With the rapid expansion of data availability, statistical modeling has become essential for analyzing intricate economic and trade relationships. Despite the increasing application of advanced statistical methods in international trade research, this study employing the Finite Mixture Model (FMM) with Bayesian estimation for time series data remain scarce. Given the heterogeneity and structural complexity inherent in trade data, FMM is particularly well-suited for capturing latent patterns and underlying market dynamics. Meanwhile, Bayesian method provides a robust framework for parameter inference, offering flexibility in handling model uncertainty and improving the reliability of estimates. This research investigates the impact of exchange rate fluctuations on China_s rice import and export by applying FMM fitted with the Bayesian method. Specifically, it identifies the presence of two components representing stable and volatile periods in the time series data, models their structur.....

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