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CHAPTER 2volume of containerised imports. Moreover, a higher percentage of containerisedimports has a destination close to port. In the case of Sydney, 85 per cent ofcontainerised trade has an origin/destination within 40 kilometres of Port Botany. As aresult, empty containers remain close to port and are exported when container ships areavailable.An econometric model of empty container exports presented in equation (2.2) isspecified in terms of containerised import volumes.ln EMXit= γi+ γi1ln CMit+ γi2Dit+ v0 it(2.2)where,EMX i = Empty container exports from the ith port in teus;CM i = Containerised imports to the ith port in thousand tonnes;D i = Dummy variable to capture a large variation in empty container exports in theith port;v = Error term;γ’s = Regression parameters; andi and t have the same meaning as mentioned in equation (2.1).The model is estimated using historical data from 1993-94 to 2003-04. The estimatedregression results, which are presented in Table I.2 (Appendix I), show that the model isa good fit with an adjusted R-square value ranging from 0.87 to 0.98 and the estimatedcoefficients are highly significant. The estimated import volume elasticities of emptycontainer exports are shown in Table 2.4. They suggest that a one per cent increase(decrease) in the volume of containerised imports will make the export of emptycontainers increase (decrease) by 1.5 per cent in Brisbane, 2.6 per cent in Sydney, 1.4per cent in Melbourne, 1.9 per cent in Adelaide and all ports and 0.7 per cent inFremantle.TABLE 2.4 ESTIMATED ELASTICITY OF EMPTY CONTAINER EXPORT AND IMPORTDEMANDPortImport volume elasticityof empty container exportsExport volume elasticityof empty container importsBrisbane 1.531 0.357Sydney 2.617 0.510Melbourne 1.416 0.617Adelaide 1.903 0.618Fremantle 0.674 0.804Full container importsAn econometric model of full container imports presented in equation (2.3) is specifiedin terms of population, real GNE and exchange rates.13
ln FUMit= βi+ βi1ln PGNEAUt+ β2ln EXUSAUt+ e0 it(2.3)where,FUM i = Per capita full container imports to the ith port in teus;PGNEAU = Per capita real Gross National Expenditure (GNE) of Australia inmillion dollars;e = Error term;β’s = Regression parameters; andEXUSAU, i and t have the same meaning as in earlier equations.The exchange rate variable is substituted by the TWI variable in the case of SydneyPorts.Since each city port has its own catchment area of consumers, it is more meaningful toinclude the income of people residing in the catchment area. However, both historicaland forecast data on real income by catchment area is not readily available. Hence, GNEat the national level is used to reflect the real income level of consumers residing in thecatchment area of the five main city ports.The econometric model of full container imports is estimated using historical data from1993-94 to 2003-04. The estimated regression statistics of the model are shown in TableI.3 (Appendix I) and the estimated elasticities are summarised in Table 2.5. The modelis a good fit with the adjusted R-square value ranging from 0.90 to 0.99. The estimatedcoefficients of the per capita real GNE are highly significant and have expected signs.TABLE 2.5 ESTIMATED ELASTICITY OF PER CAPITA FULL CONTAINER IMPORTDEMANDPort Income elasticity Exchange rate elasticityBrisbane 3.780 NSSydney 2.055 0.047Melbourne 2.157 0.026Adelaide 2.744 NSFremantle 2.883 NSNS = Not statistically significant.According to the estimated elasticities, the per capita real GNE appears to be the mainfactor influencing full container imports. A one per cent increase (decrease) in percapita real GNE leads per capita full container imports to increase (decrease) by 3.8 percent in Brisbane, 2.1 per cent in Sydney, 2.2 per cent in Melbourne, 2.7 per cent inAdelaide and 2.9 per cent in Fremantle.Although the coefficient of exchange rate variable is not found statistically significant,the variable is included in the model of Sydney and Melbourne ports. This is becausethe coefficient has an expected sign and the predictive power of the model increasessignificantly with its inclusion. The estimated elasticity of the exchange rate is positive.This implies that the volume of full container imports increases (decreases) with the14
Page 2 and 3: Bureau of Transport and Regional Ec
Page 4: FOREWORDThis report presents the na
Page 7 and 8: Other ships........................
Page 9 and 10: Table 4.3Table 4.4Proportion of 40-
Page 11 and 12: Table I.3Estimated regression stati
Page 13 and 14: Figure 4.12Figure 4.13Non-container
Page 16 and 17: EXECUTIVE SUMMARYBACKGROUNDInternat
Page 18 and 19: to 52 to 55 per cent in Brisbane, S
Page 20 and 21: containerised trade is forecast to
Page 22 and 23: next twenty years to 12.6 million t
Page 24 and 25: The total containerised trade of Po
Page 26 and 27: Other ports‘Other ports’ in thi
Page 28: CRUISE SHIPPING FORECASTSAustralia
Page 31 and 32: elation to the movement of containe
Page 34 and 35: CHAPTER 2 FREIGHT FORECASTING MODEL
Page 36 and 37: CHAPTER 2FIGURE 2.1 CONTAINERISED T
Page 38 and 39: CHAPTER 2FIGURE 2.3 NON-CONTAINERIS
Page 40 and 41: CHAPTER 2The exchange rate variable
Page 44 and 45: CHAPTER 2appreciation (depreciation
Page 46 and 47: CHAPTER 2exports by 0.2 per cent in
Page 48 and 49: CHAPTER 2on the price of sea travel
Page 50 and 51: CHAPTER 3 FREIGHT MODELLING DATA AN
Page 52 and 53: CHAPTER 3containerised imports, but
Page 54 and 55: CHAPTER 3containers which are suita
Page 56: CHAPTER 3Non-container vessel sizeT
Page 59 and 60: agricultural commodities fell becau
Page 61 and 62: container imports and 2.5 per cent
Page 63 and 64: TABLE 4.2 INTERNATIONAL CONTAINERIS
Page 65 and 66: FIGURE 4.3 NON-CONTAINERISED TRADE,
Page 67 and 68: PBC is also developing an additiona
Page 69 and 70: FIGURE 4.4 CARGO SHARES IN OUTBOUND
Page 71 and 72: TABLE 4.6CONTAINERISED EXPORTS AND
Page 73 and 74: TABLE 4.8 PROPORTION OF 40-FOOT CON
Page 75 and 76: TABLE 4.9 NON-CONTAINERISED SEA TRA
Page 77 and 78: increase by 1.3 per cent a year ove
Page 79 and 80: FIGURE 4.7 CARGO SHARES IN OUTBOUND
Page 81 and 82: per cent), Hong Kong (4.4 per cent)
Page 83 and 84: TABLE 4.13 PROPORTION OF 40-FOOT CO
Page 85 and 86: the Australian economy and the depr
Page 87 and 88: facilitate the movement of containe
Page 89 and 90: FIGURE 4.11 CONTAINERISED TRADE, 19
Page 91 and 92: TABLE 4.17 INTERNATIONAL CONTAINERI
Page 93 and 94:
55.3 per cent in 2003-04 largely du
Page 95 and 96:
TABLE 4.20 INTERNATIONAL NON-CONTAI
Page 97 and 98:
it accounts for 15 per cent of outb
Page 99 and 100:
TABLE 4.21 CONTAINERISED EXPORTS AN
Page 101 and 102:
TABLE 4.23 PROPORTION OF 40-FOOT CO
Page 103 and 104:
TABLE 4.24 NON-CONTAINERISED SEA TR
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The capacity of Fremantle Port will
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2024-25, whereas international non-
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TABLE 4.28 PROPORTION OF 40-FOOT CO
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TABLE 4.29 NON-CONTAINERISED SEA TR
Page 113 and 114:
25. International containerised exp
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TABLE 4.32 INTERNATIONAL CONTAINERI
Page 117 and 118:
FIGURE 4.19 NON-CONTAINERISED TRADE
Page 119 and 120:
TABLE 4.35 INTERNATIONAL NON-CONTAI
Page 122 and 123:
CHAPTER 5 FORECASTS OF CRUISE PASSE
Page 124 and 125:
Chapter 5Cruising typesThe cruising
Page 126 and 127:
Chapter 510.0 per cent each and the
Page 128 and 129:
Chapter 5Similarly, ship capacity o
Page 130 and 131:
Chapter 5FIGURE 5.3 SHORT-TERM SEA
Page 132 and 133:
APPENDIX IESTIMATED REGRESSION STAT
Page 134 and 135:
APPENDIX IITABLE I.3Variable by por
Page 136 and 137:
Page 138:
Page 141 and 142:
DVB 2004, The Cruise Industry and i
Page 144:
ABBREVIATIONSABS Australian Bureau
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