IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina

Listed author(s):
  • Alberto Cavallo
  • Guillermo Cruces
  • Ricardo Perez-Truglia

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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/w22103.pdf
Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 22103.

as
in new window

Length:
Date of creation: Mar 2016
Publication status: published as Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, vol 2016(1), pages 59-108.
Handle: RePEc:nbr:nberwo:22103
Note: IFM ME
Contact details of provider: Postal:
National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  1. Paul E. Carrillo & M. Shahe Emran, 2012. "Public Information and Inflation Expectations: Microeconometric Evidence from a Natural Experiment," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 860-877, November.
  2. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2014. "Inflation Expectations, Learning and Supermarket Prices," NBER Working Papers 20576, National Bureau of Economic Research, Inc.
  3. Pérez Quirós, Gabriel & Pérez, Javier J. & Paredes, Joan, 2015. "Fiscal targets. A guide to forecasters?," Working Paper Series 1834, European Central Bank.
  4. Bruine de Bruin, Wändi & van der Klaauw, Wilbert & Topa, Giorgio, 2011. "Expectations of inflation: The biasing effect of thoughts about specific prices," Journal of Economic Psychology, Elsevier, vol. 32(5), pages 834-845.
  5. Andreas Fuster & David Laibson & Brock Mendel, 2010. "Natural Expectations and Macroeconomic Fluctuations," Journal of Economic Perspectives, American Economic Association, vol. 24(4), pages 67-84, Fall.
  6. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," Review of Economic Studies, Oxford University Press, vol. 76(3), pages 1071-1102.
  7. Tomasz Michalski & Gilles Stoltz, 2013. "Do Countries Falsify Economic Data Strategically? Some Evidence That They Might," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 591-616, May.
  8. Camacho, Maximo & Dal Bianco, Marcos & Martinez-Martin, Jaime, 2015. "Toward a more reliable picture of the economic activity: An application to Argentina," Economics Letters, Elsevier, vol. 132(C), pages 129-132.
  9. Sebastian J. Goerg & Johannes Kaiser, 2009. "Nonparametric testing of distributions—the Epps–Singleton two-sample test using the empirical characteristic function," Stata Journal, StataCorp LP, vol. 9(3), pages 454-465, September.
  10. Mary A. Burke & Michael Manz, 2011. "Economic literacy and inflation expectations: evidence from a laboratory experiment," Public Policy Discussion Paper 11-8, Federal Reserve Bank of Boston.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:22103. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.