Estimation of inter-fuel substitution possibilities in China's transport industry using ridge regression

In the context of recent energy transition from hydrocarbon molecules to electrons, this research aims to examine the degree of substitution between renewable energy sources and fossil fuels through a dynamic framework of time‐varying parameters under state‐space model. For this purpose, this research selects four major oil‐importing countries and employs annual time series data for crude oil imports, gross domestic product, crude oil price, renewable energy consumption, population growth, real effective exchange rate and industrial production index for each country in the sample while covering the period 1991–2018. The estimates reveal positive and significant income, population and industrial production index elasticities for most of the countries in the sample. In addition, this research finds negative and statistically significant elasticity between renewable energy consumption and demand for imported crude oil for India, China and Japan, although magnitude is very small. However, there is insignificant and little substitution for US data. This research is unique as to our knowledge there is no such study available before and it provides insights for policymakers in oil‐exporting countries to develop sustainable long‐term diversification strategies to reduce reliance on oil revenues.

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“…(2013); Xie et al . (2015); Lin and Ahmad (2016); Lin et al (2016); and Lin and Atsagli (2017). For European data, Marques et al .…”

Section: Literature Reviewmentioning

confidence: 99%

Transition to renewable energy technologies and future prospects for oil‐exporting countries

Khan

Shaheen

2020

OPEC Energy Review

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“…In recent studies, Lin and Astagli [13] took consumption of petroleum and electricity coal consumption as well as capital formation and labor as inputs when they applies the translog production function to investigate technical change and energy substitution possibilities. For China, Xie and Hawkes [14] investigated the potential for inter-fuel substitution between coal, oil, natural gas and electricity in China's transport industry. Long et al [15] used the input matrix to include labor, capital, coal, electricity, and clinker to study the convergence analysis of eco-efficiency of China's cement manufacturers.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy-biased technical change in the Chinese industrial sector with CES production functions

Zha

Kavuri

2018

Energy

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We develop a theoretical framework to study energy-biased technical change considering capital, labor and energy as inputs. The framework involves a first order condition estimation of elasticity and technical change parameters for a three factor-nested Constant Elasticity of Substitution (CES) function. Technical change parameters, elasticities and time derivatives of marginal products are combined to compute technical change bias. Conceptually, we introduce total bias in order to estimate the direction without requiring a direct comparison with another factor. For Chinese industries from 1990 to 2012, the optimal structure is capital and energy to be combined at the composite level and then with labor to form total output. Technical change is found to be unambiguously energy biased, it increases in every year, and the bias is predominately away from labor. The results show that Chinese industrialization was fuelled by fossil fuels and energy-intensive technologies. Nonetheless, the growth rate of energy-biased technical change decreased during the 2000s that may result from more energy efficient development.

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“…To eliminate the influence of multicollinearity, the present research instead uses ridge regression analysis, which is a statistical method that is specially used for analysis of collinearity data. This method cedes the unbiased found in the least square method, but seeks a more practical and suitable regression equation [66,67]. The results of the ridge regression estimation for Equation (9) are described in Table 3.…”

Section: Stirpat-based Modelingmentioning

confidence: 99%

“…To avoid multicollinearity amongst the independent variables, a multicollinearity test was conducted. For this purpose, the variance inflation factor (VIF) analysis [29,67] was used. Based on VIF analyses, each independent variable (factor) was linearly regressed against other independent variables (factors).…”

Section: Analysis Of Driving Forces Of Cropland Changementioning

confidence: 99%

Regional Cooperation for the Sustainable Development and Management in Northeast Asia

2018

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Estimation of inter-fuel substitution possibilities in China's transport industry using ridge regression

Cited by 55 publications

References 28 publications

Transition to renewable energy technologies and future prospects for oil‐exporting countries

Transition to renewable energy technologies and future prospects for oil‐exporting countries

Energy-biased technical change in the Chinese industrial sector with CES production functions

Regional Cooperation for the Sustainable Development and Management in Northeast Asia

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