Spatial Vector Autoregressive with Metric Exogenous Variable (SpVARX) for Inflation and Outflow Forecasting

Gama Putra Danu Sohibien, Setiawan*, Dedy Dwi Prastyo

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Forecasting inflation and outflow is very important for the government to make price control policies. We propose SpVARX be applied to inflation and outflow forecasting. SpVARX can simultaneously accommodate interrelationships between variables, the influence of metric exogenous variables, and spatial aspects. Our study shows SpVARX has better forecasting performance than SpVAR, as most of SpVARX's Root Mean Square Errors (RMSEs) are smaller than SpVAR's. Based on the forecast, the highest inflation in Semarang and Solo will occur in November 2023, while the highest inflation in Yogyakarta will occur in December 2023. The highest outflow forecast for all these cities is in April 2023.

Original languageEnglish
Pages (from-to)140-147
Number of pages8
JournalProcedia Computer Science
Volume234
DOIs
Publication statusPublished - 2024
Event7th Information Systems International Conference, ISICO 2023 - Washington, United States
Duration: 26 Jul 202328 Jul 2023

Keywords

  • Exogenous Variabel
  • Forecasting
  • Money Supply
  • Outflow
  • Spatial Vector Autoregressive

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