32
Port State Control Inspection
Deficiencies
Pierre Cariou, François-Charles Wolff and
Maximo Q. Mejia, Jr.
32.1
Introduction
Port state control (PSC) is a regime of unannounced safety inspections on board foreign
ships, conducted by designated PSC authorities in a given port or offshore terminal, to
verify compliance with international regulations relating to manning, equipment,
maintenance and operations. These regulations are contained in provisions under the
International Convention for the Safety of
Life at Sea, 1974, as amended (SOLAS), the
International Convention on Standards of
Training, Certification and Watchkeeping
for Seafarers, 1978, as amended (STCW),
the International Convention for the
Prevention of Pollution from Ships, 1973,
as amended (MARPOL), the International Convention on Load Lines, 1966
(Load Lines), the International Convention on Tonnage Measurement of Ships,
1969 (Tonnage 69), the Convention on
the International Regulations for Preventing Collisions at Sea, 1972, as amended
(COLREG 72), and the Merchant Shipping
(Minimum Standards) Convention, 1976
(ILO Convention No. 147).
While the PSC regime is not a panacea
to prevent all accidents ( Jin, Kite Powell and
Talley 2008), it has played an active role in
reducing substandard shipping. Indeed, PSC
inspections provide many advantages.
Firstly, they represent a credible regime that
balances flag state responsibility against a
port state mandate. Secondly, public information on results from inspections allows
shippers, maritime administrations and
maritime stakeholders to assess a vessel’s
safety records. Thirdly, PSC inspections help
towards the understanding of factors that
explain the likelihood of having a substandard vessel, that is, a vessel whose probability
of being detained for being hazardous to
safety, health or the environment is high.
The Blackwell Companion to Maritime Economics, First Edition. Edited by Wayne K. Talley.
© 2012 Blackwell Publishing Ltd. Published 2012 by Blackwell Publishing Ltd.
PORT STATE CONTROL INSPECTION DEFICIENCIES
These factors are reflected in target factors
used by most PSC regional memoranda of
understanding (MoUs).
This chapter outlines what these targets
factors are, and how deficiencies detected
during a control either are corrected or
recur over time. To do this, we use a data
set of 42,071 vessels/inspections carried out
from 2002 to 2009 by 18 state members of
the Indian Ocean MoU (IO-MoU). The
selection of the IO-MoU is motivated by the
importance of the Indian Ocean in shipping, since it is one of the world’s largest
oceans, where major sea routes connect the
Middle East, Africa and East Asia to Europe
and America, and where strategic trades
such as crude oil and oil products from the
Persian Gulf and Indonesia transit.1 From
an empirical perspective, the IO-MoU provides a unique exhaustive data set, starting
in 2002, on the inspection and detention of
vessels, including information on deficiencies detected over time.
32.2 Substandard Vessels Using
PSC Data: A Survey
PSC traces its origins from a memorandum
of understanding signed in The Hague by
eight North Sea states in 1978. Since then,
nine regional MoUs have been established,
involving almost all the maritime countries.2 One of their main contributions has
been to set up, at a regional level, common
target criteria for selecting vessels to be
inspected;3 selection is necessary because
the resources, personnel and time made
available to inspectors are limited (Knapp
2007). Naturally, the inspecting authorities
then concentrate their efforts on substandard vessels – those with a high probability
of being detained because of hazards to
657
safety, health and the environment – using
target systems based on generic and historic
factors (Paris MoU 2010). Since January
2011, the seven criteria in the new Paris
MoU inspection regime have been ship
type, age, flag, recognized organization,
company performance, and numbers of
deficiencies and of detentions recorded
within the last 36 months.
Economic analyses of PSC regimes often
question the focus of target factors on
vessels that are not compliant with international regulations when one might expect a
focus on vessels more likely to be involved
in accidents. This has led to studies on the
potential relationship between black-listed
flags of registry and casualty data (Knapp
2007; Degré 2008), on the relevance of
target factors (Knapp 2007; Cariou, Mejia
and Wolff 2007, 2008a, 2008b, 2009; Li,
Tapiero and Yin 2009), and on differences
between the results of inspections amongst
countries of inspection (Knapp and Franses
2007, 2008; Cariou and Wolff 2010). If most
criteria, such as the age, type and classification society of a vessel, are found relevant,
a concern remains on the relative weight to
be assigned to these factors; apart from the
Australian Maritime Safety Agency (2008),
which uses its Shipsys database to calculate
a numerical risk for individual ships, PSC
authorities assign weight to risk factors
mainly on the basis of experts’ ad hoc judgment. A recent area of research looks at
opportunistic behavior, such as flag- and
class-hopping, exhibited by shipowners to
avoid controls (Cariou and Wolff 2011).
This chapter provides a contribution that
focuses on the relevance of target factors
when a dynamic approach is used. It aims
at estimating, for a given vessel, how the
results of inspections evolve over time and
whether deficiencies are recurrent.
658
32.3
P. CARIOU, F.-C. WOLFF AND M. Q. MEJIA, JR.
Descriptive Statistics
The PSC IO-MoU data set provides results
for 42,071 inspections carried out from
January 1, 2002 to December 31, 2009 by 18
countries.4 Every PSC boarding results in a
written report containing the following
information: vessel’s name, IMO number,
flag of registry, recognized organization,
type, gross tonnage, deadweight tonnage,
year of delivery, type of control (new or
follow-up), date of inspection, date of
detention, date of release, place of inspection, inspecting authority, and nature of
deficiencies detected. As reported in Table
32.1, bulk carriers (46.5% of vessels
inspected), general cargo ships (16.8%),
tankers (10.2%), and container ships (9%)
are the vessel types subjected to the greatest
proportion of inspections. Australia, with
23,674 inspections or 56.2% of all inspections from 2002 to 2009, is the country that
has undertaken the most number of inspections in the regional MoU.
Figure 32.1 presents the mean number of
deficiencies (as a bar) and the detention rate
(as a line) by year of inspection and by type
of vessel. The mean number of deficiencies
is 2.9, ranging for all vessels from a minimum
of 2.3 in 2002 to a maximum of 3.4 in 2008.
The detention rate is between 5% and 10%.
Figure 32.1 also shows that general cargo/
multi-purpose ships, Ro-Ro cargo ships and
refrigerated cargo carriers record higher
detention rates, specifically since 2006.
We generated eight generic categories of
deficiencies (see Table 32.2) to aid in analyzing potential differences in deficiencies
detected in controls taking place within the
Indian Ocean MoU. These categories are
certificates, working and living conditions,
safety-and fire-fighting appliances, stability
and structure, ship and cargo operations,
equipment and machinery, navigation and
communication, and management-related
deficiencies. Safety- and fire-fighting
appliances-related deficiencies are the most
recurrent type of deficiencies detected
(28.6%), followed by stability and structure
(18.8%) and navigation/communication
(17.6%). Safety- and fire-fighting appliancesrelated deficiencies are found for 34.7% of
vessels inspected.
Figure 32.2 presents results on the types
of deficiencies detected, according to port
state control authorities, vessel age at
inspection, and flag of registry. On board
ships visiting Australian ports, deficiencies
relating to safety and fire-fighting appliances
constituted the most recurring type (31.8%),
followed by navigation and communication
(19.8%). In India, deficiencies related to
safety and fire-fighting appliances were less
likely (13.6%) than those related to stability
and structure (23%). It was found that
vessels of 25 or more years in age had proportionately more deficiencies related to
certificates, while those that were less than
five years old tended to have more deficiencies related to navigation/communication.
Finally, deficiencies related to stability/
structure proved to be more common for
vessels flying the Russian flag.
32.4 Determinants of
Deficiencies
What follows is an attempt to explain how
the characteristics of a vessel influence the
probability that a specific deficiency, defined
as a dichotomous variable, will be recorded.
We therefore exclude vessels without deficiency5 and estimate a set of Probit models.
The factors influencing the probability of a
deficiency being detected during an inspection are as follows:
Table 32.1 Characteristics of vessels inspected (2002–2009)
Variables
Age at PSC inspection
0–4
5–9
10–14
15–19
20–24
25+
Type of ship
Bulk carrier
General cargo/multi-purpose ship
Oil tanker
Container ship
Chemical tanker
Vehicle carrier
Woodchip carrier
Refrigerated cargo carrier
Ro-Ro cargo ship
Gas carrier
Others
Flag of registry
Panama
Liberia
Hong Kong China
Bahamas
Cyprus
Singapore
Russian Federation
Malta
Greece
Others
Recognized organization
Nippon Kaiji Kyokai
Lloyd’s Register
Det Norske Veritas
American Bureau of Shipping
Germanischer Lloyd
Bureau Veritas
Russian Maritime Register
China Classification Society
Korean Register of Shipping
Others
Total number
Australia
India
Iran
South
Africa
Others
Total
18.9
26.2
20.7
15.8
13.6
4.9
14.5
12.2
9.4
10.0
22.0
31.8
14.2
10.8
12.4
14.6
21.8
26.2
17.3
17.3
13.7
14.8
20.2
16.8
9.8
10.5
10.6
8.5
14.4
46.2
16.9
20.2
16.8
14.4
16.7
15.0
58.3
6.6
6.9
9.0
3.1
4.9
2.5
0.3
0.5
1.7
6.3
44.7
33.9
3.4
7.8
4.7
0.1
0.0
0.0
1.0
0.3
4.1
19.8
29.4
27.2
6.0
5.5
0.1
0.0
3.8
2.8
0.9
4.4
44.0
25.4
3.7
10.9
2.5
2.1
2.1
5.3
0.7
0.3
3.1
15.4
29.1
14.3
20.6
4.0
1.3
0.0
0.7
5.1
1.1
8.3
46.5
16.8
10.2
9.0
3.7
3.0
1.6
1.4
1.2
1.3
5.5
31.3
7.1
8.2
5.1
4.0
5.5
0.4
3.2
3.5
31.7
25.3
4.1
6.5
2.4
4.8
5.9
0.3
5.9
1.9
42.9
23.8
6.6
2.8
3.5
3.6
3.5
14.4
6.3
2.2
33.3
23.2
11.4
4.6
7.9
5.5
4.5
0.2
6.0
2.9
33.8
22.5
7.8
3.0
2.9
3.4
5.6
0.3
5.6
1.6
47.5
28.1
7.0
6.5
4.6
4.1
5.1
2.9
4.4
2.9
34.3
37.7
14.6
10.0
9.2
7.4
7.5
0.6
3.9
5.2
4.1
23,674
24.6
14.3
6.4
8.3
8.7
8.9
3.3
6.1
3.8
15.7
5,120
18.1
13.8
9.8
7.6
6.9
7.8
18.7
2.9
2.9
11.6
7,484
25.4
16.1
10.5
9.6
15.4
11.4
2.4
2.0
1.8
5.3
3,777
14.5
11.4
7.0
8.6
14.8
8.1
2.2
2.7
1.6
28.9
2,016
30.4
14.4
9.4
8.8
8.5
8.1
4.4
3.7
4.1
8.1
42,071
Source: own calculation. Indian Ocean MoU 2002–2009.
02
03
04
05
06
Year of inspection
07
08
09
20
02
03
04
05
06
Year of inspection
07
08
09
25
30
08
20
07
15
09
5
1
3
15
4
20
5
25
6
30
30
0
0
0
0
10
15
4
20
Rate of detention (in %)
3
5
3
15
4
20
Rate of detention (in %)
10
2
5
5
1
10
2
3
15
4
20
5
Nb of deficiencies / inspection
5
1
Nb of deficiencies / inspection
5
2
Nb of deficiencies / inspection
1
25
25
25
6
6
6
30
30
30
Year of inspection
02
02
02
02
03
03
03
03
04
Year of inspection
04
04
04
05
05
05
05
06
06
06
06
07
Oil tanker
Container ship
Chemical tanker
07
Year of inspection
Year of inspection
Year of inspection
07
Ro-Ro cargo ship
Gas carrier
Others
07
09
08
09
08
09
08
09
Rate of detention (in %)
08
Rate of detention (in %)
10
2
25
09
0
20
6
0
0
Year of inspection
Rate of detention (in %)
15
5
Woodchip carrier
0
10
4
Vehicle carrier
08
10
06
07
09
5
6
05
06
Rate of detention (in %)
3
Year of inspection
Nb of deficiencies / inspection
5
2
30
Year of inspection
08
5
04
05
07
4
03
04
06
3
02
03
05
2
0
1
25
02
04
1
30
20
6
0
0
0
0
0
0
10
15
4
20
Rate of detention (in %)
3
5
3
15
4
20
Rate of detention (in %)
10
2
5
5
1
3
15
4
20
Rate of detention (in %)
10
2
5
Nb of deficiencies / inspection
5
1
Nb of deficiencies / inspection
5
2
Nb of deficiencies / inspection
1
25
25
25
6
6
6
30
30
30
Bulk carrier
0
15
09
10
0
15
5
09
03
Rate of detention (in %)
6
10
4
Rate of detention (in %)
3
Nb of deficiencies / inspection
5
2
Nb of deficiencies / inspection
1
02
Nb of deficiencies / inspection
5
0
0
09
5
4
08
3
07
08
2
06
07
08
1
30
05
06
07
25
25
6
04
05
06
0
20
5
03
04
05
0
15
4
02
03
04
Rate of detention (in %)
10
3
02
03
Nb of deficiencies / inspection
5
2
Nb of deficiencies / inspection
1
02
0
0
0
All vessels
General cargo/multi-purpose ship
Year of inspection
Refrigerated cargo carrier
Year of inspection
Figure 32.1 Mean number of deficiencies (bar) and detention rates (line) over time, by
type of vessel and year.
Source: own calculations. Indian Ocean MoU 2002–2009.
661
PORT STATE CONTROL INSPECTION DEFICIENCIES
Table 32.2 Type of deficiency by year of inspection
2002
2003
2004
2005
2006
2007
2008
2009
All
% of deficiencies
Certificates
7.2
6.3
5.9
4.5
4.2
4.4
4.9
4.9
5.2
Working/living
7.1
6.0
6.5
7.5
8.5
6.2
7.4
7.0
7.1
conditions
Safety/fire
30.7
28.4
28.5
29.2
28.1
29.1
28.4
27.0
28.6
fighting
appliances
Stability/
18.6
22.8
21.9
19.0
19.0
18.0
16.5
15.8
18.8
structure
Ship/cargo
13.2
13.1
12.3
13.7
12.0
12.3
12.3
12.3
12.6
operations
Equipment/
4.4
4.3
4.2
6.2
5.3
6.7
6.9
7.0
5.7
machinery
Navigation/
16.5
15.9
16.3
14.4
18.8
18.6
18.6
20.3
17.6
communication
Management
2.3
3.3
4.4
5.6
4.2
4.8
5.1
5.6
4.5
% of vessels
Certificates
12.2
10.4
9.9
7.6
8.0
8.9
10.2
10.1
9.7
Working/living
10.6
11.0
11.6
14.5
16.3
13.2
15.6
15.0
13.5
conditions
Safety/fire
30.0
32.5
34.0
35.9
36.5
36.0
36.5
36.9
34.7
fighting
appliances
Stability/
21.7
26.6
27.6
25.6
26.4
26.5
26.0
24.8
25.6
structure
Ship/cargo
19.4
21.1
20.9
22.9
21.4
23.1
22.9
23.0
21.8
operations
Equipment/
6.7
7.6
7.9
10.9
10.9
13.3
13.8
13.6
10.5
machinery
Navigation/
21.6
23.2
25.2
24.4
28.8
28.6
29.8
31.4
26.6
communication
Management
4.4
6.7
8.9
11.4
10.2
10.7
12.4
12.8
9.7
Number of
5431
5072
5642
5180
5087
4791
5593
5275
42071
vessels
inspected
Source: own calculations. Indian Ocean MoU 2002–2009.
Type of deficiency = f ( Age at inspection,
Flag of registry, Type of ship,
Recognized organization, Country
of inspection, Year of inspection)
(1)
Marginal effects are reported in Table 32.3.
The estimated probability of a vessel having
safety- and fire-fighting appliances-related
deficiencies is 28.4% (28.6% for observed
data in Table 32.2), 18.1% for stability and
80
60
40
20
0
Distribution of deficiencies (in %)
100
By inspection country
Australia
India
Iran
South Africa
Other countries
80
60
40
20
0
Distribution of deficiencies (in %)
100
By age at inspection
0-4
5-9
10-14
15-19
20-24
25+
80
60
40
20
0
Distribution of deficiencies (in %)
100
By flag
PNM
LIB
HK-CH
BAH
CYP
SNG
RUS
MLT
GR
Others
Certificates
Working/living conditions
Safety/fire appliances
Stability/structure
Ship/cargo operations
Equipment/machinery
Navigation/communication
Management
Figure 32.2 Type of deficiency detected by port state control authority, vessel age at
inspection and flag of registry.
Source: own calculations. Indian Ocean MoU 2002–2009.
Age at PSC inspection
0–4
5–9
10–14
15–19
20–24
25+
Flag of registry
Panama
Liberia
Hong Kong China
Bahamas
Cyprus
Singapore
Russian Federation
Malta
Greece
Others
Type of ship
Bulk carrier
General cargo/
multi-purpose ship
Oil tanker
Container ship
Chemical tanker
Vehicle carrier
Woodchip carrier
Explanatory variables
Ref
+0.008*
+0.025***
+0.039***
+0.047***
+0.045***
−0.004*
−0.005
+0.014***
−0.003
−0.002
+0.005
+0.046***
−0.002
−0.028***
Ref
+0.008**
+0.005
+0.004
+0.009
+0.002
+0.033***
+0.010
−0.001
−0.005
−0.012***
+0.001
+0.006
−0.009***
+0.005
+0.003
+0.003
Ref
−0.048***
−0.029***
−0.022***
−0.028***
−0.024***
−0.028***
−0.024***
+0.038***
+0.036***
+0.060***
+0.048***
+0.099***
+0.025***
+0.013
−0.000
+0.013
−0.001
+0.016*
+0.015*
+0.009
−0.049***
+0.011
+0.001
Ref
Ref
+0.038***
+0.041***
+0.046***
+0.051***
+0.037***
Working/living
Safety/fireconditions
fighting appliances
Ref
−0.014***
−0.015***
−0.020***
−0.027***
−0.021***
Certificates
Table 32.3 Probability of detecting a deficiency: marginal effects
−0.013
+0.038***
−0.013
−0.063***
+0.017
+0.049***
+0.034***
−0.001
−0.006
+0.003
−0.003
−0.004
+0.027***
+0.023*
−0.004
−0.025**
Ref
Ref
+0.033***
+0.093***
+0.122***
+0.134***
+0.138***
Stability/
structure
+0.014**
−0.025***
+0.003
+0.014
−0.023**
−0.033***
−0.025***
+0.002
−0.010*
−0.009*
−0.009
−0.003
−0.013**
+0.031**
−0.011**
+0.000
Ref
Ref
−0.014***
−0.030***
−0.044***
−0.049***
−0.054***
Ship/cargo
operations
−0.000
+0.018***
+0.007
−0.000
−0.024***
−0.002
+0.001
−0.002
−0.002
+0.007*
+0.005
−0.005
+0.003
−0.031***
−0.001
+0.009
Ref
Ref
+0.016***
+0.030***
+0.045***
+0.047***
+0.046***
Equipment/
machinery
−0.019**
-0.021**
−0.025***
−0.007
−0.031**
+0.003
+0.010
−0.001
+0.010
−0.006
−0.010
−0.012*
−0.014**
−0.023**
+0.001
+0.025**
Ref
Ref
−0.017***
−0.048***
−0.068***
−0.079***
−0.079***
Navigation/
communication
+0.020***
+0.007
+0.019***
+0.014**
+0.004
(Continued)
+0.013***
+0.014***
+0.006***
+0.003
+0.004
+0.005
+0.004
−0.000
−0.002
+0.004
+0.015***
Ref
Ref
−0.009***
−0.016***
−0.017***
−0.022***
−0.025***
Management
Refrigerated cargo −0.030***
carrier
Ro-Ro cargo ship
−0.008
Gas carrier
−0.024***
Others
Ref
Recognized organization
Nippon Kaiji
−0.019***
Kyokai
Lloyd’s Register
−0.011***
Det Norske
−0.012***
Veritas
American Bureau
+0.001
of Shipping
Germanischer
−0.009***
Lloyd
Bureau Veritas
−0.008***
Russian Maritime
−0.016***
Register
Certificates
(Continued)
Explanatory variables
Table 32.3
+0.033*
+0.011
+0.065***
Ref
−0.002
+0.006
+0.013*
+0.002
+0.006
−0.005
+0.003
−0.019***
+0.000
−0.001
Ref
+0.015***
+0.008**
+0.002
+0.010**
+0.006
+0.004
+0.028***
Working/living
Safety/fireconditions
fighting appliances
+0.011
+0.017
−0.016**
+0.002
+0.001
+0.006
+0.007
−0.022
+0.002
Ref
−0.016
Stability/
structure
+0.000
−0.013*
−0.004
−0.007
−0.005
−0.001
−0.001
−0.033***
−0.044***
Ref
+0.047***
Ship/cargo
operations
+0.011***
+0.027***
+0.015***
+0.008**
+0.021***
+0.019***
+0.005*
+0.010
+0.032*
Ref
+0.033***
Equipment/
machinery
−0.004
−0.029***
0.006
−0.007
−0.009
−0.008
+0.004
+0.035**
+0.006
Ref
−0.023*
Navigation/
communication
−0.004
−0.012***
−0.001
−0.006**
−0.005**
−0.009***
−0.007***
+0.004
+0.002
Ref
+0.017**
Management
−0.024***
−0.012
−0.037***
−0.030***
Ref
+0.068
−0.075***
−0.019***
−0.021***
−0.023***
Ref
+0.041
+0.094***
+0.017
+0.050***
+0.063***
Ref
+0.284
Ref
+0.015*
+0.008
−0.067***
−0.031**
−0.021*
0.017
Ref
+0.181
Ref
+0.021**
+0.044***
Stability/
structure
+0.043***
+0.069***
+0.012
+0.018
Ref
+0.124
Ref
−0.016***
−0.022***
Ship/cargo
operations
Probit regressions also include a set of year dummies.
Ref denotes the reference category.
For dummy variables, the marginal effect is for discrete change of dummy variable from 0 to 1.
The size of the sample is N = 121319 deficiencies.
Standard errors are clustered at the vessel level and significance levels are 1% (***),
5% (**) and
10% (*).
Source: own calculations. Indian Ocean MoU 2002–9.
Ref
+0.004
−0.021***
Ref
+0.037***
−0.025***
China
Classification
Society
Korean Register
of Shipping
Others
Inspecting authority
Australia
Iran
India
South Africa
Others
Estimated probability
Working/living
Safety/fireconditions
fighting appliances
Certificates
Explanatory variables
+0.006
+0.057***
+0.027***
−0.000
Ref
+0.051
Ref
+0.012**
+0.017***
Equipment/
machinery
+0.047***
−0.023*
+0.066***
+0.044**
Ref
+0.171
Ref
−0.007
−0.037***
Navigation/
communication
+0.011*
−0.011*
−0.022***
−0.029***
Ref
+0.039
Ref
−0.002
−0.015***
Management
666
P. CARIOU, F.-C. WOLFF AND M. Q. MEJIA, JR.
structure (instead of 18.8%), and 12.4% for
ship and cargo operations (instead of
12.6%). Results show the influence of age,
flag, vessel type, recognized organization,
inspecting authority and year (not reported).
The reference category of age (0–4-yearold vessels) exhibits higher probabilities
(negative signs for other age categories
reported) of certificates, ship and cargo
operations, navigation and communication,
and management-related deficiencies. Age
has a positive influence on the likelihood of
finding deficiencies related to working and
living conditions, safety and fire-fighting
appliances, stability and structure, and
equipment and machinery. The flag of registry plays a limited role. The probability of
a vessel having a deficiency for safety and
fire-fighting appliances is higher when this
vessel is a woodchip carrier (+9.9%), a gas
carrier (+6.5%) or a chemical carrier (+6%).
This result could be explained either by
inspectors making a greater effort when
inspecting vessels for which an incident
might have more severe consequences, or
by differences in the complexity of systems
aboard various vessels. Another illustration
involves refrigerated cargo carriers, for
which ship and cargo operations (+4.7%)
and equipment and machinery (+3.3%) are
essential to insure the continuity of the
“cold chain,” but which also induce more
complex equipment.
Reported recognized organizations
achieve better performance than smaller
societies gathered in the “others” category.
The probability of a vessel having deficiencies in safety and fire-fighting appliances is
higher when inspections are carried out in
Australia (+9.4%), South Africa (+6.3%) or
India (+5%), while opposite conclusions
hold for stability and structure in Australia
(−6.7%). This country-specific effect is puz-
zling, though it could simply suggest that
port state control authorities have different
priorities or that the characteristics of
vessels calling at Australian ports are different (Cariou and Wolff 2010).
32.5 Recurrent Deficiencies and
State Dependence Effects
Earlier studies did not pay too much attention to potential state dependence effects in
a vessel condition (Cariou, Mejia and Wolff
2008a being an exception). In this section,
we seek to estimate how results of past
inspections may influence the probability of
a given deficiency in t being detected. The
permanent effect for a vessel is captured by
a dummy variable equal to 1 when the same
deficiency is reported in t-1 and in t (and 0
otherwise). Therefore, vessels inspected
only once were dropped, reducing the
sample from 42,071 to 28,330 vessels.
Results on transitional states between
two successive inspections (t-1 and t) are
presented in Figure 32.3. For a vessel
without deficiency in t, two initial states
exist in t-1: either no deficiency (Nt = Nt-1),
or more (Nt > Nt-1). Now, for a vessel with
deficiencies in t, three possibilities exist in
t-1: fewer (Nt < Nt-1), the same (Nt = Nt-1),
or more (Nt > Nt-1) deficiencies. Vessels
without deficiency in t were without deficiencies in t-1 for 55% of them, while for
vessels with deficiencies in t, more than 60%
had less, 10% the same number and 30%
more in t-1. These results are evidence of
improvements in vessels’ condition over
time.
We next perform an analysis by categories of deficiencies (see Figure 32.4). We
again find evidence of a state dependence
General cargo/multi-purpose ship
60
Proportion (in %)
40
30
50
20
Proportion (in %)
40
30
50
10
20
No deficiency in t-1
Nt<Nt-1
Deficiencies in t-1
Nt=Nt-1
0
0
0
10
10
20
Proportion (in %)
30
40
50
60
60
70
70
Bulk carrier
70
All vessels
No deficiency in t-1
Nt>Nt-1
Nt<Nt-1
Deficiencies in t-1
Nt=Nt-1
60
Proportion (in %)
30
40
50
20
10
Nt<Nt-1
Deficiencies in t-1
Nt=Nt-1
70
Proportion (in %)
30
40
50
20
10
Nt<Nt-1
Deficiencies in t-1
Nt=Nt-1
Nt>Nt-1
Deficiencies in t-1
Nt=Nt-1
Nt>Nt-1
70
60
70
Proportion (in %)
50
30
40
20
Proportion (in %)
40
30
50
10
20
0
10
0
Deficiencies in t-1
Nt=Nt-1
Nt<Nt-1
Other vessels
60
60
Proportion (in %)
30
50
40
20
10
0
Nt<Nt-1
No deficiency in t-1
Nt>Nt-1
Gas carrier
70
Ro-Ro cargo ship
No deficiency in t-1
Nt>Nt-1
0
No deficiency in t-1
Nt>Nt-1
Deficiencies in t-1
Nt=Nt-1
60
70
Proportion (in %)
30
40
50
20
10
0
Deficiencies in t-1
Nt=Nt-1
Nt<Nt-1
Refrigerated cargo carrier
60
60
Proportion (in %)
30
40
50
20
10
0
Nt<Nt-1
No deficiency in t-1
Nt>Nt-1
Woodchip carrier
70
Vehicle carrier
No deficiency in t-1
Nt>Nt-1
0
No deficiency in t-1
Nt>Nt-1
Deficiencies in t-1
Nt=Nt-1
70
70
Proportion (in %)
30
40
50
20
10
0
Nt<Nt-1
Nt<Nt-1
Chemical tanker
60
60
Proportion (in %)
40
50
30
20
10
0
No deficiency in t-1
No deficiency in t-1
Nt>Nt-1
Container ship
70
Oil tanker
Deficiencies in t-1
Nt=Nt-1
No deficiency in t-1
Nt<Nt-1
Deficiencies in t-1
Nt=Nt-1
Nt>Nt-1
No deficiency in t-1
Nt<Nt-1
Deficiencies in t-1
Nt=Nt-1
Figure 32.3 Change in number of deficiencies detected between two successive
inspections, by type of vessel.
Source: own calculations. Indian Ocean MoU 2002–2009.
Nt>Nt-1
80
70
Proportion (in %)
50
60
30
40
20
10
0
80
70
Proportion (in %)
50
60
30
40
Only in t-1
Ship/cargo operations
Only in t
Both in t-1 and t
Never
Certificates
Both in t-1 and t
Only in t-1
Never
Only in t
Equipment/machinery
Only in t
Never
Working/living conditions
Only in t-1
Never
Only in t
Navigation/communication
Only in t
Both in t-1 and t
Never
Safety/fire appliances
Only in t-1
Only in t-1
Both in t-1 and t
Only in t-1
Both in t-1 and t
Only in t-1
Never
Only in t-1
Both in t-1 and t
Only in t
Management
Only in t
Both in t-1 and t
Never
Stability/structure
Figure 32.4 Change in number of deficiencies detected between two successive inspections, by type of deficiency.
Source: own calculations. Indian Ocean MoU 2002–2009.
Only in t
Both in t-1 and t
Never
10
0
20
80
70
Proportion (in %)
40
50
60
30
20
10
0
70
10
0
20
Proportion (in %)
50
60
30
40
80
80
70
Proportion (in %)
40
60
30
50
20
10
0
80
70
Proportion (in %)
30
40
50
60
10
0
20
80
70
Proportion (in %)
30
40
50
60
20
10
0
80
70
Proportion (in %)
30
50
60
40
20
10
0
PORT STATE CONTROL INSPECTION DEFICIENCIES
effect. Vessels never record any deficiency
related to certificates in more than 80% of
cases. Similar conclusions hold for working
and living conditions, equipment and
machinery, and management. We find more
contrasted patterns for safety and firefighting appliances and for navigation and
communication. The proportion of vessels
without deficiency in both t-1 and t is
around 50%, while those with deficiencies
in both t-1 and t is 10%. To further understand the transition from one state to
another, we estimated for the eight categories of deficiencies several Probit regressions on the probability of a vessel having a
specific deficiency, including a lagged value
of past deficiencies. Marginal effects are
reported in Table 32.4.
Estimates confirm the existence of a
strong state dependence over time, detected
by the lagged value on deficiency.6 This persistence effect is more likely in deficiencies
in working and living conditions (+16.4%),
safety and fire-fighting appliances (+16.9%),
stability and structure (+15.7%), and ship
and cargo operations (+15.6%), and is not
significant for administrative deficiencies
such as in certificates or management. This
could be explained by the presence of more
volatility in these deficiencies, which can be
relatively easily corrected over time. As
expected, older vessels have a higher probability of recording deficiencies related to
seaworthiness in general, with +40.4% for
stability and structure and +30.6% for equipment and machinery when vessels are more
than 25 years old. These latter are also more
likely to keep deficiencies over time in certificates (+6.8%), safety and fire-fighting
appliances (+11.1%), and navigation and
communication (+13.8%). Such deficiencies
are indeed expensive to correct and it might
not be economical to do so when vessels are
669
reaching the end of their economic life.
Finally, for bulk carriers, the negative coefficients of Deft−1 for safety and fire-fighting
appliances (−7.6%), stability and structure
(−7.3%), and ship/cargo operations (−5.9%)
suggest that their condition is likely to
improve over time.
32.6
Summary
Studies on the PSC regime and its use in
identifying substandard vessels reach a consensus on factors influencing the probability of a vessel being detained during an
inspection. However, several issues remain
unresolved. The weight to be assigned to
these factors and the increased harmonization in controls amongst various PSC
regional MoUs are some of them. This
chapter provides an original contribution
on other potential issues: factors influencing the likelihood of detecting a given deficiency and the existence of persistence
effects over time. If factors influencing the
probability of a vessel with a given deficiency being detected during a control are
similar to those of a vessel being detained
– with a strong influence exerted by age,
type, classification society, flag etc. – estimates suggest that a state dependence effect
exists and changes with the type of deficiency and vessel. Therefore, to set in
advance a fixed period of time between two
inspections, as in the inspection regime of
Paris MoU, regardless of the type of vessel
and deficiency, might not be relevant.
Furthermore, when carrying out inspection
campaigns focusing on one specific deficiency, PSC regional MoUs should probably
consider this persistence effect, because
some deficiencies might not be persistent
Existence of the same deficiency
Def t-1 (lagged value)
Age at inspection
0–4
5–9
10–14
15–19
20–24
25+
Age at inspection * Def t-1
5–9 * Def t-1
10–14 * Def t-1
15–19 * Def t-1
20–24 * Def t-1
25+ * Def t-1
Type of ship
Bulk carrier
General cargo/multi-purpose
ship
Oil tanker
Container ship
Chemical tanker
Explanatory variables
+0.164***
Ref
+0.061***
+0.115***
+0.157***
+0.224***
+0.282***
−0.022
−0.032
−0.007
−0.039*
−0.027
+0.047***
+0.050***
−0.024**
−0.002
+0.042**
Ref
+0.005
+0.020***
+0.042***
+0.082***
+0.130***
+0.032
+0.029
+0.032
+0.027
+0.068**
−0.023***
+0.027***
+0.003
−0.019**
−0.001
Working/
living
conditions
+0.061*
Certificates
−0.036*
+0.003
+0.069***
+0.106***
+0.061***
+0.023
+0.019
−0.001
+0.009
+0.111***
Ref
+0.115***
+0.176***
+0.233***
+0.272***
+0.263***
+0.169***
Safety/
fire-fighting
appliances
−0.016
−0.003
+0.063**
+0.136***
+0.119***
−0.002
+0.004
−0.000
+0.005
+0.064*
Ref
+0.118***
+0.224***
+0.307***
+0.358***
+0.404***
+0.157***
Stability/
structure
Table 32.4 Probability of transition in deficiencies from t-1 to t : marginal effects
−0.045***
−0.029*
+0.033
+0.031**
+0.036**
−0.018
−0.009
−0.009
−0.030
+0.023
Ref
+0.051***
+0.075***
+0.100***
+0.138***
+0.181***
+0.156***
Ship/cargo
operations
−0.001
+0.035***
+0.058***
+0.036***
+0.055***
−0.031
−0.041*
−0.031
−0.034
−0.018
Ref
+0.057***
+0.105***
+0.155***
+0.220***
+0.306***
+0.111*
Equipment/
machinery
−0.080***
−0.028
+0.003
+0.070***
+0.057***
+0.034
+0.042*
+0.021
+0.004
+0.135***
Ref
+0.039***
+0.064***
+0.090***
+0.124***
+0.133***
+0.072**
Navigation/
communication
−0.024**
+0.000
+0.010
+0.039***
+0.010
−0.008
0.022
−0.023
−0.010
−0.010
Ref
+0.022***
+0.021***
+0.048***
+0.040***
+0.061***
+0.061
Management
+0.004
+0.014
−0.049**
+0.014
−0.072***
Ref
−0.036*
+0.002
+0.029
−0.008
−0.044
−0.050
−0.006
−0.058
+0.019
+0.012
+0.129
−0.045***
−0.033***
−0.038***
+0.022
−0.034***
Ref
−0.023*
−0.001
+0.025
−0.021
+0.007
−0.014
Vehicle carrier
Woodchip carrier
Refrigerated cargo carrier
Ro-Ro cargo ship
Gas carrier
Others
Type of ship * Def t-1
Bulk carrier* Def t-1
General cargo* Def t-1
Oil tanker* Def t-1
Container ship* Def t-1
Chemical tanker* Def t-1
Vehicle carrier* Def t-1
Woodchip carrier* Def t-1
Refrigerated cargo * Def t-1
Ro-Ro cargo ship* Def t-1
Gas carrier* Def t-1
Estimated probability
−0.076***
−0.034
−0.028
+0.016
+0.011
−0.083**
−0.064
−0.132**
−0.015
−0.069
+0.360
+0.003
+0.101***
−0.019
−0.043
−0.083**
Ref
Safety/
fire-fighting
appliances
−0.073***
−0.002
+0.039
−0.016
+0.039
−0.000
−0.129***
−0.062
+0.096
+0.044
+0.245
−0.100***
+0.030
+0.014
−0.054*
−0.076**
Ref
Stability/
structure
−0.059***
−0.011
+0.067*
−0.064**
−0.037
−0.055
−0.093**
−0.013
+0.031
−0.062
+0.214
−0.023
−0.011
+0.021
−0.026
−0.111***
Ref
Ship/cargo
operations
Probit regressions also include a set of year dummies.
Ref denotes the reference category.
For dummy variables, the marginal effect is for discrete change of dummy variable from 0 to 1.
The sample is N = 28330 vessels subject to repeated inspections.
Standard errors are clustered at the vessel level and significance levels are 1% (***),
5% (**) and
10% (*).
Source: own calculations. Indian Ocean MoU 2002–9.
+0.071
+0.019
+0.058
Working/
living
conditions
Certificates
Explanatory variables
+0.011
+0.058*
+0.137***
+0.008
+0.040
−0.081***
−0.004
+0.027
+0.198**
+0.052
+0.092
−0.016
−0.032**
+0.077***
+0.002
−0.012
Ref
Equipment/
machinery
−0.022
+0.014
+0.095**
−0.021
+0.026
+0.008
+0.062
+0.106
+0.143**
−0.005
+0.269
−0.030
−0.048*
−0.049
−0.043
−0.095***
Ref
Navigation/
communication
−0.003
+0.047
+0.065
+0.046
+0.020
−0.089***
+0.017
+0.042
−0.017
+0.088
+0.103
+0.008
−0.012
−0.029
−0.021
−0.069***
Ref
Management
672
P. CARIOU, F.-C. WOLFF AND M. Q. MEJIA, JR.
over time. To be conclusive, however, these
preliminary findings should be supported
by further analysis on larger inspection data
sets from other PSC regional MoUs.
Notes
1
It is estimated that 40% of the world’s offshore oil production originates from countries bordering the Indian Ocean.
2 The nine MoUs are: Paris MoU – Europe
and the North Atlantic; Tokyo MoU – Asia
and the Pacific; Acuerdo de Viña del Mar –
Latin America; Caribbean MoU – Caribbean
Sea region; Abuja MoU – West and Central
Africa; Black Sea MoU – Black Sea region;
Mediterranean MoU – Mediterranean Sea
region; Indian Ocean MoU – Indian Ocean
region; Gulf Cooperation Council (GCC)
MoU – Arab States of the Gulf.
3 The final choice still remains in the hand of
sovereign states, which may have different
priorities.
4 In June 2011, the 18 countries were: Australia,
Bangladesh, Djibouti, Eritrea, Ethiopia
(observer), India, Iran, Kenya, Maldives,
Mauritius, Mozambique, Myanmar, Oman,
Seychelles, South Africa, Sri Lanka, Sudan,
Tanzania and Yemen. For more information
see www.iomou.org/.
5 Each deficiency is accounted as one observation in our sample: 121,319 deficiencies/
observations for 42.071 inspections undertaken from 2002 to 2009. Standard errors are
clustered at the vessel level when the regressions are estimated.
6 The lagged value associated is introduced
exogenously in regressions.
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