APPLICATION OF PANEL VECTOR AUTOREGRESSIVE (PVAR) MODEL ON THE ANALYSIS OF INFLATION AND GDRP RATE - Khairunnisa Khairunnisa; Khoirin Nisa; Misgiyati Misgiyati; Nusyirwan Nusyirwan (RAGAM: Journal of Statistics & Its Application, 2026)
PVAR is an extension of the VAR model applied to panel data, combining time series with cross-sectional data from various regions. This model enables all variables to be treated as endogenous and analyzed simultaneously. This study aims to examine the relationship between inflation and economic growth (GRDP) across Indonesian provinces using the Panel Vector Autoregressive (PVAR) model. The analysis includes stationarity testing (IPS test), optimal lag selection (MMSC), and parameter estimation using the Generalized Method of Moments (GMM). The validity of instruments is assessed through the Sargan-Hansen test, while causal relationships are analyzed using the Granger causality test. Results indicate a bidirectional relationship between inflation and economic growth in several provinces. The model is proven to be stable. Furthermore, the Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) analyses illustrate how shocks to one variable influence the other over time. These findings are expected to contribute to more effective formulation of regional economic policies.