This paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas.

Additional Metadata
Keywords Decision sciences, economics, finance, business, computing, and big data, theoretical models, econometric and statistical models, applications
JEL General Economics: General (jel A10), Financial Economics: General (jel G00), Capital Budgeting; Investment Policy (jel G31), Management of Technological Innovation and R&D (jel O32)
Persistent URL hdl.handle.net/1765/105878
Series Tinbergen Institute Discussion Paper Series , Econometric Institute Research Papers
Citation
Chang, C-L, McAleer, M.J, & Wong, W.-K. (2018). Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections (No. EI2018-13). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/105878