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All Journal Enthusiastic : International Journal of Applied Statistics and Data Science
Hestuningtias, Feby
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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The Implementation of the Generalized Space-Time Autoregressive (GSTAR) Model for Inflation Prediction Hestuningtias, Feby; Kurniawan, Muhammad Hasan Sidiq
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 2, October 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss2.art5

Abstract

The macroeconomic indicator used to measure a country’s economic balance is inflation. The increase in the price of goods and services causes an increase in inflation, which impacts the decrease in the value of money so that people’s purchasing power for goods and services will decrease and result in slow economic growth. One way to determine future inflation is by forecasting. The Generalized Space-Time Autoregressive (GSTAR) model is a time series model involving time and location. This study aims to predict future inflation using the GSTAR model, which uses differencing without uniform location weights, inverse distance, and normalized cross-correlation. The results showed that the models obtained were the GSTAR (2,1) and GSTAR (5,1)I(1) models. The best model to predict inflation is the GSTAR (5,1)I(1) model with the normalized cross-correlation weight, which had Root Mean Square Error (RMSE) value of 0.5743, which was smaller than the GSTAR (2,1) model.
Co-Authors Kurniawan, Muhammad Hasan Sidiq