Citation

Ahmed, Elsadig Musa (2024) Big Data Analytics Implications on Central Banking Green Technological Progress. International Journal of Information Technology & Decision Making, 23 (5). pp. 2065-2087. ISSN 0219-6220

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Abstract

This paper examines big data analytics implications on the central banking financial system’s technological progress. A digital technological progress framework and model is established to analyze the economy’s aggregate supply via covering the monetary policy, big data analytics, pollutants emissions as independent variables and the economy’s aggregate demand as a moderating variable in a modified extensive growth theory framework and model to compute the productivity indicators and the total factor productivity (TFP) as the central banking technological progress that combined the mentioned variables qualities contribution. Besides, data analytics positive and negative externalities that include data analytics shortcomings as unpriced undesirable output in the form of cybersecurity and pollutants’ emissions among other proxies are internalized in the framework and the model to integrate the digital technology innovation with digital technology shortcomings and climate change. This revised extensive theory framework and model is a remarkable technique comprehensive of the technological progress matters and sustainable economic development and is considered one of the most important sustainable development and long-run economic growth proportions in the central banking financial system functions to manage the economy’s aggregate supply and demand that unnoticed by previous studies.

Item Type:	Article
Uncontrolled Keywords:	Central bank, aggregate supply and demand, big data analytics, machine learning, artificial intelligence, financial system, technological progress, externalities
Subjects:	Q Science > QA Mathematics > QA801-939 Analytic mechanics
Divisions:	Faculty of Business (FOB)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	05 Sep 2023 00:59
Last Modified:	30 Sep 2024 08:04
URII:	http://shdl.mmu.edu.my/id/eprint/11673

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