Proceedings of the 2026 5th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2026

2026 5th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2026

📍Guiyang, China🗓️ 17-19 July 2026

Optimism Bias in Earnings Forecasts, Financial Leverage, and Corporate Earnings Management——Empirical Evidence from the Perspective of Managerial Overconfidence

Authors
Jing Wang1, *
1Guangdong University of Science and Technology, Dongguan, 523000, China
*Corresponding author. Email: 798999717@qq.com
Corresponding Author
Jing Wang
Available Online 11 September 2026.
DOI
10.2991/978-94-6239-774-3_17How to use a DOI?
Keywords
optimism bias in earnings forecasts; managerial overconfidence; financial leverage; earnings management; financing structure
Abstract

Using Chinese A-share listed companies from 2016 to 2024 as the research sample, this study examines the effect of optimism bias in earnings forecasts on earnings management and its transmission mechanism from the perspective of managerial overconfidence. Because the conventional optimistic earnings forecast dummy variable (OC) only identifies the direction of the forecast and cannot adequately distinguish improvements in firm fundamentals from strategic disclosure, this study constructs a continuous indicator, OCBias, to capture unrealized optimistic expectations by measuring the extent to which the midpoint of the forecasted profit range exceeds actual profit. The results show that the coefficient of the conventional OC variable is positive but insignificant in the baseline model, whereas OCBias is significantly and positively associated with earnings management; this finding remains robust across alternative measurements and robustness tests. Financial leverage serves as a significant transmission channel. Profitability significantly strengthens the relationship between the conventional OC indicator and earnings management, whereas the moderating effect is not significant when the continuous OCBias measure is used. In ownership-based subsample tests, the positive association between OCBias and earnings management is significant for both state-owned and non-state-owned enterprises, while the between-group difference is not statistically significant. This study extends research on the determinants of earnings management by integrating managerial expectation bias with financing structure and provides empirical evidence for identifying financial reporting risk among listed firms.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2026 5th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2026
Series
Advances in Economics, Business and Management Research
Publication Date
11 September 2026
ISBN
978-94-6239-774-3
ISSN
2352-5428
DOI
10.2991/978-94-6239-774-3_17How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Jing Wang
PY  - 2026
DA  - 2026/09/11
TI  - Optimism Bias in Earnings Forecasts, Financial Leverage, and Corporate Earnings Management——Empirical Evidence from the Perspective of Managerial Overconfidence
BT  - Proceedings of the 2026 5th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2026
PB  - Atlantis Press
SP  - 184
EP  - 201
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-774-3_17
DO  - 10.2991/978-94-6239-774-3_17
ID  - Wang2026
ER  -