Open government data and green economic growth

Economic Analysis and Policy, Journal Year: 2025, Volume and Issue: 85, P. 2207 - 2218

Published: March 1, 2025

Language: Английский

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Open government data and resource allocation efficiency: evidence from China

Applied Economics, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: March 22, 2024

Data are among the most valuable resources. This paper, utilizing China Tax Survey Database from 2009 to 2016, investigates impact of Open Government (hereafter, OGD) on efficiency resource allocation firms within Chinese context. The findings indicate that OGD significantly reduces deviation in firms' factor inputs, thereby enhancing allocation. is primarily achieved through optimization government-business relationships, reduction rent-seeking costs, and decrease information asymmetry. Given inclusive nature OGD, it has a more pronounced positive disadvantaged cities. Furthermore, while directly improves representative firm's TFP, its greater economic lies elevating aggregate TFP by efficiency. In current global economy, highly dependent data-driven processes, conclusions this paper provide novel perspective role productivity. significant implications for accelerating implementation open data policies

Language: Английский

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Does government data openness have a green effect? an examination from the perspective of green innovation

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: Feb. 14, 2025

Firms’ green R&D and innovation directly impact the national economy’s high-quality development. However, data resources play a significant role in altering traditional development models promoting sustainable economic growth. Government openness (GDO) offers vital opportunity for widespread transmission of value. Existing literature has not yet examined whether GDO can intrinsically affect micro-level firms. In this study, we examine on corporate using from A-share industrial listed companies China spanning 2007–2022 employing difference-in-differences (DID) method. The results indicate that significantly promotes innovation. Mechanism tests reveal fosters through channels such as enhancing risk-taking, alleviating financing constraints, optimizing business environment. Further examination shows improvements quality enhance Moreover, effect is comprehensive does vary with classification types. According to heterogeneity analysis, when management’s cognition higher, firm younger, environmental regulations are more stringent, intellectual property less protected, noticeable. This paper provides insights GDO, advancing emerging market countries.

Language: Английский

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Government open data and corporate supply chain concentration

International Review of Financial Analysis, Journal Year: 2025, Volume and Issue: unknown, P. 104144 - 104144

Published: March 1, 2025

Language: Английский

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Unlocking green potential: How open government data enhances green economic efficiency in China?

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 125043 - 125043

Published: March 19, 2025

Language: Английский

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The Impact of Open Government Data on Corporate Digital Innovation: Evidence from Chinese Listed Companies

Published: Jan. 1, 2025

Language: Английский

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Digital Finance and Green Technology Innovation: A Dual Path Test Based on Market and Government

Finance research letters, Journal Year: 2024, Volume and Issue: 70, P. 106283 - 106283

Published: Oct. 12, 2024

Language: Английский

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Enhancing local governments’ environmental attention through open government data: evidence from China

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(12), P. 18494 - 18511

Published: Feb. 12, 2024

Language: Английский

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In search of better methods for the longitudinal assessment of tech-derived X-risks: How five leading scenario planning efforts can help

Technology in Society, Journal Year: 2024, Volume and Issue: 77, P. 102505 - 102505

Published: March 17, 2024

This mixed methods article discusses the role of scenario analysis as a tool to assess broadest possible specter positive and negative effects technologies social processes within current existential risk assessment research. To do so, it compares contrasts case studies five ongoing, longitudinal planning efforts global nature– Shell scenarios, Intergovernmental Panel on Climate Change (IPCC), CSIS Seven Revolutions Scenarios, The Millennium Project's State Future, NIC's Global Trends 2040, derive lessons for whether how adjacent (X-risk) tech communities can better deploy methodology. Observations are derived from interviews with practitioners involved in these well an publicly available material issued by each project, including scenarios produced. emphasis is methodologies used, timelines considered, forces identifies important drivers, process engagement once created. Three practices identified include (1) constructing narratives based strong data, (2) sticking plausible (not wild cards), (3) designing engagement, which does albeit different ways. concludes few brief recommendations future efforts, particularly relevant x-risk that aim be governance. Overall, this review shows aimed at influencing governance would benefit (a) more uniformly shared vocabulary, (b) underlying theory cascading systemic change, (c) deeper methodological transparency, (d) increased transdisciplinary perspectives, yet (e) maintaining scientific rigor. These improvements emerging tech-risk X-risk where stakes highest they could be, safeguarding humanity's future.

Language: Английский

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Societal, Economic, Political and Environmental: A Review of Benchmarks and AI-assisted Systematic Literature Review of Impact of Open Government Data

Published: June 1, 2024

The purpose of this research is to review the impact on open government data in evaluation at world level and academia. First, six most renowned evaluations are reviewed with their section. Then, a systematic literature conducted test AI-assisted software using Preferred Reporting Items for Systematic Review Meta-Analysis (PRISMA) Protocol, find current status realized research.

Language: Английский

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