Document Type : مقالات پژوهشی

Authors

1 Ph.D of Economics and Associate Prof., Institute for Trade Studies and Research (ITSR), Tehran, Iran

2 Ph.D Student at Tarbiat Modares University and Researcher at Institute for Trade Studies and Research (ITSR)

Abstract

1- Introduction
An overview of the main suppliers of important imported goods in the CIS group shows that Iran is one of the main producers of ceramic products and glass products in the growing market of this region due to its comparative advantage and Iranian companies have a large capacity to meet the needs of CIS countries. In this regard, the present article analyzes the factors affecting the trade of ceramic products and glass products by HS codes as described in HS68, HS69 and HS70 in CIS trade partners (which includes the Republic of Azerbaijan, Armenia, Russia, Kyrgyzstan and Kazakhstan). The data covers the 2009-2019 period, and a panel data model is estimated by using methods of ordinary least squares, fixed effects and random effects.
2- Theoretical Framework
After the end of World War II, international trade grew faster, so that in recent years the world trade has grown largely faster than world production. Meanwhile, the share of developed countries in trade has been growing more than the total trade. Analysis of trade flows between countries showed that the exports with an emphasis on industrial goods is increasing in all countries. As trade growth increased, various models were introduced to explain business flows, the most practical of which was the Gravity model, which is widely used in international trade to explain business flows, to determine business potential, and to examine the effects of integration on Bilateral trade, etc. The gravity model is a simple model for analyzing bilateral business flows between geographic entities. In the 1980s, gravity models showed that economic growth, productivity, human capital, and economic freedom were among the factors influencing trade. They also showed that trade is affected by factors such as conditions in the origin country, economic scale, differences in the stock of factors of production or technology.
3- Methodology
The general form of the gravity model is:
Where Tijt is the trade volume of ceramic products and glass products from country i  to country j, yit is the GDP of the exporting country, Yjt is the GDP of the importer country, Zijt denotes variables affecting the flow of trade such as distance between countries (in kilometers), trade imbalances, etc., uijt is a random disturbance term iid (normally and independently distributed). In order to facilitate the estimation, the above model was linearized as follows. represent elasticities. The logarithmic form of the formulated gravity model is:



 



where Tijt is the trade volume of ceramic products and glass products of country i to country j. yit is the GDP of the exporter country. This variable represents the size of the economy of the exporting countries. yjt is the GDP of the importer country. This variable represents  the size of the economy of the importer country. is the degree of trade imbalance between the exporting country and the importing countries:
Where () export (import) of country i to (from) country j at time t.  is the distance between the exporter country and the importer country and  represents the random disturbance term iid (normally and independently distributed ).
4- Results & Discussion
The model is estimated by conventional least squares method, fixed effects and random effects by commodity groups HS68 (ceramic products, glassware and glass products), HS69 (ceramic products) and HS70 (glassware and glass products), for CIS countries, by using STATA14 software. the estimation results are presented in the following three tables.
 
Table1. Results of gravity model estimation for HS68 group by different panel methods




variable


Method


 


 


 


 


 


 


 




 


OLS


 


 


FE


 


 


RE


 




 


Coef.


SE


Coef.


SE


Coef.


SE



 

1.58


0.33


 


1.33


0.33


 


1.94


0.34



 

1.45


0.34


 


1.23


0.33


 


1.94


0.26



 

0.06-


0.04


 


0.02-


0.04


 


0.03-


0.03



 

0.17-


0.04


 


0.16-


0.04


 


0.16-


0.04




Constant


0.07-


0.04


 


0.05


0.03


 


0.02-


0.03




 
Table2. Results of gravity model estimation for HS69 group by different panel methods




variable


Method


 


 


 


 


 


 


 




 


OLS


 


 


FE


 


 


RE


 




 


Coef.


SE


Coef.


SE


Coef.


SE



 

0.53


0.09


 


0.55


0.13


 


0.56


0.12



 

1.23


0.33


 


1.32


0.24


 


1.44


0.26



 

-0.16


0.04


 


-0.24


0.04


 


-0.21


0.04



 

-0.23


0.04


 


-0.24


0.06


 


-0.23


0.06




Constant


-0.03


0.03


 


0.03


0.03


 


-0.04


0.04




 
Table3. Results of gravity model estimation for HS70 group by different panel methods




variable


Method


 


 


 


 


 


 


 




 


OLS


 


 


FE


 


 


RE


 




 


Coef.


SE


Coef.


SE


Coef.


SE



 

0.56


0.22


 


0.62


0.25


 


0.62


0.52



 

1.22


0.16


 


1.14


0.33


 


1.31


0.32



 

-0.12


0.04


 


-0.15


0.04


 


-0.22


0.04



 

-0.02


0.04


 


-0.16


0.04


 


-0.04


0.04




Constant


-0.07


0.03


 


0.05


0.03


 


-0.04


0.03




5- Conclusions & Suggestions
To estimate the value of trade between countries, a differential gravity model of bilateral trade flows was formulated and estimated with panel data from 2009 to 2019 for each of the commodity groups HS68 (ceramic products, glass and glass products), HS69 (ceramic products) as well as HS70 (glass and glass products). The parameters were estimated with a large database by using ordinary least squares, fixed-effects and random-effects methods. For the three commodity groups, the results were stable across methods. For HS68, exports were elastic with respect to the gross domestic product (GDP) of exporters and importers GDP. For HS69, exports were inelastic with respect to the exporters GDP and elastic with respect to importers GDP. Exports of HS70 were inelastic with the exporters GDP and elastic with respect to the importers. Results show that geographical distance and trade imbalance is negative and significant; trade increases if the transportation costs decrease. We also introduce the economic dimension and income per-capita; these proxies confirm the positive effects in bilateral trade.

Keywords

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