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The global economic effects of eliminating certain significant categories of nontariff measures (NTMs) are estimated in a CGE context. As a first step, a database of institutional information identifying alleged instances of NTMs for particular products and countries is constructed based on WTO, U.S. Government, and EU sources, and compared with the UNCTAD policy inventory. This database is then concorded to a GTAP-feasible multiregion, multisector aggregation. Retail price data from the EIU CityData database, similarly concorded, are analyzed econometrically, taking into account systematic deviations from purchasing-power parity, to determine whether and to what extent the presence of alleged NTMs is associated with significantly higher prices. The estimated price effects are then used to calibrate a CGE simulation in order to obtain simulation estimates of trade and welfare effects of their removal, which can be disaggregated. Removal of the categories of NTMs under consideration yields global gains on the order of $90 billion. These gains arise notably from liberalization by Japan and the European Union by region, and from liberalization of apparel and machinery/equipment by sector.

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As multilateral negotiations focus more on reductions and removal of non-tariff barriers (NTBs), the importance of quantifying the impact of these barriers has increased. Recent studies have derived ad valorem equivalents for NTBs for a large number of countries and/or products, but the derivation has been indirect, due to either lack of price data or NTB incidence measures. This paper uses city level retail price data to directly estimate the average impact of core NTBs on prices of 47 consumer products, grouped into four separate sectors, for more than 60 countries in 2001. The analysis uses both government self-reported data and a new database of private sector complaint data to assess NTB incidence. A differentiated products model is used to capture imperfect substitutability between products. With city level price data—including both inter- and intra-country price differences—a more precise distinction can be made between the impact of NTBs and the impact of local distribution costs in raising price. The model is estimated using an instrumental variables approach to incorporate the endogeneity of NTBs. Results suggest that core NTBs are still highly restrictive in many countries and for many traded goods. While NTBs appear to be complements to tariffs, in some sectors the presence of a tariff reduces the price impact of the NTB. Results also suggest that in some sectors, the restrictiveness of NTBs is highly correlated with country income.

Using supply chain analysis to examine the costs of non-tariff measures (NTMs) and the benefits of trade facilitation WTO Staff Working Paper, No. ERSD-2012-02 AbstractIt has become increasingly common to produce goods in a number of geographically dispersed stages linked by international trade. This tendency, known by names such as "production fragmentation", "processing trade", and "vertical specialization", has important implications for the analysis of nontariff measures (NTMs) and trade facilitation. First, different types of NTMs or trade facilitation issues are naturally associated with different stages in the movement of goods. Different price gaps can be assigned to these stages, making it possible to decompose the overall amount of distortion and to prioritize the policies with the largest potential efficiency gains. Second, NTMs may accumulate in long supply chains, implying that their trade-distorting effects are greater for goods produced in a fragmented manner than for goods with simple production processes. There is evidence that trade costs are more important for high technology goods or goods undergoing several stages of processing. Issues with product standards may be particularly important for goods with long supply chains. The link between NTMs and supply chains also has implications for economic development and for the relationship between liberalization in services and goods.JEL Classification: F13, F15, F29