Bayesian networks are multivariate statistical models using a directed acyclic graph to represent statistical dependencies among variables. When dealing with Bayesian Networks it is common to assume that all the variables are discrete. This is not often the case in many real contexts where also...

In this paper Object-Oriented Bayesian networks are proposed as a tool to model measurement errors in a categorical variable due to respondent. A mixed measurement error model is presented and an Object-Oriented Bayesian network implementing such a model is introduced. The insertion of evidence...

We estimate the consumption response of Italian households to the "Euro80 tax bonus" intro-duced in 2014, using the panel component on the Survey of Household Income and Wealth. We find that households that received the tax rebate increased their monthly consumption of food and means of...

The paper compares Italian and American households� wealth in 1998. The analysis is based on the Survey on Household Income and Wealth (Bank of Italy) and on the Survey of Consumer Finances (Federal Reserve Board). Tangible assets appear to be the main wealth component in both countries. In...

Sample surveys providing high quality information on both total household expenditure (consumption) and income are not commonly available. Nevertheless, surveys focusing on income usually do collect some information on expenditure data. A main drawback of this practice is that it could let some...

The objective of the paper is to adjust for the bias due to unit non-response and measurement error in survey estimates of total household financial wealth. Sample surveys are a useful source of information on household wealth. Yet, survey estimates are affected by non-sampling errors. In...

We study the distribution of housing wealth in Italy using data from a sample survey (the survey on household income and wealth) and from administrative records regarding real estate owners held by the Italian Department of the Treasury. Our results show that owners with either a low or a high...