Agglomeration economies and firm performance in Chinese cities: does CEO educational specialization matter

Abstract

This paper examines how CEOs educational background affects the agglomeration economies–firm performance relationship based on the upper echelons theory. With a sample of Chinese software and information technology services public listed firms, it is found that CEO educational specialization helps firms to reap the benefits of agglomeration. Specifically, firms led by CEOs with science or engineering degrees benefit more from specialization externalities, while firms led by CEOs with business, economics or legal degrees enjoy more diversity externalities. This paper contributes to the specialization versus diversity debate by stating the importance of individual CEOs.

Keywords:

• CEO
• educational specialization
• externalities
• firm performance

JEL classifications:

• R12
• O14

Acknowledgements

National Natural Science Foundation of China (71974076), Guangdong Natural Science Foundation of China (2019A1515011923).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Since 2000, the number of higher education institutions (HEIs) in China has more than doubled, the number of new higher education graduates has expanded nearly sevenfold, and the number of approved transnational education (TNE) partnerships between foreign and Chinese HEIs (including undergraduate, postgraduate and vocational TNE programs) has grown from 59 in 2000 to more than 1600 today (Chan 2015).

2 One of the rules imposed by the China Securities Regulatory Commission (CSRC) concerning SEOs is that firms have to achieve a minimum average ROE of 10% three years before the SEO and a minimum ROE of 10% one year before the SEO. Many firms aggressively manipulate their ROEs in order to meet the SEO requirement (Liu et al. 2014).

3 We appreciate the insights provided by an anonymous reviewer on this issue.

4 There are 29 CEOs with business degrees (e.g., MBA) as well as science/engineering degrees in the sample. The same pattern of results was obtained when the benchmark model by excluding these 29 CEOs is estimated.

5 We appreciate the insights provided by an anonymous reviewer on this issue.

6 There are only 49 CEOs aged 60 and over in the sample. Such small sample size may cause the estimation bias. Therefore, the middle-aged CEOs and old aged CEOs are put together as one group.

7 We appreciate the insights provided by an anonymous reviewer on this issue.

Additional information

Notes on contributors

Cui Zhang

Cui Zhang, Professor of economics at school of economics, Jinan University, Guangzhou, PR China. Email: [email protected].

Baifang Wang

Baifang Wang, school of economics, Jinan University, Guangzhou, PR China.