Journal of Finance and Economics
ISSN (Print): 2328-7284 ISSN (Online): 2328-7276 Website: https://www.sciepub.com/journal/jfe Editor-in-chief: Suman Banerjee
Open Access
Journal Browser
Go
Journal of Finance and Economics. 2023, 11(2), 82-91
DOI: 10.12691/jfe-11-2-3
Open AccessArticle

Which Members of OECD are Inactive or Laissez-Faire at Reducing Greenhouse Gas Emissions

Ai-Chi Hsu1, Po-Yuan Shih1 and Ting-Wei Wu2,

1Department of Finance, National Yunlin University of Science & Technology, Douliu, Yunlin 64002, Taiwan

2Department of Information Management, National Yunlin University of Science & Technology, Douliu, Yunlin 64002, Taiwan

Pub. Date: July 10, 2023

Cite this paper:
Ai-Chi Hsu, Po-Yuan Shih and Ting-Wei Wu. Which Members of OECD are Inactive or Laissez-Faire at Reducing Greenhouse Gas Emissions. Journal of Finance and Economics. 2023; 11(2):82-91. doi: 10.12691/jfe-11-2-3

Abstract

Global climate change has become a global challenge. Greenhouse gases are one of the leading causes of climate change, especially the emission of carbon dioxide and other greenhouse gases. The emissions of these gases mainly come from human activities such as energy production and use, industrial activities, transportation, and agriculture. The international community has adopted various agreements to reduce global greenhouse gas emissions and achieve climate goals in response to climate change. However, achieving greenhouse gas targets is about more than just reducing overall emissions. Economic efficiency must also be considered. Economic efficiency refers to the maximum effect achieved in achieving a specific goal: the maximum greenhouse gas reduction effect at the least cost. This study analyzed the economic and greenhouse gas emission reduction efficiency of OECD member countries through the two-stage data envelopment analysis method. And, using quartiles, the OECD member countries' comprehensive efficiency grouping to distinguish which countries are inactive in greenhouse gas emission reduction or countries that are laissez-faire. Finally, the study found that Iceland, Luxembourg, and Ireland chose not to curb greenhouse gas emissions to pursue economic development, while Latvia engaged to do both. Meanwhile, Australia, Canada, and the United States have adopted a laissez-faire approach, making no effort to rein in greenhouse gas emissions and boost national economic growth. The results of this study will provide the United Nations and international organizations with a policy reference to promote the reduction of global greenhouse gas emissions.

Keywords:
greenhouse gas reduction air pollution data envelopment analysis efficiency analysis GDP

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Peter, C., Helming, K., & Nendel, C. (2017). Do greenhouse gas emission calculations from energy crop cultivation reflect actual agricultural management practices?–A review of carbon footprint calculators. Renewable and Sustainable Energy Reviews, 67, 461-476.
 
[2]  Yamaka, W., Phadkantha, R., & Rakpho, P. (2021). Economic and energy impacts on greenhouse gas emissions: A case study of China and the USA. Energy Reports, 7, 240-247.
 
[3]  Aquilas, N. A., & Atemnkeng, J. T. (2022). Climate-related development finance and renewable energy consumption in greenhouse gas emissions reduction in the Congo basin. Energy Strategy Reviews, 44, 100971.
 
[4]  Cheng, B., Li, J., Su, H., Lu, K., Chen, H., & Huang, J. (2022). Life cycle assessment of greenhouse gas emission reduction through bike-sharing for sustainable cities. Sustainable Energy Technologies and Assessments, 53, 102789.
 
[5]  Wang, D., Du, Z., & Wu, H. (2020). Ranking global cities based on economic performance and climate change mitigation. Sustainable cities and society, 62, 102395.
 
[6]  Moutinho, V., & Madaleno, M. (2021). A two-stage DEA model to evaluate the technical eco-efficiency indicator in the EU countries. International Journal of Environmental Research and Public Health, 18(6), 3038.
 
[7]  Iqbal, W., Altalbe, A., Fatima, A., Ali, A., & Hou, Y. (2019). A DEA approach for assessing the energy, environmental and economic performance of top 20 industrial countries. Processes, 7(12), 902
 
[8]  EPA, U.S. Environmental Protection Agency, 2022 Guidance on control strategies for state and local agencies available at: www.epa.gov/state-and-local-transportation/guidance-control-strategies-state-and-local-agencies(Accessed 20 February 2023)
 
[9]  Nunez, C. (2019). Carbon dioxide levels are at a record high. Here’s what you need to know. National geographic, 13.
 
[10]  Kweku, D. W., Bismark, O., Maxwell, A., Desmond, K. A., Danso, K. B., Oti-Mensah, E. A., ... & Adormaa, B. B. (2018). Greenhouse effect: greenhouse gases and their impact on global warming. Journal of Scientific research and reports, 17(6), 1-9.
 
[11]  Rypdal, K., & Winiwarter, W. (2001). Uncertainties in greenhouse gas emission inventories—evaluation, comparability and implications. Environmental Science & Policy, 4(2-3), 107-116.
 
[12]  Zhang, Z., Qu, J., & Zeng, J. (2008). A quantitative comparison and analysis on the assessment indicators of greenhouse gases emission. Journal of Geographical Sciences, 18, 387-399.
 
[13]  Xu, X., Wei, Z., Ji, Q., Wang, C., & Gao, G. (2019). Global renewable energy development: Influencing factors, trend predictions and countermeasures. Resources Policy, 63, 101470.
 
[14]  Kazancoglu, Y., Ozbiltekin-Pala, M., & Ozkan-Ozen, Y. D. (2021). Prediction and evaluation of greenhouse gas emissions for sustainable road transport within Europe. Sustainable Cities and Society, 70, 102924.
 
[15]  Altikat, S. (2021). Prediction of CO2 emission from greenhouse to atmosphere with artificial neural networks and deep learning neural networks. International Journal of Environmental Science and Technology, 18(10), 3169-3178.
 
[16]  Wang, Q., & Zhang, F. (2021). The effects of trade openness on decoupling carbon emissions from economic growth–evidence from 182 countries. Journal of cleaner production, 279, 123838.
 
[17]  Oertel, C., Matschullat, J., Zurba, K., Zimmermann, F., & Erasmi, S. (2016). Greenhouse gas emissions from soils—A review. Geochemistry, 76(3), 327-352.
 
[18]  Lamb, W. F., Wiedmann, T., Pongratz, J., Andrew, R., Crippa, M., Olivier, J. G., ... & Minx, J. (2021). A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018. Environmental research letters, 16(7), 073005.
 
[19]  Shaw, B. K., Sangal, I., & Sarkar, B. (2022). Reduction of greenhouse gas emissions in an imperfect production process under breakdown consideration. AIMS Environmental Science, 9(5), 658-691.
 
[20]  Ji, Y. B., & Lee, C. (2010). Data envelopment analysis. The Stata Journal, 10(2), 267-280.
 
[21]  Kaffash, S., Azizi, R., Huang, Y., & Zhu, J. (2020). A survey of data envelopment analysis applications in the insurance industry 1993–2018. European journal of operational research, 284(3), 801-813.
 
[22]  Mahmoudi, R., Emrouznejad, A., Shetab-Boushehri, S. N., & Hejazi, S. R. (2020). The origins, development and future directions of data envelopment analysis approach in transportation systems. Socio-Economic Planning Sciences, 69, 100672.
 
[23]  Sarraf, F., & Nejad, S. H. (2020). Improving performance evaluation based on balanced scorecard with grey relational analysis and data envelopment analysis approaches: Case study in water and wastewater companies. Evaluation and program planning, 79, 101762.
 
[24]  Luo, Q., Miao, C., Sun, L., Meng, X., & Duan, M. (2019). Efficiency evaluation of green technology innovation of China's strategic emerging industries: An empirical analysis based on Malmquist-data envelopment analysis index. Journal of Cleaner Production, 238, 117782.
 
[25]  Nong, N. M. T. (2022). An application of delphi and dea to performance efficiency assessment of retail stores in fashion industry. The Asian Journal of Shipping and Logistics, 38(3), 135-142.
 
[26]  Forouzandeh, F., Arman, H., Hadi-Vencheh, A., & Rahimi, A. M. (2022). A combination of DEA and AIMSUN to manage big data when evaluating the performance of bus lines. Information Sciences, 618, 72-86.
 
[27]  Nong, T. N. M. (2022). Performance efficiency assessment of Vietnamese ports: An application of Delphi with Kamet principles and DEA model. The Asian Journal of Shipping and Logistics.
 
[28]  Flegl, M., & Gress, E. S. H. (2023). A two-stage Data Envelopment Analysis model for investigating the efficiency of the public security in Mexico. Decision Analytics Journal, 100181.
 
[29]  Rebolledo-Leiva, R., Angulo-Meza, L., Iriarte, A., & González-Araya, M. C. (2017). Joint carbon footprint assessment and data envelopment analysis for the reduction of greenhouse gas emissions in agriculture production. Science of the Total Environment, 593, 36-46.
 
[30]  Kao, C., & Hwang, S. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European journal of operational research, 185(1), 418-429.
 
[31]  Chen, F., Lyu, J., & Wang, T. (2020). Benchmarking road safety development across OECD countries: An empirical analysis for a decade. Accident Analysis & Prevention, 147, 105752.
 
[32]  Krausmann, F., Gingrich, S., Eisenmenger, N., Erb, K. H., Haberl, H., & Fischer-Kowalski, M. (2009). Growth in global materials use, GDP and population during the 20th century. Ecological economics, 68(10), 2696-2705.
 
[33]  Kitov, I. O. (2008). GDP growth rate and population. arXiv preprint arXiv:0811.2125.
 
[34]  Mohsen, A. S. (2015). The relationship between trade openness and investment in Syria. Journal of Life Economics, 2(2), 19-28.
 
[35]  Pologeorgis (2022). Employability, the Labor Force, and the Economy,investopedia,https://www.investopedia.com/articles/economics/12/employability-labor-force-economy.asp
 
[36]  Majid, N. (2004). What is the Effect of Trade Openness on Wages? (No. 2004-18). International Labour Office.
 
[37]  Madanizadeh, S. A., & Pilvar, H. (2019). The impact of trade openness on labour force participation rate. Applied Economics, 51(24), 2654-2668.
 
[38]  Campo, J., & Sarmiento, V. (2013). The relationship between energy consumption and GDP: Evidence from a panel of 10 Latin American countries. Latin american journal of economics, 50(2), 233-255.
 
[39]  Nayan, S., Kadir, N., Ahmad, M., & Abdullah, M. S. (2013). Revisiting energy consumption and GDP: Evidence from dynamic panel data analysis. Procedia Economics and Finance, 7, 42-47.
 
[40]  Guo, J., Li, C. Z., & Wei, C. (2021). Decoupling economic and energy growth: aspiration or reality?. Environmental Research Letters, 16(4), 044017.
 
[41]  Odhiambo, N. M. (2021). Trade openness and energy consumption in sub-Saharan African countries: A multivariate panel Granger causality test. Energy Reports, 7, 7082-7089.
 
[42]  Osei-Assibey Bonsu, M., & Wang, Y. (2022). The triangular relationship between energy consumption, trade openness and economic growth: new empirical evidence. Cogent Economics & Finance, 10(1), 2140520.
 
[43]  Qi, M., Xu, J., & Amuji, N. (2022, April 21). Energy Consumption, Economic Growth and Trade Openness. In Encyclopedia. https://encyclopedia.pub/entry/22055
 
[44]  Tucker, M. (1995). Carbon dioxide emissions and global GDP. Ecological Economics, 15(3), 215-223.
 
[45]  Cederborg, J., & Snöbohm, S. (2016). Is there a relationship between economic growth and carbon dioxide emissions?.
 
[46]  Hughes, L., & Herian, A. (2018). The correlation between GDP and greenhouse gas emissions.
 
[47]  Dou, Y., Zhao, J., Malik, M. N., & Dong, K. (2021). Assessing the impact of trade openness on CO2 emissions: evidence from China-Japan-ROK FTA countries. Journal of environmental management, 296, 113241.
 
[48]  Chen, F., Jiang, G., & Kitila, G. M. (2021). Trade openness and CO2 emissions: The heterogeneous and mediating effects for the belt and road countries. Sustainability, 13(4), 1958.
 
[49]  Islam, M., Kanemoto, K., & Managi, S. (2016). Impact of trade openness and sector trade on embodied greenhouse gases emissions and air pollutants. Journal of Industrial Ecology, 20(3), 494-505.
 
[50]  Foo, K., Cooper, J., Deaner, A., Knight, C., Suliman, A., Ranjadayalan, K., & Timmis, A. D. (2003). A single serum glucose measurement predicts adverse outcomes across the whole range of acute coronary syndromes. Heart, 89(5), 512-516.
 
[51]  Spichtig, A. N., Pascoe, J. P., Ferrara, J. D., & Vorstius, C. (2017). A comparison of eye movement measures across reading efficiency quartile groups in elementary, middle, and high school students in the US. Journal of eye movement research, 10(4).
 
[52]  Burguillo, M., del Río, P., & Jordán, D. R. (2017). Car use behaviour of Spanish households: Differences for quartile income groups and transport policy implications. Case Studies on Transport Policy, 5(1), 150-158.
 
[53]  Rugani, B., Marvuglia, A., & Pulselli, F. M. (2018). Predicting Sustainable Economic Welfare–Analysis and perspectives for Luxembourg based on energy policy scenarios. Technological Forecasting and Social Change, 137, 288-303.
 
[54]  Rugani, B., Benetto, E., Igos, E., Quinti, G., Declich, A., & Feudo, F. (2014). Towards prospective life cycle sustainability analysis: exploring complementarities between social and environmental life cycle assessments for the case of Luxembourg’s energy system. Matériaux & Techniques, 102(6-7), 605.
 
[55]  Clarke, J., Heinonen, J., & Ottelin, J. (2017). Emissions in a decarbonised economy? Global lessons from a carbon footprint analysis of Iceland. Journal of Cleaner Production, 166, 1175-1186.
 
[56]  Boyd, R., Turner, J., & Ward, B. (2015). Intended nationally determined contributions: what are the implications for greenhouse gas emissions in 2030?.
 
[57]  Casaban, D., & Tsalaporta, E. (2022). Direct air capture of CO2 in the Republic of Ireland. Is it necessary?. Energy Reports, 8, 10449-10463.
 
[58]  Bhatnagar, N., Ryan, D., Murphy, R., & Enright, A. M. (2022). A comprehensive review of green policy, anaerobic digestion of animal manure and chicken litter feedstock potential–Global and Irish perspective. Renewable and Sustainable Energy Reviews, 154, 111884.
 
[59]  Lukjanova, J., Sushchenko, O., & Zyma, O. (2019). Educated and competent staff as important factor of innovation development of machine-building and metalworking industry in Latvia. In MATEC Web of Conferences (Vol. 297, p. 06006). EDP Sciences.
 
[60]  Brizga, J., Jurušs, M., & Šmite-Roķe, B. (2022). Impact of the environmental taxes on reduction of emission from transport in Latvia. Post-Communist Economies, 34(5), 666-683.
 
[61]  Alam, M. M., Wei, H., & Wahid, A. N. (2021). COVID‐19 outbreak and sectoral performance of the Australian stock market: An event study analysis. Australian economic papers, 60(3), 482-495.
 
[62]  Maestas, N., Mullen, K. J., & Powell, D. (2023). The effect of population aging on economic growth, the labor force, and productivity. American Economic Journal: Macroeconomics, 15(2), 306-332.
 
[63]  Liang, S., Qu, S., Zhu, Z., Guan, D., & Xu, M. (2017). Income-based greenhouse gas emissions of nations. Environmental science & technology, 51(1), 346-355
 
[64]  Davis, M., Ahiduzzaman, M., & Kumar, A. (2018). How will Canada’s greenhouse gas emissions change by 2050? A disaggregated analysis of past and future greenhouse gas emissions using bottom-up energy modelling and Sankey diagrams. Applied energy, 220, 754-786.
 
[65]  Ge, M., Friedrich, J., & Damassa, T. (6). 6 graphs explain the world’s top 10 emitters.
 
[66]  Crippa, M., Oreggioni, G., Guizzardi, D., Muntean, M., Schaaf, E., Lo Vullo, E., ... & Vignati, E. (2019). Fossil CO2 and GHG emissions of all world countries. Publication Office of the European Union: Luxemburg.