This is the Data Page for:
Cavallo, Alberto, Guillermo Cruces, and Ricardo Perez-Truglia (2016) "Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina." - Brookings Papers on Economic Activity (Forthcoming)
Please cite this paper if you use the data
When forming expectations, households may be influenced by perceived bias in the information they receive. For instance, in the United States, households that do not trust inflation statistics have, on average, 50% higher inflation expectations. In this paper, we study how individuals learn from potentially biased statistics using data from both a natural experiment and a survey experiment during a period of government manipulation of inflation statistics in Argentina (2007–2015). This period is interesting because of the attention to inflation information and the availability of official and unofficial statistics. Our evidence suggests that, rather than ignoring biased statistics or naively accepting them, households react in a sophisticated way, as predicted by a Bayesian learning model. 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 could also be useful to understand 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 are not.
Paper and Appendix