June 3-5, IFSPA 2013, Hong Kong

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1 Lixian Fan, School of Management, Shanghai University, P.R. China Meifeng Luo, Dept. of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong Jingbo Yin, Dept. of International Shipping and Transport Management, Shanghai Jiaotong University, P.R. China June 3-5, IFSPA 2013, Hong Kong

2 Whether to fly a foreign flag? How to determine the priority for PSC inspection? 21% (1970s) to 71% (2012) Open Registers (FOC) Flag State Control Port State Control Maritime safety and environment

3 » Checking the statistical relationship between the flag-out behavior and ship age, a policy maker found a positive significant correlation. To reduce the flag-out rate, the policy maker setup a preferential tax policy to attract the old ships to the national flag.» The possibility of be inspected by PSC has significant positive correlation with the GDP per capita of the ship operator. Conclusion: ships from the rich countries are inspected more often in PSC?

4 » Flag selection behavior Bergantino & Marlow (1998): survey and rank the important factors, quantify their contributions to flag-out using binary choice model based on ship type, age, trade, and differences in salary, insurance, running cost, repair and maintenance cost. Hoffmann at al. (2005), binary probit model on the attributes of vessel, operator s country, builder country, classification society. Luo et al (2013) used nested logit model, on both whether flag out, which flag to choose. PSC inspection rate is one of the explanatory variable.» PSC inspection (empirical analysis) It can reduce 63% deficiencies (Carious et al. 2008), major factor of detention are age, classification society, and the place of inspection (Carious et al. 2009) ; low standard ships have more frequent shift for flags and classes. (Carious & Wolff, 2011). Knapp & Franses: PSC region has differen detention probility, need coordination (2007a, 2008); contribution of PSC inspection on casulty (2007b).

5 » FF dependent dummy variable for flying a foreign flag» Explanatory variables BUILTOPER: dummy whether the ship is built in ship operator s country. 38% FF if =1, =0, 60% FF. LDWT: log of ship size; 48%<10,000DWT (38%FF); otherwise, 68%FF REAGE: The age when the ship FF. If not, it is 0 (register when it is new) Ship type dummies: BULK, TANKER, CONTAINER, OCARGO Class: 10 dummy variables, each for one member in IACS TOPMARTAX: average income tax of the ship operator country for the highest income levels LGDPCAP: log of the GDP per capita of the ship operator country. Dummies for the location of the ship operator s country: AFRICA, ASIA, EUROPE, AMERICA, OCEANIA DFSPERFORM: difference in flag state performance between operator s and flag s DLOSSRATE, DCOMPANY, DCREW, Difference variables in loss rate, company share requirement, and crew requirement. INSPECT

6 » Dependent variable: INSPECT: Annual average inspection times per ship. Data: Tokyo MOU from ; Paris MOU from 2005 to 2008; India MOU from » Explanatory variables LDWT, AGE, BULK, TANKER, CONTAINER LGDPCAP, AFRICA, ASIA, EUROPE, AMERICA, FF Age: The age of the ship at 2011, an index for the age of the ship during study period.» Data Sources 2009 PC Register of ships from Lloyd s Fairplay, selected 48,477 ships >400GT. Annual Report from Economic Freedom of the World, BIMCO s Shipping Industry Flag State Performance, World Casualty Statistics of Lloyd s Fairplay, and existing literature.

7 » Three stage least square (3SLS) method is used to estimate the two statistical models simultaneously.» Two models also are estimated separately, to check the changes after taking into the endogeneity.» Comparing two results, we can find the over- or underestimation.

8 Estimate t Value Approx Pr> t Estimate Wald Chi-Square Pr > ChiSq INTERCEPT < <.0001 BUILTOPER < <.0001 LDWT < <.0001 REAGE < <.0001 BULK <.0001 TANKER < <.0001 CONTAINER < Taking into account the endogeneity, older ships are less likely to flag out. Withoug taking endogeneity TOPMARTAX < <.0001 LGDPCAP <.0001 into account, older ships <.0001 flag AFRICA <.0001 out more <.0001 ASIA EUROPE <.0001 AMERICA DFSPERFORM < <.0001 DLOSSRATE It is the high PSC inspection DCOMPANY <.0001 DCREW rate 1.58 that increased the CNIK probability of older ships to <.0001 CGEL flag out <.0001 CLLR < CBUV <.0001 CDNV <.0001 CABS <.0001 CCCS < <.0001 CRUS <.0001 CSKR < <.0001 CREI < <.0001 INSPECT < <.0001

9 Estimate t Value Approx Pr> t Estimate Wald Chi-Square Pr > ChiSq INTERCEPT < <.0001 BUILTOPER < <.0001 LDWT < <.0001 REAGE < <.0001 BULK <.0001 TANKER < <.0001 CONTAINER < TOPMARTAX < <.0001 LGDPCAP < <.0001 AFRICA < <.0001 Actually, bulk and tanker are more likely to flag out. Statistically, bulk and tanker ASIA EUROPE are less likely to flag out <.0001 AMERICA DFSPERFORM < <.0001 DLOSSRATE DCOMPANY <.0001 Under-estimate the probability DCREW CNIK of 2.02 flag out for ship types <.0001 CGEL <.0001 CLLR < CBUV <.0001 CDNV <.0001 CABS <.0001 CCCS < <.0001 CRUS <.0001 CSKR < <.0001 CREI < <.0001 INSPECT < <.0001

10 Estimate t Value Approx Pr> t Estimate Wald Chi-Square Pr > ChiSq INTERCEPT < <.0001 BUILTOPER < <.0001 LDWT < <.0001 REAGE < <.0001 BULK <.0001 TANKER < <.0001 CONTAINER < TOPMARTAX < <.0001 LGDPCAP < <.0001 AFRICA < <.0001 ASIA EUROPE <.0001 AMERICA DFSPERFORM < <.0001 DLOSSRATE Right hand similar, left hand not DCOMPANY <.0001 DCREW significant Asia and Europe are not CNIK significantly different from Oceania <.0001 CGEL <.0001 CLLR < CBUV <.0001 CDNV <.0001 CABS <.0001 CCCS < <.0001 CRUS <.0001 CSKR < <.0001 CREI < <.0001 INSPECT < <.0001

11 Estimate t Value Approx Pr> t Estimate Wald Chi-Square Pr > ChiSq INTERCEPT < <.0001 BUILTOPER < <.0001 LDWT < <.0001 REAGE < <.0001 BULK <.0001 TANKER < <.0001 CONTAINER < TOPMARTAX < <.0001 LGDPCAP < <.0001 AFRICA < <.0001 ASIA EUROPE <.0001 AMERICA DFSPERFORM < <.0001 DLOSSRATE DCOMPANY <.0001 DCREW CNIK <.0001 CGEL <.0001 CLLR < CBUV <.0001 CDNV <.0001 CABS <.0001 Difference variables are less CCCS < <.0001 significant in flag out decision. CRUS <.0001 CSKR < <.0001 CREI < <.0001 INSPECT < <.0001

12 Estimate t Value Approx Pr> t Estimate Wald Chi-Square Pr > ChiSq INTERCEPT < <.0001 BUILTOPER < <.0001 LDWT < <.0001 REAGE < <.0001 BULK <.0001 members are actually less TANKER < <.0001 CONTAINER likely to <.0001 flag out TOPMARTAX < <.0001 LGDPCAP < <.0001 AFRICA < <.0001 Actually, most of them are negative. Ships classified by IACS Statistically, most of them are positive=>good quality ships ASIA EUROPE <.0001 AMERICA are more likely to flag out? DFSPERFORM < <.0001 DLOSSRATE DCOMPANY <.0001 DCREW CNIK <.0001 CGEL <.0001 CLLR < CBUV <.0001 CDNV <.0001 CABS <.0001 CCCS < <.0001 CRUS <.0001 CSKR < <.0001 CREI < <.0001 INSPECT < <.0001

13 Estimate t Value Approx Pr> t Estimate Wald Chi-Square Pr > ChiSq INTERCEPT < <.0001 BUILTOPER < <.0001 LDWT < <.0001 REAGE < <.0001 BULK <.0001 TANKER < <.0001 CONTAINER < TOPMARTAX < <.0001 LGDPCAP < <.0001 AFRICA < <.0001 ASIA EUROPE <.0001 AMERICA DFSPERFORM < <.0001 DLOSSRATE DCOMPANY <.0001 DCREW CNIK <.0001 CGEL <.0001 CLLR < Left >> right, under-estimate CBUV <.0001 the role of PSC inspection on CDNV <.0001 CABS flag out <.0001 CCCS < <.0001 CRUS <.0001 CSKR < <.0001 CREI < <.0001 INSPECT < <.0001

14 Estimate t Value Approx Pr> t Estimate t Value Pr> t INTERCEPT < <.0001 LDWT < <.0001 AGE < <.0001 Actually, BULK large ships do not Statistically, large <.0001 ships have have TANKER high priority in PSC <.0001 higher PSC inspection <.0001 rate. inspection. CONTAINER < <.0001 LGDPCAP < <.0001 It is the high probability of flag out AFRICA < <.0001 for large ships that increased the ASIA statistical relationship between PSC EUROPE inspection <.0001 and ship size AMERICA < <.0001 FF < <.0001

15 Estimate t Value Approx Pr> t Estimate t Value Pr> t INTERCEPT < <.0001 LDWT < <.0001 AGE < <.0001 BULK <.0001 TANKER < <.0001 CONTAINER < <.0001 LGDPCAP <.0001 Statistically, OCARGO <.0001 type Actually, AFRICA bulk ships is higher <.0001 has the highest inspection <.0001 than ASIA OCARGO types rate EUROPE < AMERICA < <.0001 FF < <.0001 The PSC inspection is the highest in bulk, not the OCARGO type

16 Estimate t Value Approx Pr> t Estimate t Value Pr> t INTERCEPT < <.0001 LDWT < <.0001 AGE < <.0001 Actually, high income Statistically, high income BULK <.0001 countries have lower PSC countries have the highest TANKER < <.0001 inspection priority. inspection rate. CONTAINER < <.0001 LGDPCAP < <.0001 AFRICA < <.0001 ASIA The high income countries have more EUROPE < incentive to flag out, which AMERICA contributes to the <.0001 positive correlation <.0001 FF < <.0001 to the PSC inspection rate.

17 Estimate t Value Approx Pr> t Estimate t Value Pr> t INTERCEPT < <.0001 LDWT < <.0001 Without considering about the mutual AGE < <.0001 effects, the mere statistical BULK relationship 3.76 under-estimates the <.0001 TANKER importance of FF on <.0001 PSC inspection <.0001 CONTAINER < <.0001 LGDPCAP < <.0001 Actually, AFRICA FF has much higher <.0001 Statistically, FF do <.0001 have weights ASIA in setting PSC positive correlation with PSC inspection EUROPE priority <.0001 inspection rate AMERICA < <.0001 FF < <.0001

18 » We estimated the contribution of different factors to flag out and PSC inspection rate beyond mere statistical correlation. Identified biases (over- or under-estimation) and wrong signs.» On Flag-out behavior PSC inspection rate have much larger contribution to flag out than suggest by statistical correlation. High PSC inspection on old ships=>flag out Good ship class does not drive ship out. Low PSC inspection rate on tanker and containerships lead to the underestimate on their probability to flag out.» On PSC inspection Revealed sign difference on ship size, owner country s per capital GDP. Under-estimated the impact of a foreign flag on setting inspection priority.

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