Relationship-based resource allocations : Evidence from the Use of Guanxi during SEOs

Paul BROCKMAN, Michael Arthur FIRTH, Xianjie HE, Xinyang MAO, Oliver RUI

Research output: Journal PublicationsJournal Article (refereed)peer-review

22 Citations (Scopus)


We examine the role of relationship-based resource allocations during the approval process of seasoned equity offerings (SEOs) in the Chinese capital market. Our results show that guanxi-based relationships significantly increase the likelihood of SEO approvals, particularly for suspect SEO applicants with abnormal levels of earnings management (EM), related-party transactions (RPTs), and intercompany loans. More importantly, we find that guanxi-influenced SEO firms have significantly poorer performance in the post-SEO period, which indicates that it results in inefficient resource allocations. Overall, our evidence suggests that relationship-based resource allocations lead to negative spillover effects that impose social welfare losses.

Original languageEnglish
Pages (from-to)1193-1230
Number of pages38
JournalJournal of Financial and Quantitative Analysis
Issue number3
Early online date15 Aug 2018
Publication statusPublished - 1 Jun 2019

Bibliographical note

The authors thank Jay Cai (the referee) and Paul Malatesta (the editor) for helpful comments and suggestions on an earlier version of the paper. Firth thanks the government of the HKSAR (GRF340412) and Lingnan University (DR15A3) for research grants. He acknowledges the financial support from the National Natural Science Foundation of China (Nos. 71472113, 91746117, and 71272008) and the Ministry of Education Project of Key Research Institute of Humanities and Social Sciences at Universities (No. 14JJD630010). Rui acknowledges the financial support of a China Europe International Business School (CEIBS) research grant and the National Natural Science Foundation of China (No. 71372203). Brockman, He, Mao, and Rui acknowledge the profound impact Michael Firth had on them both professionally and personally.

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