Abstract:
This research discusses the use of Business Intelligence in macroeconomic forecasting and how the improved forecasting will assist better monetary policy decision making in Sri Lanka. Various macroeconomic factors are analyzed and forecasted in order to make accurate policy decisions. Forecasting is usually done over diverse statistical models and techniques. The effective policy decision making will help the government for maintaining price stability, for making right decisions over perceiving future of the economy and for futuristic planning.
The research was based on qualitative case study methodology. A case study was conducted at the Central Bank of Sri Lanka and data was collected through personal interviews by using semi structured questionnaire. The main focus is to understand the process of monetary policy decision making, how macroeconomic forecasting has been done, limitations of the existing forecasting process and the possibility of using Business Intelligence in forecasting to improve policy decision making.
Interviews were carried out with experts in Department of Economic Research, Department of statistics, Central Bank of Sri Lanka, Institute of Policy Studies and with other experts in field of econometrics and economic modeling. The research further discussed how limitations of current approaches could be addressed over today’s emerging concepts like business intelligence, neural networks. This study would provide guidance in developing a better forecasting model for Sri Lanka in the future.
