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FNEGE MEDIAS
Board Gender Quotas: Can women realistically boost firm performance
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  • Research
  • Corporate and Market Finance, Governance

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Board Gender Quotas: Can women realistically boost firm performance

This paper investigates the impact of gender quotas on firm performance using countries worldwide that have introduced a gender quota as a quasinatural experiment. Our statistical analysis shows that board members’ characteristics significantly change after implementing the gender quota. The results of our empirical analysis provide evidence that gender quotas reduce the cost of equity in the short term but decrease the Tobin’s Q in the long term and have a neutral impact on profitability in the short term and the longer term.


Mots clés
  • Corporate governance

Auteur.e(s)

TRAN Thu Ha
Associate Professor
Burgundy School of Business

Institution(s)

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Bondholder representatives on bank boards: A device for market discipline

We examine whether board representation of bondholders can be an effective market discipline mechanism to reduce bank risk, using a unique dataset combining information on bondholders and boards of directors of European listed banks. Our results show that the influence of bondholder representatives on the bank board significantly reduces bank risk without impacting profitability.
TRAN Phan Huy Hieu - Burgundy School of Business |
  • Research
  • Corporate and Market Finance

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Women in family business boards: impact and legacy

The benefit of gender diversity on the corporate boards of family firms (FFs) continues to receive growing interest. In this paper, we examine the goals of women who hold a position on the board of directors at FFs. Goal setting has been used to identify what they want to accomplish here. How do they make a difference? This question is answered through the theoretical lens of socio- emotional wealth (SEW) and goal setting. We contribute to the literature supporting gender-diverse board composition, emphasizing the goals associated with women on FF boards, and highlighting their role in family business succession. Drawing on SEW and goal setting theory, this study examines how women’s goals influence succession. Driven by the research question, our data bring together three categories of goals pursued by women in the boardroom.
EL HAYEK SFEIR Soumaya - Excelia Business School |
  • Research
  • Entrepreneurship, Governance
  • 00:02:43

What is the Initial Coin Offering?

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DELL’ERA Michele - EDC Business School |
  • Management Dictionary
  • Corporate and Market Finance, Entrepreneurship
  • 00:04:23

Environmental Tax Policies in Emerging Markets: Does Confidence in Political Institutions Matter?

The goal of this study is to examine how environmental taxes influence the comparative advantage in environmental products and carbon emissions within emerging economies. To gain a better understanding, we examine whether this impact changes depending on the level of government integrity. The results indicate that increased environmental taxes mitigate the comparative advantage in environmental goods for emerging markets. However, for countries with high levels of government integrity, higher environmental taxes enhance their competitive edge in environmental goods. Additionally, our findings show that although a rise in environmental taxes is associated with higher carbon emissions, raising such taxes results in a reduction in carbon emissions for emerging economies with solid government integrity. These findings suggest that robust political institutions are crucial in promoting the comparative advantage of emerging markets in environmental goods and mitigating climate change. In the absence of substantial confidence in political or governmental institutions, the efficient implementation of climate taxes poses considerable challenges. Furthermore, we observe that an increase in the comparative advantage of environmental goods results in a decrease in carbon emissions.
KOCAARSLAN Baris - EDC Business School |
  • Research
  • Corporate and Market Finance
  • 00:03:47

In Machine Learning We Trust: A Bankruptcy Prediction Application

Recently, ensemble-based machine learning models have been widely adopted and have demonstrated their effectiveness in bankruptcy prediction. However, these algorithms often function as black boxes, making it difficult to understand how they generate forecasts. This lack of transparency has led to growing interest in interpretability methods within artificial intelligence research. In this paper, we assess the predictive performance of Random Forest, LightGBM, XGBoost, and NGBoost (Natural Gradient Boosting for probabilistic prediction) on French firms across various industries, with a forecasting horizon of one to five years. We then apply Shapley Additive Explanations (SHAP), a model-agnostic interpretability technique, to explain XGBoost, one of the best-performing models in our study. SHAP highlights the contribution of each feature to the model’s predictions, enabling a clearer understanding of how financial and macroeconomic factors influence bankruptcy risk. Moreover, it allows for the explanation of individual predictions, making black-box models more applicable in credit risk management.
NGUYEN Hoang Hiep - EM Normandie |
  • Research
  • Corporate and Market Finance
Corporate and Market Finance
Governance

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