Addition of Subset and Dummy Variables in the Threshold Spatial Vector Autoregressive with Exogenous Variables Model to Forecast Inflation and Money Outflow

Setiawan Setiawan*, Gama Putra Danu Sohibien, Dedy Dwi Prastyo, Muhammad Sjahid Akbar, Anton Abdulbasah Kamil

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The TSpVARX model can be used in inflation and money outflow forecasting by accommodating the reciprocal relationship among endogenous variables, the influence of exogenous variables, inter-regional linkages, and the nonlinearity of the relationship between endogenous and predetermined variables. However, the impact of some events, such as Eid al-Fitr and fuel price adjustments, still cannot be accommodated in the TSpVARX model. This condition causes inflation and money outflow forecasting using TSpVARX to be unsatisfactory. Our study is to improve the forecasting performance of the TSpVARX model by adding subset and dummy variables. We use a 12th lag subset variable to capture seasonal effects and a dummy variable to represent fuel price changes. These additions enhance the model’s accuracy in forecasting inflation and money outflow by accounting for recurring patterns and specific events, like fuel price changes. Based on the RMSE values of the training and testing data, we can conclude that forecasting inflation and money outflow using TSpVARX with the addition of subset and dummy variables is better than the regular TSpVARX. The inflation and money outflow forecasting generated after the addition of subset and dummy variables are also more fluctuating as in the movement of the actual data.

Original languageEnglish
Article number352
JournalEconomies
Volume12
Issue number12
DOIs
Publication statusPublished - Dec 2024

Keywords

  • SpVAR
  • TSpVARX
  • inflation
  • nonlinear time series
  • subset variable
  • threshold spatial

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