Analyzing the Effects of Transportation Development on Macroeconomic Indicators in Iran: A Granger Causality Approach

Development of transport and logistics infrastructure is one of the fundamental prerequisites for sustainable growth and the enhancement of national economic competitiveness, and it affects macroeconomic variables through channels such as reducing transaction costs, improving spatial accessibility, and increasing the efficiency of supply chains. Accordingly, analyzing the dynamic and endogenous relationship between transport development and key macroeconomic indicators is of particular importance for evidence‑based policymaking. Using time‑series data for Iran within a Vector Autoregression (VAR) framework, this study examines the interactions between transport development and gross domestic product, inflation, unemployment, stock market index, exchange rate, and liquidity. Preliminary diagnostic tests indicate that the statistical properties of the variables are suitable for estimating the VAR model, and the optimal lag length is determined as two periods based on standard information criteria. The estimated VAR model, with an adjusted coefficient of determination of approximately 0.98 for the transport development equation, reveals a very high explanatory power. Based on Granger causality tests, transport development is found to Granger‑cause GDP growth, stock market performance, and liquidity expansion in a statistically significant manner, while several macroeconomic variables also exert significant causal effects on transport. The results of forecast error variance decomposition indicate that, in the long run, the contribution of transport‑related shocks to the variance of GDP and liquidity fluctuations increases substantially, and the impulse response functions further confirm a positive and persistent impact of transport shocks on economic growth and stock market performance.