Template-Type: ReDIF-Paper 1.0
Author-Name: Chang, C-L.
Author-Name-Last: Chang
Author-Name-First: Chia-Lin
Author-Person: pch286
Author-Name: McAleer, M.J.
Author-Name-Last: McAleer
Author-Name-First: Michael
Author-Person: pmc90
Author-Name: Wong, W.-K.
Author-Name-Last: Wong
Author-Name-First: Wing-Keung
Author-Person: pwo79
Title: Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections
Abstract: 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.
Length: 55
Creation-Date: 2018-01-01
File-URL: https://repub.eur.nl/pub/112499/Repub_112499.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI2018-08
Classification-JEL: G00, G31, O32
Keywords: Big Data, Computational science, Economics, Finance, Management, Theoretical models, Econometric and statistical models, Applications.
Handle: RePEc:ems:eureir:112499