Assessing Consistency of Consumer Confidence Data using Dynamic Latent Class Analysis

TL;DR

This paper introduces a latent class analysis method to assess the consistency of consumer confidence survey responses over time, improving the reliability of macroeconomic indices derived from such data.

Contribution

It develops a novel approach to incorporate temporal dynamics into latent class analysis for evaluating survey response consistency.

Findings

Effective detection of inconsistent responses over time

Enhanced reliability of consumer confidence indices

Applicability demonstrated on RBI survey data

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 affecting the reliability of the indices hence created. This paper describes how latent class analysis may be used to check the consistency of responses and ensure a parsimonious 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).