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Gross Domestic Product (GDP) is one of the main determinants of a country’s economic growth. This paper investigates the impact of Islamic finance on the economic growth of six Arab countries over the 14-year period from 2009 to 2022. A dynamic panel data analysis is applied to six countries (United Arab Emirates, Saudi Arabia, Oman, Iran Islamic Republic, Lebanon, and Jordan), using 84 observations. Data were collected from World Development Indicators (WDI) provided by the World Bank (2020) and PSIFIs Data (2020). The GDP growth rate is used as a proxy for economic growth, while the annual growth rate of Islamic finance, inflation, exports, gross capital formation, FDI, and gross domestic savings are used as proxies for Islamic finance. Econometric regression analysis was conducted using Pooled OLS, Fixed Effects, and Random Effects models. Multiple diagnostic tests were used to address multicollinearity, heteroscedasticity, autocorrelation, and cross-sectional dependence. After detecting heteroscedasticity and cross-sectional dependence, robust standard errors were applied in the random-effects model estimation. The empirical results indicate that the Islamic financial system has no significant impact on the economic growth of the six Arab countries studied.国内生产总值（GDP）是影响一国经济增长的核心指标之一。本文针对2009至2022年共14年的时间跨度，探究伊斯兰金融（Islamic finance）对6个阿拉伯国家经济增长的影响。研究选取阿拉伯联合酋长国、沙特阿拉伯、阿曼、伊朗伊斯兰共和国、黎巴嫩和约旦共6个样本国，采用动态面板数据分析（dynamic panel data analysis）方法，共获取84组观测值。研究数据来源于世界银行（World Bank）2020年发布的世界发展指标（World Development Indicators, WDI）以及2020年的PSIFIs数据（PSIFIs Data）。本文以GDP增长率作为经济增长的代理变量，以伊斯兰金融年度增长率、通货膨胀率、出口额、总资本形成、外商直接投资（FDI）以及国内总储蓄作为伊斯兰金融的代理指标。计量回归分析采用混合普通最小二乘法（Pooled OLS）、固定效应模型（Fixed Effects）与随机效应模型（Random Effects）开展。为处理多重共线性（multicollinearity）、异方差性（heteroscedasticity）、自相关（autocorrelation）以及截面相关性（cross-sectional dependence）问题，本文实施了多组诊断检验。在检测到异方差性与截面相关性后，研究在随机效应模型的估计过程中采用了稳健标准误（robust standard errors）进行修正。实证结果表明，伊斯兰金融体系对本次研究选取的6个阿拉伯国家的经济增长并无显著影响。