Forecasting Inflation Based on Money Supply and Interest Rates Using a Transfer Function Model

Kirana Rispanzira; Mikhratunnisa Mikhratunnisa

doi:10.30812/varian.v9i1.6143

Authors

Kirana Rispanzira Universitas Teknologi Sumbawa, Sumbawa, Indonesia
Mikhratunnisa Universitas Teknologi Sumbawa, Sumbawa, Indonesia

DOI:

https://doi.org/10.30812/varian.v9i1.6143

Keywords:

Forecasting, Inflation, Interest Rates, Money Supply, Multi-Input Transfer Function Models

Abstract

Inflation is a condition in which the prices of goods and services in a country continuously increase over an extended period. Uncontrolled inflation may lead to a decline in the value of currency, economic instability, and rising poverty levels. Several factors that influence inflation include the amount of money in circulation and Indonesia's interest rates. This study aims to model and forecast inflation in Indonesia using a multi-input transfer function model based on the amount of money in circulation and interest rates as input variables. The dataset consists of monthly observations from January 2001 to November 2025, obtained from Bank Indonesia and the Central Statistics Agency (BPS). The general stages in this study include examining data stationarity, identifying and determining the best ARIMA model for input and output series, determining the multi-input transfer function model, and forecasting. The results indicate that the transfer function model with order (0,0,0)(0,2,1)[0,0,2] provides the best performance in forecasting inflation. This model is able to capture the deflation phenomenon in early 2025 and the increasing inflation movement in the following months. The forecast for 2026 also shows a fluctuating pattern that describes macroeconomic dynamics, including changes in liquidity, interest rate policy, and global commodity conditions. A MAPE value of 1.3975% reflects excellent forecasting accuracy, indicating that the model effectively captures actual inflation dynamics. This study confirms that the transfer function approach is effective for modeling the dynamic relationship between monetary variables and inflation for forecasting inflation in Indonesia.

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Author Biographies

Kirana Rispanzira, Universitas Teknologi Sumbawa, Sumbawa, Indonesia

Mahasiswa Program Studi Ilmu Aktuaria, Universitas Teknologi Sumbawa
Mikhratunnisa, Universitas Teknologi Sumbawa, Sumbawa, Indonesia

Dosen Program Studi Ilmu Aktuaria, Universitas Teknologi Sumbawa

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