of the moments of household expenditure than random samples of equal size.