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7/28/2019 Dry Bulk Contracts Paper 9-8-10
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Microeconomic Determinants of Dry Bulk Shipping Freight
Rates and Contract Times
Amir H. Alizadeh
Cass Business School
City University
London EC1Y 8TZ
United [email protected]
Wayne K. Talley
College of Business and Public Administration
Old Dominion University
Norfolk, Virginia 23529
ABSTRACT
Th i f thi i t l l ifi d d t i t f hi i f i ht t i th
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]7/28/2019 Dry Bulk Contracts Paper 9-8-10
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The aim of this paper is to analyze vessel specific and voyage determinants of shipping freight rates in the
1. Introduction
International sea transportation has been an instrumental factor in world economic activity andinternational trade. Total seaborne trade in commodities reached an estimated 8,226 million metric tonnes
(mmt) in 2008 consisting of 3,060 mmt of dry bulk commodities, 3,052 mmt of liquid bulk
commodities, and 2,114 mmt of other dry cargo and manufactured goods.1 The dry bulk shipping market
is by far the largest sector of the world s shipping market in terms of cargo volume and weight. In 2008
the dry bulk shipping fleet transported 843 mmt of iron ore, 794 mmt of coking and thermal coal, 314
mmt of grains, 119 mmt of bauxite, alumina and phosphate rock, and 990 mmt of minor dry bulk
commodities, e.g., cement, sugar, and fertilizers. At the end of 2008 the cargo carrying capacity of theworld dry bulk shipping fleet of 418 million metric tonnes was 34.7% of the total world shipping fleet,
and the number of dry bulk ships exceeded 7,000.2 Therefore, it is not surprising that a large number of
studies have investigated the formation and behavior of dry bulk freight (charter) rates, chartering
decisions and policies, transportation strategies, and fleet deployments and operations of the dry bulk
shipping industry(See section 2).
The existence of different types of ship chartering contracts in the bulk shipping industry provide
charterers greater flexibility to secure their sea transportation requirements, while minimizing their costs.The contracts vary depending on the terms of agreement and the type of service that shipowners agree to
provide to charterers. Broadly speaking, chartering contracts can be classified into five different types:
Voyage Charter (VC), Consecutive Voyage or Contracts of Affreightment (CoA), Trip Charter (TC),
Time or Period Charter (PC), and Bareboat Charter (BC) contracts. The main differences among these
contracts are the: duration of the contract, method of freight rate calculation, cost allocations and
commercial and operational responsibilities3.
Freight rates in the bulk shipping industry fluctuate considerably in the short run (Kavussanos, 1996a).
Such fluctuations affect the formation of shipping policies, transactions and contracts and ship owners
and charterers cash flows and costs (Brown et al. 1987 and Laulajainen, 2007). Hypothesized
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window, then the charterer has the option to cancel the contract, and potentially claim compensations.
Thus, the time period between the fixture date and thelayday is the laycan period.
Once the loading or lifting day (layday) of the cargo has been determined, the trader (vessel charterer)
will enter the market to find and charter the most suitable ship for transportation of the cargo from the
loading port to the destination port. Depending on the nature of the trade, the layday may occur anytime
from one day to couple of months after the fixture date. Hence, assuming vessels are available in the
market at all time and at a constant flow, the trader has the option to enter into the freight market and hire
a vessel anytime until the very last minute (as long as it is practical) before the layday. Therefore, it is the
traders decision for all practical purposes as to when to enter the market and charter (or hire) a ship. For
instance, if the conditions are not favorable and there is enough time before the layday, the trader may
wait and not inform the shipbroker about the need for a ship. The charterers decision of when to charter a
ship i.e., the fixture date, is dependent on such market conditions as current and expected freight (charter)
rates, the volatility of freight rates, and the cost to be incurred of not being able to find a ship to charter if
the decision to hire a ship is delayed.
Although numerous macroeconomic studies on the formation and behavior of shipping freight
(charter) rates exist, there has been little investigation of microeconomic determinants, such specificvessel and voyage determinants, of shipping freight (charter) rates. Moreover, there is no study in the
literature that investigates determinants of the laycan period in shipping contracts. This paper attempts to
fill this gap not only with respect to shipping freight (charter) rates but also with respect to the laycan
period of ship charter contracts. In addition, the paper analysis, for the first time the relationship between
freight rate and the laycan period of shipping contracts.
The purpose of this paper is threefold: (1) investigate vessel and voyage determinants (e.g., vessel age,hull type, deadweight size of the fixture and route) of individual dry bulk shipping freight (charter) rates;
(2) investigate vessel and voyage determinants of the individual delivery times of chartered ships (laycan
periods); and (3) investigate the relationship between dry bulk shipping freight (charter) rates and laycan
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2. Review of literature
Like any market, dry bulk freight (charter) markets are characterized by the interaction of supply anddemandfor this market the supply and demand for charter dry bulk ships (Stradenes 1984, Beenstock
and Vergottis 1993, and Tsolakis 2005). The demand for charter dry bulk ships is a derived demand
which depends on the economics of the commodity markets and international seaborne trade, world
economic activity such as imports and consumption of energy commodities (see Stopford 2009). The
supply of charter dry bulk ships, on the other hand, depends on the size of the shipping fleet, the fleets
tonnage that is available for trading, shipbuilding activities, bunker fuel prices, the scrapping rate of the
fleet and the productivity of the shipping fleet at any point in time. Heretofore, studies analyzing,
modeling and forecasting freight (charter) rates have done so from a macroeconomic perspective.
Studies by Hawdon (1978), Strandenes (1984), and Beenstock and Vergottis (1989, 1993), among
others, argue that the shipping freight (charter) rate is determined through the interaction between supply
and demand for sea transportation. They find that world economic activity, the growth in industrial
production, seaborne trade in commodities, oil prices, availability of tonnage or stock of fleet, new vessel
buildings on order, and shipbuilding deliveries and scrapping rates determine freight rates for sea
transportation. More recent studies by Dikos et al. (2006) and Randers and Gluke (2007) also usemacroeconomic variables in a system dynamic setting to model and forecast freight (charter) rates.
Other studies have examined the time series properties of shipping freight (charter) rates such as their
dependence on past values; further, they use univariate or multivariate time series models to capture the
dynamics of freight rates. These models are then used to forecast shipping freight (charter) rates and their
volatilities (Veenstra and Franses, 1997, Kavussanos and Alizadeh, 2002, Adland and Cullinane, 2005
and 2006, Lyridis et al., 2004, and Batchelor et al., 2007). Moreover, studies such as Kavussanos and
Alizadeh (2001) investigate the seasonal behavior of dry bulk shipping freight (charter) rates and explainhow seasonal production, trade and transportation of commodities impact ship charter rates. These studies
utilize macroeconomic economic data in an attempt to capture the dynamics and fluctuations in shipping
f i ht ( h t ) t h th i f i di ti hi i f i ht t h b d
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3. Methodology
The models dependent variable for investigating determinants of shipping freight (charter) rates is
defined as the difference between an individual shipping freight rate and the value of the Baltic Index
freight rate for that specific class of vessel on the fixture date. Since Capesize and Panamax fixtures are
considered, the Baltic Capesize Average Four Trip-Charter and the Baltic Panamax Average Four Trip-
Charter Rates are used. These freight indices are used by the industry to monitor the overall shipping
market movements, to trade and settle freight derivatives4, and to benchmark operating performance of a
vessel or a fleet. Therefore, it can be argued that the Baltic Average 4TC Rates reflect the movement of
the ship freight charter market with respect to changes in macroeconomic factors. Consequently, the
difference between the freight rate for a particular charter contract and the Baltic 4TC Rates, at any point
in time, should reflect the factors specific to the vessel or the voyage under which the vessel is contracted
to operate. In other words, the difference between a single fixture rate and the benchmark index rate
should be a function of the route over which the vessel operates,RT, the laycan period of the fixture,LC,
the size of the vessel, SZ, the age of the ship, AG, and the volatility in the market, VOL. Thus, the
determinants of freight rates for dry bulk trip charter contracts are investigated using the followinghypothesized freight (charter) rate regression model:
(1)
wherettiti bfifrdfr ,, is the difference between the log of fixture rate for contract i at time t, fri,t,, and
the log of Baltic benchmark freight rate (Baltic Average 4TC Rates) at time t, bfit=ln(B4TCt). Thevariable, age-squared, appears in equation (1) since the operational performance, technological efficiency
and quality standard of ships decline, as they get older, and consequently their hire rate is assumed to be a
nonlinear function of age. The dummy variables for individual routes, RTi j, also appear in equation (1).
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rates and laycan periods can be investigated by using the Hausman (1978) test for simultaneity. The
Hausman test is performed using the two step method of Davidson and Mackinnon (1993), i.e., by first
estimating freight equation (1) and then using the estimated residuals as observations for the explanatoryvariable )( iv in the laycan equation. The significance of the coefficient of residuals of the freight
equation in the laycan equation is an indication that there is a simultaneous relationship between the
laycan period and freight rate of shipping contracts. In addition, the test can be performed by first
estimating laycan equation (2) and then using the estimated residuals as observations for the explanatory
variable )( i in the freight equation. Again, significance of the coefficient of residuals of the laycan
equation in the freight model can be evidence of the existence of a simultaneous relationship between the
two variables.
If a simultaneous interrelationship exists between the freight rate and the laycan period of a shipping
contract, then equations (1) and (2) must be re-specified to reflect this simultaneous interrelationship
i.e., by including LCi,t as an explanatory variable in the dfri,t equation (1) and including dfri,t as an
explanatory variable in theLCi,tequation (2). Therefore, we define the following system:
(3)
where i is the vector of residuals which follows a bivariate distribution with zero mean and variance-covariance matrix, .
When specifying a system of simultaneous equations, there are two main points that should beconsidered. The first issue is the problem of identification, which arises when parameters of the structural
equation cannot be deduced using the parameters of the reduced form model. Therefore, for a system of
simultaneous equations to be identified both the order and the rank conditions should be satisfied 5 The
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4. Description of Data
The worlds dry bulkfleet of ships is broadly differentiated into five size classes: Handysize (20,000
to 35,000 dwt), Handymax (35,000 to 45,000 dwt), Supramax (45,000 to 55,000 dwt), Panamax (60,000
to 80,000 dwt) and Capesize (more than 80,000 dwt, normally 120,000 to 180,000 dwt).6 Capesize bulk
carriers are almost exclusively involved in transportation of major dry bulk commodities, i.e., iron ore and
coal, between exporting and importing regions. Panamax vessels are also involved in transportation of
iron ore and coal in addition to grain. Midsize dry bulk carriers, using Supramax and Handymax vessels,
are involved in transportation of grain, bauxite and alumina, and phosphate rock, in addition to minor
bulk commodities. Handysize and smaller bulk ships are usually equipped with cargo handling gears
(cranes) and transport small-shipment-size bulk commodities between ports with relatively shallow water
depths.
The data for this study were collected from Clarksons Research Services Ltd website, Shipping
Intelligence Network (SIN), and comprise information on Panamax and Capsize trip-charter fixtures over
the period January 2003 to July 2009. The larger-sized Panamax and Capsize ships were selected for thestudy, since the trading routes for these ships are distinct and their trading activity is concentrated in a
number of major shipping routes thereby simplifying the empirical analysis of this paper. The trading
routes for smaller bulk ships are very scattered, since the market for these vessels are quite fragmented,
e.g., their trade routes utilize almost any combination of seaports. Around 45% of spot market activities in
the Capsize sector are trip-charter with the remaining contracts being voyage charter contracts. In the
Panamax sector, more than 90% of the spot fixtures are based on trip-charter contracts. The data include
information on vessel characteristics, voyage characteristics, shipowners, and charterers. After filtering
the data for missing values, omitted information, and other unusable observations, a total of 3,039 and
9,076 fixtures observations remain for Capsize and Panamax dry bulk ships, respectively.7 Specifically,
the information on each fixture consists of the vessels name, size, age, type, dwt, and the owner of the
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routes. The non-Baltic routes for Panamax carriers are: Mediterranean to Far East, PG - Indian Ocean to
Far East, Far East to PG-Indian Ocean, Continent to PG-Indian Ocean, and PG-Indian Ocean to
Continent. See the Appendix for further description of these routes. Theroutes identified represent about86.8% of the observed trip-charter fixtures; the remaining fixtures are for numerous minor routes with
less trading activities, while the four main Baltic routes represent 67% of the trip-charter fixtures, thus
indicating how concentrated the market is.
Table 22 also presents descriptive statistics for these routes via vessel type with respect to the number
of fixtures and the laycan period. It is interesting to note that the average (or mean) and the standard
deviation of the laycan period are directly related to vessel size. For instance, the average and standard
deviation of laycan periods for Capesize fixtures are 7.5 and 6.7 days, respectively, while the average and
standard deviation of the laycan period for Panamax fixtures are 4.4 and 4.6 days, respectively. The
average laycan period for the Baltic routes (first 4 routes) also seems to be longer for Capesize vessels
compared to Panamax ships. In addition, the most liquid route seems to be the Trans Pacific Round
Voyage route for both vessel types, with 54% and 35% of the activity in the Capesize and Panamax
sectors, respectively.
The descriptive statistics for the variablesvessel age, vessel size, Laycan period, freight rate and theBaltic Average 4TC Ratesare reported in Table 32. The results reveal similar average ages and standard
deviations for both Capesize and Panamax fleets. As expected, the average Capesize vessel has a
deadweight capacity of 165,000 mt, with standard deviation of 14,900 mt, while the average deadweight
capacity of Panamax vessels is 72,300 mt, with a standard deviation of 3,900 mt. The largest Capesize
vessel fixed over the sample period has a 301,800 dwt capacity. The average Capesize trip-charter rate
over the sample was 66,964 $/day, with a standard deviation of 47,611 $/day. The maximum Capesize
trip-charter rate was 303,000 $/day, and the minimum rate was 1,000 $/day. The average trip-charter ratefor Panamax ships was 32,001 $/day, with a standard deviation of 20,877 $/day. The maximum freight
rate was 125,000 $/day, and the minimum rate was 1,000 $/day. These statistics illustrate the existence of
very high volatility in the dry bulk shipping markets that has been documented in the literature. The
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5.1 Determinants of freight rates
Separate OLS estimates of equation (1) for the two dry bulk vessels Capesize and Panamax are
presented in Table 4. Diagnostic tests of the residuals, including the Breusch and Godfry test for serial
correlation and the White test for heteroscedasticity, suggest that the residuals of all models are non-
spherical. Therefore, the Newey-West (1987) method is applied to correct the standard errors of estimated
coefficients. The results suggest that in both the Capesize and Panamax markets, the dependent variable,
which is the difference between the freight rate for individual fixtures and the Baltic Indices (market rate),
can be explained by the laycan period of the contract as well as by the size and age of the vessel. The
significant and positive coefficients of the laycan and vessel size variables suggest that there exist a
positive relationship between these two variables and the freight differential (dfri,t). Estimated coefficients
of vessel age and vessel age-squared in the model suggest that there is a negative and nonlinear
relationship between the age of the vessel and hire rate for dry bulk vessels. Moreover, coefficients
measuring the impact of market volatility on freight rate differential are not significant in both the
Capesize and Panamax markets. Moreover, in the model for Capsize freight rates, significant and positive
estimated coefficient of the route dummy variable, 2, indicate that on average freight rates in route C9_03(European Continent to Far East) is 26.85% higher than the Baltic Capeszie Average 4TC Rate, while
significant and negative coefficients of route dummy variables, 4, indicate that freight rates in route
C11_03 (Far East to the European Continent) on average are 32.3% lower than the Baltic Capeszie 4TC
Rate. This is expected because routes C9_03 is considered to be a front-haul route, while C11_03 is
considered to be back-haul route, and in general back-haul routes trade at a discount to front-haul routes.
In the Panamax market, estimated coefficients for all route dummy variables are significant, which
means that there are significant differences in freight rates amongst the routes. For instance, the results
reveal that Panamax vessels operating in routes P1A and P2A tend to earn on average 3.68% and 14.94%
higher than the Baltic Panamax Average 4TC Rate, respectively. On the other hand, vessels trading in
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5.2 Determinants of Laycan Period
Separate OLS estimates of Laycan equation (2) for Capesize and Panamax vessels are found in Table5. In both equations, estimated standard errors of parameters are corrected for the presence of
heteroscedasticity and serial correlation using the Newey and West (1987) method. Starting with the
Capesize estimate, it can be seen that there is no significant difference between the laycan periods of the
Capesize charter contracts since coefficients of all dummy variables are not significantly different from
zero. The only exception is the estimated coefficient for the transpacific route in which the laycan period
is on average 1.38 days shorter than other routes. The estimated coefficients of other explanatory
variables in equation (2) reveal that laycan period of trip-charter contracts are positively related to the
freight differential (dfri,t) and log of Capesize Baltic 4TC average, bfit. This is expected because a higher
freight rate level is an indication that there is shortage of supply. As a result, charterers tend to hire ships
earlier with longer laycan period in order to avoid future freight rate increases and the possibility of
incurring extra cost due to unavailability of tonnage.
Negative and significant coefficients of vessel size and age in the laycan equation for capsize vessels
indicate that there is negative relationship between the duration of the laycan and vessel size as well as
vessel age. In other words, larger vessels and older vessels tend to be hired later than smaller and newer
Capsize vessels, everything else being equal. This is also expected, because if the charterers have a choice
between a modern and an old ship with similar freight rates, the newer vessel will be preferred to the
older ship; at the same time, a smaller Capsize vessel is preferred to larger one, since the daily freight rate
of the former will be less than that of the latter. Of course, the size of the cargo to be loaded on the vessel
is the most important factor in determing the size of the vessel chosen for hire by the charter. Finally, the
results reveal a negative and significant relationship between the duration of the laycan period of trip-
charter contracts and the volatility of capsize freight rates. Such a relationship can be attributed to the fact
that everything else being equal, the greater the uncertainty in the market the later the charterer would like
to fix tonnage (ships) for their transportation requirements. This can be explained through the option
valuation theory in the sense that higher uncertainty will increase the value of the option to wait or delay
fi i hi l h li h l d fi d h i i f i
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The estimated coefficients of other explanatory variables in equation (2) reveal that the laycan period
of trip-charter contracts in the Panamax market are also positively related to the freight differential (dfri,t)
as well as the log of the benchmark Baltic Panamax 4TC average, bfit. As explained earlier, chartererstend to hire ships earlier when a longer laycan period exists in order to avoid future freight increases,
when they expect a shortage of supply and higher freight rates due to unavailability of vessel tonnage. In
contracts to what was observed in the Capesize model, insignificant coefficients of size and age in the
laycan equation for Panamax vessels suggest that there is no relationship between the duration of the
laycan and vessel size as well as vessel age. Moreover, in line with what was observed in the Capesize
market, the results reveal a negative and significant relationship between the duration of the laycan period
of trip-charter contracts and the volatility of Panamax freight rates. Finally, the estimated coefficients of
goodness of fit of 5.77% and 3.41% for Capesize and Panamax laycan equations, respectively, suggest
that only small proportion of the variation of laycan period can be explained by variables such as the
freight rate level, volatility, size and age of the vessel.
5.3 Simultaneous-Equation Determinants of freight rate and laycan period
The estimated coefficients of the simultaneous system of equations (3) for Capesize and Pananaxfreight (charter) rates and laycan periods using the 3SLS estimation method are reported in Table 6and
Table 7, respectively. The results are qualitatively similar to those for the single equation models of the
freight rate and the laycan period -- although estimation of the two equations as a system of simultaneous
equations allows interaction between the dependent variables and yield more efficient estimates of
parameters due to higher degrees of freedom.
Estimated coefficients of route dummy variables in the freight rate equation reveal that only 2 of the 4
route dummy variables are statistically significant at the 1% levelContinent to Far East (route C9_03)
and Far East to Continent (route C11_03). The freight rate in route C9_03 is 26.75% higher than for
Capesize 4TC capsize vessels, while the freight rate in route C11_03 is 32.13% lower than that for
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freight rate increases. The positive and significant coefficient of the Baltic 4TC Rate suggest that
charterers tend to hire vessels earlier when freight rates are high. The estimated coefficient of freight
market volatility is negative and significant. Furthermore, the coefficients of vessel size and age are bothnegative and significant in the laycan equation, suggesting that the laycan period for larger and older
Capesize vessels is shorter than for smaller and newer vessels. This is to be expected as noted by the fact
that newer and more modern vessels are fixed earlier than older vessels.
The estimation results of the Panamax freight rate and laycan period simultaneous equations also
reveal similar results to those of the single equation models. Once again, freight rates differ among
Panamax routes. Vessel age and size are significant determinants of freight rates, Larger panamax vessels
command higher freight rates than smaller Panamax vessels and freight rates decrease non-linearly in
relation to vessel age. The laycan period is also a significant determinant of the Panamax freight rate; the
freight rate is higher when the vessel is hired early as opposed to being hired later.
As for the single equation model, the results for the determinants of the Panamax laycan period for
the simultaneous equation model reveal that the laycan period varies among routes. and these differences
are consistent with those observed in single equation model of laycan period. Furthermore, the laycan
period for Panamax vessels is positively related to the freight rate, the Baltic 4TC freight rate, and age of
the vessel. Among these three determinants of the laycan period, only the coefficient sign for vessel age is
not consistent with what was found for Capesize laycan period. The positive coefficient for vessel age
suggest that older Panamax vessels have a longer laycan period than newer panamax vessels.
The negative and significant coefficient of freight market volatility once again confirms that there is
an inverse relationship between market volatility and laycan period for charter contracts. This result is
consistent with real option valuation theory in the sense that as volatility increases the value of the option
to wait increases, i.e., charterers tend to delay fixing vessels. On the other hand, as freight rates (or thevalue of the underlying asset) increase, the value of the option to wait decreases and charterers tend to
enter the market earlier to hire vessels.
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shortages will seek to enter the charter market earlier, i.e., to fix their transportation requirements well in
advance. When the volatility and uncertainty of freight rates increase, charterers are expected to delay
their hiring of vessels as long as it is feasible to wait for the market to stabilize and avoid paying apremium to fix a vessel. Finally, laycan periods for trip-charter contracts in the dry bulk market are
negatively related to the age of vessels, i.e., newer ships have longer laycans than older ones.
Appendix
In the capsize market, route C8_03 is a transatlantic route with delivery and redelivery in Europe
(Gibraltar to Hamburg range). Route C9_03 is a trip from Europe to the Far East with delivery in Europe
or Mediterranean and redelivery in the Far East. Route C10_03 is a transpacific round trip with delivery
and redelivery in the Far East for trips to Australia, North Pacific, or even South Africa or India. Route
C11_03 is a trip from Far East to the Continent Europe via South Africa or Australia. The Baltic
Exchange also reports the average of these four routes as the Average 4TC, which is used for Forward
Freight Trading. The four main Baltic routes represent 95% of the trip-charter fixtures, which shows how
concentrated the capsize market is. It should be noted that there are other active Capesize routes such as
Bolivar to Rotterdam (C7) and Richards Bay to Rotterdam (C4), amongst others, where vessels are hired
on a voyage charter basis. These fixtures are not considered in our sample of trip-charter contracts.
In the Panamax sector, the Baltic Exchange compiles and reports more or less the same four main routes,
which again cover a large proportion of activities and fixtures. These routes are numbered as: P1A_03,
transatlantic route with delivery and redelivery in Europe; P2A_03, Europe to the Far East; P3A_03,
transpacific round trip with delivery and redelivery in the Far East for trips to Australia, North Pacific, or
even South Africa or India; and P4_03, Far East to the Continent. The equally weighted average of these
four routes is reported as the average Panamax 4TC. The average Panamax 4TC rate is also believed to
convey the general earnings of Panamax vessels that are actively used for FFA trading.
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Table 1: Components of the Baltic Average 4TC Rates (Indices) for Capsize and Panamax
Dry Bulk ShipsCapesize
Route Size (dwt) Description WeightingC8_03 172,000 Delivery Gibraltar to Hamburg range for Transatlantic round voyage 25%C9_03 172,000 Delivery Continent Europe to Mediterranean for a trip to the Far East 25%C10_03 172,000 Delivery China to Japan range for a Transpacific round voyage 25%
C11_03 172,000Delivery China to Japan range for a trip to European Continent andMediterranean
25%
Panamax
Size (dwt) Description WeightingP1A_03 74,000 Delivery Gibraltar to Hamburg range for Transatlantic round voyage 25%
P2A_03 74,000 Delivery Skaw to Gibraltar range for trip to the Far East via US Gulf 25%
P3A_03 74,000 Delivery Japan to South Korea for a Transpacific round voyage 25%
P4_03 74,000Delivery Far East for a Trip to Europe (Skaw to Cape Passero range) viaNorth Pacific or Australia
25%
Route C8_03 to C11_03 are based on a standard Baltic Capesize vessel of the following specification: 172,000mt dwt, not over 10 years of age, 190,000 cbm grain, max LOA 289m, max beam 45m, draft 17.75m, 14.5 knotsladen, 15 knots ballast on 56 mts fuel oil, no diesel at sea
Routes P1A_03, P2A_03, P3A_03 and P4_03 are based on a standard Baltic Panamax vessel of the followingspecifications: 74,000 mt dwt , not aged over 7 years with 89,000 cbm grain, max LOA 225 m, draft 13.95 m,capable of about 14 knots on 32 mts fuel oil laden, 28 mts fuel oil ballast and no diesel at sea.
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Table 2: Descriptive Statistics for Routes and Laycan Periods for Dry Bulk Ships
Sample period: 1st January 2003 to 31 July 2009.
Route Number of Fixtures Laycan Period (days)Capesize No Percentage Mean Median Min Max SD
1 Trans Atlantic Round Voyage 366 12.0% 8.6 8.0 0.0 39.0 7.02 Continent to Far East 492 16.2% 9.0 8.0 0.0 35.0 7.23 Trans Pacific Round Voyage 1642 54.0% 6.7 6.0 0.0 77.0 6.34 Far East to Continent 391 12.9% 7.7 7.0 0.0 31.0 6.55 Other routes 148 4.9% 8.2 7.0 0.0 42.0 7.7
Total Fixtures 3039 7.5 6.0 0.0 77.0 6.7
Panamax
1 Trans Atlantic Round Voyage 1397 15.4% 3.7 3.0 0.0 40.0 4.42 Continent to Far East 1033 11.4% 4.1 3.0 0.0 38.0 4.53 Trans Pacific Round Voyage 3174 35.0% 4.2 3.0 0.0 61.0 4.24 Far East to Continent 503 5.5% 4.8 4.0 0.0 34.0 4.55 Mediterranean to Far East 104 1.1% 5.5 5.0 0.0 27.0 5.26 PG - Indian Ocean to Far East 865 9.5% 5.7 4.0 0.0 32.0 5.57 Far East to PG-Indian Ocean 376 4.1% 3.7 3.0 0.0 30.0 3.98 Continent to PG-Indian Ocean 218 2.4% 3.3 3.0 0.0 17.0 3.69 PG - Indian Ocean to Continent 208 2.3% 5.2 4.0 0.0 30.0 5.510 Other routes 1198 13.2% 4.8 3.0 0.0 47.0 5.3
Total Fixtures 9076 4.4 3.0 0.0 61.0 4.6
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Table 3: Descriptive Statistics of Explanatory Variables
AgeSize
Dwt
Laycan
period
Freight
Rate
BalticAve 4TC
Diff FRand Baltic
years 000 mt days $/day $/day %
CapesizeMean 9.9 165.1 7.5 66,964 72,451 -0.0307
Median 9.0 170.2 6.0 55,000 63,235 -0.017Maximum 36.0 301.8 77.0 303,000 233,988 1.058Minimum 0.0 101.7 0.0 1,000 2,320 -1.957Std. Dev. 7.1 14.9 6.7 47,611 46,378 0.227Skewness 0.6 -0.1 1.4 1.5 1.3 -0.38Kurtosis 2.5 6.6 8.7 5.2 4.2 6.39JB test 215.9 1652 5175 1747 1039 4554P-value 0.000 0.000 0.000 0.000 0.000 0.000
PanamaxMean 9.6 72.3 4.4 32,001 32,506 0.0003
Median 8.0 73.6 3.0 26,500 27,642 0.000Maximum 33.0 79.9 61.0 125,000 94,977 2.394Minimum 0.0 50.3 0.0 1,000 3,537 -2.295Std. Dev. 7.0 3.9 4.6 20,877 20,189 0.373Skewness 0.85 -1.05 2.07 1.22 1.02 0.096Kurtosis 2.83 3.48 12.09 4.14 3.35 6.42JB test 1100 1745 37726 2758 1636 1488.8
Probability 0.000 0.000 0.000 0.000 0.000 0.000
Sample period: 1st January 2003 to 31 March 2009, consist of 3039 Capsize Trip-charter fixtures, and 9079 ofPanamax trip-charter fixtures.
JB is the Bera and Jarque (1980) test for normality which follows 2)2(. The 5% critical value for this test is 5.991.
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Table 4: Determinants of Capsize and Panamax Trip-Charter Freight Rates
)iid(0,~;d 2
1
,5
2
432,10, ii
K
j
jijtiiititi vvRTVOLAGAGSZLCfr
Capesize Panamax
Coeff P-val Coeff P-val
0 Constant -0.7242 0.000 0 Constant -0.4435 0.0001 Laycan LCi,t 0.0024 0.000 1 Laycan LCi,t 0.0035 0.0002 Size SZi 0.0039 0.000 2 Size SZi 0.0060 0.0003 Age AGi 0.0084 0.001 3 Age AGi 0.0066 0.0004 AG
2i -0.0008 0.000 4 AG
2i -0.0006 0.000
5 Volatility VOLt -0.0233 0.154 5 Volatility VOLt 0.0020 0.878
Route Route
1 Trans Atlantic Round Voyage 0.0298 0.319 1 Trans Atlantic Round Voyage 0.0368 0.000
2 Continent to Far East 0.2685 0.000 2 Continent to Far East 0.1494 0.000
3 Trans Pacific Round Voyage -0.0301 0.263 3 Trans Pacific Round Voyage -0.0910 0.000
4 Far East to Continent -0.3230 0.000 4 Far East to Continent -0.1709 0.0005 Mediterranean to Far East 0.2474 0.000
6 PGIndian Ocean to Far East 0.0809 0.000
7 Far East to PG-Indian Ocean -0.0757 0.000
8 Continent to PG-Indian Ocean 0.1900 0.000
9 PGIndian Ocean to Continent -0.1504 0.0002
R 0.5807 0.346
BG test 37.054 0.000 111.44 0.000White test 208.10 0.000 801.53 0.000JB test 2.15*105 0.000 1.4*104 0.000
BG test is the Breusch and Godfrey LM test for 10 th order serial correlation in residuals, which follows Chi-squared distribution with 10 degrees of freedom. White Test is the White (1980) the F-test for heteroscedasticity. This is an LM test which follows Chi-squared distribution with 4 degrees of freedom. JB the Jarque and Bera test for normality of residuals, which follows a Chi-squared distribution with 2 degrees of freedom. Standard Errors are corrected for hetreoscedasticity and Serial Correlation using Newey and West (1987) method.
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Table 5: Determinants of the Laycan Period of Trip-Charters Contracts
)iid(0,~; 2
1
,5432,10, ii
K
j
jijtiittiti RTVOLAGSZbfidfrLC
Capesize Panamax
Coeff P-val Coeff P-val
0 Constant 11.0116 0.000 0 Constant -0.9773 0.6591 Diff Freight Rate dfri,t 3.3320 0.000 1 Diff Freight Rate dfri,t 2.1310 0.0002 Baltic 4TC Rate bfit 0.4027 0.046 2 Baltic 4TC Rate bfit 0.4602 0.0003 Size SZi -0.0273 0.007 3 Size SZi 0.0205 0.4564 Age AGi -0.0849 0.000 4 Age AGi 0.0139 0.3645 Volatility VOLt -3.2349 0.000 5 Volatility VOLt -1.0252 0.000
Route Route
1 Trans Atlantic Round Voyage 0.1386 0.846 1 Trans Atlantic Round Voyage -1.2121 0.000
2 Continent to Far East -0.3820 0.614 2 Continent to Far East -1.1709 0.000
3 Trans Pacific Round Voyage -1.3851 0.033 3 Trans Pacific Round Voyage -0.5197 0.0054 Far East to Continent 0.1803 0.816 4 Far East to Continent 0.1840 0.480
5 Mediterranean to Far East 0.2333 0.662
6 PG - Indian Ocean to Far East 0.7599 0.003
7 Far East to PG-Indian Ocean -1.0153 0.000
8 Continent to PG-Indian Ocean -1.9339 0.000
9 PG - Indian Ocean to Continent 0.6261 0.1262
R 0.0577 0.0341
BG test 44.27 0.000 65.15 0.000White test 26.53 0.055 63.28 0.000
JB test 6283 0.000 4.17*104 0.000
BG test is the Breusch and Godfrey LM test for 10
th
order serial correlation in residuals, which follows Chi-squared distribution with 10 degrees of freedom. White Test is the White (1980) the F-test for heteroscedasticity. This is an LM test which follows Chi-squared distribution with 4 degrees of freedom. JB the Jarque and Bera (1980) test for normality of residuals, which follows a Chi-squared distribution with 2 degrees of freedom. Standard Errors are corrected for hetreoscedasticity and Serial Correlation using Newey and West (1987) method.
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Table 6: Determinants of Freight Rates and Laycan Periods of Capeszie Ship Trip-Charter contracts: A
Simultaneous Equation Estimation
i
K
j
jijtiittiti
i
K
j
jijtiiititi
RTVOLAGSZbf if rLC
RTVOLAGAGSZLCfr
,2
1
,,25432,10,
,1
1
,,15
2
432,10,
d
d
)(0,~,2
,1
i
i
i
dfri,t Equation LCi,t Equation
Variables Coeff p-val Variables Coeff p-val
0 Constant -0.7532 0.000 0 Constant 11.921 0.0001 Laycan LCi,t 0.0047 0.000 1 Diff Freight Rate dfri,t 6.4483 0.000
2 Size SZi 0.0039 0.000 2 Baltic 4TC Rate bfit 0.4878 0.021
3 Age AGi 0.0084 0.000 3 Size SZi -0.0386 0.0004 AGi
2 -0.0008 0.000 4 Age AGi -0.0518 0.012
5 Volatility VOLt -0.0150 0.238 5 Volatility VOLt -3.1427 0.000Routes Routes
1,1 Trans Atlantic Round Voyage 0.0293 0.083 2,1 Trans Atlantic Round Voyage -0.0010 0.999
1,2 Continent to Far East 0.2675 0.000 2,2 Continent to Far East -1.2539 0.048
1,3 Trans Pacific Round Voyage -0.0266 0.074 2,3 Trans Pacific Round Voyage -1.3085 0.019
1,4 Far East to Continent -0.3213 0.000 2,4 Far East to Continent 1.1686 0.0762
R 0.5777 0.0507
BG test 58.93 0.000 62.65 0.000
White test 71.94 0.000 35.10 0.000
JB test 20.9*104 0.000 6223 0.000
BG test is the Breusch and Godfrey LM test for 10
th
order serial correlation in residuals, which follows Chi-squared distribution with 10 degrees of freedom. White Test is the White (1980) the F-test for heteroscedasticity. This is an LM test which follows Chi-squared distribution with 4 degrees of freedom. JB the Jarque and Bera test for normality of residuals, which follows a Chi-squared distribution with 2 degrees of freedom. Standard Errors are corrected for hetreoscedasticity and Serial Correlation using Newey and West (1987) method.
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Table 7: Determinants of Freight Rates and Laycan Periods of Panamax Ship Trip-Charter Contracts: A System of
Simultaneous Equations
i
K
j
jijtiittiti
i
K
j
jijtiiititi
RTVOLAGSZbf if rLC
RTVOLAGAGSZLCfr
,2
1
,,25432,10,
,1
1
,,15
2
432,10,
d
d
)(0,~,2
,1
i
i
i
dfri,t Equation LCi,t Equation
Variables Coeff p-val Variables Coeff p-val
0 Constant -0.4487 0.000 0 Constant -0.2105 0.902
1 Laycan LCi,t 0.0067 0.000 1 Diff Freight Rate dfri,t 4.0890 0.000
2 Size SZi 0.0058 0.000 2 Baltic 4TC Rate bfit 0.4508 0.000
3 Age AGi 0.0064 0.000 3 Size SZi 0.0093 0.653
4 AGi2 -0.0006 0.000 4 Age AGi 0.0329 0.005
5 Volatility VOLt 0.0074 0.346 5 Volatility VOLt -1.0504 0.000
Routes Routes
1,1 Trans Atlantic Round Voyage 0.0404 0.000 2,1 Trans Atlantic Round Voyage -1.2722 0.000
1,2 Continent to Far East 0.1522 0.000 2,2 Continent to Far East -1.4568 0.000
1,3 Trans Pacific Round Voyage -0.0887 0.000 2,3 Trans Pacific Round Voyage -0.3438 0.028
1,4 Far East to Continent -0.1703 0.000 2,4 Far East to Continent 0.5248 0.034
1,5 Mediterranean to Far East 0.2450 0.000 2,5 Mediterranean to Far East -0.2508 0.595
1,6 PG - Indian Ocean to Far East 0.0778 0.000 2,6 PG - Indian Ocean to Far East 0.6009 0.003
1,7 Far East to PG-Indian Ocean -0.0720 0.000 2,7 Far East to PG-Indian Ocean -0.8621 0.001
1,8 Continent to PG-Indian Ocean 0.1950 0.000 2,8 Continent to PG-Indian Ocean -2.2912 0.000
1,9 PG - Indian Ocean to Continent -0.1514 0.000 2,9 PG - Indian Ocean to Continent 0.9270 0.0072
R 0.3412 0.0278
BG test 167.18 0.000 122.35 0.000White test 799.29 0.000 60.479 0.000
JB test 13495 0.000 41000 0.000
BG test is the Breusch and Godfrey LM test for 10 th order serial correlation in residuals, which follows Chi-squared distribution with 10 degrees of freedom. White Test is the White (1980) the F-test for heteroscedasticity. This is an LM test which follows Chi-squared distribution with 4 degrees of freedom. JB the Jarque and Bera (1980) test for normality of residuals, which follows a Chi-squared distribution with 2 degrees of freedom. Standard Errors are corrected for hetreoscedasticity and Serial Correlation using Newey and West (1987) method.