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An Early Warning System For Inflation In The Philippines Using Markov-Switching And Logistic Regression Models

Author

Listed:
  • Christopher CRUZ

    (Bangko Sentral ng Pilipinas, Philippines)

  • Claire MAPA

    (University of the Philippines School of Statistics, Philippines)

Abstract

With 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 forecasting performance.

Suggested Citation

  • Christopher CRUZ & Claire MAPA, 2013. "An Early Warning System For Inflation In The Philippines Using Markov-Switching And Logistic Regression Models," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 4(2), pages 136-150.
    • Handle: RePEc:srs:jtpref:v:4:y:2013:i:2:p:136-150
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    References listed on IDEAS

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    Cited by:

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    2. Lawrence Xaba & Ntebogang Moroke & Johnson Arkaah & Charlemagne Pooe, 2015. "A Comparative Study of Stock Price Forecasting using nonlinear models," Proceedings of International Academic Conferences 2704207, International Institute of Social and Economic Sciences.
    3. Diteboho Xaba & Ntebogang Dinah Moroke & Johnson Arkaah & Charlemagne Pooe, 2016. "Modeling South African Banks closing stock prices: a Markov-Switching Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 8(1), pages 36-40.
    4. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.

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    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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