Planning for business cycle fluctuations in budgeting: The application of innovative data sources and techniques

Abstract

Severe economic crises, such as the COVID-19 pandemic, have illustrated that failure to plan for such inevitable but unpredictable events in budgetary processes adversely impacts the delivery of services. An expansion of planning and forecasting capabilities is required to improve budgetary processes. We aim to contribute by empirically investigating how the impact of the business cycle can be measured and used to enhance budgetary planning in a healthcare context. Specifically, we employ the time series vector autoregression technique to analyse the dynamic relationship between Gross Domestic Product and health expenditure. Our findings reveal that health expenditure is highly sensitive to GDP shocks, and that these effects persist over multiple years. By integrating the impact of the business cycle into the budgetary process, we demonstrate improved sophistication and accuracy in both annual and multi-year budgeting, as well as in long-term budget planning. In conclusion, our findings offer valuable insights into the multi-year impacts of economic shocks on budgets, thereby strengthening resilience and facilitating improved budget adaptation in anticipation of unforeseen events.