Examining Trade Response of Armington-Krugman-Melitz Encompassing Module in a CGE Model
Examining Trade Response of Armington-Krugman-Melitz Encompassing Module in a CGE Model
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发表时间：
2015-07
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通讯作者：
K. Itakura;Kazuhiko Oyamada
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作者：
K. Itakura;Kazuhiko Oyamada
可计算一般均衡（CGE）模型已广泛用于量化自由贸易协定和经济伙伴关系协定的经济影响。就最近的例子而言，根据日本内阁秘书处（2013）的数据，预计跨太平洋伙伴关系协定（TPP）将使日本实际 GDP 增长 0.66%。太平洋经济合作理事会（2012）也估计到2020年TPP对日本实际GDP的影响将提高2.0%。这两个估计都是基于全球CGE模型的模拟结果；前者使用GTAP模型（Hertel，（1997）和McDougall（2003）），后者开发了自己的全局CGE模型（Zhai（2008）和Petri等人（2012））。估计的经济影响差异似乎很大，但这并不奇怪，因为估计的组成部分不同。佩特里等人。 (2012) 考虑了自由化的详尽组成部分；例如取消关税、减少非关税壁垒、开放服务贸易和外国直接投资。另一方面，内阁秘书处（2013）估计了取消关税的影响，从而导致了较低的估计。除了自由化组成部分的差异之外，我们更有趣的是思考他们的全球可计算一般均衡模型中使用的贸易规范的差异。佩特里等人。 （2012）根据 Melitz（2003）基于公司层面的产品差异化定义了他们的贸易模块。 GTAP 模型一直使用基于国家级产品差异的传统 Armington (1969) 规范。因此，我们有兴趣比较全球 CGE 模型中的不同贸易规范及其对贸易自由化经济影响估计的影响。本文按照 Dixon 和 Rimmer (2012) 以及 Oyamada (2013) 的建模策略介绍了 AKME 模块。我们修改了 GTAP 模型（Hertel，1997），这是研究人员广泛用于量化政策影响的全球 CGE 模型。我们重新定义了存储在基准 GTAP 数据库中的贸易流信息，并实施了 Oyamada (2013) 和 Oyamada (2014b) 中建立的校准程序。我们进行贸易自由化模拟，以比较不同的贸易规范，详细分解贸易反应。由于通过检查 AKME 模块来比较贸易影响的尝试屈指可数，因此我们提供了另一个结果以供进一步了解。当我们将贸易规范从标准 GTAP 模型依次转换为阿明顿模型、克鲁格曼模型和梅利茨模型时，自由化对区域贸易的影响就会被放大。通过引入“代理商采购”，我们可以将区域进口的模拟结果分解为代理商的特定需求，这是标准 GTAP 模型所不具备的。此外，通过代理采购，我们可以确定内部制造贸易流量占最大份额。进一步分解表明，在克鲁格曼规范中，密集的保证金贸易效应更为明显，而在梅利茨规范中，广泛的保证金贸易效应则更为显着。这些分解显然丰富了我们对贸易自由化的解释。
Computable General Equilibrium (CGE) models have been widely used for quantifying economic impacts of free trade agreements and economic partnership agreements. For the recent examples, it is estimated that Trans-Pacific Partnership (TPP) will increase Japanese real GDP by 0.66%, according to Cabinet Secretariat (2013) in Japan. Pacific Economic Cooperation Council (2012) also estimated that the impact of TPP on Japanese real GDP would be 2.0% higher by 2020. Both of the estimates are based on simulation results obtained from global CGE model; the former uses the GTAP model (Hertel, (1997), and McDougall (2003)), and the latter develops their own global CGE model (Zhai (2008), and Petri et al. (2012)). The difference in the estimated economic effects seems to be large, however, it is not surprising since the components taken into their estimates are different. Petri et al. (2012) considers exhaustive components of liberalization; such as removing tariffs, reducing non-tariff barriers, liberalizing trade in services and foreign direct investment. On the other hand, Cabinet Secretariat (2013) estimates the impact of removing tariffs, thereby resulted in the lower estimate. Beside the difference in the components of liberalization, it is more interesting for us to ponder the difference in trade specification used in their global CGE model. Petri et al. (2012) define their trade module by following Melitz (2003) based on product differentiation at the firm level. The GTAP model has been using the conventional Armington (1969) specification based on product differentiation at the country level. Thus, we are interested in comparing different trade specifications in global CGE model and its implications for resulting estimates of economic impacts of trade liberalization.This paper introduces the AKME module following the modeling strategy in Dixon and Rimmer (2012) and Oyamada (2013). We modify the GTAP model (Hertel, 1997), which is a global CGE model widely used by researchers for quantifying policy impact. We redefine trade flow information stored in the benchmark GTAP Data Base, and implement a calibration procedure established in Oyamada (2013) and Oyamada (2014b). We run simulation of trade liberalization to draw a comparison between different trade specifications, decomposing the trade response in detail. Since there exits only a handful of attempts to compare the trade effects by examining the AKME module, we provide another results for further insights. Impacts of liberalization on regional trade are amplified as we switch trade specification from the standard GTAP model to Armington, Krugman, and Melitz in turn. By introducing “sourcing-by-agent”, we can decompose the simulation results on regional imports into agent specific demands, which is not available in the standard GTAP model. Also with the sourcing-by-agent, we can identify the intra-manufactured trade flows as the largest share. Further decomposition reveals that intensive margin trade effects are more pronounced in Krugman specification, whereas extensive margin trade effects are significant in Melitz specification. These decompositions clearly enrich our interpretation of trade liberalization.