Innovation and economic growth in China: evidence at the provincial level

Abstract

China has enjoyed high economic growth for three decades since the initiative of economic reform in 1978. This growth has, however, been driven mainly by labour-intensive, export-oriented manufacturing activities. Has innovation played a role in China's economic growth? What are the determinants of innovation in the Chinese economy? These are some of the questions that are to be explored in this study using China's provincial statistics. Answers to these questions have important policy implications for China's economic development in the future, as innovation is vital for the transformation of the country's growth model.

Keywords:

• innovation
• economic growth
• Chinese economy

JEL classifications:

• O33
• O53

Acknowledgements

This work was supported by an Australian Research Council (ARC) Discovery Project grant (DP1092913). The author acknowledges Dahai Fu and Rebecca Doran-Wu for excellent research assistance and an anonymous referee for valuable comments and suggestions.

Notes

Calculated using information from the 2008 Statistical Communiqué of National Economy and Social Development, National Bureau of Statistics of China (released on 26 February 2009, www.stats.gov.cn).

The State Council, People's Republic of China (www.gov.cn/jrzg/2006-02/09/content_183787.htm).

In this paper, Chinese ‘regions’ refer to China's 31 administrative areas, including provinces, autonomous regions and municipalities (Beijing, Shanghai, Tianjin and Chongqing). Thus, ‘regional’ and ‘provincial’ are used interchangeably in the text.

For a comprehensive literature review, refer to Wu (2011).

An anonymous referee rightly pointed out that ‘provincial growth is not quite the same as aggregate economic growth in China’. Thus, one important qualification for this study is that ‘growth’ here refers to regional growth in China.

Zheng and Hu (2006) reported a TFP growth rate of 2.56% that implies a share of 23.2% over economic growth rate during the period considered.

These numbers for 1990 and 2008 are drawn from China Statistical Yearbook of Science and Technology and 2008 Statistical Communiqué of National Economy and Social Development, National Bureau of Statistics of China (released on 26 February 2009, www.stats.gov.cn), respectively.

This figure was drawn from 2005 China Statistical Yearbook on Science and Technology compiled by the National Bureau of Statistics and Ministry of Science and Technology, Beijing, China Statistics Press.

The percentage shares are based on investments in science and technology by the central and local governments. The raw data are drawn from the online database China's Science and Technology Statistics 2008 (www.most.gov.cn). As for the allocation of central government funding, it is managed through two nationally competitive grant schemes, the National Natural Science Foundation of China (NSFC) and the National Social Science Foundation (NSSF). Similar schemes are also available for the allocation of local government funding.

China's 2007 R&D expenditure, employment and investment data are drawn from the Annual Statistics of Science and Technology, National Bureau of Statistics of China (www.stats.gov.cn).

Student numbers are drawn from China Statistical Yearbook 2008 compiled by the National Bureau of Statistics of China (www.stats.gov.cn).

China's patent and publication data are drawn from the Annual Statistics of Science and Technology published by National Bureau of Statistics of China (www.stats.gov.cn).

For a comprehensive literature survey, see Jones (2005).

The e-copies of these yearbooks are available on the website of National Bureau of Statistics of China (www.stats.gov.cn).

It is noted that, as discussed in the text, the use of patent data as a measure of innovation is sensitive to the choice of the rate of knowledge depreciation. It also ignores other indicators such as scientific publications, new products, the quality of patents and so on.

For the estimation of China's capital stock series, refer to Wu (2008).

In details, the three regions are the coastal region (Beijing, Tianjin, Shanghai, Fujian, Guangdong, Hebei, Jiangsu, Liaoning, Shandong and Zhejiang), the middle region (Shanxi, Hainan, Jilin, Anhui, Heilongjiang, Guangxi, Jiangxi, Hubei, Hunan, Henan and Hainan) and the western region (Inner Mongolia, Ningxia, Tibet, Xinjiang, Gansu, Guizhou, Qinghai, Shaanxi, Sichuan, Yunnan and Chongqing).

The choice of instrumental variables (IVs) is important for GMM estimators. Here the IVs are selected using the XTABOND command in STATA.

In contrast, Hayakawa (2007) argues that the system GMM estimator is less biased than differencing GMM estimators.

The readers may refer to Nishimizu and Page (1982) for details.

Investment refers to gross capital formation. The figures are according to the author's own estimates.