Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina / Alberto Cavallo, Guillermo Cruces, Ricardo Perez-Truglia.

Format:

Book

Author/Creator:

Cavallo, Alberto.

Contributor:

National Bureau of Economic Research.

Cruces, Guillermo.

Perez-Truglia, Ricardo.

Series:

Working Paper Series (National Bureau of Economic Research) no. w22103.

NBER working paper series no. w22103

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Other Title:

Learning from Potentially-Biased Statistics

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2016.

Summary:

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.

Notes:

Print version record

March 2016.