Accounting for sampling design in the SHIW
AbstractThis paper analyses how sampling design affects variance estimates and inference using the data collected by the Survey on Household Income and Wealth (SHIW). The SHIW combines three basic features: stratification, clustering, and weighting to correct for unequal probabilities of selection among sampling units. A model to assess variance is presented and a Jackknife Repeated Replication method is suggested to estimate variance. Empirical evidence shows that: 1) simple random sampling formula for variance underestimates by a factor of between 3 and 2 the estimates that take into account all the design features; 2) the bias of unweighted estimates may be fairly substantial; 3) all these factors can seriously mislead inference based on SHIW data.
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Bibliographic InfoPaper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 662.
Date of creation: Apr 2008
Date of revision:
Find related papers by JEL classification:
- C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-06-21 (All new papers)
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