Infrastructure Victoria Second Container Port Advice Container trade forecasts for Victoria

Transcription

1 Infrastructure Victoria Second Container Port Advice Container trade forecasts for Victoria 13 February

2 Contents Glossary 5 1 Purpose and overview Container trade in Victoria This report 8 2 Previous forecasts 9 3 Methodology Central case High and low cases Origin and destination of containers 16 4 Containerised Forecasts Central case forecasts Mix of full and empty containers Mix of 20ft and 40ft containers Origin and destination regions of containers Commodity types of container trade High and low cases Low case forecasts High case forecasts 33 5 Non-containerised demand analysis Approach to analysis non-containerised trade Commodity types of non-containerised trade Motor vehicles Break bulk Dry bulk Liquid bulk 40 References 41 Appendix A 42 2

3 Table of Figures Table 1: Forecasts of total container trade, volumes (TEU): previous studies...10 Table 2: Overview of forecast approach Central case...11 Table 3: Overview of forecast approach Low and High cases...13 Table 4: Correction factors and final GSP-trade multipliers...15 Table 5: Forecasts of total container trade, volumes (TEU): central, low and high cases...18 Table 6: Forecasts of total container trade, compound annual growth rates: central, low and high cases...18 Table 7: Forecasts of total container trade by /, volumes (TEU)...20 Table 8: Forecasts of total container trade by /, compound annual growth rates...20 Table 9: Forecasts of total container trade by Full/Empty, volumes (TEU)...21 Table 10: container trade by Full/Empty, compound annual growth rates...21 Table 11: Forecasts of total container trade by 20ft/40ft, volumes (TEU)...22 Table 12: Forecasts of total container trade by 20ft/40ft, compound annual growth rates...22 Table 13: Forecasts of direct container trade imports by region of origin, volumes (TEU)...23 Table 14: Forecasts of direct container trade imports by region of origin, compound annual growth rates...24 Table 15: Forecasts of direct container trade exports by region of destination, volumes (TEU)...25 Table 16: Forecasts of direct container trade exports by region of destination, compound annual growth rates...26 Table 17: Forecasts of full direct container trade imports by commodity, volumes (TEU)...27 Table 18: Forecasts of full direct container trade exports by commodity, volumes (TEU)...28 Table 19: Forecasts of total container trade, volumes (TEU)*...29 Table 20: Forecasts of total container trade, compound annual growth rates...30 Table 21: Forecasts of total container trade by Full/Empty, volumes (TEU)...30 Table 22: Forecasts of total container trade by Full/Empty, compound annual growth rates...31 Table 23: Forecasts of total container trade by 20ft/40ft, volumes (TEU)...32 Table 24: Forecasts of total container trade by 20ft/40ft, compound annual growth rates...32 Table 25: Forecasts of total container trade, volumes (TEU)...33 Table 26: Forecasts of total container trade, compound annual growth rates...33 Table 27: Forecasts of total container trade by Full/Empty, volumes (TEU)...34 Table 28: Forecasts of total container trade by Full/Empty, compound annual growth rates...34 Table 29: Forecasts of total container trade by 20ft/40ft, volumes (TEU)

4 Table 30: Forecasts of total container trade by 20ft/40ft, compound annual growth rates...35 Table 31: Actual and forecast non-containerised trade at PoM: existing studies (in tonnes)...37 Table 32: Forecasts of total container trade by /, volumes (TEU): central case...42 Table 33: Forecasts of total container trade by Full/Empty, volumes (TEU): central case...44 Table 34: Forecasts of total container trade by 20ft/40ft, volumes (TEU): central case...46 Table 35: Forecasts of direct container trade imports by region of origin, volumes (TEU): central case...48 Table 36: Forecasts of direct container trade exports by region of destination, volumes (TEU): central case...50 Table 37: Forecasts of Bass Strait container trade by /, volumes (TEU): central case...52 Table 38: Forecasts of total container trade, volumes (TEU): low case...54 Table 39: Forecasts of total container trade, volumes (TEU): high case

5 Glossary AEM BITRE DTF FY GDP GSP IV NEI OECD PoH PoHDA PoM RORO TEU UNESCAP Access Economics Macro model Bureau of Infrastructure, Transport and Regional Economics Department of Treasury and Finance Financial Year Gross Domestic Product Gross State Product Infrastructure Victoria Not Elsewhere Identified Organisation for Economic Cooperation and Development Port of Hastings Port of Hastings Development Authority Port of Melbourne Roll On Roll Off Twenty Foot Equivalent Unit United Nations Economic and Social Commission for Asia and the Pacific 5

6 Infrastructure Victoria Second Container Port Advice Victoria s containerised trade is forecast to roughly double from around 2.7 million TEU in 2016 to 5.6 million TEU by

7 1 Purpose and overview The Victorian Government has asked Infrastructure Victoria to provide independent advice on the sequencing, timing and location of investment in future Victorian commercial port capacity. This advice is to address two key questions: 1. What is the long term demand for and capacity of existing Victorian commercial ports? 2. Whether a second (container) port should be located at Port of Hastings or Bay West? The approach to answering these questions will be guided by the objectives of Infrastructure Victoria s 30-year strategy and the Minister s terms of reference for this project. A critical first step in understanding the sequence, timing and location of investment required in Victoria s ports is to understand likely future paths for port demand. This report therefore provides container trade forecasts for a low, central and high scenarios for the period FY It also discusses volumes of container trade by origin and destination countries and gives consideration to long term trends in non-container trades. In addition to preparing new forecasts a brief review of available demand forecasts including forecasts prepared for Port of Hastings, the Port of Melbourne lease transaction and BITRE is also included in this report. The overall purpose of developing the container trade forecasts is to compare capacity and demand scenarios in order to estimate the timeframe in which a new port will be required in Victoria. Different trade scenarios combined with different capacity optimisation plans will dimension the upper and lower bounds for when a second port is required. 1.1 Container trade in Victoria Port of Melbourne (PoM) has historically been able to expand to meet the increasing demand for containerised freight. However, as the city has grown and changed around the port environs, the ability for PoM to continually expand is becoming increasingly constrained. Demand for container port capacity in Victoria has grown steadily, driven by the demand for imports and to a lesser extent the increases in containerised exports. The total volume of containerised international trade through PoM had increased by a rate of 5.9 per cent per annum from 1.1 million TEU in FY1999 to 2.5 million TEU in FY2013. In recent years this rate of growth has been more subdued with annual volumes reaching 2.6 million TEU in FY2016 representing an average growth rate of around 1.7%. However, even with this period of subdued growth, total container numbers have more than doubled in the past 16 years. Growth in Victoria s economy and its population have been key factors in driving this increase in container numbers. Work undertaken by Deloitte for Infrastructure Victoria concluded that population and economic growth are forecast to continue to increase. In the past 30 years Victoria s population has grown from 4.2 million people to approximately 6.1 million. This growth is expected to continue with a forecast of 6.6 million in FY2021, 8.3 million in FY2036 and 9.4 million by FY2046 (DELWP 2016). At an aggregate level population, GSP and exchange rates have been key drivers in influencing the volume of containerised exports and imports to and from Victoria. As such, as these factors continue to grow into the future, it is expected the container volumes will also continue to grow. In order to meet increasing demand, the PoM undertook the Port Capacity Project. This project included upgrades to Swanson dock and the development of a new international container terminal and automotive facility at Webb Dock. The new container terminal at Webb Dock is expected to commence operations in 2017 with a capacity of 350,000 TEU per annum when fully operational the new terminal will have a capacity of 1.4 million TEU (VICT 2016). Once the Port Capacity Project is completed it is expected that PoM will have an annual international container capacity of between 4 5 million TEU. What is not clear is what the 7

8 ultimate capacity of PoM will be - some estimates have put the ultimate capacity of the port on the current footprint at between 7 9 million TEU per annum. With the growth of containerised trade likely to continue into the future and long term constraints on the ultimate capacity of PoM it becomes important to develop a clear, robust and detailed trade forecast to support decision making on the timing and location of investment in Melbourne s future ports. 1.2 This report This report is set out in the following sections: Section 2 provides a brief summary of other recent forecasts of container trade in Victoria Section 3 sets out the methodology that has been used to develop the forecasts Section 4 provides the main outputs of this report, detailed forecasts of containerised trade including a central, high and low case as well as details on the mix of container types, destinations and commodities. Section 5 provides commentary and consideration of non-containerised trade Unexpected events The forecasts in this report are generally based on historical trends and relationships. For example, many forecasts depend on the historical relationship between Gross State Product (or components of it) and trade in certain goods. These historical relationships are then used to forecast the most likely level of trade in the future. That is, the forecasts in this report should be seen as averages or expected values. Where possible we have taken into consideration known changes in production or behaviour. For example, we have accounted for the reduction in vehicle manufacturing in Victoria and changes in the location of oil refining. We have also accounted for long run changes in the relationship between trade and economic growth. However, these forecasts do not account for intermittent, difficult to predict events. For example, the level of agricultural exports depends heavily on the weather and this factor is outside the scope of the forecasts presented in this report. Further, we have not accounted for potential events (such as a recession) that will affect trade if they occur but which cannot currently be forecast. 8

9 containerised trade (TEU) 2 Previous forecasts Given the importance of international trade to Australia s economy, potential future growth in trade volumes and its implication for port and landside infrastructure is frequently analysed. In recent years that has been particularly true for Victoria and PoM. In the period 2013 to November 2016, a number of long-term forecasts of containerised trade have been prepared. The major publicly available forecasts include the following: Port of Hastings Development Authority (PoHDA 2013): FY forecast prepared by Deloitte for the Port of Hastings preliminary business case; Department of Treasury and Finance (DTF) (PoHDA 2015): FY forecast (international container trade only); and Bureau of Transport, Infrastructure and Regional Economics (BITRE 2014): FY forecast for PoM. Forecasts of total containerised demand from these three sources are illustrated in Figure 1 and Table 1. Figure 1: Forecasts of total container trade, volumes (TEU): previous studies 22 M 20 M 18 M 16 M 14 M 12 M 10 M 8 M 6 M 4 M 2 M M Financial year Historical PoHDA (2013) BITRE (2014) DTF (2014) Source: BITRE (2014); PoHDA (2013); PoHDA (2015); Port of Melbourne (2016); Ports Australia (2016) 9

10 Table 1: Forecasts of total container trade, volumes (TEU): previous studies FY PoHDA 2013 DTF 2014 BITRE M 2.3 M 2.9 M M 2.8 M 3.7 M M 4.4 M 5.8 M M 6.9 M n/a M 11.0 M n/a 2060 n/a 17.1 M n/a Source: PoHDA (2015) 1 ; PoHDA (2013); BITRE (2014). As can be seen in the chart, there is a wide range in the long term forecasts that have been prepared, this can be attributed to the different modelling approaches and data being used in the different forecasts. In 2013, Deloitte prepared a container demand forecast for Victoria to support the Port of Hastings preliminary business case (PoHDA 2013). Under these forecasts, it was expected that trade volumes would reach 7 million TEU in around FY2032 (not reported in Table 1). Forecasts were prepared by extrapolating historical actual container throughput at PoM based on forecasted growth of the Gross State Product (GSP) for Victoria and a GSP-demand multiplier. The multiplier was derived using a regression analysis on historical PoM containerised trade and economic growth for the period FY This same approach has been used to develop the high and low cases in this report and so a detailed description of this approach is presented in Section 3.2. The years leading up to FY2012 had seen a strong relationship between GSP growth and trade growth. In 2014, Victorian s Department of Treasury and Finance (DTF) prepared a forecast of Victorian port international container throughput to FY Based on the DTF forecast, container trade is expected to increase from 2.3 million in FY2016 to 4.4 million in FY2030. A detailed methodology for this forecast is not publicly available. In 2014, the Australian Government s Bureau of Transport, Infrastructure and Regional Economics BITRE (2014) produced a set of 20 year forecasts for Australian container ports, including PoM. Forecasts were prepared using econometric models of containerised (full and empty) exports and imports at PoM. In these models, population, income, exchange rates and export and import prices are included as drivers of demand. In line with the DTF 2014 forecast (PoHDA 2015), BITRE expects PoM s total container trade to double between FY2016 and 2030, albeit starting from a higher base in FY2016 (2.9 million TEU). 1 DTF forecasts reported in Table 1 are taken from PoHDA (2015) since the original document is not publicly available. Forecasts in PoHDA (2015) are presented in five year intervals for the period For the purpose of this review, DTF forecasts were interpolated to obtain forecasts at an annual basis. 2 See previous footnote. 10

11 3 Methodology Two different approaches were taken to prepare three containerised trade forecast scenarios for a low, central and high case. Central case forecasts were prepared using an established approach to forecast port throughput at Australian ports developed by Deloitte which has been applied to a number of ports around Australia. The detailed approach used in the central case allows for forecasts at a high level of robustness and a high level of granularity including the prediction of trade by commodity and container size. The approach also allows for consideration of trade by country of origin and destination. To support the central case, a high and low case forecast were also developed. To forecast the low and high cases, total trade volumes have been forecast in line with the approach used for the Port of Hastings preliminary business case, effectively extrapolating actual demand in FY2016 based on the expected GSP in Victoria and a trade multiplier. That is, the central case can be thought of as a detailed bottom-up analysis while the high and low case can be thought of as a less detailed top-down analysis. A detailed description of the two approaches used is provided in the following sections. 3.1 Central case Deloitte has an established approach to forecasting container port throughput that has been applied previously to several projects in Sydney and Melbourne. For this report, future container demand forecasts for Victoria under the central case have been developed based on this existing approach. In particular, Deloitte s established approach for forecasting container port throughput was updated using the most recent data and forecasts available for the Victorian economy. The overall approach for the modelling in the central case involves forecasting future trade for the full range of commodities traded through the port and then aggregating this into total container trade. The number of TEUs required to complete these movements is then estimated. That is, the central case can be thought of as a detailed bottom-up analysis. An overview of the approach to forecast container throughput under the central case is provided in the table below. Table 2: Overview of forecast approach Central case Level of aggregation demand and 20ft and 40ft Commodity types Approach / Assumption Sum of commodity level forecasts Sum of commodity level forecasts Allocating commodities to the types of containers they are normally transported in Use of historical relationship between demand or supply of the commodity and macroeconomic data. The relationship is different for each commodity. For example, for consumer goods, the relationship between household consumption (a well-known macroeconomic variable) and trade in consumer goods is analysed using historical data. Then a forecast of household consumption is used to forecast trade in consumer goods using this historical 11

12 relationship. This provides one component of the overall trade through the port and the steps can be replicated for other types of trade. Knowing which type of containers are used to transport consumer goods then informs the number and mix of containers moving through the port. Similar analysis is undertaken for all the different types of trade and this allows for an overall view of the total trade through the port. The detailed forecasts are therefore fundamentally driven by a number of forecasts of key macroeconomic variables. To forecast these macroeconomic variables over the next decade the Deloitte Access Economics Macro (AEM) model has been used. AEM is a macro-econometric model of the Australian economy. It describes the aggregate actions of households, businesses, government and international entities. The formulation of these behavioural equations is based on mainstream economic theory. The trade forecasts then link these macroeconomic forecasts to demand and supply of commodities and this allows for an estimation of the level of imports and exports of commodities. Forecasts of imports and exports of commodities are calculated by measuring the consumption and production of each commodity that is driven by changes in economic aggregates. For example, higher activity in the construction industry will lead to more trade in cement and other construction materials. The relationship between underlying economic activity and trade is specific to each commodity. The modelling also includes some judgemental adjustments to ensure smooth and sensible transition from historical data to forecasts. The result of these steps is forecasts of the volume of imports and exports through PoM by commodity, measured in tonnes. The total export and import quantities are then simply the sum of the forecast trade for each of the commodities. Aggregate macroeconomic trade data (such as total rural exports, total non-rural commodity exports, total non-commodity goods exports and total imports) is used as a check to ensure that the bottom up forecasts of trade in individual commodities are consistent with national level forecasts. The data used to determine the relationship between macroeconomic activity and trade in commodities is obtained from the Australian Bureau of Statistics and historical trade volumes data from PoM are used to calculate average weight of different commodities moving through PoM. The model also maintains a seasonal pattern in both exports and imports. These forecasts are based on historical data sourced from the Australian Bureau of Statistics. These forecasts in terms of tonnes must then be transformed into an implied freight task measured in TEUs using two factors: the historical ratio of TEUs per tonne by commodity and the changing mix between 20ft and 40ft containers seen over recent years. This step is not a simple application of historical rates. For example, the carrying capacity (payload) of a 40 foot container is not twice that of a 20 foot container. As such, a move to 40 foot containers over time will result in a larger increase in TEUs than would otherwise be expected by the volume increase in tonnes. As a result, rather than measuring simple, historical TEUs per tonne, the modelling adjusts for the gap between the expected capacity of a 40 foot container (equal to two 20 foot containers) and the actual measured capacity. The rising share of 40 foot containers in overall container trade explains some, but not all, of the decline in tonnes per TEU of trade across recent history. The adjusted tonnes per TEU measure is then forecast into the future based on historical relationships. This allows for the forecast to take into account the changing commodity mix and its effect on the change in TEUs per tonne over time. It should also be noted that the rate of containerisation is assumed to remain constant for all commodities over the forecast period. For empty containers, the approach to modelling is based on that set out by the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP) 3. In brief, the major directional movement for trade at the port is identified. In the case of PoM, imports are the major 3 See UNESCAP (2005), Regional Shipping and Port Development Strategies (Container Traffic Forecasts), Monograph Series on Managing Globalisation, New York, Available: 12

13 directional movement. 4 The number of empty container exports (the minor flow) is then estimated as the difference between total direct international imports and full direct international exports. This methodology therefore assumes that total international direct trade balances. However, in the central case, rather than force imports and exports to equal in the short term, Deloitte Access Economics has incorporated an adding up adjustment that creates a gradual shift toward balanced trade over the long run. Transhipment has also been considered separately as it is not generally related with macroeconomic conditions in Victoria. A relatively minor component of containerised trade through the port (around 6 per cent in FY2015 according to PoM data), transhipment is assumed to move broadly in line with overall trade trends, on the basis that the volume of direct trade reflects the overall importance of the port within the region, which itself influences the volume of transhipment. 3.2 High and low cases The overall approach to developing the low and high demand forecasts was the same as that used by Deloitte in 2013 as part of the Port of Hastings preliminary business case. This is a different and more simplified approach than that taken to prepare the central case forecasts this reflects the role of the high and low cases as providing bounds on the central forecast and the fact that the detailed forecast prepared for the central case is a significant exercise which cannot be easily applied to generating numerous scenarios. In general, the approach for developing the high and low case forecasts can be thought of as a top-down approach. In this top-down approach, the historical relationship between total trade measured in TEUs and GSP growth is combined with a forecast of GSP to create a forecast of total trade in TEU. The total trade levels are then broken down into components of trade using assumed or estimated shares, some of these shares are based on the central case forecast. In particular, the shares of each commodity from the central case, were applied to the total forecast developed in the low and high cases An overview of the approach to forecast container throughput under the low and high cases for different levels of aggregation is provided in Table 3. Table 3: Overview of forecast approach Low and High cases Level of aggregation demand and 20ft and 40ft Commodity types Approach / Assumption Use of a GSP-trade multiplier and forecast GSP growth 50% split to ensure balanced trade in short run. Split as calculated under the detailed central case forecast and applied to low and high cases forecast imports and exports Not provided The remainder of this section explains the approach taken to derive total expected container volumes at PoM under the low and high cases. A major driver of total container movements in Victoria under the low and high scenarios is assumed to be economic growth in Victoria. As a result, forecasts of total container trade have been generated by extrapolating actual demand in FY2016 using a forecast of Victorian GSP and a GSP-container trade multiplier. 4 A small share of empty container imports is also apportioned to the major movement. Empty container imports make up around 8% of total container imports. 13

14 The forecast of Victorian GSP in the low and high cases was the same as that used in the central case. The GSP-container trade multiplier measures the historical relationship between the annual growth of total container movements (measured in TEU) and annual GSP growth in Victoria and was derived using a regression analysis. To do this, data on total container throughput for Melbourne from FY1987 to FY2016 was sourced from Ports Australia (2016) and Port of Melbourne (2016), this was combined with data on GSP growth from Deloitte Access Economics. The result of this analysis is a GSP-container trade multiplier that can be used to forecast container volumes. The analysis indicates that the relationship between container throughput at the port of Melbourne and Victoria s GSP growth is between 1.4% and 2.2% (this is the 95% confidence interval). That is, if GSP increases by 1% then the number of containers passing through the port is expected to increase by somewhere in the range of 1.4% to 2.2%. This implies that container movements would be expected to grow at up to twice the rate of GSP based on historical data, using the upper bound of the forecast. For example, in a year where Victorian GSP grows at 3%, total container trade could be expected to grow at up to 6.6%. To generate the high and low cases, this full statistical range was used. That is, in the low case, a 1% increase in GSP increases trade volumes by 1.4% while in the high case a 1% increase in GSP increases trade volume by 2.2%. A critical weakness of this approach is that the historical relationship between trade and GSP may not be sustained in the future. For example, the boom in trade with China and the containerisation of freight are likely to be one-off events that boosted trade and will not be repeated in the near future. The GSP-trade multipliers have therefore been adjusted by a scaling factor to reflect that the historical pace of trade growth relative to GSP is unlikely to be sustained further out into the forecast horizon. 5 The scaling factor was drawn from a BITRE (2010) study that developed a correction factor that can be applied to forecast port throughput. The BITRE study essentially looked at how the GSP-trade multiplier had weakened over time and created an index that could be used to adjust future values of the GSP-trade multiplier. An adjusted version of this correction factor was used in this study to extend the period of time where the scaling factor could be applied from FY2030 until FY2065. Table 4 presents the original BITRE (2010) correction factor, the adjusted factor and the final GSPtrade multipliers used to generate forecasts under the low and high scenario. For example, the final GSP-trade multiplier for the low case for any year is calculated as the product of the coefficient 1.4 and the adjusted BITRE factor for the specific year. The final GSP-trade multiplier used for the high case is the product of the BITRE factor and the coefficient 2.2. Note that it was assumed that the final trade multipliers cannot be lower than one. As a result, under the low case, the GSP-trade multiplier is 1.0 starting from FY2031 up until the end of the forecast horizon in FY2065, while under the high case, the multiplier is 1.0 starting from FY We have followed the BITRE methodology from Road and freight estimates and forecasts in Australia to determine the scaling factor, and extended it out to our forecast horizon. 14

15 Table 4: Correction factors and final GSP-trade multipliers FY BITRE (2010) factor Adjusted BITRE factor Final GSP-trade multiplier: Low Case Final GSP-trade multiplier: High Case Source: BITRE (2010); Deloitte 15

16 3.3 Origin and destination of containers Additional analysis was undertaken to establish the likely origin and destination of trade. Overall, this analysis provided trade shares for import and export trade movements by region of the world. The regions considered are: Africa; Europe; Middle East; North America; North Asia; Pacific; South Asia; South/Latin America; and Other. Of these, the major trading partners for Australia are North Asia and South Asia, together the two regions account for around 60% of containerised imports coming into Victoria and over 60% of containerised exports moving out of Victoria. Given their importance to the overall level of trade, the categorisation of countries into these two regions is important to understand. North Asia is assumed to be made up of China, Japan, the Korean peninsula and Mongolia while South Asia is all other countries within the Asian continent notably including India, Indonesia, Hong Kong, Malaysia, Pakistan, Singapore, Sri Lanka, Taiwan, Thailand and Viet Nam. The approach to forecasting trade by region was to estimate a gravity model of trade for each region. A gravity model of trade essentially tries to estimate the level of trade between two countries by looking at the size of both of their economies and how close the two countries are geographically. Two large economies located next to each other (such as France and Germany) would be expected to trade more than two smaller economies located further away (such as New Zealand and Ireland). Gravity models of trade have been used in economics with great success since the early 1960s. To estimate the gravity model of trade, historical data on trade between PoM and various countries was gathered for the period from FY2005 to FY2016. This data was available for both imports and exports and included trade with most countries. Data on historical GDP was sourced from OECD (2016). OECD data was used as Deloitte Access Economics does not produce GDP forecasts for all international countries. A standard gravity model was estimated using regression analysis and produced reliable results. The form of the basic model was: Where F is the trade flow between country i and j, G is a constant, M is the size of each country s economy and D is the distance between the pair of countries. The βs are then variables to be estimated from the data. Special variables were included for South Asia, North Asia and the Pacific as these regions were found to have levels of trade with Australia that differed somewhat in recent years from what was predicted by the basic gravity model. Overall, the model is able to explain the majority of the historical trade pattern seen in the data and is statistically robust. Using the historical relationship, forecasts of trade can then be made using forecasts of GDP growth rates (also sourced from the OECD). As with the central case forecasts, the modelling also includes some judgemental adjustments to ensure a smooth and sensible transition from historical data to forecasts. 16

17 containerised trade (TEU) 4 Containerised Forecasts This section summarises the results of the demand models, presenting forecast container throughput for PoM under the low, central and high scenario. Figure 2 and Table 5 show that in FY2030 total containerised demand will reach 4.2 million TEU under the central case, 4.1 million TEU under the low case and 5.3 million TEU under the high case. Thereafter, demand grows notably less under the low case compared to the central and high case. By FY2050, container demand is expected to reach 7.2 million TEU under the central case, 6.1 million under the low case and 8.7 million TEU under the high case. Figure 2: Forecasts of total container trade, volumes (TEU): central, low and high cases 12 M 11 M 10 M 9 M 8 M 7 M 6 M 5 M 4 M 3 M 2 M 1 M M Forecast Financial year Historical Central Case Low Case High Case 17

18 Table 5: Forecasts of total container trade, volumes (TEU): central, low and high cases FY Central Low High 2006^ 1,930,172 1,930,172 1,930, ^ 2,236,552 2,236,552 2,236, ,700,580 2,700,580 2,700, ,057,040 3,040,633 3,312, ,616,080 3,557,482 4,263, ,194,106 4,062,702 5,278, ,862,804 4,505,063 6,191, ,568,872 4,993,432 7,060, ,337,338 5,528,578 7,852, ,197,297 6,114,665 8,685, ,167,833 6,757,441 9,598, ,278,132 7,461,081 10,597, ,531,514 8,208,516 11,659,301 Notes: ^ Actual container volumes Table 6: Forecasts of total container trade, compound annual growth rates: central, low and high cases FY Central Low High ^ 3.8% 3.8% 3.8% ^ 3.2% 3.2% 3.2% % 3.0% 5.2% % 3.2% 5.2% % 2.7% 4.4% % 2.1% 3.2% % 2.1% 2.7% % 2.1% 2.2% % 2.0% 2.0% % 2.0% 2.0% % 2.0% 2.0% % 1.9% 1.9% Notes: ^ Actual compound annual growth rates 18

19 containerised trade (TEU) 4.1 Central case forecasts container throughput by import and export demand for PoM as estimated by Deloitte under the central case is illustrated in Figure 3. It is expected that total container trade reaches a volume of 10.5 million TEU by FY2065. Figure 3: Forecasts of total container trade by /, volumes (TEU) 12 M 11 M 10 M 9 M 8 M 7 M 6 M 5 M 4 M 3 M 2 M 1 M M Financial year This following sections present the container trade forecasts for the central case by imports/exports, full/empty, 20ft/40ft, type of commodity and region of origin of destination over five year increments to FY2065. Note that Appendix A provides more detailed forecasts, presenting forecast throughput for each year for the period FY

20 Table 7: Forecasts of total container trade by /, volumes (TEU) FY 2006^ 984, ,730 1,930, ^ 1,132,971 1,103,580 2,236, ,356,585 1,343,995 2,700, ,533,441 1,523,598 3,057, ,817,398 1,798,682 3,616, ,111,235 2,082,870 4,194, ,452,099 2,410,705 4,862, ,812,471 2,756,401 5,568, ,205,222 3,132,116 6,337, ,645,276 3,552,020 7,197, ,142,400 4,025,433 8,167, ,711,545 4,566,586 9,278, ,354,383 5,177,131 10,531,514 Notes: ^ Actual container volumes Table 8: Forecasts of total container trade by /, compound annual growth rates FY ^ 3.6% 3.9% 3.8% ^ 3.0% 3.3% 3.2% % 3.2% 3.1% % 3.4% 3.4% % 3.0% 3.0% % 3.0% 3.0% % 2.7% 2.7% % 2.6% 2.6% % 2.5% 2.6% % 2.5% 2.6% % 2.6% 2.6% % 2.5% 2.6% Notes: ^ Actual compound annual growth rate 20

21 4.1.1 Mix of full and empty containers The following tables provide forecast mix of full and empty containers and compound annual growth rates over five year increments to FY2065. Table 9: Forecasts of total container trade by Full/Empty, volumes (TEU) FY Full Empty Full Empty Full Empty 2006^ 872, , , ,617 1,542, , ^ 1,034,709 98, , ,957 1,801, , ,238, , , ,375 2,080, , ,400, , , ,015 2,294, , ,676, , , ,262 2,617, , ,963, , ,121 1,086,750 2,959,316 1,234, ,294, ,199 1,050,210 1,360,495 3,345,111 1,517, ,646, ,417 1,107,606 1,648,795 3,753,660 1,815, ,028, ,297 1,167,780 1,964,335 4,196,706 2,140, ,457, ,426 1,230,769 2,321,251 4,688,620 2,508, ,942, ,064 1,296,119 2,729,314 5,238,455 2,929, ,496, ,679 1,364,778 3,201,809 5,861,644 3,416, ,123, ,157 1,435,602 3,741,529 6,558,828 3,972,686 Notes: ^ Actual container volumes Table 10: container trade by Full/Empty, compound annual growth rates FY Full Empty Full Empty Full Empty ^ 4.4% -3.2% 3.4% 5.2% 3.9% 3.0% ^ 3.0% 3.1% 1.6% 6.8% 2.4% 6.1% % 3.0% 1.5% 5.9% 2.5% 5.3% % 1.1% 1.0% 6.4% 2.7% 5.5% % 1.0% 1.2% 4.8% 2.5% 4.3% % 1.2% 1.1% 4.6% 2.5% 4.2% % 1.1% 1.1% 3.9% 2.3% 3.6% % 1.2% 1.1% 3.6% 2.3% 3.4% % 1.2% 1.1% 3.4% 2.2% 3.2% % 1.3% 1.0% 3.3% 2.2% 3.1% % 1.4% 1.0% 3.2% 2.3% 3.1% % 1.5% 1.0% 3.2% 2.3% 3.1% Notes: ^ Actual compound annual growth rate 21

22 4.1.2 Mix of 20ft and 40ft containers The following tables provide forecast mix of 20ft and 40ft containers and compound annual growth rates over five year increments to FY2065. Table 11: Forecasts of total container trade by 20ft/40ft, volumes (TEU) FY 20ft 40ft 20ft 40ft 20ft 40ft 2006^ 478, , , , , , ^ 484, , , , ,149 1,277, , , , ,466 1,004,026 1,696, , , , ,068 1,076,940 1,980, ,429 1,209, ,352 1,194,330 1,211,781 2,404, ,122 1,432, ,700 1,405,170 1,356,822 2,837, ,695 1,685, ,012 1,645,693 1,531,707 3,331, ,924 1,949, ,765 1,896,635 1,722,689 3,846, ,318 2,234, ,438 2,167,678 1,934,755 4,402, ,092,209 2,553,067 1,082,298 2,469,722 2,174,507 5,022, ,230,638 2,911,762 1,215,381 2,810,052 2,446,019 5,721, ,389,601 3,321,944 1,367,564 3,199,022 2,757,165 6,520, ,569,441 3,784,942 1,539,237 3,637,894 3,108,678 7,422,836 Notes: ^ Actual container volumes Table 12: Forecasts of total container trade by 20ft/40ft, compound annual growth rates FY 20ft 40ft 20ft 40ft 20ft 40ft ^ 0.3% 6.4% 0.8% 6.7% 0.6% 6.5% ^ 0.8% 4.6% 0.8% 5.1% 0.8% 4.8% % 3.9% 1.9% 3.9% 1.8% 3.9% % 4.1% 2.4% 3.9% 2.4% 4.0% % 3.4% 2.3% 3.3% 2.3% 3.4% % 3.3% 2.5% 3.2% 2.5% 3.3% % 3.0% 2.4% 2.9% 2.4% 2.9% % 2.8% 2.3% 2.7% 2.3% 2.7% % 2.7% 2.3% 2.6% 2.4% 2.7% % 2.7% 2.3% 2.6% 2.4% 2.6% % 2.7% 2.4% 2.6% 2.4% 2.6% % 2.6% 2.4% 2.6% 2.4% 2.6% Notes: ^ Actual compound annual growth rate 22

23 4.1.3 Origin and destination regions of containers The following tables present forecast direct overseas container trade at PoM under the central case by region of origin and destination over five year increments to FY2060. In addition, the tables present forecast total Bass Strait trade (direct and transhipments), and other trade comprising overseas transhipments and total coastal trade. Table 13: Forecasts of direct container trade imports by region of origin, volumes (TEU) FY Africa Europe Middle East North America North Asia Pacific South Asia South/ Latin America Unspecified Overseas Bass Strait Other** 2010^ 4, ,558 7, , ,814 74, ,994 13, , ,068 74,542 1,132, , ,618 11,908 96, ,390 84, ,715 17, ,138, ,305 62,789 1,356, , ,719 13,506 96, ,377 96, ,751 19, ,288, ,541 77,475 1,533, , ,509 16,149 98, , , ,745 23, ,543, ,564 89,861 1,817, , ,106 18, , , , ,938 26, ,807, , ,766 2,111, , ,114 22, , , , ,089 29, ,112, , ,582 2,452, , ,621 25, , , , ,157 33,722 1,055 2,433, , ,264 2,812, , ,146 29, ,407 1,073, ,536 1,026,653 38,236 1,206 2,782, , ,303 3,205, , ,391 33, ,794 1,171, ,667 1,251,484 43,477 1,376 3,173, , ,297 3,645, , ,647 37, ,326 1,273, ,533 1,510,612 49,014 1,567 3,613, , ,654 4,142, , ,488 43, ,451 1,394, ,122 1,802,727 54,719 1,785 4,117, , ,993 4,711,545 Notes: ** Includes transhipments and coastal movements 23

24 Table 14: Forecasts of direct container trade imports by region of origin, compound annual growth rates FY Africa Europe Middle East North America North Asia Pacific South Asia South/ Latin America Unspecified Overseas Bass Strait Other** ^ 6.8% 5.6% 9.1% -0.8% 4.3% 2.2% 4.4% 4.4% 12.8% 3.9% 0.4% -2.8% 3.0% % 1.1% 3.2% 0.0% 3.3% 3.2% 5.2% 3.1% 3.2% 3.1% 1.9% 5.4% 3.1% % 1.6% 3.6% 0.4% 3.8% 3.6% 5.7% 3.5% 3.6% 3.7% 1.8% 3.0% 3.5% % 1.6% 3.2% 1.7% 2.6% 3.2% 5.2% 2.3% 3.2% 3.2% 1.8% 2.7% 3.0% % 1.5% 3.2% 1.6% 2.6% 3.2% 4.9% 2.6% 3.2% 3.2% 2.1% 2.7% 3.0% % 1.1% 2.9% 1.3% 2.4% 2.9% 4.3% 2.5% 2.9% 2.9% 2.0% 2.5% 2.8% % 1.1% 2.7% 1.4% 2.0% 2.7% 4.1% 2.5% 2.7% 2.7% 2.1% 2.4% 2.6% % 1.3% 2.7% 1.5% 1.8% 2.7% 4.0% 2.6% 2.7% 2.7% 2.1% 2.4% 2.6% % 1.6% 2.6% 1.6% 1.7% 2.6% 3.8% 2.4% 2.6% 2.6% 2.2% 2.4% 2.6% % 1.8% 2.6% 1.6% 1.8% 2.6% 3.6% 2.2% 2.6% 2.6% 2.3% 2.4% 2.6% Notes: ** Includes transhipments and coastal movements 24

25 Table 15: Forecasts of direct container trade exports by region of destination, volumes (TEU) FY Africa Europe Middle East North America North Asia Pacific South Asia South/ Latin America Unspecified Overseas Bass Strait Other** 2010^ 7,460 31,272 26,948 55, , , ,894 7, , , ,174 1,103, ,012 29,873 32,464 47, , , ,576 8, ,054, , ,809 1,343, ,722 41,119 37,524 44, , , ,567 11,866 1,109 1,216, , ,774 1,523, ,574 61,398 45,039 41, , , ,409 18,270 1,332 1,462, , ,101 1,798, ,502 68,034 52,842 45, , , ,074 20,637 1,562 1,715, , ,341 2,082, ,596 75,217 61,817 50, , , ,942 23,472 1,828 2,007, , ,606 2,410, ,586 81,842 71,269 55, , , ,516 26,489 2,107 2,314, , ,009 2,756, ,582 88,701 81,536 60, , ,027 1,170,145 29,890 2,411 2,647, , ,071 3,132, ,731 96,724 93,009 66, , ,667 1,375,327 33,782 2,750 3,020, , ,477 3,552, , , ,947 72,814 1,087, ,749 1,609,249 38,036 3,132 3,440, , ,744 4,025, , , ,738 80,354 1,206, ,720 1,874,220 42,665 3,570 3,920, , ,591 4,566,586 Notes: ** Includes transhipments and coastal movements 25

26 Table 16: Forecasts of direct container trade exports by region of destination, compound annual growth rates FY Africa Europe Middle East North America North Asia Pacific South Asia South/ Latin America Unspecified Overseas Bass Strait Other** ^ -3.5% -0.8% 3.2% -2.7% 5.8% -2.3% 7.5% 2.2% 7.8% 4.3% 1.1% -0.8% 3.3% % 8.3% 3.7% -1.6% 3.8% 3.7% 3.5% 9.0% 3.7% 3.6% 0.7% 2.4% 3.2% % 8.3% 3.7% -1.6% 3.8% 3.7% 3.5% 9.0% 3.7% 3.8% 1.2% 2.5% 3.4% % 2.1% 3.2% 2.1% 2.6% 3.2% 4.1% 2.5% 3.2% 3.2% 1.4% 2.2% 3.0% % 2.0% 3.2% 2.1% 2.6% 3.2% 3.9% 2.6% 3.2% 3.2% 1.7% 2.1% 3.0% % 1.7% 2.9% 1.8% 2.4% 2.9% 3.5% 2.4% 2.9% 2.9% 1.8% 1.9% 2.7% % 1.6% 2.7% 1.8% 2.2% 2.7% 3.3% 2.4% 2.7% 2.7% 1.9% 1.8% 2.6% % 1.7% 2.7% 1.9% 2.0% 2.7% 3.3% 2.5% 2.7% 2.7% 2.0% 1.8% 2.5% % 1.9% 2.6% 1.9% 2.0% 2.6% 3.2% 2.4% 2.6% 2.6% 2.1% 1.7% 2.5% % 2.1% 2.6% 2.0% 2.1% 2.6% 3.1% 2.3% 2.6% 2.6% 2.2% 1.8% 2.6% Notes: ** Includes transhipments and coastal movements Growth rates for Africa, Europe and South/Latin America are forecast to be relatively high in the short run as these regions have a very small level of trade with Australia. Small forecast increases in the total volume of trade therefore result in high levels of growth. For example, trade with South Asia, although growing at 3.1% during actually increases by some 100,000 TEU while trade with South/Latin America only increases by around 8000 TEU. 26

27 4.1.4 Commodity types of container trade The following tables present forecast of trade at PoM under the central case by type of commodity over five year increments to Note that commodity level forecasts exclude empty container movements and transhipments, however, totals for empty and transhipped containers are provided at the bottom of the tables for information. Table 17: Forecasts of full direct container trade imports by commodity, volumes (TEU) Commodity 2006^ 2010^ Beef Beverages 5,898 9,097 16,461 19,780 24,108 28,147 32,252 36,656 41,373 46,430 51,799 57,614 63,902 Construction 8,732 8,391 22,891 24,323 29,988 35,193 40,947 47,424 54,719 62,980 72,302 82,922 94,950 Dairy 5,021 8,120 10,690 12,813 13,988 15,066 16,133 17,212 18,303 19,416 20,536 21,701 22,907 Household goods 115, , , , , , , , , , , , ,968 Iron, steel, aluminium 11,809 19,175 26,678 30,181 35,825 42,998 51,430 60,302 69,696 79,839 90, , ,082 Machinery, vehicle parts 114, , , , , , , , , , , , ,176 Metal, non-metal, rubber manufacturing 67,067 92, , , , , , , , , , , ,902 Petroleum products 5,975 7,289 10,329 11,453 13,392 15,066 16,739 18,465 20,254 22,127 24,078 26,156 28,353 Plastics, chemicals 70,462 79, , , , , , , , , , , ,451 Pulp, paper products 54,783 56,170 66,312 69,421 77,904 88,200 98, , , , , , ,311 Textiles, clothing, footwear 67,771 77, , , , , , , , , , , ,677 Timber, wood products 17,780 24,304 35,905 39,841 48,201 57,632 68,272 80,490 94, , , , ,590 Wheat Wine 1,615 2,633 4,741 6,010 6,809 7,795 8,649 9,588 10,623 11,771 13,034 14,452 16,033 Wool Other manufacturing 121, , , , , , , , , , , , ,143 Other cereals 1,759 4,111 5,249 5,624 6,269 6,761 7,288 7,819 8,353 8,900 9,463 10,054 10,665 Other agriculture 33,957 46,584 67,643 68,471 77,845 85,128 92, , , , , , ,756 Other 19,361 21,034 32,027 35,311 43,276 49,913 56,866 64,516 72,848 81,934 91, , ,514 Direct Full - Other (Empty, Transhipped) 724, ,882 1,092,366 1,232,392 1,484,802 1,746,284 2,048,227 2,367,450 2,715,091 3,104,173 3,543,366 4,045,783 4,613, , , , , , , , , , , , , , ,442 1,132,971 1,356,585 1,533,441 1,817,398 2,111,235 2,452,099 2,812,471 3,205,222 3,645,276 4,142,400 4,711,545 5,354,383 Notes: ^ Actual container volumes

28 Table 18: Forecasts of full direct container trade exports by commodity, volumes (TEU) Commodity 2006^ 2010^ Beef 12,321 13,579 16,025 17,111 18,526 19,715 20,561 21,439 22,319 23,203 24,086 24,980 25,851 Beverages 3,255 3,254 3,434 3,835 4,118 4,416 4,709 5,021 5,352 5,701 6,065 6,449 6,849 Construction 1,434 1,398 1,132 1,174 1,201 1,229 1,258 1,291 1,326 1,364 1,406 1,451 1,499 Dairy 47,300 43,205 48,236 51,975 54,950 58,078 61,367 64,987 68,945 73,267 77,953 83,071 88,616 Household goods 9,844 8,213 9,529 9,783 10,363 11,025 11,687 12,351 13,056 13,829 14,689 15,647 16,693 Iron, steel, aluminium 23,294 29,422 24,944 25,439 26,267 27,116 28,094 28,877 29,519 30,063 30,527 30,913 31,162 Machinery, vehicle parts 29,273 20,476 26,175 27,394 28,252 28,831 29,240 29,528 29,749 29,954 30,151 30,365 30,525 Metal, non-metal, rubber manufacturing 17,935 19,988 28,752 31,708 34,679 36,680 38,460 40,380 42,412 44,540 46,751 49,097 51,457 Petroleum products 1,115 1,564 2,080 2, Plastics, chemicals 28,328 26,267 31,061 32,562 34,695 36,747 38,624 40,564 42,543 44,570 46,627 48,757 50,896 Pulp, paper products 69,299 86,967 89,531 93,428 95,750 98, , , , , , , ,648 Textiles, clothing, footwear 6,719 6,324 7,956 8,047 8,159 8,275 8,384 8,499 8,609 8,710 8,797 8,876 8,938 Timber, wood products 8,679 48,255 50,325 42,361 44,368 46,264 48,350 50,771 53,465 56,410 59,574 63,004 66,691 Wheat 7,969 32,733 34,759 42,824 44,145 47,009 49,424 52,092 54,948 57,960 61,084 64,347 67,706 Wine 36,260 29,630 21,404 20,887 21,948 23,013 23,958 24,960 26,007 27,093 28,194 29,341 30,520 Wool 13,701 12,374 13,523 14,207 14,056 14,007 13,955 13,930 13,927 13,944 13,979 14,033 14,098 Other manufacturing 38,409 42,236 35,539 34,228 34,039 34,596 35,137 35,424 35,588 35,731 35,884 36,085 36,237 Other cereals 34,017 25,615 37,554 43,449 45,706 48,695 51,245 53,982 56,863 59,872 62,979 66,217 69,544 Other agriculture 92,807 80, , , , , , , , , , , ,390 Other 12,328 16,090 14,555 15,235 16,768 18,034 19,013 20,099 21,247 22,439 23,660 24,931 26,204 Direct Full - 494, , , , , , , , , , , ,787 1,025,524 Other (Empty, Transhipped) 451, , , ,241 1,113,253 1,359,577 1,651,079 1,957,989 2,292,736 2,669,388 3,097,573 3,590,800 4,151, ,730 1,103,580 1,343,995 1,523,598 1,798,682 2,082,870 2,410,705 2,756,401 3,132,116 3,552,020 4,025,433 4,566,586 5,177,131 Notes: ^ Actual container volumes 28