The course Tourism Economics is a compulsory course for university tourism management majors. To deepen students’ understanding of tourism economics and combine theoretical economic knowledge with practical applications, it is necessary to set up experimental classes of some hours. Supply, demand, elasticity and marginal utility are permanent themes of economics. Therefore, the purpose of the experiment is to help students understand and master the basic theories, methods and skills of tourism economics, use multiple regression models to analyze the impact of the growth of various factors on the growth in tourism economy and explore the relationship between economy, employment and tourism demand.

The purpose of this article is to explain how to allocate a certain number of hours to conduct simulation experiments on tourism economics in the university tourism economics course. We took China’s tourism economic growth as an example. Using a multiple logarithmic-linear regression model and excel’s built-in multiple regression programs, the paper analyzed the impact of China’s economic growth and changes in urban unemployment rates on tourism economic growth from 2001 to 2020.

Experimental Project and Class Hours

Experimental project: An Analysis of the Impact of China’s Economic and Employment Growth on Tourism Growth from 2001 To 2020: The Application of Logarithmic-Linear Multiple Regression Models. The experiment takes 8 hours, accounting for 13.3% of the total course hours (60 hours).

Experimental Purpose and Requirements

The purpose of the experiment is to help students understand and master the fundamental theories, methods and skills of tourism economics, use multiple regression models to analyze the impact of various factors on tourism economic growth and explore the relationship between economy, employment and tourism demand.

Experimental requirements: Students need to learn the process, methods and collecting, sorting and analyzing data. Students must be familiar with the production of excel data tables and use excel software to perform multiple linear regression. Each student must write and submit an experiment report. Students are required to cultivate scientific and rigorous analytical thinking and the ability to solve practical problems. The experiment is not limited to the 8-hour in-class schedule. It requires students to make full use of extracurricular time to collect data and learn related methods.

Laboratory Conditions

Computers and data labs with multimedia equipment are required. Each student uses a computer installed with Microsoft Office suite and can access the Internet.

The experiment uses the following log-linear multiple regression model[1, 2]:

log(EXPT) = α + β₁ log(GDP) + β₂ log(UER) (1)

Where:

EXPT: The average expenditures (RMB yuan) of urban residents on domestic tourism from 2001 to 2020. It is an indicator of tourism economic growth.

GDP: China’s GDP (RMB 100 million) in the calendar years from 2001 to 2020 reflects overall economic growth and should have a positive impact on the tourism economy. The estimated coefficient β₁ is expected to have a positive sign.

UER: The registered unemployment rate (%) of the urban population in China from 2001 to 2020. It reflects the overall urban employment situation. Its growth should have a negative impact on tourism economic growth. The estimated coefficient β₂ is expected to have a negative sign.

Log represents the natural logarithm. Therefore, the estimated coefficien 1 β₁ is the average elasticity of urban residents’ tourism expenditure relative to economic growth. β₂ is the average elasticity of urban residents’ tourism expenditure relative to the urban unemployment rate.

• Defining variables: The experiment defines three variables EXPT, GDP, UER. Refer to Introduction to experimental methods

• Collecting, organizing and analyzing information and data. All data comes from the online database of the National Bureau of Statistics of China[3]

• Establishing a standard excel data calculation table (Table 1)

• Calling the multiple regression program from the built-in program of excel. The route is file, option, add-in, analysis tool library and OK. Click on regression in Data Analysis in the upper right corner of the excel tool bar

The output of multiple regression results is reported in Table 2

Table 1: Excel Data Calculation

Table 2: Output of Multiple Regression Results

Experiment Report Writing

Writing an experimental report of about 2,000 words: the most important is to interpret the estimated coefficients and analyze the economic mechanism.

For example, the coefficient of the estimated variable GDP, β₁，is 1.1265. The t-statistic is 18.99, indicating that the estimate is significant at the 5% level. The economic meaning of coefficient is that from 2001 to 2020, for every 1% increase in China’s GDP, the average domestic travel expenditure of urban residents will increase by 1.13%. It shows that economic growth does promote tourism demand, which is in line with the prediction of tourism economics.

The coefficient of the estimated urban registered unemployment rate variable UER, namely β₂， is -2.8993. The t-statistic is -3.30, indicating that the coefficient is significant at the 5% level. The economic meaning of the coefficient is that from 2001 to 2020, for every 1% increase in the registered unemployment rate in China’s urban areas, the average domestic travel expenditure of urban residents will drop by 2.90%. It shows that unemployment growth has a tremendous negative impact on tourism demand, which is also in line with the theoretical expectations of tourism economics.

The policy significance is that vigorously developing the economy and increasing the employment rate will significantly promote the growth of the tourism industry.

Experiment Score

Scoring is made based on the experimental report and the percentage of participation in the experiment. The experimental score accounts for 25% of the total course score. The experimental score structure is as follows:

• Completing the entire experimental process: 40%

• Submitting a complete experiment report: 10%

• Correctly interpreting the economic meaning of the estimated coefficients: 30%

• Policy suggestions: 20%

We believe that the experimental classes of tourism economics for university tourism management majors can help students understand and master the fundamental theories, methods and skills of tourism economics. Therefore, taking China’s tourism economic growth as an example, this article designs an in-class experiment on the impact of China’s economic growth and the change in unemployment rates on tourism economic growth. It explains the laboratory conditions, experimental methods and procedures, how to write experimental reports and how to score experimental reports.

Through the application of experiments in course teaching, our experiments have achieved remarkable results. The vast majority of students have mastered the use of excel’s built-in multiple regression program, the application of multiple logarithmic-linear regression models in tourism economics, data collection and excel datasheet production. They also learned how to analyze the impact of social and economic fundamentals on the growth of the tourism economy.

China’s tourism economic growth experiment found that economic growth has significantly promoted tourism demand. In contrast, the increase in unemployment has a significant negative impact on tourism demand, which is in line with the theoretical expectations of tourism economics. Therefore, the experimental results not only deepen the students’ understanding of theory but also cultivate their strong interest in the study of tourism economics.

1. DiPasquale, D. and Wheaton, W.C. (1996). Urban Economics and Real Estate Markets. Englewood Cliffs, New Jersey: Prentice-Hall.

2. Gujarati, D.N. (2003). Basic Econometrics (4th ed.). New York: McGraw-Hill.

3. NBSC. (2021). National Data: Yearly Data. Retrieved March 15, 2021, from http://data.stats.gov.cn/easyquery.htm?cn=C01