Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 781

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Public spending and green economic growth in BRI region: Mediating role of green finance

Zhang, Dongyang, Mohsin, Muhammad, Rasheed, Abdul Khaliq, Chang, Youngho, Taghizadeh-Hesary, Farhad·2021·Energy Policy
DOI 10.1016/j.enpol.2021.112256
Open this paper in CoChat — free account

Abstract

Abstract Generally, public spending on education, research, and development (RD however, such notion lacks evidence, particularly in Belt and Road Initiative (BRI) member countries. In this study, panel data of BRI member countries from 2008 to 2018 is analysed using the generalized method of moments (GMM) method and data envelopement analysis (DEA) to assess the relationship between public spending on R&D and green economic growth and energy efficiency. The study found a fluctuating green economic growth indicator during the research period attributed to the non-serious nature of government policies. The findings reveal that the GMM method confirms both composition and technique effects in the entire sample. Nonetheless, the result of the sub-sample showed a heterogeneous effect on high GDP per capita countries. Moreover, the study shows that public spending on human resources and R&D of green energy technologies prompts a sustainable green economy through labour and technology-oriented production activities and different effects in different countries.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.enpol.2021.112256

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Research works printed but not linked: 73

  1. A, 2007, 35, 2466
  2. Acheampong, 2018, Economic growth, CO2 emissions and energy consumption: what causes what and where?, Energy Econ., 74, 677, 10.1016/j.eneco.2018.07.022 · DOI · Paper page
  3. Afonso, 2010, Government size, composition, volatility and economic growth, Eur. J. Polit. Econ., 10.1016/j.ejpoleco.2010.02.002 · DOI · Paper page
  4. Akhtar, 2018, Advances and significance of solar reflectors in solar energy technology in Pakistan, Energy Environ., 10.1177/0958305X18758487 · DOI
  5. Al-mulali, 2011, Oil consumption, CO2 emission and economic growth in MENA countries, Energy, 36, 6165, 10.1016/j.energy.2011.07.048 · doi:10.1016/j.energy.2011.07.048
  6. Alemzero, 2020, Assessing energy security in Africa based on multi-dimensional approach of principal composite analysis, Environ. Sci. Pollut. Res.
  7. Aly, 2017, Solar power potential of Tanzania: identifying CSP and PV hot spots through a GIS multicriteria decision making analysis, Renew. Energy, 10.1016/j.renene.2017.05.077 · DOI · Paper page
  8. Anser, 2019, Impact of energy consumption and human activities on carbon emissions in Pakistan: application of stirpat model, Environ. Sci. Pollut. Res., 10.1007/s11356-019-04859-y · DOI
  9. Anser, 2018, Moderating effect of innovation on corporate social responsibility and firm performance in realm of sustainable development, Corp. Soc. Responsib. Environ. Manag., 10.1002/csr.1495 · DOI
  10. Arellano, 1991, Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Rev. Econ. Stud., 58, 277, 10.2307/2297968 · DOI · Paper page
  11. Chapple, 2005, Assessing the relative performance of U.K. university technology transfer offices: parametric and non-parametric evidence, Res. Policy, 10.1016/j.respol.2005.01.007 · DOI · Paper page
  12. Dai, 2015, Environmental issues associated with wind energy - a review, Renew. Energy, 10.1016/j.renene.2014.10.074 · DOI · Paper page
  13. Facchini, 2018, Public spending structure, minimal state and economic growth in France (1870–2010), Econ. Model., 72, 151, 10.1016/j.econmod.2018.01.014 · DOI
  14. Färe, 1989, Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach, Rev. Econ. Stat., 10.2307/1928055 · DOI · Paper page
  15. Färe, 2005, Characteristics of a polluting technology: theory and practice, J. Econom., 10.1016/j.jeconom.2004.05.010 · DOI · Paper page
  16. Guo, 2017, Non-cooperative two-stage network DEA model: linear vs. parametric linear, Eur. J. Oper. Res., 10.1016/j.ejor.2016.11.039 · doi:10.1016/j.ejor.2016.11.039
  17. Hainaut, 2018, The Landscape of Domestic climate investment and finance flows: Methodological lessons from five years of application in France, Int. Econ., 155, 10.1016/j.inteco.2018.06.002 · doi:10.1016/j.inteco.2018.06.002
  18. Huntington, 2015, Crude oil trade and current account deficits, Energy Econ., 50, 70, 10.1016/j.eneco.2015.03.030 · DOI
  19. Iqbal, 2020, Oil supply risk and affecting parameters associated with oil supplementation and disruption, J. Clean. Prod., 255, 10.1016/j.jclepro.2020.120187 · DOI
  20. Iram, 2020, Prioritization of renewable solar energy to prevent energy insecurity: an integrated role, Singapore Econ. Rev.
  21. Ji, 2017, Comparisons of initial carbon allowance allocation rules in an O2O retail supply chain with the cap-and-trade regulation, Int. J. Prod. Econ., 187, 68, 10.1016/j.ijpe.2017.02.011 · DOI · Paper page
  22. Jin, 2018, Impact of land input on economic growth at different stages of development in Chinese cities and regions, Sustain. 2018, 10
  23. Kuang, 2020, Provincial cultivated land use efficiency in China: empirical analysis based on the SBM-DEA model with carbon emissions considered, Technol. Forecast. Soc. Change, 10.1016/j.techfore.2019.119874 · DOI · Paper page
  24. Lepitzki, 2018, The role of a low carbon fuel standard in achieving long-term GHG reduction targets, Energy Pol., 119, 423, 10.1016/j.enpol.2018.03.067 · DOI
  25. Li, 2020, Energy investment, economic growth and carbon emissions in China—empirical analysis based on spatial Durbin model, Energy Pol., 140, 111425, 10.1016/j.enpol.2020.111425 · DOI · Paper page
  26. Lin, 2018, The energy, environmental and economic impacts of carbon tax rate and taxation industry: a CGE based study in China, Energy, 159, 558, 10.1016/j.energy.2018.06.167 · DOI · Paper page
  27. Lin, 2019, Fiscal spending and green economic growth: evidence from China, Energy Econ., 83, 264, 10.1016/j.eneco.2019.07.010 · DOI
  28. Liu, 2018, Exploring the development of electric vehicles under policy incentives: a scenario-based system dynamics model, Energy Pol., 120, 8, 10.1016/j.enpol.2018.04.073 · DOI
  29. Liu, 2020, How green is the “belt and road initiative”? – evidence from Chinese OFDI in the energy sector, Energy Pol.
  30. Mahmoudabadi, 2019, Comprehensive performance evaluation of banking branches: a three-stage slacks-based measure (SBM) data envelopment analysis, Int. Rev. Econ. Finance, 10.1016/j.iref.2019.08.001 · DOI
  31. Martínez-Moya, 2019, Energy efficiency and CO2 emissions of port container terminal equipment: evidence from the Port of Valencia, Energy Pol., 10.1016/j.enpol.2019.04.044 · doi:10.1016/j.enpol.2019.04.044
  32. Meleddu, 2018, Public spending on renewable energy in Italian regions, Renew. Energy, 10.1016/j.renene.2017.09.015 · DOI
  33. Mohsin, 2018, Assessing oil supply security of South Asia, Energy, 155, 438, 10.1016/j.energy.2018.04.116 · DOI
  34. Mohsin, 2021, Nexus between energy efficiency and electricity reforms: a DEA-Based way forward for clean power development, Energy Pol., 149, 112052, 10.1016/j.enpol.2020.112052 · DOI · Paper page
  35. Montalbano, 2019, Energy efficiency, productivity and exporting: firm-level evidence in Latin America, Energy Econ., 79, 97, 10.1016/j.eneco.2018.03.033 · DOI
  36. Nieto, 2018, Less than 2 °C? An economic-environmental evaluation of the paris agreement, Ecol. Econ., 146, 69, 10.1016/j.ecolecon.2017.10.007 · DOI · Paper page
  37. Omri, 2013, CO2 emissions, energy consumption and economic growth nexus in MENA countries: evidence from simultaneous equations models, Energy Econ., 40, 657, 10.1016/j.eneco.2013.09.003 · DOI · Paper page
  38. Paramesh, 2018, Optimization of energy consumption and environmental impacts of arecanut production through coupled data envelopment analysis and life cycle assessment, J. Clean. Prod., 203, 674, 10.1016/j.jclepro.2018.08.263 · DOI
  39. Peña-Martel, 2018, The role of the media in creating earnings informativeness: evidence from Spain, BRQ Bus. Res. Q., 21, 168, 10.1016/j.brq.2018.03.004 · DOI
  40. Qi, 2019, Energy intensity convergence in Belt and Road Initiative (BRI) countries: what role does China-BRI trade play?, J. Clean. Prod., 10.1016/j.jclepro.2019.118022 · DOI
  41. Ragwitz, 2005, Evidence from RD&D spending for renewable energy sources in the EU, Renew. Energy, 10.1016/j.renene.2004.12.001 · doi:10.1016/j.renene.2004.12.001
  42. Ringler, 2017, How to benefit from a common European electricity market design, Energy Pol., 10.1016/j.enpol.2016.11.011 · DOI
  43. Rodriguez-Gonzalez, 2018, An integrated stochastic economic-ecological-social model with stratified-population, Ecol. Model., 368, 15, 10.1016/j.ecolmodel.2017.11.012 · doi:10.1016/j.ecolmodel.2017.11.012
  44. Salim, 2012, Why do some emerging economies proactively accelerate the adoption of renewable energy?, Energy Econ., 10.1016/j.eneco.2011.08.015 · DOI · Paper page
  45. Shah, 2019, Energy security and environmental sustainability index of South Asian countries: a composite index approach, Ecol. Indicat., 106, 105507, 10.1016/j.ecolind.2019.105507 · DOI
  46. Shu, 2016, How green management influences product innovation in China: the role of institutional benefits, J. Bus. Ethics, 133, 471, 10.1007/s10551-014-2401-7 · DOI · Paper page
  47. Shuai, 2020, Modeling the role of environmental regulations in regional green economy efficiency of China: empirical evidence from super efficiency DEA-Tobit model, J. Environ. Manag., 10.1016/j.jenvman.2020.110227 · DOI · Paper page
  48. Sun, 2020, Estimating persistent and transient energy efficiency in belt and road countries: a stochastic frontier analysis, Energies, 13, 3837, 10.3390/en13153837 · DOI
  49. Sun, 2020, Low-carbon financial risk factor correlation in the belt and road PPP project, Finance Res. Lett., 35, 101491, 10.1016/j.frl.2020.101491 · DOI
  50. Sun, 2020, The role of environmental entrepreneurship for sustainable development: evidence from 35 countries in Sub-Saharan Africa, Sci. Total Environ.
  51. Sun, 2020, Carbon emission transfer strategies in supply chain with lag time of emission reduction technologies and low-carbon preference of consumers, J. Clean. Prod.
  52. Sun, 2020, Analyzing carbon emission transfer network structure among provinces in China: new evidence from social network analysis, Environ. Sci. Pollut. Res.
  53. Taghizadeh-Hesary, 2019, The way to induce private participation in green finance and investment, Finance Res. Lett., 31, 98, 10.1016/j.frl.2019.04.016 · DOI · Paper page
  54. Taghizadeh-Hesary, 2020, Sustainable solutions for green financing and investment in renewable energy projects, Energies, 13, 788, 10.3390/en13040788 · DOI · Paper page
  55. Tehreem, 2020, Impact of average temperature, energy demand, sectoral value added, and population growth on water resource quality and mortality rate: it is time to stop waiting around, Environ. Sci. Pollut. Res., 10.1007/s11356-020-09822-w · DOI
  56. Tyteca, 1996, On the measurement of the environmental performance of firms - a literature review and a productive efficiency perspective, J. Environ. Manag., 10.1006/jema.1996.0022 · DOI · Paper page
  57. van de Ven, 2017, Historical energy price shocks and their changing effects on the economy, Energy Econ., 10.1016/j.eneco.2016.12.009 · DOI
  58. Wang, 2019, Incentive model for enterprises based on carbon emission intensity, J. Clean. Prod., 235, 1353, 10.1016/j.jclepro.2019.06.351 · doi:10.1016/j.jclepro.2019.06.351
  59. Wooldridge, 2001, Applications of Generalized Method of Moments Estimation, Am. Econ. Assoc., 15
  60. Wu, 2021, A comprehensive evaluation of the eco-carrying capacity and green economy in the Guangdong-Hong Kong-Macao Greater Bay Area, China, J. Clean. Prod.
  61. Xie, 2017, Provincial transfers of enabled carbon emissions in China: a supply-side perspective, Energy Pol., 107, 688, 10.1016/j.enpol.2017.04.021 · DOI
  62. Xing, 2018, Central-local government fiscal relations and cyclicality of public spending: evidence from China, Int. Tax Publ. Finance, 25, 946, 10.1007/s10797-017-9478-8 · DOI
  63. Yang, 2017, The governance environment and innovative SMEs, Small Bus. Econ., 48, 525, 10.1007/s11187-016-9802-1 · DOI
  64. Yoshino, 2019, Modelling the social funding and spill-over tax for Addressing the green energy financing gap, Econ. Modell., 77, 34, 10.1016/j.econmod.2018.11.018 · doi:10.1016/j.econmod.2018.11.018
  65. Yoshino, 2020, Covid-19 and optimal portfolio selection for investment in sustainable development goals, Finance Res. Lett., 101695
  66. Zaim, 2004, Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework, Ecol. Econ., 10.1016/j.ecolecon.2003.08.003 · DOI
  67. Zhang, 2019, A bibliometric analysis on green finance: current status, development, and future directions, Finance Res. Lett., 29, 425, 10.1016/j.frl.2019.02.003 · DOI · Paper page
  68. Zhang, 2019, A multidimensional measure of energy poverty in China and its impacts on health: an empirical study based on the China family panel studies, Energy Pol., 131, 72, 10.1016/j.enpol.2019.04.037 · DOI
  69. Zhang, 2020, Does better access to credit help reduce energy intensity in China? Evidence from manufacturing firms, Energy Pol., 145, 111710, 10.1016/j.enpol.2020.111710 · DOI
  70. Zhang, 2018, Credit and market risks measurement in carbon financing for Chinese banks, Energy Econ., 76, 549, 10.1016/j.eneco.2018.10.036 · DOI
  71. Zhang, 2018, The linkage of CO2 emissions for China, EU, and USA: evidence from the regional and sectoral analyses, Environ. Sci. Pollut. Res.
  72. Zhao, 2017, Enterprises' compliance with government carbon reduction labelling policy using a system dynamics approach, J. Clean. Prod., 163, 303, 10.1016/j.jclepro.2016.04.096 · DOI
  73. Zhou, 2006, Slacks-based efficiency measures for modeling environmental performance, Ecol. Econ., 60, 111, 10.1016/j.ecolecon.2005.12.001 · DOI · Paper page

Cited by

See all 781

Metadata

Authors
Zhang, D., Mohsin, M., Rasheed, A. K., Chang, Y., & Taghizadeh-Hesary, F.
Venue
Energy Policy
Publisher
Elsevier BV
Published
2021-06
Volume
153
Pages
112256
ISSN
0301-4215 (ISSN-L)
DOI
10.1016/j.enpol.2021.112256
OpenAlex
W3152140428
Cited by
781
References
2
FWCI
113.23
Type
journal article
Language
en
Open access
closed
Licence
Funders
Government of Japan Ministry of Education Culture Sports Science and Technology

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Public spending and green economic growth in BRI region: Mediating role of green finance. https://app.cochat.ai/papers/10.1016/j.enpol.2021.112256
The paper
Zhang, D., Mohsin, M., Rasheed, A. K., Chang, Y., & Taghizadeh-Hesary, F. (2021). Public spending and green economic growth in BRI region: Mediating role of green finance. Energy Policy. https://doi.org/10.1016/j.enpol.2021.112256

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.