Carriers in liner shipping markets frequently make public announcements of general rate increase (GRI) intentions, based on which EU authorities have concerns as to whether this harms market competition. This paper aims to empirically investigate how well the GRI system works from an industrial competition perspective, which will indirectly indicate whether carriers are able to manipulate spot rates following GRI announcements. Taking the Far East–North Europe trade between 2009 and 2013 as an example, the paper first reveals the gradual increase of GRI frequency and size, which reflects carriers’ attempts to restore profitability against overcapacity. However, out of all the GRI events only 28.6% were observed to be successful. Since these GRI successes must be the results of either price collusion (if any) and/or normal rate change by carriers in response to fundamental market developments, the effective collusion, if it exists, is actually lower than 28.6%. Next, we identify eight factors influencing GRI successes. To further assess their impact, we applied an ordered logit regression analysis, which, based on four of the factors involved, yields good predictability for GRI success. The four factors, in sequence of explanation power, are the total capacity of GRI carriers, the idling fleet size, the spot rate level, and the average ship-loading factor. Clearly the latter three factors are market fundamentals, which are unlikely to be influenced by an individual carrier in the short term. In actual fact, the conclusion reached is that there is little evidence that carriers can manipulate and distort spot rates through GRIs.
This study introduces a state-of-the-art volatility forecasting method for container shipping freight rates. Over the last decade, the container shipping industry has become very unpredictable. The demolition of the shipping conferences system in 2008 for all trades calling a port in the European Union (EU) and the global financial crisis in 2009 have affected the container shipping freight market adversely towards a depressive and non-stable market environment with heavily fluctuating freight rate movements. At the same time, the approaches of forecasting container freight rates using econometric and time series modelling have been rather limited. Therefore, in this paper, we discuss contemporary container freight rate dynamics in an attempt to forecast for the Far East to Northern Europe trade lane. Methodology-wise, we employ autoregressive integrated moving average (ARIMA) as well as the combination of ARIMA and autoregressive conditional heteroscedasticity (ARCH) model, which we call ARIMARCH. We observe that ARIMARCH model provides comparatively better results than the existing freight rate forecasting models while performing short-term forecasts on a weekly as well as monthly level. We also observe remarkable influence of recurrent general rate increases on the container freight rate volatility.