International Journal of Social Science & Economic Research
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BALAR Khalid and CHAABITA Rachid

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BALAR Khalid1 and CHAABITA Rachid2
1,2. Department of Economic Science and Management, Hassan II University/Faculty of Economic and Social Legal Sciences Ain Chock, Casablanca, Morocco

Khalid, BALAR, and CHAABITA Rachid. "BIG DATA IN ECONOMIC ANALYSIS: ADVANTAGES AND CHALLENGES." Int. j. of Social Science and Economic Research, vol. 4, no. 7, July 2019, pp. 5196-5204, Accessed July 2019.
Khalid, B., & Rachid, C. (2019, July). BIG DATA IN ECONOMIC ANALYSIS: ADVANTAGES AND CHALLENGES. Int. j. of Social Science and Economic Research, 4(7), 5196-5204. Retrieved from
Khalid, BALAR, and CHAABITA Rachid. "BIG DATA IN ECONOMIC ANALYSIS: ADVANTAGES AND CHALLENGES." Int. j. of Social Science and Economic Research 4, no. 7 (July 2019), 5196-5204. Accessed July, 2019.

[1]. New Horizons for a Data-Driven Economy - Springer. doi:10.1007/978- 3-319-21569-3
[3]. Taylor, Shroeder and Meyer
[4]. Schroeder, cprof- 9780199661992-chapter-11
[5]. K. Balar and A. Naji, A Model for Predicting Ischemic Stroke Using Data Mining Algorithms IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 11, November 2015.
[6]. Hilbert, Martin. "Big Data for Development: A Review of Promises and Challenges. Development Policy Review.". Retrieved 2015-10-07.
[9]. Choi and Varian's, 4932.2012.00809.x/full
[10]. Brynjolffson's DB%202012-12- 12.pdf
[11]. Choi and Varian, 4932.2012.00809.x/full
[12]. Moat et al.
[13]. Einav et al. 033_Paper_Einav_10.pdf
[14]. Friedman and Rockoff,
[15]. Scott Keeter,
[16]. Einav, Farronato and Levin,
[17]. Einav, Les lecteurs interesses par ces nouvelles techniques pourront consulter le papier de Hal Varian, "Big Data: New Tricks for Econometrics" (,
[18]. Jenkins and Levin,
[20]. Sascha Becker,
[21]. Kaiser Fung,
[22]. Marcus and Davis,
[23]. Barry Eichengreen,

In this paper, we focus on the impact of big data in the economic field. The potential for big data and Predictive Analytics to improve outcomes is tremendous. We discuss some of the latest (and most interesting) methods currently available for analyzing and utilizing big data when the objective is improved prediction. Our discussion includes a summary of various so?called dimension reduction and machine learning methods as well as a summary of recent tools that are useful for ranking prediction models associated with the implementation of these methods. We also provide a brief empirical illustration of big data in action, in which we show that the granularity and multidimensionality of big data offers advantages to economists in identifying economic trends when they occur (nowcasting), testing the behavioral theories of previously untested agents, and creating a set of tools for manipulating and analyzing this data. However, even though these new databases and statistical techniques open up many opportunities, they also pose many challenges for economists: access to these data, the ability to replicate them, and the development of technical skills to manipulate them. Also, closer collaboration between big data companies and researchers working on Big Data would be highly beneficial for the advancement of economic discipline.