Effect of place-based policy on regional economic growth: A quasi-natural experiment from China’s Old Revolutionary Development Program

Dan Pan, Peiyao Zhou and Fanbin Kong

PLOS ONE, 2023, vol. 18, issue 7, 1-20

Abstract: Triggering economic growth is a requirement to promote human welfare and realize sustainable development in many developing countries. However, place-based policies’ impact on economic growth is debatable, and its underlying mechanism is unknown. China’s Old Revolutionary Development Program (ORDP) is a large-scale and novel type of place-based policy targeted at undeveloped regions in China. We evaluate the effect of ORDP on economic growth by employing a time-varying difference-in-differences model and further explore the potential mechanisms and heterogeneity effects. VIIRS/DNB nightlight data is used to measure economic growth. We find that ORDP can significantly promote economic growth by 4.0% and the result is still robust after several tests. Mechanism analysis shows that ORDP can improve economic growth through government intervention, industrial structure optimization, and information infrastructure construction. Heterogeneity analysis indicates that the ORDP performs better on economic growth in central Chinese cities and high-economy cities. At the same time, our paper provides three practical suggestions for stimulating economic growth in ORDP, which can be enlightening for other developing countries.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288901 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 88901&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0288901

DOI: 10.1371/journal.pone.0288901

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().