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

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      Author(s): 1 , * , , 2 , 3 , 4 , * ,
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      Publication date (Electronic):
      Journal: PLOS ONE
      Publisher: Public Library of Science

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

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          Most cited references58

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          Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme

          J J Heckman, H Ichimura, P. Todd (1997)
          Article 0 comments Cited 651 times – based on 0 reviews     Review now
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            The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations.

            R M Baron, D A Kenny (1986)
            In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.
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              MEASURING ECONOMIC GROWTH FROM OUTER SPACE.

              J Henderson, Adam Storeygard, David N Weil (2012)
              GDP growth is often measured poorly for countries and rarely measured at all for cities or subnational regions. We propose a readily available proxy: satellite data on lights at night. We develop a statistical framework that uses lights growth to augment existing income growth measures, under the assumption that measurement error in using observed light as an indicator of income is uncorrelated with measurement error in national income accounts. For countries with good national income accounts data, information on growth of lights is of marginal value in estimating the true growth rate of income, while for countries with the worst national income accounts, the optimal estimate of true income growth is a composite with roughly equal weights. Among poor-data countries, our new estimate of average annual growth differs by as much as 3 percentage points from official data. Lights data also allow for measurement of income growth in sub- and supranational regions. As an application, we examine growth in Sub Saharan African regions over the last 17 years. We find that real incomes in non-coastal areas have grown faster by 1/3 of an annual percentage point than coastal areas; non-malarial areas have grown faster than malarial ones by 1/3 to 2/3 annual percent points; and primate city regions have grown no faster than hinterland areas. Such applications point toward a research program in which "empirical growth" need no longer be synonymous with "national income accounts."
              Article 0 comments Cited 326 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Dan Pan:
                ORCID: https://orcid.org/0000-0001-7204-6313
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Peiyao Zhou: Role: Data curationRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Fanbin Kong: Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Bing Xue: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Title: PLOS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 27 July 2023
                Publication date Collection: 2023
                Volume: 18
                Issue: 7
                Electronic Location Identifier: e0288901
                Affiliations
                [1 ] School of Economics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, China
                [2 ] China Academy of Public Finance and Public Policy, Central University of Finance and Economics, Beijing, China
                [3 ] School of Economic Management, Nanjing Forestry University, Nanjing, Jiangsu, China
                [4 ] School of Economic and Management, Zhejiang A&F University, Hangzhou, Zhejiang, China
                Institute for Advanced Sustainability Studies, GERMANY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-7204-6313
                Article
                Publisher ID: PONE-D-23-12877
                DOI: 10.1371/journal.pone.0288901
                PMC ID: 10374117
                SO-VID: 96d0a98d-f043-47bd-8efc-e2c333262f61
                Copyright © © 2023 Pan et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 28 April 2023
                Date accepted : 6 July 2023
                Page count
                Figures: 4, Tables: 9, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: No. 71863016; No. 72063019
                Award Recipient :
                ORCID: https://orcid.org/0000-0001-7204-6313
                This study was supported by the National Natural Science Foundation of China (No. 71863016; No. 72063019); Humanities and Social Sciences Research Project of the Ministry of Education in China (No. 19YJCZH270). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Social Sciences
                Subject: Economics
                Subject: Development Economics
                Subject: Economic Growth
                Subject: Earth Sciences
                Subject: Geography
                Subject: Human Geography
                Subject: Urban Geography
                Subject: Cities
                Subject: Social Sciences
                Subject: Human Geography
                Subject: Urban Geography
                Subject: Cities
                Subject: Social Sciences
                Subject: Economics
                Subject: Development Economics
                Subject: Economic Development
                Subject: People and Places
                Subject: Geographical Locations
                Subject: Asia
                Subject: China
                Subject: Engineering and Technology
                Subject: Civil Engineering
                Subject: Urban Infrastructure
                Subject: Social Sciences
                Subject: Economics
                Subject: Finance
                Subject: Social Sciences
                Subject: Economics
                Subject: Microeconomics
                Subject: Urban Economics
                Subject: Engineering and Technology
                Subject: Structural Engineering
                Subject: Built Structures
                Custom metadata
                Data Availability All relevant data are within the paper and its Supporting Information files.

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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