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Section 7. Economics of recreation and tourism
https://doi.org/10.29013/EJEMS-21-78-90
Eric Duan,
American Heritage School, Boca Raton, Florida, USA E-mail: [email protected]; [email protected]
INTERNATIONAL TRADE AND INTERNATIONAL TOURISM: WHAT'S THE RELATIONSHIP BETWEEN?
Abstract. Tourism plays an important role in the development of many countries. This year, however, the Covid-19 pandemic and its associated economic shutdown have disrupted nearly every aspect of people's lives, especially tourism which has been hit hard by the pandemic. International trade is also a significant contributor to the economic growth of a nation. The purpose of this project is to find out the relationship between international trade and international tourism and take the advantage of this relationship to improve the local economy. The data from NBS of China was gathered and graphed. R-Studio was used to analyze the data and to obtain the relationship between international trade and international tourism. Trend lines were shown using Excel, the correlation diagram and the linear regression analysis were performed. Three trade variables were shown to be positively correlated with international tourism. The negative association between Registered Capital of Foreign Funded Enterprises and tourism outcomes may be explained by the relationship between the trade variables. These results can be supportive of the Chinese government policies/strategies that aim to enhance the country's foreign trade volume as well as to promote international tourism.
Keywords: International trade, International tourism, correlation, R-studio, linear regression, stepwise.
1. Introduction China, the tourism industry has been expanding sig-
Due to the development of transportations and nificantly in recent years. international relationships, international trade and This year, however, the Covid-19 pandemic and international tourism take place more frequently its associated economic shutdown have disrupted than before and play an important role in many coun- nearly every aspect of people's lives and created cri-tries. The United Nations World Tourism Organiza- ses for most countries in the world. Service indus-tion (UNWTO) stated that: growth in international tries, especially tourism, have been hit hard by the tourist arrivals continues to outpace the economy. pandemic. The discovery of the association between 2019 was another year of strong growth, interna- international trade and international tourism can tional tourist arrivals (overnight visitors) worldwide provide a fresh perspective for government officials grew 4% in 2019 to reach 1.5 billion, based on data as well as global executives on how to sustain a mean-reported by destinations around the world [1]. In ingful economic recovery.
International tourism refers to traveling across national borders, including outbound and inbound tourism. People travel to different countries to meet local people and learn about their cultures with one of the benefits being that it can boost businesses such as travel agencies, hotels, resorts, and restaurants. These businesses will further attract foreign funds and generate income which can help facilitate the local economic growth and provide employment opportunities [2]. International trade refers to the commodities and labor service between different countries [3]. International trade is also a significant contributor to the economic growth of a nation. Imports and exports can create huge benefits for countries, to name a few:
• They bring in a variety of products from different areas, such as specialty products that only can be produced locally, due to the climate;
• Promote efficiency in production and prevent monopoly by bringing in lower prices and more choices. This leads to close and mu-
• Generate more employment opportunities through the establishment of newer industries and companies to meet the demands of trading partners.
This study aims to analyze and evaluate the association between international tourism and international trade in China.
2. Method
2.1. Data Source
The data was collected from the National Bureau of Statistics (NBS) of China. This website is authoritative and official [4]. NBS is an agency directly under the State Council and is in charge of statistics and economic accounting in China. The website includes data on the country's foreign trade and international tourism over the recent ten years of data. Specifically, the 9 indices included in this study, and their corresponding labels are shown in table 1. All data are from 2008 to 2017 and ordered by region/province of China [5].
tually beneficial counties' relations;
Table 1.- Variable labels for each measure
Variable names Variable labels
Foreign Trade indices Total Value of Imports and Exports Commodities Value Imports Exports
Total Value of Imports Commodities Value Imports
Total Value of Exports Commodities Value Exports
Number of Foreign Funded Enterprises (year-end) F Funded Etpr
Registered Capital of Foreign Funded Enterprises Cpt F F Etpr
Total Investment of Foreign Funded Enterprises Invest f f Etpr
International tourism indices Number of Foreign Visitors Foreigners Visitor
Number of Oversea Visitor Arrivals Ovs Visitor Arrivals
Foreign Exchange Earnings from International Tourism F Exch Earnings
2.2. Data Analysis Descriptive analysis:
Using Microsoft Excel to generate line graphs for visual observation of each index's trend. Compare the trends, differences, and similarities visually. Make a hypothesis based on the observation of the graphs and try to prove it in the following analysis.
Linear correlation:
Input the data into RStudio. Transform the wide data format into a long data format using the "gather" function to gather columns into key-value pairs. For instance, the data was in a wide format with 31 rows (regions) and 11 columns (years 2008-2017) per index. The gather function transforms each index data into a 310 x 3 data frame with regions sequenced by year as rows. Then all the index data frames were
merged into one, and the correlation between the indices within foreign trade, within international tourism, also between foreign trade and international tourism were examined. The correlations are represented using the "corrplot" function with a digital rate so that the correlations can be examined in a numerical way.
Regression analysis:
Using stepwise linear regression analysis, foreign trade indices' linear relationship with the international tourism indices were modeled. Regression analysis is a powerful statistical process with the goal of finding the relations within a dataset, especially the relationships between the independent variables (predictors) and a dependent variable (outcome). It can be used to build models for inference or prediction. Linear regression is a commonly used statistical technique for continuous outcomes. It is widely used in biological, behavioral and social sciences.
Stepwise linear regression is a method of regressing multiple variables while simultaneously removing the weakest correlated variables. Hence, the stepwise variable selection alleviates the concern of collinearity among the predictor variables. Function "stepAIC" in the "MASS" library was used to achieve this.
Multiple linear regression follows the formula: y = ax + ax + ax + ... + ax. The coefficients (an,
/001122 nn v07
a^ ... an) denote the magnitude of additive relation between the predictor and the response. The null hypothesis would be that there is no relation between the predictor and the response. The p-value of F statistic can be used to determine whether the null hypothesis can be rejected or not [6]. In the output of the linear regression, the p-value for each term tests the null hypothesis that the coefficient is equal to zero (no effect). A low p-value (< 0.05) indicates that the null hypothesis can be rejected.
The F-test linear regression tests whether any of the independent variables in a multiple linear regression model are significant [7]. The Residual Standard Error (RSE) estimate gives a measure of error of prediction. It is the average amount that the real
values of the outcome variable differ from the predictions provided by the regression line. The lower the RSE the more accurate the model.
R-squared (R2) is a goodness-of-fit measure for linear regression models. It evaluates the scattering of the data points around the fitted regression line which is the strength of the relationship between the model and the dependent variable [8]. In other words, it measures the proportion of variability in the outcome that can be explained by the model on a 0-100% scale. The higher the value, the better the model is able to explain the variability in the outcome. However, an increase in the number of predictors mostly results in an increased value of R2 due to inflation of R-squared. Adjusted R-squared adjusts the value of R2 to avoid this effect [6].
3. Result
3.1. Line graph showing the trend of each index
Figures 1-7 plot the indices in the dataset with Excel. Each plot is a line graph of each region's index from year 2008 to 2017 that is color coded by region. The regions with the highest values of that particular index are marked in the graph. For the cities that are both well developed in tourism and trade, such as Beijing, Shanghai, and Jiangsu, the international trade and international tourism trends are quite similar. It is reasonable to hypothesize that the international trade indices are associated with international tourism indices.
Figure 1 shows that the tendency of exporting and importing reached the max in 2013 and seems to continue to grow up after 2017. Figure 2 shows that the number of foreign funded enterprises increased from 2008 to 2017, so are the registered capital of foreign funded enterprises and the total investment of foreign funded enterprises as shown in figures 3 and 4. The registered capital of foreign funded enterprises also surged in 2014 mostly. In 2016 to 2017 the total investment of foreign funded enterprises boosted dramatically. Figure 5 (Number of Oversea Visitor Arrivals) shows that Guangdong province was outstanding among all other provinces.
(Figure 6) shows the number of foreign visitors fluc- (the foreign exchange earnings) is somewhat similar tuated a lot. In 2012, the number of foreign visitors with figure 5, Guangdong province was outstanding decreased dramatically except Guangdong. Figure 7 and increased continuously.
Figure 1. Total value of Imports and Exports from 2008 to 2017 colored by region/province
Figure 2. Number of Foreign Funded Enterprises from 2008 to 2017 colored by region/province
Figure 3. Registered Capital of Foreign Funded Enterprises from 2008 to 2017 colored by region/province
Figure 4. Total Investment of Foreign Funded Enterprises from 2008 to 2017 colored by region/province
Figure 5. Number of Oversea Visitor Arrivals from 2008 to 2017 colored by region/province
Figure 6. Number of Foreign Visitors from 2008 to 2017 colored by region/province
Figure 7.
3.2. The Correlation Diagram
Function "cor ()" was used to calculate correlations between indices and "corrplot()" was to produce graphical displays of the correlation matrices with the size of the circles being proportional to the correlation coefficients. The numbers inside the circles are the correlation coefficients and the color of the circles shows positive or negative correlation. The correlation between international tourism variables and between international trade variables are shown in figure 8-9 respectively. Figure 10 and table 2 show the correlation matrix of all indices in this study. All measures are highly correlated.
In the international tourism variables diagram, the number of foreign visitors and the number of overseas visitor arrivals are most related to the foreign exchange earnings from international tourism and have a rate of 0.88 and 0.93. In the correlation diagram of international trade variables, the total
value of imports and exports commodities is the most correlated with the total value of imported commodities and the total value of exported commodities and have the rate of 0.95 and 0.97. In the correlation diagram of international trade and international tourism variables, the foreign exchange earnings from international tourism and the total value of imports and exports commodities, have a very high correlation rate - 9.3, which confirms the hypothesis made in section 3.1. In addition, the total value of imports and exports commodities have high correlation rates of 0.86, 0.93, and 0.85 with the international tourism variables, and a number of foreign-funded enterprises have high rates of 0.86, 0.92 and 0.87 with the international tourism variables. The number of registered capitals of foreign-funded enterprises and the total investment of foreign-funded enterprises are less correlated with international tourism.
Figure 8. The correlation diagram of international tourism variables
Figure 9. The correlation diagram of international trade variables
Figure 10. The correlation diagram of international trade and international tourism variables
With stepwise regression analysis, the international trade variables for each tourism index were selected, as shown in (table 3). The outcome statistics (residual standard error, R-squared, F-statistic,
p-value) for each model are summarized in table 3 variances, and outliers [9]. as well. The final models with regression coefficients and their individual p-values are listed in the Appen-
dix. Figures 11-13 show the residuals versus fits plot which is a scatter plot of residuals on the y-axis and fitted values (estimated responses) on the x-axis. The plot is used to detect non-linearity, unequal error
Table 2. - Correlation between international tourism and foreign trade
Number of Foreign Visitors Arrivals Number of Oversea Visitor Arrivals Foreign Exchange Earnings from International Tourism
Total Value of Imports and Exports Commodities 0.851078 0.85969 0.925436
Total Value of Exports Commodities 0.80545 0.871164 0.904975
Total Value of Imports Commodities 0.82789 0.763141 0.863186
Number of Foreign Funded Enterprises 0.865586 0.856527 0.91641
Registered Capital of Foreign Funded Enterprises 0.74859 0.636119 0.777374
Total investment of Foreign Funded Enterprises 0.721392 0.642273 0.772427
Linear regression analysis
From the residuals versus fits pot (figures 1113), the residuals appear to «bounce randomly» around the zero line. This suggests that the assumption of the linear relationship is reasonable. Some residuals «stand out» from the basic random pattern of residuals which suggests that there are some outliers.
From the result of linear regression, the registered capital of foreign-funded enterprises turns out to be negatively associated with international tourism. The total value of imported commodities, the total value of exported commodities, and the number of foreign-funded enterprises are strongly and
positively associated with international tourism. Table 3.- Final model for each tourism index from stepwise analysis
International Tourism Index Number of Foreign visitors Number of Oversea Visitor Arrivals Foreign Exchange Earnings from International Tourism
1 2 3 4
Predictor Variables region region region
year year year
Total Value of Imports Total Value of Imports
Total Value of Exports Total Value of Exports
Number of Foreign Funded Enterprises Number of Foreign Funded Enterprises Number of Foreign Funded Enterprises
Registered Capital of Foreign Funded Enterprises Registered Capital of Foreign Funded Enterprises Registered Capital of Foreign Funded Enterprises
Residual Standard Error 0.4487 on 267 degrees of freedom 0.7273 on 266 degrees of freedom 569.2 on 267 degrees of freedom
Multiple R-squared 0.9428 0.9861 0.9687
1 2 3 4
Adjusted R-squared 0.9338 0.9839 0.9638
F-statistic 104.7 on 42 and 267 DF 439.5 on 43 and 266 DF 196.6 on 42 and 267 DF
P-value < 0.00000000000000022 < 0.00000000000000022 < 0.00000000000000022
Figure 11. Foreign visitors final model residuals vs. fits plot
Figure 12. Oversea visitor arrivals final model residuals vs. fits plot
Figure 13. Foreign exchange earnings final model residuals vs. fits plot
4. Conclusion
Both international trade and international tourism have been on the rise over the past decade. All measures are highly correlated with each other. Four variables are strongly associated with international tourism. Three are positively associated: total value of imports and exports commodities and number of foreign funded enterprises. The registered capital of foreign funded enterprises is negatively associated.
Both imports and exports are positively associated tourism outcomes. Results are consistent with findings in Thailand, which is also a major tourist destination in the region. According to one study of Thailand, the degree of trade openness was positively correlated with the country's international tourism demand [1].
Other countries that had similar findings include but are not limited to the following: Malaysia [10], Portugal [11], Romania [12]. Therefore, it is recommended that the government deliver a policy that promotes both imports and exports.
The negative association between Registered Capital of Foreign Funded Enterprises and tour-
ism outcomes may be explained by the relationship between the trade variables. For example, the larger number of Enterprises the more tourists attracted, and the larger number of Enterprises the more capital of Enterprises. However, the former relationship is much stronger than the latter, so that the relationship between capital and tourist's attraction became negative.
Theories that connect international trade and international tourism include the following: [1]
• International trade boosts business travel and contributes to networking at the individual, business, and national levels.
• International trade promotes product advertisements that attract consumers' attention, which creates awareness of both a product and its country of origin. This may stimulate the desire to travel to the home country of that product.
• International trade encourages a country to improve essential infrastructure in order to facilitate related trade activities, for example, transportation and communication systems.
The improvement of infrastructure, in turn, helps attract more tourists.
Moreover, The Thailand study found that countries having a high trade value with Thailand tend to have a high number of tourists visiting the country [1]. Future studies in China can explore this area.
Compared to Beijing, most other regions have lower tourism indices of foreign visitors and foreign exchange earnings from International tourism. This is not the case for the number of oversea visitor arrivals, however. This may suggest that there can be a different pattern between the number of foreign visitors and the number of oversea visitor arrivals.
Yunnan Province seems to be higher than Beijing in all three tourism indices. This is not surprising, as tourism is very developed in Yunnan Province. These results can be supportive of the Chinese government policies/strategies that aim to enhance the country's foreign trade volume as well as to promote international tourism.
5. Discussion
The positive correlation can be found in many countries [13]. The expansion of international tourism boosts the revenue of the economy, creates mil-
lions of jobs, improve the infrastructures of the country, and cultivates a sense of cultural exchange between foreigners and citizens. A good economic situation is a basic need for the development ofinternational trade. For example, Thailand is a major tourist destination [14]. In 2015, the international tourism revenue of Thailand accounted for nearly 5.8% GDP of the country, and tourism contributes to the economic growth of the service sector of international trade. The countries that have trading relations with Thailand, such as Japan, China, the United States, and Singapore all tend to have a large number of tourists visiting Thailand.
After the deliberate and precise analysis, the International trade and international tourism indeed have a strong relationship. The total value of imported commodities, the total value of exported commodities, and the number of foreign-funded enterprises are positively associated with international tourism. These results can help the Chinese government to develop strategies and policies focused on tourism to improve trade with foreign countries. Eventually, the development of international trade and international tourism will benefit the county's economic condition.
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