Impact of Australian tree species selection research in China: an economic perspective

Forest Ecology and Management, 60 (1993) 59-76

59

Elsevier Science Publishers B.V., Amsterdam

Impact of Australian tree species selection research in China: an economic perspective Daniel W. McKenney*'a, Jeff S. Davis b, John W. Turnbull b, Suzette D. Seaflec aForestry Canada- Ontario Region, P.O. Box 490, Sault Ste Marie, Ont., P6A 4J2, Canada bAustralian Centre for International Agricultural Research, G.P.O. Box 1571, Canberra, A. C. T. 2601, Australia CDivision of Forestry, Commonwealth Scientific and Industrial Research Organisation, P.O. Box 4008, Queen Victoria Terrace, Canberra, A.C.T. 2600, Australia (Accepted 1 March 1993)

Abstract

Given increasingly limited research budgets, there is a growing need for forestry research to be more systematically evaluated. Such evaluations can often provide insights for setting research priorities and guiding the allocation of research resources. The Australian Centre for International Agricultural Research (ACIAR), through collaborative projects with the Commonwealth Scientific and Industrial Research Organisation, Australia (CSIRO) and the Chinese Academy of Forestry (CAF), has been involved in tree species selection trials in southern China since 1984. In particular, the trials have examined the potential of fast-growing species of Eucalyptus, Acacia and Casuarina. The Chinese have been planting Australian tree species since 1890, but there has been little progress in determining which species and provenances would be best for the local climate and soils. This paper presents an assessment of the likely economic impact of these trials. Owing to the long term nature of forestry, the analysis primarily has an ex ante perspective. That is, while the trials have been underway for a number of years, large-scale production plantations of the newly selected species are only just now being planted. Most of the wood from these plantings will not be harvested for another 7-15 years. Sensitivity analysis on both the cost and benefits of the research is required to gauge the impact of different assumptions on the overall benefits. In this analysis, sensitivity analysis suggests internal rates of return of 27-45%. Base-case benefit estimates suggest economic gains to China of a net present value of $A72 million in 1986, the commencement of the project, and an internal rate of return of about 34%, indicating the research is an attractive economic investment.

Introduction This paper describes the projected economic impact of a collaborative research project in China supported by the Australian Centre for International Agricultural Research (ACIAR). The project essentially deals with the selection of fast-growing species of Eucalyptus, Acacia and Casuarina for southern China. Owing to the long-term nature of forestry, many of the social gains from this research have not yet been realised even though the project has been *Corresponding author.

© 1993 Elsevier Science Publishers B.V. All rights reserved 0378-1127/93/$06.00

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underway for several years. This analysis therefore has both an ex post and an ex ante perspective. The approach illustrates certain generic concepts that need to be considered in economic evaluations of this type. There have been relatively few empirical analyses of the economic returns to research in forestry (e.g. Fox, 1986; Jakes and Risbrudt, 1988; Huang and Teeter, 1990; Hyde et al. 1992; McKenney et al., 1992 ). Many of the analytical advances have occurred in the context of evaluating agricultural research (see Norton and Davis, 1981 for a review). The aim of this paper is to provide an empirical example of forestry research evaluation in a developing country context and highlight some relevant methodology. The second section provides some background on forestry in China and the research projects under consideration. The third section describes the economic evaluation framework and the results of the analyses. The final section presents some conclusions.

Background China's forest area covers 124 million hectares, about 13% of the land area (Dong, 1991 ). More than half of the 100 X 106 cubic metres of wood harvested annually comes from southern provinces, mainly from trees planted by collectives and individuals (Bennett, 1988 ). There is an immense domestic demand for fuelwood, poles and sawn timber and a government policy to increase the amount of wood used for paper pulp. Plantations of high yielding eucalypts and acacias are expected to make an important contribution to wood production in southern China, where the climate is conducive to high growth rates. Similarly, casuarinas have an important role to play in coastal shelterbelts. Eucalypts were introduced into southern China in about 1890. These and subsequent introductions came from unselected and often incorrectly named trees growing as exotics in a variety of countries. Eucalypts were originally planted as ornamentals and roadside shade. It was not until the 1950s that extensive areas of eucalypts were established. Much of the wood harvested from these plantations has been used for mining timber (Turnbull, 1981 ). Eucalypt plantations now cover an estimated area of 600 000 ha (principally in Guangdong, Guangxi, Hainan Island, Yunnan and Fujian provinces). A further one billion trees planted around fields, homes and villages, and along roads, railways and watercourses provide a significant timber resource, especially in Sichuan and Yunnan provinces (Wang, 1991 ). Because of the current timber supply deficit, the availability of unproductive land, and an aim to have a eucalypt resource of sufficient size to support a pulp and paper industry, the goal of the Chinese Ministry of Forestry is to rapidly increase the area of eucalypts. It has been forecast that the total area of eucalypt plantations in China will reach 1.3X 10 6 ha by the year 2000

D. W. McKenney et al. / Forest Ecology and Management 60 (1993) 59- 76

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(Wang, 1991 ). When the rapid expansion of the eucalypt area began, the trees were raised from local seed sown in primitive nurseries and planted on infertile sites without fertilizer. As a result only robust species survived. The present large areas of Eucalyptus exserta and Eucalyptus citriodora are the product of this selection process. They tolerate infertile soils, but have low yields and have wood with relatively poor pulping properties. The average yield of plantation-grown eucalypts in China is only 5-8 m 3 ha-1 year-1 (Liu, 1988 ). Casuarinas have been grown in China for more than 80 years, but it was not until the 1950s that large plantation areas were established in southern coastal areas. These plantings were established originally to stabilise coastal sand dunes and protect adjacent farmland. The shelterbelts extend along the coast from Hainan Island to Zhejiang, a distance of about 4000 km, and cover several hundred thousand hectares. They have become an important source of fuelwood and poles (Turnbull, 1983; Zhong, 1990a; Cao and Xu, 1990). The major species planted is Casuarina equisetifolia, but there are significant areas of Casuarina cunninghamiana and Casuarina glauca. The source of the original seed of these species is unknown. In southern China a native acacia, Acacia confusa, has been widely used in plantings around houses and along roads, railways and waterways. It is relatively slow growing and has a crooked stem so that its principal use is for fuelwood and shelter. An exotic acacia, Acacia auriculiformis, proved to be faster growing than A. confusa, but with similar poor stem form. This species has been used extensively in Guangdong Province. It will grow on very infertile sites and provides shade and shelter and a variety of wood products. As with the eucalypt and casuarinas the source of the original seed introduction is unknown. An Australian forestry mission to China in 1980 recommended testing new introductions of species and provenances of eucalypts, acacias and casuarinas to increase plantation productivity (Carter et al., 1981 ). Subsequently a project in Guangxi Zhuang Autonomous Region demonstrated that substantial increases in yield could be obtained through the introduction of new species and provenances of eucalypts and pines and strategic applications of fertilizer (Cameron et al., 1988; McGuire et al., 1988). A complementary project to test a wider range of Australian tree species and provenances over more diverse environmental conditions in other provinces where major tree planting activities were planned was supported by ACIAR. It was implemented in 1985 by the Chinese Academy of Forestry's research institutes in Guangzhou and Beijing, and the CSIRO Division of Forestry, Canberra.

ACIAR collaborative project The first phase of the project commenced in 1985 with the primary objective of identifying Australian eucalypts, acacias and casuarinas which would

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be more productive than those currently planted in China. The project involved introducing from Australia and elsewhere a wide range of species and provenances of known origin. During the first 3 years 19 field trials were established. These were located in Yunnan Province in the cool subtropical, high altitude plateau areas of southwestern China: in warm subtropical Fujian Province: and tropical Guangdong and Hainan Island provinces. These are areas targeted for eucalypt plantation development. The trials were designed to test the adaptability of the new introductions. Survival and health were assessed and growth measured. Seedlots from previous introductions were included in the trial as controls for comparative purposes. Statistical considerations suggested a relatively small plot size be used, usually between nine and 25 trees, which limited the amount of growth data that could be obtained, but maximised the number of seedlots that could be screened. More detailed information on the trials used for estimating the impact of this project are given by Yang et al. ( 1989 ), Zhou and Bai (1989), Wang et al. ( 1989 ), Wang (1990) and Zhong ( 1990b ). Growth measurements indicate that some of the new introductions are growing very much faster than the controls. On tropical Hainan Island, E. urophylla produced more than twice the wood volume of the local E. citriodora, and A. aulacocarpa, A. crassicarpa and a new introduction ofA. auriculiformis also yield about twice the wood volume of the local A. auriculiformis. In subtropical Fujian, E. urophylla and E. grandis had produced about three times the wood volume of local E. citriodora after 5 years. In the highlands of Yunnan Province the growth differential between the new and locally grown material was less. New provenances of E. globulus did not grow faster than the local source although there is potential for them to be of higher quality through improved stem form. However, E. nitens is growing significantly faster than the more frost sensitive E. globulus. The data for casuarinas are based on 5-year-old trees on Hainan Island. At this stage, Casuarinajunghuhniana, an Indonesian species, is growing considerably faster ( 132% ) than the local Casuarina equisetifolia. New provenances of C. equisetifolia from Australia have not grown faster than the local provenance. The C. junghuhniana used in this trial was from a plantation in Tanzania as seed from the natural forests in Indonesia was not available. It should therefore be regarded as a random sample of C. junghuhniana rather than a selection from the likely best provenances available, as was the case in the trials of the acacias and eucalypts. While the experimental data suggest very substantial increases in wood production are possible from introduced species, it must be emphasised that some caution is necessary as a result of the small plot size. There is a potential for the volume estimates in small plots to be inflated owing to edge-effects. Nevertheless, the results to date, ranging from 30 to 60% of rotation age, do provide an indication of the potential of the new species. They also serve as

D. 14( McKenney et al. / Forest Ecology and Management 60 (! 993) 59- 76

63

source data for a generic approach to evaluate the potential economic gains from this type of forestry research. It is unlikely that any new species can be fully utilised until reliable sources of seed are available within China. Action has already been taken to establish seed orchards and to prepare breeding programs for further improvement of the most promising species. For example, seed orchards of acacia established in 1988 in Hainan Island and Zhejiang provinces are starting to produce seed. Breeding plans have been developed for E. globulus, E. grandis and E. urophylla and seed production areas have been established. China's tree improvement strategy is to develop seed orchards of superior genotypes and to use vegetative propagation to mass produce superior clones where feasible (Hong, 1992). Present indications are that the extensive plantations of E. exserta and E. citriodora will be replaced by E. urophylla in tropical areas with low typhoon risk, E. tereticornis or E. camaldulensis in tropical areas with higher typhoon risk and E. grandis or E. urophylla in subtropical areas. It is also likely that new provenances ofA. auriculiformis will be used extensively in the tropical lowlands, especially for boundary plantings, and that the fast growing A. crassicarpa and A. mangium will be planted on the slopes of the hilly land in tropical areas. In the cooler highlands of Yunnan, Sichuan and Guizhou provinces and in the coastal Zhejiang province there is likely to be an increased role for E. nitens (Wang et al., 1993 ). Seed from Australia is in short supply and may inhibit the adoption of E. nitens. Local seed orchards will likely take more than 10 years after establishment to come into production. For this study it has therefore been assumed that the cool sub-tropical highland component of the research will result in relatively low benefits and so E. nitens and E. globulus have been excluded from the economic assessment. The use of C. junghuhniana for extensive plantations is less likely until it is tested more thoroughly in coastal areas and its resistance to the bacterial wilt disease (Pseudomonas sp. ) evaluated. This species is readily propagated by vegetative means in India and Thailand and this method may be used to establish plantations, at least until seed is available in sufficient quantities.

Impact assessment A range of research evaluation frameworks has been employed in past assessments of the impact of research. Some have used very simple models which estimate the value to society of the research as the expected increase in product output valued at the current or expected price. Others have used economic welfare-theory based measures of the impact of technology with multistage, multi-regional traded good models incorporating research spillovers between regions to estimate the potential value to society of the research.

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Whether a simple or more complex evaluation framework is chosen depends largely upon the use to be made of the information generated. For some decision making situations the information generated by a simple framework will be all that is required while for others more complex inter-regional interactions will be important. Even if a simple framework is considered appropriate, care is required in the choice of the framework and especially the estimation procedures adopted. In particular, the estimated value of the expected increase in output should be used with care. Figure 1 illustrates two possible options for a simple measure of the gains from research. A single-region, non-traded, single good model is represented. The demand for the product is represented by D. Before research the product supply is So. After research the cost of producing the product is reduced, shifting the supply to St. The economic welfare-theory based measures of the gains from research suggest that the area abde is a close approximation of society's gains. For a given cost reduction owing to research, in this case bf, the area, abfe, will remain the same regardless of the supply and demand characteristics of the product involved. The rest of the welfare gains, here bdf, will change depending upon the supply and demand characteristics. In the extreme, this area can be as large as bcf. In most cases this variable area is a relatively small share of the total welfare gain estimate. The second measure illustrated is the value of the change in output. In most studies which use this measure it is rare to find clear specification of the assumptions regarding the supply and demand conditions. Figure l can be used to illustrate the differences which can occur if different implicit assumptions are made. If it is assumed that the demand is perfectly elastic and the current price is used to value the increase in output, the area bcQ2Qo will be estimated.

~

Price

P 1

a

°$1

D

Q

Q 0

Q 1

Quantity 2

Fig. 1. An illustrationof a simpleframeworkfor assessingthe gainsfrom research.

D. I4/. McKenney et al. / Forest Ecology and Management 60 (1993) 59- 76

65

On the other hand, if the demand conditions are as represented in Fig. 1 the change in equilibrium output is likely to be significantly less. If the current price is used to value the increase in output the gains from research are bgQ~Qo. Alternatively, if the after research expected price is used the gains are hdQiQo. Clearly the estimate of the gains can be very sensitive to the assumptions regarding the supply and demand conditions. Many studies using the value of output-change measure also estimate the change in output from the research results or researcher controlled (farm) trials. As has been discussed by Davis and Bantilan (1991) additional estimation errors can arise as the relationship between this type of information and the aggregate supply and demand conditions is often complex and not incorporated in the estimates. In this study the simple welfare theory based measure is adopted to estimate the expected gains from research. There is a clearer welfare theory basis for this measure as opposed to the 'value of the change in output', and in addition, it is in general likely to be less sensitive to the often uncertain underlying supply and demand conditions. For reasons highlighted in Davis and Bantilan ( 1991 ) the cost reduction, that is bf, will be used to estimate the research gains not the output increase (bc or bg). This assessment uses only wood values to estimate benefits. Any important non-wood value benefits are ignored. Hartman ( 1976 ) provides the first formal analytical approach to the economics of forestry when non-wood values enter the decision calculus (see also Bowes and Krutilla, 1989). Depending on which non-wood values are important over- or under-estimates of the research gains may result. Clearly for many of the forestry related problems in China, the planting of any suitable tree species would help, hence it would be J Choose appropriate ] evaluation framework

Ees~l atcehCoUlrrgyt preoC!unc°tli°gnY caonsds

1 Sensitivity analysis for important J parameter values

[

reduction in the unit I D cost of production using the new J technOl°gy J I Estimate the

i__n,i .... ....pusJ welfare gains from the use of the new technology, inclusive of research costs

Fig. 2, Steps in evaluating the impact of research.

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inappropriate to attribute all non-wood benefits to the trials being analyzed here. The next section outlines the cost analysis which has been developed to assess the impact of the research. The cost per cubic meter (i.e. unit cost) of providing wood from plantations is calculated via compounding all establishment and maintenance costs. This approach is used to provide an estimate of the unit cost reduction due to the research productivity (volume) gains. Project research costs are then summarised and the total value of the unit cost reductions are used to estimate the net gains expected to stem from the project through time. As most of the gains are still to be realised, sensitivity analysis is used to indicate whether the estimates are robust. The general steps in the analysis are summarised in Fig. 2. Current and new species wood production costs

The economic assessment of gains to wood production from research requires identification of the relevant costs for different silvicultural regimes. As costs and outputs occur through time, a dynamic dimension needs to be included in the analysis. In forestry such costs may include: site preparation, planting, fertilizer, survival assessments, pruning, thinning, harvest activity and an opportunity cost for land. Often land costs are ignored (Samuelson, 1976). The following two sub-sections describe the costs of growing both currently used and newly introduced species of eucalypts, acacias and casuarinas in southern China. This cost analysis is separated into the costs of production of the new seedlings, and plantation costs through to final wood production. Seed orchard costs in China

For the Chinese to realise the benefits of increased wood production owing to the ACIAR species selection trials some additional costs will be incurred. These include the costs of obtaining seed for adopting the new species. If available, the seed could be purchased. However, the Chinese have generally chosen to develop seed orchards for the major species groups in the project. For an economic analysis this cost should be applied to each plantation that utilises the new species. However, note that the cost of doing the research that identifies the better species should be applied to all plantations that can utilise the improved technology, now and into the future. This approach recognises the permanent nature of the technological improvement and is similar to the approach used by McKenney et al. ( 1992 ) for evaluating the potential economic benefits of tree breeding. Table 1 provides a summary of the estimated costs of the relevant seed orchard programs in China. The costs are given in annual terms and as a cost per hectare of plantation. The method of calculating seed orchard costs per

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Table 1 Average seed orchard costs in China Species

Annual cost over productive life of orchard (Yuan ha-~ )1

Average annual seed production ('000 seeds per ha of orchard)

Potential plantation area (hectares per hectare of seed orchard) 2

Seed orchard cost per ha of plantation (Yuan ha-~ )

Tropical Casuarina Tropical Acacia Tropical Eucalypt Warmsub-tropicalEucalypt

959 1827 1084 1098

10832 498 4559 4506

677 28 342 338

1.42 65.90 3.17 3.25

~Annual costs estimated using costs compounded at 5% real interest rate. 2Based on 4:1 seed to seedling ratio and initial plantation stocking rates of: 3333 seedlings per hectare for Eucalyptus, 4444 seedling per hectare for Acacia and, 4000 seedlings per hectare for Casuarina; proposed (by the Chinese) seed orchard sizes are: 30 ha for sub-tropical Eucalyptus, 50 ha for tropical Eucalyptus, 10 ha for Acacia and 100 ha for Casuarina. Source: Information provided by scientists in Chinese Academy of Forestry.

hectare of plantation can be summarised as follows. All the orchard establishment and management costs (e.g. land costs, site preparation, fertilizer, animal control) over time are converted to an annual cost over the productive life of the orchard. This annual cost is converted to an average cost per hectare of plantation by dividing by the average annual potential planting area the orchard can support. The potential planting program is contingent on the fecundity of the orchard (i.e. how much viable seed it produces), the efficiency of nursery practices (i.e. the n u m b e r of seeds required to produce a seedling) and the stocking rate of plantations (i.e. the number of seedlings planted per hectare of plantation). Unless nursery practices are very inefficient or the species is a poor seed producer, the seed orchard costs comprise only a small proportion of the plantation establishment costs. These orchard costs range from 1.4 to 65.9 Yuan h a - ~ (Table 1 ). As these costs are so small, they have a relatively minor impact on the overall cost of wood production. For the species examined here, variations on the initial assumptions of orchard costs and orchard seed yields had little effect on the seed orchard costs per hectare of plantation and hence the overall net benefit estimates. Plantation costs with current a n d new technology

The unit cost of producing wood is calculated by compounding all plantation establishment and management costs forward to the end of the plantation's life and dividing by harvest yield. The costs are then expressed per unit of production (e.g. Yuan m - 3 ) . When multiple products are realised from

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plantations the issue of cost allocation arises. Here the unit cost of production has been calculated based on total wood yield through time since the allocation of costs among joint products is generally arbitrary and can lead to biased cost estimates for each product (Hof et al., 1985; Bowes and Krutilla, 1989). Given that some products are produced before the rotation age, this approach can provide an overestimate of the unit cost. Hence the resultant benefit estimates could be construed as conservative. Table 2 includes the estimates of wood production from existing species plantations which are used as the basis for the cost analysis. Many wood products can potentially be obtained from plantations depending on how they are managed through time (e.g. fuelwood, pulpwood, sawlogs). No attempt has been made to determine whether the research will result in a change to the optimum economic rotation length or management regime. The analysis is based on current practices in China. Different flows of products are generated by different species through time. Some species provide early output and each has its own rotation length. Table 3 summarises the plantation information used in the cost analysis. In some cases yield estimates have been calculated from trial measurements over several years. Columns 1 and 2 have been taken directly from Table 2. As Table 2 Existing plantation production estimates over time ( m 3 ha- 1 ) Species category and wood product

Casuarina equisetifolia

Total Production level each year production I 2 3 4 5 6 7 8 9

10

11 12 13 14 15

142

(total)

Fuelwood Other industrial roundwood Sawlogs for sawn timber Acacia auriculiformis

(total) Fuelwood Pulpwood Eucalyptus citriodora

tropical (total) Fuelwood Pulpwood

52 50

4

10

8

30 50 40

40 200 50 150 175 50 125

Eucalyptus citriodora

56

sub-tropical (total) Fuelwood Pulpwood

26 30

50 150

45

5 25

8

100

8 4 4

2 30

Source: Estimates by project scientists based on plantation production patterns for existing (control) species.

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Table 3 Summary of estimates for plantations used in cost analysis Species

Average rotation

Wood yields

Area of Potential plantation area seed orchard from orchard (ha) (ha year-1 ) (7)' (6)

(1)

Current (m 3) (2)

Gain (%) (3)

Expected (m 3) (4)

Estimates of expected plantings (hayear - l ) (5)

15 15 15 15

142 142 142 142

39 65 98 132

197 234 281 329

10000 10000 10000 10000

1O0 100 100 1O0

67692 67692 67692 67692

10

200

144

488

1200

10

277

10 10 10

175 175 175

135 114 107

411 375 362

33000 33000 33000

50 50 50

17102 17102 17102

56 56

217 186

178 160

10000 10000

30 30

10126 10126

Tropical casuarina

1989 trial 1990 trial 1991 trial 1992 trial

results results results results

Tropical acacia

1989 trial results Tropical eucalypt

1989 trial results 1990 trial results 1991 trial results

Warm sub-tropical eucalypt

1990 trial results 1991 trial results

7 7

1The wide variation in potential plantation area results from the fecundity of the species and the proposed size of the seed orchards. In some cases more seed will be produced than apparently necessary.

already indicated the trial results do not include a completed full plantation rotation. In Table 3 Columns 2 and 3 are used to estimate the expected total wood production in Column 4. The projected rotation ages for the different species have been set at 7 years (tropical eucalypt), l0 years (sub-tropical eucalypts and tropical acacia) and 15 years (casuarina). Clearly the rotation age depends on the product being produced. These ages are based on current practices in China. In Brazil, eucalypt pulpwood is generally harvested on a 7-10 year rotation. The same rotation age is applicable to fast-grown acacias for pulpwood, but if these species are grown for higher value timber, as is the case in Malaysia, the rotation age may be a minimum of 20 years. Casuarinas are generally slower growing. A rotation of 15 years for trees harvested for poles and fuelwood is appropriate based on existing experience in China. Chinese forestry researchers have provided estimates of the expected level of annual plantings of each species. This information is summarised in Column 5 of Table 3. Column 6 of Table 3 indicates the estimated levels of seed orchard establishment and Column 7 provides estimates of the plantation area which could be potentially supported by these seed orchards. These plantation area estimates are based on the information provided in Table 1.

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Data on establishment and annual maintenance cost estimates were developed for plantations of each species by Australian and Chinese project scientists based on existing plantation information. This information was adjusted to account for changed costs resulting from the new introductions. Examples of the latter include increased seed costs (see Table 1 ) and increased fertilizer use to ensure output increases are sustained. Table 4 provides a summary of this cost analysis for each species. The old technology and new technology unit cost of wood production are given in the first two columns. These wood production costs range from 19 Yuan m -3 to 83 Yuan m -3 for the old technology, falling to between 9 and 48 Yuan per m - 3 respectively with the yield increases expected from the new technologies. The unit cost reductions owing to research range from 8 Yuan m -3 for tropical casuarina to 37 Yuan m - 3 for warm sub-tropical eucalypts. In percentage terms these represent production cost reductions ranging from 16 to 50%, but correspond to 39 and 217% volume production increases. This result illustrates the need for caution in assuming a one to one correspondence between volume increases and cost reductions. The cost estimates in Table 4 have been calculated by compounding all costs to the end of the rotation and dividing by total wood production. The compound rate used was 5%. Eight percent Table 4 Estimates of unit cost reductions for forestry research in China Species

Unit cost of production

Unit cost reduction

Old species (Yuan m -3 )

Introductions (Yuan m - 3 )

(Yuan m -3 )

(%)

51 51 51 51

42 39 36 33

9 12 15 18

18 24 29 35

19

9

10

53

38 38

22 24

16 14

42 37

83 83

47 48

36 35

43 42

Tropical casuarina 1989 1990 1991 1992

trial trial trial trial

results results results results

Tropical acacia 1989 trial results

Tropical eucalypt 1989 trial results 1990 trial results

Warm sub-tropical eucalypt 1990 trial results 1991 trial results

Unit costs estimated using all plantation costs compounded at a real interst rate of 5o~/odivided by total wood yield.

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Table 5 Project costs Year

ACIAR $A

CSIRO and CAF ~

Total costs nominal $A

Total costs in constant 1990 $A

1985/1986 1986/1987 1987/1988 1988/1989 1989/1990 1990/1991 Total

111400 63500 73400 183554 178696 156326 766879

101500 85000 84000 254000 250000 250000 1024500

212900 148500 157400 437544 428696 406326 1791366

268781 176866 176855 463797 428696 383326 1898321

~China Academy of Forestry. Source: Project documents. Nominal research costs are converted to 1990 dollars assuming an inflation rate of 6% per year. To avoid confusion, the 10% discount rate for estimating net present values of the research is net of inflation.

was also used to illustrate the sensitivity of the research returns to various assumptions. In general, as would be expected, the higher the compound rate the higher the unit cost both with and without the new technology. The unit cost reduction is therefore larger in absolute terms. Project research costs

Table 5 summarises the costs of the project from 1985/1986 to 1990/1991. The costs include those incurred by ACIAR, CSIRO and the Chinese Academy of Forestry (CAF). The research costs for CAF and especially CSIRO are both direct and indirect ( e.g. the use of existing buildings and equipment ) costs.

Anticipated project net benefits The present value of net benefits are calculated by subtracting the present value of the research costs from the gross benefits. The gross benefits are estimated using the unit cost reductions and the framework discussed earlier (Fig. 2 ). As the plantations have yet to reach the harvesting stage, these benefits are as yet only anticipated. In light of this, several alternative estimates are presented allowing for different possible circumstances. Base case

The base case project net benefits have been calculated from 1989 to 1992 using the information in Tables 1 to 4. In years where trial growth measurements were not available previous year's data were used (see Table 3). In

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addition the following assumptions were adopted: ( 1 ) a substantial lag between the start of the research project in 1985/1986, and the harvesting of plantations of the new species. This lag was assumed to be 17-24 years depending on the species. Important components were: completion of the species selection trials; establishment of seed orchards and production of seeds (in this case the trials and orchard establishment overlapped ); and establishment of improved plantations which take between 7 and 15 years before harvesting. (2) Adoption of the new introductions was assumed to be at the levels of current plantings of the old species or the area for which seed is available from the seed orchards being established, whichever was lowest. ( 3 ) The demand for the final wood products was assumed to be perfectly elastic (i.e. a horizontal demand curve in Fig. 1 ). This implies that price would be unaffected by the increased output as a result of the research. This would appear to be a reasonable assumption owing to the fact that in China, prices are generally administered and the areas concerned produce a relatively small share of total wood output. (4) The interest rate for compounding costs was assumed to be 5%; this being the real rate (net of inflation ) for plantation-forest types of investments (e.g. see Row et al., 1981 ). The discount rate for the research investment to estimate net present values was a real rate of 10%. The basis for the different rates is that plantation activities are commercial types of investments and therefore warrant a 'private' rate of interest. On the other hand, public sector research investments can be considered more risky than commercial investments and hence warrant a higher rate. Internal rates of return are also used for the research assessment analysis. Another justification for the higher discount rate is that agricultural research projects generally show high rates of return, hence the rate may be viewed as an appropriate opportunity cost of public research funds. The annual research gross benefits were estimated in two parts; first, the area abfe in Fig. 1 using the pre-research output and the unit cost reductions, and second, the area bcf, using the with-new technology output and unit cost reductions. As indicated in the earlier discussion, care is required in using the second area, bcf, but in this case it did not represent a major share of the benefits. Table 6 provides the base case research benefits estimates. The net present value (NPV) of anticipated benefits using the 1989 trial results is estimated as $A7 1.6 million with an internal rate of return (IRR) of 33.8%. The NPV is expressed in constant 1990 Australian dollar terms, but discounted to the commencement of the project (1985/1986). The equivalent value if compounded to 1990 is $A1 15.4 million. By most standards these returns are high, especially given the substantial lags before benefits begin to flow. Using the trial results from 1990, 1991 and 1992 had little effect on the net benefit estimates.

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D. W. McKenney et al. / Forest Ecology and Management 60 (1993) 59- 76 Table 6 Summary of research benefits analysis Costs in cost analysis compounded at 5%

Case

Net present value (SAm)

Internal rate Net present value of return (SAm)

(%)

1985/1986 1989/1990 Base case 1989 trial 1990 trial 1991 trial 1992 trial

results results results results

71.6 67.3 65.3 67.6

Costs in cost analysis compounded at 8% Internal rate of return

(%) 1985/1986 1989/1990

115.4 108.4 105.1 108.9

33.8 33.1 32.7 32.8

88.3 83.3 81.3 84.7

142.1 134.2 131.0 136.3

35.3 34.6 34.2 34.3

187.8 56.4

38.0 28.9

143.6 43.3

231.2 69.7

39.6 30.3

92.8

32.8

71.1

114.5

34.4

Base case lag shortened: 2 years 87.8 4 years 107.5

141.3 173.1

38.6 45.2

104.3 124.0

167.9 199.8

39.6 45.7

Base case lag lengthened: 2 years 57.9 4 years 46.7

93.2 75.2

30.1 27.1

71.3 57.6

114.9 92.8

31.3 28.2

Sensitivity analysis (1989 base) Extra seed purchase 116.6 Base case half unit 35.0 cost reduction Base case half unit 57.6 cost reduction extra seed purchase

Notes: Net present value calculated using a 10% discount rate. All monetary information is reported in 1990 constant dollars.

Sensitivity analysis Table 6 also includes estimates of research benefits for a range of alternative assumptions for several key parameters (i.e. costs, lag periods and adoption rates). The last three columns present estimates using a compounding rate of 8% for the plantations and seed production costs. The results of this component of the sensitivity analysis are perhaps contrary to those expected by some. They are due to the fact that the higher compounding rate in general results in higher unit costs for the plantations. This therefore translates into higher unit cost reductions and hence a higher return owing to research. In the base-case, the NPV in 1985/1986 is increased by approximately $A 17 million, while the IRR increases from 33.8 to 35.3%. Other situations include: increased plantings where seed shortfalls exist by purchasing additional seed; alternative lag structures regarding the time from

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the commencement of the research to its impact on wood production. This lag varied from 4 years less to 4 years longer than the base case. Table 6 indicates that NPVs (in 1985/1986 $A) range from $A35.0 million to $A143.6 million and IRRs from 27.1 to 45.7%.

Concluding remarks An economic evaluation of the impact of the results of species selection trials has indicated that substantial economic gains to China can be expected to flow from this research by the turn of the century. Valued at the commencement of the project (1985/1986) the net present value of the research is of the order of $A72 million. This represents an internal rate of return of almost 34% which, given the long lags assumed in the analysis, is a very attractive public return to the research investment. Given the inherent uncertainties in long-term research projects, economic analysis of impacts should consider the sensitivity of the results to changes in input values (e.g. costs, lag periods, adoption rates ). In this case sensitivity analysis still suggested the project was worthwhile. The assessment has considered only gains which are likely to be achieved in the provinces of southern China. It is expected that there will be spillover gains to other countries from this research which would increase the economic value of the project.

Acknowledgements The authors gratefully acknowledge the cooperation of the many Chinese scientists who provided information. In particular we appreciate the contributions of Bai Jaiyu and his staff at the Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou and Wang Houran and his colleagues at the Research Institute of Forestry, Chinese Academy of Forestry, Beijing. We also thank Bill Hyde, Ken Menz and the journal referees for helpful comments on an earlier draft. Any errors are the responsibility of the authors.

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