Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey
Sumru Altug and
Cem Çakmaklı
International Journal of Forecasting, 2016, vol. 32, issue 1, 138-153
Abstract:
In this paper, we formulate a statistical model of inflation that combines data on survey expectations with the inflation target set by central banks. Our model produces inflation forecasts that are aligned with survey expectations, thus integrating the predictive power of the survey expectations into the baseline model. Furthermore, we incorporate the inflation target set by the monetary authority in order to examine the effectiveness of monetary policy in forming inflation expectations, and therefore, in predicting inflation accurately. The results indicate that the predictive power of the proposed framework is superior to that of the model without survey expectations, as well as to the performances of several popular benchmarks, such as the backward- and forward-looking Phillips curves and a naïve forecasting rule.
Keywords: Inflation forecasting; State space models; Survey-based expectation; Inflation targeting; Term structure of inflation expectations (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207015000813
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey (2015) 
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: https://EconPapers.repec.org/RePEc:eee:intfor:v:32:y:2016:i:1:p:138-153
DOI: 10.1016/j.ijforecast.2015.03.010
Access Statistics for this article
International Journal of Forecasting is currently edited by R. J. Hyndman
More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().