The role of the conditional independence assumption in statistically matching income and consumption

Abstract

The need of new indicators that cover cross-cutting information on household economic well-being is among the current priorities of the National Statistical Institutes as well as a major goal at European level. The purpose of this paper is to apply statistical matching techniques on two different data sources to provide joint information on household income and consumption in Italy. We use data observed on the EU Statistics on Income and Living Condition and the Household Budget Survey. This paper focuses on the role of the available information in improving the matching outputs obtainable from traditional statistical matching methods. More precisely, rough information concerning household income, derived from the Household Budget Survey through a suitable method, is considered. The statistical matching methods will use this additional variable as a matching variable that is highly correlated with one of the target variables, thereby justifying the use of the usually neglected conditional independence assumption. In this paper, important insights on the application of the Renssen’s weight calibration approach when matching data from complex sample surveys are also provided. Finally an ex-ante collection of information in SILC could enhance the application of matching techniques and improve the accuracy of the final estimates.