australia's north-west shelf gas project : a general equilibrium analysis of its impact on the...

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Australia’s North-West Shelf Gas Project The sheer scale of the North-West Shelf Natural Gas Project inevitably entails substantial consequences for the Australian and West Australian econo- mies. In this paper an applied general equilibrium model is used to estimate the size of these effects. Expenditure during the construction phase stimu- lates the industries that supply the in- vestment goods. This higher demand, however, is inflationary and so reduces the competitiveness of export and im- port competing industries. The net re- sult is that the project does not have much impact on simulated real GDP during the construction phase. The pro- duction phase entails major increases in exports, in the output of industries supplying inputs to the project, and in real national income. However, the ex- port surge causes the real exchange rate to appreciate, leading to deteriorat- ing conditions in other internationally trading industries. Nevertheless, the upshot is an improvement in the bal- ance of trade and an increase in real GDP of about 1% during a typical year of the production phase. Peter Higgs is with the Graduate School of Management, University of Melbourne, 200 Leicester Street, Carlton 3053, Austra- lia; Alan Powell is with Monash University, Wellington Road, Clayton 3168, Australia. This paper was prepared with financial support from Woodside Offshore Petroleum. Comments by Ken Clements and Robert Greig of the Economic Research Centre at the University of Western Australia continued on page 180 A general equilibrium analysis of its impact on the Australian economy Peter J. Higgs and Alan A. Powell The North-West Shelf Gas Project, located near Dampier in the State of Western Australia (WA), is the largest resource development in Australia’s history. Exploration of the site commenced in the 1960s and substantial reserves were found early in the 1970s. Recoverable reserves in the North Rankin and Goodwyn fields are estimated to be 300 000 million m3 of natural gas and 56.1 million m3 of condensate respectively.* In 1979 the state and federal governments gave official environmental approval and the project began in 1980. Initial development included the (Japanese built) North Rankin A production platform which is located 134 kilometres off shore. A submarine trunkline to the shore and a domestic gas (DOMGAS) processing plant were also constructed. In 1984 the first sales of natural gas were made to the State Energy Commission of Western Australia (SECWA), signalling the start of a 20-year contract between SECWA and the participants in the project.” In 1985 a 20-year contract for the sale of liquefied natural gas (LNG) to Japan was signed and the go ahead was given for the construction of two LNG processing trains, LNG storage tanks, LNG loading jetty, and a fleet of seven (Japanese built) LNG carriers. The construction of the Goodwyn A platform, associated on shore facilities and a third LNG train were announced in 1989. In August of that year the first shipment of LNG arrived in Japan. It is expected that production from the Goodwyn A platform and the third LNG train will commence by 1993.4 For the purposes of this study we have split the project into a construction phase and a production phase, as described in the next section. To study the effects of the project we use ORANI, a large general equilibrium model of the Australian economy.’ A brief over- view of this model is then given, and the economic environment underlying the simulations is described. Macro and sectoral results are then discussed, followed by concluding remarks. A technical appendix appears at the end of the paper. 0301-4207/92/030179-12 0 1992 Butterworth-Heinemann Ltd 179

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Page 1: Australia's North-West shelf gas project : A general equilibrium analysis of its impact on the Australian economy

Australia’s North-West Shelf Gas Project

The sheer scale of the North-West Shelf Natural Gas Project inevitably entails substantial consequences for the Australian and West Australian econo- mies. In this paper an applied general equilibrium model is used to estimate the size of these effects. Expenditure during the construction phase stimu- lates the industries that supply the in- vestment goods. This higher demand, however, is inflationary and so reduces the competitiveness of export and im- port competing industries. The net re- sult is that the project does not have much impact on simulated real GDP during the construction phase. The pro- duction phase entails major increases in exports, in the output of industries supplying inputs to the project, and in real national income. However, the ex- port surge causes the real exchange rate to appreciate, leading to deteriorat- ing conditions in other internationally trading industries. Nevertheless, the upshot is an improvement in the bal- ance of trade and an increase in real GDP of about 1% during a typical year of the production phase.

Peter Higgs is with the Graduate School of Management, University of Melbourne, 200 Leicester Street, Carlton 3053, Austra- lia; Alan Powell is with Monash University, Wellington Road, Clayton 3168, Australia.

This paper was prepared with financial support from Woodside Offshore Petroleum. Comments by Ken Clements and Robert Greig of the Economic Research Centre at the University of Western Australia

continued on page 180

A general equilibrium analysis of its impact on the Australian economy

Peter J. Higgs and Alan A. Powell

The North-West Shelf Gas Project, ’ located near Dampier in the State of Western Australia (WA), is the largest resource development in Australia’s history. Exploration of the site commenced in the 1960s and substantial reserves were found early in the 1970s. Recoverable reserves in the North Rankin and Goodwyn fields are estimated to be 300 000 million m3 of natural gas and 56.1 million m3 of condensate respectively.* In 1979 the state and federal governments gave official environmental approval and the project began in 1980.

Initial development included the (Japanese built) North Rankin A production platform which is located 134 kilometres off shore. A submarine trunkline to the shore and a domestic gas (DOMGAS) processing plant were also constructed. In 1984 the first sales of natural gas were made to the State Energy Commission of Western Australia (SECWA), signalling the start of a 20-year contract between SECWA and the participants in the project.”

In 1985 a 20-year contract for the sale of liquefied natural gas (LNG) to Japan was signed and the go ahead was given for the construction of two LNG processing trains, LNG storage tanks, LNG loading jetty, and a fleet of seven (Japanese built) LNG carriers. The construction of the Goodwyn A platform, associated on shore facilities and a third LNG train were announced in 1989. In August of that year the first shipment of LNG arrived in Japan. It is expected that production from the Goodwyn A platform and the third LNG train will commence by 1993.4

For the purposes of this study we have split the project into a construction phase and a production phase, as described in the next section. To study the effects of the project we use ORANI, a large general equilibrium model of the Australian economy.’ A brief over- view of this model is then given, and the economic environment underlying the simulations is described. Macro and sectoral results are then discussed, followed by concluding remarks. A technical appendix appears at the end of the paper.

0301-4207/92/030179-12 0 1992 Butterworth-Heinemann Ltd 179

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continued from page 179 Construction and production phases and an anonymous referee are acknow- ledged with thanks,

‘Hereafter, just ‘the project’. ‘See Woodside Petroleum Ltd, Beyond the Flame: The Story of Australia’s North West She/f Nafural Gas Project, Woodside, Perth, 1989, p 132. 3 Note that ihe 1500 kilometre pipeline from the DOMGAS slant to users in Perth and the south-west of WA was built by SECWA. 4A third off-shore facility is planned to be built from 1998 to commence production in 2004 (see op tit, Ref 2, p 79); however, this is not included in our study. 5P.B. Dixon, B.R. Parmenter, J. Sutton and D.P. Vincent, ORANI: A Multisectoral Mod- e/ of the Australian Economy, North- Holland, Amsterdam, 1982 (referred to be- low as DPSV). ‘See WA Department of Resources De- velopment, LNG Export Sale of the Cen- turv. Special Edition of frosoect. Sorina. 1989, p 19.

“.

7See appendix for details. ‘See appendix for details. By the oil and gas industry we mean the input-output industry described as ‘Oil, gas and brown coal’, in M. Kenderes and A. Strzelecki. Parameters and CID Summaries in the ORANI Database 1977-78, 1978-79 and 7980431, Impact Project Research Mem- orandum, Archive No OA-435, Industries Assistance Commission, Canberra, 1988, p 8. According to official sources, brown coal accounts for only about 5% of the total value of output of this industry. ‘A$2 billion per year is a semi-official esti- mate: see WA Department of Resources Development (op tit, Ref 6, p 19). Note that the exports of LNG and condensates in 1989 prices were first converted into 1980-81 prices using the oil price series contained in Australian Bureau of Agri- cultural and Resource Economics, Com- modity Statistical Bulletin, Canberra, 1988, p 192. See appendix for more details. We have assumed that the prices of fluid fossil fuels from the project are perfectly corre- lated with that of Saudi light crude, and that the A$2 billion figure is based on an oil price of US$20 per barrel, converted at US$O.75 per Australian dollar. “‘For a concise description of the model, see P.B. Dixon, B.R: Parmenter, A.A. Powell and D.P. Vincent, ‘The aaricultural sector of ORANI 78: theory, data and application’, in A.C. Kelley, WC. Sander- son and J.G. Williamson, eds, Modeling Growing Economies in Equilibrium and Disequilibrium, Duke Press Policy Studies, Durham, NC, 1986, pp 237-276. “CRESH (constant ratios of elasticities of substitution, homothetic) is a generaliza- tion of CES in which the Allen-Uzawa partial elasticities between pairs of inputs can differ but are constrained to exhibit constant ratios: see G. Hanoch, ‘CRESH production functions’, Econometrica, Vol 39, No 3, September 1971, pp 395-419.

The construction phase is defined to cover the period 1980-93, while the production phase spans 1994-2004. According to a 1989 WA govern- ment publication, during 1980-89 approximately A$6.1 billion was invested in the project.6 It is planned to spend a further A$2.6 billion on a third LNG train and the Goodwyn A development by 1993.To simulate this expenditure of some 8.7 billion nominal dollars it is assumed that in a typical year of the construction phase A$850 million (1989 prices) of capital formation took place in the North-West Shelf.’ This additional activity was imposed on investment in the model’s existing oil and gas (O&G) industry.* However, the model’s database was first modified to incorporate detailed commodity and sourcing information on the project’s investment expenditures.

The project has significantly increased the size of the Australian O&G industry and is expected to generate significant sales of natural gas to the WA economy and a large flow of exports of LNG over the period 1994-2004.

To simulate the effects of the increased size of the Australian O&G industry we first estimated its preexisting capital stock by capitalizing its returns as given in the model’s database. Next the investment stream of the project over the construction phase was accumulated in real dollars. The resulting figures suggest that the project will have almost doubled the size of the Australian O&G industry by 1993. (Note that in the construction phase as modelled the additional capital stock is put in place but not yet switched on.) In simulations of the production phase a 98% increase in O&G capital stock actually in use is imposed.

To capture the effects of increased exports of fluid-state fossil fuels in a typical year of the production phase we imposed an exogenous increase in the physical volume of O&G exports sufficient to generate A$2 billion per annum if the price of fluid fossil fuels held firm at about US$20 per barrel.’

The ORANI model

ORANI is built up from explicit microeconomic assumptions about the behaviour of producers, investors and consumers.‘” It describes: (1) the demand for commodities and primary factors (labour, capital and agricultural land) by final and/or intermediate users; (2) the supply of commodities by domestic producers; (3) the relationship between commodity prices and the cost of production; (4) commodity and factor balances; and (5) various descriptors of the macroeconomy (eg GDP, the balance of trade and aggregate price indexes) built up from their components.

The 112 representative producers of ORANI are assumed to be price takers who choose their input mixes to minimize costs subject to nested production functions. No activity earns pure profits. At the first level of the production functions, effective inputs of 114 classes of produced inputs, of primary factors, and of ‘other costs’ (mainly production taxes and working capital) are required in fixed proportions. At the second level, effective units of produced input i are defined as constant elasticity of substitution (CES) combinations of domestic supplies and imports of the ith commodity, while effective units of primary factors are defined as CRESH” combinations of capital, agricultural land, and effective inputs of labour. Finally, at the third level, effective inputs of

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labour are defined as CRESH combinations of 10 occupational groups Industries are single-product producers, except for some multiproduct agricultural industries in which the output mix is assumed to be independent of the input mix, the former being chosen to maximize revenue subject to empirically estimated CRETH12 transformation

frontiers. In the closures of ORANI used here,‘” rates of return are exogenous

and the sizes of the capital stocks in the 111 non-O&G industries adjust endogenously in response to the shocks.14 Investors are assumed to minimize the costs of capital formation subject to production functions for capital goods which allow substitution between foreign and domestic sources of supply.

Households are assumed to be price takers who maximize utility

subject to an aggregate expenditure constraint. The household demand elasticities are estimated from a fitted linear expenditure system. As with intermediate users and investors, a CES aggregator function allows direct substitution between domestic and imported commodities.

In the version of ORANI used here, real government demand moves in proportion to real GNP.

We comment on three other basic features. First, major export

commodities face downward-sloping foreign demand curves with high, but not infinite, elasticities. Second, commodity markets clear (which is not necessarily true of the labour market). Third, explicit trade and transport margins cause producers’ and purchasers’ prices to differ.

In addition to the standard ORANI model as described above a macro-accounting module developed by Horridgel’ was used together with some additional equations of our own.16 As discussed in the next section, these additions make explicit some important macroeconomic details.

“CRETH (constant ratio of elasticities of transformation, homothetic) is the output analoaue of CRESH: see D.P. Vincent, P.B. Dixon and A.A. Powell, ‘The estima: tion of supply response in Australian agri- culture: the CRESHXRETH production system’, international Economic Review, Vol 21, No 1, 1980, pp 221-242. ‘31n a model having more variables than independent equations, it is necessary to set the values of a subset of the variables exogenously. This process defines a clo- sure of the model. 14Recall that the change in the size of the O&G industry is treated as an exogenous shock for our production phase results. 15M. Horridge, The Long-Term Costs of Protection: Experimenfal Analysis with Different Closures of an Australian Com- putable General Equilibrium Model, Un- published PhD dissertation, University of Melbourne, 1987. “These additional equations are de- scribed in more detail in the appendix ‘% principle we allow each of the 112 industries in the model to have different required rates of return (ie supply prices of capital) to allow for varying risk (and perhaps other differences). ‘*In short-run closures of ORANI, capital stocks are held exogenous with rates of return responding to shocks. In the long- run closure reported here it is assumed that by the middle of the construction phase (by about 1986) capital stocks in all industries have adjusted (where neces- sary) to levels consistent with the changes in the economic environment brought ab- out by the project. “These are alternative names for the same phenomenon (see R.G. Gregory, ‘Some implications of growth in the mining sector’, Australian Journal of Agricultural Economics, Vol20, No 2,1976, pp 71-91; and W.M. Corden, ‘Booming sector and Dutch disease economics: survey and consolidation’, Oxford Economic Papers, Vol 36, 1984, pp 359-380). Hereafter we will refer just to the Gregory effect (the term commonly used in Australia).

Economic environment

The economic environment underlying the simulations is determined by our choice of exogenous variables. Key assumptions are discussed below.

We assume that Australia is a small part of the world capital market, and that real rates of return required to obtain finance are not dependent on developments in the Australian economy. Hence our counterfactual simulations take real rates of return on each type of investment17 as exogenously given with no long-run’s changes being induced by the project.

The project is assumed, from the viewpoint of the 197Os, to be a new profit opportunity. Because (in the sense defined above) Australia is seen as a negligible part of the world capital market, no other profit opportunity in these simulations is crowded out by competition for funds. On the other hand, because the operating environment of all Australian industries is affected to a greater or lesser extent by the project, their profitability responds to its existence and hence also their investment and capital stocks. One important example of such general equilibrium consequences captured in our simulations is the Gregory effect or Dutch disease syndrome.” Put loosely, this signifies the deterioration in the trading environment facing other exporters and import competitors resulting from the expansion of mineral exports. Relative to what would otherwise have occurred, this shows up as an appreciation of the real exchange rate.

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201n reality it is likely that both the level of employment and the real wage would change; the exact details of such an out- come would, however, depend on trade union behaviour and on other features not captured in our model. “The Armington elasticity of substitution between domestic and imported oil and gas is set at 50.0, and the price of imported oil and gas is exogenous and set to zero chanae.

Our labour market closure keeps employment exogenous and allows the real wage rate to adjust. Thus we express the project’s good news for labour in terms of the increase in the real wage which would be possible if employment did not also expand.‘”

The main advantage of the Horridge extension of ORANI is explicit treatment of the asset position of Australian residents. Because we do not know how residents would choose to dispose of additional income generated by the project, we arbitrarily assume that they save enough to keep their real assets intact, and consume the balance. Thus changes in real consumption unambiguously capture the welfare of Australian residents.

So much for consumers; but what of the public sector? We assume that the three tiers of government maintain their share of GNP at a combined percentage, with tax rates adjusting to ensure the constancy of this proportion. Real investment in government dominated industries moves in proportion to real GNP, as does other real government spending. The mix of commodity demands made by governments is assumed to be independent of the project.

As explained above, investment, the capital stock, and exports in the O&G industry were set exogenously. It was also necessary to set the domestic price of oil and gas exogenously to ensure that the share of imported oil and gas in the domestic economy remained roughly unchanged.*’ Finally, it was assumed that the world demand curve facing Australian exports of O&G is flat.

Macro results

Table 1 indicates the likely macroeconomic impact of the project for a typical year in its construction and production phases.

Construction phase

The key to understanding the results for the construction phase is that it is similar to an aggregate demand shock. Recall that in this phase there is no additional O&G output. Therefore the additional investment is simply an increase in demand with a particular commodity profile. This increase causes the consumer price index (CPI) and the GDP deflator to rise, which is tantamount to an appreciation of the real exchange rate** and a decline in Australia’s international competitiveness. A symptom of this is the rise in the real wage rate. As a result, aggregate exports are projected to fall and aggregate imports to rise. The increase in aggregate imports also reflects the general expansion in demand and in particular the demand for imports by the project. The fall in exports and the increase in imports lead to a decline in the balance of trade.23

The project’s construction activity is reflected in a relatively signifi- cant increase in real private investment in Table 1. Investment by the government sector is constrained by our assumption that it moves in line with GNP.

In summary, the construction phase is not expected to have much impact on real GDP, real GNP, or real household consumption.

‘qhe nominal exchange rate is exoge- nous and set to zero change. Production phase

23Note that the balance of trade is mea- sured as a percentage of GDP at the start

The production phase is expected to produce a significant increase in

of a typical year during the construction aggregate exports which leads to further appreciation of the real

phase. exchange rate, as reflected by increases in the domestic price indices.

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‘In our closure of the model these price index values merely indicate a change in the real exchange rate. bFor the purpose of interpreting the aggregate export projections it is important to note that our model’s database reflects the 1980-81 economy rather than today’s economy. In 1980-81 the price of a barrel of oil was roughly US$35.65 whereas today it is approximately US$20. The general equilibrium model’s projection was for a 5.113% increase in aggregate exports during the export phase. However, this is an overestimate as the contribution of oil to aggregate exports in the model is based on a price of US$35.65 per barrel. If there were no complications involving Gregory effects, this overstatement would be corrected by scaling the aggregate export projec- tions by 0.56 (ie $20/$35.65). Such a calculation would yield an aggregate export response of 2.9%. The scale factor of 0.56 must be revised upwards, however, to take account of the dimin- ished pressure placed on other export industries when the export price of oil is $20 rather than $35.65. Thus a conservative estimate of the net effect of the project on aggregate exports is 3%.

Australia’s North-West Shelf Gas Project

Table 1. Macroeconomic projections.

Variable

(% deviation in a typical year from situation with no North-West Shelf Gas Project)

Consumer price indexa GDP deflate? Real household consumption Real total investment Real private investment (including North-West Shelf) Real government expenditure Aggregate exports (foreign currency value) Aggregate imports (foreign currency value) Change in balance of trade (% of GDP) Real GDP Real GNP Real wage rate

Construction Production phase phase [II WI

0.19 1.75 0.21 1.99 0.01 0.99 0.72 4.38 1.58 -1.76 0.01 0.76

-0.95 3.00b 0.30 1.33

-0.14 0.42 -0.02 1.06

0.01 0.76 0.09 0.89

This appreciation and the increase in the size of the economy (as shown by the results for real GDP and GNP) cause aggregate imports to rise. However, the net effect is an improvement in the balance of trade.

The labour market is stimulated by the production phase. The projected increase in the real wage rate in Table 1 reflects both indirect income and expansion effects and direct effects in the O&G industry. Real GDP, real GNP, and real household consumption also register rises; aggregate investment, however, experiences a moderate decline.

Sectoral results

The results in Table 2 show the sectoral implications of the project for a typical year in its construction and production phases.

Construction phase

The industries benefiting most from the construction phase are services to mining (17), construction machinery (77), other machinery and equipment (78), and other construction (88). All are significant sup- pliers of investment goods to the project.

To explain the remaining results in the first column of Table 2, it is convenient to distinguish three main groups on the basis of their international trade exposure: the export, import competing, and non- traded sectors. The export sector comprises Australia’s traditional exporters, namely agricultural and agriculturally based industries (l-4, 18, 25 and 30) and mining industries (12-14 and 64), all of which experience a contraction in output. This is due to the loss of international competitiveness noted above. Another adversely affected group con- tains the following export-related industries: agricultural industries (5), (6) and (S), agricultural services (9), chemical fertilizers (49), ships and boats (69), agricultural machinery (76), road transport (93), and rail and other transport (94). These industries depend on sales to exporters and so are expected to suffer moderate declines in output during the construction phase.

The import competing sector can be subdivided according to primary source of demand. The first subgroup is the import competing (in- termediate demand) category, containing industries 31-34, 4&42, 44, 45,48,50,51,55,57,58,62,65,67,71,75 and S&82. Like the exporters

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Table 2. Sectoral projections.

Industry output

(% deviation in a typical year from situation with no North-West Shelf Gas Project)

1 Pastoral zone 2 Wheat-sheep zone 3 High rainfall zone 4 Northern beef 5 Milk cattle and pigs 6 Other farming (sugar, fruit and nut) 7 Other farming (vegetables, cotton, seeds, tobacco) 8 Poultry 9 Agricultural services

10 Forestry and logging 11 Fishing and hunting 12 Ferrous metal ores 13 Non-ferrous metal ores 14 Black coal 15 Oil and gas 16 Other minerals 17 Services to mining 18 Meat products 19 Milk products 20 Fruit and vegetables 21 Margarine, oils and fats 22 Flour and cereal products 23 Bread, cakes and biscuits 24 Confectionery and cocoa 25 Other food products 26 Sofi drinks and cordials 27 Beer and malt 28 Other alcoholic drinks 29 Tobacco products 30 Cotton ginning etc 31 Man-made fibres, yarns 32 Cotton yarns and fabrics 33 Worsted and woollen yarn 34 Textile finishing 35 Textile floor overlays 36 Other textile products 37 Knitting mills 38 Clothing 39 Footware 40 Sawmill products 41 Veneers and boards 42 Joinery and wood net 43 Furniture and mattresses 44 Pulp paper paperboard 45 Bags, fibreboard boxes 46 Paper products net 47 Newspapers and books 48 Commercial printing 49 Chemical fertilizers 50 Other basic chemicals 51 Paints, varnishes 52 Pharmaceutical goods 53 Soap and detergents 54 Cosmetics and toiletries 55 Other chemical goods 56 Petrol and coal products 57 Glass and glass products 58 Clay products, refractories 59 Cement 60 Ready mixed cement 61 Concrete products 62 Non-metallic ore goods 63 Basic iron and steel 64 Other basic metals 65 Structural metal ores 66 Sheet metal products 67 Other metal products 68 Motor vehicles and parts 69 Ships and boats 70 Locomotives 71 Aircraft

Construction phase 111

Production phase tw

-0.30 a.21 -0.23 -0.47 -0.10 -0.67 -0.16 -0.20 -0.21 -0.12 -0.33 -1.64 -1.13 -2.87 -0.04

0.12 8.68

-0.34 -0.01 -0.01 -0.11 -0.06

0.02 -0.03 -0.93

0.01 -0.01 a.11

0.04 a.37 -0.43 -0.30 -0.08 -0.12 -0.05 -0.11 -0.07 -0.05 -0.23 -0.05

0.03 0.06 0.00

a.07 -0.09 -0.02 -0.00

0.01 a.33 XI.16

0.04 a.09 -0.00 -0.02 -0.20

0.06 -0.03

0.01 0.24 0.23 0.23 0.11 0.15

-0.93 0.22

a.02 0.01

a.27 -0.01

0.33 0.02

-2.83 -1.96 -2.10 -4.30 -0.83 -6.28 -1.19 -1.80 -1.70

0.62 -2.98

-15.72 -11.33 -27.25 130.54 a.26 21.49 -3.16 -0.03

0.19 -0.83 -0.48

0.14 0.03

-8.77 0.35 0.48

-0.05 0.33

-3.47 -3.66 -2.49 -0.35 -0.68

0.48 0.61

-0.37 -0.23 -1.96 a.14

0.31 0.43 0.78

-0.52 -0.27

0.12 0.14 0.42

-2.05 -1.72

0.20 -0.24

0.20 0.18

-0.78 0.44

-0.26 0.04 0.34 0.36 0.33 0.39

4.29 -9.78 a.10 -0.41 X1.80 -2.28

0.48 2.67 0.48

continued on page 185

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Table 2 (continued).

Industry output

(% deviation in a typical year from situation with no North-West Shelf Gas Project)

Construction phase III

Production phase WI

72 Scientific equipment 0.01 0 35 73 Electronic equipment 0.07 -0.69 74 Household appliances -0.02 0.45 75 Other electrical goods 0.48 -0.65 76 Agricultural machinery -0.27 -2.63 77 Construction machinery 1.94 -3.09 78 Other machinery and plant 0.46 -0.88 79 Leather products -0.12 -1.17 80 Rubber products -0.09 -0 42 81 Plastic products etc 4.08 -0.94 82 Signs’ writing gear -0.06 -0.29 83 Other manufacturing -0.13 -0.94 84 Electricity -0.10 -0.15 85 Gas -0.01 0.28 86 Water, sewers and drains 0.02 0.87 87 Residential building 0 01 0.82 88 Other constructron 0.40 0.04 89 Wholesale trade 0.03 -0.44 90 Retail trade 0.02 0.71 91 Mechanrcal repairs 0.03 0.78 92 Other repairs 0.10 0.89 93 Road transport -0.04 1.15 94 Rail and other transport -0.47 7.57 95 Water transport -0.16 i .78 96 Air transport 0.05 0.70 97 Communication 0.04 0.66 98 Banking -0.00 0.63 99 Non-banking finance 0.08 0.69

100 Investment and services 0.14 0.86 101 Insurance and services -0.02 0.86 102 Other business services 0.27 0.94 103 Ownership of dwellings 0.01 1.50 104 Public administration 0.01 0.69 105 Defence 0.01 0.76 106 Health -0.01 0.83 107 Education, libraries 0.01 0.77 108 Welfare and religious 0.01 0.71 109 Entertainment, leisure 0.01 0.74 110 Restaurants, hotels 0.02 0.89 111 Personal services 0.02 1.08 112 Non-competing imports 0.01 0.38

and suppliers dependent on them, these industries suffer from the appreciation of the real exchange rate. Industries in the import compet- ing (consumption demand) category sell their goods largely to consum- ers. Industries 7, 20, 21, 24, 27-29, 35-39, 43, 46, 47,52-54, 56, 68, 73, 74, 79 and 83 belong to this group. In general these industries experience a contraction in output in the construction phase. Note that aggregate real consumption hardly changes - see Table 1, column [I]. Thus contraction in these industries is due to loss of market share to imports. The final subgroup is import competing (investment demand), containing industries 66, 70, 77 and 78 which, while suffering from the real exchange rate appreciation, benefit from increased investment demand. As discussed above, industry 78 experiences a net increase in output. The same is true for industries 70 and 77.

The remaining industries belong to the non-traded sector. These neither export a significant proportion of their output nor compete to any significant extent with imports. Their prospects largely depend on the overall domestic market. As the construction phase hardly affects real GDP (see Table 1, column [I]), the output of most of them scarcely changes. Some exceptional cases (eg 59, 60, 61, 88, 100 and 102 - see Table 2, column [I]) benefit from direct sales to the project.

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Production phase

The sectoral effects of the project for a typical year in its production phase are given in the final column of Table 2. The industries that benefit most are those that supply the required intermediate goods or services, the most obvious example being services to mining (17).

The industries that suffer the most are the traditional exporters, namely agricultural and agriculturally based industries (l-4, 18, 25 and 30) and mining industries (12-14 and 64). This is simply the Gregory effect again. The export related industries (5, 6, 8, 9, 49, 69, 76, 93 and 94) in turn are adversely affected.

The projected real exchange rate appreciation reduces real import prices, and thus import competing industries’ prospects. However, the production phase is projected to increase real GDP and consumption. Therefore, although import competing industries experience pressure on market share, in the areas of intermediate production and consump- tion their markets are growing. In the investment area, on the other hand, the market is contracting. The prospects for individual import competing industries reflect the net balance.

The majority of import competing (intermediate demand) industries (namely 31-34, 40-42, 44, 45, 48, 50, 51, 55, 57, 58, 62, 67, 71, 75 and 8&82) experience a contraction in output. On the other hand, the import competing (consumption) industries (namely 7, 20, 21, 24, 27-29, 35-39, 43, 46, 47, 52-54, 56, 68, 73, 74, 79 and 83) show mixed results. Roughly half of them experience an increase in output due to the increase in real consumption generated by the project. The import competing (investment) category consists of industries 66,70,77 and 78. Of these, 66, 77 and 78 suffer significant contractions in output.

Almost all the industries in the non-traded sector are projected to experience an increase in output in a typical year of the production phase. This is because they do not directly suffer from the real exchange rate appreciation but benefit from the increase in demand.

Regional results

Our method requires industries to be designated as either national or local before regional projections are made. National industries are those whose output is traded between states, whereas almost all the output of local industries is sold within state borders. Users of the regional model usually assume that a national industry located in several states records equal percentage output responses in each of them. This assumption was also adopted for this study with the exception of the national O&G industry for which all of the national response was allocated to WA.

The regional model requires that supply equals demand within states for the local industries. One major component of demand for the output of local industries, namely consumption, increases faster than the national average in those states in which labour incomes increase by more than the national average. Another component of demand facing local industries is purchases by national industries. If a state’s economy is highly dependent on national industries which do particularly well (or particularly badly) under a shock, this will be reflected in above (or below) average stimuli to the local industries supplying them.

The effects on local WA industries for a typical year in each phase are shown in Table 3. Reflecting the assumption noted above, the output response of the national industries other than O&G (namely, industries 1-8, 10-14, 16-22, 24, 25, 28-59, 61-85, 93-96, 104, 105 and 112) is the

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Table 3. Local West Australian industry projections.

aAn L signifies that this industry is defined as a local industry in the regional model.

“The entries in the table may be identified with gross state products at factor cost.

RESOURCES POLICY September 1992 187

industry output

(% deviation in a typical year from situation with no North-West Shelf Gas Project)

Construction Production phase phase

111 Bl

9 L” 15 23 L 26 L 27 L 60 L 86 L 87 L 88 L 89 L 90 L 91 L 92 L 97 L 98 L 99 L

100 L 101 L 102 L 103 L 106 L 107 L 108 L 109 L 110 L 111 L

Agricultural services -0.17 Oil and gas -0.48 Bread cakes and biscuits 0.26 Sofi drinks and cordials 0.40 Beer and malt 0.59 Ready mixed cement 3.42 Water, sewers, and drains 1.16 Residential building 1.48 Other construction 4.76 Wholesale trade 1.49 Retail trade 0.67 Mechanical repairs 1.06 Other repairs 1.39 Communication 1.08 Banking 0.98 Non-banking finance 1.37 Investment and services 1.53 Insurance and services 0.91 Other business services 2.08 Ownership of dwellings 1.47 Health 0.56 Education, libraries 0.20 Welfare and religious 0.47 Entertainment, leisure 0.92 Restaurants, hotels 1.07 Personal services 1.21

-1.47 1576.52

1.37 1.81 2.97 3.66 5.04 6.67 1.79 3.41 3.14 3.82 9.71 4.82 5.22 5.48 6.32 7.03 5.31 7.34 3.11 1.64 2.76 4.20 4.87 5.67

same as reported in Table 2. The output response for the WA O&G industry (15) as reported in Table 3 is much larger than that reported in Table 2. This is due to the location of the project and to the fact that the projections in Table 3 are changes relative to the preexisting local industry. Finally, it can be seen from Table 3 that, with the sole exception of services to agriculture (9), all the WA local industries enjoy significant benefits from both phases.

The regional model also provides estimates, presented in Table 4, of the project’s impact on gross state productions (GSPs). As expected, WA benefits the most in both phases. Due to the importance of export industries to its economy, the state to lose most is Queensland (the Gregory effect at work again). The other losers are Tasmania and New South Wales. Again this is primarily due to the contraction in export oriented industries located in these states. To take a leading example, consider the worst hit of the national industries, black coal (14). According to the model’s database, 56% of this industry is located in NSW. The industry is relatively large, moreover, accounting for over 2% of gross state product. It follows that the decline in the output of

Table 4. Gross regional products.’

Gross regional product

(% deviation in a typical year from situation with no North-West Shelf Gas Project)

New South Wales and Australian Capital Territory Victoria Queensland South Australia and Northern Territory Western Australia Tasmania Australia

Construction Production phase phase [II [III

-0.14 a.37 -0.05 0.34 -0.23 -1.88

0.02 0.15 0.79 12.01

-0.14 xl.74 a.02 1.06

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black coal is more than sufficient to explain the drop in the GSP of NSW. On the other hand, South Australia and Victoria gain (at least in the production phase). This is largely due to the stimulus in aggregate demand generated.

Conclusion and research perspective

Because of the scales of its investment spending and hydrocarbon output, the project has had and will continue to have substantial and pervasive effects on the WA and Australian economies. Contrary to some expectations, effects on macroeconomic variables such as real GDP during the construction phase are dwarfed by those of the production phase. The concentration of stimulatory effects in the state of the project’s location (WA), however, is in line with expectations.

We conclude by noting some areas for future research. The impact of the project was estimated above by imposing a number of exogenous shocks on the preexisting O&G industry in the ORANI model. While this was successful in capturing the key effects, it would not remain optimal with greater resources and time. Given the latter, a better strategy would recognize both the preexisting O&G industry and a new one having the exact sales pattern and cost structure of the project. It might also be possible to improve the regional projections by construct- ing a bottom-up multiregion mode124 which could be expected to yield a

“Such a major extension presupposes a better locally detailed account of responses to shocks which (like the

very large data mobilization effort. project) originate at the state level.

Appendix

Documentation of the economic model

Equations

The equations of the national econo- mic model are those of the ORANI as implemented under the TABLO facility of the GEMPACK software suite,2” plus a macro-accounting mod- ule consisting of Equations (l)-(8) together with equations defining vari- ables 108 and 109 as listed by Horridge,2h and five additional equa- tions. Of the last mentioned, the first two are definitional, the third is an expenditure function for government, the fourth describes the ownership by Australians of the capital stock located in Australia, while the fifth ensures that real investment in government dominated industries moves with real GNP.

Regional results are obtained by a top-down disaggregation of the national model using the ORES sys- tem of regional equations,*’ modified

to accommodate the current applica- tion. (Specifically, output, investment and export response for the national O&G industry was attributed solely to the WA industry.)

Database, parameter settings and software

The bulk of the database and parameter settings are described by Kenderes, and Kenderes and Strzelecki.28 Note the following settings of some key parameters: oKL = 1.28 (a long-run value for the labour/capital substitu- tion elasticity); Horridge’s h = 0.45, a parameter reflecting our assumption about the adjustment path of saving; and yL7 = lo-‘, a parameter implying that the foreign currency price elas- ticity of demand for Australian exports of fluid fossil fuels is -106.

The regional database used was the standard 198@81 ORANI regional

data file (regdat81,dat) extracted from the Melbourne Institute of Applied Economic and Social Research’s ORES program library.*’ The regional consumption parameters cQ(Us) (for all states, commodities and sources of supply) and y were both set to unity.

The model is solved using the soft- ware package GEMPACK mounted on a Toshiba 5200/100 laptop personal computer.‘0

Closure

A list of the variables chosen as exoge- nous for each of the simulations is available from the authors. Some de- tails concerning the key non-zero ex- ogenous shocks are given below.

The exogenous shocks

Construction phase Simulating the effects in a typical year of the construction phase involved

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ABARE,“s the price of Arab light crude per barrel has fallen from US$35.65 in June of 1980 to the assumed US$20.00. Thus, if the volume of exports required to gener- ate A$2 billion worth of exports in the production phase had been exported in 1980-81 it would have yielded A$3.565 billion (ie A$2 billion x

US$35.65/US$20.00). However, the value of the Australian dollar has since fallen from A$1 = US$l.1612 in 198s-81 to the assumed exchange rate of A$1 = US$O.75. Thus, in terms of 198&81 Australian dollars the new O&G exports are worth A$2.303 bil- lion (ie A$3.565 billion x 0.75/ 1.1612).

three steps. In the first, the overall increase in O&G investment was re- lated to that in the preexisting indus- try. In the second, the pattern of investment demand generated by the project was estimated. Finally, the database was modified to reflect the new investment profile so that the appropriate investment supplying in- dustries would respond to the invest- ment surge.

Overall increase in investment

As noted in the text, over the period 1980 to 1993 the project will have involved total expenditure of A$8.7 billion, consisting of a mixture of nominal dollars for different years.” To match the calibration date of our model, this sum had to be converted to 198(k81 dollars. To do this the investment stream was split in two, the first covering the A$6.1 billion spent over 1980 to 1989 and the second, the A$2.6 billion planned for 1990 to 1993. It was assumed that annual infla- tion over 1980 to 1993 would be 8% and that the A$h.l billion spent over the decade ending in mid-1990 flowed at the uniform annual rate of A$0.61 billion. Discounting this flow at 8% gives a total of A$4.42 billion (198C 81 prices).‘2 It was also assumed that the A$2.6 billion planned to be spent over the triennium 1990-91 to 1992-93 will be spent at the annual rate of A$0.87 billion, yielding a real total of A$1.12 billion pa. Thus total real in- vestment to mid-1993 is roughly A$5.54 billion. Hence in a typical year of the 13 year investment phase addi- tional real investment due to the pro- ject is reckoned at A$().43 billion (= .5.54/13). Real investment in the preexisting O&G industry in the model’s database is A$l.OO billion. Thus the overall increase in real invest- ment in a typical year is equal to 43% (ie (A$0.43 billion/A$l.OOl billion) X 100) and the construction phase exogenous shock is ~(15) = 43.0. Finally, note that in term of 1989-90 dollars, A$0.43 billion (real) is equiv- alent to A$0.85 billion.

Pattern of investment demand

A useful starting point is the overall size of major project components:

North Rankin A$2.0 billion; DOM- GAS A$O.S billion; LNG trains 1 and 2 A$3.0 billion; LNG train 3 and related facilities A$1.3 billion; and Goodwyn A$1.5 billion. On the basis of confidential information provided by Woodside, estimates were made of the pattern of investment demand across the ORANI commodities required to build each of the above components. The investment profile of the project in practice turned out to be insufficiently different from the industry wide profile contained in our database for this refinement to have much effect on the results.

Production phase

Simulating the production phase in- volved two shocks: (1) an increase in the size of the capital stock in the O&G industry; and (2) an increase in exports of O&G. To find the right size for the first shock, we had first to estimate the size of the capital stock in the preexisting industry. We did this by capitalizing the returns to capital as given in the model’s database for the O&G industry, using the following equation:

Asset value = rental/(rate of return + depreciation rate)

The return to capital (rental) in the O&G industry is A$788.097 million (real); the denominator above was taken to be 0.14, or 14% real, com- prising a 4% risk free return, 2% risk premium and 8% depreciation. This calculation puts the real size of the O&G capital stock at A$5.629 billion. Finally, the project’s cumulated real investment of A$5.54 billion must be compared with this figure, yielding an increase in the capital stock of 98% (ie A$5.54 billion/A$5.63 billion) x 100).

Exports

As seen above, in a typical year of its production phase the project is ex- pected to generate about A$2 billion (1989 prices) worth of exports. The next step is to put this figure on a real basis, which involves accounting for changes in the world oil price and the US$/A$ exchange rate between 198CXl and 1988889. According to

In the ORANI database real ex- ports of O&G are A$227.358 million. Thus, the new exports of A$2303 mil- lion (real) means an increase of 1012.9% (ie (A$2303.0/A$227.358) x 100).

25See DPSV for the core of the ORANI model: for its TABLO implementation (in- cluding some minor modifications) see G. Codsi, M. Horridge, and K. Pearson, An Implementation of ORANI Us/no the GEM- PACK Program TABLO, Impact Project Computina Document No C8-01. University of Melbourne, September 1988; p 76. 260p tit, Ref 15, p A211 7 and pp A2/15-A2/ 16 respectively. 270p cif, Ref 5, Chapter 6; ORES consists of their Equations (39.2) (39.8), (39.11) (39.12) (39.18) (39.21) (39.22) (39.34) (39.26) and (39.38). Equations (39.2), (39.1 l), (39.24) and (39.26) were modified to accommodate the current application. ‘*M. Kenderes, The 1977-78 REGlON 78 Data Base, Impact Project Research Memorandum, Archive No OA-260. Indus- tries Assistance Commission, Canberra, 1984; OP cit. Ref 8: M. Kenderes and A. Strzelecki, A List;ng of fhe 7980-81 ORANI Database: Balanced and with Typical Year Data in Agriculture, Impact Project Research Memorandum, Archive No OA-438, Industries Assistance Com- mission, Canberra, 1988. 29This file in turn is based on D. Clark, State Shares in Australian Industrv Out- puts: Mining, Manufacturing and coktruc- tion, 1983184, University of Melbourne, IAESR Research Paoer No 411987. April 1987; on T. Lawson, I\lotes on Creating the REGION 78 1977-78 Data Base. Impact Project Research Memorandum, Archive No OA-246, Industries Assistance Com- mission, Canberra, 1984; and on M. Ken- deres, The 1977-78 REGION 78 Data Base, Impact Project Research Memoran-

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dum, Archive No OA-260, Industries Assistance Commission, Canberra, 1984. “See K.R. Pearson, ‘Automating the com- putation of solutions of large economic models’, Economic Modelling, Vol 7, 1988, pp 385-395; and G. Codsi and K.R. Pearson, ‘GEMPACK: general-purpose software for applied general equilibrium and other economic modellers’, Computer

190

Science in Economics and Management, Vol 1,1988, pp 189-207. GEMPACK uses the sparse matrix routines written by I.S. Duff: see his MA28 - A Set of FORTRAN Subroutines for Sparse Unsymmetric Linear Equations, Harwell Report Ft. 8730, HMSO, London, 1977. “This differs from the A$12 billion capital cost reported in Woodside (op tit, Ref 2, p

122). However, the Woodside figure in- cludes expenditure on a third off-shore platform which is not included in the A$8.7 billion estimate. 32To avoid repetition of the phrase ‘in 1980-81 prices’, below we will just refer to real dollar amounts, it being understood that the dollars are so valued. 330p tit, Ref 9.

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