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The country ICT level and the Fintech firm Performance: Evidence from BRICS ‎Countries ‎

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  • NEIFAR, MALIKA
  • Gharbi, Leila

Abstract

Purpose The scope of this paper is to investigate if the information and communications ‎technology (ICT) can improve the FinTech firm performance in the BRICS countries from ‎monthly macro time series data during 2014M01-2022M12. ‎ Design/methodology/approach Through the Bayesian VAR-X approach and the time series ‎DYNARDL simulation models, we investigate the impact of the ICT and its components on ‎the firm performance for both the short-run (SR) and the long-run (LR) historical and ‎predictive trend. Besides these regression models, this study applies the Granger Causality ‎‎(GC) in quantile and the frequency domain (FD) GC tests to show more details about the ‎causality linkage.‎ Findings From the BVAR-X approach, historical IRFs conclude that the ICT has positive ‎effect on PI for all countries in the SR and a positive effect in the LR only for China. From ‎the DYNARDL simulation models, predictive IRFs results corroborate with the historical ‎IRFs results except for the China and SA in the SR and for Brazil and India in the LR. We ‎conclude in addition that the predictive positive relationships is driven by MCS for Brazil, IUI ‎for China, FBS for SA, and all of the ICT components for the India case. GC type test results ‎are in accordance with previous results. ‎ Originality The novelty of this research is based on the idea of studying the effect of the ICT ‎on FinTech firm performance by using several time series data based dynamic technics so that ‎we can estimate and predict the SR adjustments that arise from the impact of ICT to the LR ‎relationship with the firm profitability. ‎

Suggested Citation

  • NEIFAR, MALIKA & Gharbi, Leila, 2025. "The country ICT level and the Fintech firm Performance: Evidence from BRICS ‎Countries ‎," MPRA Paper 123778, University Library of Munich, Germany, revised 25 Feb 2025.
    • Handle: RePEc:pra:mprapa:123778
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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

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