Naru Lertvitavaschai ECON4861 Prof. Jo 2021/12/16 Is Thailand Tourism-Driven Economy: VAR approach Introduction: Over the last few decades, the Thai government has been actively investing in the tourism industry as a means to stimulate the country’s overall growth. Namely, the government viewed that the Thai economy could be regarded as a “tourism-driven economy” or the case in which the tourism industry is believed to be a catalyst for economic growth. Though many countries, especially the developing ones, believed in the tourism-driven hypothesis, many studies have been done to show that the causal relationship between tourism income and economic growth is not strong. Moreover, the direction in which a single industry pushed the whole economy is even more vague. Therefore, this study aimed at observing whether Thailand manifests any characteristics of a tourism-driven economy, and if the Thai government’s current tourism promoting policies will be efficient in expanding the overall growth. Lastly, I will analyze the outcome and give my policy suggestions that will suit the country’s tourism-growth model. Research objectives: to assess the effect of tourism promotions on Thailand's economic growth. Research methods: ○ Data: Model estimates based on quarterly data from 2005 to 2014 gathered from the Ministry of Tourism and Sports, Tourism Authority of Thailand, National Economic and Social Development Board, Bureau of Budget Ministry of Finance and Bank of Thailand ○ Econometrics tool: The research process was 1. Stationary test 2. Vector Autoregressive Model Estimation and 3. The Impulse Response Function Analysis Literature Review: According to Ghartey (2010) study on the relationship between economic growth and tourism income of Jamaica from 1963 to 2008, it found that the expansion of the tourism sector played an important role in causing economic expansion, both in the short-term and long-term. Similar studies have been conducted and supported that the Tourism–Led Growth hypothesis is true in developing countries. However, a study by Antonakakis.et al. (2015) used PVAR to examine the relationship between tourism income and growth in 113 countries from 1995 to 2011, which were clustered into six groups. The PVAR estimates showed that the overall model does not support the assumption of Tourism–Led Growth, but on the other hand, Economic–Driven–Tourism Growth was recognized in every cluster. Only a few countries with competitive tourism markets and high economic development tended to accept the Tourism–Led Growth hypothesis in a short run. Data Analysis: The research used the Structural Vector Regressive (SVAR) model to estimate the relationship between tourism budget (TB) tourism revenue from foreign tourists (TR) and real national income (GDP). to use for calculating the Impulse Response Function. The structural models are as follows εTB εTR , εGDP are the errors of the government budget for tourism, tourism income from foreigners, and national income respectively. The errors here are called “Pure Shock,” or shock influenced by only the variables themselves being considered.The above structure models can be rearranged in a Reduced Form as follows: eTB, eTR, eGDP are total shocks that affect the variables. To make the research results consistent with economic facts and theories, we must arrange total shock in order that represents each shock as composition of the three variables, starting with the total shock of the tourism promotion budgets, which includes its own pure shock. The total shock of tourism income is calculated based on the pure shock of tourist income and the pure shock of the tourism promotion budget. The total shock of the economic expansion is determined in the similar manner as follows: The Impulse Response Function of this Structural Vector Autoregressive will convey the magnitude and the direction of change of variable of interest when the pure shock occurs in one of the variables. Research Outcome: The stationary test showed that all three variables are stationary when the first difference. Then, we estimated the Vector Autoregressive Model according to Equations above with an optimal lag length of 3, since it is the most appropriate length of historical influence according to AIC statistics as shown in Table 1 Table 1 When applying Impulse Response Function with the vector autoregressive model estimate results according to the structure of Total Shock specified in equation above, the response coefficient of tourism income on the Total Shock of tourism promotion budget is positive and doesn't fluctuate much over 20 quarters as shown in Figure 1. The persistent results of the policy implementation reveals that the change in tourism budget results in the foreign tourism income, but not significantly. Figure 2 indicates the response coefficient of national income to Total Shock of tourism income, which is positive and large in the first 2-3 quarters and then remains constant. For the response coefficient of national income to Total Shock of tourism promotion budgets, Figure 3 suggests some increase in national income, but the magnitude is low, indicating that tourism promotion measures have little effect on the overall growth. Lastly, the response coefficient of tourism income to Total Shock of itself, which represents the stability of the income from tourists to various changes. As shown in Figure 4, it can be concluded that tourism income responds to changes in the same direction. For example, if foreign tourists have more wealth or Positive Shock, they will travel more, or on the contrary if there are unexpected events such as terrorist attacks or political disruptions, Negative Shock, the income from tourism will decrease. However, the important observation is that when shocks occur, the initial response in the first few quarters may be large, but then it dies down. Tourism promotion policies affect national income or economic growth in two ways, directly and indirectly. Regarding the direct effect, when there is a change in tourism budgets, the tourism-related manufacturing sectors such as hotels and restaurants will respond to accommodate such changes. The expansion of these businesses to support the increase of foreign tourists will cause economic growth. As for the indirect effect, tourism promotion attracts foreign tourists to travel in Thailand and increases domestic spending. In addition, the results of the study found that the occurrence of unforeseen events such as natural disasters, political instability will affect tourism income for only a short period of time. The results of the study can be summarized into two parts: 1) Considering both direct or indirect effects, the shocks from tourism promotion policies impact national income and economic expansion even though the results are only clearly visible in the short term. Therefore, to some extent, the Thai economy fits the tourism-driven hypothesis. 2) The tourism sector in Thailand is relatively strong since it is able to respond to unexpected events quickly. The main reasons are that Thailand has a good amount of tourism supplies, including a diversity of cultural sites, natural attractions, and tourist activities. Policy recommendations: 1) The government should continue implementing the tourism measures consistently to expand the tourism industry further. 2) There should be measures to manage tourism supply, such as environmental protection, tourist site development, as well as cultivating awareness of the people to take care of natural resources. In other words, the government should focus on both the demand side and supply side of the tourist sector and other tourism-related industries to sustain the consistent growth obtained from tourism. Work Cited Antonakakis, N., Dragouni, M., Eeckels, B., & Filis, G. (2015). Tourism and Economic Growth Revisited: Empirical Evidence from a Panel VAR Approach. MPRA Paper No.67419. Ghartey, E. E. (2010). Tourism, Economic Growth and Monetary Policy Jamaica. Prepared for 11th Annual SALISES 2010 Conference in Port of Spain, Trindad–Tobago, 24–26 March 2010.
