The Effect of Information and Communication Technology Investment on Energy Intensity in Thailand
Main Article Content
Abstract
The aims of this study are to examine the causal relationship between ICT investment (ICT) and energy intensity (EI) as well as to find out how ICT investment influences the process of energy use in long run, with time series over the period 1990-2017 for the case of Thailand. The result of ARDL shows that ICT has a positive impact on EI by 0.207% in long run through an investment in software and ICT services (ICT2). Per capita GDP (GDPP) and ratio of service output to manufacturing output (SS) increase EI by 0.348% and 0.068% respectively. These reflect that service-driven economy with a rapid expansion of ICT investment tends to pose a further challenge to a goal to reduce energy intensity in Thailand.
From the causal relationship analysis, there is a unidirectional causality running from ICT to EI, and bilateral causality between ICT and GDPP as well as between ICT and SS. A one-way relation running from EI to GDPP is found. This means ICT not only has a direct effect on EI via a change in technology effect but also contains indirect effects on EI through scale effect of GDPP and structure effect of SS. However, the results indicate two-way relations between GDPP, SS and RE as well as a one-way relation from ICT to RE, which suggests 1% increase in RE decreases EI by 0.143. These reflect an increase in energy intensity forced by ICT investment can be optimized by accelerating the deployment of renewable energy. In this respect, the novel findings of this study provide policy makers with a pathway to maintain a proper balance between economic expansions and energy intensity reduction goals, which would drive a future of Thailand’s energy development plan.
Article Details
สงวนลิขสิทธิ์ © 2553 คณะเศรษฐศาสตร์ มหาวิทยาลัยศรีนครินทรวิโรฒ
คณะเศรษฐศาสตร์ มหาวิทยาลัยศรีนครินทรวิโรฒ จัดพิมพ์วารสารเศรษฐศาสตร์และนโยบายสาธารณะ เพื่อเผยแพร่บทความวิชาการทางเศรษฐศาสตร์ นโยบายสารธารณะ และสาขาอื่นๆที่เกี่ยวข้อง ทัศนะและข้อคิดเห็นใดๆที่ปรากฏในวารสารเป็นความคิดเห็นส่วนตัวของผู้เขียน โดยบทความที่ได้รับการตอบรับจะถือเป็นลิขสิทธิ์ของคณะเศรษฐศาสตร์ มหาวิทยาลัยศรีนครินทรวิโรฒ
บรรณาธิการ ผู้ช่วยศาสตราจารย์ ดร.ณัฐญา ประไพพานิช
References
ASEAN. (2018). ASEAN Investment Report 2018: Foreign Direct Investment and the Digital Economy in ASEAN. The ASEAN Secretariat and United Nations Conference on Trade and Development, Jakarta, Indonesia. Retrieved January 2019, from https://asean.org/storage/2018/11/ASEAN-Investment-Report-2018-for-Website.pdf
Bhattacharya, M., Paramati, S.R., Ozturk, I., and Bhattacharya, S. (2016). The Effect of Renewable Energy Consumption on Economic Growth: Evidence from Top 38 Countries. Applied Energy, 162, 733-741.
BOT. (2019). Investments in 3G and 4G Technology Projects in Thailand. Focused and Quick Issue 139, Monetary Policy Group. Bank of Thailand.
Chan, C. A., Gygax, A., Wong, E., Leckie, C. A., Nirmalathas, A., and Kilper, D. (2012). Methodologies for Assessing the Use-Phase Power Consumption and Greenhouse Gas Emissions of Telecommunications Network Services. Environmental Science and Technology, 485-492.
EEP. (2015). Energy Efficiency Plan 2015. Retrieved April 2018, from http://www.eppo.go.th/images /POLICY/PDF/EEP2015.pdf
Ehrlich, P., and Holdren, J.P. (1971). Impact of Population Growth. Science New Series, 171(3977), 1212-1217.
Elliott, G., Stock, J.H., and Rothenberg, T.J. (1996). Efficient Tests for an Autoregressive Unit Root, Econometrica, 64(4), 813-836.
Harris, R., and Sollis, R. (2003). Applied Time Series Modeling and Forecasting. Wiley & Sons, West Sussex, UK.
IEA. (2018). World Energy Outlook 2018. Retrieved January 2019, from https://ethz.ch/content/dam /ethz/special-interest/mavt/process-engineering/separation-processes-laboratory-dam/documents /education/ccs%20notes/World%20Energy%20Outlook%202018.pdf
Islam, N. (1995). Growth empirics: a panel data approach. The Quarterly Journal of Economics, 110(4), 1127-1170.
Kwiatowski, D., Phillips, P.C.B., Schmidt, P., and Shin, Y. (1992). Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root. Econometrica, 54(3), 159-178.
Lin, B., and Zhao, H. (2015). Energy Efficiency and Conservation in China’s Chemical Fiber Industry. Journal of Cleaner Production, 103, 345-352.
Lutkepohl, H. (2006). Structural Vector Autoregressive Analysis for Cointegrated Variables. Chapter of Modern Econometric Analysis: Surveys on Recent Developments, Springer, Berlin, Germany.
Mankiw, N.G., Romer, D., and Weil, D.N. (1992). A Contribution to the Empirics of Economic Growth. The Quarterly Journal of Economics, 107(2), 407-437.
Mustafa, M., and Selassie, H. (2016). Macroeconomic Dynamics of Income Growth: Evidence from ARDL Bound Approach, GMM and Dynamic OLS. European Journal of Business, Economics and Accountancy, 4(5), 32-47.
Öcal, O., and Aslan, A. (2013). Renewable Energy Consumption-Economic Growth Nexus in Turkey. Renewable and Sustainable Energy Reviews, 28, 494-499.
Oh, W., & Lee, K. (2004). Energy Consumption and Economic Growth in Korea: Testing the Causality Relation. Journal of Policy Modeling, 26(8-9), 973-981.
ONEP. (2017). Second Biennial Update Report of Thailand. Office of Natural Resources and Environmental Policy and Planning. Retrieved May 2018, from https://www4.unfccc.int/sites/Submissions Staging/NationalReports/Documents/347251_Thailand-BUR2-1-SBUR%20THAILAND.pdf
Pesaran, M.H., Shin, Y., and Smith, R.J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Applied Econometrics, 16(3), 289-326.
Rosa, E.A., Rudel, T.K., York, R., and Jorgenson, A. (2015). The Human Anthropogenic Driving Forces of Global Climate Change. Chapter of Climate Change and Society: Sociological Perspectives, Oxford University Press, New York, US.
Pokrovski, V.N., (2003). Energy in the Theory of Production. Energy, 28; 769-788.
Sadorsky, P. (2012). “Correlations and Volatility Spillovers between Oil Prices and the Stock Prices of Clean Energy and Technology Companies”. Energy Economics, 34, 248-255.
Salahuddin, M., and Alam, K. (2016). Information and Communication Technology, Electricity Consumption and Economic Growth in OECD Countries: A Panel Data Analysis. International Journal of Electrical Power and Energy Systems, 76, 185-193.
Simelytè, A., and Dudzeviciüté, G. (2017). Consumption of Renewable Energy and Economic Growth. Conference paper: Contemporary Issues in Business, Management and Education, EISSN 2029-7963.
Suh, S. (2007). Indirect Emissions from Services and its Applications for Energy Use and Greenhouse Gas
Emissions. Energy and Environmental Science, 451-468.
Tiwari, A.K. (2011). A Structural VAR Analysis of Renewable Energy Consumption, real GDP, and CO2 Emissions: Evidence from India. Economic Literature, 31(2), 1793-1806.
Türsoy, T. (2017). Causality between Stock Prices and Exchange Rates in Turkey: Empirical Evidence from the ARDL Bounds Test and a Combined Cointegration Approach. International Journal of Financial Studies, 5(1), 1-10.
Uddin, S.G., Sjo, B., and Shahbaz, M. (2013). The Casual Nexus between Financial Development and Economic Growth in Kenya. Economic Modelling, 35, 701-707.
UNFCCC. (2012). Report on the Twenty-First Meeting of the Least Developed Countries Expert Group. United Nations Framework Convention on Climate Change. Retrieved May 2017, from https://unfccc.int /resource/docs/2012/sbi/eng/07.pdf
Virmani, V. (2004). Unit Root Tests: Results from Recent Tests Applied to Select Indian Macroeconomic Variables. Indian Institute of Management Ahmedabad, Gujarat, India.
World Bank. (2018). Investment in ICT in Infrastructure Project Database of World Development Indicator. World Bank Group. Retrieved April 2019, from http://datatopics.worldbank.org/world-development-indicators/.
Yang, Y., Cai, W., and Wang, C. (2014). Industrial CO2 Intensity, Indigenous Innovation and R&D Spillovers in China’s Provinces. Applied Energy, 131, 117-127.
York, R., Rosa, E.A., and Dietz, T. (2003). Footprints on the Earth: The Environmental Consequences of Modernity. American Sociological Review, 68(2), 279-300.