ECONOMETRICS ANALYSIS OF THE IMPACT OF COVID 19 (SARS cov 2) ON INTERNATIONAL e COMMERCE

In addition, confirmed death cases are also cases in which the patients are already dead when testing reveals the residuals or presence of COVID-19 virus.[Table A.1 Appendix2] 3.2.2 Stoc

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FOREIGN TRADE UNIVERSITY Faculty of International Business

-*** -SCIENTIFIC RESEARCH

“ECONOMETRICS ANALYSIS OF THE IMPACT OF

COVID-19 (SARS-CoV-2) ON INTERNATIONAL

E-COMMERCE”

SUPERVISOR: Lê Hồng Mỹ Hạnh

Submitted by: Group 2

1912255432 - Lê Minh Tâm

1912255433 - Nguyễn Quốc Thái

1912255437 - Nguyễn Trí Thông

1912212195 - Trần Minh Khải

1912215304 - Nguyễn Phúc Xuân Ngân

Ho Chi Minh City May 20 th , 2021

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ABSTRACT VIEW

We investigate the effects of the Corona virus worldwide, specifically the number of cases and deaths, on 5 E-commerce businesses (Amazon, Alibaba, Jingdong, Ebay and Rakuten) in terms of stock values and interest over time The results show that there is a positive relationship between the pandemic (cases and deaths) and the performance of E-commerce businesses In detail, stock values rise considerably and interest over time also increases compared to pre-COVID times.

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Table of Contents

1 Introduction 4

2 Literature review 5

2.1 Previous studies 5

2.2 Overall effect of COVID-19 6

3 Methodology and Data 7

3.1 Descriptive statistics 7

3.2 Data description 8

3.3 Hypotheses 10

3.4 Method of research 11

3.5 Model 11

4 Result 12

4.1 Pearson correlation coefficients 12

4.2 OLS model results and problems with the model 12

4.3 Correction and final result 13

4.4 Limitations 15

5 Conclusion and Recommendation 16

5.1 Conclusion 16

5.2 Recommendation 17

APPENDIX 1 REFERENCES 19

APPENDIX 2 TABLES AND FIGURES 20

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1 Introduction

The E-commerce business has been gaining considerable growth since the appearance of world-changing innovations like the Internet, World Wide Web and more recently and also having a deep influence in our life - smartphones Stepping into the age of technology, traditional methods of commercials are getting outdated and proving to be inefficient Due to its reliance on physical interaction, the reach is, most of the time, limited to a particular geographical area Meanwhile, E-commerce is computed digitally and online, therefore broadening its reach to potentially everyone and everywhere around the globe In short, it is commonly recognized that E-commerce has integrated itself as an inseparable part of the world’s development However, there has been another major event that has changed the world we live in since 2020 - COVID-19 It is a global consensus that during the pandemic, almost every aspect of our personal life and every field of jobs are negatively affected to a certain extent Noticeably, the decrease in revenue, adjustment in the workforce and job market, disrupted supply chain have all taken a big toll on numerous companies worldwide.

Therefore, many people have been speculating whether there is any relationship between one of the most important businesses in our society (E- commerce) and the current COVID-19 pandemic More specifically, we will be looking into the number of COVID-19 cases and deaths everyday in the year

2020 to determine their effects on the 5 biggest E-commerce businesses right now - Amazon, Alibaba, Jingdong, Ebay and Rakuten For the companies, we will

be looking into their stock prices and interest over time of each company.

Understanding the effects of COVID-19 on these companies’ performance will be

important because of two reasons Firstly, it will provide us with a better idea of

whether E-commerce businesses are affected negatively or positively by the pandemic.

Secondly, it will help us predict necessary actions to take in the future in order to

minimize the threats (if any) and maximize the potential For instance, the increase in

the number of cases and deaths has made the stock price of these firms rise or fall? If

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we find that there is a positive effect in these companies' financial indicators, we may conclude that the pandemic does not negatively affect these companies but rather supports its business And if the previous statement is true, what further action steps can we take to be more successful and adapt with the new normal in the future when the pandemic still continues.

This paper’s analysis is based on the methodology presented in the research paper

published by MBA Nguyễn Hoàng Nam (2021)[1] In this paper, he managed to quantify

the effect of COVID-19 on Vietnam’s economic activities by constructing six hypotheses Moreover, we are also inspired by the publication of Hung-Hao Chang and Chad

Meyerhoefer (2020)[2], in which they utilized Ubox, the largest business-to-consumer

agri-food E-commerce platform in Taiwan, as dependent variables to measure the of COVID-19 on the demand and growth of online food platforms.

2 Literature review

2.1 Previous studies

According to the study of United Nations Publications [3], the widespread

pandemic caused a sharp deceleration in financial activities for which businesses were generally ill-equipped However, a noticeable effect of the raging pandemic has been the transition of multiple firms to E-commerce stemming from the requirement for necessity of moving online This report makes a preparatory appraisal of the effect of the COVID-19 emergency on E-commerce It incorporates overviews of E-commerce businesses and customers and its accomplices within the eTrade for all activity, examinations by other multilateral offices, and inquiries embraced by the United Nation Organization.

In addition, the study of Luis Varona and Jorge R Gonzales (2021) [4] analyzed

the short-term behavioral dynamics of economic activity, as well as explained the causal relationships in the COVID-19 pandemic context is based on the baseline amount of COVID-19 transmission per day Research data was collected with economic variables, including: economic activity index, public expenditure index, real interest rate index, exchange rate index, international dong price index, index stock

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price numbers of the Lima Stock Exchange, The study uses the ARDL model to measure the impact of COVID-19 on the economy of Peru The research results show that there is a negative effect with the expected sign, the statistical significance

is 1 Moreover, Akbulaev et al.'s study (2020) [5] focuses on the economic impact of

COVID-19 The study assessed the impact of COVID-19 on the economy in many aspects, from the impact on production, employment, import and export, to the analysis of the State's support for producers in the mandatory quarantine.

Last but not least, the study by Prince Asare Vitenu-Sackey and Richard Bar

(2021) [6] aimed to assess the impact of the pandemic on poverty reduction and

global GDP by measuring at the heterogeneous effects of each country Data utilized was collected from 170 countries, using econometric panel techniques such as OLS and squared regression to determine the result Variables included

in the study were total COVID-19 cases, total confirmed deaths, rigor index, human development index, and gross domestic product per capita The study's findings indicate that the severity of many people's conditions and the rise of the disease have negatively impacted poverty alleviation and economic growth However, the deaths recorded to date positively affect both poverty reduction and economic growth This development signals the nature of controlling population growth as it hinders economic growth and poverty alleviation.

2.2 Overall effect of COVID-19

The COVID-19 pandemic has devastated the global economy, leaving many people around the world in dire straits COVID-19 has created some uncertainty regarding economic and social policies From a business perspective, the epidemic has had a negative impact on the finance and various other industries Currently, the potential impact of COVID-19 on globalization and global health in terms of mobility, trade, travel and the most affected countries is absolutely volatile, which is terrifying The world economic order and activities are changing drastically as most countries are going through a period of stay-at-home isolation, social distancing and even nationwide shutdown.

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Amid the year 2020, the COVID-19 pandemic has overwhelmed the world financial advance Development confinements has hindered financial activities in most regions and countries However, COVID-19 has had varied effects on different regions and countries depending on the time, concentration of the infected cases and the nation’s own financial status Developing countries and least developing countries, as well as their population, are more prone to worldwide financial downturns and recessions than ever On the other hand, a few nations, especially those within the Asia-Pacific locale, have experienced moderate contamination rates

in later months of the pandemic, permitting for a speedier return to pre-pandemic levels of financial movement than others, especially those in Europe and the Americas, which were anticipated to encounter many more waves of COVID-19 cases by late 2020 Nevertheless, as stated above, with no absolute evidences nor any solid patterns of the future development of the virus, virologists and economists could only guess what will happen in the future.

3 Methodology and Data

3.1 Descriptive statistics

The variables utilized in this research paper are as follow in this table,

with the source and time frame included:

Variable Description

amzn The stock price of Amazon

jd The stock price of Jingdong

rkuny The stock price of Rakuten

amznint Amazon’s Interest over time

babaint Alibaba’s Interest over time

jdint Jingdong’s Interest over time

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Expecte

d sign

-study their effects

We use data from several sources to conduct our analysis, including

information about coronavirus cases and death cases worldwide, stock prices of

E-commerce companies, and interest over time of those.

3.2.1 Coronavirus cases/deaths

From a reliable source of information about COVID-19 on Worldometer.com, we

obtain the number of confirmed and death cases over the year of 2020 Confirmed

cases were validated by the COVID-19 test which is different from suspected cases

in which patients only have the early symptoms of COVID-19 Death cases are

confirmed immediately after the COVID-19 patients deceased In addition, confirmed

death cases are also cases in which the patients are already dead when testing

reveals the residuals or presence of COVID-19 virus.[Table A.1 (Appendix2)]

3.2.2 Stock prices

Stock price provides one measure of the efficiency of that company operating during

the 19 It also has daily data, which, along with cases and deaths of

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19, assists us in constructing the panel data set on a daily level Thus we chose

to study the effect of COVID-19 on E-commerce companies’ stock prices collected from the Nasdaq Stock market.

In the publication of Hung-Hao Chang and Chad Meyerhoefer (2020) [2], they

utilized the financial statistics Ubox, the largest business-to-consumer agri-food E-commerce platform in Taiwan, as dependent variables to measure the of

COVID-19 on the demand and growth of online food platforms With their

resourceful database, they successfully constructed an extensive and detailed

panel data set to efficiently estimate the effect the pandemic has caused on

Ubox’s statistics and to draw conclusion about its impact on the industry.

As this method proves to be an interesting and efficient way to achieve the desirable results, after referencing various reports and articles, we selected five companies that are consensually deemed as the top ranking ones of the E- commerce industry around the globe as the basis to statistically demonstrate the effect of COVID-19 These companies are, ranked respectively in order of higher

to lower: Amazon, Alibaba, Jingdong, Ebay and Rakuten They will work as the representatives of the industry of E-commerce as a whole for this research; thus, the impact of COVID-19 on them will then be concluded as the effect to the industry itself The data will be collected from 01/11/2019 to 31/12/2020, as we wish to include the growth of the stock price during the pre-COVID period of time into account for a more precise calculation (*)1.[Table A.2 (Appendix 2)]

3.2.2 Interest over time

When diseases break out in many countries, social distancing is mandatory in many countries People have to stay at home and thus have difficulty with shopping in stores and markets which have a high rate of coronavirus affection As a result, people turned to shopping online through many different E-commerce platforms We have researched the data for selected companies’ volume of searches on the search engine of Google,

1 (*) Because the Nasdaq stock market do not open on Saturdays and Sundays, the timeline will have missing values

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as it is the most popular engine, from November 2019 to April 2021 Utilizing the extension Google trend, which is specified in measuring the Internet users’

interest in a topic or a search term in a period of time, we obtained the interest

The fact that companies have a high interest over time percentage means they are increasing in popularity in that time range, which in turn means they are becoming more favorable in purchasing Consequently, we believe it would be a factor affecting the firms’ stock prices [Table A.3 (Appendix 2)]

3.3 Hypotheses

Conducting this research, we based our analysis off the methodology presented in

the research paper published by MBA Nguyễn Hoàng Nam (2021) [1] In this

publication, he constructed six hypotheses in order to measure the impact of

COVID-19 on Vietnam’s economic activities These hypotheses are as follow

Utilizing his model, he successfully managed to numerically quantify the effect COVID-19 has on the growth of these financial indicators, thus proving that COVID-19 has an influence on Vietnam’s economic activities’ development Inspired by Mr.Nam's methodology and models, we established our own hypotheses in order to measure the impact of COVID-19 on the state of the worldwide E-commerce industry These hypotheses, which would serve as the foundation for our final claim and results in this paper, are:

2 (**) Interest over time: Numbers represent search interest relative to the highest point on the chart for the given region and time A value of 100 is the peak popularity for the term A value of 50 means that the term is half as popular A score of 0 means there was not enough data for this term (Source: Google Trend)

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3.4 Method of research

This research employed the method of Ordinary Least Square (OLS) Estimation to measure the correlation of the selected E-commerce companies' stock price, as the indicators of their business status, with other two factors: cases or deaths of COVID-

19 and the company's interest over time According to the OLS estimation method,

we would check the p_value of the explanatory factors to verify their significance to the models With the null hypothesis H0: Bi =0, which indicates that a variable is statistically insignificant, the lower the p_value of each independent variables is, preferably below 0.05 and still acceptable if below 0.1, the higher the probability that

we can reject this hypothesis and conclude that the variable is vital to the model Afterwards, we would run a few tests to detect some possible problems in our models and database: VIF was used to test for Multicollinearity; Breusch-Pagan test, White test and Park test were to detect Heteroskedasticity; lastly, Durbin-Watson test and Breusch-Godfrey test were employed to check for Autocorrelation Afterwards, if any problem were present in our models, we would use different methods to fix the models, mitigate the unwanted effects and achieve the optimal models and results for this research.

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The Ordinary Least Squares (OLS) estimation model is:

Yi= B1 + B2 X +B3 Inti + u

In this model, Yi represents the ith company’s daily close/last stock price within

the period of 2020 The X variable is an explanatory variable standing for the

number of daily new confirmed cases (nc), total confirmed cases (ttc), daily new

confirmed death (nd) and total death (ttd) Lastly, the variable Inti is an

independent variable of the ith company’s interest over time.

4 Result

4.1 Pearson correlation coefficients

Using the Pearson correlation coefficients method, we obtain the results as in the table A.4 and A.5 (Appendix 2) The significance of each pair of variables must be less than 0.05 for the variables to have a statistically significant correlation As observed from the tables, all of the dependent variables and its explanatory variables have statistically significant correlation.

4.2 OLS model results and problems with the model

After performing the OLS model mentioned above, we obtained its results, which are displayed in the tables A.6, A.7, A.8 and A.9 (Appendix 2) The variables in the results all have p_values < 0.05, which means they are statistically significant to the models We also do not include any results that has

an insignificant variable’s coefficients, as its result is quite unreliable.

We then perform the VIF test to see if our models have the Multicollinearity problems With all the VIF values < 5, we can safely conclude that our models are not affected by the problem of Multicollinearity.

In the same table, you will notice that our models failed the White test for

the presence of Heteroskedasticity The latter, our d-statistic was outside the acceptance range, which proved our models had Autocorrelation problems.

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4.3 Correction and final result

As we can observe from the testing result, our models and results are influenced by heteroskedasticity and autocorrelation Thus we employed the Newey-West (1987)

[8] test to attempt to mitigate and correct these two problems simultaneously.

Firstly, we will try to find the relationship between COVID-19 daily new confirmed cases and 5 companies’ stock The effect of COVID-19 daily cases on five companies’ stock can be indicated in the table below.

Table 2 Newey-West result of the effect of Daily new confirmed cases

From this table the COVID-19 has the largest impact on Amazon’s stock price

when the Beta is as high as 0.001913, which can be explained by its domination in the E-commerce market When the new COVID-19 cases increase to 1000 cases, Amazon stock price will likely increase by 1.13 Dollars Ebay, Alibaba and JD have their stock increased when there are more and more COVID-19 cases occurring but with less acceleration compared to Amazon Rakuten’s stock price seems to be

affected by COVID-19 slightly All results have a very small amount of P-value which indicates that COVID-19 clearly has an impact on the company's stock price at 5% significance level (P-value = 0.000 < 0.05) All regression models do not run in

multicollinearity problems due to their VIF values being smaller than 2.

standard error

Table 3 Newey-West result of the effect of Total confirmed cases

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Next , in the table above, we can observe the impact of total COVID-19 cases on the stock price From this, we can conclude that although the P-value of these estimators are statistically significant, compared to New COVID-19 cases the effect of Total COVID-19 cases has a relatively small impact on the 5 companies’ stock price.

Table 4 Newey-West result of the effect of Daily New confirmed deaths

Beside determining the effect of total confirmed cases, we also conduct an estimation

on how Daily COVID-19 deaths can lead to changes in companies’ stock price The

estimation’s result is shown in table The test also shows very small P-values (P-value < 0.05), the COVID-19 daily death cases have a significant impact on the selected

companies’ stock prices beside Daily New COVID-19 cases When we try to run an

estimation on how COVID-19 Total death cases relate to our five companies’ stock price,

we predict that the result would be the same when we conduct it on Total COVID-19

confirmed cases As predicted, table 14 shows that although the effect of Total

COVID-19 death cases on companies’ stock price is not as strong as Total COVID-COVID-19 cases and Daily New COVID-19 deaths but it still be more influence than Total COVID-19 cases

with a very high reliable P-value (P-value < 0.000).

Table 5 Newey-West result of the effect of Total confirmed deaths

According to the research result, we can conclude that COVID-19 had a positive

impact on Amazon, Alibaba, JD, Rakuten and Ebay’s stock prices with high statistical

significance Amazon’s stock seems to be influenced by COVID-19 cases the most All

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our hypotheses are accepted; COVID-19 had an effect on all selected’s

businesses’ stock price.

When more and more COVID-10 cases occur, countries from all over the world tend to close their borders and preserve their citizen’s health as much as they can This action can restrict people from moving and therefore cut their basic daily needs

as well When the opportunity comes, E-commerce companies overwhelmingly thrive from these bad situations when they can provide foods and products to customers while complying with social distance rules from these countries.

4.4 Limitations

First of all, it is glaringly apparent that our model has too few independent

variables, which can drastically increase the disturbance u of the model This means

we might have not considered or included all the factors contributing to the growth of the companies’ stock price, such as other financial statistics, demand of traders, etc Unfortunately, due to our inability to find any other relevant variable with daily values,

we had to accept this defection in our model Nevertheless, the R-squared values of our OLS models are relatively acceptable, with only one exception of the smallest being 0.2384 As a result, we are convinced that we have selected two of the major variables affecting the stock prices of chosen companies.

Secondly, another major drawback of our model is the overgeneralization stemming from the fact that we have chosen to analyze the effect of COVID-19 on the global E- commerce industry through its influence on the stock prices of five top companies in the industry This can be deemed as biased because their relations with COVID-19 might not

be the best measurement of the pandemic’s effect on the industry as a whole, because the effect might be tremendously different when we consider smaller companies, even being opposed to the result we have collected from this research This is due to the fact that the size, market share, business capability and other factors of a firm play major roles in how they are affected by COVID-19 Without taking the smaller companies into account, the models can generate bias results.

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Additionally, choosing stock price as the main indicator of a company’s financial performance can be a limitation to our model Other financial statistics, such as net profit (loss), net cash flow, expense, etc can serve as better measurement for a company’s business status However, as explained above, we were unable to compile a usable database with these statistics due to the low number of total observations and rare occurrence of COVID-19 in that model Inevitably, we must utilize stock prices as a means to estimate the selected companies’ financial performance, as they have a sufficient number of values on a daily basis for us to create a large scale database that can effectively demonstrate the effect of COVID-19.

Despite these limitations, we believe this research paper can contribute as a basis to further research in the future into the effect of COVID-19 to E-commerce and other industries as well.

5 Conclusion and Recommendation

5.1 Conclusion

Because of the widespread of COVID-19 pandemic, social distancing and staying

at home are expected to push shoppers to shop online A large number of suppliers facing a reduction in leisure purchases, supply chains and an increase in purchases

of basic toiletries, basic supplies and other items are also affected by the pandemic Due to the supply chain instability and global customer requirements, the COVID-19 incident has had a huge impact on the E-commerce market.

The analysis conducted in this paper proves that COVID-19 has a positive effect

on the stock price of all 5 E-commerce companies: Amazon, Alibaba, Jingdong, Ebay and Rakuten.

This result implies that even though other businesses suffer from the pandemic, commerce is still consistent or rather doing better than before the pandemic Due to its contactless nature while having a potential reach of everywhere on Earth, this aligns extremely well with the compulsory situation we have to place ourselves in - quarantine Unlike traditional commercial, E-commerce is relatively safer for users as

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they can order things virtually and do not have to physically contact anyone The

number of rising cases and deaths resulting in higher stock values and interest over time also implies that more and more people are aware of the level of threat COVID-

19 can pose on one’s health As a result, they are bound to stay at home more often,

if not to say all the time, and transferring all of their normal physical work to online: from their job to their hobbies and in this case, their shopping platform More people staying at home helped the E-commerce business to be more profitable than ever

before, due to the suitable characteristics of the business There is only 1 major

negative effect that COVID-19 had on E-commerce business: supply-chain The

shipping/delivering process is slowed down by the pandemic However, consumers are still buying because they have no other alternatives.

5.2 Recommendation

A strategy for COVID and post-COVID situation is a must, and the crisis plan will have to be conducted fast and reactively according to many scenarios.

Firstly, finding ways to increase shipping speed or rather improve the customers’

experience while waiting for their items to arrive is important and should be focused

on because it is the supply chain that tends to hinder E-commerce growth Logistics and postal services have been slowed in many countries, due to new COVID-19

related safety guidelines and government recommendations Specifically, there are recommendations that should be used by the majority of businesses:

- Simplifying internal processes (be mindful and not turn a simple task into a complicated and end up with a slow process in the end, along with side effects such as frustration If your process is long and tedious, consider starting from scratch and building up a more simple, quick and efficient process.

- Using Electronic data interchange, which is a technique that replaces the

paperwork with electronic data in order to speed up the process as a whole.

- Provide reliable, helpful online tracking information By letting customers have plenty of options for package tracking, such as on-site tracking, links to the

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to reach out more target audiences and fulfill their goals.

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APPENDIX 1 REFERENCES

kinh tế ở Việt Nam, University of Economics Ho Chi Minh City.

2 Hung-Hao Chang and Chad Meyerhoefer (June 2020), COVID-19 and The demand for online food shopping services: Empirical evidence from Taiwan , National Bureau of Economics Research.

3 Torbjörn Fredriksson and Sabrina Ielmoli (UNCTAD), and Nanno Mulder

(UNECLAC) (2021), COVID-19 and E-commerce - A global review, United Nations

COVID-19 Pandemic.

10 EU-Vietnam Business Network (2018), E-COMMERCE INDUSTRY IN

VIETNAM RESEARCH REPORT.

11 Susan Meyer (2020), Understanding the COVID-19 Effect on Online Shopping Behavior.

12 SearchNode Inc ( 2021), 30 Ecommerce Trends for 2021 [Survey Report].

13 Shrestha, N et al (2020), The Impact of COVID-19 on Globalization, One Health.

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Table A.1 Summary of COVID-19’s statistics

Variable Number of Maximum Minimum Mean

Table A.2 Summary of selected companies’ stock prices

Variable Number of Maximum Minimum Mean

4.49e+07 256828.8 949495.1 4839.212

Standard

deviation

593.5119 33.57524 21.57024 9.974053 1.394147

Standard

deviation

8.841074 8.749688 13.10722 7.973937 9.015578

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Table A.4 Summary of selected companies’ interest over time

0ebay 0.9318* 0.6914* 1

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Table A.5 Correlation between stock price and COVID-19’s statistics

Variable Beta R squared Adj R- squared P value VIF White test d-statistic

Table A.6 OLS result of the effect of Daily new confirmed cases

Variable Beta R squared Adj R- squared P value VIF White test d-statistic

Table A.7 OLS result of the effect of Total confirmed cases

Variable Beta R squared Adj R- P value VIF White d-statistic

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Table A.9 OLS result of the effect of Daily new confirmed death

Database of companies’ stock price and COVID-19’s statistics:

Daily

Total

Daily Date Total cases new new AMZN BABA EBAY RKUNY JD

deaths cases death

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Daily

Total

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Daily

Total

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Daily

Total

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Daily

Total

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Daily

Total

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Daily

Total

Tiêu đề	Econometrics Analysis Of The Impact Of Covid-19 (Sars-Cov-2) On International E-Commerce
Tác giả	Lê Minh Tâm, Nguyễn Quốc Thái, Nguyễn Trí Thông, Trần Minh Khải, Nguyễn Phúc Xuân Ngân
Người hướng dẫn	Lê Hồng Mỹ Hạnh
Trường học	Foreign Trade University
Chuyên ngành	International Business
Thể loại	Scientific Research
Năm xuất bản	2021
Thành phố	Ho Chi Minh City

Định dạng
Số trang	139
Dung lượng	1,23 MB