Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods

29 Pages Posted: 28 Nov 2020

See all articles by Saeed Nosratabadi

Saeed Nosratabadi

Hungarian University of Agriculture and Life Sciences

Amir Mosavi

affiliation not provided to SSRN

Puhong Duan

Hunan University

Pedram Ghamisi

Helmholtz-Zentrum Dresden-Rossendorf

Filip Ferdinand

J. Selye University

Shahaboddin Shamshirband

Ton Duc Thang University

Uwe Reuter

Dresden University of Technology

João da Gama Batista

CentraleSupélec

Amir H Gandomi

Stevens Institute of Technology - School of Business

Date Written: October 14, 2020

Abstract

This paper provides a state-of-the-art investigation on advances in data science in emerging economic applications. Analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

Keywords: data science; deep learning; ensemble machine learning models; economics; hybrid machine learning

Suggested Citation

Nosratabadi, Saeed and Mosavi, Amir and Duan, Puhong and Ghamisi, Pedram and Ferdinand, Filip and Shamshirband, Shahaboddin and Reuter, Uwe and da Gama Batista, João and Gandomi, Amir H, Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods (October 14, 2020). Available at SSRN: https://ssrn.com/abstract=3711309 or http://dx.doi.org/10.2139/ssrn.3711309

Saeed Nosratabadi (Contact Author)

Hungarian University of Agriculture and Life Sciences ( email )

Hungary

Amir Mosavi

affiliation not provided to SSRN

Puhong Duan

Hunan University ( email )

2 Lushan South Rd
Changsha, CA Hunan 410082
China

Pedram Ghamisi

Helmholtz-Zentrum Dresden-Rossendorf ( email )

Bautzner Landstraße 400
Dresden, 01328
Germany

Filip Ferdinand

J. Selye University ( email )

Slovakia

Shahaboddin Shamshirband

Ton Duc Thang University ( email )

19 Nguyen Huu Tho
District 7
Ho Chi Minh City, Ho Chi Minh 0848
Vietnam

Uwe Reuter

Dresden University of Technology ( email )

Einsteinstrasse 3
Dresden, 01062
Germany

João da Gama Batista

CentraleSupélec ( email )

Labo M.A.S
Grande Voie des Vignes
Châtenay-Malabry CEDEX, 92295
France

Amir H Gandomi

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States
2012165029 (Phone)

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