ILRI SLU
 
 
 
Sunday, 19 Nov 2017
 
 
How to value AnGR? | Print |

Adam G. Drucker (2002)

International Livestock Research Institute, P.O. Box 5689, Addis Ababa, Ethiopia

1 This work is based on the studies of Anderson et al. (1999) and Drucker et al. (2001)


Introduction

Having examined the conceptual economic background and the policy issues that we aim to resolve through animal genetic resources (AnGR) valuation in this second case study on the same subject, it is now necessary to consider the tools with which such valuation can be realised. This case study examines a variety of potentially applicable valuation methodologies, some of which have been developed for assessing the value of crop genetic resources.

However, as will be seen below, the field of economic valuation of AnGR per se requires substantial development and, hence, examples of valuation studies that have actually been carried out are extremely limited.

Animal genetic resource valuation

Contrasting animal and plant genetic resource valuation

Animal genetic diversity, in general, and valuation in particular, has not received the same amount of attention as plant/crop genetic resources (PGR). As a result, the development of methodologies for AnGR must draw heavily on the literature available on PGR valuation. Given that the underlying principles of genetics and gene action are similar for plants and animals, it is worth asking what can be learnt from PGR valuation methodologies that would be of benefit to AnGR valuation?

There are indeed a number of methodological difficulties that have arisen in valuing PGR that are also likely to affect AnGR. For example, Evenson (1991) has shown that the measurement of the benefits of germplasm diversity to crop development is extremely difficult. The genetic resources are seldom traded in markets and are often the product of generations of informal innovations. Thus, identifying the contribution of a particular local breed to the success of an improved breed would be complicated. Furthermore, the base materials used for breeding are themselves the result of a production function and identifying the returns to respective factors (e.g. labour, on-farm technology, intellectual inputs, etc.) is likely to be possible only in the most general terms (Evenson 1991; Pearce and Moran 1994).

However, in addition to confronting similar challenges, there are several differentiating characteristics between AnGR and PGR that may have an influence on valuation. According to Hammond (1996) of the FAO (Food and Agriculture Organisation of the United Nations) Animal Genetics Resources Group, animal resources resources tend to be:

 

  • more mobile.
  • comparatively high cost per unit.

    very low fecundity, with ‘seed’ needing to be deep frozen to survive.

  • seriously affected by many rapidly spreading animal diseases both within and across animal species, including Homo sapiens.

    These primary differences lead to a suite of related considerations, which will impact on valuation methodologies (as we shall see below) as well as resource management strategies. These differences include:

  • the relatively small total number of animal genetic resources and extremely small number of these which have been exposed to date to modern development technology
  • the high impact of some biotechnologies on the dispersal ability of animal resources
  • the few remaining wild relatives of domestic animal species
  • the low level of knowledge of animal biology compared with the wide range of environments over which sustainable production is being sought
  • the high impact of animal disease protocols on international transport and access; and
  • the low level of gene-banking of animal resources at risk..

    These substantial differences convey policy, legal and technical uniqueness, which must be addressed to achieve effective management of AnGR. They are also likely to have implications for valuation.

Ø From your own experience of AnGR in your community, consider how relevant each of the above factors has been in determining the degree of genetic erosion. What implications does this have for AnGR conservation in your community and what factors might you take into account in an appropriate valuation model?

Valuation methodologies

How can we measure these values and which valuation methodologies are the most appropriate? A range of potential valuation methodologies exists. These are presented in Table 1 and can be categorised broadly into 3 groups on the basis of the practical purpose for which they may be conducted (Drucker et al. 2001). Following the identification of a given breed being at risk, these methodologies can be applied in order to justify conservation costs by: (i) determining the appropriateness of AnGR conservation programme costs (i.e. consider environmental values); (ii) determining the actual economic importance of the breed at risk (i.e. considering breed values); and/or (iii) priority setting in AnGR breeding programmes (i.e. consider trait values). Each of these categories is discussed below and a summary is presented in Table 1.

Table 1. Animal genetic resources (AnGR) valuation methodology evaluation.

Valuation methodology
Purpose, objective or strength
Actor(s) for whom valuation method is most relevant
Role in conservation
Type of data Required
Data availability
Conceptual weakness or difficulties
(a) Methodologies for determining the appropriateness of AnGR conservation programme costs
Contingent Valuation Method (CVM)
 
 
 
 
 
 
Production Loss Averted
Indicate magnitude of potential production losses in the absence of AnGR conservation
Farmers and policy-makers in charge of conservation
Justify conservation programme costs of at least this magnitude
Estimate of potential production losses (e.g. percentage of herd and market value of animals)
Animal market values available for commercial breeds. Potential herd loss must be estimated
Not a consumer/
producer surplus measure of value. Ignores substitution effects
Opportunity Cost
Identify cost of maintaining AnGR diversity
Farmers and policy-makers in charge of conservation
Define opportunity cost of AnGR conservation programme
Household costs of production
and net income
Not normally available. Requires survey
 
Least Cost
Identify cost-efficient programme for the conservation of AnGR
Policy-makers in charge of conservation; farmers and breeders to some extent
Define minimum cost of conservation programme
Household costs of production
and profitability
Not normally available. Requires survey
 
 
(b) Methodologies for determining the actual economic importance of the breed
Aggregate Demand & Supply
Identify value of breed to society
Policy-makers in charge of conservation and livestock policy, as well as breeders
Value potential losses associated with AnGR loss.
Intertemporal or farm-level data
Available for commercial breeds. Not normally available for others – requires survey
Requires shadow pricing of home labour and forage
Cross-
sectional
Farm and Household
Identify value of breed to society
Policy-makers in charge of conservation and livestock policy; as well as breeders and farmers
Value of potential losses associated with AnGR loss
Consumer and producer price differences by location
Not normally available. Requires survey
Requires shadow pricing of home labour and forage
Market Share
Indication of current market value of a given breed
Policy-makers in charge of conservation and livestock policy; as well as breeders and farmers
Justify economic importance
of given breed
Market value of animal products by breed
Generally available but not always by breed
Not a consumer/
producer surplus measure of value. Ignores substitution effects
Intellectual Property Rights (IPRs) & Contracts
Market creation and support for ‘fair and equitable’ sharing of AnGR benefits
Policy-makers in charge of conservation; as well as breeders and farmers
Generate funds and incentives
for AnGR conservation
Royalty payments or terms of contract
Usually available when such arrangements exist although can be commercial secret
Limited duration
of contracts
 
(c) Methodologies for priority setting in AnGR breeding programmes
Evaluation of Breeding Programme
Identify net economic benefits of stock improvements
Farmers and breeders
Maximise economic benefits of conserved AnGR
Yield effects and input costs
Available for commercial breeds. Not normally available for others – requires survey/research
Difficulty in separating the contribution of genetic resources from other costs of programme
Genetic Production Function
Identify net economic benefits of stock improvements
Farmers and breeders
Maximise expected economic benefits of conserved AnGR
Yield effects and input costs
Available for commercial breeds. Not normally available for others – requires survey/research
 
Hedonic
Identify trait values
Farmers and breeders, as well as policy-makers in charge of conservation
Value potential losses associated with AnGR loss. Understand breed preferences.
Characteristics of animals and market prices
Available for commercial breeds. Not normally available for others – requires survey/research
Not a
consumer/
producer
surplus
measure of value. Ignores substitution effects
Farm Simulation Model
Model improved animal characteristics on-farm economics
Farmers and breeders
Maximise economic benefits of conserved AnGR
Inputs and outputs. Technical coefficients of all major activities
Available for commercial breeds. Not normally available for others – requires survey
Correct definition of
farm objective function. Aggregation
for estimating consumer surplus can also be problematic
Identify society’s ‘willingness to pay’ (WTP) for the conservation of AnGR
Policy-makers in charge of conservation
Define upper bound to economically justified conservation programme costs
Society’s preferences expressed in terms of WTP
Not normally available. Requires survey
Response difficulties when used for ‘non-charismatic’ species and/or chronic genetic erosion
 

Top Of Page

Methodologies for determining the appropriateness of AnGR conservation programme costs

There are those methodologies that seek to determine the appropriateness of AnGR conservation programme costs.

The Contingent Valuation Method (CVM) relies on questionnaires about willingness to pay (WTP) or willingness to accept (WTA) payment for conservation. Pearce and Moran (1994, p. 61) argue that CVM is a promising option for biodiversity valuation in general because: it is the only way to elicit non-use values directly; the potential for information provision and exchange during the survey process offers scope to experiment with respondent knowledge and understanding of biodiversity; and it can be used as a surrogate referendum on determining conservation priorities based on public preferences.

Hypothetically then, farmers might be asked about their willingness to accept payment for on-farm maintenance of AnGR, and the general public might be queried on WTP for maintenance on-farm or in gene banks. In this way, an upper bound to the costs that society is willing to confront for AnGR conservation could be determined. However, CVM has never been attempted for genetic resources valuation per se.

An alternative approach to defining an upper bound for economically justifiable conservation costs is to identify the minimum that society could economically justify based on a measure of production loss averted. This approach attempts to identify the magnitude of potential production losses in the absence of AnGR conservation. For example, Smith (1984a) compared conservation costs for AnGR in the UK to a potential catastrophic event resulting in the loss of an arbitrary 1% of the total annual production value, on the assumption that conservation of AnGR would prevent these losses. A variation of this approach has been used by Brown and Golstein (1984) in order to value ex-situ (plant) collections. They used a model where the benefits of reducing expected future production losses are weighed against gene bank operating costs and searches, arguing that all varieties should be conserved for which the marginal benefit of preservation exceeds marginal cost. Oldfield (1989), on the other hand, focuses on actual crop losses (in this case related to Southern Corn Leaf Blight) as a measure of value of the genetic improvement efforts used to eventually overcome such losses.

The magnitude of such losses is, however, a poor proxy for the value of genetic materials as such an approach fails to account for substitution possibilities. This is because crop production losses are not necessarily mirrored by agricultural production losses and consumer/producer surplus2 may only be marginally affected if satisfactory substitutes exist at reasonable prices (Evenson et al. 1998). The Smith (1984a) approach is also open to such criticism.

2. Total surplus (i.e. consumer plus producer surplus) is a measure of the total value of consumption minus the total cost of production. Since shifts in demand and supply curves cause changes to the prices and quantities consumed/produced, changes in ‘utility’ or welfare should be measured through a total surplus approach rather than by simply looking at the value of consumption/production (i.e. price multiplied by quantity).

An opportunity cost approach is used by Brush et al. (1992) by applying the concept of option value to the maintenance of on-farm diversity by Peruvian peasant potato farmers even when the immediate advantages of switching to improved varieties are large. The benefits forgone are thus a measure of the cost of maintaining the option of switching to other varieties at a later date. This form of option value is essentially a kind of insurance and is therefore similar to an approach used by Heisey et al. (1997). They compare a portfolio of wheat varieties actually cultivated by Pakistani farmers with an alternative more diverse portfolio and find that switching to the more genetically diverse portfolio would generate expected yield losses of tens of millions of dollars per year. This suggests that this approach to measuring farmers’ willingness to pay for genetic diversity can sometimes generate negative estimates. Both approaches can be used to value ex-situ collections, although it would be a mistake to assign values to gene banks on the basis that they are the sole source of insurance against production losses (Evenson et al. 1998, p. 8 and p. 19).

Brush and Meng (1998) propose a cost-effective strategy for crops that could be easily adapted to livestock. Instead of attempting to justify conservation programme costs on the basis of society’s willingness to pay or the production losses that can be potentially avoided, they argue that once the need for conservation of a particular breed has been agreed on, the costs of such a programme can be minimised by recognising the factors influencing farmer animal selection decisions, thereby identifying those households that most value such breeds. Since these are the households most likely to continue to maintain such breeds they will also be the least costly to incorporate into a conservation programme.

The basic methodology is thus to link the probability of a household’s maintaining a certain breed with the household’s costs of production and net income. Such a cost-side approach has the advantage of bypassing the difficulties involved in estimating the total benefits to society while providing a frame of reference for the magnitude of expenditures necessary to implement an in-situ conservation programme.

 

Methodologies for determining the actual economic importance of the breed

Although demonstrating the appropriateness of conservation programme costs is important, identifying the actual economic importance of a breed can also provide a strong argument for conservation.

Econometric estimation of aggregate demand and supply curves can be used in order to provide a measure of consumer and producer surplus based on the fact that changes in the traits or the composition of breeds will produce shifts in the estimated functions, which in turn will bring about a change in consumer and producer surplus (ILRI 1999). Where multiple demand equations (one for each breed) can be estimated, the substitution effects across breeds can be explicitly modelled providing the most comprehensive evaluation of breeds while capturing substitution effects as well. Cross-sectional household and farm studies can also be used in order to construct demand and supply functions.

A simpler but conceptually inferior approach is the market share analysis. This approach involves identifying the total share of market value that can be attributed to a given breed as a measure of the value to society of the bundle of traits embedded in the breed. However, this approach does not provide a consumer/producer surplus measure of value.

The existing or potential value of intellectual property rights and/or contracts for AnGR use and conservation could also be used as an indication of the economic importance of given breeds.

Brush and Meng (1998, p. 7) point out that the most direct method of valuing genetic resources is to privatise them and allow the market to set a price. Note that at present ex-situ genetic resources collected before the CBD entered into force are treated as public goods. Theoretically, privatisation would provide compensation to those who safeguard genetic resources, thus stimulating conservation without public investment while providing an idea of genetic resources users’ willingness to pay for conservation. Privatisation could be achieved through the use of intellectual property rights (IPRs) and/or contracts for exploration/extraction.

However, ITDG (Intermediate Technology Development Group ) (1996) argue that IPRs, and patents in particular, which are being promoted (mostly by the North) as the appropriate tool for the privatisation of genetic resources, fail to reward local people for their important contributions (of knowledge and resources) to the products for which industry is awarded patent protection. For example, the world’s smallest cattle breed, the ‘vechur’, was bred in India and needs only 1.5 kg of feed daily. It has now been patented in the UK (ITDG 1996, p. 13). There is therefore considerable, and as yet unresolved, international debate as to whether the scope of intellectual property needs to be extended, or whether new property rights need to be developed to prevent the patenting of such products.

In any case, Brush and Meng (1998), point out that contracts would be preferable to IPRs on the grounds that the former are the easiest means to create a market for genetic resources. They argue that contracts between producers of genetic resources (e.g. farmers) and private users (e.g. biotechnology companies) are a way to avoid the monopoly-related problems associated with IPRs. Model agreements for ‘biodiversity prospecting’ now exist – for example, the Merck bioprospecting royalty agreement in Costa Rica (Laird 1993) – for pharmaceutical research. Material transfer agreements and collector agreements for crop germplasm potentially are a step in the direction of contracts. Such contracts could eventually be applied to AnGR.

 

2.2.3 Methodologies for priority setting in AnGR breeding programmes

Given that the FAO recommends ‘active and sustainable utilisation’ (i.e. in-situ conservation), together with improving the production levels of adaptive breeds as central to the better management/conservation of AnGR (FAO 1997; Hammond 1998), ensuring that conservation and their related breeding programmes are maximising their potential benefits is important. For this purpose, several valuation methodologies can be applied. These include:

Breeding programme evaluation approaches are used to evaluate the costs and benefits of breeding programmes and/or the new animals/breeds. Cervigni (1993) shows how the benefits of genetic material could be valued assuming (critically) that the yield effects of successive breeding stages and the necessary input cost information can be identified. This would require using the difference between the benefits of an improved breed (based on price and increased yield) and the costs of all other factors employed in breeding operations (capital, labour, etc.). The value of using alternative inputs/traits could then be compared to see how they affected economic returns. For this purpose, breeding programmes have long used a selection index as a device for multiple trait selection in farm livestock, first introduced for animal breeding by Hazel (1943).

For example, Mitchel et al. (1982) measured the value of genetic contributions to pig improvement in Great Britain by determining the heritability of important characteristics and isolating the genetic contributions to improved performance. Using linear regression techniques to compare control and improved groups over time, they found that the returns were substantial, with costs in the region of 2 million British pounds sterling (UK£) p.a. (UK£ 1 = 2.382US$ in 1981 and 1.923 in 1982) relative to benefits of UK£100 million p.a. The use of crossbreeding in commercial production was estimated to contribute approximately UK£16 million p.a.

Genetic production function models are similar to the above. However, their focus is on predicting potential future values rather than using the actual results of breeding programmes. In this context, existing AnGR are valued by weighting the expected value of the new breed by the probability of this being successfully developed. The expected value reflects the discounted stream of benefits of the new breed over the period in which these benefits are expected to take place (Scarpa 1999).

Gollin and Evenson (1994) use such a methodology to report a breeding function for rice, while Simpson and Sedjo (1996), borrowing from labour economics, have attempted to develop a valuation model grounded in search theory which depends on the cost of the search (effort and expense involved in research), the expected rewards and the best alternative identified to date. However, their preliminary results reveal low economic values for biodiversity because of the fact that crop improvement researchers make very little use of the vast amount of material available to them. At least for crops then, genetic resources may be valuable, but are not perceived as being scarce. On the other hand, given the low level and higher cost of gene-banking of animal resources at risk, this perception of 'abundance' may not be so important in the case of AnGR.

Predicting potential future values requires the incorporation of option3 which, according to Artuso, would require a model structured in the form of a stochastic dynamic programming problem, since the decision to preserve genetic material in any time period 'allows for a new choice in the following time period that includes the option to benefit from new information about the expected value of the preserved genetic resources' (Artuso 1998, p. 7). In terms of in-situ conservation, incorporating option value into such models also requires consideration of risk aversion, since farmers may seek to minimise the frequency and/or duration of major production failures.

3. In the context of genetic resources, option values are presumed to be the future value of such resources in producing new breeds or commercial products (Evenson et al. 1998, p. 19).

In this context, Smith (1985) argues that reductions in uncertainty can be modelled by including risk in the discount rate when assessing the benefits over time from one cycle of selection. He concludes that the costs of developing alternative selection stocks are small relative to the possible returns (although differences between private and social costs/benefits may exist). Hence, breeding selection based on the current set of economic objectives is suboptimal in an intertemporal context (as some animal geneticists might suggest). Instead, given uncertainty about future needs, selection should be 'directed to cater for foreseeable and even unpredictable futures' (Smith 1985, p. 411). In particular, Smith (1984b) advocates the storage of stocks that contain currently undesirable traits that may only have temporary current value (e.g. market or grading requirements, carcass or product composition, special behavioural adaptations to current husbandry conditions, etc.).

The evaluation of breeding programmes could also make use of a method suggested by Evenson (1991). This relates yield value improvements to the genetic resources and other activities used to produce them, through a hedonic valuation of animal characteristics. With enough variability in the relevant vector of phenotypic (or genetic) traits of the animals, a hedonic function that attempts to decompose the total value (price) of the single animal transacted into its relevant traits can be identified. In principle, the technique could also be used to value breeds (ILRI 1999).

While Evenson (1996, p. 9-18) reviewed five studies of rice production that use hedonic trait valuation (covering India and Indonesia), examples of such an approach being used for AnGR valuation are more limited. These include a study of cattle in Nigeria by Jabbar et al. (1998) and in Canada by Richards and Jeffery (1995). The former concluded that hedonic pricing produced a satisfactory model of the prices of cattle exchanged at market. Moreover, it showed that although there were some differences in prices that were solely because of breed, most variation in prices was because of such variables as wither height and girth circumference that vary from animal to animal within breeds. Variation because of type of animal or month of transaction was also greater than that because of breed. Richards and Jeffery (1995) attempted to identify the value of relevant production and type traits for dairy bulls in Alberta, Canada. A hedonic valuation model is estimated that models semen price as a function of individual production and longevity characteristics for a sample of Holstein bulls.

In addition, Evenson (1991) notes that the hedonic pricing technique is likely to be particularly useful for assessing the value of the contribution to newly developed 'successful' varieties of the genetic materials that were conserved ex-situ. This could also provide an indication of the relative returns to further genetic resources collection as opposed to further developments based on existing resources.

Farm-level simulation models of animal production can also be used by breeding programmes in order to ensure that breed benefits are being maximised by directly modelling the effects of improved animal characteristics on the economics of farms.

Farm models have been built for several species, farmed using high-input management approaches. For example, Ladd and Gibson (1978) use such a model to measure the economic values of three heritable characteristics in swine: backfat, feed efficiency and average daily weight gain.

These models would have to be adapted to developing countries to be used widely. However, farm modelling offers great potential as a tool to measure the value of specific changes, such as in litter size, productivity or a breed change, to a specific production system. If the model is coupled with sophisticated market models, the results can be aggregated and used for welfare analysis as well. It is probably most useful in those agricultural contexts in which farm animals are only one of the various outputs of farms. It can incorporate mechanisms linking cause and effect, and explore the effect of breeds not yet known (ILRI 1999).

Overview of AnGR valuation methodologies and knowledge gaps

We have thus seen that although some models have been developed for assessing the value of crop genetic resources and that some of these may be potentially adaptable to AnGR, it can be appreciated that the field of economic valuation of AnGR requires substantial development. As a result, the questions raised by Artuso (1998), cannot as yet be answered in quantitative terms nor can specific techniques be recommended. Rather, a broad array of these tools needs to be tried to determine which is best or most suitable for differing circumstances (ILRI 1999).

The valuation techniques reviewed here have been shown to have strengths and weaknesses. The decision of which technique to use for a particular application requires experience and judgement on the part of the analyst. Data availability and/or the potential for acquiring relevant data will clearly be an important determinant, especially given the problems of missing markets and market imperfections commonly encountered in developing country situations. Where such missing markets/imperfections are significant, the resulting impact of any violations of the underlying assumptions of the potential valuation methodologies must be carefully considered and appropriate measures taken (if application is still a possibility). As indicated in Table 1, such violations will frequently require that much of the required data will have to be collected through specially designed surveys4 and adequate shadow pricing5 of relevant inputs/outputs used where market prices do not exist or are distorted. In choosing between methodologies, the analyst will also have to be aware of how different methodologies will be of interest to different actors, which include inter alia farmers, breeders and policy-makers in charge of conservation (see Table 1).

4 Given that the FAO (1998) proposes conducting AnGR resource assessments as part of the development of farm AnGR management plans, such data may increasingly become available. This of course assumes that economic valuation issues are properly incorporated into such assessments from the beginning. Nevertheless, as many countries have not yet carried out such assessments, yet alone contemplated the need to incorporate such issues, specifically designed surveys will need to be carried out, at least in the short- to medium-term.

5 Market prices are assumed to reflect their economic scarcity. Where this is not the case appropriate adjustments should be made. This might include eliminating the influence of taxes, subsidies or minimum wages. It may also require the use of international market prices. Where such adjustments are made, the resulting prices used in the economic analysis are termed ‘shadow prices’.

Given this state of the art of AnGR valuation, ILRI (International Livestock Research Institute) is currently in the process of implementing a 'strategic framework for international research in AnGR valuation' (ILRI 1999, 2000) which includes the field testing of potential valuation methodologies. A subsequent evaluation of the more promising methodologies will then be undertaken and a set of guidelines for preferred methods elaborated. Case studies are currently underway at several locations in Africa and Latin America.

Ø From your experience of animal genetic resource erosion in your community or country, which of the above methodologies do you consider likely to be the most useful? Why? What policy and/or management questions will these methodologies provide answers to and who are the principal stakeholders who will benefit from the application of these particular valuation methodologies? What data is needed for these methodologies and how would you obtain it?

Conclusions

Drawing heavily on the limited PGR valuation literature, it is apparent that a range of valuation methodologies is available for consideration of their potential application to AnGR. These can be broadly categorised into the following 3 methodological groups:(i) for determining the appropriateness of AnGR conservation programme costs (i.e. consider environmental values); (ii) for determining the actual economic importance of the breed at risk (i.e. consider breed values); and/or (iii) for priority setting in AnGR breeding programmes (i.e. consider trait values).

However, given that examples of AnGR valuation studies using these methodologies that have actually been carried out are extremely limited, it is clear that the field of economic valuation of AnGR per se requires substantial development.

Hence, a broad range of these tools needs to be field tested in order to determine which is best or most suitable for differing circumstances. In terms of methodological development, the nature of the threat to AnGR diversity suggests the importance of ensuring that at least some of the empirical results obtained with these methodologies are capable of supporting in-situ conservation activities in developing countries.

Reference

Anderson S., Drucker A. and Guendel S. 1999. Conservation of animal genetic resources. External Programme, Wye College, University of London, Wye, UK. 280 pp.

Artuso A. 1996. Creating linkages between valuation, conservation and sustainable development of genetic resources. In: Evenson R.E., Gollin D and Santaniello V. (eds), Proceedings of Paper prepared for the Symposium on the Economics of Valuation and Conservation of Genetic Resources for Agriculture, held at the Centre for International Studies on Economic Growth, Tor Vergata University, Rome, Italy, 13-15 May 1996. FAO (Food and Agricultural Organization of the United Nations), Rome Italy, CEIS-Tor Vergata and CABI Publishing, Wallingford, UK. pp. 197-206

Brown, G. and Goldstein, J. 1984. A model for valuing endangered species. Journal of Environmental Economics and Management 11:303-309.

Brown, K., Pearce, D., Perrings, C. and Swanson, T. 1993. Economics and the conservation of global diversity. Working Paper Number 2. Global Environmental Facility. Washington D.C, USA. 61pp.

Brush S. and Meng E. 1996. Farmers´ valuation and conservation of crop genetic resources. In: Evenson R.E., Gollin D and Santaniello V. (eds), Proceedings of Paper prepared for the Symposium on the Economics of Valuation and Conservation of Genetic Resources for Agriculture, held at the Centre for International Studies on Economic Growth, Tor Vergata University, Rome, Italy, 13-15 May 1996. FAO (Food and Agricultural Organization of the United Nations), Rome Italy, CEIS-Tor Vergata and CABI Publishing University, Wallingford, UK.

Brush, S., Taylor, J. and Bellon, M. 1992. Technology adoption and biological diversity in Andean potato agriculture. Journal of Development Economics, 39:365-387.

Cervigni, R. 1993. Estimating the benefits for plant genetic resources for food and agriculture. CSERGE (Centre for Social and Economic Research on the Global Envrionment), University College London, London, UK.

Drucker, A., Gomez V. and Anderson S. 2001. The economic valuation of farm animal genetic resources: a survey of available methods. Ecological Economics 36:1-18.

Evenson, R. 1991. Genetic resources: assessing economic value. In: Vincent, J., Crawford, E. and Hoehn, J. (eds),. Valuing environmental benefits in developing economies. Special Report 29. Proceedings of a seminar series held February to May 1990 at Michigan State University, Michigan, USA, 1990. Yale University, New Haven, USA .

Evenson R. 1998. Valuing genetic resources for plant breeding: hedonic trait value, and breeding function methods. In: Evenson R.E., Gollin D and Santaniello V. (eds), Proceedings of Paper prepared for the Symposium on the Economics of Valuation and Conservation of Genetic Resources for Agriculture, held at the Centre for International Studies on Economic Growth, Tor Vergata University, Rome, Italy, 13-15 May 1996. FAO (Food and Agricultural Organization of the United Nations), Rome Italy, CEIS-Tor Vergata and CABI Publishing University, Wallingford, UK.

Evenson, R., Gollin, D. and Santaniello, V. (eds). 1998. Agricultural values of plant genetic resources. (Commonwealth Agricultural Bureau) International, Wallingford, UK. 285 pp. CAB International, Wallingford, UK. 285pp.

FAO (Food and Agriculture Organisation of the United Nations). 1997. Nations discuss utilization and conservation of genetic resources. In: FAO Global Programme for Management of Farm Animal Genetic Resources. FAO, Rome, Italy. http://dad.fao.org/dad-is/library/programm/index.html. (Accessed January 2000).

FAO (Food and Agriculture Organisation of the United Nations). 1998. Secondary Guidelines for Development of National Farm Animals Genetic Resource Management Plans: Management of Small Populations at Risk. FAO, Rome, Italy. 215pp.

Gollin, D. and Evenson, R.E. 1994. The economic impact of the International Rice Germplasm Center (IRGC) and the International Network for the Genetic Evaluations of Rice (INGER). International Rice Research Institute IRRI (International Rice Research Institute), Manila, The Philippines.

Hammond, K. 1998. The status of global farm animal genetic resources. In: Evenson R.E., Gollin D and Santaniello V. (eds), Proceedings of Paper presented at the Symposium on the Economics of Valuation and Conservation of Genetic Resources for Agriculture held at the, Centre for International Studies on Economic Growth, Tor Vergata University, Rome, Italy, 13-15 May 1996. FAO (Food and Agricultural Organization of the United Nations), Rome Italy, CEIS-Tor Vergata and CABI Publishing University, Wallingford, UK. pp.16-23.

Hazel, L. 1943. Genetic basis for selection indexes. Genetics, 28: pp. 476-490.

Heisey, P., Smale, M., Byerlee, D. and Souza, E. 1997. Wheat rusts and the costs of genetic diversity in the Punjab of Pakistan. American Journal of Agricultural Economics, 79: 726-737.

ILRI (International Livestock Research Institute). 1999. Economic valuation of animal genetic resources. In: Rege J.E.O. (eds), Proceedings of an FAO/ILRI workshop held at FAO (Food and Agriculture Organisation of the United Nations) Headquarters, Rome, Italy, 15-17 March 1999. ILRI, Nairobi, Kenya. 80 pp.

ILRI (International Livestock Research Institute). 2000. Report of the research planning workshop on Economic Valuation of Animal Genetic Resources. February 2-4, held at ILRI, Nairobi, Kenya, 2-4 February 2000. ILRI, ILRI, Nairobi, Kenya. 25pp.

ITDG (Intermediate Technology Development Group). 1996. Livestock keepers safeguarding domestic animal diversity through their animal husbandry. Dynamic Diversity Series. ITDG, Rugby, UK.England. 19pp.

Jabbar, M., B. Swallow B., G. d'Iteran G. and, A. Busari A. 1998. Farmer preferences and market values of cattle breeds of West and Central Africa. Journal of Sustainable Agriculture 12: 21-47.

Ladd, G. and Gibson, C. 1978. Microeconomics of technical change: what's a better animal worth? American Journal of Agricultural Economics, 60:236-240.

Laird, S. 1993. Contracts for biodiversity prospecting. In: Reid, W., Meyer C.A., Gamez R., Sittenfeld A. (eds), et al. Biodiversity prospecting: Using genetic resources for sustainable development. World Resources Institute,. Washington DC, USA. . pp.99-130.

Mitchell, G., Smith, C., Makower, M. and Bird, P. 1982. An economic appraisal of pig improvement in Great Britain. Animal Production, 35: pp. 215-224.

Oldfield, M. 1989. The value of conserving genetic resources. Sinauer Associates, Sunderland. Massachusetts, USA.

Pearce, D. and Moran D. 1994. The economic value of biodiversity. Earthscan,. London, UK. 172pp.

Richards, T. and Jeffrey, S. 1995. Hedonic pricing of dairy bulls - an alternative index of genetic merit. Department of Rural Economy, Project Report 95-04. Faculty of Agriculture, Forestry, and Home Economics. University of Alberta Edmonton, Canada. 39pp.

Scarpa, R. 1999. Revealed preference valuation methods for farm animal genetic material: principles, strengths and weaknesses. Paper presented at an ILRI (International Livestock Research Institute)-FAO (Food and Agriculture Organisation of the United Nations) planning workshop on Valuation of Animal Genetic Resources held at FAO, Rome, Italy, 15-17 March 1999.

Simpson R. D. and Sedjo R. A. 1996. The value of genetic resources for use in agricultural improvement. In: Evenson R.E., Gollin D and Santaniello V. (eds), Proceedings of Paper prepared for the symposium on the Economics of Valuation and Conservation of Genetic Resources for Agriculture held at the, Centre for International Studies on Economic Growth, Tor Vergata University, Rome, Italy, 13-15 May 1996. FAO (Food and Agricultural Organization of the United Nations), Rome Italy, CEIS-Tor Vergata and CABI Publishing, Wallingford, UK. pp.55-66.

Smith, C. 1984a. Estimated costs of genetic conservation of farm animals. In: Animal genetic resources conservation and management, data banks and training. FAO Animal Production and Health Paper No. 44/1. FAO (Food and Agriculture Organisation of the United Nations), Rome, Italy. pp. 21-30.

Smith, C. 1984b. Genetic aspects of conservation in farm livestock. Livestock Production Science 11: 37-48.

Smith, C. 1985. Scope for selecting many breeding stocks of possible economic value in the future. Animal Production, 41: 403-412.


Top Of Page

Last Updated on Thursday, 18 February 2010 06:30