This study utilized datasets on inbound tourism expenditure by product at current prices for the period of 2019–2023. The researchers investigate the trends in tourism sector spending through the major categories. The focus of the study is on forecasting based on future spending patterns within the categories of accommodation, food and beverage services, transportation, shopping, travel agencies/other reservation services, and entertainment/recreational services with the use of GRETL software for the ARIMA model on time-series forecasting. Forecasting results of the inbound tourism expenditure shows that accommodation has the highest constantly accrued expenditure, and significant differences exist between food and beverage services and other categories, with the latter registering minimal spending. Accommodation, food and beverage services recorded steady increases in expenditures. On the other hand, shopping, transportation, and recreation activities experienced relatively slow growth from the predicted years. These predictions thus require acute interventions that solve the issue sector-wise and improve the tourism industrys appeal. Future studies should focus on what factors are supporting such trends and introduce alternative models for better forecasting.

Economic Development

Spending Patterns

Time-Series Analysis

ARIMA Modeling

Inbound Tourism Expenditure