Vector Error Correction Model (VECM) Modeling in Indonesian Economic Growth Analysis (2014 - 2023) using Artificial Intelligence (AI) Based Statistical Analysis Tools

Abstrak

Vector Error Correction Model (VECM) is a time series modeling method that is often referred to as a form of restricted VAR. It is useful in understanding the interrelationship between variables where all variables are treated as endogenous variables. This study focuses on the analysis of Indonesia's economic growth using four variables, namely: GDP, Trade Openness, Exchange Rate, and the amount of money in circulation (M2) during the period 2014 - 2023. The analysis was carried out using the AI-based STATA application which was carried out in stages starting from the stationary test, determining the optimal lag, stability, cointegration, VECM and finally the Impulse Response Function (IRF). The results of the analysis carried out using the Johansen Cointegration Test for the four variables have a long-term equilibrium stability relationship (cointegration) with each other. The model formed is VECM (1). From the structural analysis of the IRF, it can be seen that all response movement variables are approaching the equilibrium point (convergence) or returning to their previous equilibrium.