Disaggregating the Vegetables, Fruits and Nuts Sector to the Tariff Line in the GTAP-HS Framework

IF 2.2 Q2 ECONOMICS
M. Chepeliev, A. Golub, T. Hertel, Wajiha Saeed, Jayson Beckman
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引用次数: 1

Abstract

Computable general equilibrium (CGE) models provide valuable insights into economy-wide and aggregate sectoral impacts of trade policies. However, when it comes to the assessment of specific interventions, the level of aggregation in these models is often deemed too coarse to inform negotiations. For example, in the Global Trade Analysis Project (GTAP) Data Base, all vegetables, fruits and nuts – over hundred individual commodities – are represented under one sector. Analysis at the tariff line level is typically provided by partial equilibrium (PE) models, which cannot, however, capture economy-wide effects. In this paper, we contribute to the development of the GTAP-HS framework, which comprises disaggregated values of output, trade flows and domestic absorption with supporting model components nested within the standard GTAP GE model. We construct the GTAP-HS database with GTAP vegetables, fruits and nuts sector disaggregated into 79 commodities. We apply this modelling framework to the assessment of the ongoing trade frictions between the United States and its trading partners. We find that there are significant advantages to using this nested approach to trade policy analysis, including possibilities of the trade policies assessment at the tariff line, representation of the commodity-specific substitution and avoidance of the ‘false competition’ critique.
在GTAP-HS框架内将蔬菜、水果和坚果分类为关税细目
可计算一般均衡(CGE)模型为贸易政策对整个经济和总体部门的影响提供了有价值的见解。然而,在评估具体干预措施时,这些模型中的汇总水平往往被认为过于粗糙,无法为谈判提供信息。例如,在全球贸易分析项目(GTAP)数据库中,所有蔬菜、水果和坚果——超过100种单一商品——都在一个部门下表示。关税线层面的分析通常由部分均衡(PE)模型提供,但该模型无法捕捉整个经济的影响。在本文中,我们为GTAP-HS框架的开发做出了贡献,该框架包括产出、贸易流和国内吸收的分解值,以及嵌套在标准GTAP-GE模型中的支持模型组件。我们构建了GTAP-HS数据库,将GTAP蔬菜、水果和坚果部门分解为79种商品。我们将这一建模框架应用于评估美国与其贸易伙伴之间正在发生的贸易摩擦。我们发现,使用这种嵌套方法进行贸易政策分析具有显著优势,包括在关税线上进行贸易政策评估的可能性、特定商品替代的代表性以及避免“虚假竞争”批评。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.60
自引率
12.00%
发文量
0
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