Elsevier

Journal of Policy Modeling

Volume 39, Issue 1, January–February 2017, Pages 65-78
Journal of Policy Modeling

Impact of the China–Australia FTA on global coal production and trade

https://doi.org/10.1016/j.jpolmod.2017.01.001Get rights and content

Abstract

Using a computable partial equilibrium model, this study provides a comprehensive and prospective empirical analysis of the economic impacts of the China–Australian Free Trade Agreement (ChAFTA) on global coal output, trade, consumption and welfare. Based on data from 2014, the simulated results indicate that ChAFTA has a significant trade creation effect. ChAFTA will increase Australia’s coal exports to China by 35.7% and China’s exports to Australia by 19.9%. However, the impacts of ChAFTA on global coal production and price are relatively limited. Results also demonstrate that ChAFTA will cause an annual net welfare loss of US$ 200 million for China and a net welfare gain of US$ 569.3 million for Australia. Moreover, Chinese consumers and Australian coal producers are the biggest beneficiaries of ChAFTA. Based on the research conclusions, we put forward some policy recommendations.

Introduction

After a decade of negotiations, the China–Australia Free Trade Agreement (ChAFTA) was formally signed on 17 June 2015 and entered into force on 20 December 2015. ChAFTA is China’s fourteenth FTA and its first FTA with a major economy.1 ChAFTA is also one of the FTAs with the highest degree of liberalization of trade and investment. Under the agreement, 85.4% of goods traded between both sides will cut tariffs to zero immediately. About 97% of Australian exports to China and 100% of China’s exports to Australia will be tariff free following the designed timeline step by step.

In fact, regional trade agreements (RTAs), which are permitted by Article XXIV of the GATT, have become increasingly prevalent since the early 1990s. As of 1 February 2016, some 454 physical RTAs had been received by the GATT/WTO and 267 of these were in force.2 By June 2016, all WTO members have at least one RTA in force.

With such rapid growth in the numbers, RTAs’ impacts have become a hot topic in academic research. Viner (1950) is one of the earliest studies of the trade effects of FTAs; he propose that FTAs have a positive effect on trade creation and a negative effect on trade diversion, and describe how these two effects determine the welfare effects of a FTA.

Most of the follow-up literature consists of empirical studies. The gravity equation has long dominated the empirical literature as the main econometric method for estimating FTAs’ ex-post trade effects (Baier, Bergstrand, & Feng, 2014). Using the gravity equation, Carrère (2006) estimation shows that FTAs have a significant effect on trade creation among members; however, this effect varies among FTAs. Vicard (2011) argues that an FTA’s effect on trade between two countries depends on both the economic characteristics of the country pair and the characteristics of all other members of the RTA. Baier and Bergstrand (2007) and Magee (2008) dynamic analyses found that the average trade creation effect of RTAs is close to 50%, and will increase to almost 100% after 10 years. Using gravity equations, Baier et al. (2014) provide the first evidence that both intensive and extensive (goods) margins are affected by RTAs, and Anderson and Yotov (2016) estimate the volume effects of FTAs using panel data gravity method.

Almost all of the above studies are ex-post analyses that examine trade flows after the RTA has been implemented. Ex-ante studies usually use computable general equilibrium (CGE) models to simulate the predicted effects of RTAs. Based on a multi-sector and multi-region dynamic CGE model, Ghosh and Rao (2005) estimate the potential economic impacts of a possible Canada–U.S. customs union in the three NAFTA countries. Siriwardana (2007) assesses the trade-diversion and trade-creation effects of the Australia–US FTA using the Global Trade Analysis Project (GTAP) model. Waschik (2009) simulate the effects of FTAs on non-members. Follow-up studies include Kitwiwattanachai, Nelson, and Reed (2010), Ahmed (2011), Lakatos and Walmsley (2012), Jean, Mulder, and Ramos (2014), Bhattacharyya and Mandal (2016).3

Some scholars have simulated the economic impacts of ChAFTA since China and Australia launched free trade agreement negotiations in 2005. Mai, Adams, Fan, Li, and Zheng (2005) simulate the potential benefits of ChAFTA using a CGE model. The results show that it will sharpen the competitiveness of the Chinese manufacturing sector and raise the welfare of Australian consumers. Zhou, Wu, Hu, and Cui (2006) use the GTAP model to simulate the impact of ChAFTA on China’s agriculture and the simulation results show that the challenges faced by China’s agriculture are greater than the opportunities. Yu, Cheng, and Yang (2010) use the GTAP model to simulate the impact of ChAFTA on dairy production, trade, and consumption in the China and Australia.

The gravity model and the CGE model are two of the main quantitative tools for analyzing the economic impacts of FTAs. Both methods are often criticized, however, for having poor econometric foundations and performing poorly (Anderson & Wincoop, 2003; Hertel, Hummels, Ivanic, & Keeney, 2007). In addition, most of the related literatures analyze trade effects of RTAs using the aggregated data, but the analysis focused on the industry level is relatively rare.

Using a computable partial equilibrium model, we attempt to carry out a comprehensive, ex post evaluation of the impacts of ChAFTA on global coal output, trade, and consumption. At present, China is the world’s largest coal producer, consumer, and importer, and Australia is one of the world’s largest coal exporters. Taking into account the two countries’ important positions in the global coal industry, we can predict that ChAFTA will significantly affect global coal production, trade, and consumption.

The paper makes three main contributions. First, it provides a feasible method to empirically analyze the economic impacts of FTAs at the industry level and from a global perspective. Second, it simulates the impacts of FTAs not only on the trade flows of global coal, but also on the output, price, and producers’ and consumers’ welfare in related countries. Third, to improve the accuracy of simulation results, we estimated supply elasticities, demand elasticities, and substitution elasticities using data from 4-digit HS classification codes.

The paper is organized as follows. Section 2 addresses global coal production and trade. Section 3 introduces the global simulation model (GSIM) and data. Section 4 discusses the main empirical results, and Section 5 concludes and policy implications.

Section snippets

Global coal production and consumption

Although being widely criticized for carbon dioxide emissions, coal has long been a primary source of fuel for most of the world’s population. Global coal consumption reached the equivalent of 3961.4 Mts of oil in 2014, accounting for 30% of global energy consumption. Global coal consumption grew by only 0.4% in 2014, which is well below the 10-year average annual growth of 2.9%. At present, however, coal is still the second-largest source of global energy after oil. Over the years, China has

The GSIM model

To overcome the deficiencies of CGE models, Francois and Hall (1997) developed a partial equilibrium model called the Commercial Policy Analysis System (COMPAS) model, which is based on Armington (1969) hypothesis. However, the COMPAS model can only perform bilateral perspective analysis. Francois and Hall (2003) and Francois (2009) extended the COMPAS model into the global simulation model (GSIM).

The COMPAS and GSIM models are computable partial equilibrium models. Compared to CGE models, the

Impacts of ChAFTA on the global coal industry

The simulation of the GSIM model belongs to a comparative static analysis. Australia had already adopted a zero-tariff policy on coal imports prior to signing ChAFTA, and therefore ChAFTA will only change the tariff that China imposes on coal imported from Australia, from the current 6% to 0.

Conclusions and policy implications

Newly signed by the world’s largest coal importer and the world’s largest coal exporter, ChAFTA is bound to have a huge impact on the global coal industry. We use a computable partial equilibrium model to simulate ex ante ChAFTA’s effects on countries’ trade, output, and welfare at the industry level. Results indicate that ChAFTA has a very strong trade creation effect, but a relatively moderate trade diversion effect. Results also demonstrate that Chinese consumers and Australian coal

Acknowledgments

The research is founded by National Natural Science Foundation of China: “The welfare effects and policy implications of trade facilitation: a study based on the heterogeneous firm trade model”. Grant no. 71473082.

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