Economics at your fingertips  

Initial Beliefs Uncertainty and Information Weighting in the Estimation of Models with Adaptive Learning

Jaqueson Galimberti ()

No 2021-01, Working Papers from Auckland University of Technology, Department of Economics

Abstract: This paper evaluates how the way agents weight information when forming expectations can affect the econometric estimation of models with adaptive learning. One key new finding is that misspecification of the uncertainty about initial beliefs under constantgain least squares learning can generate a time-varying profile of weights given to past observations, distorting the estimation and behavioural interpretation of this mechanism in small samples of data. This result is derived under a new representation of the learning algorithm that penalizes the effects of misspecification of the learning initials. Simulations of a forward-looking Phillips curve model with learning indicate that (i) misspecification of initials uncertainty can lead to substantial biases to estimates of expectations relevance for inflation, and (ii) that these biases can spill over to estimates of inflation rates responsiveness to output gaps. An empirical application with U.S. data shows the relevance of these effects.

Keywords: expectations; adaptive learning; bounded rationality; macroeconomics (search for similar items in EconPapers)
JEL-codes: E70 D83 D84 D90 E37 C32 C63 (search for similar items in EconPapers)
Date: 2021-02
New Economics Papers: this item is included in nep-ets, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Working Papers from Auckland University of Technology, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Gail Pacheco ().

Page updated 2021-06-11
Handle: RePEc:aut:wpaper:202101