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Does ICT Drive Fintech firm Performance? Evidence from BRICS ‎Countries ‎

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  • Neifar, Malika

Abstract

Purpose: The scope of this paper is to see if the aggregate information and communications technology index (ICT) drives firm performance (profitability and efficiency) for BRICS countries from a des-aggregate panel data of the firm-yearly level (by country) during 2014-2022, from an aggregate monthly time series data and a panel data of country-monthly level during 2014-01-2014-12, all covering the Covid outbreak event. Design/methodology/approach: Through static and dynamic long-run (LR) panel models, the Bayesian VAR-X short-run (SR) approach, and the time series and the panel (LR and SR) ARDL models, we investigate the stability of the linkage between firm performance and the aggregate ICT vis à vis the Covid outbreak. Findings: Using an international sample of 316 FinTech firms from BRICS countries, we find that ICT mechanisms on their own are in general negatively associated with firm performance (profitability and efficiency) with some exceptions. We also find that the ICT and the firm-performance relationship is more significant among countries with respect to the considered pre ou post Covid 19 outbreak period. Originality: The novelty of this research is based on the idea of studying the effect of the aggregate ICT on firm performance by using several dynamic approaches so that we can estimate the SR adjustments that arise from the impact of ICT to the LR relationship.

Suggested Citation

  • Neifar, Malika, 2024. "Does ICT Drive Fintech firm Performance? Evidence from BRICS ‎Countries ‎," MPRA Paper 121772, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:121772
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    More about this item

    Keywords

    FinTech Firm performance and ICT; BRICS area; Dynamic Panel Regressions and GMM for ‎firm level panel data; Bayesian VAR-X and ARDL models for TS data; PARDL for macro ‎panel data; Covid 19 outbreak‎;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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