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Takuma Matsuda

Publications and source records attributed to Takuma Matsuda.

2 recordsLinked to original sources

Unified Merger List in the Container Shipping Industry from 1966 to 2022: A Structural Estimation of M&A Matching

We construct a novel unified merger list in the global container shipping industry between 1966 (the beginning of the industry) and 2022. Combining the list with proprietary data, we construct a structural matching model to describe the historical transition of the importance of a firm's age, size, and geographical proximity on merger decisions. We find that, as a positive factor, a firm's size is more important than a firm's age by 9.858 times as a merger incentive between 1991 and 2005. However, between 2006 and 2022, as a negative factor, a firm's size is more important than a firm's age by 2.013 times, that is, a firm's size works as a disincentive. We also find that the distance between buyer and seller firms works as a disincentive for the whole period, but the importance has dwindled to economic insignificance in recent years. In counterfactual simulations, we observe that the prohibition of mergers between firms in the same country would affect the merger configuration of not only the firms involved in prohibited mergers but also those involved in permitted mergers. Finally, we present interview-based evidence of the consistency between our merger lists, estimations, and counterfactual simulations with the industry experts' historical experiences.

econ.GN

Unified Container Shipping Industry Data From 1966: Freight Rate, Shipping Quantity, Newbuilding, Secondhand, and Scrap Price

We construct a new unified panel dataset that combines route-year-level freight rates with shipping quantities for the six major routes and industry-year-level newbuilding, secondhand, and scrap prices from 1966 (the beginning of the industry) to 2009. We offer detailed instructions on how to merge various datasets and validate the data's consistency by industry experts and former executives who have historical knowledge and experience. Using this dataset, we provide a quantitative and descriptive analysis of the industry dynamics known as the container crisis. Finally, we identify structural breaks for each variable to demonstrate the impact of the shipping cartels' collapse.

econ.GN