Spatial characteristics and dynamics of provincial total factor productivity in China

Abstract

This paper explores the influence of spatial effects on the convergence of total factor productivity (TFP) across Chinese regions. We use the Moran index, Markov transition matrix and panel data techniques to analyse spatial dependence, transition dynamics and disparities in TFP across Chinese provinces over the period from 1978 to 2004. We find that in the period following 1978, there has been an increase in spatial dependence in provincial-level TFPs across the various regions in China. However, the extent of this dependence is not the same across regions and the direction of movement of provincial TFP does not show convergence. On the contrary, provincial TFPs at the middle quintile level moved to the quintile levels at the highest and lowest levels, suggesting divergence and polarization in TFP across Chinese regions. The ‘New Eastern Region’ appears to be a TFP convergence club over the sampling period but no evidence is found suggesting convergence of TFP between provinces in the other subgroups. Policy implications are discussed.

Keywords:

• productivity
• spatial dependence
• transition dynamics
• convergence

JEL classification:

• C33
• O47
• R11

Acknowledgments

This project is supported by the National Natural Sciences Foundation of China (70603011), Significant Project of National Social Science Foundation of China (07&ZD017), the Social Science Foundation of the State Education Ministry of China (05JC630072) and China Postdoctoral Science Foundation (20070410112).

Notes

Notes

1. The eastern region includes 11 provinces and municipalities: Beijing, Tianjin, Hebei, Liaoling, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan. The central region indicates nine provinces: Shanxi, Inner Mongolia, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan. The western region indicates nine provinces, municipalities and autonomous regions: Guangxi, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.

2. The New Economic Geography focuses on the determinant impact of regional spatial dependence on the economic development and output. Ying (2003), Bao et al. (2003), Aroca (2006), Ho and Li (2006) integrated geographic proximity and the spatial effect in analysing regional growth and city income distribution in China. Aroca et al. (2006) provides a review on this aspect.

3. In fact, in this paper, we have used both the traditional TFP estimation applying the Cobb–Douglas function and the trans-log function. However, due to space limitations, we only report the results of the trans-log in the paper but we will compare the traditional TFP results for robustness checks. In fact, many researchers have applied the DEA method to estimate provincial TFP and investigated the growth of TFP in regions (Wu 2000; Zheng and Hu 2006). This paper can provide a comparison of provincial TFP estimation and focus on the spatial characteristics and convergence of provincial TFP in China.

4. Ascari and Di Cosmo (2004) assume the same elasticity for labour and human capital inputs. In this paper we relax this restriction.

5. In fact, the northeast, as China's old industrial base, with a relatively high degree of industrialization, has a relatively high level of technology.

6. The new eastern China denotes the northeast plus traditional eastern China (excluding Guangxi). The far west China includes Inner Mongolia, Xinjiang, Qinghai and Tibet. The remaining provinces are included in the large central China.

7. The results of estimated provincial TFP using the traditional Cobb–Douglas production function and the corresponding test results are available from the author subject to request.