This paper is aimed at evaluating the incidence of measurement error in the Bank of Italy's Survey of Household Income and Wealth (SHIW). In the case of time-invariant variables, we assess the degree of inconsistency of answers given by panel households in subsequent survey waves. For quantities that vary with time, we estimate the incidence of measurement error by decomposing observed variability into true dynamics and error-induced noise. We apply the Heise model or the latent Markov model, depending on whether the data are continuous or categorical. We also present regression models that explain the error-generating process. Our results are relevant to researchers who use SHIW data for economic analysis, but also to data producers involved in similar income and wealth surveys. The methods we describe and test can be employed in a number of contexts to gain better understanding of data-related problems and plans for survey improvement. Copyright 2008 The Authors. Journal compilation 2008 International Association for Research in Income and Wealth Published.
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