Working Paper: NBER ID: w22103
Authors: Alberto Cavallo; Guillermo Cruces; Ricardo Perez-Truglia
Abstract: When forming expectations, households may be influenced by the possibility that the information they receive is biased. In this paper, we study how individuals learn from potentially-biased statistics using data from both a natural and a survey-based experiment obtained during a period of government manipulation of inflation statistics in Argentina (2006-2015). This period is interesting because of the attention to inflation information and the availability of both official and unofficial statistics. Our evidence suggests that rather than ignoring biased statistics or navively taking them at face value, households react in a sophisticated way, as predicted by a Bayesian learning model, effectively de-biasing the official data to extract all its useful content. We also find evidence of an asymmetric reaction to inflation signals, with expectations changing more when the inflation rate rises than when it falls. These results are useful for understanding the formation of inflation expectations in less extreme contexts than Argentina, such as the United States and Europe, where experts may agree that statistics are unbiased but households do not.
Keywords: Inflation expectations; Bayesian learning; Argentina; Household behavior
JEL Codes: C83; C93; E31; E58
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| biased statistics (C46) | inflation expectations (E31) |
| official data debiasing (Y10) | inflation expectations (E31) |
| inflation rise (E31) | inflation expectations (E31) |
| inflation fall (E31) | inflation expectations (E31) |
| manipulation of statistics (C80) | inflation expectations stability (E31) |