Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Chia-Lin Chang (), Michael McAleer and Wing-Keung Wong

No EI2018-08, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

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.

Keywords: Big Data; Computational science; Economics; Finance; Management; Theoretical models; Econometric and statistical models; Applications. (search for similar items in EconPapers)
JEL-codes: G00 G31 O32 (search for similar items in EconPapers)
Pages: 55
Date: 2018-01-01
New Economics Papers: this item is included in nep-big, nep-cmp and nep-mkt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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https://repub.eur.nl/pub/112499/Repub_112499.pdf (application/pdf)

Related works:
Journal Article: Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections (2018)
Working Paper: Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections (2018)
Working Paper: Big data, computational science, economics, finance, marketing, management, and psychology: connections (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureir:112499

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