Dynamic modelling of price expectations and judgments

Official data about consumers’ qualitative expectation and perception of inflation are derived from repeated surveys conducted by national statistical institutes. In EU, these data are published in aggregate form, and cannot be described by means of classical methods based on cumulative models for ordinal data. This article illustrates an integrated approach that locates CUB mixture models for ratings in a time series perspective in order to investigate the joint evolution of inflation judgments and expectations in Italy. In order to measure the common sentiment of interviewees through the feeling component of the model, net of possible uncertainty and nuisance effects, its estimation is pursued through profile likelihood methods given the empirical frequency distributions of consumers’ opinions observed over time. Then, the relationship between the time series of the estimated feeling parameters is modelled using a dynamic regression model and the results are compared in three periods marked by different economic conditions. Results indicate that each series has a substantial inertial component, and thus it is characterized by a slow variation over time, and that both judgments about past price levels and previous expectations affect current expectations about the future in fairly different ways for the three time periods.