Development zones and firms’ performance: the impact of development zones on firms’ performance for a Chinese industrial cluster

ABSTRACT

This paper examines the policy effect of development zones on firms’ performance, excluding the agglomeration effect. We constructed an industrial cluster dataset on China’s manufacturing industries to identify the impacts on firms’ productivity and other performance indices after the establishment of development zones in 2006. Based on the estimated results obtained from a difference-in-differences analysis, development zones are conducive to promoting firms’ performance, and the policy effect is heterogeneous across industrial clusters, regions and firms. The findings drawn from this study can be beneficial to policymakers in their pursuit of promoting regional development through favourable industrial policies.

KEYWORDS:

• industrial clusters
• development zones
• manufacturing industries
• productivity
• policy effect

JEL:

• D24
• L52
• O14
• R11

ACKNOWLEDGEMENTS

The authors are grateful to two anonymous reviewers and the editor for their detailed and thoughtful comments during the publication process. Any remaining errors are the authors’ own.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. Governments make large capital investments to improve transport infrastructure, utilities, storage and other service facilities within development zones (Wang, 2013).

2. Compared with provincial development zones, national development zones have a larger area, more preferential policies and higher administration authority.

3. The Catalogue of China’s Development Zones (2018 version) is an official statement that publishes basic information about national and provincial development zones, including name, code, type, year of establishment, area as well as pillar industries.

4. A typical example is that existing provincial development zones are upgraded to national development zones, which provides them more opportunities for long-term development via upgrades.

5. We chose 2006 as the policy year for two reasons. First, the existing database of Chinese industrial enterprises only identifies manufacturing industry cluster data from 1998. To avoid endogeneity, we had to select development zones that were established after 1998. Second, 87% of the total number of new development zones were set up in 2006 during the sample period. Moreover, approval for the creation of new development zones was almost stopped after 2006, whereas upgrading the existed ones became the main trend for zones.

6. The dataset classifies industrial sectors with a four-digit-code industry, in compliance with the industrial classification for national economic activities (GB/T4754-2002).

7. Because of the limitation of China’s input–output tables, we cannot use Delgado et al.’s (2016) method directly.

8. According to the Statistical Classification of Large, Medium and Small Enterprises (2003), we define firms with a revenue of more than 300 million yuan and that employ more than 2000 people as large firms.

9. A universal measure of firms’ productivity is total factor productivity (TFP). Due to data limitations, we used output per worker instead of TFP. Meanwhile, when we change the definition of productivity, the conclusion is similar.

10. Compared with the Pearl River Delta, the Yangtze River Delta is the largest city cluster in eastern China, and is more affected by development zones in 2006.

Additional information

Funding

This study was funded by the Zhejiang Provincial Philosophy and Social Science Leading Talent Cultivation Project [grant number 21YJRC06-1YB], the National Natural Science Foundation of China [grant numbers 72273130 and 71773112], the Fundamental Research Funds for the Central Universities [grant number 2020XZA215], the Pre-Research Funds for Zhejiang University of Technology [grant number SKY-ZX-20210204] and the Fundamental Research Funds for Zhejiang University of Technology [grant number GB202103002].