Impact of COVID-19 Pandemic on Thailand Economy and Tourist Industry: An Empirical Forecasting Using ARIMA

Abstract

Goal:The tourism sector always plays a vital role among other sectors, which contributes heavily to Thailand's GDP. Due to the recent Pandemic crises, the tourism industry worldwide faces a decline. The aim of writing this paper is to forecast, tourist inflow for Thailand for the next nine months by using ARIMA forecasting Design / Methodology / Approach: In order to meet the study objective, we adopted the univariate time series forecasting of tourist arrival. The AR(12) and MA(12) process with d(1) order to specify the appropriate model also applied for forecasting selection of international tourist arrivals, after diagnostic checking of series through correlogram Q-statistics and correlogram of residuals for adjusted ARIMA (12,1,12) in which we found low residual against 70 lags. Results:The evidence predicts that in the next nine months, Thailand will face significant negative zone arrival of international tourists due to the COVID-19 pandemic crises, which adversely affect Thailand's economy due to the shortfall of international tourist arrivals. However decline in tourist arrival will eventually decrease air pollution in Thailand, thus it positively impact on environmental quality. Limitations of the investigation:In terms of limitation of this study, this forecasting is only valid for Thailand based on historical and current data. Practical implications:We highly recommend government of Thailand for enchasing overall logistics performance and furthermore increase use to renewable energy and green performance in their tourism sector.Originality / Value: This study provides tourism forecasting estimation for Thailand, which can help government to reshape their tourism policies due to Covid-19 pandemic crises. As this study is the first attempt to provide forecasting related with Covid-19 for tourism sector.

A Review Research on Tourism in the Green Economy

“…In general, green energy plays a leading role in transitioning to a green economy (Potts et al 2019), particularly in tourist destinations in emerging economies (Tazikhina et al 2022;Huang et al 2021). Several articles study various initiatives in the adoption of renewable energy sources (Khan et al 2022;Janjua et al 2021;; with 102 citations, Hens et al (2018) authored the most cited articles in the area. On the demand side, the behaviour of energy consumption is also a frequently analysed aspect (Ohajionu et al 2022), with specific studies carried out on energy consumption during the COVID-19 pandemic (Strielkowski et al 2021).…”

Classical Forecasting of International Tourist Arrivals to Thailand

“…In the other way, based on the imputation method of the spatial weighting method, ANN outperformed. Lately, in 2021, Janjua et al [ 13 ] adopted the univariate time series forecasting method of tourist arrival based on the data from January 1991 to March 2020. The ARIMA(12, 1, 12) was suggested to forecast the international arrival from April 2020 to December 2020.…”

“…From the forecasting methods mentioned above, different models have been applied and developed for tourism demand forecasting. They corporate the classical approach [ 5 – 13 ], the machine learning approach [ 11 , 13 ], and the combination of classical approaches and/or the machine learning approaches [ 6 , 8 , 9 , 11 , 13 ]. The objective of this paper is to apply three classical forecasting methods: decomposition, Holt–Winter’s exponential smoothing and the Box–Jenkins to get the estimate of the tourism demand base on the monthly historical time series from 2008 to 2019.…”

La pandemia: impacto económico y pronóstico de recuperación

“…En la literatura se pueden encontrar trabajos que han utilizado esta metodología para pronosticar el comportamiento de la economía, a partir de la crisis desencadenada por el Covid-19. Por ejemplo, Janjua et al, (2021), pronosticaron el flujo de turismo para un país como Tailandia, cuya economía depende de los ingresos de los turistas. Con diferentes proyecciones ARIMA, ellos encontraron que el turismo se reduciría en los siguientes nueve meses.…”