Clustering and forecasting inflation expectations using the World Economic Survey : the case of the 2014 oil price shock on inflation targeting countries
Borradores de Economía; No. 993
Date of last update2017-05-04
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Las opiniones contenidas en el presente documento son responsabilidad exclusiva de los autores y no comprometen al Banco de la República ni a su Junta Directiva.
This paper examines inflation expectations of the World Economic Survey for ten inflation targeting countries. First, by a Self Organizing Maps methodology, we cluster the trajectory of agents inflation expectations using the beginning of the oil price shock occurred in June of 2014 as a benchmark in order to discriminate between those countries that anticipated the shock smoothly and those with brisk changes in expectations. Then, the expectations are modeled by artificial neural networks forecasting models. Second, for each country we investigate the information content of the quantitative survey forecast by comparing it to the average annual inflation based on national consumer price indices. The results indicate the presence of heterogeneity among countries to anticipate inflation under the oil shock and, also different patterns of accuracy to predict average annual inflation were found depending on the observed inflation trend.
C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion processesC63 - Computational Techniques; Simulation ModelingC45 - Neural Networks and Related TopicsE27 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy: Forecasting and Simulation: Models and ApplicationC02 - Mathematical Methods
- Borradores de Economía