文章基本信息

标题：Gravity model and Pakistan - China Trade
本地全文：下载
作者：Alexander Okhotnikov ; Muhammad Imtiaz Subhani ; Shatila Khodor 等
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2021
卷号：258
页码：1-8
DOI：10.1051/e3sconf/202125806036
语种：English
出版社：EDP Sciences
摘要：Pakistan being an important ally of the war against terror paying huge price of not merely of innocent lives of people but huge monetary losses in many sectors of economy, one lucrative sector is international trade. Pakistan’s export potential has undergone strenuous pressures to perform according to the past performance. There was a need to reveal new export potential and lucrative sectors of economy with recommended policy changes so that new paradigm change in international trade can be initiated. This empirical study carried to meet the objective in which gravity model is used for investigating the bilateral trade between Pakistan and China. This model is being used extensively by the researchers worldwide to make predictions about volume of international trade to suggest the policy changes in international trade management. The findings confirm that the tariff rates significantly and negatively affects the Export Volume from Pakistan to China as t-stats > 1.5 which results the trade deficit to be increased, while the affinity (i.e. bilateral visits of people of Pakistan and China to each other countries, bilateral dialogues between China and Pakistan, Social integrations programs between China and Pakistan etc.) between China and Pakistan and Geography (i.e. the trading countries are both in Asia with the connected borders) significantly and positively affects the Export Volume from Pakistan to China as t-stats > 1.5, thus the trade deficit is reduced due to stated affinity and geography. The large value of F-stats also reports that the relationships of export volume from Pakistan to China with all outlined stated explanatory variables/ predictors (i.e. the gravity model for bilateral trade between Pakistan and China) will remain alive for longer period of time in future.