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In this paper we integrate the costs of trade finance in a computable general equilibrium (CGE) model to evaluate the trade and output effects of counterfactual policy experiments on costs of and access to trade finance. The costs of financing international trade consist of two components: the financial costs and the costs associated with the risk of goods not being delivered, considering risk aversion of traders. These costs are determined for four ways to finance international trade (cash-in-advance, trade loans, letters of credit, and exports financed with internal working capital). Trade finance costs are a weighted average of the costs under the four different ways of financing. The framework is applied to trade of four ECOWAS countries employing data collected on financial costs, costs of risk and trade finance instrument shares through a comprehensive bank survey in these countries complemented with data from the literature. Counterfactual experiments on increases in the availability of letters of credit and trade loans and the costs of these instruments show that raising the shares and costs to African averages would increase trade of the four ECOWAS countries by about 11%. The framework is generic and can be applied to other countries.

In this paper the evolution of global trade patterns until 2050 is projected with a recursive dynamic computable general equilibrium (CGE) model. Feeding the model with exogenous projections on macroeconomic, demographic, sectoral and trade cost variables, the evolution of trade patterns emerges endogenously from the model. The approach is innovative in both modelling approach and exogenous inputs. GDP growth emerges endogenously in the model because of diffusion of ideas as a result of international trade and trade cost changes are based on estimates of technology and trade policy changes. The projections indicate that (i) because of projected reductions in trade costs, trade will grow more than GDP, generating a global trade-toGDP growth rate of 1.1; (ii) because of structural change, the global share of manufacturing trade falls from 64% in 2020 to 52% by 2050, whereas the share of services trade rises substantially from 24% to 38%; (iii) because of technological catch-up, the share in global trade of both developing and least-developed countries (LDCs) will rise (with developing countries overtaking developed economies around 2035), the share of intra-developed country trade will fall, whereas the share of intra-developing country trade and those between developing and developed countries will rise.

Several Least-Developed Countries (LDCs) will graduate from the LDC status in the coming decade implying that they will lose preferential access to export markets. We quantify the expected impact of LDC graduation on exports of graduating and non-graduating LDCs incorporating detailed preference utilization data in a partial equilibrium model. We compare the results under actual and full preference utilization rates. Separately, we explore how underutilization of tariff preferences affects the exports of countries benefiting from such preferences. The analysis generates four main results. First, according to our projections, graduation will have a negative impact on the exports of graduating LDCs (more than US$ 6 billion export loss or 6% of exports), especially in the clothing sector. Second, the adverse trade effects of graduation would be overestimated by 30% under full instead of actual utilization rates. Third, our projections suggest that the increase in exports of non-graduating LDCs following graduation of other LDCs would be limited, implying that non-graduating poorer LDCs may hardly benefit from graduation of richer LDCs. Fourth, our projections suggest that increasing the utilization of LDC preferences would have positive trade effects. The exports of LDCs would increase by almost US$ 7 billion if they simultaneously switched to a full utilization regime.

Climate change mitigation faces two main policy challenges: the need for global cooperation to tackle the collective action problem and the need to share the burden of global carbon pricing fair way following the principle of common but differentiated responsibility (CBRD). In this paper we explore the best ways to incentivize regions to reduce their CO2 emissions while minimizing the welfare losses for low-income countries using simulations with a recursive dynamic computable general equilibrium (CGE) model. We first present the necessity, efficiency and urgency of global carbon pricing policies climate change mitigation policies. Global carbon pricing is necessary to tackle climate change, is more efficient than regional carbon pricing, and is urgent to prevent a patchwork of carbon pricing policies leading to calls for border carbon adjustment (BCA). However, because the impact of global carbon pricing on most regions is negative, complementary policies are needed to provide sufficient incentives to join a global carbon pricing coalition and at the same time share the burden fairly. We examine four potential complementary policies: BCA, Nordhaus's climate club, a global incentive scheme, and emission trading with progressive emission reduction targets. We evaluate these proposals based on their projected effects on average income and income inequality among countries, as well as their effectiveness as an incentive to introduce carbon pricing. BCA scores poorly along the three dimensions; Nordhaus's carbon club performs well as an incentive tool but has a negative impact on income and income inequality; the global carbon incentive has a positive impact on income and income inequality but performs poorly as an incentive tool; and emission trading with progressive reduction targets scores well across all dimensions. We conclude with a discussion of the feasibility of emission trading.

Since the outbreak of the COVID-19 pandemic there has been a discussion among researchers and policy makers about changes to global value chains, both about expected changes and changes that should be promoted by government policies. In this paper we conduct an in-depth analysis of the reasons for changes in global value chains as a result of COVID-19 both from a positive angle, analysing expected changes in the behaviour of firms, and from a normative angle, assessing the different arguments for policy interventions by governments. After this analysis international cooperation of trade policies and the role of WTO in crises like the COVID -19 pandemic is explored. The analysis generates three main conclusions. First, the COVID-19 pandemic could contribute to diversification of sources of supply whose extent will vary by sector depending on the costs of value chain reorganization. The pandemic, by contrast, is not likely to contribute much to re-shoring, the return of manufacturing activities to industrialized countries, which is more likely to be driven by pre-existing trends such as rising factor costs in emerging countries, increasing uncertainty about trade policy, and robotization and automation of production. Second, the pandemic has led to increased attention to the provision of essential goods in situations of crisis and our analysis concludes that to achieve this objective, global cooperation should be preferred to national policies such as domestic production and export restrictions. Third, the largest risk for the global economy in the aftermath of the pandemic is a move away from open, non-discriminatory trade policies, which would jeopardize the large benefits of open trade regimes in the current global economy characterized by scale economies, innovation spillovers, and a global division of labour.

The WTO Global Trade Model, a quantitative trade model, is employed to project the impact on the global economy of the COVID‐19 pandemic. Because of the profound uncertainty about the duration of the pandemic and the containment measures, three scenarios are constructed, V‐shaped, U‐shaped and L‐shaped recovery, corresponding with a duration of the pandemic of 3 months, 6 months and more than a year. The pandemic and containment measures are assumed to lead to a general reduction of labour supply, a rise in trade costs, and reductions in both demand and supply in sectors most affected by the containment measures. GDP and trade are projected to fall by, respectively, 5% and 11% in the V‐shaped and L‐shaped scenarios and trade by, respectively, 8% and 20%. The response of trade to the reduction in GDP, measured by the trade‐to‐GDP elasticity, is projected to rise as the crisis lasts longer. The reason is that a longer duration will lead to a larger drop in spending on durables which are highly tradable.

This paper provides an economic analysis of the trade conflict between the US and China, providing an overview of the tariff increases, a discussion of the background of the trade conflict, and an analysis of the economic effects of the trade conflict, based both on empirics (ex post analysis) and on simulations (ex ante analysis). Bilateral tariffs have increased on average to 17% between the US and China, and the Phase One Agreement signed in January 2020 between the two countries only leads to minor reductions in the tariffs to 16%. The trade conflict has led to a sizeable reduction in trade between the US and China in 2019 and is accompanied by considerable trade diversion to imports from other regions, leading to a reorganization of value chains in (East) Asia. The simulation analysis shows that the direct effects of the tariff increases on the global economy are limited (0.1% reduction in global GDP). The impact of the Phase One Agreement on the global economy is even smaller, although the US is projected to turn real income losses into real income gains because of the Chinese commitments to buy additional US goods. The biggest impact of the trade conflict is provoked by rising uncertainty about trade policy and the paper provides a framework to analyze the uncertainty effects.

This paper compares the solution methods and baseline calibration of three different quantitative trade models (QTMs): computable general equilibrium (CGE) models, structural gravity (SG) models and models employing exact hat algebra (EHA). The different solution methods generate identical results on counterfactual experiments if baseline trade shares or baseline trade costs are identical. SG models, calibrating the baseline to gravity-predicted shares, potentially suffer from bias in the predicted welfare effects as a result of misspecification of the gravity equation, whereas the other methods, calibrating to actual shares, potentially suffer from bias as a result of random variation and measurement error of trade flows. Simulations show that predicted shares calibration can generate large biases in predicted welfare effects if the gravity equation does not contain pairwise fixed effects or is estimated without domestic trade flows. Calibration to actual shares and to fitted shares based on gravity estimation including pairwise fixed effects display similar performance in terms of robustness to the different sources of bias.

The WTO Global Trade Model is employed to project the medium-run economic effects of a global trade conflict. The trade conflict scenario is based on recent estimates in the literature of the difference between cooperative and non-cooperative tariffs. The study provides three main insights. First, the projected macroeconomic effects in the medium run are considerable. A global trade conflict started in 2019 would lead to a reduction in global GDP in 2022 of about 1.96% and a reduction in global trade of about 17% compared to the baseline. For context global GDP fell about 2.1% and global trade 12.4% in the global financial crisis of 2009. Second, behind the single-digit aggregate production effects there are much larger, double-digit sectoral production effects in many countries, leading to a painful adjustment process. In general, a global trade conflict leads to a reallocation of resources away from the most efficient allocation based on comparative advantage. Third, the large swings in sectoral production lead to substantial labour displacement. On average 1.15% and 1.74% of high-skilled and low-skilled workers respectively would leave their initial sector of employment.

This document provides a technical description of the WTO Global Trade Model developed by the Center for Global Trade Analysis (GTAP) and the World Trade Organization (WTO). The model can be used to generate global trade projections and to assess the medium and long run effects of a wide range of global and national trade policies. The WTO Global Trade Model is a recursive dynamic extension of the static GTAP model (Corong et al., 2017), and implements a parsimonious approach to incorporate monopolistic competition - i.e., Eithier-Krugman or Melitz-type firm heterogeneity - in the standard GTAP model following Bekkers and Francois (2018).

This paper assesses the utility of economic theory of rational trade wars to predict such events or to prescribe courses of action to control their consequences. Trade wars are fundamentally political events whose causes are almost completely political and whose consequences are to a significant degree also political. Contemporary economic theory has developed during a uniquely peaceful and liberal period in world history, affecting how economists have thought about trade conflicts, leaving the profession unprepared to provide serious analysis or advice.

The reduction of non-tariff measures (NTMs) has become the key policy variable to evaluate modern and deep free trade agreements (FTAs), such as the Transatlantic Trade and Investment Partnership (TTIP). In this chapter we overview the two main approaches to estimating NTM reductions associated with the implementation of FTAs. We then detail how these reductions are estimated in different impact assessment studies of TTIP, we compare and analyse the main differences in these estimations and how they affect the overall economic impact of TTIP. We find that accounting for differences in the expected NTM reductions can explain a large share of the discrepancies regarding the overall potential economic effects between different impact assessments of TTIP.

We infer sectoral productivity from trade and production data and test the hypothesis that technological catch-up is slower in tacit knowledge intensive sectors, operationalised by measures of complex task intensity. Furthermore, we examine whether catch-up is slower in sectors with a large skill intensity, a high degree of export sophistication and high income elasticity. Employing Comtrade and UNIDO data between 1960 and 2000 covering manufacturing sectors, we find that catch-up is slower in more tacit knowledge intensive sectors, as well as in skill intensive and export sophisticated sectors. With more recent data from 1997 to 2011 from GTAP we find instead that catch-up is faster in more tacit knowledge intensive manufacturing sectors, whereas catch-up is slower in more tacit knowledge intensive services sectors. Catch-up is consistently faster in income elastic sectors, both for manufacturing and services.

The Centre for European Policy Studies (CEPS) is an independent policy research institute in Brussels. Its mission is to produce sound policy research leading to constructive solutions to the challenges facing Europe. The views expressed in this book are entirely those of the authors and should not be attributed to CEPS or any other institution with which they are associated or to the European Union. This book, commissioned by the Foreign Trade Association, aims to provide an independent and in-depth contribution on the status of bilateral economic exchanges and persistent trade barriers between the European Union and China. A second objective is to encourage a frank and open dialogue, based on a scientific evaluation and without prejudice, of the possibility of a preferential trade agreement between the two sides. The study was carried out by CEPS, in cooperation with the World Trade Institute at the University of Bern.