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​Measuring the Systemic Risk Contribution of Philippine Industries and Conglomerate Groups​

Author

Listed:
  • Jorjin F. Godoy

    (Bangko Sentral ng Pilipinas)

Abstract

This study evaluates the exposure of Philippine industries and conglomerates to systemic risk using SRISK, a metric that measures expected capital shortfall during market downturns. It also examines how macroeconomic indicators—gross domestic product (GDP) growth, the policy rate, the USD–PHP exchange rate, unemployment, and inflation—influence systemic risk through a vector autoregression (VAR) model. The findings show that SRISK was three times higher during the COVID-19 pandemic than during the Global Financial Crisis, rising from 2017 and peaking in Q1 2024. Although its share has declined, the banking sector has remained the largest contributor to systemic risk, while the property sector’s risk contribution has increased since 2018. At the conglomerate level, a widening network of major groups contributes significantly to systemic risk, indicating increasing complexity and potential for contagion. Impulse responses indicate that higher GDP growth, policy rate, and inflation reduce risk in the short term, while increased unemployment and peso depreciation increase risk. Variance decomposition analysis reveals that systemic risk variability is primarily driven by shocks to GDP, followed by the policy rate, unemployment, the USD–PHP exchange rate, and inflation. For the banking sector, self-induced shocks remain the dominant influence

Suggested Citation

  • Jorjin F. Godoy, 2025. "​Measuring the Systemic Risk Contribution of Philippine Industries and Conglomerate Groups​," BSP Discussion Paper Series 202508, Bangko Sentral ng Pilipinas.
  • Handle: RePEc:bhd:dpaper:202508
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    File URL: https://www.bsp.gov.ph/Sites/researchsite/Publications/BSP-Discussion-Papers/DP202508.pdf
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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