Firm location and corporate dividend policy: evidence from China

ABSTRACT

We investigate the relation between a firm’s geographic location and its dividend policy. We find that firms headquartered in the National Central Cities, cities with high-speed rail (HSR), and with shorter distance to the nearest National Central City pay higher dividends. We find evidence that attributes the higher dividends to an increase in the number of analysts’ site visits, greater information transparency, and a reduction in financial constraints. Finally, the observed increases in dividends tend to be stronger for firms that benefit the most from improvements in the information environment after the arrival of HSR, such as firms located in regions without regional airports, firms located in areas with a lower regional gross domestic product, firms located a greater distance to the closest National Central City, and firms that are smaller, state-owned, have a shorter listing history in the exchanges, and have a more concentrated ownership.

KEYWORDS:

• Dividends payout policy
• HSR
• firm location
• asymmetric information

JEL CLASSIFICATION:

• G35
• G30
• G39

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ In particular we delete special treatment (ST) companies. According to the Shanghai and the Shenzhen Stock Exchanges, ST shares are under special treatment as their net profits were negative in two consecutive fiscal years.

² Zhang (2012) and Ke et al. (2017) find that the transport infrastructure plays an important role in China’s regional economic growth. Chen and Hall (2011) argue that HSR ‘potentially assisting face-to-face contacts in knowledge-generating process’..

³ If there are more than one HSR lines operated in a particular city, the opening year of the first HSR line is used.

⁴ In a pooled regression, standard errors can be biased downward when the residuals are correlated. In a panel data set the residuals may be correlated across industries and years. We thus adjust the standard errors by correcting for simultaneous clustering by industry and year.

⁵ To mitigate the influence of outliers, we winsorize all continuous variables at the 1% and 99% levels.

⁶ John, Knyazeva, and Knyazeva (2011) Table 2 reports that this ratio is 0.78% of market value of equity for all of their US sample firms.

⁷ Zhang, Yang, and Wang (2017) report evidence that HSR has a negative impact on China’s Big Three airlines. Park and Ha (2006) and Adler, Pels, and Nash (2010) also find that there is a functional similarity between HSR and airlines, and that they have a competitive relationship.

⁸ For purposes of brevity, we report in Table 7 only the estimated coefficients on our key variables of interest.

⁹ Many studies find that the transport infrastructure increases regional growth and industrial innovation in Europe and Japan (Cheshire 1995; Kim 2000; Spiekemann and Wegener 2006; Elhorst and Oosterhaven 2008), while other studies find a negative relation between HSR and regional economy (Vickerman 1997; Sasaki, Ohashi, and Ando 1997; Preston and Wall 2008; Ahlfeldt and Feddersen, 2010).

¹⁰ For purposes of brevity, we only report in Table 8 the estimated coefficients on our key variables of interest.

Additional information

Funding

This work was supported by ‘the Fundamental Research Funds for the Central Universities’ under grant 2017XKQY086.