Presentation Schedule
Using ARIMA Forecast for Scenario Projections to Compare Funding Mechanisms in the Singaporean Arts Sector (110029)
Session: On Demand
Room: Virtual Poster Presentation
Presentation Type:Virtual Poster Presentation
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 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. A multi-method forecasting framework is applied, where ARIMA time-series models are combined with regression-based scenario analysis. Approaching the problem in three stages: Stage 1 - Baseline Forecasting ARIMA models were fitted to historical data for employees, employee costs, and income to establish baseline projections for FY2025 absent policy intervention. Stage 2 - Regression Modelling Linear regression models were estimated to quantify relationships between income and both employment and employee costs. Such models allow scenario-based projections that make changes in income levels translate into workforce implications. Stage 3 - Scenario Projection For each scenario, the model adjusted baseline income projections according to the assumed uplift under that scenario, and projected the employment and cost outcomes
Authors:
Amberyce Ang, Singapore University of Social Sciences, Singapore
Elijah Loy, Hwa Chong Institution, Singapore
About the Presenter(s)
Amberyce Ang
Senior research specialist with the National council of social services, Singapore
See this presentation on the full schedule – On Demand Schedule
Virtual Poster Presentation
Conference Comments & Feedback
Place a comment using your LinkedIn profile[wplinkpress_comments]
Share this Presentation
