Using ARIMA Forecast for Scenario Projections to Compare Funding Mechanisms in the Singaporean Arts Sector

This study uses Autoregressive Integrated Moving Average (ARIMA) forecasting models and regression analysis to explore the impact of three government funding mechanisms on financial sustainability in Singapore’s arts and heritage sector. Based on data obtained from the Ministry of Culture, Community and Youth (MCCY) for FY (FY refers to “Financial Year”, which is generally from 1 April to 31st March of the following year) 2022-2024, we modelled three funding scenarios: direct organisational grants (Scenario A), citizen-directed cultural vouchers (Scenario B), and a hybrid model combining both approaches (Scenario C). The results showed that while direct funding provides the most significant immediate capacity increase, a hybrid model provides a better balance between organisational stability and demand, thereby offering a more sustainable pathway for sector development. Our study makes a methodological contribution by illustrating the application of ARIMA forecasting to cultural policy evaluation, and compared the outcome of supply-side and demand-side interventions in the cultural sector.