quality adjusted prices for australia's black coal...

Quality adjusted prices for Australia's black coal exports

Quality adiusted prices for Australia's black coal exports

ABARE report to the

Department of Primary Industries and Energy

Lindsay Hogan, Sally Thorpe and Simon Middleton

October 1997

- e ABARE

Hogan, L., Thorpe, S. and Middleton, S. 1997, Quality Adjusted Prices for Australia's Black Coal Exports, ABARE report to the Department of Primary Industries and Energy, Canberra.

Australian Bureau of Agricultural and Resource Economics GPO Box 1563 Canberra 2601

Telephone +61 2 6272 2000 Facsimile +61 2 6272 2001 Internet www.abare.gov.au

ABARE is a professionally independent government economic research agency.

Acknowledgments This report was funded by the former Coal Development Branch in the Department of Primary Industries and Energy under the Coal Australia Promotion Program (CAPP). It represents part of the Commonwealth government's response to the recommendations in the Taylor study of the black coal industry in Queensland and New South Wales. The authors wish to thank Luan Ho Trieu of ABARE for help with the early econometric analysis, and Robin Bryant, Jim Collins, Rob Jenkins and Steve Payne who were with the Coal Development Branch. The authors also acknowledge that commentary of coal market analysts was useful to this study.

ABARE project 1387

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Contents

Summary 1

I . Introduction 3

2. Australia's coal exports Coal export volumes Coal export prices Coal quality

3. Coal priceequality data and estimation method 20

Australia's coal export controls database Hedonic pricing models and estimation method

4. Quality adjusted prices for Australia S coal exports 38

Estimated coal price-quality relationships Estimated quality adjusted coal prices

5. Conclusion 55

Appendixes A General hedonic price relationships 56 B Correlation coefficients for the quality characteristics of Australia's

coal exports to Japan 59 C Use of dummy variables in estimating price-quality relationships 70 D Econometric results 76

References 81

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Boxes 1 Use of coal in iron and steelmaking 2 Use of coal in electricity generation

Figures A Composition of coal 14 B Changes in properties of the organic matter with degree

of coalification 17 C Indicative price-quality relationships for metallurgical coal 35 D Prices for Australia's metallurgical and thermal coal exports - .

to Japan 48 E Prices for Australia's metallurgical and thermal coal exports

to North Asia 50 F Quality adjusted metallurgical and thermal coal prices for

all regions 52

Tables Australia's coal exports, by destination Contracts available from the coal export controls database Average coal prices from the export controls database: all contracts Description of coal quality data Quality adjusted prices for Australia's coal exports: all contracts Deviation of quality adjusted coal prices from average prices: all contracts Correlation coefficients for quality characteristics: metallurgical coal Correlation coefficients for quality characteristics: thermal coal Econometric results

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Summary

Quality adjusted prices for Australia's black coal exports for Japanese fiscal years (JFY) 1989-96 have been estimated in this study using price and quality information from the Australian government's coal export controls database. Quality adjusted coal prices have been estimated using the average quality of Australia's coal exports in JFY 1995 (JFY 1994 for soft coking coal). These prices account for changes in coal quality over time and between regions, thus providing a more accurate indicator of underlying coal price movements. Given Japan's dominant position in the regional coal market, the estimated quality adjusted coal prices can be used to assess the extent to which prices of coal exported to Japan differ from coal prices in other markets.

Australia's metallurgical coal exports are divided into three categories - hard coking coal, soft coking coal, and semisoft coking and pulverised coal injection (PCI) coal. Thermal coal is classified according to the end use, including electricity generation, cement manufacture and general industrial use. A number of coal attributes, such as fluidity, vitrinite reflectance and coke strength after reaction, were not available from the coal export controls database and were not included in the study. To the extent that any of these excluded quality characteristics are important determinants of coal price, the reliability of the estimated quality adjusted prices is reduced.

Quality adjusted coal prices will be similar to average coal prices to the extent that, for each coal category, coal quality is relatively stable and for each region

: similar to the average coal quality. There are a relatively large number of cases where the percentage deviation of the regional quality adjusted coal price from the average price exceeds 1 per cent, but relatively few where it exceeds 5 per cent. The main differences between quality adjusted and average coal prices are for semisoft coking and PC1 coal and, with the exception of electricity generation in Japan, for thermal coal. These results are consistent with general expectations that there is greater uniformity in the price-quality relationships for hard and soft coking coal exports and thermal coal exports to Japan's electricity sector than for other coal categories.

Price differences between metallurgical coals exported from Australia to Japan (Australia's largest export market) tend to be slightly smaller when based on quality adjusted prices rather than average prices. Nevertheless, the quality adjusted price gap was still large in the study period, with quality adjusted hard coking coal prices, for example, about 19 per cent higher than quality adjusted

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semisoft coking and PC1 coal prices in JFY 1995 and JFY 1996. By contrast, quality adjusted prices of coal used for electricity generation tend to be marginally higher than average prices, while quality adjusted prices of thermal coal used in either general industry or cement manufacture tend to be slightly lower than average prices. Hence, the price gaps between different thermal coal end uses tend to be slightly larger when based on quality adjusted prices rather than average prices.

Quality adjusted prices of Australia's hard and soft coking coal exports to Japan are consistently about US$0.3-0.4 a tonne (in JFY 1995 prices) higher than quality adjusted prices for North Asia. This relationship is reversed for the semisoft coking and PC1 coal category, with quality adjusted prices for north Asia slightly above those for Japan. Quality adjusted prices for hard coking coal exports to west Asia tend to fluctuate somewhat, but are similar to quality adjusted prices for Japan in several years.

By contrast, quality adjusted prices for thermal coal exports to Japan are consistently higher in each end use category than those for north Asia, the major alternative market for Australia's thermal coal exports. However, the price gap has narrowed considerably since JFY 1993 to close to US$1 a tonne, particularly for coal used in cement manufacture and general industry. Greater regional variability in quality adjusted thermal prices in specific end use categories is partly explained by the relatively larger number of spot sales of thermal coal which are subject to short term market influences and a relatively small number of shipments to some regions. Consistent with higher transport costs to end market, quality adjusted prices for Europe and the Americas tended tdbe at least US$2 a tonne lower than prices for Japan across the study period (with the major exception being metallurgical COG exports to ~ u r o i e in JFY 1994-96).

Overall, based on the estimated quality adjusted prices for each of the major coal categories, Japan tends to pay a price premium for thermal coal but not for metallurgical coal. These results are not consistent with Japan taking advantage of any potential market power, at least in terms of paying lower prices relative to those paid by other countries in the region. However, there is still the issue of whether Japan is able to influence the absolute level of coal prices in the regional coal market.

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I . Introduction

Black coal is Australia's single most important export commodity, with exports estimated to be valued at $7.9 billion in 1996-97 - $4.7 billion for coking coal exports of 78 million tonnes and $3.1 billion for thermal coal exports of 68 million tonnes (ABARE 1997). In a major study into the black coal industry in Queensland and New South Wales, Taylor (1994) noted that it is difficult to assess whether the collective buying practices used by both the steel mills and the power utilities in Japan have resulted in lower coal prices to this market. A key reason for this difficulty is that coal price comparisons over time and between regions may be distorted by the impact of differences in the quality of coal traded.

Associated with the Taylor study recommendations concerning coal market transparency, the objective in this study is to estimate quality adjusted prices for Australia's black coal exports using the Australian government's coal export controls database. Quality adjusted coal prices account for coal quality differences, thus providing a more accurate indicator of movements in underlying coal prices for specified coal categories both over time and between different export markets. The estimated quality adjusted coal prices could be particularly useful in assessing the extent to which prices of coal exported to Japan differ from coal prices in other markets.

The coal export controls database contains information on coal shipments from Australia between 1989 and 1996. Before March 1996, companies were required under the Commonwealth government's coal export controls approval process to notify the Department of Primary Industries and Energy (DPIE) about details of the proposed transaction to obtain an export permit. Details were required on the price, quantity and quality of the coal for each coal transaction. A small number of settlements were rejected under this policy, although some of these were renegotiated at higher prices. The present Commonwealth government, elected in March 1996, automatically approves transactions but still records the details.

In this study, quality adjusted prices are estimated for Australia's coal exports to Japan, north Asia, south Asia, west Asia, Europe and the Americas for JFY 1989-96 (years beginning 1 April). Hedonic regression techniques are used to estimate price-quality relationships in Australia's coal exports and the quality adjusted prices are calculated as the prices that would have been received for coal (in each major coal category) with a constant set of quality characteristics

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both over time and between regions. The metallurgical coal categories include hard coking coal. soft cokine coal. and semisoft cokine and PC1 coal. Thermal coal is clalified according &end "se, including electrycity generation, cement manufacture and general industrial use.

Hedonic pricing models have been widely used to estimate the impact of varying quality on the prices received for a wide range of commodities. The hedonic pricing method is explained in Bemdt (1991), Deaton and Muellbauer (1980) and Rosen (1974). Traditional applications of this approach have been in agricultural markets - for example, Bowman and Etheridge (1992), Gleeson, Lubulwa and Beare (1993), Golan and Shalit (1993), Lame (1991), Mercier, Lyford and Oliveira (1994), Oczkowski (1994) and Payne and Whan (1971) - and more recently in the context of wool futures - for example, Lubulwa et al. (1997).

Hedonic pricing studies for Australian coal include Porter and Gooday (1990), Low et al. (1993). Koerner (1993,1996). Tang andLa Croix (1994) and Chang (1995). ~ & i o u s c o a l quality charact&ristics were found to be significani determinants of price, but quality adjusted coal prices were not calculated in any of these studies. The usefulness of these latter studies has also been constrained by the relatively limited price and quality data for Australia's coal exports. The DPIE export controls database represents the most compre- hensive information available for this type of analysis.

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2. Australia's coal exports

An understanding of coal pricing arrangements and coal quality attributes is essential in constructing and interpreting empirical models of coal price- quality relationships. The quality of coal varies widely and this can have a significant impact on its possible end uses and thus on the price received. Therefore, coal contracts commonly involve price penalties for variations in coal qualities outside set specifications.

Coal is classified into broad groups depending on the end use and the manner in which the coal performs its function for that end use. These include metallurgical coal - hard coking, soft coking, semisoft coking and PC1 coals -and thermal coal. Coking coal is mainly used to produce the coke required in iron and steelmaking. Premium or hard coking coal is a necessary input in making hard coke. Weaker (soft and semisoft) coking coals are also used in the coking coal blend to minimise costs, although within technical limits. Reflecting changing conditions in the Japanese market, soft coking coals were placed in the semisoft coking coal category in early 1996. PC1 coal is pulverised and injected into the base of the blast furnace, which reduces the volume and quality requirements for coking coal in the traditional steelmaking process, and thermal coal is used mainly for combustion purposes in electricity generation, cement manufacture and general industry.

Coal export volumes Australia is the world's largest coal exporting nation, accounting for 43 per cent and 25 per cent of the world's metallurgical and thermal coal exports respectively in 1995-96. Australia's metallurgical and thermal coal exports, on a quantity basis, are given in table 1 for the major countries and regions of destination.

Between 1989-90 and 1995-96, Japan's share of Australia's metallurgical coal exports fell from 51 per cent to 33 per cent. By contrast, India has become a significant coking coal export market, with a market share of 13 per cent in 1995-96. The relative fall in the importance of Japan reflects relatively stronger growth in steelmaking in other countries and technological innovation which has reduced coal input requirements in steelmaking. The relative importance of the Asian and European markets for Australia's metallurgical coal exports has declined in recent years from 66 per cent and 20 per cent respectively in 1989-90 to 61 per cent and 17 per cent respectively in 1995-96.

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In contrast to the declining metallurgical coal export share, Japan's share of Australia's thermal coal exports has increased in recent years, reaching 57 per cent in 1995-96. The importance of South Korea and Taiwan in Australia's thermal coal trade has also increased, these countries accounting for 16 per cent and 11 per cent of exports respectively in 1995-96. Overall, the relative importance of the Asian market for Australia's thermal coal exports has increased markedly in recent years - up from 81 per cent in 1989-90 to 92 per cent in 1995-96. This increase largely reflects strong growth in electricity generation in this region.

Coal export prices

Coal pricing arrangements Australia's coal exports are sold under long term contracts (which cover sales for more than one year) or term contracts (which cover sales for a period of

I Australia's coal exports, by destination

1989 1990 1991 1992 1993 1994 1995 Unit -90 -91 -92 -93 -94 -95 -96p

Metallurgical coal Quantity

Asia India Mt 0.0 0.0 3.3 5.5 7.7 8.9 9.9 Japan Mt 30.8 31.4 28.8 31.1 28.6 30.4 25.2 South Korea Mt 5.1 5.7 6.8 8.8 7.8 8.6 7.9 Taiwan Mt 2.8 3.2 2.8 2.8 2.7 3.0 3.1 Other Asia Mt 1.4 1.1 1.3 1.6 1.6 1.1 0.8 Total Asia Mt 40.2 41.5 43.0 49.8 48.3 52.0 47.0

Europe a Mt 12.0 10.3 12.0 12.2 13.5 13.8 13.0 Other Mt 8.5 10.1 10.0 7.5 8.1 7.6 17.3 Total exports Mt 60.6 61.9 65.1 69.5 69.9 73.3 77.3 World exports % 33.4 33.7 36.6 38.5 40.7 42.9 43.4

Thermal coal Asia

Japan Mt 25.3 26.7 31.4 32.8 32.8 34.6 35.0 Hong Kong Mt 2.4 3.5 4.0 3.8 3.4 2.7 1.6 South Korea Mt 3.4 4.9 5.2 6.7 8.7 8.8 9.6 Taiwan Mt 3.1 4.1 3.8 5.5 5.7 5.4 6.8 Other Asia Mt 1.5 1.2 1.2 1.8 1.2 2.2 3.4 Total Asia Mt 35.7 40.4 45.6 50.6 51.8 53.6 56.4

Europe a Mt 7.5 10.1 11.7 7.7 6.1 7.1 2.8 Other Mt 0.8 0.9 0.8 1.4 1.3 2.2 2.0 Total exports Mt 44.0 51.5 58.2 59.7 59.2 62.9 61.2 World exports % 22.0 23.4 26.1 26.7 25.4 28.5 24.9

Continued 0

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up to one year), or as spot sales (which cover a particular sale). Australia's metallurgical and thermal coal exports are mainly sold under long term contracts to steel mills and electricity utilities respectively, whereby prices and tonnage are reviewed on an annual basis. However, a large number of spot sales of thermal coal are also made to the cement and general industry sectors.

Coal pricing arrangements between Australia and Japan are described in various industry reports and publications such as Australian Coal Association and ACIL (1994), Bowen and Gooday (1993), Colley (1995), Porter and Schmitz (1995) and Taylor (1994). Benchmark prices for the major coal types were negotiated on an annual basis before JFY 1996, although the negotiations were not always concluded before 1 April. The first stage in these annual price reviews was typically for Japan's steel mills to negotiate benchmark prices for hard coking coal with Australia, the United States and Canada. This was usually followed by price negotiations for other metallurgical coals.

1 Australia's coal exports, by destination (continued)

Metallurgical coal Asia

India Japan South Korea Taiwan Other Asia Total

Europe a Other Total exports

Thermal coal Asia

Japan Hong Kong South Korea Taiwan Other Asia Total

Europe a Other Total exports

Unit

% % % 70

70

% % % %

% % % % % % 70

70

%

1991 1992 1993 -92 -93 -94

Market shares

s Mainly Eumpean Union. p Preliminary. Sources: ABS, lnrernarional Trade, electronic database, cat. no. 5464.0, Canberra; Depmment of Foreign Affairs and Trade, electmnic database compiled from trade data provided by the ABS.

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Separate negotiations were held between representatives of the Japanese steel mills' ioint ourchasing cartel and selected revresentatives from the coal - - - supplying companies of each exporting nation. In practice, the Japanese steel mills negotiated with individual sellers onlv, and the vrice that was negotiated with oneseller became the benchmark that all other producers tended to accept. BHP Australia Coal, Australia's largest coal company, often took a leading position in the negotiations by being the first to reach agreement on coking coal prices with Japan's steel mills. Historically, prices received for the benchmark hard coking coals strongly influenced the prices received for the remaining coals traded in the Pacific Rim area (Coddington 1996).

Japan's steel mills abandoned benchmark pricing in the annual Japanese coal contract negotiations for JFY 1996 and adopted the 'fair treatment system'. It reflects theconcern that the individual steel &lls were getting unfair treatment in that the price paid for a coal did not reflect the coal's value in use in particular steel mill; (lnt&national Energy Agency 1996; BZW 1996). under the new system, each coal company negotiates with individual steel mills over coal price, quantity and quality. Until recently, Japan's steel mills also jointly negotiated all annual contracts for benchmark semisoft coking coals.

All thermal coal purchased under annual contract by Japan's power utilities is priced according to a negotiated benchmark price adjusted for the relative calorific values of the coals. 'Qpically, annual contracts for thermal coal shipments to smaller Japanese buyers for general industrial use and cement manufacture are the last to be negotiated, although price changes no longer tend to follow Japan's power utilities' benchmark.

The benchmark price for all long term thermal coal transactions with Japan's power utilities is coal with a calorific value of 6700 kilocalories per kilogram on a gross as received basis. There is no single benchmark price for each coking coal type traded long term with Japan's steel mills, but relative price movements for Australian coals tend to be relatively stable. Consequently, representative coking coal brands which are widely traded and which account for sizable volumes of trade have tended to serve as indicative benchmark prices for the various types of coking coals. (These benchmark coal prices are included in figure D in chapter 4 together with quality adjusted prices and export unit values for Australia's coal exports to Japan.)

Published coal price information ABS export unit values The main official source of national coal price information is customs unit values -fob prices for exporters and cif prices for importers. The Australian

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~ u r e a u o f Statistics publishes export unit values for New South Wales and Queensland on a monthly basis by country of destination for hard coking coal, semisoft and PC1 coal, other coking coal and thermal coal. This dataset has a finer level of coal categorisation than is available for many other coal trading nations. Export unit values indicate broad movements in prices for the major coal types.

Barlow Jonker publications The Barlow Jonker indicator (BJI) price series, expressed in US$ a tonne fob, is published weekly in COALFAX. The BJI price pertains to shipments ex Newcastle of coals spot traded in the industrial market. Its coverage is coal with 15 per cent maximum ash, 0.75 per cent maximum sulphur and a calorific value of 6700 kilocalories per kilogram. Prices are based on actual shipments where possible, and a panel of traders and shippers provide price estimates where actual data are not available.

The Australian Coal Report, published by Barlow Jonker, includes monthly export unit values from the ABS coal trade statistics and a collection of useful derived price aggregates for the main destination regions of Australia's coal exports. The Coal Marketing Manual is an annual publication which includes price and quality specifications for Australian coals traded long term to key markets. The South African Coal Report, published by Barlow Jonker, provides a monthly steaming coal marker price for spot coal exported to Europe.

Coal Week International Coal Week International, published by McGraw-Hill, includes a monthly thermal coal price table which specifies, in US$ a tonne fob on a gross as received basis for the world's main coal export ports, ash and sulphur contents as well as kilocalories per kilogram for a coal price range. Similar to the thermal coal trade press, Coal Week International includes a monthly coking coal price table, mainly covering hard coking prices at key export ports. This specifies volatile matter and ash and sulphur contents for a coal price range in US$ a tonne fob.

ZEA's Coal Znfomtion A selection of the main coal indicator price series monitored in the trade press is reproduced in the International Energy Agency's annual publication Coal Information (International Energy Agency 1996). As an annual indicator of the prices for thermal coals traded long term into Asia, the Agency reports the

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New South Wales benchmark price to Japan's power utilities in US$ a tonne fob. The New South Wales benchmark coal has a heating value of 6700 kilocalories per kilogram on a gross air dried basis. All long term contracts with Japan's power utilities are based on a common price when measured fob in energy equivalents. The South African price, expressed in US$ a tonne fob paid to ENEL of Italy, is a key indicator price for thermal coal into Europe.

Representative monthly spot prices for thermal coals into Asia and Europe (reproduced in Coal Information) are the Taipower tender price and the ~ c ~ l o s k e ~ Coal ~nformition services (MCIS) marker price respectively. The Taipower mice is evaluated on a US$ a tonne cif basis at 6200 kilocalories per kilogram on a gross as received basis, while the MCIS is a volume weighied average of the US$ a tonne cif prices received for most coal imports to Europe. All prices in the MCIS are adjusted to 6000 kilocalories per kilogram for coals of 1 per cent or less sulphur content, and coals of higher sulphur content are excluded from the calculation.

Tex Report's Coal Manual Coking coal price-quality information in Coal Information and in several annual publications of the coal trade press mainly pertains to Japan (TEX Report 1996). Most of this information is available in the Tex Report's Coal Manual. This is also similar to the information provided in Barlow Jonker's Coal Marketing Manual. The Tex Report's Coal Manual includes annual US$ a tonne fob price and quality specifications for the main coking coal brands traded long term with Japan. Most of this information is sourced from suppliers' press releases issued at the completion of the annual contract negotiations. However, with the introduction of the 'fair treatment system' in JFY 1996, this principal source of information has become commercial-in- confidence.

Coal quality Several important attributes of coal can be used to summarise the quality of the coal. These quality characterisiics refer to either the composition or properties of the coal which influence its direct ability to perform the function required in the transport or end use of the coal. The function of coal in the major coal end uses - steelmaking and electricity generation - are described briefly in boxes 1 and 2 respectively. A specification range of several quality characteristics for various end uses is given in Quinn and Calcott (1994).

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Box I : Use of coal in iron and steelmaking

Molten steel is typically produced either from the basic oxygen furnace using molten pig iron (which is produced from the blast furnace or by direct smelting) or by melting steel scrap or scrap substitute in an electric arc furnace (EM). Direct smelting uses cheaper steaming coals and less capital than does the blast furnace in iron making and it avoids coke making. However, the cost effectiveness of direct smelting is largely unproven.

The electric arc furnace uses mainly scrap steel or scrap substitute and electricity. In 1994, around a third of the world's steel output was produced using electric arc furnaces. Increased penetration of the electric arc, at the expense of blast furnace iron and steelmaking, directly reduces the demand for coking coal because coking coal is not used in the electric arc process.

The use of coal in steelmaking is discussed further in Biawas (1981), Dwyer and Muir (1992). Labson et al. (1994) and Scott (1994).

Blast furnace iron and steelmaking The traditional steelmaking process uses coal to produce coke for use in the blast furnace. This is done by heating bituminous coal to above 900 degrees celsius in the absence of air in a coke oven. The oven chamber of a large modem coke oven is about 7 metres high, 18 metres long and 0.6 metres wide, and receives a charge of around 70 tonnes of coal (Scott 1994). Water and other volatile components are driven off as combustion flues heat the coal charge through the walls of the oven. Heating continues, the charge first passing through aplastic state and expanding against the oven walls, then solidifying to form a coherent mass and finally shrinking away from the oven walls.

The cycle time from charging to complete carbonisation is 25 hours for the large coke oven specified above. The hot coke (around 1 100 degrees celsius) is pushed out of the oven and transported in a coke car to a quenching tower where is is rapidly cooled with water.

Coke is used by feeding it into the top of the blast furnace with flux and iron ore (in a mixture of lumps, pellets and sinter). Air which is preheated to about 1200 degrees celsius is injected into the base of the furnace, reacting with the coke to produce carbon monoxide. The carbon monoxide ascends the blast furnace and facilitates the reduction of the iron ore into molten iron. The heat generated by the combustion of the coke maintains the reactions which occur in the furnace. The iron ore passes through five reactivity zones in the blast furnace, each of which performs a different function in the production of iron. The final zone, known as the 'deadrnan', is the bed of coke.

The coke in the blast furnace must provide a permeable, coherent structure through which the gas can rise and the molten iron metal can fall, while supporting the weight of the burden in the blast furnace. A blast furnace is a cylindrical vessel up to 24 metres high which ranges in volume from 500 cubic metres to 5000 cubic metres. The walls of the blast furnace are not designed to support the full weight of the charge so the capacity of the coke to perform this role is important to the integrity and longevity of the blast furnace.

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Box I : Use of coal in iron and steelmaking (continued)

The molten iron ore is extracted from the base of the hlast furnace and is transported to the basic oxygen furnace where it is combined with scrap steel and fluxes such as limestone. An oxygen probe blasts 99 per cent pure oxygen into the furnace, raising the temperature to about 1700 degrees celsius. This melts the scrap and facilitates the removal of impurities. The flux is subsequently removed from the molten metal and alloys are added. The alloy agents include chromium, nickel, molybdenum (for stainless steel), manganese, tungsten, cobalt and silicon. They modify the characteristics of the molten metal to produce steel capable of performing different functions.

After the alloys are fully mixed in the molten steel, the end product is processed by continuous casting to produce intermediate products in the required shape, such as rod, bar or slab products.

The quality of coals used to make coke are judged by the performance of the coke in the blast furnace. The three diverse functions - chemical, thermal and physical - performed by the coke in the blast furnace necessitates that the coal from which the coke is derived has certain characteristics. l)Jpically, to achieve the characteristics required of coal in the steelmaking process, modern coke ovens use a blend of coals.

Pulverised coal injection The development of pulverised coal injection has helped reduce the volume requirements for coking coal in the traditional steelmaking process. In pulverised coal injection, finely ground coal is injected at the base of the blast furnace to provide the reductant agents to reduce iron ore to hot iron metal and to provide the heat to sustain this process. However, the PC1 coal is unable to provide the permeable bed of coke that is required in the blast fumace, so it is only a partial substitute for higher quality coking coal. The quality of the coke, and thus the coking coal, must increase with higher injection rates as the proportion of coke to iron ore falls in the blast furnace. Premium hard coking coal has few contaminants and produces strong coke. Overall, approximately one tonne of cheaper semisoft coking coal or PC1 coal replaces about 1.4 tonnes of coking coal otherwise used to make coke in the production process. Japan is the country with the highest use of PC1 coal, currently accounting for around 35 per cent of world consumption.

Composition and properties of coal Coal is comprised of fixed carbon, volatile matter, ash and water (figure A). This proximate analysis of coal is the most common form of coal evaluation.

Fixed carbon content The fixed carbon content of the coal influences the specific energy content or calorific value of the coal. The calorific value is the amount of heat released by the complete combustion of the coal under specified conditions and is usually measured in kilocalories per kilogram. The calorific value is

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Box 2: Use of coal in electricity generation

The purpose of coal fired electricity generation is to convert the energy content of the coal to usable energy in the form of electricity. The traditional electricity generation process is the conventional steam cycle. In a pulverised fuel power station, thermal coal is fed into a pnlverising mill which mechanically gn'nds the coal to an average diameter of approximately 100 microns. The pulverised coal is fed into the furnace chamber with hot air to produce superheated steam in the boiler tubes. The pulverisation of the coal enhances its ability to mix with the air during the process of combustion to ensure ahigh carbon burnout rate. The superheated steam produced in the boilers passes through the turbine generators to generate electricity.

The ability of the steam turbine to generate electricity at full capacity depends on the temperature and pressure of the steam supply. The quality of the thermal coal used is an important influence on heat release and transfer, and thus steam conditions. Variations in the quality of the pulverised fuel can affect both the technical and environmental performance of the plant.

New technological developments have sought to improve the energy efficiency of the process by improving the combustion efficiency of the coal. However, the fundamentals of the conventional steam cycle process remain essentially unchanged.

Costs of conventional coal fired power generation have increased with the introduction of more stringent environmental standards, particularly those relating to emissions of particulates and sulphur dioxide. These include the cost of installing flue gas desulphurisation units to reduce sulphur dioxide emissions and the cost of purchasing low sulphur thermal coal. The increasing importance of environmental standards in electricity generation has also encouraged the development of cost effective cleaner technologies. New technologies for electricity generation include combined cycle gas turbines, pressurised fluidised bed combustion and the integrated gasification combined cycle. Various technologies are discussed in more detail in Skompska (1993).

particularly important for power station applications of coal use because it dictates the capacity of the pulverised coal to generate heat and thus electricity. The fixed carbon content, measured as a percentage of the air dried coal sample, is approximated by taking the difference between 100 per cent and the sum of the estimated inherent moisture content, volatile matter content and ash content, also measured on an air dried sample basis.

I Volatile matter content Volatile matter is the proportion of the air dried sample which is released in the form of gas or vapo&dGing a standardised heating test (Skompska 1993). The volatile matter may originate from both coal and mineral matter and is a positive influence on the abilitiof the coal to sustain combustion. A high volatilk matter

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A Composition of coal

Non-coal m&er Coal maUer I I I 7

Water

MinemI mafier

Source: Sanders (1966).

content indicates coal which is easy to ignite and which will bum with a large steady flame. Thus, volatile matter estimates are often used to calculate combustibility indexes, which are indicators of the reactivity of the coal.

Overall, volatile matter is a positive feature for thermal coal which is used for combustion purposes, but is inversely related to coke yield (Roberts and Callcott 1984). A high volatile matter content - generally exceeding 30 per cent of the air dried coal - increases the potential risk of spontaneous combustion.

Ash content Ash is the residue remaining after the complete combustion of all coal organic matter and oxidation of the mineral matter present in the coal (Skorupska 1993). Ash is therefore the incombustible material present in the coal and is measured as a percentage of the air dried coal sample. Ash does not contribute to the calorific value of the coal and increases costs. In particular, a higher ash content results in higher transport and handling costs per unit of energy contained in the coal, and in waste which usually requires disposal after the combustion process.

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For coking coals, ash remains in the coke and becomes incorporated in blast fumace slag. With thermal coals, boiler combustion results in ash falling to the bottom of the furnace or mixing with the flue gas where emission regulation requires it to be trapped and collected. Net disposal costs of ash residue are reduced where ash is a valued input: ash can be used in manufacturing cement, for example. Coking coal contracts typically contain penalties for ash outside the specified range.

Moisture content Moisture content refers to the water in coal. The total moisture content of coal is the sum of inherent (or air dried) moisture and excess moisture. Inherent moisture is the moisture that remains after the coal is air dried and is measured as a percentage of the air dried coal sample. The moisture content of coal influences how easily it is handled (Skompska 1993). Transport costs directly increase with moisture content. Transporting coal with a high moisture content involves a risk of the moisture consolidating in the cargo. This can result in the stability of the vessel being compromised during transport and, in the extreme, the vessel capsizing. By contrast, extremely low total moisture increases the risk of spontaneous combustion.

Sulphur content Fixed carbon and coal volatile matter can be further divided into the elements carbon, hydrogen, nitrogen, sulphur and oxygen using ultimate analysis (Sanders 1996).

Sulphur is a particularly important element and can have significant negative effects in coal applications. Sulphur increases the tendency for fouling and corrosion of metal surfaces in both steaming and metallurgical applications, for example, and results in emissions of sulphur dioxide. Most power stations in Japan have desulphurisation equipment to meet emission regulations, but operating costs increase with the sulphur content of the coal. However, Australian coals are generally low in sulphur, typically less than 0.7 per cent (DPIE 1996). Sulphur content levels outside the specified range typically incur penalties in coal contracts.

Other properties Laboratory tests which simulate the conditions of coal use further indicate various properties of the coal such as its ability to be handled, its spontaneous combustion propensity and its grindability. There are several tests that are respectively used to differentiate premium coking coals from other coking and

COAL PRICING

thermal coals, and premium thermal coals from other thermal coals. A detailed description of these tests is given in Carpenter (1988). Two such tests which are commonly reported, and which are included in the coal export controls database and thus in the empirical analysis, are the crucible swelling number (or free swell index) for coking coals and the Hardgrove grindability index for thermal coals.

Crucible swelling number The crucible swelling number indicates the capacity of the coal to expand when subjected to a standardised heat, and is used to evaluate the coking properties of the coal (that is, the ability of the coal to form coherent coke for blast furnace use). Coking coal is determined by its coking properties primarily. The crucible swelling number ranges from zero to nine. A crucible swelling number of zero means that the coal fails to form a coherent mass and cannot provide a permeable base in the blast furnace and thus is unsuitable for this purpose. A crucible swelling number of nine implies very good coking properties.

Hardgrove grindability index The Hardgrove grindability index reflects the abrasion resistance or strength of the coal. Grindability is an important characteristic for thermal and PC1 coals because it dictates the ability and cost of grinding the coal to an appropriate size specification. A higher index indicates that the coal is easier to grind (which reduces capital and operating costs in pulverising mills). Many Australian coals have a Hardgrove grindability index of 50-60, and are assessed to be relatively easy to grind (DPIE 1996).

There are numerous other tests used in coal evaluation, although none are available from the coal export controls database. The Gieseler plastometer, for example, is used to test the fluidity of coking coal. Coal buyers, particularly in Japan, have argued that fluidity is an important quality characteristic, but ACIRL (1996) has found little evidence of a positive correlation between fluidity and coke quality. Coke strength after reaction is a measure of coke strength which is argued to be important since the coal must be able to form large angular coke which retains its form despite constant abrasion and collision in the blast furnace. Coke strength after reaction is positively related to coke quality.

Quality characteristics of coal types Coal is formed by the decay of organic matter which is trapped under sedimen- tary layers. The matter is subjected to intense heat and pressure which increases

COAL PRICING

B Changes in properties of the organic matter with degree of coalification

(a) Voloh'Ie rmrlter 1 W

50

% dnimj

- I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

I I I I

(b) Fired carbon 100 - ' I I I I I I I

% d m j

I I I I ' I 1 I I I I I I I I I I I I

I I I I I

I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

(c) Calorific value 36 - I I I I

I I I I

I I I I I I I I I I I I I I I

I I I I I I I I I I I I I 1 I I I

MJkg mmmj

(d) Moisfure 100 - I I I I I I I I I

I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I ! ! I I

50 I I I 1 I I I

I l l I I I I I I I I I I

I I I I---I-C-,-,-,-- I %

(e) W n i t e reflectance 5

4

3

2

1

Rmax%

- I I I I 1- ! 10," "ol;,il; *; --I I I I I I - I I 1- I I I I I* h ~ h v o l i l I I *I . *I I I /' - I subbiminous I I I I I

li8"it~ - I I I 0' I I /'

I I I

- 1 ' I I I M M I I I I

- I I I I I I L- I I

- - - - + - r 4 1 I I I I I I

Source: Corpmler (1988).

COAL P R Z C ~ G

its carbon content while decreasing its moisture content. The quality of coal varies significantly because coal originates from organic matter of varying compositions that has been subjected to different transformation processes over different time frames.

Coal is ranked by the amount of alteration it has undergone from its organic material stage. These ranks include anthracite, bituminous coal, sub-bituminous coal, lignite (or brown coal) and peat (Bureau of Resource Sciences and the Australian Mining Industry Council 1994). Higher rankcoals, such as anthracite and bituminous coal, are those which have undergone the greatest degree of transformation. Coking coal tends to have a higher rank than thermal coal.

The relationship between some key quality characteristics and coal rank is given in figure B. Vitrinite reflectance is an accurate measure of coal rank and is also used to evaluate coking coal blends. The moisture content of coal is primarily a function of the age of the coal and the geological nature of the transformation process from organic matter to coal. Older, higher rank coals tend to have a lower inherent moisture content given their longer exposure to heat and geological pressure. Similarly, volatile matter tends to decrease as the rank of a coal increases. By contrast, the fixed carbon content and calorific value of coal tend to rise with the rank of the coal.

Several important quality characteristics of Australia's major coal brands are published in various publications including, for example, the DPIE (1996) and the TEX Report (1996). (The minimum, maximum and average value of each of these quality characteristics are given in table 4, chapter 3, for coal from both published sources and the coal export controls database.) Overall, the quality characteristics of the major metallurgical and thermal coal types are as follows.

Hard coking coal must be able to form strong coke and is the highest quality category of coking coal. It tends to have a high crucible swelling number of 6-9, moderate volatile matter content, low inherent moisture, ash and sulphur contents, and a vitrinite reflectance of 0.9-1.6.

Soft coking coal tends to have a lower fixed carbon content and crucible swelling number, and higher inherent moisture and volatile matter contents.

Semisoft coking coal is a low grade or weak coking coal which is not capable of producing a good coke, and which tends to have a lower crucible swelling number and higher ash content.

COAL PRICING

PC1 coal tends to have relatively low inherent moisture and ash contents, a relatively high volatile matter content and a moderate Hardgrove grindability index.

Thermal coal tends to have a relatively high calorific value, volatile matter content and ash content, a moderate Hardgrove grindability index, and a low sulphur content and crucible swelling number.

COAL PRICING

3. Coal price-quality data and estimation method

The objective in this study is to derive quality adjusted prices for Australia's coal exports, based on Australia's coal export controls database, by applying hedonic regression techniques to estimate the ,extent to which coal quality characteristics influence coal prices. The coal export controls database is described below, followed by a discussion of the hedonic regression models and the estimation method used in this study. Hedonic pricing theory and its various applications are described in Bemdt (1991), Deaton and Muellbauer (1980) and Rosen (1974).

Australia's coal export controls database The DPIE Coal Development Branch maintained a coal export controls database for the period 1988 to early 1996. Companies have been required to provide DPIE with information on each coal contract, including the price, quantity and quality characteristics of the coal.

The fob price of coal in each shipment is specified in US$ a tonne, while the volume specified in the coal contract is given by the base tonnage. The agreed tonnage, which is also reported, is that approved under export controls provisions. There have been only a small number of occasions when the base tonnage diverged from the agreed tonnage. The quality characteristics of the coal in each shipment are fixed carbon content, total moisture, inherent moisture, volatile matter content, ash content, sulphur content, calorific value, free swell index (or crucible swelling number) and the Hardgrove grindability index.

The export controls database identifies the end use sector of Australia's coal exports. The end use sectors include the steel industry, the power generation industry, the cement industry and an aggregate general industry category. The coal type - broadly defined by the intended use of the coal such as coke making or electricity generation (as described in chapter 2) --is also identified in the database. The main specific coal types are hard coking coal, soft coking coal, semisoft coking coal, PC1 coal and thermal coal. The database also includes anthracite coal, although Australia has negligible volumes of this coal type, and semiprocessed coal products such as briquettes. In addition, the coal brand of each shipment of coal is identified in the database. Generally, the brand name relates to the mine name from which the coal was extracted.

COAL PRICING

The database contains information on the contract year - that is, the year in which the coal was traded - for each shipment. i he database has three types of coal contracts which are used to facilitate coal trade: long term, term and spot contract sales. The difference between the nature of these cdntracts is the period of time over which they are effective. A long term contract is one whereby contractual obligations exceed one year in length while a term contract is one whereby the contractual relationship extends no longer than one year in terms of tonnages delivered and the price under which these coal tonnages are delivered. Despite the long term contract operating for more than one year, the price and tonnages involved in the contracts are usually reviewed annually. A spot contract is different to a long term contract and term contract in that the period of the contract is specified for one coal shipment only.

Ten separate end user regions are specified in the database, including Japan, north Asia (China, Hong Kong, North Korea, South Korea and Taiwan), west Asia (Bangladesh, Burma, India, Pakistan and Sri Lanka), south Asia (Indonesia, Malaysia, Philippines, Singapore, Thailand and Vietnam), Oceania (Fiji, New Caledonia, New Zealand and Papua New Guinea), the Americas (Argentina, Brazil, Canada, Chile, Colombia, Haiti, Mexico, the United States and Venezuela), western Europe (Austria, BelgiumlLuxem- bourg, Denmark, Finland, France, West Germany, Greece, Ireland, Italy, Malta, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom), eastern Europe (Albania, Bulgaria, Croatia, Czecho- slovakia, East Germany, Hungary, Poland, Romania, Slovenia, the former Soviet Union and Yugoslavia), Africa (Mozambique, Nigeria and South Africa) and the Middle East (Algeria, Egypt, Iran, Israel, Lebanon, Morocco and Turkey).

Hedonic pricing models and estimation method To the extent that coal quality varies over time and between regions, a comparison of prices between different time periods and regions will not provide accurate estimates of underlying price movements. Quality adjusted coal prices are preferred indicators of price change and can be derived by estimating price-quality relationships using hedonic pricing models and calculating the price of a coal with a constant set of quality characteristics. The assumed set of quality characteristics of each major coal category is based on the average quality of coal exported in JFY 1995, with the exception of soft coking coal which is based on exports in JFY 1994. The construction of quality adjusted price indexes based on hedonic regression analysis is discussed in Bemdt (1991).

COAL PRICING

Hedonic pricing models are described in general terms in appendix A. Rather than a simple estimate of price-quality relationships based on general functional forms, this study incorporates information about pricing arrangements where useful (particularly for pricing of coal in Japan's electricity sector). The expected direction of the impact of a particular quality characteristic on price is used to check the plausibility of the econometric results.

In the coal export controls database, key quality information is not available for all coal shipments; in particular, calorific value is not available for metallurgical coal exports, while crucible swelling number is not available for thermal coal. Overall, the relationship between the price and quality of Australia's coal exports is considered separately for three distinct coal categories: metallurgical coal for use in steelmaking, thermal coal for use in electricity generation, and thermal coal for general industrial use and cement manufacture.

The coal export controls database contains a number of coal shipments which are characterised by an extreme value of one or more quality characteristics. Two typical approaches to the presence of such outliers are the inclusion of a dummy variable to account for that observation, or the exclusion of that observation. Individual observations in the coal export controls database are confidential, so the latter approach (which is simpler anyway) is adopted in this study. Coal shipments for which a full set of price and quality data are unavailable are also excluded from the sample used in the econometric analysis.

The regions used in the study include: Japan, north Asia, south Asia (including Oceania), west Asia, Europe (including western Europe, eastern Europe, the Middle East and Africa) and the Americas. The total number of shipments available for use in the regression analysis by coal type, Japanese fiscal year and region of destination is given in table 2. The number a~ld proportion of total coal shipments that are spot sales are also provided in table 2.

Based on this sample of coal shipments from the coal export controls database, average coal prices (in JFY 1995 US dollars) and annual percentage changes are given in table 3. The minimum, maximum and average values of several important coal quality characteristics based on this sample are provided in table 4. Corresponding values are also provided for benchmark coals and Australia's major coal brands as published in DPIE (1996) and TEX Report (1996). Notably, there' is significantly more detail available from the coal export controls database for thermal coal, by end use sector, than from other sources.

COAL PRICING

2 Contracts available from the coal export controls database

JFY JFY 1989 1990

no. no. Long term, term and spot contracts Metallurgical coal Hard coking coal 76 72

Japan 28 29 North Asia 12 8 South Asia 0 0 West Asia 20 16 Europe 9 17 Americas 7 2

Sofi coking coal 33 25 Japan 22 18 North Asia 8 6 South Asia 0 0 West Asia 1 1 Europe 0 0 Americas 2 0

Semisofr and PC1 coals 70 74 Japan 67 63 North Asia 3 7 South Asia 0 0 West Asia 0 0 Europe 0 0 Americas 0 4

Total metallurgical coal 179 171 Japan 117 110 North Asia 23 - 21 South Asia 0 0 West Asia 21 17 Europe 9 17 Americas 9 6

Thermal coal Electricity 74 87

Japan 45 41 North Asia 16 18 South Asia 6 12 West Asia 0 0 Europe 7 15 Americas 0 1

JFY 1991

no. no.

JFY JFY 1993 1994

no. no.

JFY JFY 1995 1996.

no. no.

129 77 8 1 45 39 21 3 1 0 3 5 4 1 3

Continued 0

COAL PRICING

2 Contracts available from the coal export controls database (continued)

JFY JFY JFY JFY JF'Y JFY JFY JFY 1989 1990 1991 1992 1993 1994 1995 1996

no. no. no. no. no. no. no. no.

Cement 19 33 54 83 66 40 23 18 Japan 16 17 32 38 49 3 1 18 12 North Asia 1 12 12 32 12 7 4 5 South Asia 2 2 8 9 5 2 1 1 West Asia 0 0 0 2 0 0 0 0 Europe 0 2 2 2 0 0 0 0 Americas 0 0 0 0 0 0 0 0

General industry 105 110 119 159 204 161 131 53 Japan 99 104 103 134 178 142 107 45 North Asia 3 3 10 20 19 15 18 7 South Asia 3 3 2 2 2 1 3 0 West Asia 0 0 0 0 0 0 0 0 Europe 0 0 4 1 2 2 1 1 Americas 0 0 0 2 3 1 2 0

Total thennal coal 198 230 274 347 379 332 283 148 Japan 160 162 184 227 290 253 206 102 North Asia 20 33 41 78 63 56 61 33 South Asia 11 17 14 14 9 4 7 2 West Asia 0 0 0 2 1 0 0 3 Europe 7 17 34 23 12 17 6 5 Americas 0 1 1 3 4 2 3 3

Spot contracts Metnllurgical coal Hard coking coal 6 5 10 20 17 18 11 4

Japan 2 2 2 4 1 3 3 1 North Asia 1 0 6 4 1 2 3 0 South Asia 0 0 0 0 0 0 0 0 West Asia 0 1 1 1 9 8 4 0 Europe 1 2 0 9 3 2 0 2 Americas 2 0 1 2 3 3 1 1

Sofr coking coal 4 2 2 2 3 4 4 0 Japan 0 2 2 2 2 4 2 0 North Asia 2 0 0 0 0 0 0 0 South Asia 0 0 . 0 0 0 0 0 0 West Asia 0 0 0 0 0 0 0 0 Europe 0 0 0 0 0 0 0 0 Americas 2 0 0 0 1 0 2 0

Continued 0

COAL PRICING


Semisoft and PC1 coals Japan North Asia South Asia West Asia Europe Americas

Total metallurgical coal Japan North Asia South Asia West Asia Europe Americas

Thermal coal Electricity

Japan North Asia South Asia West Asia Europe Americas

Cement Japan North Asia South Asia West Asia Europe Americas

General industry Japan North Asia South Asia West Asia Europe Americas

Total thennal coal

J F Y 1989

no. 12 12 0 0 0 0 0

22 14 3 0 0 1 4

16 15 0 0 0 1 0

5 5 0 0 0 0 0

57 53

1 3 0 0 0

78

J N 1990

no. 18 15 1 0 0 0 2

25 19 1 0 1 2 2

17 8 1 1 0 6 1

17 7 8 1 0 1 0

74 70

1 3 0 0 0

108

J F Y 1991

no. 16 10 1 0 1 2 2

28 14 7 0 2 2 3

33 12 4 0 0

17 0

38 19 10 7 0 2 0

83 72 7 2 0 2 0

154

J N 1992

no. 12 7 3 0 1 0 1

34 13 7 0 2 9 3

26 13 6 1 0 6 0

63 29 21 9 2 2 0

114 95 15 1 0 1 2

203

J F Y 1993

no.

11 7 1 0 0 0 3

3 1 10 2 0 9 3 7

24 15 2 1 1 5 0

47 35 8 4 0 0 0

146 134

8 1 0 1 2

217

J F Y 1994

no.

25 13 3 0 1 0 8

47 20 5 0 9 2

11

47 28 10 0 0 9 0

22 17 3 2 0 0 0

118 107

9 1 0 1 0

187

J F Y 1995

no.

18 16 0 0 0 0 2

33 2 1 3 0 4 0 5

42 27 13 1 0 0 1

13 10 2 1 0 0 0

93 76 12 2 0 1 2

148

J F Y 1996

no.

10 5 3 0 0 0 2

14 6 3 0 0 2 3

19 8 5 1 2 2 1

13 8 4 1 0 0 0

35 28 6 0 0 1 0

67 Continued 0

COAL PRICING


JFY 1990

no.

J N 1991

no.

JFY J N 1992 1993

J N 1994

no. no. no. no.

137 184 42 18 11 6 2 1 9 6 2 2

no. no.

113 44 27 15 4 2 0 2 1 3 3 1

Japan 73 North Asia 1 South Asia 3 West Asia 0 Europe 1 Americas 0

Spot contracts as a share of total contracts Metallurgical coal Hard coking coal 8 7 14

Japan 7 7 8 North Asia 8 0 43 South Asia - - - West Asia 0 6 8 Europe 11 12 0 Americas 29 0 50

Soft coking coal Japan North Asia South Asia West Asia Europe Americas

Semisofl and PCI coals Japan North Asia South Asia West Asia Europe Americas


67 0 100 -

0 - - - 0 0 - -

100 - 21 30 22 25 0 38 - - - . - - -

67 40

22 24 20 24 17 27 - -

33 0 0 50

63 38 Continued O

COAL PRICING


JFY JFY JFY JFY JFY JFY JFY JFY 1989 1990 1991 1992 1993 1994 1995 1996

% % % % 92 % % 70 Thermal coal - - - - - - - - Electricity 22 20 33 25 22 36 33 25

Japan 33 20 24 24 24 35 33 18 North Asia 0 6 21 23 6 29 33 24 South Asia 0 8 0 33 50 0 33 100 West Asia - - - - 100 - - 67 Europe 14 40 61 30 50 60 0 50 Americas - 100 0 0 0 0 100 33

Cement 26 52 70 76 71 55 57 72 Japan 3 1 41 59 76 71 55 56 67 North Asia 0 67 83 66 67 43 50 80 South Asia 0 50 88 100 80 100 100 100 West Asia - - - 100 - - - - Europe - 50 100 100 - - - -

Americas - - - - - - - - General industry 54 67 70 72 72 73 71 66

Japan 54 67 70 71 75 75 71 62 North Asia 33 33 70 75 42 60 67 86 South Asia 100 100 100 50 50 100 67 - West Asia - - - - - - - -

Europe - - 50 100 50 50 100 100 Americas - - - 100 67 0 100 -

Total thermal coal 39 47 56 59 57 56 52 45 Japan 46 52 56 60 63 60 55 43 North Asia 5 30 51 54 29 39 44 45 South Asia 27 29 64 79 67 75 57 100 West Asia - - - 100 100 - - 67 Europe 14 41 62 39 50 59 17 60 Americas - 100 0 67 50 0 100 33

COAL PRICING

3 Average coal prices from the export controls database: all contracts JFY 1995 USW or percentage change from previous year

Metnllurgieal coal Hard coking coal



Semisoft and PCI coals Japan North Asia South Asia West Asia Europe Americas




JFY 1991

US$/t

56.7 57.0 56.4

- 57.3 54.3 56.2

52.6 52.7 52.3

- - - -

47.8 47.9 48.2

- - -

45.0

53.6 53.4 52.6

- 56.9 53.7 47.0

42.7 45.0 43.5 37.9

-

38.6 -

JFY 1993

US$/t

49.8 51.4 51.1 - 47.4 47.1 48.4

46.3 46.3 46.3

- - - -

41.3 41.3 41.7

- - -

38.5

46.9 47.2 46.3

- 47.4 46.4 41.3

37.6 38.8 37.6 28.1

- 31.9 - -

JFY JFY 1995 1996

39.6 38.9 40.8 39.4 39.3 38.7 33.5 36.1

- - 34.5 34.6

- - Continued 0

COAL PRICING

3 Average coal prices from the export controls W a s e : all conhacts (continued)

J F Y J F Y J F Y J F Y J N JFY J F Y J F Y 1989 1990 1991 1992 1993 1994 1995 1996

US$/t US$h US$/t US$/t US$lt US$/t US$/t US$/t

Cement 47.1 42.6 41.1 34.8 30.6 30.5 36.5 33.6 Japan 48.4 46.6 44.7 40.1 32.3 30.7 37.1 34.2 North Asia 46.7 39.2 33.3 30.2 27.5 28.7 35.0 32.4 South Asia 43.1 39.0 32.9 32.4 30.1 32.8 42.8 32.5 West Asia - - - - - - - - Europe - - - - - - - - Americas - - - - - - - -

General industry 47.8 47.7 43.4 37.5 32.2 31.6 37.2 34.7 Japan 48.4 48.1 44.5 39.4 33.2 32.2 38.1 35.4 North Asia 43.0 38.3 36.1 30.9 28.0 29.0 34.0 32.9 South Asia 49.5 47.9 45.4 41.8 32.7 39.6 31.5 - West Asia - - - - - - - - Europe - - - - - - - - Americas - - - - - - - -

Total thermal coal 47.3 46.2 42.6 38.8 35.4 33.6 38.9 38.0 Japan 48.4 47.7 44.7 41.1 36.0 34.0 39.7 38.2 North Asia 45.9 43.9 41.2 37.3 35.3 33.6 38.5 38.0 South Asia 44.7 44.7 36.1 31.2 29.6 31.5 33.5 34.3 West Asia - - - - - - - -

Europe 44.8 45.2 38.6 34.3 31.9 30.8 34.5 34.6 Americas - - - - - - - -

J F Y 1990

% Percentage change from previous year Metullurgical coal Hard coking coal -0.4

Japan 4 . 5 North Asia -1.7 South Asia - West Asia -1.2 Europe 3.2 Americas 1.7

Soft coking coal 4 . 5 Japan -0.5 North Asia -0.1 South Asia - West Asia - Europe - Americas

J F Y 1994

%

-7.7 -10.4 -10.5

- -2.4 -5.0 -5.1

-12.8 -9.8

-10.4 - - -

J F Y 1995

%

9.3 9.4

10.7 -

8.8 12.7 -3.9

- - - - - -

J F Y 1996

%

0.2 4 . 2 3.0 -

0.8 -1.4 4 . 7

- - - - -

, -

Continued 0

29

COAL PRICING

3 Average coalprices from the export controls ahtabme: all contracts (continued)

JFY JFY JFY JFY JFY JFY JFY 1990 1991 1992 1993 1994 1995 1996

% % % 70 % % %

Semisoft and PCI coals -0.7 -6.4 -5.2 -9.0 -10.4 14.4 -0.8 Japan -0.7 -6.2 -5.1 -9.2 -10.5 14.2 -1.2 North Asia -0.7 -6.0 -5.3 -8.6 -10.6 14.1 -0.6 South Asia - - - - - - -

West Asia - - - - - - - Europe - - - - - - - Americas - -5.7 -5.6 -9.5 -7.0 17.9 -2.2

Total metallurgical coal -1.1 4 . 7 -4.7 -8.2 -10.0 9.6 -0.5 Japan -1.4 4 . 6 -3.9 -8.0 -11.8 10.2 -2.9 North Asia -2.0 4 . 2 -6.5 -5.8 -11.2 11.1 -3.2 South Asia - - - - - - - West Asia -1.3 -5.9 -5.0 -12.3 -4.1 8.9 1.0 Europe 3.2 -7.7 -7.1 -7.0 -3.6 12.7 -1.4 Americas -1.0 -15.5 -6.3 -6.2 -8.8 15.4 -2.1





Total thermal coal Japan North Asia South Asia West Asia Europe Americas

4 Description of coal qualify data

- -

DPIE (1996) s TEX report (1996) DPIE coal export controls database

Bench- Mini- Maxi- Mini- Maxi- Mini- Maxi- .niY Unit mark mum mum Average mum mum Average mum mum Average 199Sb

Metallurgical coal H a d coking coal Goonyella

Fixed carbon content % 65.0 58.0 71.9 64.9 57.5 70.2 66.1 56.8 72.2 65.4 65.8 Total moisture % 8.0 8.0 10.0 9.0 8.0 9.0 8.1 6.0 11.0 8.4 8.5 Inherent moisture % 1.0 1.0 2.0 1.4 1.0 2.0 1.4 1.0 2.0 1.4 1.4 Volatile matter % 26.0 17.2 33.5 25.0 19.5 34.0 24.8 17.0 34.5 24.6 24.0 Ash % 8.4 6.3 14.0 8.7 6.0 9.8 8.2 6.0 11.3 8.6 8.8 Sulphur % 0.7 0.3 0.9 0.6 0.4 0.9 0.6 0.1 1 .O 0.6 0.6 Crucible swelling number (or free swell index) no. 7.0 6.0 8.5 7.4 6.0 9.0 7.2 4.0 9.0 7.0 7.0

Soft coking coal Daiyon Fixed carbon content % 53.5 Total moisture % 8.0 Inherent moisture % 2.5 Volatile matter % 7.4 Ash % 37.0 Sulphur % 1 .O Crucible swelling number (or free swell index) no. 4.5

Semisoft and PC1 coals Warkworth Fixed carbon content % 53.7 Total moisture % 8.5 Inherent moisture % 2.5 Volatile matter % 34.5 Ash % 9.3 Sulphur % 0.7 Crucible swelling number (or free swell index) no. 4.5

4 Description of coal quality data (continued)

D P E (1996) a TEX mport (19%) DPIE coal export controk database

I Beneh- Mini- Maxi- Mini- Maxi- Mini- Maxi- JFY Unit mark mum mum Average mum mum Average mum mum Average 1995b

Thermal coal

, . . .- ... . . . . - . ~ ~ ~ ~

Inherent moisture % - 1.0 7.5 2.5 - - - 1.0 5.5 2.7 2.7 2 Volatile matter % - 15.0 44.5 29.9 - - - 11.0 41.0 30.5 30.5 1 0

1 Electricity generation Calorific value kcaVkg 6 700 6 356 7 550 6 887 - - - 6250 7250 693 6802 Fixed carbon content % - 39.0 72.8 53.6 - - - 41.0 68.5 53.1 53.5

I Total moisture % - 6.0 16.0 8.9 - - - 6.0 13.0 8.7 8.8

~ - ~ ~ ~ - - ~ ~ ~ ~

; Ash 90 Sulphur 9% Hardgrove

grindability index index

Cement manufacture Calorific value kcaVkg Fixed carbon content % Total moisture 90 Inherent moisture % Volatile matter % Ash % Sulphur %

"cr "

~ k d g r o v e grindability index index - - - - - - - 39 84 52 49

General industry Calorific value kcaJikg - - - - - - - 6000 7550 6815 6850 Fixed carbon content % - - - - - - - 37.0 77.0 51.6 53.8 Total moisture 70 - - - - - - - 6.0 11.0 8.7 8.4 Inherent moisture % - - - - - - - 1.0 6.0 2.7 2.6 Volatile matter % - - - - - - - 10.0 42.0 31.8 29.1 Ash % - - - - - - - 6.0 22.0 13.9 14.6 Sulphur % - - - - - - - 0.3 1.8 0.6 0.7 Hardgrove

grindability index index - - - - - - - 35 85 50 52

a Data under elect~icity generation refer to total thermal coal. b Average for JFY1995 except for sofl coking coal which refen to JFY 1994.

COAL PRICING

Linear equations are estimated using ordinary least squares using the TSP software package (version 4.3A) for JFY 1989-96. Quadratic equations are particularly problematic in this study given the high degree of correlation between each of the quality characteristics and their corresponding squared terms, as well as between various interaction terms (see appendix B for the correlation coefficients for metallurgical and thermal coal aggregates). A high degree of correlation between independent variables makes it difficult to estimate the impact of each individual independent variable on the price: there is a tendency to inappropriately obtain coefficient estimates which are not significantly different from zero, and the coefficient estimates are sensitive to changes in the data. Various diagnostic tests and the implications of rnisspecification of functional form, heteroscedasticity and multicollinearity are discussed in Beggs (1988), Greene (1993) and Gujarati (1988), for example.

Gleeson, Lubulwa and Beare (1993) discussed possible sources of specification error in an hedonic price analysis of the wool market. Most notably, parameter estimates will be biased when variables are omitted from the regression which are important in explaining differences in coal prices and these omitted variables are not highly correlated with other quality characteristics which are included in the regression equation.

The coal export controls database contains information on important quality characteristics. However, some quality characteristics which may be important, such as fluidity and vitrinite reflectance, are not reported and thus are not available for the regression analysis. It is assumed in this study that the omission of those quality characteristics which are not available for consider- ation in the empirical study do not result in a significant bias in the estimated coefficients.

Metallurgical coal Assuming that pricing of different metallurgical coals is consistent, a single regression equation is estimated for all metallurgical coal shipments. However, the possibility that prices vary according to coal type and contract type is tested by incorporating dummy variables for soft coking coal and semisoft coking and PC1 coal and a dummy variable for spot contracts. Similarly, time dummy variables are included to account for annual movements in the general price of metallurgical coal. Dummy variables are explained in detail in appendix C.

/ If inherent moisture (IM), volatile matter (VM) and ash (ASH) are included in the equation, fixed carbon content is excluded because the relationship between this variable and price is implicit in the regression equation. Allowing

33

COAL PRICING

for the impact of the other quality characteristics reported in the coal export controls database - total moisture (TM), sulphur (SULPHUR) and crucible swelling number (CSN) - the general price-quality relationship for metallurgical coal (excluding various dummy variables) is given by:

(1) Pi = f (TM,, IMi, VM;., ASH;., SULPHUR,, CSN,)

where i includes only metallurgical coal shipments.

Indicative price-quality relationships for Australia's metallurgical coal exports to Japan since JFY 1989 are illustrated in figure C. Particularly interesting is the observed relatipnship between price and volatile matter whereby prices for semisoft coking and PC1 coal with very low or high volatile matter levels are lower than those with volatile matter levels in the middle range. In addition, the correlation between volatile matter and fixed carbon content is -0.99 for Australia's coal exports to Japan for JFY 1989-96 (appendix B). Therefore, the relationship between price and fixed carbon content is almost a perfect mirror image of that between price and volatile matter.

It is hypothesised in the empirical study that thecrucible swelling number has a positive impact on price, while higher levels of total moisture, inherent moisture, ash and sulphur, and very low or very high levels of volatile matter each have a negative impact on the coal price received. The possibility that there may be a kink in the relationship between price and volatile matter is considered through the use of dummy variables (appendix C). As discussed earlier, several other dummy variable are included to hlow for the price impact of different coal types, different contract types, and changes in coal demand and supply.

Thermal coal The pricing arrangements for thermal coal for use in electricity generation in Japan are the most transparent in the market. These pricing arrangements do not fully account for the value in the use of coal with various quality characteristics, but the price of thermal coal for use in electricity generation is determined in nearly all cases by calorific value. In particular, for long term and term contracts, the coal price is adjusted relative to a benchmark price in proportion to the extent to which its calorific value (CALORIE) exceeds the benchmark calorific value of 6700 kilocalories per kilogram (gross air dried basis). This pricing formula is based on nominal coal prices in practice, but is equivalent to the following formulation based on real prices:

COAL PRICING

C Indicative price-quality relationships for metallurgical coal a

- (a) Crucible swelling number

Price

Hard coking cool

Orher merallurgical con1

0 I 2 3 4 5 6 7 8 9 Crucible swelling number

(b) Volaiile matter Price

Hard coking cool

< - - cokrng coal

Orhcr metollurgicnl coal

Olher mlallurgical coal volnnlc C L a w volarile> mntrer

m n e r I I I I I I

I5 20 25 30 35 40 45 Volatile matter

(c) Fixed carbon content Price

Hard coking cool

Other merollurgical coal

Other merallurgicol coal C Low volnrilc 2

mnrrcr I I I I I 1

45 50 55 60 65 70 75 Fired carbon contenr

a For long arm and tam eonmct &la. Based on the coal erpon control &tab=.

COAL PRICING

Zndicahve price-quality relationships for metallurgical coal a C (continued)

(d) Inherent moisture Price

Hard coking coal

Other mctollurgical coal

1 2 3 4 Inherent moisture

(e) Ash Price

Hard coking cool

Other metallurgical cool

I I 6 7 8 9 I0 I1 I2

Ash (f) Subhur

Price

Hard coking cool

Sqfr coking cool

Other mefallurgicnl cool

0.4 0.6 0.8 1.0 1.2 1.4 1.6 Sulphur

u For long term and term sonmr dab. Based on h e coal srpon eontml databm.

COAL PRICING

(2) Pi = Pm . CALORIEi / CALORIEBM

= PBM . CALORIEi I6700

where i is for thermal coal shipments to Japan's electricity sector only, and the subscript BM refers to the benchmark coal.

Equation 2 can be transformed by taking natural logarithms (In) of both sides of the equation to give the following:

(3) In Pi = (In PBM - In 6700) + In CALORIEi

The coefficient for in CALORIEi is unity, implying a 1 per cent increase in calorific value results in a corresponding 1 per cent increase in the real price of coal used in Japan's electricity sector. To facilitate a comparison between the pricing of coalio Japan's eleciricity sector and other thermal coal, equation 2 is the basis of the empirical equation in the study for thermal coal exports to Japan's electricity sector.

Separate equations are estimated for other thermal coal shipments for use in electricity sectors in countries other than Japan and for use in other industries. The following general relationship is estimated in both cases:

(4) Pi = f (TMi, IMi, VMi, ASHi, SULPHUR, CALORIEi, HGIi)

where i includes corresponding thermal coal shipments other than those to Japan for use in electricity generation and HGI is the hardgrove grindability index. In the empirical study, it is hypothesised that calorific value, volatile matter and the Hardgrove grindability index each have a positive impact on price, while higher levels of total moisture, inherent moisture, ash and sulphur each have a negative im~ac t on the coal vrice received. Dummy variables are also included-to allow' for the possibility that there may he significant differences in pricequality relationships for thermal coal used in different end use sectors.

COAL PRICING - -

4. Quality adjusted prices for Australia's coal exports

Estimated coal price-quality relationships The estimated coal price-quality relationships are given in table 9 in appendix D. The preferred equations are chosen largely on the basis of goodness of fit (adjusted R squared), diagnostic tests (RESET tests for general misspecification and Lagrange multiplier tests for heteroskedasticity) and plausibility of results.

Metallurgical coal Including coal shipments based on long term, term and spot contracts, around 96 per cent of the variability in metallurgical coal prices between JFY 1989 and JFY 1996 is explained by variations in coal quality and several dummy variables. Total moisture does not have a significant impact on any of the metallurgical coal types. However, all other quality characteristics - inherent moisture, volatile matter, ash, sulphur and the crucible swelling number - are estimated to have a significant impact on the price of at least one metallurgical coal type with the expected sign. Notably, as expected, there is a significant kink in the relationship between price and volatile matter for,semisoft coking and PC1 coal, such that very low and high levels of volatile matter incur a price penalty.

There are no recorded shipments of metallurgical coal to South Asia (REG3). The main econometric results relating to the spot market and regional differences are as follows. Prices are given in J F T 1995 US dollars.

~ e t a l l u r ~ i c a l coal export prices to Japan (REG1) and west Asia (REG4) are estimated to have been significantly different only in JFY 1989, JFY 1990 and JFY 1993. In general, prices of Australia's metallurgical coal exports to north Asia (REG2) and the Americas (REG6) are estimated to have been US$0.34 a tonne and US$1.67 a tonne respectively lower than prices of coal exports to Japan, while export prices to Europe (REGS) are estimated to have been up to US$4.59 a tonne lower between JFY 1989 and FJY1993.

There are some regional differences in the relative prices of metallurgical coal types. In particular, the price of semisoft coking and PCIcoal to North Asia is estimated to have been US$0.69 a tonne higher than for other regions in the study period.

COAL PRICING

Spot metallurgical coal prices are estimated to have been about US$0.7 a tonne (JFY 1995 prices) lower in JFY 1990, JFY 1992 and JFY 1993.

The estimated relationships between metallurgical coal price and quality are as follows.

A 1 percentage point increase in the inherent moisture content is estimated to result in a fall of US$2.25 a tonne (in JFY 1995 prices) in hard coal and soft coking coal prices and US$0.97 a tonne in semisoft coking and PC1 coal prices.

A 1 percentage point increase in the volatile matter content does not have a significant impact on the prices of hard coal and soft coking coal, but is estimated to increase the price of semisoft coking and PC1 coal by US$0.18 a tonne up to a volatile matter content of 30, and to reduce the price by US$0.05 a tonne over this level.

A 1 percentage point increase in the ash content is estimated to result in a fall of US$0.46 a tonne in hard coking coal prices, US$1.81 a tonne in soft coking coal prices and US$O. 17 a tonne in semisoft coking and PC1 coal prices.

A 1 percentage point increase in the sulphur content does not have a significant impact on hard coking, semisoft coking and PC1 coal prices, but is estimated to result in a fall in the price of soft coking coal by US$3.64 a tonne.

An increase in the crucible swelling number by 1 point is estimated to result in an increase in the price of metallurgical coal by US$0.23 a tonne.

The coal type dummy variables are estimated to be significantly different from zero, which indicates that the coal classification contains significant information in explaining differences in the prices of hard coking, soft coking, and semisoft coking and PC1 coal. Relative metallurgical coal prices in an efficient market might be expected to be fully explained by differences in coal quality (Hogan et al. 1997). One interpretation of the empirical results is that the coal type dummies indicate the presence of more complex price-quality relationships than are currently modelled. The metallurgical coal market may also appear to be more segmented than is actually the case, to the extent that information on important quality characteristics is unavailable and has not been incorporated in the regression analysis.

Thermal coal In the regression analysis, an estimated 98 per cent of the price variability for coal exported to Japan's electricity sector, 72 per cent of the price variability

COAL PRICING

of coal exported to other countries for electricity generation, and 91 per cent of the price variability in other thermal coal markets are explained by coal quality differences and various dummy variables.

Coal exports to Japan for use in electricity generation Calorific value of coal exports to Japan's electricity sector, is the only quality characteristic which is found to have a significant impact on price, including the price of coal sold on the spot market. The main results are as follows.

An increase in calorific value by 1000 kilocalories per kilogram is estimated to result in an increase in coal price of between US$5.43 and US$7.78 a tonne.

Spot prices are estimated to be US$0.08 to US$1.31 a tonne (JFY 1995 prices) lower than long term and term contract prices.

Given the pricing arrangements in this sector, as discussed in chapter 3, these results for thermal coal sold under long term or term contracts are equivalent to a 1 per cent increase in calorific value resulting in a 1 per cent increase in price.

Coal exports to countries other than Japan for use in electricity generation In the estimated equation for thermal coal shipments to electricity sectors other than Japan's, both calorific value and sulphur content are found to have a significant impact on price. Only a small number of coal shipments are destined to west Asia (REG4) and the Americas (REG6), so these countries are excluded from the regression analysis. The key results are as follows.

The price of coal to Europe (REGS) is estimated to US$3.46 a tonne lower than that of coal to other regions in general, although coal prices to South Asia (REG 3) are estimated to have been about US$7 a tonne lower in JFY 1992, JFY 1993 and JFY 1994.

An increase in calorific value by 1000 kilocalories per kilogram is estimated to result in an increase in the coal price by US$7.67 a tonne.

A 1 percentage point increase in sulphur content is estimated to result in a fall of US$2.46 a tonne in the coal price.

Spot prices are estimated to be US$3.67 a tonne lower than long term and term contract prices, except in JFY 1992 when the price is estimated to have been significantly lower.

COAL PRICING - - -

Coal exports for use in general industry or cement manufacture In the estimated equation for Australia's thermal coal shipments for use in general industry or cement manufacture, calorific value and ash content are found to have a significant impact on the coal price in both end uses while volatile matter content and sulphur content also have a significant impact on the price of coal used in general industry. West Asia (REG4), Europe (REG5) and the Americas (REG6) are excluded from the regression analysis because they receive only alimitednumber of skpmen t s. The key results are as follows.

Coal prices to north Asia (REG2) are generally estimated to be significantly lower than coal prices to Japan. The price of coal exported to south Asia (REG3) for use in cement manufacture is also generally estimated to be significantly lower than coal prices to Japan, while the price of coal used in general industry is generally significantly higher than coal prices to Japan.

A 1 percentage point increase in ash content is estimated to result in a fall of US$0.30 a tonne in the coal price.

An increase in calorific value of 1000 kilocalories per kilogram is estimated to result in an increase of US$3.16 a tonne in the price of coal for cement manufacture.

In general industry, an increase in calorific value of 1000 kilocalories per kilogram is estimated to result in an increase in the coal price of US$5.61 a tonne, a 1 percentage point increase in volatile matter increases the coal price by US$0.13 a tonne and a 1 percentage point increase in sulphur content reduces the coal price by US$1.84 a tonne.

Spot prices were only significantly lower than long term and term contract prices in JFY 1989, JEY 1992 and JEY 1993.

Estimated quality adjusted coal prices Quality adjusted coal prices are calculated by applying the average quality of Australia's coal exports in JEY 1995 (JFY 1994 for soft coking coal) to the estimated price-quality relationships. The average quality is based on the sample from the coal export controls database as given in table 4. Estimated quality adjusted coal prices by year, coal type and region are provided in table 5. Quality adjusted coal prices will be similar to average coal prices to the extent, for each coal category, that coal quality is relatively stable and for each region similar to the average coal quality.

There was a relatively large number of cases where the regional quality adjusted coal price varied by more than 1 per cent from the average price based

- 41

COAL PRICING

Quality adjusted prices for Australia's coal exports: all contracts 5 .

Metallurgical coal Hard coking coal



Semisoft and PC1 coals Japan North Asia South Asia West Asia Europe Americas




JFY 1992

US$/t

53.8 54.3 53.9

- 54.3 50.5 51.9

49.8 50.1 49.8

- - - -

46.0 46.1 46.4

- - -

44.4

51.0 51.1 49.3

-

53.8 49.7 45.4

40.4 42.8 40.2 30.0

- 36.1

-

COAL PRICING - -

5 Quality adjusted prices for Australia's coal exports: all contracts (continued)

J N J N 1989 1990

US$/t US$/t

Cement 46.7 42.7 Japan 47.9 46.6 North Asia 45.2 38.6 South Asia 44.4 43.1 West Asia - - Europe - - Americas - -

General industry 48.6 47.3 Japan 48.9 47.7 North Asia 46.2 39.6 South Asia 48.4 47.8 West Asia - - Europe - - Americas - -

Total thermal coal 48.1 46.2 :Japan 48.7 47.8 North Asia 47.6 44.0 South Asia 47.2 45.0 West Asia - - Europe 44.2 44.9 Americas - -

JFY 1990

% Percentage change from previous year MefnUurgical coal Hard coking coal 4 . 5

Japan 4 . 9 North Asia -0.9 South Asia - West Asia -1.2 Europe 3.2 Americas 4.6

Sofr coking coal -1.0 Japan -0.9 North Asia 4 . 9 South Asia - West Asia - Europe - Americas -

JFY 1991

'70

- - Continued 0

COAL PRICING

5 Quality adjustedprices for Australin's coal exports: all contracts (continued)

Semisoji and PC1 coals Japan North Asia South Asia West Asia Europe Americas






Total t h e m 1 coal Japan North Asia South Asia West Asia Europe Americas

JFY 1990

%

-1.1 -1.1 -1 .o

- - - -

-1.2 -1.7 -1.9

-

-1.3 3.2 2.4

-3.2 -1.1 -5.4 -5.7

- 1.4 -

-8.7 -2.6

-14.5 -2.9

- - -

-2.5 -2.5

-14.1 -1.2

- - -

-3.9 -1.9 -7.6 -4.5

-

1.4 -

JFY 1992

%

-5.3 -5.2 -5.3

- - -

-5.6

4 . 9 -4.4 -6.6

- 4 . 3 -7.2 -6.2

-4.7 -5.5 -5.1

-29.5 -

-3.5 -

-14.9 -11.8 -8.8 -6.5

- - -

-13.3 -12.3 -9.3 -0.9

- - -

-8.6 -8.7 -8.8

-20.6 -

-3.5 -

JFY 1996

%

0.0 0.0 0.0 - - -

0.0

4 . 2 -2.1 -3.2 -

0.1 0.0

-3.5

-1.6 -3.8 0.4

-7.5 - -1.9 - -6.6 -6.4 -6.5 0.4 - - -

-6.4 -6.2 -6.4 -

- - -

-2.2 -3.6 4 . 2 -9.6

- -1.9

-

COAL PRICING

on the sample from the export controls database (table 6). The main differences between quality adjusted and average coal prices are in the semisoft coking and PC1 coal category for metallurgical coal, and in all categories (except for electricity generation in Japan) for thermal coal. This is consistent with the expectation that there is greater uniformity in the quality of hard and soft coking coal exports than for other coal categories, and that there is a well defined price-quality relationship for thermal coal exports to Japan's electricity sector. There were relatively fewer percentage deviations larger than 1 per cent for the metallurgical and thermal coal aggregates compared with the individual coal categories, indicating that some of the percentage deviations were offsetting.

Quality adjusted and other coal prices, by region Quality adjusted prices for Australia's coal exports to Japan, together with other published price information, are presented in figure D. For hard coking coal to Japan, quality adjustedprices are consistently lower than average prices between JFY 1989 and JFY 1994, but higher in the subsequent two years. There were only two years where the percentage deviation exceeded 1 per cent, with -1.1 per cent in JFY 1992 and -1.6 per cent in JFY 1993.

Throughout the time period, quality adjusted and average hard coking coal prices based on the export controls database were lower than the benchmark price but higher than the export unit value. The benchmark price is based on the relatively highly valued Goonyella coal brand and would be expected to be above any average hard coking coal price. Average prices are based on the coal export controls database whereby information is based on an intention to export coal rather than the actual shipment, while export unit values are based on actual data. Differences between average prices and export unit values are likely to reflect changes in price and the date of shipment from that recorded in the database as well as sampling bias because complete price-quality data were not available for all coal shipments in the database.

Similarly, the quality adjusted prices of soft coking coal exports to Japan tend to be lower than actual prices, although the differences do not tend to be large. JFY 1992 was the only year in which the difference exceeded 1 per cent (a percentage deviation of -1.2 per cent). A small number of soft coking coal shipments were recorded in JFY 1995 and JFY 1996, but quality adjusted prices were not reported for these years because the soft coking coal category was officially merged with the semisoft coking coal category in early 1996. However, these prices were included in prices for total metallurgical coal.

COAL PRICING

The quality adjusted prices of semisoft coking and PC1 coal are consistently higher than the corresponding average prices. Except for JFY 1995 when the percentage deviation was only 0.3 per cent, quality adjusted prices were around 1.3-2.5 per cent higher than actual prices during the study period. Thus, except for JFY 1995, the gap between quality adjusted hard coking coal prices and quality adjusted semisoft coking and PC1 coal prices was slightly smaller than the gap based on average prices. Nevertheless, the quality adjusted price gap is still large. For example, in JFY 1996, quality adjusted hard coking coal prices were about 19 per cent higher than quality adjusted semisoft coking and PC1 coal prices, while the gap based on average prices was 20 per cent.

6 Deviation of quality adjusted coal prices from average prices: all contracts

Mefallurgical coal Hard coking coal



Semisofl and PC1 coals Japan North Asia South Asia West Asia Europe Americas


JFY 1989

%

-0.3 -0.3 -0.3

- 0.4

-0.8 -0.4

-0. I -0.4

1.1 - - - -

1.8 1.8 2.1 - - - -

0.1 0.1 0.6 -

0.2 -0.8 -0.8

JFY 1990

70

-0.4 -0.8 0.5 -

0.4 -0.8 2.4

-0.6 -0.9 0.3 - - - -

1.4 1.4 1.7 - - -

4.4

-0.1 -0.2 0.6 -

0.1 -0.8 2.6

JFY 1994

%

-0.5 -0.4 -0.5

- -1.0 2.4

-3.9

1.9 -0.1 -0.4

- - - -

1.8 1.9 2.0 - - -

0.6

0.4 0.6 0.6 -

-0.4 2.4

-0.4

JFY 1995

%

0.3 0.4

-0.9 -

0.3 0.2

10.6 - - - - - - -

0.3 0.3 0.3 - - -

-3.6

0.4 0.4

-0.2 -

0.8 0.2 6.8

JFY 1996

%

0.1 0.6

-3.7 -

-0.5 1.6

11.4 - - - - - - -

1.2 1.6 1.0 - - -

-1.4

0.7 1.2

4 . 1 -

-0.1 1.6 5.2

Continued 0

COAL PRICING

For Australia's thermal coal exports to Japan, quality adjusted prices of coal used for electricity generation tend to be slightly (up to 1 per cent) higher than average prices, while quality adjusted prices of coal used in either general industry or cement manufacture tend to be moderately (up to 6 per cent) lower than average prices. In contrast to metallurgical coal, the price gaps between different thermal coal end uses tend to be larger when based on quality adjusted prices rather than average prices.

Quality adjusted and other prices for Australia's coal exports to north Asia are presented in figure E. The differences between quality adjusted and average

Deviation of qualily adjusted coalpricesfrom average prices: all contracts 6 (continued)




General industry Japan North Asia South Asia West Asia Europe Am:ricas

Total t h e m 1 coal Japan North Asia South Asia West Asia Europe Americas

JFY 1990

%

0.3 1 .o 0.4

4 . 7 -

-0.7 -

0.2 0.0

-1.4 10.5

- - -

-0.8 4 . 9 3.5

4 . 2 - - -

0.1 0.1 0.2 0.8 -

-0.7 -

JFY 1991

%

4 . 7 0.7

-2.5 12.3

- -3.0

- -1.9 -3.8

3.0 5.9 - - -

-1.2 -1.0 -2.2

-12.7 - - -

-1.0 4 . 8 -1.9 9.2 -

-3.0 -

JFY 19%

%

-0.8 4 . 4 -1.0 -3.6

- -0.9

- 0.7

-0 .1 2.2 1.9 - - -

0.6 -0.5

3.8 - - - -

-0.5 -0.4 -0.6 -1.1

- -0.9

-

COAL PRICING - - - -

prices for metallurgical coal exported to North Asia were broadly similar to those for Japan over the study period. However, for thermal coal exports to north Asia, quality adjusted prices for coal used in electricity generation tend to be moderately (up to 4 per cent) lower than average prices, while quality adjusted prices for coal used in general industry or cement manufacture tend to be moderately (up to 8 per cent) higher than average prices. Thus, quality adjusted price gaps for thermal coal tend to be smaller than gaps based on average prices.

Nearly all of Australia's coal exports to west Asia are hard coking coal. Quality adjusted hard coking coal prices for west Asia diverge from average prices by up to 1 per cent, but with no tendency to diverge in a particular direction. Australia does not export metallurgical coal to south Asia, but there are a number of thermal coal shipments to this region. Quality adjusted prices of

D ~ k e s for ~ustralia's metallurgical and thermal coal exports to Japan a

(a) Hard coking coal (b) Sop coking coal 65 65

-I-- Average database 60 60 - Japanese benchmark -

Quoliry adjusted

55

50

45 - - Export unit value 45 ---- Average darabase 40 - - Japanese benchmark - 40 - Quality adjusted

US@ , , , , , , , , US%/r , , , , , , , , 1989 1990 1991 1992 1993 1994 1995 1996 1989 1990 1991 1992 1993 1994 1995 1996

(c) Semisojl and PC1 coal (d) To&[ metallurgical cod 65 65 ---- Average database ---- Average darabase , 60 -- Japanese benchmark - - Japanese benchmark - Quality adjusted Quality adjusted

50

45

40 40

US$/: , , I , , , , , UsUr , , , , , , , , 1989 1990 1991 1992 1993 1994 1995 1996 1989 1990 1991 1992 1993 1994 1995 1996

a For lapatme fiscal years. Prices in JFY 1995 US dollar$.

COAL PRICING

coal used for electricity generation and cement manufacture in south Asia tend to be moderately (up to 12 per cent) higher than average prices while, based on a small number of coal shipments, there is considerable relative price volatility for coal used in general industry.

For Australia's coal exports to Europe, quality adjusted hard coking coal prices tended to be slightly lower than average prices up to JFY 1993, after which the pattern reversed. Thermal coal for use in electricity generation is the only other category of coal for which there are a significant number of coal shipments to Europe. In this category, there were moderate (up to 5 per cent) deviations between the two price series in the study period, with no pattern evident in these differences.

Australia's coal shipments to the Americas mainly comprise hard coking, semisoft coking and PC1 coal. Quality adjusted prices for hard coking coal

Prices for Australia's metallurgical and thermal coal exports to Japan a contmued) D ,

(a) Eleclricily gcnerPfion (6) General induslry 55 55

I--- Average database 45 50 -\"-,- ; i----zls- 40

35 ---- Average database 30 - - Japanese benchmark - 3O - Quality adjusted

us.W , , , , , , , , USPt , , , , , , , , 198919901991 199219931994 199519% 198919901991 19921993199419951996

(c) Cement manufacture (d) Total thermal coal 55 55 ---- Average darabose ---- Average database 50 Quality ndlusted - Qualily adjusted \\;uA. ; -<---I; 45

40

35 . 30 30

U S @ t , , , , , , , , USPt , , , , , , , , 1989 1990 1991 1992 1993 1994 1995 1996 1989 1990 1991 1992 1993 1994 1995 1996

0 For Japanese fiscal yean. Priscs in J F I 1995 US dollars.

COAL PRICING

tended to be moderately (up to 4 per cent) lower than average prices up to JFY . . - 1994, but exceeded average prices by aro"nd 1 1 per cent inlboih JFY i995 and JFY 1996. By contrast, quality adjusted prices for semisoft coking and PC1 coal tended to be moderately (up to 4 per cent) higher than average prices across the study period, with the exceptions of JFY 1995 and JFY 1996 when they were moderately (up to 4 per cent) lower.

Quality adjusted prices by coal category A regional comparison of quality adjusted prices for each coal category is given in figure F. Quality adjusted prices of Australia's hard coking coal exports to North Asia were consistently about US$0.3-0.4 a tonne (in JFY 1996 prices) lower than quality adjusted prices for Japan across the study period. Quality adjusted prices for west Asia fluctuated around the price for

E Prices for Australia's metallurgical and thermal coal exports to North Asia a

(a) Hard coking coal @I) Soft coking coal 65 65 ---- Average database

Quality adjured - - Japanese benchmark

50

45 - - Erpon unir value 45 ---- Average database 40 - - Japanese benchmark - 40 - Quality odjusred

uSPr , , , , , , , , USWf , , , , , , , I 1989 1990 1991 1992 1993 1994 1995 1996 198919901991 19921993199419951996

(c) Semisoft and PC1 coal (d) Total metallurgical coal 65 65 ---- Average database - - fiport unir value 60 -- Japanese benchmark - -I-- Average darabase - Quality adjured 60 Quality adjusted

55

50 50

45 45

40 40

U S P r l l , , , l , , USPi , , , , , , , , 1989 1990 1991 1992 1993 1994 1995 1996 198919901991 19921993 1994 19951996

a For Japamw fiscal y-. Riess in JFY 1995 US dollan.

COAL PRICING,

Japan - from US$1.2 and US$1 a tonne above in JFY 1989 and JFY 1990 respectively to US$2.7 a tonne below in JFY 1993 -but were similar to the price for Japan in all other years. Consistent with higher transport costs to end market, quality adjusted prices for Europe and the Americas tend to be US$2-5 a tonne lower than prices for Japan, although coal exported to Europe was not lower in the last three years of the study.

Similar to hard coking coal, quality adjusted prices of Australia's soft coking coal exports to North Asia are consistently about US$0.3-0.4 a tonne lower than quality adjusted prices for Japan. However, this price relationship is reversed for semisoft coking and PC1 coal. Quality adjusted prices of semisoft coking and PC1 coal for the Americas tend to be around US$2-3 a tonne lower than prices for Japan.

E Prices for Australia's metallurgical and thermal coal exports to North Asin a (continued)

(a) Electricity generation (b) General industry 50 5 0

---- Average database Quality adjusted -

40

35 35

---I Average database 30 ---- - Japanese benchmark - 30

Quality adjusted ...I*-' US$/l , , , , , , , , ~ S ~ , , , , , , , ,

1989 19901991 1992 1993 1994 1995 19% 1989 19901991 1992 1993 1994 199519%

(c) Cement manufactnre (d) Total thermal coal 5 0 5 0 ---- Average datnbnse ---- Average database Quality adjured

Quality adjusted - - Export unit value - 40

35 3 5

30 3 0

US@ , , , , , , , , USQt , , , , , , I I

198919901991 19921993 1994 199519% 1989 1990 1991 1992 1993 1994 1995 19% (I For lnpancse f i s d y m . Ricer in JW 1995 US dollars.

COAL PRICING

EgionZquality adjusted prices for total metallurgical coal reflect differences in the relative quantities of particular metallurgical coal types which are exported to each region, as well as transport cost differences. The extent to which differences in quality adjusted prices of metallurgical coal are not explained by these factors suggests the presence of other important influences. The major 'anomaly' for metallurgical coal is the quality adjusted price of hard coking coal to Europe in JFY 1994 and subsequent years, although this outcome is based on a small number of coal shipments.

There is a greater regional divergence in the quality adjusted prices for thermal coal end use categories than in those for metallurgical coal types. For each thermal coal end uiecategory, quality adjusted price> for Japan kxceeded those for north Asia, across the study period, although the extent of this divergence tended to be smaller in JFY 19448nd subsequent years, particularly for

F Quality adjusted metal1ur~'cal and thermal coal prices for all regions a

(a) Hard coking coal (b) Sofi coking coal 65 65 - North Asia :=7- iy 50 - Arncricos 45 - -- Europe 45 - West Asia 40 - - Nonh Asia 40 - Japan

USM , , , , , , , , US$h , , , , , , , , 1989 1990 1991 1992 1993 1994 1995 1996 1989 1990 1991 1992 1993 1994 1995 1996

(c) Semisofl and PC1 coal (dJ Total metallurgical coal 65 65

- Americas 60 - Nonk Asia - 60 - Japan 55 55

:- :: 40 40

usm , , , , , , , , USM , , , , , , , , 1989 19901991 1992 1993 1994 1995 19% 1989 1990 1991 1992 1993 1994 1995 1996

n For Japaoese fiscal yean. Pnees in JFY 1995 US dollars.

COAL PRICING

industry and cement manufacture. In these latter years, the difference was close to US$1 a tonne (the only exception being a divergence of US$2.60 a tonne for electricity generation in JFY 1995). Thus, even in the latter years when the difference was smallest, it was still more than double that for metallurgical coal. That is, there is no consistent difference between the quality adjusted prices for Japan and north Asia across all coal categories which could be explained by transport costs.

The quality adjusted price for thermal coal tends to be highest for that used in electricity generation, followed by general industry and cement manufacture. Similar to metallurgical coal, regional quality adjusted prices for total thermal coal are expected to largely reflect differences in the relative export quantities of particular thermal coal end use categories and transport cost differences. However, there is a relatively large number of thermal coal shipments which

Quality adjusted rnetnllurgical and thermal coal prices for all regions a F continued

(a) Electricity g e n e r d n (b) General industry 50

- Soulh Asia 45 %?$ - Nonh Asio *+ - Norrh Asio - - Japan 40 - 35 - 35 '' 30 '+ 30

USVl , , , , , , , , USVl , , , , , , , , 1989 1990 1991 1992 1993 1994 1995 19% 1989 1990 1991 1992 1993 1994 1995 19%

(c) Cement manufacture (d) Total thermal coal 50 45-E ;-&. 40

35

30 30 '' . ,# .'

U S V t , 1 , , , , , I USVl , , , , , , , I

1989 1990 1991 1992 1993 1994 1995 1996 198919901991 1992 1993 1994 1995 1996 n For Japanese fiscal yuus. Prices in IFY 1995 US dollars.

COAL PRICING - - - - -- -

are negotiated in the spot market. The extent to which there are spot transactions, particularly if there is arelatively small number of coal shipments to any given region, is likely to increase the variability in the relationship between regional quality adjusted prices. This is because spot transactions are subject to short term market influences considerably more than are long term or term contract sales. This variability is most evident in the quality adjusted prices of Australia's thermal coal exports to south Asia.

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5. Conclusion

In this study, price-quality relationships for Australia's black coal exports for JFY 1989-96 have been estimated usine information collected bv DPIE as vart of the coal export controls process. ~ u a ? i t ~ adjusted coal prices \;ere estimited using the average quality of Australia's coal exports in JFY 1995 (JFY 1994 for soft coking coal). Quality adjusted coal prices account for changes in coal quality over time and between regions, thus providing a more accurate indicator of underlying coal price movements. Quality adjusted coal prices will be similar to average coal prices to the extent, for each coal category, that coal quality is relatively stable and.for each region similar to the average coal quality.

Overall, the differences in the quality adjusted prices of Australia's metallurgical coal exports to Japan and other regions do not tend to be large. Excluding west Asia, quality adjusted prices for Japan tend to be slightly higher for hard coking coal, but slightly lower for semisoft and PC1 coal. Quality adjusted prices for hard coking coal exports to west Asia were similar to those for Japan in a number of years, and prices to west Asia fluctuated around the Japanese price in other years. By contrast, quality adjusted prices for thermal coal exports to Japan tend to exceed those to other export markets, although the price gap has narrowed markedly since JFY 1993.

Thus, Australia's coal export prices to Japan do not tend to diverge substan- tially from prices to other markets for each metallurgical coal category, and tend to be above other export market prices for thermal coal. However, as discussed in Hogan et al. (1997), whether Japan's dominant market position influences the absolute price level of different coal categories in the regional coal market remains an issue.

COAL PRICING - - - - - - -

Appendix A: General hedonic price relationships

Hedonic price theory is based on the principle that differences in the prices of differentiated or heterogeneous goods sold in the same market at the same time largely reflect differeGces in &e characteristics of the goods. The theory suggests for this study that the relative prices of different coal brands sold into the same market at the same time reflect the relative quality characteristics of the coal brands. As indicated in chapter 2, coal is mainly differentiated by value in its end use.

The most important results from the hedonic price relationship are the estimated implicit prices for quality characteristics and the estimated quality adjusted prices of coal in each time period. The implicit price of each characteristic, which is a measure of the amount that producers receive and buyers pay for the particular quality characteristic, is determined by the interaction of sellers and buyers in the market. Thus, the hedonic price model reflects the outcome of both the demand for and supply of the various quality characteristics. Assuming coal users aim to maximise profit and operate in a competitive market, the implicit price of each quality characteristic is equal to its value of marginal product.

The general hedonic price relationship may be written as follows:

whereby P, the price of coal in shipment i, is some function of K coal quality characteristics, QCki (k = l ,2 , . . ., K).

There are two key aspects to the hedonic price relationship - the choice of quality characteristics and the functional form of the relationship between price and quality characteristics.

Choice of quality characteristics -

Quality characteristics should only be included if they are likely to have value in use to buyers, or to have a significant impact on the marginal costs of producers. The coal quality characteristics which are available from the coal export controls database and which are used as end use performance indicators include total and inherent moisture content (TM and IM respectively), volatile matter content (VM), ash content (ASH) and sulphur content (SULPHUR) for

D

COAL PRICING

all coal shipments, crucible swelling number (CSN) for metallurgical coal only, and calorific value (CALORIE) and the Hardgrove grindability index (HGI) for thermal coal only. Fixed carbon content (FCC) is also available because this is derived by difference, as described in chapter 2, such that:

Choice offunctional form When there is little information about the nature of the relationship between price and quality characteristics, functional forms which are often used include linear, log-linear and quadratic specifications.

If the relationship between price and quality characteristics is linear (or additive), the general hedonic price relationship in equation A1 reduces to:

(A31 Pi = a. + a l QCli + a2 QCzi+ ... + aK QCKi

where ak (k = 0, 1 , . . ., K ) are parameters to be estimated. The coefficients, ak (k = 1 , 2, . . ., K ) , are equivalent in the linear model to the implicit price of quality characteristic k (that is, QCk).

If the relationship between price and quality characteristics is multiplicative, the general hedonic price relationship in equation A1 can be rewritten as:

644) Pi = ebo . QC, f l . QC2,b2 . . . QCKfK

which can be simplified to the following log-linear model:

(A5) In Pi = bo + bl in QCli + bz in QCzi ..., + bK in QCKi

where In represents the natural logarithm and bk (k = 0,1, . . ., K) are parameters to be estimated. The coefficients, bk (k = 1,2, . . ., K), are equivalent in the log- linear model to the price elasticity of quality characteristic k. That is, bk is the percentage change in price given a 1 per cent increase in quality characteristic k.

A common approximation of a general relationship, as given in equation Al, is the following quadratic equation:

COAL PRICING

where co, ck and cjk G, k = 1, 2, ..., K) are parameters to be estimated. This specification allows for the possibility that the relationship between a quality characteristic and price is U-shaped. This form also allows for interaction effects between different quality characteristics. There are several variations of the quadratic a~~roximation of the general functional form in equation Al , inc1udi;lg the trksiog form. It is evident from equation A6 that the quadratic eauations are considerablv more com~lex and require more data than either thk linear or log-linear spdcifications & equations A3 and A4 respectively.

COAL PRICING

Appendix B: Correlation coeficients for the quality characteristics of Australia's coal exports to Japan

7Correlation coeficients for qualio characteristics: metallurgical coal a

Level terms FCC TM IM VM ASH SULP CSN

Squared terms FCC*FCC TM*TM IM*IM VM*VM ASH*ASH SULP*SULP CSN8CSN

Interaction terms F C F T M FCC*IM FCC*VM FCC*ASH FCC*SULP FCC8CSN TM*IM TM*VM TM*ASH TM*SULP TM*CSN IM*VM IM*ASH IM*SULP IM*CSN VM*ASH VM*SULP VM*CSN ASH*SULP ASH*CSN SULP*CSN

FCC no.

1.00 0.09

-0.83 -0.99 0.10

-0.35 0.48

TM no.

IM no.

VM ASH no. no.

SULP CSN no. no.

-0.27 0.35 0.17 -0.64 0.31 -0.26 ,

-0.31 0.14 0.91 0.18

-0.09 0.98 0.21 -0.64 0.33 -0.41

-0.11 -0.22 0.95 -0.05

-0.04 0.97 0.29 -0.58 0.20 -0.72 0.73 -0.50 0.12 0.53 0.28 4 .53 0.88 -0.23 0.12 0.85 0.90 -0.14

-0.07 0.96 0.50 0.82

Continued 0

COAL PRICING

coefficients for quality characteristics: metallurgical coal

FCC* TM* IM* VM* ASH* SULP* CSN* FCC TM IM VM ASH SULP CSN

no. no. no. no. no. no. no. Level terms FCC TM IM VM ASH SULP CSN

Squared terms F C C FCC TM*TM ZMLZM VM*VM ASH*ASH SULP*SULP CSN* CSN

Interaction terms FCC*TM

FCC* VM FCCASH FCCSULP FCC*CSN TM*ZM TM*VM TM*ASH TM*SULP TM*CSN IM*VM IM*ASH ZM*SULP IM*CSN VM*ASH VM*SULP VM*CSN ASH*SULP ASH*CSN SULP* CSN

-0.27 0.41 0.12 -0.64 0.31 -0.30

-0.31 0.18 0.87 0.25

-0.09 0.98 0.17 -0.63 0.32 -0.41

-0.14 -0.15 0.91 0.03

-0.05 0.97 0.27 -0.60 0.15 -0.71 0.71 -0.48 0.10 0.46 0.25 -0.54 0.89 -0.22 0.13 0.80 0.84 -0.07

-0.08 0.94 0.49 0.84

Continued 0

COAL PRICING

Correlntion coeflcients for qualify characteristics: metallurgical coal 7 (continued)

FCC* FCC* FCC* FCC* F C C FCC* TM* TM IM VM ASH SULP CSN IM

no. no. no. no. no. no. no. Level t e r n FCC TM IM VM ASH SULP CSN

Squared terms FCC*FCC TM*TM IM*IM VM*VM ASH*ASH SULP*SULP CSNSCSN

Interaction terms FCC*TM

Continued 0

COAL PRICING

Correhhon coeficients for quality characteristics: metallurgical coal 7 (continued,

TM* TM* TM* TM* IM* IM* IM* VM ASH SULP CSN VM ASH SULP

no. no. no. no. no. no. no. Level term FCC TM IM VM ASH SULP CSN

Squared terms F C C F C C TM*TM

ASH*ASH SULP*SULP CSN* CSN

Interaction terms F C C T M FCC*IM FCC*VM FCC*ASH FCC*SULP F C C CSN TM*IM TM*VM 1.00 TM*ASH 4 . 0 1 TM*SULP 0.39 TM*CSN 4.33 IM*VM 0.86 IM*ASH 0.70 IM*SULP 0.72 IM* CSN 0.27 VM*ASH 0.80 VM*SULP 0.67 VM*CSN 0.04 ASH*SULP 0.24 ASH*CSN -0.48 SULP*CSN 4.18

1.00 -0.57 1.00 -0.69 0.90 1 .OO 4 .49 0.83 0.76 1.00 0.50 0.29 0.07 0.18

-0.52 0.79 0.81 0.65 -0.24 0.63 0.46 0.89

0.81 4.16 4.42 4 . 1 6 4.13 0.22 0.29 0.64 0.94 4.65 4.69 4.55 0.79 -0.34 4.50 4.05

Continued 0

COAL PRICING

Correlation coeficients for quality characteristics: metallurgical coal 7 (continued)

IM* VM* VM* VM* ASH* ASH* SULP* CSN ASH SULP CSN SULP CSN CSN

no. no. no. no. no. no. no. Level terms FCC TM IM VM ASH SULP CSN

Squared terms FCC*FCC TM*TM IM*IM VM*VM ASH*ASH SULP*SULP CSN*CSN

Interaction terms FCC*TM FCC*IM

TM*IM TM*VM TM*ASH TM*SULP TM* CSN IM*VM IM*ASH IM*SULP IM*CSN 1.00 VM*ASH 0.04 1.00 VM*SULP 0.21 0.59 1 .OO VM*CSN 0.78 -0.16 0.11 1.00 ASH*SULP -0.07 0.41 0.75 -0.07 1.00 ASH* CSN 0.40 -0.47 -0.30 0.75 -0.06 1 .OO SULP*CSN 0.53 -0.31 0.26 0.79 0.36 0.77 1.00 a Fw JFf 198946. Quality characteri~tics indude FCC (fixed carbon content). TM (total moisture), IM (inherent moisture), VM (volatile matter), ASH, SULP (sulphur) and CSN (crucible swelling number).

COAL PRICING

8 Correlation coefJieients for quality characteristics: thermal coal a

CAL FCC TM IM VM ASH SULP

Level terms no. no. no. no. no. no. no.

CAL 1.00 FCC 0.49 1.00 TM -0.04 -0.27 1.00 IM -0.29 4 . 6 6 0.46 1.00 VM -0.14 -0.88 0.40 0.60 1.00 ASH -0.70 -0.24 4 . 3 3 -0.07 -0.24 1.00 SULP -0.16 -0.19 0.05 4 .02 0.16 0.11 1.00 HGI 0.40 0.75 -0.35 -0.60 -0.72 -0.03 4 . 2 0 Squared terms CAL*CAL 1.00 0.49 -0.04 -0.29 -0.14 4 .70 -0.16 FCC*FCC 0.49 1.00 -0.26 -0.63 -0.88 -0.23 -0.20 TM*TM -0.03 -0.25 1.00 0.45 0.37 -0.32 0.03 IM*IM -0.27 -0.62 0.40 0.97 0.54 -0.02 -0.07 VM*VM -0.12 -0.88 0.39 0.63 0.99 -0.24 0.15 ASH*ASH -0.68 -0.22 4 .34 -0.08 -0.25 0.99 0.12

Interaction terms

- HGI no.

COAL PRICING

8 Correlation coefficients for quality characteristics: thermal coal a (continued)

Level terms

CAL* CAL

no.

FCC* FCC

no.

TM* TM no.

IM* IM no.

VM* VM no.

ASH* ASH

no.

SULP* S U P

no.

HGI* HGI

no.

CAL FCC

ASH SULP

Squared terms CAI.*CAl. 1 .W . - .- -. . - FCCFCC 0.50 1.00 TM*TM -0.03 -0.25 1.00 - ~ - ... - .. - -- - ~-

IM*ZM -0.27 -0.58 0.40 1.00 VM*VM -0.13 -0.87 0.37 0.58 1.00 ASH*ASH -0.68 -0.21 -0.32 -0.03 -0.25 1.00 SULP'SULP -0.17 -0.18 0.00 4 .08 0.12 0.15 1.00 HGZ'HGZ 0.40 0.74 -0.32 -0.48 -0.68 0.01 -0.18 1.00

Interaction terms CAL*FCC 0.68 0.97 4 .22 -0.58 -0.77 -0.36 -0.19 0.72 CAL*TM 0.25 -0.11 0.95 0.30 0.34 -0.53 -0.04 -0.22 CAL*ZM -0.20 -0.60 0.46 0.96 0.64 -0.16 -0.05 -0.55 CAL*VM 0.05 -0.80 0.37 0.48 0.97 4.38 0.10 -0.64 CAL*ASH -0.59 -0.17 -0.37 4.08 -0.29 0.98 0.12 0.05 CAL*SULP -0.07 -0.16 0.03 -0.09 0.14 0.06 0.97 -0.17 CAL*HGI 0.57 0.78 -0.29 4 . 5 2 -0.65 -0.14 -0.20 0.98 FCC*TM 0.36 0.58 0.63 -0.18 -0.38 -0.47 -0.12 0.28 FCC*IM -0.16 -0.35 0.47 0.87 0.40 -0.23 4 . 0 7 -0.43

Continued 0

65

COAL PRICING

8 Correlation coeflcients for quality characteristics: thermal coal a (continued)

Level terms CAL FCC TM IM VM ASH SULP HGI

Squared terms CAL*CAL FCC*FCC TM*TM

Interaction terms CAL*FCC CAL*TM CAL*IM

CAL* CAL* CAL* CAL* CAL* CAL* FCC TM IM VM ASH SULP

CAL* HGI

~ ~

Continued 0

COAL PRICING ~ - ~ 8 Correlation coefjicients for quality characteristics: thermal coal a (continued)

Level terms CAL FCC

VM ASH SULP HGI

Squared terms CAL*CAL FCC*FCC TM*TM IM*IM VM*VM ASH*ASH SULP*SULP HGI*HGI

Interaction terms CAL'FCC CAL*TM CAL*IM CAL*VM CAL*ASH CAL*SULP CAL*HGI FCCTM FCCIM FCCVM FCCASH FCC*SULP FCC*HGI TM*IM

FCC* FCC* FCC* FCC* FCC* FCC* TM IM VM ASH SULP HGI no. no. no. no. no. no.

TM* IM

Continued 0

COAL PRICING

8 Correlation coeflcients for quality characteristics: thermal coal a (continued)

- - -

TM* TM* TM* TM* IM* IM* VM ASH SULP HGI V M ASH no. no. no. no. no. no.

IM* SULP

no. Level terms CAL FCC TM IM VM ASH SULP HGI

Interaction terms CAL*FCC CAL*TM CAL*IM CAL*VM

TM*IM TM*VM 1.00 TM*ASH 0.15 1 .OO TM*SULP 0.29 0.21 1.00 TM*HGI -0.06 -0.06 0.00 1 .OO IM*VM 0.78 0.18 0.10 -0.30 1 .OO IM*ASH 0.44 0.62 0.10 -0.34 0.80 1 .OO IM*SULP 0.46 0.25 0.82 -0.22 0.56 0.56 1.00 IM*HGI 0.48 0.12 0.03 0.11 0.79 0.72 0.49 VM*ASH 0.44 0.72 0.21 -0.52 0.52 0.71 0.41 VM*SULP 0.41 0.12 0.93 -0.25 0.25 0.16 0.84 VM*HGI 0.55 -0.27 0.07 0.20 0.30 -0.07 0.10 ASH*SULP -0.03 0.47 0.83 -0.23 -0.04 0.23 0.71 ASH*HGI -0.66 0.46 -0.16 0.1 1 -0.50 -0.03 -0.26 SULP*HGI -0.10 0.06 0.88 0.11 -0.21 -0.12 0.64

Continued 0

COAL PRICING

8 Correlation coefficiene for quality characteristics: thermal coal a (continued)

IM* VM* VM* VM* ASH* ASH* SULP* HGI ASH SULP HGI SULP HGI HGI no. no. no. no. no. no. no.

Level terms CAL FCC TM IM V M . ..& ASH SULP HGI

Squared terms CAL*CAL FCC*FCC TM*TM IM*IM VM*VM ASH*ASH SULP*SULP HGICHGI

a For IFY 1989-96. Quality characteristics include CAL (calorific value), FCC (fixed catbon content), TM (total moisture), IM (inherent moishlre), VM (volatile matter). ASH, SULP (sulphur) and HGI (hardgrove grindability index).

COAL PRICING

Appendix C: Use ofdummy variables in estimating price-quality relationships

Dummy variables for changes in quality adjusted prices over time Coal shipments are identified for JFY 1989-95. The impact of each specified quality characteristic on the real coal price is assumed to be constant over this period. However, changes in supply and demand for coal influence aggregate coal prices. To illustrate the use of dummy variables to take into account changes in general prices in each time period, assume that the coal price is only related to a single quality characteristic, QC, and that there are only two time periods (1994 and 1995). The price-quality relationship in each year is then given by the following:

(c1) Pi = a. + al Qci for coal shipments in 1994

= bo+al QCi for coal shipments in 1995

where ao, bo and a , are parameters to be estimated. Define two dummy variables corresponding to each year as follows:

(c2) DJFY94[ = 1 for coal shipments in 1994

= 0 for coal shipments in 1995

(c3) DJFY95, = 0 f or coal shipments in 1994

= I f or coal shipments in 1995.

By definition, these dummy variables sum to unity for each coal shipment i, or:

Incorporating these dummy variables into equation C1, and using the result in equation C4, gives the following:

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= (a0 + a, QCi) DJFY94; + (bo + al QC,) (1 - DJFY94i)

This equation can be rewritten in a general form, consistent with the approach taken in equation 8 in chapter 3, as the following:

where gk (k = 0, 1,2) are parameters to be estimated. Including shipments for the entire period (JFY 1989-95) is a simple extension of this case, such that equation C5 can be rewritten as:

where dummy variables are defined analogous to that for 1994 and gk (k = 0, 1, . . ., 7) are now the parameters to be estimated.

Dummy variables for long term, term and spot contracts Coal shipments are classified by contract type. Dummy variables are included in the empirical equations to allow for the possibility that contract type may have a significant influence on the price received. Again, assume for simplicity that the coal price is only related to a single quality characteristic, QC. How- ever, now assume that there is only a single time period. The price-quality relationship for each contract type is then given by:

(C8) Pi = a. + al QCi for coal shipments under long term contracts

= bo + al QC; for coal shipments under term contracts

= co + al QC, for coal shipments under spot contracts

where ao, bo, co and al are parameters to be estimated. Define three dummy variables corresponding to each contract type as follows:

(C9) DLTERMi = 1 for shipments under long term contracts

= 0 for shipments under term or spot contracts

COAL PRICING

(C 10) D T E W 1 for shipments under term contracts

= 0 for shipments under long term or spot contracts

(c11) DSPOT, = 1 for shipments under spot contracts

= 0 for shipments under long term or term contracts,

By definition, these dummy variables sum to unity for each coal shipment i , or:

Using the approach given above, these dummy variables are incorporated into equation C8, and the results in equation C12 are used, giving the following:

This equation can be rewritten in a general form, consistent with the approach taken in equation 8 in chapter 3, as the following:

where gk (k = 0, 1,2,3) are parameters to be estimated.

It may be more realistic to assume that the spot price relative to prices under either long term and term contracts varies over time. In this case, assume there are two time periods (1994 and 1995 as before). Coal prices are then given by the following:

(C15) Pi=ao+alQCi for shipments under long term contracts: 1994

= bo + al QCi for shipments under long term contracts: 1995

= co + al QCi for shipments under term contracts: 1994

= d o + a l QCi ' for shipments under term contracts: 1995

= eo+ a l QCi for shipments under spot contracts: 1994

=fo+ a1 Qci for shipments under spot contracts: 1995

COAL PRICING

where ao, bo, co, do, eo, fo and al are parameters to be estimated. Using the dummy variables defined previously, equation C15 can be rewritten as follows:

(C16) Pi = ([ao + al QCil DLTERMi + [co + al QCiJ DTERMi

+ [eo + al QCi] DSPOT) DJFY94; + ([bo + a , QC;] DLTERMi

+ [do + a , QC;] DTERMi + (&, + a1 QCi] DSPOT;) DJFY95;

= ([ao + a , QC;] DLTERMi + [co + al QCi] DTERM,

+ [eo + al QCi] DSPOTi) DJFY94i + ([bo + al QCi] DLTERMi

+ [d, + a , QCi] DTERMi + ++a+ QCi] DSPOTi) ( 1 - DJFY94;)

= (bo + a , QC;) DLTERMi + (do + al QCi) DTERW

+ Cfo + al QCi) DSPOTi + ([ao - bo] DLTERMi

+ [c0 - do] DTERMi

+ [eo - f o ] DSPOTi) DJFY94;

= (bo + al QCi) ( 1 - DTERM, - DSPOT;) + (do + a, QC;) DTERM,

+ 6 + a , QCi) DSPOT, + ([ao - bo] [ 1 - DTERM, - DSPOT;]

+ [c0 - do] DTERM, + [eo - fo] DSPOT;) DJFY94;

= bo + a , QCi + (do - bo) DTERM, + Cfo - bo) DSPOTi + (ao - bo) DJFY94i

+ (bo + co - a. - do) DTERw.DJFY94i + (bo + eo - a0 - fo) DSPOTi.DJFY94;

It is possible that the gap between the coal price under long term and term contracts, for similar quality characteristics, is constant over time. If this is the case, and this hypothesis can be tested empirically, equation C16 reduces to the following simpler form:

(C17) Pi = bo + al QCi + (do - bo) DTERMi + + - bo) DSPOTi

since (co - ao) = (do - b o ) If there is no significant gap between long term contract prices and term contract prices, the relationship simplifies further to the following:

since a. = co and bo = do.

COAL PRICING

The specification in equation (C16) can be expressed in the following general form:

where gk (k = 0, 1 , . . . , 8 ) are now parameters to be estimated.

Dummy variables to represent kinks in price-quality relationships

It was hypothesised in chapter 3, that there are two linear segments (that is, a single kink) in the relationship between coal price and volatile matter. The appropriate specification for the dummy variables is derived in this section. Spline functions are explained in Greene (1993).

For simplicity, assume the coal price, Pi, in each shipment i is related to a single quality characteristic, volatile matter (VM), such that:

(c20) Pi = a,, + al VMi for VMi < VM*

= bO + bl VMi for VMi 2 VM*

where ak and bk (k = 0, 1 ) are parameters to be estimated and VM* is the point at which the kink is hypothesised to occur. VM* is derived from equation C20 by equating the two expressions and is given by:

( c 2 1) VM* = (bo - ao) l (a, - b l )

Define two dummy variables corresponding to each of these linear segments as follows:

(c22) DVMli= 1 for VMi < VM* = 0 for VMi 2 VM*

(c23) DVM& = 0 for VMi < VM* = 1 for VMi 2 VM*.

By definition, these dummy variables sum to unity for each coal shipment i, or alternatively:

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By incorporating the dummy variables into equation C20 and using the results in equations C21 and C24, the price-quality relationship can be written as a single equation as follows:

( ~ 2 5 ) Pi = (ao + al VM,) DVMli + (bo + bl VMi) DVM2,

= (ao + a, VMi) (1 - DVM2J + (bo + bl VMi) DVM2i

= a. + a1 VMi + (bo - ao) DVM2, + (b l - a l ) VMi.DVM2i

=ao + a1 VMi + (al - b l ) VM*.DVM2i + (bl - al ) VMi.DVM2,

= a. + al VMi + (bl - a l ) (VMi - VM*) DVM2,

This equation can be rewritten in a general form, consistent with the approach taken in equation (8) in chapter 3, as the following:

(C26) Pi = go + gr VM, + gz (VMi - VM*) DVMi

where gk (k = 0, 1,2) are parameters to be estimated and DVMi= DVM2i.

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Appendix D: Econometric results

Notation used in the econometric results in table 9 Subscripts i Coal shipment i from Australia k Coal quality characteristic k

Coal prices Pi Price of coal in shipment i from Australia (1995 US$ a

tonne)

Coal quality characteristics Qck Quality characteristic k (general formulation) FCC, Fixed carbon content of coal in shipment i (per cent, air

dried basis) TM, Total moisture content of coal in shipment i (per cent, as

received) IMi Inherent moisture content of coal in shipment i (per cent,

air dried basis) VMi Volatile matter content of coal in shipment i (per cent, air

dried basis) ASH, Ash content of coal in shipment i (per cent, air dried basis) SULPHUR, Sulphur content of coal in shipment i (per cent) CALORIE, Calorific value of coal in shipment i (kcaVkg, air dried

basis) LN(CALORIEi) Natural logarithm of calorific value of coal in shipment i CSN, Crucible swelling number (or free swell index) for coal

in shipment i HGl, Hardgrove grindability index for coal in shipment i

Dummy variables (equals 0 except as specified) Dummy variables for annual changes in the general level of coal prices DJFY89, Value of 1 for JFY 1989 DJFY90, Value of 1 for JFY 1990 DJFY9 1 , Value of 1 for JFY 1991 DJFY92; Value of 1 for JFY 1992 DJFY93; Value of 1 for JFY 1993 DJFY94, Value of 1 for JFY 1994 DJFY96, Value of 1 for JFY 1996

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Dummy variables for differences associated with spot sales DSPOT, Value of 1 for spot contracts DSP0T8gi Value of 1 for spot contracts in JFY 1989 DSPOZ90i Value of 1 for spot contracts in JFY 1990 DSPOZ9 1 Value of 1 for spot contracts in JFY 1991 DSPOT92, Value of 1 for spot contracts in JFY 1992 DSPO193i Value of 1 for spot contracts in JFY 1993 DSPOZ94i Value of 1 for spot contracts in JFY 1994 DSP0796i Value of 1 for spot contracts in JFY 1996

Dummy variables for regional differences DREGli Value of 1 for contracts with Japan DREG2i Value of 1 for contracts with North Asia DREG3i Value of 1 for contracts with South Asia DREG4, Value of 1 for contracts with West Asia DREGSi Value of 1 for contracts with Europe DREG6, Value of 1 for contracts with the Americas D**REHi Value of 1 for contracts in year ** (JFY 1989 to JFY 1996

respectively) with region # (Japan, north Asia, south Asia, west Asia, Europe and the Americas respectively)

Dummy variables for dixerences between coal categories DSOFT, Value of 1 for soft coking coal; 0 elsewhere DSEMZSOFTi Value of 1 for semisoft coking and PC1 coal; 0 elsewhere DINDUSTRYi Value of 1 for thermal coal in general industry; 0

elsewhere

Dummy variables for quality characteristics DVMi Value of 1 for volatile matter; 0 elsewhere D**CALORIEi Value of 1 for calorific value in year ** (JFY 1989 to JFY

1996 respectively)

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9 Econometric results a

Thermal coal Metallurgical coal:

iron and steel making b Electricity - Japan c Electricity - other c Other bd

Estimate t-statistic Estimate t-statistic Estimate t-statistic Estimate t-statistic e

Independent variable Constant term DJFY89 DJFY90 DJFY91 DJFY92 DJFY93 DJFY94 DJFY96 DSPOT DSPOT89 DSPO790 DSPO791 DSPOT92 DSPO793 DSPO794 DREGZ DREG3 DREGS DREG6 D89REG2 D9OREG2

Continued 0

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9 Econometric results a (continued)


iron and steel making b Electricity -Japan c Electricity - other e Other bd

Estimate t-statistic Estimate t-statistic Estimate t-statistic Estimate tstatistic e

Independent variable IM ASH SULPHUR CSN CALORIE

D91CAWRIE D94CAWRIE D96CAWRIE DSOFT DSOFT*ASH DSOFT*

SULPHUR DSOFT* DREG4

DSOFT* DREG6 4.12 5.27 - - - - - -

DSEMISOFT -16.17 -11.10 - - - - - - DSEMISOFT* IM

DSEMISOFT* VM

DSEMISOFT* DVM* I VM-30)

DSEMISOFT* ASH

DSEMISOFT *DREG2

DINDUSTRY DINDUSTRY*

VM DINDUSTRY* SULPHUR

~ -~

Continued 0

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9 Economehic results a (continued)


iron and steel making b Electricity - Japan c Electricity - other c Other bd

Estimate t-statistic Estimate t-statistic Estimate t-statistic Estimate t-statistic e

Independent variable Adjusted R squared 0.96 0.98 0.72 0.91 No. of observations 1255 459 341 1351 RESET

test 2 f F(1.1219) 1.99 F(1.441) 0.27 F(1.324) 0.06 F(1,1321) 0.96 RESET

test 3 f F(2,1218) 1.01 F(2,440) 0.35 F(2,323) 4.17 F(2,1320) 10.77 RESET

test 4 f F(3.1217) 0.76 F(3.439) 0.24 F(3,322) 3.07 F(3,1319) 7.17 LM test 1 g CHISQ(1) 0.09 CHISQ(1) 3.33 CHISQ(1) 0.88 CHISQ(1) - LM test 2 g CHISQ(1) 0.15 CHISQ(1) 3.54CHISQ(1) 0.59 CHISQ(1) - LM test 3 g CHISQ(1) 0.05 CHISQ(1) 3.08 CHISQ(1) 1.21 CHISQ(1) - a Estimated by ordinary least squares using the TSP software package. All repotted coefficienu are significantly different from rn at the 5 per cent significance level. b The dependent variable is the real coal price (1995 US$/t). e The dependent variable is log of the real coal price (1995 USSIt). d Cement and general industry. e White's heteroskedastic consistent t statistics. f Reset tests are based on the F distribution and are tests of general misspecification of functional form. The null hypothesis of correctly specified functional form is accepted at the 5 per cent significance level in all cases except RESET tests 2 and 3 for other electricity, cement and general indushy. g LM (Lagrange multiplier) tests are based on the chi-squared distribution and are tests of hetemskedasticity. The null hypothesis of no heteroskedasticity is accepted nt the 5 per cent significance level in all reported cases.

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