Skip to main content

Advertisement

SpringerLink
Log in

The impact of economic factors and governance on greenhouse gas emission

  • Research Article
  • Published:
Environmental Economics and Policy Studies Aims and scope Submit manuscript

Abstract

Governance is a basic factor explaining the poor economic, social and environmental performance of many developing countries. Since good governance impacts the environment and management of carbon emissions, in this study, we examine the relationship between governance and economic performance and its impact on CO2 emissions, employing the World Bank’s Aggregate Governance Indicators. To this end, data from Organization of the Petroleum Exporting Countries over 8 years (from 2006 to 2015) is analyzed through spatial econometric techniques for panel data. The results show that the governance index (with a negative sign) and GDP growth variable (with a positive sign) have the greatest impact on carbon dioxide emissions. The inflation rate, exports, imports, foreign investment, and employment also have an impact on CO2 emissions. The policy recommendations of this research are that governments can help protect the environment by adopting better governance practices, improving the governance structure, and implementing a clean technology strategy in production to reduce greenhouse gas emissions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. The Environmental Performance Index ranks 180 countries on 24 performance indicators across ten issue categories covering environmental health and ecosystem vitality. These metrics provide a national-level gauge of how close countries are to established environmental policy goals.

References

  • Akbari NA, Moallemi M (2005) Economic integration in the Persian Gulf states (using a spatialeconometric methods). Q Econ Preceding stud 25:109–126 (In Persian).

    Google Scholar 

  • Al-mulali U, Ting L (2014) Econometric analysis of trade, exports, imports, energy consumption and CO2 emission insixregions. Renew Sustain Energy Rev 33:484–498

    Google Scholar 

  • Álvarez G, Fernández J, Gómez M (2016) Governance, environmental and economic factors, an international analysis. Environ Policy Gov Environ 26:29–44

    Google Scholar 

  • Anselin L (2001) Spatial effects in econometric practice in environmental and resource economics. Am J Agric Econ 83:705–710

    Google Scholar 

  • Anselin L, Bera AK (1998) Spatial dependence in linear regression models with an introduction to spatial econometrics. In: Ullah A, Giles DEA (eds) Handbook of applied economics statistics. Marcel Dekker, New York

    Google Scholar 

  • Bailey TC, Gatrell AC (1995) Interactive spatial data analysis. Addison Wesley Longman Limited, Harlow

    Google Scholar 

  • Baltagi BH, Li D (2003) Prediction in the panel data model with spatial correlation. Advances in spatial econometrics. Springer, Berlin, Heidelberg, pp 283–295

    Google Scholar 

  • Baltagi B, Egger P, Paffermayr M (2007a) A generalized spatial panel data model with random effects. Syracuse University, Working Paper

  • Baltagi B, Song SH, Koh W, Jung BC (2007b) Testing for serial correlation, spatial autocorrelation and random effects using panel data. J Econom 140:5–51

    Google Scholar 

  • Baltagi B, Bresson G, Pirotte A (2007c) Panel unit root tests and spatial dependence. J Appl Econom 22:339–360

    Google Scholar 

  • Battisti M, Delgado M, Parmeter C (2015) Evolution of the global distribution of carbon dioxide: a finite mixture analysis. Resour Energy Econ 42:31–52

    Google Scholar 

  • Belotti F, Hughes G, Mortari A (2013) A command to estimate spatial panel models in Stata. German Stata Users Group Meeting, pp 1–37

  • Belotti F, Hughes G, Mortari AP (2017) Spatial panel-data models using Stata. Stata J. https://doi.org/10.1177/1536867X1701700109

    Article  Google Scholar 

  • Benjamin K (2018) Bamboo beating bandits: conflict, inequality, and vulnerability in the political ecology of climate change adaptation in Bangladesh. World Dev 102:183–194

    Google Scholar 

  • Bernard J-T, Gavin M, Khalaf L, Voia M (2014) Environmental Kuznets curve: tipping points, uncertainty and weak identification. Environ Resour Econ 60(2):285–315

    Google Scholar 

  • Biermann F (2009) Global environmental governance. In: A world environment organization: solution or threat for effective environmental governance? pp 117–144. ISBN: 9781138378810

  • Burnett JW, Bergstrom JC, Wetzstein ME (2013) Carbon dioxide emissions and economic growth in the US. J Policy Model 35:1014–1028

    Google Scholar 

  • Cliff AD, Ord JK (1973) Spatial autocorrelation. Pion Ltd., London

    Google Scholar 

  • Cliff AD, Ord JK (1981) Spatial processes: models and applications. Pion Limited, London

    Google Scholar 

  • Copeland BR, Taylor MS (2004) Trade, growth, and the environment. J Econ Lit 42:7–71

    Google Scholar 

  • Cruz L, Thiago A, Almeida N, Barata E, Sánchez G (2017) Economic growth and environmental impacts. An analysis based on a composite index of environmental damage. Ecol Ind 76:119–130

    Google Scholar 

  • Davis SJ, Caldeira K, Matthews HD (2010) Future CO2 emissions and climate change from existing energy infrastructure. Science 329:1330–1333

    Google Scholar 

  • Destek M, Ball E, Manga M (2016) The Relationship between CO2 emission, energy consumption urbanization and trade openness for selected CEECs. Res World Econ 1:1–7. https://doi.org/10.5430/rwe.v7n1p52

    Article  Google Scholar 

  • Dinda S (2004) Environmental Kuznets curve hypothesis: a survey. Ecol Econ 49:431–455

    Google Scholar 

  • Doda B (2014) Evidence on business cycles and CO2 emissions. J Macroecon 40:214–227

    Google Scholar 

  • Elhorst JP (2003) Specification and estimation of spatial panel data model. Int Reg SciRev 26(3):244–268

    Google Scholar 

  • Elhorst JP (2011) Spatial panel models. Geogr Anal 42:338–355

    Google Scholar 

  • Elhorst JP (2017) Spatial panel data analysis. Springer International Publishing, Cham, pp 2050–2058

    Google Scholar 

  • Energy Information Administration (EIA) (2018) https://www.eia.gov/aeo. Accessed Feb 2017

  • Environmental Permitting (2012) https://www.defra.gov.uk. Accessed Feb 2017

  • Eskeland GS, Harrison AE (2003) Moving to greener pasture? Multinationals and the pollution heaven hypothesis. J Dev Econ 70:1–23

    Google Scholar 

  • Faizi A, Khodadad F, Ghaderi S (2016) Effects of short-term and long-term financial green environmental emissions Iran. In: 3rd international conference on green economics. Article COI Code: GETOROUD03_020. http://www.civilica.com/Paper-GETOROUD03-GETOROUD03_020.html.

  • Ferrero I, Fernández-Izquierdo MA, Muñoz-Torres MJ (2016) The effect of environmental, social and governance consistency on economic results. Corp Soc Responsib Environ Manag 22:193–207

    Google Scholar 

  • Frankel J (2008) Environmental effects of international trade. Glob Council 31:1–88

    Google Scholar 

  • Gera W (2016) Public participation in environmental governance in the Philippines: the challenge of consolidation in engaging the state. Land Use Policy 52:501–510

    Google Scholar 

  • Gill G, Sakrani T, Cheng W, Zhou J (2017) Comparison of adjacency and distance-based approaches for spatial analysis of multimodel traffic crash data. Int Arch Photogramm Remote Sens Spatial Inf Sci XLII-2/W7, pp 1157–1161. https://doi.org/10.5194/isprs-archives-XLII-2-W7-1157-2017.

    Google Scholar 

  • Global temperature (2016) NASA, NOAA data show 2016 warmest year on record globally. https://www.Global+temperature

  • Goldemberg J (1998) Leapfrog energy technologies. Energy Policy 26:729–741

    Google Scholar 

  • Griffith DA (1996) Some guidelines for specifying the geographic weights matrix contained in spatial statistical models. In: Arlinghaus SL (ed) Practical handbook of spatial statistics. pp 65–82

  • Hamidisepehr A, Chattopadhyay S, Edwards DR (2017) An assessment of climate change impacts on future water availability and droughts in the Kentucky River Basin. Environ Process 4:477–507

    Google Scholar 

  • Harris JM (2004) Trade and the environment. Tufts University Global Development and Environment InstituteTufts University, Medford, MA, 02155. http://ase.tufts.edu/gdae. Accessed Jan 2017

  • He J (2006) Pollution haven hypothesis and environmental impacts of foreign direct investment: the case of industrial emission of sulfur dioxide (SO2) in Chinese province. Ecol Econ 60:228–245

    Google Scholar 

  • Hsiao C, Pesaran MH, Tahmiscioglu AK (2002) Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods. J Econom 109:107–150

    Google Scholar 

  • IPCC (2014) Climate change 2014: synthesis report. In: Pachauri RK, Meyer LA (eds) Contribution of Working Groups I, II and III to the Fifth assessment report of the inter governmental panel on climate change. IPCC, Geneva, Switzerland, p 151. https://www.ipcc.ch. Accessed Mar 2017

  • Jakob M, Steckel JC (2014) How climate change mitigation could harm development in poor countries. WIREs Clim Change 5:161–168. https://doi.org/10.1002/wcc.260

    Article  Google Scholar 

  • Jakob M, Haller M, Marschinski R (2012) Will history repeat itself? Economic convergence and convergence in energy use patterns. Energy Econ 34:95–104. https://doi.org/10.1016/j.eneco.2011.07.008

    Article  Google Scholar 

  • Jakob M, Steckel JC, Klasen S, Lay J, Grunewald N, Martínez-Zarzoso I, Renner S, Edenhofer O (2014) Feasible mitigation actions in developing countries. Nat Clim Change 4:961–968. https://doi.org/10.1038/nclimate2370

    Article  Google Scholar 

  • Jayachandran S (2015) The roots of gender inequality in developing countries. Annu Rev Econ 7:63–88

    Google Scholar 

  • Kapoor M, Kelejian HH, Prucha IR (2007) Panel data models with spatially correlated error components. J Econom 140:97–130

    Google Scholar 

  • Kapusuzoglou A (2014) Casuality relationships between carbon dioxide emissions and economic growth: results from a multi-country study. Int J Econ Perspect 8(2):5–15

    Google Scholar 

  • Kasman A, Duman YS (2015) CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: a panel data analysis. Econ Model 44:97–103. https://doi.org/10.1016/j.econmod.2014.10.022

    Article  Google Scholar 

  • Kelejian H, Prucha HIR (1997) Estimation of spatial regression models with autoregressive errors by two-stage least squares procedures. A serious problem. Int Reg Sci Rev 20:103–111

    Google Scholar 

  • Konyar K (2001) Assessing the role of US agriculture in reducing greenhouse gas emissions and generating additional environmental benefits. Ecol Econ 38:85–103

    Google Scholar 

  • Larch M, Wanner J (2017) Carbon tariffs: an analysis of the trade, welfare, and emission effects. J Int Econ 109:195–213

    Google Scholar 

  • Lee WJ (2013) The contribution of foreign direct investment to clean energy use, carbon emissions and economic growth. Energy Policy 55:483–489

    Google Scholar 

  • Lee L, Yu J (2009) Some recent developments in spatial panel data models. Reg Sci Urban Econ 1:1–17

    Google Scholar 

  • Lesage JP, Pace RK (2009) Introduction to spatial econometrics. Chapman and Hall/CRC, New York. https://doi.org/10.1201/9781420064254.

    Google Scholar 

  • Millo G, Piras G (2012) splm: spatial panel data models in R. J Stat Softw 1:1–47

    Google Scholar 

  • Moran PAP (1950) Notes on continuous stochastic phenomena. Biometrika 37:17–23

    Google Scholar 

  • Nguyen D, Omri A, Rault C (2014) Causal interactions between CO2 emissions, FDI, and economic growth: evidence from dynamic simultaneous-equation models. Econ Model 42:382–389

    Google Scholar 

  • Paltsev S, Morris J, Cai Y, Karplus V, Jacoby H (2012) The role of China in mitigating climate change. Energy Econ 34:444–450

    Google Scholar 

  • Papa M, Najam A, Taiyab N (2006) Global Environmental Governance. A Reform Agenda. International Institute for Sustainable Development. https://www.iisd.org/pdf/2006/geg.pdf.

  • Pazienza P (2015) The relationship between CO2 and Foreign direct investment in the agriculture and fishing sector of OECD countries: evidence and policy considerations. Intellect Econ 9:55–66

    Google Scholar 

  • Puliafito SE, Allende DG, Castesana PS, Ruggeri MF (2017) High-resolution atmospheric emission inventory of the Argentine energy sector. Comparison with Edgar global emission database. Heliyon 3:489

    Google Scholar 

  • Sanwal M (2007) Trends in global environmental governance: the emergence of a mutual supportiveness approach to achieve sustainable development. Glob Environ Politics 44:16–22

    Google Scholar 

  • Sawada M (2009) Global spatial autocorrelation indices—Moran’s I, Geary’s C and the general cross-product statistic

  • Saygin D, Worrell E, Patel MK, Gielen DJ (2011) Benchmarking the energy use of energy-intensive industries in industrialized and in developing countries. Energy 36:6661–6673

    Google Scholar 

  • Slumeluian K, Shafiee Sarvestani M, Jafari M (2014) Investigating the impact of commercial openness on macro variables in Iranian economy. Q J Econ Res Iran 43:1–21

    Google Scholar 

  • Smarzynska BK, Wei SJ (2001) Pollution havens and foreign direct investment: dirty secret or popular myth. NBER Working Papers from National Bureau of Economic Research, Inc, p 8465. https://econpapers.repec.org/paper/nbrnberwo/8465.htm

  • Smith TE (2010) Spatial Weight Matrices. pp 1–6. ESE 505: https://www.seas.upenn. Accessed Sept 2017

  • Stead D (2015) What does the quality of governance imply for urban prosperity. Habitat Int 45:64–69

    Google Scholar 

  • Steckel JC, Edenhofer O, Jakob M (2015) Drivers for the renaissance of coal. Proc Natl Acad Sci 112:E3775–E3781. https://doi.org/10.1073/pnas.1422722112

    Article  Google Scholar 

  • Tobler WR (1970) A computer movie simulating urban growth in the Detroit region. Econ Geogr 46:234–240

    Google Scholar 

  • Tunc I (2006) CO2 responsibility: an input–output approach for the Turkish economy. Energy Policy 35

  • United Nations (2015) Adoption of the Paris agreement

  • Unruh GCU (2000) Understanding carbon lock-in. Energy Policy 28:817–830

    Google Scholar 

  • World Bank (2008) The International Bank for Reconstruction and Development. https://openknowledge.worldbank.org/handle/10986/5990. Accessed Dec 2016

  • World Bank (2015) Africa development indicators. World Bank, Washington, D.C., USA. [online]. http://siteresources.worldbank.org/AFRICAEXT/Resources/english_essay_adi2010.pdf. Accessed Feb 2017

  • Worldwide governance indicators (2016) https://databank.worldbank.org/source/worldwide-governanceindicators. Accessed Dec 2016.

  • Wrigley N, Holt T, Steel D, Tranmer M (1996) Analysing, modelling, and resolving the ecological fallacy. In: Longley P, Batty M (eds) Spatial analysis: modelling in a GIS environment. GeoInformation International, Cambridge, pp 23–40

    Google Scholar 

  • Xing Y, Kolstad CD (2002) Do lax environmental regulations attract foreign investment. Environ. Resour. Econ 21:1–22

    Google Scholar 

  • Zhang YJ (2011) The impact of financial growth on carbon emissions: an empirical analysis in China. Energy Policy 39:2197–2203

    Google Scholar 

  • Zhou SH (2016) Environmental, social and governance reporting in China. Soc Environ Account J 36:82–93

    Google Scholar 

  • Zra’nzhad M, Anwari I (2005) Using panel data in Econometrics. Econ Stud (economic value) 2:21–52

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Agricultural Economics, Mashhad Ferdowsi University, Mashhad, Iran

    Marzieh Ronaghi

  2. Department of Agricultural Economics, University of Kentucky, Lexington, KY, USA

    Marzieh Ronaghi, Michael Reed & Sayed Saghaian

Authors
  1. Marzieh Ronaghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Reed
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sayed Saghaian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sayed Saghaian.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ronaghi, M., Reed, M. & Saghaian, S. The impact of economic factors and governance on greenhouse gas emission. Environ Econ Policy Stud 22, 153–172 (2020). https://doi.org/10.1007/s10018-019-00250-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10018-019-00250-w

Keywords

JEL Classification

Search

Navigation