2294 part 1 final report.pdf - Agra CEAS Consulting

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Prevention and control of animal diseases worldwide Part I: Economic analysis: prevention versus outbreak costs In terms of the global impact on trade from outbreaks of transboundary diseases, the size of the impact will depend on whether the outbreak occurs in significant world exporting countries, in which case a ban on exports from that country can send significant shocks to other major exporting as well as importing countries. For example, in 1997, the EU classical swine fever outbreak significantly affected intra-EU trade, as the Netherlands was a major exporter of pork and live pigs within the EU, but global pork trade was largely unaffected since the Netherlands, as well as Germany, Belgium, France, Italy and Spain, were not major exporters of pork outside the EU. By contrast, in 1996/97 the global pigmeat market was affected by the FMD outbreak in Taipei China, a major world exporter whose pork exports fell to 15% of the previous year’s value (Table 8). Furthermore, the net trade position of a major trading country can determine how localised the impact of an animal disease will be, and the impact is likely to be different when an affected country is both a major world exporter and a major importer, compared to a situation where an affected country is a significant exporter only. While it is possible to identify the resulting diversion in trade flows, as one country’s loss can be another country’s gain, the resulting net effect in terms of total loss in world trade revenues is difficult to establish. Available evidence suggests it is rather substantial. For example, restrictions on trade as a consequence of BSE notifications may have resulted to an estimated net loss of US$4.1 billion in world trade (Table 9). According to some analysts, the various world-wide import bans on meat from disease-infected areas, combined with heightened border inspections and testing, have limited global meat trade growth, from the 7% annual gains witnessed during the late 1990s to only 2% annually over the past few years (to 2006) (A111d). Given a global volume in meat trade of about 18 million tonnes and a global value estimated at US$72 billion (2004 estimates, FAO), this represents a potential annual loss in trade of some 0.9 million tonnes (or US$3.6 billion). In 2001 the severity and visibility of the FMD pandemic that affected major meat markets (EU, Mercosur) led to countries around the globe closing their borders to at least 25% of world beef trade and nearly 40% of global pork exports. In 2004 and 2005, the impact of the AI outbreak in Asia led to an unprecedented 8% decline in global poultry trade, and a loss of approximately US$ 1 billion in export earnings for the Asian region alone. With the continuing menace of AI, it is estimated that global poultry trade value is down nearly US$2 billion in 2006 (A295). Due to the complexity of the factors involved and the methodological difficulties, very few studies have tried to forecast such global aspects of the potential trade impact. A notable exception is the FAO/OECD short term commodity model (STM) 87 , which has been used to evaluate the short term global impact of a potential outbreak of Avian Influenza (as well as FMD and BSE) in different parts of the world. The model attempts to measure the impact of exogenously imposed export shocks to baseline projections. The potential impact is evaluated under difference scenarios of consumption shocks that the crisis may provoke to the EU-25 and/or the rest of the world, with implications on export volumes and 87 Developed in the context of Aglink-Cosimo, a collaborative modelling project between the OECD and the FAO. This is presently one of the most comprehensive partial equilibrium models for global agriculture and it is one of the tools used in the generation of baseline projections underlying the OECD-FAO Agricultural Outlook. It is a dynamic, multi-commodity, partial-equilibrium, global trade model, which provides one-year-ahead projections for demand, imports, exports, stocks and prices, given predetermined supply for 18 basic agricultural products, covering 50 countries /regions. Four meat categories, sub-divided into disease-affected and disease-free markets, are included in the model alongside a comprehensive coverage of the feed sector. Changes in real income, population and exchange rates are the principal exogenous variables driving global agricultural commodity markets. This model has also been used to evaluate the impact of FMD and BSE. Civic Consulting • Agra CEAS Consulting 78
Prevention and control of animal diseases worldwide Part I: Economic analysis: prevention versus outbreak costs domestic/international prices. The model scenarios and assumptions are constantly revised in view of new developments in animal disease occurrence (preliminary model results in A76, A111d and A283). The latest results (December 2006, A283) indicate that in the event of a global consumption shock due to AI (assuming this results in a 10% shift in global consumption away from poultry to other meats) international poultry prices would fall by 7% while pigmeat and beef prices would increase substantially (11-16% for beef and 15-19% for pigmeat). The net effect on world trade would be a fall in exports by 13% (while exports of developing countries would fall by 19% and imports by 12%). If the outbreak only occurred in the EU-25 (and assuming a 10% shift in EU consumption away from poultry) the effect on prices and global trade would be minimal but developing countries would expand their exports by 6% and drop their imports by 9%. A hypothetical outbreak in Brazil would result in a 3% increase in poultry prices and a 6% fall in world trade, although developing countries would increase their exports by 17% 88 . The same model demonstrates the importance of regionalisation policies in mitigating the trade losses caused by outbreaks not just in the disease-affected countries but for the world. Model results indicate that in the event of an FMD outbreak in Brazil, Brazilian exports of beef would fall by 9% and 60% respectively if regionalisation was applied, compared to a total ban on exports if regionalisation was not applied. Given that Brazil is the world’s largest beef exporter, the application of regionalisation has dramatic effects on world trade (reducing the impact to virtually zero) compared to a scenario where the policy is not applied (in which case the global decline in exports is 9%). These effects are reflected in world prices, with a significant containment in the decline of Brazil beef prices when regionalisation is applied (from 56% drop in the policy-off scenario down to a 7% in the policy-on) as well as significantly halting world price increases for beef. A selection of examples of the various ripple effects in terms of demand and trade impacts, caused by disease outbreaks in different parts of the world and at a global level, as identified from the reviewed literature, can be found in Table 8 below. Table 8 Ripple effects: selected examples of demand/price shocks and trade impact Country Impact Demand/price shocks global Vietnam An international survey of 19 countries (including Argentina, Brazil, Chile and Thailand) conducted in May 2006 shows that in most countries, about a fifth of the respondents reduced their consumption because of concern over AI. The impact was higher (30%) in HPAI-affected countries like Thailand and Italy, but even in HPAI-free countries such as Argentina and Brazil some 15% of respondents were affected. (A255) A 2004 FAO survey found that in Vietnam and Cambodia, prices of non-poultry meats rose up to 30% when live-bird markets were disrupted by HPAI and remained high even after the poultry 88 As already discussed, results depend on the scenarios and assumptions made, for example on consumer response. With potential outbreaks and consumption shocks uncertain, the above scenarios are only some of the possible impact assessments that can be made. Indeed, the results differ substantially from previous runs of the model using different assumptions (A76, A111d). These results should therefore be interpreted with caution. Civic Consulting • Agra CEAS Consulting 79
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Annexes Prevention and control of a
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