GTAP Resources: Resource Display
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"European Regions Faced with the Doha Round: A CGE Assessment" by Laborde, David and Sebastien Jean Abstract The broadest regional classification (NUTS-1) breaks the European Union down in 78 regions, and this number will rise to 119 in the enlarged EU. Although economic interactions are admittedly very important across these regions, income per capita varies in a proportion from one to 7 in the fifteen-member EU, and from one to more than 20 in the enlarged Union. The share of agriculture in value added varies from 1.41%, up to 22.09%. In this context, trade policy is likely to have very contrasted impacts across regions. These cross-regional contrasts are important in various respects. They condition the nature and magnitude of adjustments to be expected as a result of trade liberalization, as well as the opportunity and adequacy of any flanking policies. They also shed light on the nature of the interactions between trade policy and cohesion policy, both of the Community's competence. Even at the aggregate level, the regional structure of the EU's economy is likely to influence the impact of trade policies. However, such a regional approach to trade policies was still lacking so far for the EU. Hence the questions addressed by this article: how to assess the impact of trade liberalization at the regional level in the EU? What does a regional assessment add to the understanding of the nature and magnitude of the impact of trade liberalization on the EU? What are the conclusions to be drawn as far as the Doha Round is concerned, in general but also separately for each of the main aspects of the negotiation? This article presents a bottom-up CGE model designed to provide with an accurate assessment of the regional impact of trade policies in the EU, and applies it to a plausible outcome of the Doha Round. The approach proposed here is two-tiered and embeds two CGE models. A preliminary, EU-wide assessment is delivered using the MIRAGE model, with each EU's countries treated separately. The information thus produced about the impact on international trade –more specifically on the price of EU imports and on the demand addressed to EU's exports– is then used as an input for the regional analysis. This regional analysis is carried out using DREAM, an original model built on purpose. DREAM is a bottom-up, CGE model describing separately each NUTS-1 EU region, and its relationships with the rest of the world. DREAM is very similar to the MIRAGE model (see Bchir et al., 2002) in terms of theoretical structure. Capital is assumed to be perfectly mobile across the whole EU, while labor is imperfectly mobile across regions within countries. In order to make the model tractable, some simplifying assumptions had to be made. In particular, the model is static, and the country mix of imports (geographical distribution across providers, including foreign EU regions) as well as the country mix of exports (geographical distribution across markets, including foreign EU regions) is assumed to be constant over regions, within each EU country. In addition, perfect competition is assumed to hold, technologies exhibit constant return to scale, and goods are differentiated only according to geographical origin. In order to implement this model, a database describing the required variables for 119 NUTS-1 EU regions and 21 sectors is built. This requires a heavy work in order to harmonize and complete existing data. The model is applied to the Doha Round. Pre-experiment simulations are run to take into changes such as China entering the WTO, the phasing out of MFA, and the implementation of the Uruguay Round agreement. The experiment then relies on plausible outcomes of the negotiation, considered separately for agricultural domestic support, agricultural export subsidies, market access in agricultural products, market access in textile-clothing, and market access other non-agricultural products. The simulations make it possible to characterize the impact involved for each European region. Cross-regional differences mainly arise as a result of differences in sectoral output specialization, along with sectoral and geographical trade specialization. These differences interact with the nature of the shock, with region-wide equilibrium constraints, and with close cross-regional economic links. As illustrated by the comparison with the results of an accounting allocation methodology, the results are not easily proxied based on a simple calculation, even when economy-wide constraints and regional characteristics are taken into account. Agricultural sectors are especially sensitive ones, due both to their relatively high level of protection and to their uneven distribution across EU regions. The specific role of transport and communication is also noteworthy. Indeed this sector is in average more important in wealthier regions, and it is generally among the most favored ones as a result of liberalization. |
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Public Access  GTAP Resource 1582 (192.1 KB) Replicated: 0 time(s) Presentation (544.1 KB) Replicated: 0 time(s)Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 9/15/2023 2:05:45 PM
