AN EARLY WARNING SYSTEM FOR INFLATION IN THE PHILIPPINES USING MARKOV-SWITCHING AND LOGISTIC REGRESSION MODELS
AbstractWith the adoption of the Bangko Sentral ng Pilipinas (BSP) of the Inflation Targeting (IT) framework in
2002, average inflation went down in the past decade from historical average. However, the BSP’s inflation
targets were breached several times since 2002. Against this backdrop, this paper attempts to develop an early
warning system (EWS) model for predicting the occurrence of high inflation in the Philippines. Episodes of high
and low inflation were identified using Markov-switching models. Using the outcomes of the regime classification,
logistic regression models are then estimated with the objective of quantifying the possibility of the occurrence of
high inflation episodes. Empirical results show that the proposed EWS model has some potential as a
complementary tool in the BSP’s monetary policy formulation based on the in-sample and out-of sample
The Copyright Transfer Form to ASERS Publishing (The Publisher)
This form refers to the manuscript, which an author(s) was accepted for publication and was signed by all the authors.
The undersigned Author(s) of the above-mentioned Paper here transfer any and all copyright-rights in and to The Paper to The Publisher. The Author(s) warrants that The Paper is based on their original work and that the undersigned has the power and authority to make and execute this assignment. It is the author's responsibility to obtain written permission to quote material that has been previously published in any form. The Publisher recognizes the retained rights noted below and grants to the above authors and employers for whom the work performed royalty-free permission to reuse their materials below. Authors may reuse all or portions of the above Paper in other works, excepting the publication of the paper in the same form. Authors may reproduce or authorize others to reproduce the above Paper for the Author's personal use or for internal company use, provided that the source and The Publisher copyright notice are mentioned, that the copies are not used in any way that implies The Publisher endorsement of a product or service of an employer, and that the copies are not offered for sale as such. Authors are permitted to grant third party requests for reprinting, republishing or other types of reuse. The Authors may make limited distribution of all or portions of the above Paper prior to publication if they inform The Publisher of the nature and extent of such limited distribution prior there to. Authors retain all proprietary rights in any process, procedure, or article of manufacture described in The Paper. This agreement becomes null and void if and only if the above paper is not accepted and published by The Publisher, or is with drawn by the author(s) before acceptance by the Publisher.