Modelling Qualitative Data from Repeated Surveys

This article presents an innovative dynamic model that describes the probability distributions of ordered categorical variables observed over time. For this purpose, we extend the definition of the mixture distribution obtained from the combination of a uniform and a shifted binomial distribution (C...

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Bibliographic Details
Main Authors: Marcella Corduas, Domenico Piccolo
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Computation
Subjects:
Online Access:https://www.mdpi.com/2079-3197/11/3/64
Description
Summary:This article presents an innovative dynamic model that describes the probability distributions of ordered categorical variables observed over time. For this purpose, we extend the definition of the mixture distribution obtained from the combination of a uniform and a shifted binomial distribution (CUB model), introducing time-varying parameters. The model parameters identify the main components ruling the respondent evaluation process: the degree of attraction towards the object under assessment, the uncertainty related to the answer, and the weight of the refuge category that is selected when a respondent is unwilling to elaborate a thoughtful judgement. The method provides a tool to quantify the data from qualitative surveys. For illustrative purposes, the dynamic CUB model is applied to the consumers’ perceptions and expectations of inflation in Italy to investigate: (a) the effect of the COVID pandemic on inflation beliefs; (b) the impact of income level on respondents’ expectations.
ISSN:2079-3197