amirreza soori; mehdi mohrami
Abstract
1- IntroductionAn 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 ...
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1- IntroductionAn 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 FrameworkAfter 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- MethodologyThe 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 & DiscussionThe 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 methodsvariableMethod OLS FE RE Coef.SECoef.SECoef.SE 1.580.33 1.330.33 1.940.34 1.450.34 1.230.33 1.940.26 0.06-0.04 0.02-0.04 0.03-0.03 0.17-0.04 0.16-0.04 0.16-0.04Constant0.07-0.04 0.050.03 0.02-0.03 Table2. Results of gravity model estimation for HS69 group by different panel methodsvariableMethod OLS FE RE Coef.SECoef.SECoef.SE 0.530.09 0.550.13 0.560.12 1.230.33 1.320.24 1.440.26 -0.160.04 -0.240.04 -0.210.04 -0.230.04 -0.240.06 -0.230.06Constant-0.030.03 0.030.03 -0.040.04 Table3. Results of gravity model estimation for HS70 group by different panel methodsvariableMethod OLS FE RE Coef.SECoef.SECoef.SE 0.560.22 0.620.25 0.620.52 1.220.16 1.140.33 1.310.32 -0.120.04 -0.150.04 -0.220.04 -0.020.04 -0.160.04 -0.040.04Constant-0.070.03 0.050.03 -0.040.035- Conclusions & SuggestionsTo 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.
amirreza souri
Abstract
Since the end of the Second World War, international trade has grown faster than the world production in nearly a year. In this period, trade among the developed nations has increased much faster than trade in general accounting for an increasing proportion of total trade. Balassa (1966) and Grubel (1967, ...
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Since the end of the Second World War, international trade has grown faster than the world production in nearly a year. In this period, trade among the developed nations has increased much faster than trade in general accounting for an increasing proportion of total trade. Balassa (1966) and Grubel (1967, 1970) demonstrated the importance of simultaneous increase by all countries regarding their exports of most industries. The pioneering studies of the gravity model were realized by Tinbergen (1962) and Pöyhönen (1963). The gravity model is analogous to Newton's law of gravity, where the state gravity between two objects is directly related to each other and inversely related to distance. Anderson's (1979) and Deardorff (1998) have considered that the gravitational equation helps explain the pattern of international trade.
In the 1980’s, Romer (1986, 1990), and Lucas (1988) studied the endogenous growth models. Endogenous growth theories identify a number of channels that affects growth, such as productivity, human capital, and openness. Most of the studies show that trade and economic growth are positively correlated.
When economic geography was born in 1990’s some authors as in Krugman (1993) explained the relationship between North and South considering the mobility between the countries. This process involves trade flows, migration, and direct foreign investment.
In last years, a number of gravity models have been applied to explain the bilateral trade flows (Egger 2002; Serlenga & Shin 2007; Faustino & Leitão, 2008).
The objective of this paper is to examine the pattern of Iran trade by adopting an argument gravity model. The manuscript uses a panel data approach. This study analyses the link between gravity model and Iran trade. The manuscript considers the determinants of Iran and and D8 countries within the years of 2006 to 2015. This study uses country-specific characteristics (per capita income, market size, geographical distance, and factor endowments).The structure of the paper is a follows.
This model is analogous to Newton’s law of gravity, which states that the gravity between two objects is directly related to their masses and inversely related to their distance.
Where Fij denotes the flow from country i to country j. Yi and Yj are the economic sizes of the two countries, usually measured as the gross domestic product (GDP), or per-capita GDP. Dij is the distance between the countries. G is a gravitational constant.
In order to facilitate the econometric estimations, we apply logs the gravity equation (1), hence, we obtain a linear relationship as follows:
Where lnG corresponds to the intercept, while , and are elasticity’s.
According to the gravity approach, the trade between the two countries is directly related to their incomes (or per-capita incomes) and inversely related to the distance between them.
Since the pioneering studies of Tinbergen (1962), Pöyhönen (1963), Anderson (1979), Pagoulatos and Sorensen (1975), Caves (1981), Toh (1982), Krugman, (1997), and Badinger and Breuss (2008) the geographic distance has been an important determinant of trade. The distance can be analyzed in terms of geography, culture, language, and adjacency (Border). Rauch (1999) and Eichengree and Irwin (1998) emphasize the importance of border and common language.
Anderson (1979) introduced the product differentiation by country of origin assumption. A few years later Bergstrand (1985), Egger (2002) and Grossman and Helpman (2005) used the income per capita to specify the supply side of economies.
Usually geographic distance measures the cost of transport. According to the literature there is an increase in the flow of trade if the transportation costs decrease. The theoretical predictions show a negative correlation between distance and the trade. Balassa (1966), Balassa and Bauwens (1987), Stone and Lee (1995), Clark and Stanley (2003), and Badinger and Breuss (2008) found a negative sign between geographical distance and trade.
The empirical model uses the dummy variables to the cultural distance, language, and to the border.
The similarities of the countries encourage bilateral trade. Frankel et al. (1998) and Papazolou et al. (2006) demonstrate the importance of these qualitative variables to analyze the regional trading agreements (RTAs).
Balassa (1966) and Balassa and Bauwens (1987) found a positive sign. The empirical studies show that gravity models utilize gravitational factors as in volume of trade, capital follows, and migration (Baltagi et al., 2003; Faustino & Leitão, 2008; Kabir & Salin, 2010; Leitão & Faustino, 2009, 2010; Serlenga & Shin, 2007; Skabic & Orlic, 2007; White, 2009).
Where is bilateral trade (exports plus imports), is a set of explanatory variables.
All variables are in the logarithm form; is the unobserved time-invariant specific effects; captures a common deterministic trend; e is a random disturbance assumed to be normal, and identical distributed (IID) with .
The combined data used within the period of 2006 to 2015 for each of the commodity groups HS28 (inorganic chemical products), HS29 (organic chemical products), and HS38 (various products of the chemical industry) with a large database and in a minimum method ordinary squares, fixed effects, and random effects are estimated. The results of the study showed that the explanatory power of the model was high for all the three groups of products and the volume of trade of the HS28 commodity group with regard to the GDP of the exporters and the GDP of the importers,.Meanwhile, the size, economic dimensions, and the per capita income have significant direct effects. Trade imbalance and distance have a significant but inverse effect on the business flow of the countries under study.
Amir Reza Soori
Abstract
Abstract
In this paper, we analyze the determinants of Intra-Industry trade (IIT) in the Agriculture, Industry and service sectors between Iran and her trading partners, i.e. European Union, ECO, GCC, D8, OIC and ASEAN countries using dynamic panel data and GMM during 1980-2009.
This study uses country-specific ...
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Abstract
In this paper, we analyze the determinants of Intra-Industry trade (IIT) in the Agriculture, Industry and service sectors between Iran and her trading partners, i.e. European Union, ECO, GCC, D8, OIC and ASEAN countries using dynamic panel data and GMM during 1980-2009.
This study uses country-specific characteristics such as economic size, per capita income, foreign direct investment, geographical distance, and trade imbalance as explanatory variables. The results indicate that economic size, per capita income, and geographical distance explain most of IIT between Iran and her trading partners. According to econometric findings, the economic size has high and positive correlation with IIT, however per capita income affects negatively IIT. Thus, differences in aggregate demand and supply should be considered in selecting trade partners. The similarity in income structure leads to same demand structure and expansion of trade volume. In addition, geographical distance and trade imbalance has negative effect on IIT flow in Iran.
Keywords: Intra-industry Trade, Regional blocs, Dynamic, panel data, Economic scale, GMM
JEL Classification:C20 , F12.
