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The Energy Journal
Volume 44, Number 2

Debt and Optionality in U.S. LNG Export Projects

Peter R. Hartley and Kenneth B. Medlock III

DOI: 10.5547/01956574.44.2.phar
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U.S. liquefied natural gas (LNG) export projects have substantially more spot trading of LNG than traditional projects. While this reduces the debt capacity of the projects, it allows project developers to better exploit many types of real options. Exploiting those options greatly increases the positive skewness of project cash flows. While the modal operating profits for a representative U.S. LNG export project are unlikely to cover fixed costs, interest and taxes at usual leverage ratios, the mean real equity return is likely to be positive. Some quarters could return extremely high profits. Understanding determinants of spot trading of LNG matters because increased spot trading will better integrate global natural gas markets.

Impact of the Feed-in Tariff Policy on Renewable Innovation: Evidence from Wind Power Industry and Photovoltaic Power Industry in China

Boqiang Lin and Yufang Chen

DOI: 10.5547/01956574.44.2.blin
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Technological innovation is the key to develop wind power and photovoltaic power industries. The feed-in tariff (FIT) policy, as a demand-pull policy, is important to support renewable energy technological innovation. Using the "difference-in-differences" method, this paper investigates the impact of FIT policy of wind power and the impact of the FIT policy designed according to differences in the distribution of resources on wind power technological innovation. The findings show that the FIT policy can drive patenting in wind power technologies during the implementation period, but may play a relatively weak promoting role in technological innovation in the latter term, and the FIT policy designed according to differences in the distribution of resources also stimulates more patent counts. Finally, based on the fixed effect negative binomial regression model, this paper finds that the higher feed-in tariffs can increase the patent counts in photovoltaic power technologies.

Are Autocracies Bad for the Environment? Global Evidence from Two Centuries of Data

Apra Sinha, Ashish Kumar Sedai, Abhishek Kumar, and Rabindra Nepal

DOI: 10.5547/01956574.44.2.asin
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Reducing carbon dioxide emissions is crucial for reducing the danger posed by climate change. There are factors for and against democracies in achieving these desired reductions. Using data from 150 countries, we estimate the marginal emission intensity (i.e., the change in per-capita carbon dioxide emissions for a unit change in per-capita income) across autocracies and democracies. We use regional waves of democratization and mean per-capita income of other countries in the region as instruments for democracy and per-capita income, respectively. Using these instruments, we obtain the causal estimate of the difference in marginal emission intensity and confirm that democracies have lower per-capita carbon dioxide emissions per unit increase in per-capita income compared to autocracies. Our results suggest that these benefits of democracies have occurred in recent decades, following the surge in public concerns about climate change and intergovernmental initiatives to reduce emissions. There is also evidence to suggest that strengthening rule enforcement and improving access to justice can be critical in decreasing carbon dioxide emissions.

Impact of Low-carbon City Construction on Financing, Investment, and Total Factor Productivity of Energy-intensive Enterprises

Huwei Wen, Shuai Chen, and Chien-Chiang Lee

DOI: 10.5547/01956574.44.2.hwen
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Faced with the global climate change, as a major greenhouse gas emitter, China launched a pilot policy on low-carbon city construction since 2010. Few studies have discussed how climate policies affect the investment and financing behavior of energy-intensive enterprises. Based on the micro data of A-share listed enterprises in China’s energy-intensive industries, this study aims to assess the productivity effect of low-carbon city pilot (LCCP) policy and investigates the mechanism of financing and investment using the difference-in-difference method. Empirical results provide evidence that the LCCP policy has significantly improved the total factor productivity of energy-intensive enterprises. In terms of the mechanisms, the LCCP policy has increased the supply of bank credit to enterprises and encouraged their long-term investment in fixed assets and R&D activities. The productivity effect of the LCCP policy is greater for state-owned enterprises and enterprises with political connection. Urban human capital, industrial agglomeration, and resource endowment contribute to the productivity effect of LCCP policy for enterprises in the energy-intensive industries. The findings show that the LCCP is an effective comprehensive policy to promote the high-quality development of energy-intensive industries, and the findings also provide enlightenment for enacting better climate transition policies.

Coping with Externally Imposed Energy Constraints: Competitiveness and Operational Impact of China’s Top-1000 Energy-Consuming Enterprises Program

Yuxian Xiao, Haitao Yin, and Jon J. Moon

DOI: 10.5547/01956574.44.2.yxia
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Global climate change has caused governments worldwide to take actions to improve their energy efficiency. This paper investigates how China's Top-1000 program, a command-and-control type of energy-saving mandate, has affected the operational choices of firms, and in turn, their profitability. We apply the propensity score matching method to find "identical twins" for the participants in the Top-1000 program, then conduct a difference-in-differences analysis on the matched sample. Our findings suggest that the profitability of the enterprises targeted for energy savings decreased by one-third, mainly due to increased production costs. The targeted enterprises tended to increase their fixed assets per capita, which was associated with improvements in energy efficiency. Furthermore, compared to similar untargeted enterprises, there was a significant slowdown in the production growths of the targeted enterprises, raising concerns about carbon leakage due to increased production by less efficient producers.

Downside Risk and Portfolio Optimization of Energy Stocks: A Study on the Extreme Value Theory and the Vine Copula Approach

Madhusudan Karmakar and Samit Paul

DOI: 10.5547/01956574.44.2.mkar
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Energy stocks are potentially a hedge against inflation and have a number of advantages over other forms of energy investing. This motivates us to study on portfolio management of energy stocks. We compare the performance of proposed GARCH-EVT-vine copula models under three different dimensions with other competing models using energy stocks from the U.S. market. In our proposed model, we use static C- and D-vine copulas. We compare the accuracy and efficiency of different models in forecasting portfolio VaR and CVaR. We also examine whether the proposed models yield greater economic and statistical performances than the competing models in a tactical asset allocation framework. Our findings indicate that the proposed models perform best overall. In fact, the relatively better performance of the proposed model is even more prominent when the portfolio size increases. Further, the comparative analysis between GARCH-EVT- static vine and GARCH-EVT-dynamic vine copula models produces mixed results.

Efficiency Measurement in Norwegian Electricity Distribution: A Generalized Four-Way-Error-Component Stochastic

Mike G. Tsionas and Subal C. Kumbhakar

DOI: 10.5547/01956574.44.2.mtsi
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In this paper, we introduce a new model to estimate efficiency by generalizing the state-of-the-art panel stochastic frontier model, the salient feature of which is decomposition of inefficiency into a persistent and a transient component. The proposed model introduces an autoregressive process to allow for temporal dependence in transient inefficiency. Both firm heterogeneity and persistent inefficiency components are allowed to be correlated with some exogenous and endogenous covariates in the model. Our model solves the endogeneity problem and it also introduces determinants of both persistent and transient inefficiency. Since the transient component is autoregressive, the likelihood function is not available in closed form. To address this problem we use the Maximum Simulated Likelihood and (Simulated or Bayes) Generalized Method of Moments method to estimate the parameters and several other quantities of interest, including transient and persistent inefficiency. Since the model is dynamic and accommodates determinants of inefficiency, it is useful to production managers who wish to identify how much of their present inefficiency is affected by past inefficiency, as well as how and in what ways efficiency can be improved. We use Norwegian electricity distribution data to showcase an application of our model.

The Thirst for Power: The Impacts of Water Availability on Electricity Generation in China

Yao An and Lin Zhang

DOI: 10.5547/01956574.44.2.yaan
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Economic development under restricted resource availability has become a complex challenge for both developing and well-established economies. To maintain a sustainable electricity supply and mitigate the impact of water shortage on economic development, it is therefore important to understand how utility firms respond to the change in water availability and unpacks the underlying mechanisms of power outage. By pairing plant-level information with the fine-scale grid monthly meteorological data, we find significant plant-level technology substitution in response to water scarcity: a one-standard-deviation decrease in water availability causes an approximate 205 GWh decline per hydro power plant, a 145 GWh increase per nuclear plant, and a 28 GWh increase per coal-fired plant. This water-induced technology substitution takes place within the grid, and we do not identify cross-grid adjustment. Our estimation shows that the technology substitution is associated with a hidden increase in carbon emission up to 32000 tons per year by plant, resulting in an additional cost of 0.18 million USD. Water scarcity slows down the transition towards renewable energy.

Investigating the Determinants of the Growth of the New Energy Industry: Using Quantile Regression Approach

Bin Xu and Boqiang Lin

DOI: 10.5547/01956574.44.2.bixu
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Expanding the supplies of new energy can not only reduce CO2 emissions, but also alleviate energy shortage. This paper applies the quantile regression to investigate the new energy industry in China. The results show that economic growth exerts the greatest effect on the new energy industry in the lower 10th quantile province. This is because these provinces have the developed economies, demand for a higher ecological environment and new energy resources. Foreign energy dependence has a minimal impact on the new energy industry in the 25th–50th quantile province, due to their minimal oil importation. The contribution of technological progress to the upper 90th quantile province is the lowest, because their R&D capabilities are the weakest. The impact of energy consumption structure decreases in steps from the lower 10th quantile provinces to the upper 90th quantile provinces. The agricultural sector promotes the new energy industry in most provinces.

Time-Frequency Spillovers and the Determinants among Fossil Energy, Clean Energy and Metal Markets

Qian Ding, Jianbai Huang, and Jinyu Chen

DOI: 10.5547/01956574.44.2.qdin
View Abstract

Using the frequency-domain spillover index method, we investigate time-frequency spillovers and their underlying drivers among fossil energy, clean energy and metal markets. We find that short-term spillovers are stronger than long-term spillovers. Global clean energy markets are powerful spillover transmitters that can have strong impacts on fossil energy and metal markets. Rare earth metals are most vulnerable to spillover effects from clean energy and base metal markets, particularly in the long term. Different clean energy sources and metal markets have heterogeneous connectedness, e.g., the impact of wind energy on rare earth market is greater than that of solar energy. The short-term spillovers are mainly driven by policy changes, while the long-term spillovers are mainly affected by stock market uncertainty and economic fundamentals. Our findings have important implications for the construction of optimal diversification strategies and the design of policy incentives to promote clean energy investments across different time horizons.

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