Where to Go for the ‘World Supermarket’ – an Analysis of COVID-19 Impact on Zhejiang’s Foreign Trade Based on Stata

By Zhentian XU, Ziying LIU, Yiming WENG, Lizhu WANG

This article is to offer an analysis of the COVID-19 impact on Zhejiang’s foreign trade in 2020 by using Stata regression. It applies difference in differences model to deal with imports and exports data of Zhejiang Province between 2019 and 2020, to explore how Coronavirus factor influence trade volume in Zhejiang. Meanwhile, it talks about two examples in Zhejiang that show surprisingly growing trend, as well as the challenges and opportunities for its further development in the future.

Dedicated to developing international market and trade, Zhejiang Province in China is praised as the “World Supermarket” for its remarkable performance of foreign trade in recent years, accounting for the largest share of export growth in 2019 in China. However, since the global outbreak of COVID-19 in 2020,the amount of foreign trade decreases fearfully , which poses a threat to the foreign trade in Zhejiang. Despite this, opportunities still exist.


The data used in the paper covers that of Nov-Dec 2018, Nov-Dec 2019, Jan-Mar 2019 and Jan-Mar 2020, collected from Zhejiang official statistical database. Data 1 shows the impact brought by COVID-19 in China and data 2 presents the impact of the control of COVID-19.



We choose difference in differences model to test the impact of COVID-19 situation on foreign trade in Zhejiang since it can better solve the problem of intervention effect evaluation.

We use ie (total import and export volume) as the measure of foreign trade, and three dummy variables as explanatory variables: covid (whether an COVID-19 situation occurred), janfeb/mar (measuring time trends), janfeb covid/mar covid (=covid*janfeb/mar).

When using Stata to deal with data, we find that the constant term of regression result is very significant, but the parameter term is not, and the R-squared is very small, indicating that variables in the model are not enough to explain the change of ie . By observing the data, we find that ie of each city in Zhejiang has large differences, and they generally locate in various areas, like costal, estuary or hilly areas.

Thus, we suppose that the model may ignore the unique individual effects (unobserved heterogeneity) of each city, so the model cannot account for the errors in the regression. In this case, we want to control individual fixed effects and choose the areg command among many methods, as the areg command is interpreted as linear regression with a large dummy-variable set. All variables in our model are dummy variables, and areg seems to be more applicable.


Model 1(impact of domestic COVID-19 situation on foreign trade in Zhejiang):

ie = 455.15 + 76.02covid – 40.37janfeb – 125.83janfebcovid + ei

From the model 1, R-squared is 0.98, which indicates that the model is enough to explain the impact of domestic epidemic on Zhejiang’s foreign trade. The P >| t| of covid is 0.017, with 95% confidence interval indicating significant difference, indicating that under the same conditions of other factors, ie of intervention group is 7.602 billion yuan more than that of control group; the P >| t| of janfeb is 0.189, indicating that the time trend is not significant; the P >| t| of janfebcovid is 0.006, which shows that under the same conditions of other factors, affected by the domestic epidemic situation, ie of each city in Zhejiang fell by 12.583 billion yuan from January to February.

Model 2(impact of the control of COVID-19 situation on foreign trade in Zhejiang):

ie = 207.39 – 24.90covid – 18.93mar + 44.14marcovid + ei

From model 2, R-squared is 0.99, which indicates that the model is enough to explain the impact. The P >| t| of covid is 0.032, indicating that ie of intervention group is 2.490 billion yuan less than that of control group under the same conditions of other factors; the P >| t| of mar is 0.098, with 90% confidence interval indicating significant difference, showing that under the same conditions of other factors, compared to the mean ie of January and February, March’s ie decreases by 1.893 billion yuan; the P >| t| of marcovid is 0.009, indicating that under the same other factors, ie in Zhejiang increases by 4.414 billion yuan in March due to the gradual control of epidemic situation.


From the data, we find Zhoushan so special, as its ie has risen significantly. After the analysis, we find some causes. Firstly, Zhoushan is an island city, enabling it to be less influenced by COVID-19. Secondly, benefited from the plunge of international oil price, ie of its petrochemical industry is three times that of last year. Thirdly, During the epidemic, Zhoushan’s logistics of major international routes operated stably.


Despite the negative impact of the epidemic, in the first quarter, the exports of high-tech products increased by 2.1%, which shows an opportunity for Zhejiang to optimize its structure of foreign trade. The reason behind this miracle is that, in recent years, many manufacturing companies in Zhejiang have paid more attention to R&D investment, causing Zhejiang’s manufacturing shift to both ends of the “smile curve”. The epidemic has had a negative impact on foreign trade in the short term, but it may also eliminate some export products with low technology and low competitiveness, making more capital flow into the high-tech industry.

At the same time, due to the global spread of COVID-19, In March, the province’s exports of medical products increased by 24.4%. It is estimated that the export of anti-epidemic materials will continue to grow rapidly.


In a nutshell, although the epidemic has brought adverse effects on Zhejiang ’s foreign trade, many opportunities also emerge. The plunge in oil prices has promoted investment in petrochemicals, and oil processing trade may become the main driving force of Zhoushan’s trade growth. Meanwhile, Zhejiang’s trade of high-tech products and anti-epidemic materials products increased against the trend, which means they are likely to become an opportunity of Zhejiang’s foreign trade.


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  2. Gov, Zhejiang. Data Zhejiang GOV. Retrieved from http://data.tjj.zj.gov.cn/page/systemmanager/admin/homePage.jsp?orgCode=33
  3. How is the positive economic growth in the first quarter (2020, April 30). Retrieved from https://baijiahao.baidu.com/s?id=1665352421718012644&wfr=spider&for=pc&isFailFlag=1
  4. LU, J. (2020, January 17). Zhejiang’s imports and exports broke through the first three trillion, and the export growth contribution rate ranked first in the country in 2019. Retrieved from https://baijiahao.baidu.com/s?id=1655962395714430542&wfr=spider&for=pc
  5. Zhejiang: Opening up a new pattern brings foreign trade against the trend. (2019, December 30). Retrieved from http://www.xinhuanet.com//mrdx/2020-01/23/c_138729387.htm
  6. Zhoushan fights against the new trend of growth in the first quarter. (2020, April 27). Retrieved from https://m.sohu.com/a/391540358_120045022

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