Trade opening has become an important asset for economic development in many countries and an important engine of economic globalization (Wang, Shan-Li, et al, 2020). With continuous foster on the regional economic cooperation, countries with close proximity further promote the mobility and development of infrastructures and policies. Nevertheless, testing a trade integration model of bilateral trade is not sufficiently well estimated with the Bayesian approach to provide practical evidence of trade integration. Moreover, in identifying the factors determining trade integration, testing using the Bayesian gravity equation is essential. After performing a series of simulation experiments, a relationship between bilateral trade volume and simulated trade determinants was predicted for the trade model. The results of the estimated coefficients on GDP in Thailand and GDP of Yunnan province, China are positively significant predictors of the trade growth. The distance between the countries has a negatively significant estimation that implies barriers in trade. The model predicts trade integration, especially towards the trade on route R3A. The Bayesian approach of the gravity model gives robust estimates for determining the impact factor for the bilateral trade, including the fact that the elasticities of total trade volume with respect to distance, population, and the exchange rate of Thailand are negative while the GDP per capita are positively significant. Further, economic size, GDP per capita, and exchange rate of the destination, and population and area of Yunnan province are positively predicted by the model. The estimated parameters are directly the elasticities, in which increases in GDP is consistent with the higher trade volumes. Further, evidence of the gravity equation is used for understanding trade potential, and after some integrations, the estimation is applied for the real trade. The measures of bilateral trade resistance or costs associated with the trade flow has influenced the expanding of the bilateral trade in the model in the GMS economies. Finally, trade integration can be implemented with evidence and estimates of the gravity model. The Bayesian experiment for the estimation of the impacts of the trade integration on route R3A predicts an increase of GDP, population, exchange rate, and GDP per capita as predominant predictors in the Bayesian gravity model. Thus, the results revealed that economic size, bilateral distance, and GDP per capita has affected the plausible trade agreements for trade integration on route R3A.
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