scholarly journals Application of the Gravity Model of International Trade to the Brazilian Case

2021 ◽  
Vol 10 (1) ◽  
pp. 9
Author(s):  
Brecken Eatherton ◽  
Kishore G. Kulkarni
Keyword(s):  
International Trade ◽  
Gravity Model ◽  
Brazilian Case

Free Trade Agreement between Tunisia and the European Union, Do Institutions Matter?: An Empirical Validation by A Gravity Model

2015 ◽  
Vol 5 (2) ◽  
pp. 19-36
Author(s):  
Anis Kacem
Keyword(s):  
European Union ◽  
International Trade ◽  
Gravity Model ◽  
Free Trade ◽  
Spatial Econometrics ◽  
Free Trade Agreement ◽  
Trade Agreement ◽  
The European Union ◽  
Institutional Dimension ◽  
North And South

Tunisia has signed a free trade agreement with the European Union in 1996, which provides for the reduction of tariff barriers between Tunisia and the EU. In this article, we aim to know and test whether the similarity of the institutional framework has to stimulate international trade between Tunisia and the European Union. In this context, we built a variable called “Institutional distance” to valid the institutional dimension of international trade, near borders effects reported in the literature. To this end, a gravity model was used initially (Tunisia and 21 European countries). Secondly, the estimate shows the existence of spatial autocorrelation. The latter has been corrected using spatial econometrics. The results show that the geographical distance remains more important than the institutions in this type of agreement between north and south shores of the Mediterranean.

scholarly journals The Effect of Corruption on International Trade: A Case Study of Indonesian Trade to Nine Countries

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Danang Ibnu Atsir ◽  
Sunaryati Sunaryati
Keyword(s):  
International Trade ◽  
Maximum Likelihood ◽  
Gravity Model ◽  
Bilateral Trade ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Likelihood Method ◽  
Geographical Distance ◽  
Pseudo Maximum Likelihood

Corruption is a form of abuse of ethical authority by public officials, which is divided into two parts: bribery and forced collection. The effect of corruption like bribes and illegal levies is widespread in the public sector. One interesting investigation is the effect of corruption on international trade. Corruption becomes a barrier in international trade, where corruption plays a role in the access of trade goods and services from within and abroad. Using the gravity model, the focus of this research was the effect of corruption on international trade by taking a case study of Indonesia’s bilateral trade with its nine largest export destination countries. Using panel data, analysis tools used in this research were common effect, fixed effect, random effect and poisson pseudo maximum likelihood (PPML). In this research, it was found that geographical distance variable in its fixed units caused the omitted variable so that the error term correlated with independent variables. In order to overcome the problem, poisson pseudo maximum likelihood method was used in performing regression gravity model with linear log form, so the omitted variable issue on the geographical distance can be eliminated. The results of this research concluded that corruption played a role in international trade through bureaucratic mechanisms of trade and investment licensing and the effect of corruption was more detrimental to exporters.Keywords:   Gravity Model, Corruption, International Trade, Poisson Pseudo Maximum Likelihood (PPML).

scholarly journals Estimating China’s Trade with Its Partner Countries within the Belt and Road Initiative Using Neural Network Analysis

2019 ◽  
Vol 11 (5) ◽  
pp. 1449 ◽  
Author(s):  
Koffi Dumor ◽  
Li Yao
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
International Trade ◽  
Network Analysis ◽  
Gravity Model ◽  
Accurate Estimation ◽  
Belt And Road Initiative ◽  
Neural Network Analysis ◽  
Belt And Road ◽  
The Belt And Road

The Belt and Road Initiative (BRI) under the auspices of the Chinese government was created as a regional integration and development model between China and her trade partners. Arguments have been raised as to whether this initiative will be beneficial to participating countries in the long run. We set to examine how to estimate this trade initiative by comparing the relative estimation powers of the traditional gravity model with the neural network analysis using detailed bilateral trade exports data from 1990 to 2017. The results show that neural networks are better than the gravity model approach in learning and clarifying international trade estimation. The neural networks with fixed country effects showed a more accurate estimation compared to a baseline model with country-year fixed effects, as in the OLS estimator and Poisson pseudo-maximum likelihood. On the other hand, the analysis indicated that more than 50% of the 6 participating East African countries in the BRI were able to attain their predicted targets. Kenya achieved an 80% (4 of 5) target. Drawing from the lessons of the BRI and the use of neural network model, it will serve as an important reference point by which other international trade interventions could be measured and compared.

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