PEMODELAN TINGKAT INFLASI INDONESIA MENGGUNAKAN MARKOV SWITCHING AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY - Omy Wahyudi; Budi Warsito; Alan Prahutama (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2015)
The financial sector often under conditions of fluctuating due to changes in monetary policy, the political instability even just a rumor. The linear model cannot capture changes in these conditions, so the model used is Markov Switching Autoregressive Conditional Heteroskedasticity (SWARCH). This model produces value of transition probability and the duration of each state. Filtering and smoothing process performed to determine probability of the observation data in each state. Modeling about the inflation data in Indonesia was done. The model used is SWARCH (2.1) with 240 data. The probability of inflation rate switch from non crisis state to crisis state is 0.016621, while the probability of inflation rate switch from crisis state to non crisis state is 0.195719. Expectation value of the length time in non crisis state is 60.16 days and the crisis state is 5.11 days.Keywords : filtering, smoothing, transition probability, SWARCH