Date: 12 February 2025, Wednesday
Time: 10.30 – 11.30
Place: MA-330
“Political Bias in the Coverage of Corporate Misconduct: Effects on Employees and Managers”
by
Minjia Zhang
University of Manchester
Abstract
We document a political bias in the media coverage of corporate violations and examine how it affects the company’s labor force. Media outlets with a political leaning that is incongruent with that of the firm tend to write articles with a more negative tone when covering the company’s misconduct. This worsens the employees’ perception of their employer, senior managers, and expectations about the company’s future, negatively affecting their productivity. It also amplifies the negative effects of low abnormal stock market performance on the likelihood of top management dismissal.
Bio
Minjia Zhang is a Ph.D. candidate in Finance at the University of Manchester, specializing in empirical corporate finance, social media, political polarization, labor, and corporate governance. She holds a M.Sc. in Accounting and Finance (Distinction) from the University of Manchester and a B.S. in Accounting (Distinction) from Zhejiang University of Finance and Economics. Her research interests include empirical corporate finance, social media, political polarization, labor, and corporate governance. She has presented her work at different international conferences, including the UK Women in Finance and the International Corporate Governance Conference. Her studies contribute to understanding how corporate policies and media influence financial and labor market dynamics. Since 2023, Minjia has worked as a teaching assistant for very large cohorts of undergraduate courses (e.g., Financial Decision Making, Foundation of Finance). She has been responsible for preparing and delivering workshops, besides holding office hours. She has also gained industry experience in credit risk management at the Bank of Ningbo, where she managed client assessments and facilitated risk analysis. Minjia is a CFA Level II candidate and possesses expertise in quantitative research methodologies, data analysis, and financial modeling. She is proficient in Stata, Python, and LaTeX, equipping her with advanced analytical capabilities for academic and professional applications. Corporate social responsibility, credit risk, financial intermediation, information flow between securities markets, and market frictions and their impact in OTC markets.