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Modern Financial Econometrics
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Modern Financial Econometrics

A special issue of International Journal of Financial Studies (ISSN 2227-7072).

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1586

Special Issue Editors

Prof. Dr. Nicholas Giannakopoulos

E-Mail Website
Guest Editor
Bictevac Laboratory—Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece
Interests: fintech; supply chain; finance; CeFi; DeFi; strategic digital marketing; big data; statistics; econometrics; decision support systems (DSSs)
Dr. Nikos Kanellos

E-Mail Website
Guest Editor
Bictevac Laboratory—Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece
Interests: entrepreneurship; innovation; business model innovation; technology and innovation; innovation management; crisis management

Special Issue Information

Dear Colleagues,

The Special Issue titled “Modern Financial Econometrics” focuses on the integration of econometric analysis with emerging technologies such as fintech, big data, and web analytics. Its main foci are developing and applying advanced econometric techniques to better understand and predict financial phenomena.

This Special Issue’s scope covers a wide range of topics: the impact of digital marketing on financial markets, the utilization of big data for enhanced econometric models, and the role of econometric analysis in optimizing supply chain and logistics operations within the financial sector. Its purpose is to provide a platform for cutting-edge research that bridges traditional financial studies with modern technological advancements, offering new insights and methodologies.

This Special Issue situates itself within the existing literature by expanding on established econometric theories and incorporating novel approaches from the realms of fintech and digital analytics. It will address contemporary challenges faced by the financial industry through interdisciplinary research, thus enhancing the practical applications of econometric analysis.

By doing so, it not only contributes to the theoretical advancement of financial econometrics but also provides practical tools and strategies for industry practitioners, reinforcing the vital connection between academic research and real-world financial applications.

Prof. Dr. Nicholas Giannakopoulos
Dr. Nikos Kanellos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Financial Studies is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • econometric models
  • fintech
  • big data
  • financial applications
  • supply chain sector
  • technological advancements

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

19 pages, 836 KiB  
Article
GINI’s Odyssey in Greece: Econometric Analysis of Income Inequality, GDP, and Unemployment Through Economic Phases (Pre-Crisis, Crisis, Memoranda, and Post-Memoranda)
by Panagiotis Karountzos, Nikolaos T. Giannakopoulos, Damianos P. Sakas, Kyriaki I. Efthalitsidou and Stavros P. Migkos
Int. J. Financial Stud. 2024, 12(4), 129; https://doi.org/10.3390/ijfs12040129 - 23 Dec 2024
Viewed by 1106
Abstract
This study explores the relationship between income inequality, economic growth, and unemployment in Greece from 2003 to 2020, encompassing key economic phases: pre-crisis, crisis, memoranda, and post-memoranda. The aim is to analyze how economic growth (logarithm of GDP-LOGGDP) and unemployment influenced income inequality [...] Read more.
This study explores the relationship between income inequality, economic growth, and unemployment in Greece from 2003 to 2020, encompassing key economic phases: pre-crisis, crisis, memoranda, and post-memoranda. The aim is to analyze how economic growth (logarithm of GDP-LOGGDP) and unemployment influenced income inequality (GINI coefficient) during periods of economic turmoil and recovery. Using linear regression analysis on 18 years of annual data, this study identifies significant relationships between the variables, with diagnostic tests confirming model robustness. The findings reveal a strong positive and statistically significant relationship between LOGGDP and income inequality, indicating that economic growth, without effective redistributive mechanisms, exacerbated disparities. Unemployment had an even stronger positive effect on inequality, highlighting its role in deepening income disparities, particularly during the crisis years marked by economic contraction and austerity measures. These results underline the critical need for balanced economic policies that promote inclusive growth while addressing structural inequalities and labor market vulnerabilities. This study also employs advanced econometric methods, including Vector Autoregression (VAR), Vector Error Correction Model (VECM), and Granger Causality Test, to analyze the dynamics between GDP (LOGGDP), income inequality (GINI), and unemployment. The Granger Test reveals that unemployment Granger-causes GDP with a two-period lag, highlighting the importance of labor market conditions for economic growth, while no direct causal relationship is found between GDP and inequality. These methods provide deeper insights into the short- and long-term interactions, offering valuable guidance for balanced economic policymaking. Full article
(This article belongs to the Special Issue Modern Financial Econometrics)
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