Abstract
This study investigates the impact of international tourism revenues, the real effective exchange rate, and oil revenues on economic growth in Kazakhstan using the quantile regression method. Unlike traditional linear models that primarily focus on average effects, analyzing the determinants of economic growth across different distribution points (or quantile levels) provides more nuanced and valuable insights for policymakers. The research utilizes annual time series data from 1995 to 2023. After testing the stationarity of the variables using the Augmented Dickey-Fuller (ADF) test, both least squares regression analysis and quantile regression models were applied. The results indicate a positive and statistically significant effect of oil revenues on Gross Domestic Product (GDP) at all quantile levels. In contrast, while tourism revenues and the real effective exchange rate index also had a positive impact on economic growth, these effects were not found to be statistically significant in the quantile regression models. These findings suggest that the Kazakh economy remains heavily reliant on energy revenues, which may heighten its economic vulnerabilities. The study emphasizes the need for increased economic diversification, support for the tourism sector through effective policies, and a review of exchange rate policies. It also highlights the importance of tailoring growth strategies not just based on average performance but also according to different levels of economic outcomes.