Accounting for sampling design in the SHIW

Ivan Faiella ()
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Ivan Faiella: Bank of Italy - Economic and Financial Statistics Department

No 662, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research Department

Abstract: This 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.

Keywords: Survey; Methods (search for similar items in EconPapers)
JEL-codes: C42 (search for similar items in EconPapers)
Date: 2008-04
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