Léa H. Stern

856 total citations
15 papers, 404 citations indexed

About

Léa H. Stern is a scholar working on Accounting, Finance and Strategy and Management. According to data from OpenAlex, Léa H. Stern has authored 15 papers receiving a total of 404 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Accounting, 4 papers in Finance and 2 papers in Strategy and Management. Recurrent topics in Léa H. Stern's work include Corporate Finance and Governance (10 papers), Private Equity and Venture Capital (5 papers) and Financial Markets and Investment Strategies (4 papers). Léa H. Stern is often cited by papers focused on Corporate Finance and Governance (10 papers), Private Equity and Venture Capital (5 papers) and Financial Markets and Investment Strategies (4 papers). Léa H. Stern collaborates with scholars based in United States, Canada and Belgium. Léa H. Stern's co-authors include M. Martin Boyer, Michael S. Weisbach, Berk A. Sensoy, Ji‐Woong Chung, Isil Erel, Chenhao Tan, Benjamin Bennett, Peter J. McDonnell, J.J. Doyle and Ashley Behrens and has published in prestigious journals such as Review of Financial Studies, Journal of Corporate Finance and Journal of Financial Intermediation.

In The Last Decade

Léa H. Stern

13 papers receiving 377 citations

Peers

Léa H. Stern

ACCOU

EE

FINAN

SM

MIS

Richard A. Cazier United States

Marc Steffen Rapp Germany

Nur Adiana Hiau Abdullah Malaysia

Korok Ray United States

Francesca Battaglia Italy

Abdulkadir Mohamed United Kingdom

Elisabete Gomes Santana Fėlix Portugal

Jian Cao United States

Soon Suk Yoon United States

Dimitris Balios Greece

Richard A. Cazier United States

Léa H. Stern

421 ×1.3

ACCOU

160 ×1.1

EE

99 ×0.9

FINAN

130 ×1.9

SM

26 ×0.6

MIS

Citations per year, relative to Léa H. Stern Léa H. Stern (= 1×) peers Richard A. Cazier

Countries citing papers authored by Léa H. Stern

Since Specialization

Citations

This map shows the geographic impact of Léa H. Stern's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Léa H. Stern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Léa H. Stern more than expected).

Fields of papers citing papers by Léa H. Stern

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Léa H. Stern. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Léa H. Stern. The network helps show where Léa H. Stern may publish in the future.

Co-authorship network of co-authors of Léa H. Stern

This figure shows the co-authorship network connecting the top 25 collaborators of Léa H. Stern. A scholar is included among the top collaborators of Léa H. Stern based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Léa H. Stern. Léa H. Stern is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

1.

Stern, Léa H., et al.. (2023). Stereotypes about Successful Entrepreneurs. AEA Papers and Proceedings. 113. 186–190.

2.

Stern, Léa H., et al.. (2022). Venture Capital (Mis)Allocation in the Age of AI. SSRN Electronic Journal. 9 indexed citations

3.

Stern, Léa H., et al.. (2022). <p>Machine Learning About Venture Capital Choices</p>. SSRN Electronic Journal.

4.

Erel, Isil, Léa H. Stern, Chenhao Tan, & Michael S. Weisbach. (2021). Selecting Directors Using Machine Learning. Review of Financial Studies. 34(7). 3226–3264. 97 indexed citations

5.

Bennett, Benjamin, et al.. (2020). Paid Leave Pays Off: The Effects of Paid Family Leave on Firm Performance. SSRN Electronic Journal. 4 indexed citations

6.

Erel, Isil, Léa H. Stern, Chenhao Tan, & Michael S. Weisbach. (2018). Selecting Directors Using Machine Learning. SSRN Electronic Journal. 7 indexed citations

7.

Erel, Isil, Léa H. Stern, Chenhao Tan, & Michael S. Weisbach. (2018). Selecting Directors Using Machine Learning. SSRN Electronic Journal. 7 indexed citations

8.

Stern, Léa H.. (2017). A Learning-Based Approach to Evaluating Boards of Directors. SSRN Electronic Journal. 1 indexed citations

9.

Stern, Léa H.. (2015). A Learning-Based Approach to Evaluating Boards of Directors. SSRN Electronic Journal. 5 indexed citations

10.

Boyer, M. Martin & Léa H. Stern. (2014). D&O insurance and IPO performance: What can we learn from insurers?. Journal of Financial Intermediation. 23(4). 504–540. 52 indexed citations

11.

Boyer, M. Martin & Léa H. Stern. (2013). D&O Insurance and IPO Performance: What Can We Learn from Insurers?. SSRN Electronic Journal. 2 indexed citations

12.

Chung, Ji‐Woong, Berk A. Sensoy, Léa H. Stern, & Michael S. Weisbach. (2012). Pay for Performance from Future Fund Flows: The Case of Private Equity. Review of Financial Studies. 25(11). 3259–3304. 143 indexed citations

13.

Boyer, M. Martin & Léa H. Stern. (2012). Is corporate governance risk valued? Evidence from directors' and officers' insurance. Journal of Corporate Finance. 18(2). 349–372. 43 indexed citations

14.

Stern, Léa H. & M. Martin Boyer. (2010). Is Corporate Governance Risk Valued? Evidence from Directors’ and Officers’ Insurance. SSRN Electronic Journal. 33 indexed citations

15.

McDonnell, Peter J., J.J. Doyle, Léa H. Stern, & Ashley Behrens. (2004). A Modified Delphi Technique to Obtain Consensus on the Treatment of Dysfunctional Tear Syndrome. 45(13). 3909–3909. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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