Sami Ben Jabeur

Personal Details

First Name:	Sami
Middle Name:
Last Name:	Ben Jabeur
Suffix:
RePEc Short-ID:	pbe900
	[This author has chosen not to make the email address public]

Affiliation

Institut de Préparation à l'Administration et à la Gestion (IPAG)

Paris, France
http://www.ipag.edu/
RePEc:edi:ipagpfr (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

Sorry, no citations of working papers recorded.

Articles

1. Sami Ben Jabeur & Youssef Fahmi, 2018. "Forecasting financial distress for French firms: a comparative study," Empirical Economics, Springer, vol. 54(3), pages 1173-1186, May.

   Cited by:

   1. Ding, Shusheng & Cui, Tianxiang & Bellotti, Anthony Graham & Abedin, Mohammad Zoynul & Lucey, Brian, 2023. "The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 90(C).
   2. Katarina Valaskova & Pavol Durana & Peter Adamko & Jaroslav Jaros, 2020. "Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities," JRFM, MDPI, vol. 13(5), pages 1-16, May.
   3. Amit Sareen & Sudhi Sharma, 2022. "Assessing Financial Distress and Predicting Stock Prices of Automotive Sector: Robustness of Altman Z-score," Vision, , vol. 26(1), pages 11-24, March.
   4. Cristina Zeldea, 2020. "Modeling the Connection between Bank Systemic Risk and Balance-Sheet Liquidity Proxies through Random Forest Regressions," Administrative Sciences, MDPI, vol. 10(3), pages 1-14, August.
   5. Surbhi Bhatia & Manish K. Singh, 2022. "Fifty years since Altman (1968): Performance of financial distress prediction models," Working Papers 12, xKDR.
   6. Lucia Svabova & Lucia Michalkova & Marek Durica & Elvira Nica, 2020. "Business Failure Prediction for Slovak Small and Medium-Sized Companies," Sustainability, MDPI, vol. 12(11), pages 1-14, June.
   7. Jie Sun & Mengru Zhao & Cong Lei, 2024. "Class-imbalanced dynamic financial distress prediction based on random forest from the perspective of concept drift," Risk Management, Palgrave Macmillan, vol. 26(4), pages 1-44, December.
   8. Stef, Nicolae & Bissieux, Jean-Joachim, 2022. "Resolution of corporate insolvency during COVID-19 pandemic. Evidence from France," International Review of Law and Economics, Elsevier, vol. 70(C).
   9. Ben Jabeur, Sami & Serret, Vanessa, 2023. "Bankruptcy prediction using fuzzy convolutional neural networks," Research in International Business and Finance, Elsevier, vol. 64(C).
   10. Jiaming Liu & Chengzhang Li & Peng Ouyang & Jiajia Liu & Chong Wu, 2023. "Interpreting the prediction results of the tree‐based gradient boosting models for financial distress prediction with an explainable machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1112-1137, August.
   11. David Alaminos & Manuel Ángel Fernández, 2019. "Why do football clubs fail financially? A financial distress prediction model for European professional football industry," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-15, December.
   12. Alexandra Horobet & Stefania Cristina Curea & Alexandra Smedoiu Popoviciu & Cosmin-Alin Botoroga & Lucian Belascu & Dan Gabriel Dumitrescu, 2021. "Solvency Risk and Corporate Performance: A Case Study on European Retailers," JRFM, MDPI, vol. 14(11), pages 1-34, November.
   13. Fernández-Gámez, Manuel Ángel & Soria, Juan Antonio Campos & Santos, José António C. & Alaminos, David, 2020. "European country heterogeneity in financial distress prediction: An empirical analysis with macroeconomic and regulatory factors," Economic Modelling, Elsevier, vol. 88(C), pages 398-407.

2. Sami Ben Jabeur & Asma Sghaier, 2018. "The relationship between energy, pollution, economic growth and corruption: A Partial Least Squares Structural Equation Modeling (PLS-SEM) approach," Economics Bulletin, AccessEcon, vol. 38(4), pages 1927-1946.

   Cited by:

   1. Maolin Cheng & Bin Liu, 2019. "Analysis on the Influence of China’s Energy Consumption on Economic Growth," Sustainability, MDPI, vol. 11(14), pages 1-25, July.
   2. Dmitry Burakov & Alexander Bass, 2019. "Institutional determinants of environmental pollution in Russia: a non-linear ARDL approach," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(1), pages 510-524, September.
   3. Bin Wang & Qiuxia Zheng & Ao Sun & Jie Bao & Dianting Wu, 2021. "Spatio-Temporal Patterns of CO 2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM," Mathematics, MDPI, vol. 9(21), pages 1-24, October.
   4. Jeerawadee Pumjaroen & Preecha Vichitthamaros & Yuthana Sethapramote, 2020. "Forecasting Economic Cycle with a Structural Equation Model: Evidence from Thailand," International Journal of Economics and Financial Issues, Econjournals, vol. 10(3), pages 47-57.
   5. Nicolae Stef & Sami Ben Jabeur, 2020. "Climate Change Legislations and Environmental Degradation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(4), pages 839-868, December.

3. Ben Jabeur, Sami, 2017. "Bankruptcy prediction using Partial Least Squares Logistic Regression," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 197-202.

   Cited by:

   1. Sylvia Jenčová & Róbert Štefko & Petra Vašaničová, 2020. "Scoring Model of the Financial Health of the Electrical Engineering Industry’s Non-Financial Corporations," Energies, MDPI, vol. 13(17), pages 1-17, August.
   2. Stef, Nicolae & Zenou, Emmanuel, 2021. "Management-to-staff ratio and a firm's exit," Journal of Business Research, Elsevier, vol. 125(C), pages 252-260.
   3. Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
   4. Asma Sghaier & Sami Ben Jabeur & Boutheina Bannour, 2018. "Using partial least square discriminant analysis to distinguish between Islamic and conventional banks in the MENA region," Review of Financial Economics, John Wiley & Sons, vol. 36(2), pages 133-148, April.
   5. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
   6. Sun, Xiaojun & Lei, Yalin, 2021. "Research on financial early warning of mining listed companies based on BP neural network model," Resources Policy, Elsevier, vol. 73(C).
   7. Ben Jabeur, Sami & Serret, Vanessa, 2023. "Bankruptcy prediction using fuzzy convolutional neural networks," Research in International Business and Finance, Elsevier, vol. 64(C).
   8. Daniel Ogachi & Richard Ndege & Peter Gaturu & Zeman Zoltan, 2020. "Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya," JRFM, MDPI, vol. 13(3), pages 1-14, March.
   9. ben Jabeur, Sami & Mefteh-Wali, Salma & Carmona, Pedro, 2021. "The impact of institutional and macroeconomic conditions on aggregate business bankruptcy," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 108-119.
   10. Jabeur, Sami Ben & Gharib, Cheima & Mefteh-Wali, Salma & Arfi, Wissal Ben, 2021. "CatBoost model and artificial intelligence techniques for corporate failure prediction," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
   11. Rémi Stellian & Jenny P. Danna‐Buitrago, 2020. "Financial distress, free cash flow, and interfirm payment network: Evidence from an agent‐based model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 598-616, October.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-DCM: Discrete Choice Models (2) 2014-06-07 2014-06-07
2. NEP-FOR: Forecasting (2) 2014-06-07 2014-06-07
3. NEP-MAC: Macroeconomics (2) 2014-06-07 2014-06-07
4. NEP-KNM: Knowledge Management and Knowledge Economy (1) 2014-06-07
5. NEP-RMG: Risk Management (1) 2014-06-07

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