Big data, computational science, economics, finance, marketing, management, and psychology: connections

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

No 2018-05, Documentos de Trabajo del ICAE from Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico

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: A10 G00 G31 O32 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2018-01
New Economics Papers: this item is included in nep-big and nep-cfn
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https://eprints.ucm.es/id/eprint/46293/1/1805.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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