Peramalan dan Uji Ketahanan (Stress Testing) Inflation at Risk (IaR) menggunakan Model Quantile Vector Autoregression with Exogenous Variables (QVARX)

Juliarini, Ni Kadek (2025) Peramalan dan Uji Ketahanan (Stress Testing) Inflation at Risk (IaR) menggunakan Model Quantile Vector Autoregression with Exogenous Variables (QVARX). Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Inflasi merupakan kenaikan harga barang dan jasa secara umum dan terus menerus dalam jangka waktu tertentu. Inflasi dapat dipengaruhi oleh shocks dan dalam kondisi ekstrem, kemampuan Bank Indonesia dalam mengendalikannya relatif terbatas. Oleh karena itu, peramalan risiko inflasi dan uji ketahanan (stress testing) akan diperlukan guna mengantisipasi skenario yang dapat memengaruhi stabilitas ekonomi. Berdasarkan hasil analisis, estimasi parameter model telah diformulasikan secara sistematis melalui pendekatan QMLE dan dioptimalkan menggunakan algoritma FN. Model QVARX menunjukkan keunggulan dalam mengakomodasi volatilitas tinggi sedangkan VARX lebih sesuai untuk sektor inflasi yang relatif stabil. Prediksi inflasi di luar data training dan testing periode Januari 2025 sampai Oktober 2025 secara umum menunjukkan pola penurunan pada semua kategori inflasi. Hal ini mengindikasikan potensi perbaikan stabilitas harga pada periode mendatang. Peramalan IaR menunjukkan inflasi perumahan memiliki potensi risiko paling tinggi dibandingkan inflasi lainnya, sedangkan inflasi kesehatan memiliki risiko inflasi paling rendah. Stress testing menunjukkan shocks inflasi pada kondisi ekonomi normal cenderung bertahan sementara dan efeknya hanya dirasakan di awal periode guncangan. Berbeda halnya pada kondisi ekonomi ekstrem, efek guncangan cenderung tidak signifikan di awal periode guncangan, namun bertahap dengan nilai yang semakin tinggi. Inflasi pendidikan dan perumahan merupakan sektor yang paling rentan terhadap guncangan, sehingga intervensi pada kedua sektor ini dapat menjadi kunci untuk memitigasi transmisi inflasi lintas sektor terutama dalam kondisi ekonomi yang tidak stabil.
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Inflation is a general and continuous increase in the prices of goods and services over a period of time. Inflation can be affected by shocks and under extreme conditions, Bank Indonesia's ability to control it’s relatively limited. Therefore, inflation risk forecasting and stress testing will be required to anticipate scenarios that may affect economic stability. Based on the analysis, the model parameter estimation has been formulated systematically through QMLE approach and optimized using FN algorithm. QVARX model shows superiority in accommodating high volatility while VARX is more suitable for relatively stable inflation sectors. Predicted inflation outside the training and testing data for the period January 2025 to October 2025 generally shows a decreasing pattern in all inflation sectors. This indicates the potential for improvement in price stability in the coming period. IaR forecasting results show housing inflation has the highest potential risk compared to other inflation, while health inflation has the lowest inflation risk. Stress testing shows that inflation shocks in normal economic conditions tend to last temporarily and the effects are only felt at the beginning of the shock period. Unlike in extreme economic conditions, the effect of shocks tends to be insignificant at the beginning of the shock period, but gradually with increasingly high values. Education and housing inflation are the most vulnerable sectors to shocks, so interventions in these two sectors can be the key to mitigate the transmission of inflation across sectors especially in unstable economic conditions.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Forecasting, Stress Testing, Financial Stress Index (FSI), Financial Condition Index (FCI), Inflation at Risk (IaR), Quantile Vector Autoregression with Exogenous Variables (QVARX). ============================================================ Forecasting, Stress Testing, Financial Stress Index (FSI), Financial Condition Index (FCI), Inflation at Risk (IaR), Quantile Vector Autoregression with Exogenous Variables (QVARX).
Subjects:	Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions:	Faculty of Mathematics and Science > Statistics > 49101-(S2) Master Thesis
Depositing User:	Ni Kadek Juliarini
Date Deposited:	23 Jul 2025 05:44
Last Modified:	23 Jul 2025 05:44
URI:	http://repository.its.ac.id/id/eprint/120344

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