National Income with the advancement of economic development, an increasing number of people are opting to travel. Residents’ income is a key factor influencing tourism spending. Focusing on Wuhan City as a case study, this paper utilizes data from 1996 to 2015 and employs EViews software along with co-integration analysis to empirically examine the relationship between residents’ per capita disposable income and per capita tourism expenditure, providing, National Income a quantitative assessment of their dynamic interaction. The findings indicate the existence of a long-term stable relationship between the rise in residents’ income and tourism consumption. Increases in residents’ National Income have been shown to drive tourism spending. Specifically, a 1% rise in per capita disposable income results in a 1.1317% increase in tourism expenditure. Based on these results, boosting residents’ income levels and implementing holiday benefit policies could stimulate tourism consumption, thereby supporting the growth of China’s tourism sector and contributing to overall economic development.

With economic development, tourism has become an increasingly popular activity. According to iiMedia Research, the number of domestic tourists reached 5.54 billion in 2018, marking a 10.8% increase compared to the previous year, National Income while domestic tourism revenue totaled 5.1 trillion yuan, up 12.3% from the prior year. These figures indicate that tourism is experiencing robust growth, establishing itself as a new driver of economic expansion. As people’s living standards continue to improve, the demand for tourism is expected to rise further, leading to greater development of the tourism industry and contributing to overall economic growth. Therefore, it is essential to examine the factors that influence residents’ tourism spending.

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Tourism is influenced by various factors. Individual leisure time and personal travel motivations can affect tourism consumption; however, the most National Income critical factor is residents’ income. Disposable income determines spending capacity, and tourism expenditure is directly linked to the amount of disposable income available. With the steady progress of China’s reform and opening-up, residents’ per capita disposable income has consistently increased over the past five years, as illustrated in Figure 1. In 2017, the nationwide per capita disposable income was 25,974 yuan, a nominal rise of 9.0% compared with the previous year, and a real increase of 7.3% after adjusting for inflation. That year, the per capita consumption expenditure was 18,322 yuan, showing a nominal growth of 7.1% and a real growth of 5.4% after price adjustments.

Therefore, by analyzing historical data on residents’ National Income and tourism consumption, it is possible to predict the near-future demand in the tourism market. Studying the relationship between disposable income growth and tourism spending provides a valuable foundation for forecasting tourism market trends for service providers. This research is crucial for understanding China’s tourism market, the structure of tourism consumption, and for promoting the continued development of the country’s tourism industry.

Many scholars have explored this topic. For instance, Huang Cancan (2016) determined the initial income distribution by choosing the starting wage rate, the Gini coefficient for urban residents, and the proportion of tourism consumption across different National Income groups. The results indicated that the aggregate effect influences the tourism spending of the middle-income group more significantly, while the structural effect of the initial income distribution has a greater impact on the high-income group’s tourism spending. Fang Jing (2015) applied econometric methods to develop a univariate linear model, tested for autocorrelation, corrected for autocorrelation, and addressed heteroscedasticity, concluding that rural residents’ per capita net income has a strong linear relationship with per capita tourism expenditure. Yao Lifen, Long Ruyin, and Li Qingchen (2010) used co-integration theory, an error correction model, and the Granger causality test to empirically examine the connection between domestic tourism consumption and residents’ income in China, analyzing both urban and rural populations. They found a long-term equilibrium between tourism consumption and income, noting that increases in rural residents’ income have a clearer effect on tourism consumption than those of urban residents.

Liu Jia (2007) observed that tourism consumption shares general characteristics with other types of consumption and is closely linked to disposable income and prices: it rises with higher disposable income and falls as prices increase. Su Fajin (2012) compared urban and rural residents’ tourism consumption in relation to income, finding that both current and permanent income Granger-cause changes in tourism expenditure. Sun Gennian and Xue Jia (2009a, 2009b) applied the Cobb-Douglas production function and logarithmic linear models to quantitatively analyze how changes in per capita income drive domestic tourist flows and travel rates, demonstrating that personal disposable income is a fundamental factor influencing and constraining domestic tourism demand. Liu Na (2017) concluded that residents’ discretionary income can serve as a key indicator for predicting their short-term tourism consumption capacity. Huang Lianyun (2017) studied tourism consumption patterns in Chengdu and found that increasing rural residents’ per capita disposable income is more effective than raising urban residents’ income, suggesting that rural consumers will become a major growth driver for Chengdu’s tourism sector.

Using Wuhan as a case study, this paper examines residents’ disposable income and tourism expenditure data from 2001 to 2015. It explores the relationship between income growth and tourism consumption in depth and, based on the analysis, proposes targeted measures to stimulate the development of China’s tourism industry and, in turn, support broader economic growth.

Considering the current situation and the availability of relevant data, this study focuses on analyzing the per capita disposable income and per capita tourism expenditure of residents in Wuhan from 1996 to 2015. The time series data for residents’ per capita disposable income and tourism spending were sourced from the Wuhan Statistical Yearbook and China Tourism Statistical Yearbook for the years 1996 to 2015. During the EViews data processing and model construction, to address heteroscedasticity in the time series and account for price index fluctuations, the per capita disposable income and tourism expenditure were transformed using natural logarithms, denoted as LNINCOME and LNCOST.

First, we can examine the scatter plots of the two variables, LNINCOME and LNCOST (illustrated in Figure 2). From the scatter plot, it is evident that the data points align closely, suggesting a strong relationship between the two variables.

To further assess the strength of their association, a correlation analysis is necessary. We used Eviews to conduct a correlation analysis on these two variables, with the results presented in Figure 3. As shown in Figure 3, the correlation coefficient between per capita disposable income and per capita tourism expenditure is 0.9571, which is very close to 1. This indicates a significant positive correlation between the two variables, suggesting that residents’ per capita tourism spending tends to increase as their disposable income rises.

The basis for conducting a co-integration analysis between the two time series, LNINCOME and LNCOST, is that both variables need to be stationary, meaning they should not exhibit large fluctuations over time. To assess this, we first examine the stationarity of the two sequences and use EViews to generate their time series plots (Figure 4). From Figure 4, it is evident that both LNINCOME and LNCOST are influenced by time, indicating that these sequences are not stationary. Therefore, we proceed to examine their stationarity using the differencing method.

Initially, both datasets are transformed using first-order differences, labeled as DLNINCOME and DLNCOST. The time series plots after first-order differencing, obtained from EViews, are shown in Figure 5. As observed in Figure 5, the sequences DLNINCOME and DLNCOST appear to be relatively stable.

To more precisely confirm the stationarity of the sequences, the ADF (Augmented Dickey-Fuller) unit root test is applied using EViews. According to the results displayed in Figures 6 and 7, the P-value of the ADF test in Figure 6 is 0.9995, which is significantly higher than the 5% threshold. Therefore, the null hypothesis of non-stationarity cannot be rejected, indicating that LNINCOME and LNCOST are non-stationary at the 5% significance level. The original time series plots clearly show a non-stationary pattern.

Among the factors influencing tourism spending, residents’ disposable income is particularly significant. The level of income affects both the extent of consumption and the satisfaction of demand, thereby shaping changes in consumption patterns (Tian, 2002). When residents have higher incomes, they possess greater financial capacity to spend on tourism. Disposable income serves as the economic foundation for tourism consumption. During a trip, tourists incur expenses such as meals, accommodations, transportation, and lodging choices—all of which are closely linked to their financial means. In other words, residents’ disposable income directly impacts the travel options they can afford. Hence, it is a crucial factor in determining tourism expenditure.

Residents with greater disposable income have more funds available for leisure activities and may even enjoy paid vacation benefits. Conversely, those with limited disposable income often face constraints on leisure time, weaker leisure awareness, and difficulty covering travel costs. As a result, tourism demand tends to be higher among residents with more disposable income. This rise in tourism demand subsequently leads to greater tourism spending, illustrating why higher income levels among residents encourage increased tourism consumption.

Based on an empirical analysis of the relationship between Wuhan residents’ per capita disposable income and per capita consumption expenditure, this study reaches the following conclusions: There exists a long-term and stable correlation between residents’ income growth and their tourism spending. Residents’ income growth is a key factor influencing tourism consumption, and this effect is unidirectional: an increase in income drives higher tourism expenditure, whereas changes in tourism spending do not affect income. Quantitatively, for every 1% increase in residents’ income, tourism consumption rises by 1.1317%.

By examining the link between Wuhan residents’ income growth and tourism spending, this study provides insights that can be extended to the national level, helping to predict future consumption trends and offering a policy reference to promote China’s tourism industry. Based on these findings, the following recommendations are proposed:

• Increase residents’ disposable income: Since income growth stimulates tourism consumption, policies should focus on raising residents’ disposable income. Adjusting the income distribution, reducing the gap between rich and poor, shrinking the low-income population, and expanding the middle class will increase the number of potential tourists. Enhancing social security and providing subsidies to low-income households can also alleviate concerns about basic living costs, allowing more disposable income for travel.
• Implement holiday travel incentives: As most residents travel during their leisure time, the government should introduce preferential policies for key holidays, such as “May 1st” and “11th” Golden Week. Measures like waiving bridge and road tolls or offering discounted airfare, travel packages, and promotional deals can reduce travel costs, making tourism more accessible and encouraging higher spending.
• Promote local tourism: Local governments can diversify management of tourism enterprises and implement policies that support residents and local tourism development. Residents should be able to enjoy nearby scenic spots without waiting for long holidays, which encourages regular travel and stimulates local tourism markets.
• Develop welfare-oriented travel policies: Policies that provide more leisure time for residents, such as paid vacation systems or dual holiday arrangements, can encourage tourism. Enterprises can also offer travel incentives linked to employee performance, balancing work obligations with opportunities to travel.
• Enhance tourism technology and services: In the digital age, convenient online services for booking tickets and hotels improve the overall travel experience. High-quality services and reasonable prices attract more tourists and promote repeat visits. Tourism companies should focus on consumer needs, efficient management, and service quality to foster a virtuous cycle of growth in the industry.
• Strengthen tourism regulation: To address issues such as misleading promotions, price gouging, and chaotic group tours, tourism authorities must enforce regulations to protect consumers. Travel agencies that violate rules should face penalties, while those providing good service should be rewarded. Providing guidance and assistance to travelers ensures a healthier, more sustainable tourism sector.