Econometric analysis on the effect of port state control inspections on the probability of casualty: Can targeting of substandard ships for inspections be improved?
Introduction
The maritime industry is characterized by an extensive legal framework with limited legal enforcement possibilities in case of non-compliance. This creates loopholes and distortion to competition due to the existence of a market of substandard ships. Flag states are to be seen as the first line of defense in eliminating sub-standard vessels followed by the second line of defense, the port states. The lack of trust in the industry has further created an increased amount of industry driven inspections for certain ship types. This article looks into the effect of inspections (either port state control or industry inspections) on the probability of casualty, determines the magnitude of improvement possibilities for port state control and gives recommendation on how to improve targeting on substandard ships.
Section snippets
Overview of datasets and classification of casualties
Three datasets have been used for the analysis and their relation can be seen in Fig. 1. Set A consists of the inspection database of 183,819 inspections from various Memoranda of Understanding (MoU) for the time period January 1999–December 2004 where the time period is not fully covered by all regimes. This total dataset is a combination of six individual inspection datasets (Paris MoU, United States Coast Guard, Caribbean MoU, Indian Ocean MoU, Viña del Mar Agreement on PSC and the
Model explanation and variables used
Binary logistic regression is used to provide the estimated probability (P) of a ship having a casualty. The dependent variable (y) in this case is “casualty” or “no casualty”. The binary logistic model in its end result provides the necessary coefficients (β) in order to compute the “estimated probabilities of casualty (per seriousness)” given a certain combination of dependent variables (X) which can be classification society, flag state, port state, deficiency code and ship owner.
In binary
Visualization of results: effect of inspections on the probability of casualty
Due to the lack of cooperation of some of the port state control regimes, a portion of vessels that are only inspected in these regions (Tokyo MoU, Black Sea MoU and Mediterranean MoU) is missing from the dataset. The results would have been refined by incorporating this data but will be left as a recommendation for future research.
Table 7 gives a short summary of some of the results of the variables of interest with their respective coefficients and significance across the casualty types. The
The magnitude of improvement possibilities for port state control
Fig. 3 gives on overview of the magnitude of improvement possibilities for targeting vessels. The figure is only based on ships that are relevant for port state control (excluding the fishing fleet >400 gt) and is a summary of the total time frame (1999–2004). The graph shows several groups out of which group 1 of about 36% of the vessels eligible for inspections are identified not to have been problematic over the time period and have also not been targeted by the regimes in question. About 7%
Conclusions and recommendations
Improvement for port state control has been identified in the area of targeting and possibly the inspections itself. About 36% of the vessels eligible for inspections are identified not to have been problematic over the time period in question and have also not been targeted by the regimes in question. About 7% of the vessels eligible for port state control have been targeted over the time frame but did not have a casualty and also no deficiencies and therefore represent a group of
Acknowledgments
The authors would like to acknowledge the following port state control regimes for providing their inspection data: Paris Memorandum of Understanding (MoU), Caribbean MoU, Viña del Mar Agreement on PSC, United States Coast Guard (USCG), Indian Ocean MoU and the Australian Maritime Safety Authority (AMSA). In addition, the authors would like to thank the data providers for the casualty data which were the International Maritime Organization (IMO), Lloyd's Maritime Intelligence Unit and in
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