Research Information System
Economies, vol.12, no.352, pp.1-27, 2024 (ESCI)
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.