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Quantifying the impacts of agricultural trade liberalisation Lecture 27 Economics of Food Markets Alan Matthews
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Issues to address What can we learn from empirical studies about the gains from further agricultural trade liberalisation? How confident can we be in modelling results? Why do results vary?
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Reading Martin and Anderson 2006 AJAE article Taylor Oxfam CGE critique Anderson and Martin book, available on the web, esp. Chapters 2 and 12. Also McCalla and Nash Volume 2 Various briefs and commentaries –Bouët, Elliott, FAO, Ackerman, Economist
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Early studies showed substantial impacts.. Many studies purport to show –Large gains from agricultural trade liberalisation –Large share of gains accruing to developing countries –All developing countries share in these gains Examples –IMF 2002: $128 billion, of which $30 billion to DCs –Goldin et al: 2003 $364 billion, of which $176 billion to DCs –Anderson 2003: $165 billion, of which $43 billion to DCs –World Bank 2004: $400-900 billion from total trade liberalisation, more than half of which to DCs, of which agriculture would account for 70%
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.. But estimates of gains have been steadily shrinking Source: Bouët 2006
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…and not all developing countries will necessarily gain Panagariya 2002 “The presumption that such liberalization will broadly benefit the poor countries, implicit in the allegations that agricultural subsidies in the rich countries hurt the poor in developing countries, is unlikely to be supported by closer scrutiny in its unqualified form.” Charlton and Stiglitz 2004 “The existence of net losses for developing countries in some areas of reform should not imply that no reform is required—rather it suggests that a selective approach is needed.”
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Impact of Doha Round agreement (Bouet et al., 2004) Change in production Agri-food exports Agri-food imports Returns to land Change in welfare EU25-1.572.712.8-15.010.14 US-1.050.82.8-0.210.07 Asia developed-2.0811.89.6-1.790.06 Cairns developed3.6612.82.81.080.04 Mediterranean0.738.8-1.50.77-0.16 Cairns developing1.2510.4-0.70.60-0.07 China0.0113.210.10.300.15 RoW0.646.8-0.71.15-0.08 South Asia-0.016.47.8-0.100.15 SSA0.764.7-0.80.22-0.05 World-0.396.16.0-0.09
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Approaches to quantifying impacts Modelling –Single or multi-commodity models –Partial or general equilibrium models –Commodity coverage –Econometric or general equilibrium –Static or dynamic
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Why results may differ Base period and initial levels of protection Elasticity assumptions Taking account of complementary policies Price transmission elasticities
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Recent World Bank estimates Anderson, Martin, Van der Mensbrugge, June 2005 USD billion2015 Base case 2001 Scaled dynamics 2001 Compara- tive static GTAP elasticities GTAP elas + fixed land World287.3156.4127.488.577.8 Dev countries85.743.923.710.62.0 Sub Saharan Africa 4.82.80.70.2-0.1 South Africa1.30.80.70.50.4 Selected SSA countries 1.00.60.30.40.3 Rest of SSA2.51.4-0.2-0.6-0.8
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What determines the impacts - 1 Scenario assumptions –Full or partial agricultural trade liberalisation –Agricultural or total liberalisation –OECD countries only or global liberalisation –The counterfactual – what assumption is the modeller making about the reference scenario against which the policy scenario is being compared.
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What determines the impacts - 2 Net trade status The existence of preferences Dynamic effects through capital accumulation Taking account of productivity effects of increased trade Scaling effects which depend on the base year reported Modelling structure and parameter estimates
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Recent improvements in modelling techniques Many early studies simulated cuts in applied tariffs –Ignored tariff overhang –Ignored role of preferences –Good data on applied tariffs have become available only recently (MAcMaps), incorporated into GTAP 6 2001 database
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