![]() ![]() The Port of New York/New Jersey retook the top spot at 460,414 TEUs in June up ~24,000 TEUs compared with May. Looking at five-month periods (see Figure 2), top West Coast ports (orange), with the exception of Long Beach and (barely) Seattle, experienced container throughput shifts to other ports, including on the East and Gulf Coasts. ![]() In June 2022, the top 10 represented 86.7% of all volume, compared with 85.1% in May 2022 and 86.1% year-on-year. ![]() The top 10 ports reversed the trend of losing business to smaller ports. While investigating the Far East to Northern Europe trade route only, we believe that the proposed approach of integrating such judgements by practitioners can improve forecast performance for other trade routes and shipping markets, too, and probably allows detection of market changes and/or economic development notably earlier than factual data available at that time.The slight decline in container import volume in June 2022 versus May 2022 impacted smaller ports more, and the East and Gulf Coast ports continued to lead the West Coast ports in volume as importers continue to mitigate supply chain risk.Ĭomparing the top five West Coast ports to the top five East and Gulf Coast ports in June 2022 versus May 2022 shows that, of the total import container volume, the East dipped to 45.4% in June 2022 from 44.4% in May 2022, while the West edged slightly higher to 42.3% in June 2022 from 41.5% in May 2022. ![]() Hence, a sampling of sentiments, perceptions and/or confidence from a panel of practitioners active in the maritime shipping market contributes to an improved predictive power, even when compared to models that integrate hard facts in the sense of factual data collected by official statistical sources. We find that incorporating the Logistics Confidence Index (LCI) provided by Transport Intelligence into the ARIMAX model improves forecast performance greatly. As a base case, an autoregressive integrated moving average (ARIMA) model was used and compared the results with multivariate modelling frameworks that could integrate exogenous variables, that is, ARIMAX and Vector Autoregressive (VAR). This study presents a novel approach to forecast freight rates in container shipping by integrating soft facts in the form of measures originating from surveys among practitioners asked about their sentiment, confidence or perception about present and future market development. ![]()
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