Next Article in Journal
Karst as Important Resource for Geopark-Based Tourism: Current State and Biases
Next Article in Special Issue
Stakeholder Management: An Approach in CCS Projects
Previous Article in Journal
Environmental and Social Pressures in Mining. Results from a Sustainability Hotspots Screening
Previous Article in Special Issue
Developing Adequate Communication of Waste Footprints of Products for a Circular Economy—A Stakeholder Consultation
Article Menu
Issue 4 (December) cover image

Export Article

Open AccessArticle
Resources 2018, 7(4), 81; https://doi.org/10.3390/resources7040081

Relationships between Causal Factors Affecting Future Carbon Dioxide Output from Thailand’s Transportation Sector under the Government’s Sustainability Policy: Expanding the SEM-VECM Model

Faculty of Economics, Chulalongkorn University, Wang Mai, Khet Pathum Wan, Bangkok 10330, Thailand
*
Author to whom correspondence should be addressed.
Received: 30 October 2018 / Revised: 28 November 2018 / Accepted: 28 November 2018 / Published: 3 December 2018
Full-Text   |   PDF [2963 KB, uploaded 5 December 2018]   |  
  |   Review Reports

Abstract

This research aims to analyze the relationships between causal factors likely to affect future CO2 emissions from the Thai transportation sector by developing the Structural Equation Modeling-Vector Autoregressive Error Correction Mechanism Model (SEM-VECM Model). This model was created to fill information gaps of older models. In addition, the model provides the unique feature of viable model application for different sectors in various contexts. The model revealed all exogenous variables that have direct and indirect influences over changes in CO2 emissions. The variables show a direct effect at a confidence interval of 99%, including per capita GDP ( Δ ln ( GDP ) t 1 ), labor growth ( Δ ln ( L ) t 1 ), urbanization rate factor ( Δ ln ( U R T ) t 1 ), industrial structure ( Δ ln ( I S ) t 1 ), energy consumption ( Δ ln ( E C ) t 1 ), foreign direct investment ( Δ ln ( F D I ) t 1 ), oil price ( Δ ln ( O P ) t 1 ), and net exports ( Δ ln ( X E ) t 1 ). In addition, it was found that every variable in the SEM-VECM model has an indirect effect on changes in CO2 emissions at a confidence interval of 99%. The SEM-VECM model has the ability to adjust to the equilibrium equivalent to 39%. However, it also helps to identify the degree of direct effect that each causal factor has on the others. Specifically, labor growth ( Δ ln ( L ) t 1 ) had a direct effect on per capita GDP ( Δ ln ( GDP ) t 1 ) and energy consumption ( Δ ln ( E C ) t 1 ) at a confidence interval of 99%, while urbanization rate ( Δ ln ( U R T ) t 1 ) had a direct effect on per capita GDP ( Δ ln ( GDP ) t 1 ), labor growth ( Δ ln ( L ) t 1 ), and net exports ( Δ ln ( X E ) t 1 ) at a confidence interval of 99%. Furthermore, industrial structure ( Δ ln ( I S ) t 1 ) had a direct effect on per capita GDP ( Δ ln ( GDP ) t 1 ) at a confidence interval of 99%, whereas energy consumption ( Δ ln ( E C ) t 1 ) had a direct effect on per capita GDP ( Δ ln ( GDP ) t 1 ) at a confidence interval of 99%. Foreign direct investment ( Δ ln ( F D I ) t 1 ) had a direct effect on per capita GDP ( Δ ln ( GDP ) t 1 ) at a confidence interval of 99%, while oil price ( Δ ln ( O P ) t 1 ) had a direct effect on industrial structure ( Δ ln ( I S ) t 1 ), energy consumption ( Δ ln ( E C ) t 1 ), and net exports ( Δ ln ( X E ) t 1 ) at a confidence interval of 99%. Lastly, net exports ( Δ ln ( X E ) t 1 ) had a direct effect on per capita GDP ( Δ ln ( GDP ) t 1 ) at a confidence interval of 99%. The model eliminates the problem of heteroskedasticity, multicollinearity, and autocorrelation. In addition, it was found that the model is white noise. When the SEM-VECM Model was used for 30-year forecasting (2018–2047), it projected that CO2 emissions would increase steadily by 67.04% (2047/2018) or 123.90 Mt CO2 Eq. by 2047. The performance of the SEM-VECM Model was assessed and produced a mean absolute percentage error (MAPE) of 1.21% and root mean square error (RMSE) of 1.02%. When comparing the performance value with the values of other, older models, the SEM-VECM Model was found to be more effective and useful for future research and policy planning for Thailand’s sustainability goals. View Full-Text
Keywords: CO2 emissions; SEM-VECM model; long-term relationship; economic growth; policy modeling CO2 emissions; SEM-VECM model; long-term relationship; economic growth; policy modeling
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Sutthichaimethee, P.; Ariyasajjakorn, D. Relationships between Causal Factors Affecting Future Carbon Dioxide Output from Thailand’s Transportation Sector under the Government’s Sustainability Policy: Expanding the SEM-VECM Model. Resources 2018, 7, 81.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Resources EISSN 2079-9276 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top