Breaks or long range dependence in the energy futures volatility: Out-of-sample forecasting and VaR analysis

The aim of this paper is to propose an empirical strategy that allows the discrimination between true and spurious long memory behaviors. That strategy is based on the comparison between the estimated long memory parameter before and after filtering out the breaks. To date the breaks, we use the probability smoothing of the Markov Switching GARCH model of Haas et al. (2004). Application of this strategy to the crude oil, heating oil, RBOB regular gasoline and the propane futures energy with the one, two, three and four months maturities show strong evidence for the presence of long range dependence in all futures energy prices volatility¹ time series. This result of long range dependence in the volatility is confirmed by the superiority of the FIGARCH and FIEGARCH models compared with the Markov switching GARCH models in terms of out-of-sample forecasting and value at risk (VaR) performances. Moreover, we show that the proposed empirical strategy is robust to different data frequency. Practical implications of the results for market participants are proposed and discussed.     

Parameter identification for fractional Ornstein–Uhlenbeck processes based on discrete observation

Fractional Ornstein–Uhlenbeck process is an extended model of the traditional Ornstein–Uhlenbeck process that provides some useful models for many physical and financial phenomena demonstrating long-range dependencies. Obviously, if some phenomenon can be modeled by fractional Ornstein–Uhlenbeck processes, the problem of estimating unknown parameters in these models is of great interest, especially, in discrete time. This paper deals with the problem of estimating the unknown parameters in fractional Ornstein–Uhlenbeck processes. The estimation procedure is built upon the marriage of the quadratic variation method and the maximum likelihood approach. The consistency of these estimators is also provided. Simulation outcomes illustrate that our methodology is efficient and reliable.     

Efficient estimation of partially linear varying coefficient models

In this paper, we consider the problem of estimating a semiparametric partially linear varying coefficient model. We derive the semiparametric efficiency bound for the asymptotic variance of the finite-dimensional parameter estimator. We also propose an efficient estimator for estimating the finite-dimensional parameter of the model. Simulation results show substantial efficiency gain of our proposed estimator over a conventional estimator as considered in Ahmad et al. (2005).     

Implied discount rate and payback threshold of energy efficiency investment in the industrial sector

The industrial sector is responsible for about a third of the energy usage in the United States, and there is significant energy saving potential from the industrial sector. However, the phenomenon of “energy efficiency gap” – the scenario in which cost-effective energy efficient technologies enjoy only limited market success – appears frequently in the industrial sector. This article tries to explain this efficiency gap in the industrial sector by empirically estimating the implied discount rates and payback thresholds industrial firms use to evaluate their energy efficiency investments. Using the Industrial Assessment Centers (IAC) database from 2002 to 2011, with more than 30 000 energy efficiency recommendations, this article builds structural models of firms’ evaluation of an energy efficiency project. The model results show that the implied discount rates of medium to small industrial firms range from 40 to 45%, and the average payback threshold is about 9 months.     

Spatial patterns of flypaper effects for local expenditure by policy objective in Japan: A Bayesian approach

The empirical work on local public finance has found that the marginal effect of lump-sum grants on expenditure is larger than that of income, thereby providing evidence of the “flypaper effect”. However, most existing studies only employ single equation models to test the flypaper effect. In this paper, we specify a seemingly unrelated regression (SUR) model to examine the flypaper effect in Japan, primarily because other categories of expenditure influence the expenditure on particular policy objectives. We also include spatial interaction in our estimation model and employ a Bayesian approach in estimating our model. Our results show that SUR with a spatial error model is better for this purpose than several other specifications. Using this approach, we observe evidence of the flypaper effect in land development, police, education, and debt expenditure, and spatial interaction in sanitation, police, education, and disaster recovery expenditure.     

Conditional density forecast of China’s energy demand via QRNN model

We propose a new method for conditional density forecast of China’s energy demand through quantile regression neural network (QRNN). This method has at least two advantages. First, it is flexible to explore the true nonlinearity in the energy demand system via neural network structure. Second, it is able to describe the whole conditional distribution of energy demand via quantile regression. In the empirical study on China’s energy demand, QRNN outperforms several classical methods in terms of forecast accuracy both in-sample and out-of-sample. Considering China’s economic and social environment, we set a scenario for predictors and forecast the conditional density of China’s energy demand from 2015 to 2020. The empirical results show that the conditional density curve moves to right and its dispersion increases over time, which indicates that the energy demand in China will keep growing with an average annual rate of 9.672% and its uncertainty is enlarged with 42.210%.     

Can investors of Chinese energy stocks benefit from diversification into commodity futures?

We attempt to evaluate the diversification potential of commodity futures for energy stocks in China. With a variety of copula functions and three risk-based dynamic measures, our results show that even though commodity futures are not helpful in improving the risk-adjusted returns of energy stocks, they can significantly reduce the volatilities and expected-shortfalls of the diversified portfolios. Such diversification benefits are much larger during large market downturns than during normal times. In particular, gold (copper) futures are the most (least) attractive in diversifying risks of energy stocks in most cases. The results also highlight that the non-linear dependence cannot be ignored when estimating the diversification benefits, and more various risk hedging strategies are expected for investors holding energy stocks, especially coal company stocks.     

Trends in the extraction of non-renewable resources: The case of fossil energy

This paper considers a strategy for the extraction and production of non-renewable resources that are finite in quantity. Specifically, we illustrate empirical data on reserves, production, consumption, and price evolution for fossil fuel. Our model is an intertemporal model of a short decision time horizon with a monopolistic resource producer extracting non-renewable resources. The model is solved numerically using a finite horizon solution method called Nonlinear Model Predictive Control (NMPC), which approximates well models with a longer decision time horizon. Consistent with the results of recent empirical studies, our numerical solution method shows a U-shaped path for the price and an inverted U-shaped path for the extraction rate, in the case of modest initial stock of proved reserves.     

Measuring capital services by energy use: an empirical comparative study

From an engineering perspective, the service that a capital good provides is energy conversion – that is, the physical ‘work’ done by a machine. A capital good’s service can thus be measured directly by the energy consumed in production. We show important empirical advantages of this approximation over traditional measures. The empirical application reveals that this approach avoids a number of conceptual problems of the latter. Furthermore, this measure captures the utilization of the capital stock more accurately as it is more sensitive to fluctuations in economic activity. With a growth accounting exercise, it is shown that the differences between the new and the traditional measures are important for empirical work. Using the new measure yields significantly different results. Especially in times of global recession it provides higher and more feasible total factor productivity growth rates.     

中国工业部门的能源替代研究——基于对ALLEN替代弹性模型的修正

To overcome the drawbacks in estimating the rate of input substitution in existing econometric models, our paper is first to estimate the absolute/net rate of input substitution of capital and labor for energy in China’s industrial sector. Based on trans-log cost function with constant elasticity of substitution and combined MES method with technology progress and output effect, our paper finds a significant substitution relationship between labor and energy and an uncertain substitution relationship between capital and energy with some complementary characteristics. Furthermore, technology progress and output effect are found to have enhanced the substitution of labor for energy in the past 30 years. Based on these empirical findings, constructive suggestions are made concerning the medium and long-term development strategy of energy in China’s industrial sector. __________ Translated from Shuliang jingji jishu jingji yanjiu 数量经济技术经济研究 (The Journal of Quantitative & Technical Economics), 2008, (5): 30–42     

International sanctions’ impact on energy efficiency in target states

This paper investigates the impact of international sanctions on energy efficiency by employing the panel fixed effect as well as average marginal effect from the Tobit model via data on 30 sanctioned states over the period 1996–2015 with international sanctions including unilateral, plurilateral, U.S., EU, UN, economic, and non-economic cases. Overall, we find that the imposition of unilateral sanctions leads to a 0.067% decrease in energy efficiency, but that of plurilateral sanctions positively contribute to energy efficiency in the case of the full sample of countries. Moreover, the imposition of UN sanctions has a greater decrease on energy efficiency in the target states than the 0.042% reduction of energy efficiency when the sanctionist is the U.S. For robustness, empirical results indicate that the imposition of plurilateral sanctions results in a drop of energy efficiency in Islamic countries, but an increase in non-Islamic countries, while there are also negative shocks induced by the imposition of EU sanctions on energy efficiency in Asian countries, but not for non-Asian countries. We also consider endogenous problems and dynamic specification by using indicator variables and System GMM. In summary, our empirical findings provide policy suggestions for those sanctioned countries about how to maintain energy efficiency when facing international sanctions.     

Model for evaluating the environmental sustainability of energy projects

This article focuses on the problem of assessing the environmental sustainability of energy projects. For this purpose an original model, which is based on various indicators that measure the environmental sustainability of energy projects, has been developed. This model, so called index of environmental sustainability of energy projects (IESEP), can be used in scenario comparison, while measuring the effectiveness of the proposed alternatives. Finally, an example of how to use this model is provided by analyzing alternatives to ameliorate the environmental sustainability of a hydroelectric project. In doing so, it is possible to show the usefulness of this model when used as a decision making tool for energy planners.     

How good are supply function equilibrium models: an empirical analysis of the ERCOT balancing market

We present an empirical analysis of a supply function equilibrium model in the Texas spot electricity market. We derive conditions for optimal bidding behavior in a spot market with ex ante bilaterally contracted sales. By estimating costs, we are able to derive a set of ex post-and ex ante-optimal supply functions and use a non-parametric behavioral model to compare our theoretically optimal supply functions to actual offers made. Our results show that with the exception of the largest generators, firms make offers with markups and markdowns far in excess of what a model of profit-maximizing behavior suggests.     

A model of technological breakthrough in the renewable energy sector

Models with induced technological change in the energy sector often predict a gradual expansion of renewable energies, and a substantial share of fossil fuels remaining in the energy mix through the end of our century. However, there are historical examples where new products or technologies expanded rapidly and achieved a high output in a relatively short period of time. This paper explores the possibility of a ‘technological breakthrough’ in the renewable energy sector, using a partial equilibrium model of energy generation with endogenous R&D. Our results indicate, that due to increasing returns-to-scale, a multiplicity of equilibria can arise. In the model, two stable states can coexist, one characterized by a lower and one by higher supply of renewable energy. The transition from the low-output to the high-output equilibrium is characterized by a discontinuous rise in R&D activity and capacity investments in the renewable energy sector. The transition can be triggered by a rise in world energy demand, by a drop in the supply of fossil fuels, or by policy intervention. Under market conditions, the transition occurs later than in the social optimum. Hence, we identify a market failure related to path-dependence and technological lock-in, that can justify a strong policy intervention initially. Paradoxically, well-intended energy-saving policies can actually lead to higher emissions, as they reduce the incentives to invest in renewable energies by having a cushioning effect on the energy price. Hence, these policies should be supplemented by other instruments that restore the incentives to invest in renewable energies. Finally, we discuss the influence of monopoly power in the market for innovations. We show that market power can alleviate the problem of technological lock-in, but creates a new market failure that reduces static efficiency.     

Quantifying landscape externalities of renewable energy development: Implications of attribute cut-offs in choice experiments

Renewable energy is worldwide seen as a key element necessary to address climate change. However, finding socially acceptable locations for renewable energy facilities and the accompanying infrastructure increasingly often faces fierce opposition. This paper quantifies the landscape externalities of renewable energies employing a choice experiment. In addition, it is investigated how accounting for non-compensatory choice behavior, i.e. attribute cut-offs, affects welfare measures and subsequently policy recommendations. The empirical application is Germany where we conducted a nationwide survey on the development of renewable energies. We first show that cut-off elicitation questions prior to the choice experiment at least partially influence preferences. We further find that most participants state cut-off levels for attributes. Many are, however, at the same time willing to violate the self-imposed thresholds when choosing among the alternatives. To account for this effect, stated cut-offs are incorporated into a mixed logit model following the soft cut-off approach. Model results indicate substantial taste heterogeneity in preferences and in the use of cutoffs. Also, welfare estimates are substantially affected. We conclude that welfare changes from renewable energy development could be strongly underestimated when cut-offs are ignored.     

Modeling corner solutions with panel data: Application to the industrial energy demand in France

This paper provides an empirical application of Lee and Pitts (1986) approach to the problem of corner solutions in the case of panel data. This model deals with corner solutions in a manner consistent with the firm behavior theory while controlling for unobserved heterogeneity. In this model, energy demand at industrial plant level is the result of a discrete choice of the type of the energy to be consumed and a continuous choice that defines the level of demand. The econometric model is, essentially, an endogenous switching regime model which requires the evaluation of multivariate probability integrals. We estimate the random effect model by maximum likelihood using a panel of industrial French plants from the paper and pulp industry. We calculate empirical price elasticities of energy demand from the model. We also study the effects on energy demand of an environmental policy aimed at reducing CO₂ emissions. The authors are grateful to the Institut Français de eEnergie for its financial support and to the SESSI for providing the data. We would like to thank two anonymous referees for useful comments and suggestions. the usual disclaimer applies.     

Heterogeneity in the Effect of Home Energy Audits: Theory and Evidence

A longstanding question in the study of energy demand concerns the role of information as a determinant of home efficiency improvements. Although the provision of information via energy audits is frequently asserted to be an effective means for governments to encourage the implementation of efficiency-enhancing renovations, empirical support for this assertion is tenuous at best. Apart from endogeneity issues with respect to receiving an audit, two other factors have complicated attempts to measure their effect: First, the nature of the information provided by the audit is typically unobserved, and, second, the response to this information may vary over households. Using household data from Germany, we address both sources of heterogeneity by estimating a random-parameter model of four retrofitting alternatives. In addition to confirming the importance of costs and savings as determinants of renovation choices, our results suggest that the effects of consultancy vary substantially across households, with some households responding negatively to the provision of information.     

New models of trader beliefs and their application for explaining financial bubbles

One challenging and exigent problem in behavior finance is how to establish verifiable models describing the appearance and burst of price bubbles. Current results are enhanced in this paper through a series of improvement as follows: new models are proposed for describing the return and dividend processes, especially the trader's behavior with the adaptive expectation belief and the bounded rational expectation belief, respectively; with these models, we establish dynamical systems in terms of the price-to-earnings ratio and the forecast-to-earnings ratio; the detailed solution and asymptotic analysis of these equations provide new, elaborate and quantitative explanations for both the formation and disappearance of different price bubbles; inspired by the herd behavior framework, a new random belief evolutionary mechanism is devised to model the belief change between two beliefs; a specific genetic algorithm is designed to efficiently estimate model parameters; simulation and empirical studies are carried out to illustrate the application of new methods. Both theoretical and empirical results sufficiently show the reasonability, practicality, efficiency and robustness of our new models and methods for properly explaining the appearance and burst of different kinds of price bubbles.     

Bioenergy innovation and energy policy

Using panel data on 13 OECD countries between 1979 and 2008 this paper examines the affect climate and energy policies have had on the rate of biotechnology innovations. The explanatory variables include a vector of important determinants of patenting activity for biotechnologies (e.g. specific and general research and development expenditures, energy consumption, energy prices and total number of registered patents). Fixed effects are employed to capture unobservable country-specific heterogeneity using a negative binomial model. The empirical results indicate that policies are important for stimulating innovations in biotechnologies. The development of feed-in-tariffs (FITs) and the implementation of tradable green certificates have had a positive and statistically significant impact on patent activity. The economic impact of green certificates is found to be larger than that of FITs. In addition, R&D activities have also had a positive and statistically significant effect on innovation.     

A dual theory approach to estimating risk preferences in the parimutuel betting market

This paper introduces an alternative empirical approach to estimating risk preferences in the parimutuel betting market using a dual theory model which is amended to include bettors’ misperceptions of probabilities. We replicate previous empirical results and test our alternative empirical approach using parimutuel horse race betting data. Our results suggest that while bettors are risk-averse, they are also prone to misperceiving probabilities by overweighting low probabilities and underweighting high probabilities. As an application, these results replicate the choice patterns consistent with the Allais paradox.