scholarly journals The ever-evolving trade pattern: a global VAR approach

Author(s):  
Razieh Zahedi ◽  
Asghar Shahmoradi ◽  
Ali Taiebnia
Keyword(s):  
2020 ◽  
Vol 71 (1) ◽  
pp. 1-14
Author(s):  
Sugata Marjit ◽  
Reza Oladi ◽  
Punarjit Roychowdhury

AbstractMotivated by recent insights from behavioral economics and social psychology, we present a theory of trade that seeks to explain inter-industry trade between countries that are similar in their production sides, but differ in their income distribution. By assuming status-dependent preferences that are non-homothetic, we show that income inequality differential can be a basis for inter-industry trade between otherwise similar economies.


Author(s):  
Ke Zhang ◽  
Xingwei Wang

With the development of trade liberalization, the pollutants emissions embodied in global trade are increasing. The pollution haven hypothesis caused by trade has aroused wide attention. The fragmentation of international production has reshaped trade patterns. The proportion of intermediate product trade in global trade is increasing. However, little has been done to study the pollution haven of different pollutants under different trade patterns. In this paper, major environmental pollutants CO2 (carbon dioxide), SO2 (sulfur dioxide), and NOx (nitrogen oxides) are selected as the research objects. This study investigated the global pollution haven phenomenon in 43 countries and 56 major industries from 2000 to 2014. Based on the MRIO model, the trade mode is divided into three specific patterns: final product trade, intermediate product trade in the last stage of production, and the trade related to the global value chain. The results show that trade liberalization could reduce global CO2, SO2, and NOx emissions, and intermediate product trade has a more significant emission reduction effect than final product trade. Trade’s impacts on each country are various, and the main drivers are also different. For example, the European Union avoids becoming a pollution haven mainly through the trade related to the global value chain. The suppressed emissions under this trade pattern are 71.8 Mt CO2, 2.2 Mt SO2, 2.2 Mt NOx. India avoids most pollutants emissions through intermediate product trade. China has become the most serious pollution haven through final product trade. The trade pattern could increase China 829.4 Mt CO2, 4.5 Mt SO2, 2.6 Mt NOx emissions in 2014.


2010 ◽  
Vol 42 (4) ◽  
pp. 643-658 ◽  
Author(s):  
Yang Wan ◽  
Changyou Sun ◽  
Donald L. Grebner

The market of wooden beds in the U.S. has been flooded with imports from China and Vietnam in recent years. Static and dynamic Almost Ideal Demand System models are used to assess the import demand for wooden beds from the top seven supplying countries. The analyses reveal that the antidumping investigation on China has some temporary trade depression effect on China, but trade diversion occurs to Vietnam, Indonesia, Canada, and Brazil. The formal implementation of antidumping duties since 2005 has not shown any significant effect on the trade pattern. U.S. consumers spend more on beds from newly industrialized countries and there are moderate degrees of substitution among wooden beds from most countries.


2018 ◽  
pp. 307-327 ◽  
Author(s):  
Sophannak Chorn ◽  
Savuth Cheng ◽  
Yuthnea Ngoy
Keyword(s):  

2019 ◽  
Vol 2019 (256) ◽  
Author(s):  
Mauricio Vargas ◽  
Daniela Hess

Using data from 1980-2017, this paper estimates a Global VAR (GVAR) model taylored for the Caribbean region which includes its major trading partners, representing altogether around 60 percent of the global economy. We provide stilyzed facts of the main interrelations between the Caribbean region and the rest of the world, and then we quantify the impact of external shocks on Caribbean countries through the application of two case studies: i) a change in the international price of oil, and ii) an increase in the U.S. GDP. We confirmed that Caribbean countries are highly exposed to external factors, and that a fall in oil prices and an increase in the U.S. GDP have a positive and large impact on most of them after controlling for financial variables, exchange rate fluctuations and overall price changes. The results from the model help to disentangle effects from various channels that interact at the same time, such as flows of tourists, trade of goods, and changes in economic conditions in the largest economies of the globe.


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