The economic costs of terrorism: evidence from the Xinjiang Uygur Autonomous Region in China

ABSTRACT

I investigate the economic influence of terrorism in China using the synthetic control method pioneered by Abadie and Gardeazabal (2003). Organized terrorist attacks began in 1996 in China’s Xinjiang Uygur Autonomous Region. Comparing actual Xinjiang with a synthetic control without terrorism, I find that terrorist attacks have a pernicious effect on Xinjiang’s economic growth, leading to a loss of 38% of Xinjiang’s GDP per capita in 2018. My result challenges the traditional view that economic growth is not significantly affected by terrorism.

KEYWORDS:

• Synthetic control method
• terrorism
• economic growth
• xinjiang

JEL CLASSIFICATION:

• H56
• P16
• O18

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data within the supplementary material are openly available in figshare at http://doi.org/10.6084/m9.figshare.17526110.

Notes

¹ According to the exclusive documentaries released by China Global Television Networks (CGTN), terrorist activities in Xinjiang escalated in several stages. The Baren Township Riots in 1990 marked the beginning. The Yining Riots in 1997 marked a sharp rise with seven killed, 198 beaten and injured. The Urumqi Riots in 2009 were the deadliest, with 197 killed, and over 1,700 wounded. The violence did not stay in Xinjiang – the ETIM committed terrorist attacks in other big cities of China to gain more significant influence. On 28 October 2013, three terrorists drove a jeep into Beijing’s Tian’anmen Square, killing two tourists. More than 40 people were injured in the incident. On 1 March 2014, eight terrorists murdered 31 travellers (141 wounded) in the Kunming Railway Station with machetes. Source: https://www.bilibili.com/video/av78266046/

² ‘China’s Xinjiang offers 100 million-yuan anti-terror rewards.’ 2017–02-23. CGTN. https://news.cgtn.com/news/3d63544f7a596a4d/share_p.html

³ CHLR applies the Jorgenson-Fraumeni (J-F) method to calculate the real average labour force human capital. Refer to http://humancapital.cufe.edu.cn/rlzbzsxm/zgrlzbzsxm2017/zgrlzbzsbgsjk/sysm.htm for details and data source.

Additional information

Funding

The author received no direct funding for this research.