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Articles

Unusual patterns in China’s prefectural GDP growth rates

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Pages 331-334 | Published online: 30 Apr 2018
 

ABSTRACT

This article examines the last (rightmost) digit of China’s prefectural GDP growth rates, and find that they are unevenly distributedamong 0 to 9. There are too many 0s, 1s, 2s, 5s and too few 4s, 7s, 9s. Moreover, the distribution of the last digit is less skewed when the macro economy grows quickly and when the prefecture’s growth rate ranks high within the province. These patterns reveal that local officials artificially influence the data in order to exceed some thresholds. However, they do not necessarily imply that China's GDP data are falsified.

JEL CLASSIFICATION:

Acknowledgments

I am grateful for comments from the anonymous referee, Alexandra Benham, Lee Benham, Ruixue Jia, Marc Law, Gary Libecap, Qing Liu, John Nye, Mary Shirley, Zheng Song, Colin Xu as well as participants of the Roland Coarse Institute workshop and Tsinghua Macro Seminar.

Disclosure statement

No potential conflict of interest was reported by the author.

Supplementary material

Supplemental data for this article can be accessed here.

Notes

2 There are five layers of governments in China: central authorities, provinces, prefectures, counties and townships. In 2013, there were 31 provinces and 355 prefectures.

3 All GDP growth rates are rounded at precision of 0.1 percent point.

4 See Degeorge, Patel, and Zeckhauser (Citation1999) for details of threshold mentality.

5 We define the two dummies because officials tend to adjust the growth rates to exceed integer numbers and multiples of 0.5.

6 We thank the anonymous referee for pointing out the two reasons.

7 We thank the anonymous referee for pointing out this pattern and possible reasons.

8 For example, Shandong Province uses the share of the tertiary sector in overall GDP as an indicator to evaluate prefecture governments. For details, see http://renshi.people.com.cn/GB/140563/12501283.html.

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