Despite the rapid growth of Korea’s abalone aquaculture industry, stagnant domestic demand has led to persistent oversupply, placing downward pressure on prices and underscoring the need for effective supply-demand forecasting. In response to increasing mortality risks, farmers have shortened the grow-out period, inadvertently exacerbating the oversupply problem. This study develops a simultaneous equation model to capture the dynamic interactions between abalone supply and demand. To address potential structural changes in the time-series data, multiple breakpoint tests were conducted. Most variables in the behavioral equations were statistically significant at the 1% level. However, the coefficient for shipment volume in the grow-out stock equation for abalone over one year was not statistically significant, although it remained economically plausible. The model incorporates both in-sample and out-of-sample forecast evaluations, along with a policy simulation module to enhance practical applicability. Except for export-related equations, the model exhibits strong predictive accuracy. These results suggest that the proposed framework is a valuable tool for forecasting and policy planning in Korea’s abalone industry.
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Moon et al. (2025) studied this question.
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