The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses some research that is related to the seven disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas.

Additional Metadata
Keywords Big Data, Computational science, Economics, Finance, Management, 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)
Sponsor National Science Council, Ministry of Science and Technology (MOST), the Australian Research Council, Research Grants Council of Hong Kong, Asia University, China Medical University Hospital, Hang Seng Management College, Lingnan University
Persistent URL hdl.handle.net/1765/104260
Series Econometric Institute Research Papers
Citation
Chang, C-L, McAleer, M.J, & Wong, W.-K. (2018). Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections (No. EI 2018-08). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/104260