The Weighting Process in the SHIW

37 Pages Posted: 7 Aug 2007

Date Written: June 2007

Abstract

The design of a probability sample jointly determines the method used to select sampling units from the population and the estimator of the population parameter. If the sampling fraction is constant for all the units in the sample, then the unweighted sampling mean is an unbiased estimator. In the Survey on Household Income and Wealth (SHIW), units included in the sample have unequal probabilities of selection and each observation is weighted using the inverse of the proper sampling fraction (design weight) adjusted for the response mechanism (non-response weight) and for other factors such as imperfect coverage. In this paper we present the weighting scheme of the SHIW and assess its impact on bias and variance of selected estimators. Empirical evidence shows that the increasing variability induced by using weighted estimators is compensated by the bias reduction even when performing analysis on sample domains. A set of longitudinal weights is also proposed to account for the selection process and the attrition of the SHIW panel component. These weights, given their enhanced description of the "panel population", should be better suited to perform longitudinal analysis; nevertheless their higher variance implies that they are not always preferable in terms of mean square error.

Keywords: Survey Methods

JEL Classification: C42

Suggested Citation

Faiella, Ivan and Gambacorta, Romina, The Weighting Process in the SHIW (June 2007). Bank of Italy Temi di Discussione (Working Paper) No. 636, Available at SSRN: https://ssrn.com/abstract=1005301 or http://dx.doi.org/10.2139/ssrn.1005301

Ivan Faiella (Contact Author)

Bank of Italy ( email )

Via Nazionale 91
00184 Roma
Italy

Romina Gambacorta

Bank of Italy ( email )

Via Nazionale 91
00184 Roma
Italy

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
81
Abstract Views
2,973
rank
380,739
PlumX Metrics