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Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections

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

No 18-024/III, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: 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.

Keywords: Decision sciences; economics; finance; business; computing; and big data; 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)
New Economics Papers: this item is included in nep-big, nep-cmp, nep-hpe, nep-ict and nep-upt
Date: 2018-03-01
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Working Paper: Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections (2018) Downloads
Working Paper: Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections (2018) Downloads
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