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Does Information Asymmetry Affect Corporate Tax Aggressiveness?

Published online by Cambridge University Press:  05 September 2017

Tao Chen  and
Chen Lin
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Abstract

We investigate the effect of information asymmetry on corporate tax avoidance. Using a difference-in-differences matching estimator to assess the effects of changes in analyst coverage caused by broker closures and mergers, we find that firms avoid tax more aggressively after a reduction in analyst coverage. We further find that this effect is mainly driven by firms with higher existing tax-planning capacity (e.g., tax-haven presence), smaller initial analyst coverage, and a smaller number of peer firms. Moreover, the effect is more pronounced in industries where reputation matters more and in firms subject to less monitoring from tax authorities.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 52 , Issue 5 , October 2017 , pp. 2053 - 2081
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2017 

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Footnotes

1

We thank Paul Malatesta (the editor) and an anonymous referee for their very valuable and constructive comments and suggestions. We are grateful for constructive comments and discussions from Thorsten Beck, Candie Chang, Xin Chang (Simba), Jianguo Chen, Agnes Cheng, Louis Cheng, Jing Chi, Tarun Chordia, Stephen Dimmock, Huasheng Gao, Zhaoyang Gu, Xiaoxiao He, Chuan Yang Hwang, Kose John, Jun-Koo Kang, Young Sang Kim, Kai Li, Wei-Hsien Li, Angie Low, Chris Malone, John G. Matsusaka, Mujtaba Mian, James Ohlson, Kwangwoo Park, Xuan Tian, Naqiong Tong, Wilson Tong, David Tripe, Kam-Ming Wan, Albert Wang, Cong Wang, Chishen Wei, Scott Yonker, Hua Zhang, Lei Zhang, and conference and seminar participants at the 2015 China International Conference in Finance (CICF), 2014 International Conference on Asia-Pacific Financial Markets (CAFM), 2015 Auckland Finance Meeting, 2015 Conference on the Theories and Practices of Securities and Financial Markets, 2014 Australasian Finance and Banking Conference (AFBC), Massey University, Nanyang Technological University, Hong Kong Polytechnic University, Xiamen University, and Chinese University of Hong Kong. We thank Scott Dyreng for providing the Exhibit 21 data. Chen is grateful for the financial support from Singapore Ministry of Education Academic Research Fund Tier 1 (Reference number: RG58/15). Lin gratefully acknowledges the financial support from the Research Grants Council of Hong Kong (Project No. T31/717/12R).

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