This thesis examines whether there is a bidirectional relationship between economic complexity and economic growth for 34 OECD countries using years between 1998–2024. The aim is to investigate whether there is any short-run predictiveness for economic complexity and economic growth. To estimate the bidirectional relationship, we have conducted a panel vector autoregressive framework estimated through the generalized method of moments (GMM) approach. This methodology allows both economic growth and complexity to be treated as endogenous variables while capturing dynamic interactions over time. The results present mixed evidence regarding the bidirectional relationship between trade, technology, and research complexity and economic growth. Growth had a significant positive effect in predicting future trade complexity, while the reverse relationship was found to be insignificant. In contrast, technology complexity significantly predicted increases in short-run growth, whereas significant reversed relationships were insignificant. Research complexity also showed significant predictive effects on future short-run growth, while no significant reverse relationship was found. Overall, the findings suggest that trade, technology, and research complexity influence growth differently, as well as how growth influences the complexity measurements differently in short-run.