Assessing Consistency of Consumer Confidence Data Using Latent Class Analysis with Time Factor

Abstract

In many countries information on expectations collected through consumer confidence surveys are used in macroeconomic policy formulation. Unfortunately, before doing so, the consistency of responses is often not taken into account, leading to biases creeping in and, in turn, affecting the consistency of the indices hence created. This paper describes how latent class analysis may be used to check the consistency of responses and ensure parsimony in the questionnaire. In particular, we examine how temporal changes may be incorporated into the model. Our methodology is illustrated using three rounds of Consumer Confidence Survey (CCS) conducted by Reserve Bank of India (RBI).