Modeling Adequacy Ratio in Life Insurance Using Markov Switching Approach
Abstract View: 28,
DOI:
https://doi.org/10.32665/statkom.v5i1.6459Keywords:
Life Insurance, Markov Switching Model, Nonlinear, Regime, Time SeriesAbstract
Background: The life insurance sector often experiences nonlinear fluctuations during macroeconomic shocks and disasters. To capture these dynamics, nonlinear methods such as the Markov switching model are appropriate.
Objective: This study examines the effects of premium adequacy and investment returns on the claim payment ratio in Indonesia’s life insurance sector using a Markov switching approach.
Methods: This study analyzed 115 monthly observations of premium adequacy, investment returns, and claim payment ratios from January 2016 to July 2025, obtained from the Otoritas Jasa Keuangan (OJK). Three Markov switching models (MSM, MSV, and MSMV) were compared to identify the dominant source of regime-switching behavior. The two-regime Markov switching variance model was selected based on convergence and the lowest Akaike Information Criterion (AIC).
Results: The optimal model identified a volatile regime and a stable regime. The volatile regime had a 75.87% persistence probability with an average duration of four months, whereas the stable regime showed a 90.52% persistence probability and an average duration of 10.5 months. The probability of transitioning from volatility to stability (24.13%) exceeded the probability of shifting from stability to volatility (9.48%).
Conclusion: Indonesia’s conventional life insurance sector demonstrates resilience by maintaining stable conditions and recovering from periods of volatility.
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