Heterogeneity, Asymmetries and Learning in InfIation Expectation Formation: An Empirical Assessment

Relying on Michigan Survey' monthly micro data on inflation expectations we try to determine the main features -- in terms of sources and degree of heterogeneity - of inflation expectation formation over different phases of the business cycle and for different demographic subgroups. We identify three regions of the overall distribution corresponding to different expectation formation processes, which display a heterogeneous response to main macroeconomic indicators: a static or highly autoregressive (LHS) group, a "nearly" rational group (middle), and a group of "pessimistic" agents (RHS), who overreact to macroeconomic fluctuations. Different learning rules have been applied to the data, in order to test whether agents' are learning and whether their expectations are converging towards rational expectations (perfect foresight). The results obtained by applying conventional and recursive methods confirm our initial conjecture that behaviour of agents in the RHS of distribution is more associated with learning dynamics. We also regard the overall distribution as a mixture of normal distributions. This strategy allows us to get a deeper understanding of the existence and the main features of convergence and learning in the data, as well as to identify the demographic participation in each subcomponent