Nonparametric Efficiency Analysis under Price Uncertainty: A First-Order Stochastic Dominance Approach

This paper extends the nonparametric approach to efficiency analysis to deal with uncertainty of input-output prices. We generalize the notion of economic efficiency to derive necessary and sufficient first-order stochastic dominance (FSD) efficiency conditions. Interestingly, the FSD conditions include as limiting cases the traditional conditions for economic efficiency and technical efficiency. Furthermore, we propose empirical tests for these FSD conditions, which require minimal assumptions concerning the preferences of the decision-maker and the statistical distribution of the prices. From operational point of view, the FSD conditions can be tested empirically using standard mathematical programming techniques. An empirical application to the Dutch electricity distribution sector illustrates the approach.     

能源价格对能源强度的影响——以国内制造业为例

本文运用1985-2003年的时间序列数据，对我国制造业、能源价格和能源强度之间的关系作了实证研究。计量检验的结果表明，能源相对价格的上升对于降低总能源强度、石油强度、电力强度和煤炭强度具有积极的贡献。提高能源价格是改善能源效率的一个有效政策工具。     

Improving Electricity Market Price Forecasting with Factor Models for the Optimal Generation Bid

In liberalized electricity markets, the electricity generation companies usually manage their production by developing hourly bids that are sent to the day‐ahead market. As the prices at which the energy will be purchased are unknown until the end of the bidding process, forecasting of spot prices has become an essential element in electricity management strategies. In this article, we apply forecasting factor models to the market framework in Spain and Portugal and study their performance. Although their goodness of fit is similar to that of autoregressive integrated moving average models, they are easier to implement. The second part of the paper uses the spot‐price forecasting model to generate inputs for a stochastic programming model, which is then used to determine the company's optimal generation bid. The resulting optimal bidding curves are presented and analyzed in the context of the Iberian day‐ahead electricity market.     

Comparisons of Economic Inefficiency Between Output and Input Measures of Technical Inefficiency Using the Fourier Flexible Cost Function

The current paper constructs a Fourier flexible cost function, which is commonly known to be a more general function form than the typical translog form, and can globally approximate a true (but unknown) cost function. Both allocative and technical inefficiencies are considered using the Fourier function in the context of the parametric approach. The former is modeled using shadow input prices and the latter is formulated either by adding an extra term of scale parameter (when the Farrell's (1957) input technical inefficiency is assumed), or by correcting all the terms involving output quantities by a scale parameter (when the Farrell's output technical inefficiency is assumed). It is found that sample banks could save up to 23% of total costs, within the range of 3 and 69% uncovered by the previous works, in which allocative inefficiency plays a more important role than technical inefficiency. Furthermore, the cost of misallocated labor input alone constitutes more than 80% of total allocative inefficiency. Financial deregulation starting from 1991 in Taiwan appears to have improved economic efficiency of the banking industry.     

Creative destruction over the business cycle: a stochastic frontier analysis

This paper examines the within-industry distributions of jobs created and destructed across plants in terms of technical efficiency, technical efficiency change, scale effect, and technical change. It further investigates how these distributions vary with economic activity. By applying the stochastic frontier analysis to plant-level longitudinal data on Taiwan??s 23 two-digit manufacturing industries spanning the period 1992?C2003, we find that jobs created (destructed) are disproportionately clustered at plants with lower technical efficiency but higher rate of technical change. A fall in economic activities is associated with a statistically significant decrease (increase) in the fraction of newly created (destructed) jobs accounted for by plants with a higher rate of technical change, indicating that creative destruction is more pronounced during economic contractions.     

液态高铅渣侧吹还原分析

文章介绍了液态高铅渣侧吹还原工艺及其在工业上的应用,分析了高铅渣侧吹还原熔炼能源消耗及经济效益。阐明了该工艺对提升铅冶炼技术水平实现节能减排的意义和作用。     

Electricity derivatives pricing with forward-looking information

In order to increase overall transparency on key operational information, power transmission system operators publish an increasing amount of fundamental data, including forecasts of electricity demand and available capacity. We employ a fundamental model for electricity prices which lends itself well to integrating such forecasts, while retaining ease of implementation and tractability to allow for analytic derivatives pricing formulae. In an extensive futures pricing study, the pricing performance of our model is shown to further improve based on the inclusion of electricity demand and capacity forecasts, thus confirming the general importance of forward-looking information for electricity derivatives pricing. However, we also find that the usefulness of integrating forecast data into the pricing approach is primarily limited to those periods during which electricity prices are highly sensitive to demand or available capacity, whereas the impact is less visible when fuel prices are the primary underlying driver to prices instead.     

Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?

Solar energy is one of the fastest growing sources of electricity generation. Forecasting solar stock prices is important for investors and venture capitalists interested in the renewable energy sector. This paper uses tree-based machine learning methods to forecast the direction of solar stock prices. The feature set used in prediction includes a selection of well-known technical indicators, silver prices, silver price volatility, and oil price volatility. The solar stock price direction prediction accuracy of random forests, bagging, support vector machines, and extremely randomized trees is much higher than that of logit. For a forecast horizon of between 8 and 20 days, random forests, bagging, support vector machines, and extremely randomized trees achieve a prediction accuracy greater than 85%. Although not as prominent as technical indicators like MA200, WAD, and MA20, oil price volatility and silver price volatility are also important predictors. An investment portfolio trading strategy based on trading signals generated from the extremely randomized trees stock price direction prediction outperforms a simple buy and hold strategy. These results demonstrate the accuracy of using tree-based machine learning methods to forecast the direction of solar stock prices and adds to the broader literature on using machine learning techniques to forecast stock prices.     

Derivation of netput shadow prices under different levels of pest pressure

In this paper, we propose a framework to derive agricultural netput shadow prices that assign values to netputs in terms of their contribution to technical and environmental efficiency. Our modeling approach is based on the dual representation of an event-specific data envelopment model and is applied to a panel dataset of Dutch arable farms. Results show that netput shadow prices vary significantly across pest pressure events, suggesting the relevance to consider the event-specific nature of the production technology when computing them. By revealing the relative importance of pesticides in terms of their contribution to environmental efficiency, this study provides a potential framework for constructing penalties aiming to internalize some portion of the social cost of pesticide use.     

方法、数据与全要素生产率测算差异

研究目标：检验不同方法之间TFP测算结果的“一致性”和“稳健性”,探讨测算方法和数据选取问题。研究方法：以中国2004~2012年总量分行业面板数据为例,从多个角度比较TFP测算结果,以及通过统计检验选取适用测算方法。研究发现：第一,研究的问题不同,测算方法之间“一致性”的检验结论不同;第二,在选择测算方法时,进行相关统计量检验是必要的,这有助于鉴别模型设定是否合理,缩小可选模型范围;第三,测算方法的选择,要符合数据本身的特征,基于宏观分行业面板数据,DEA是更为适用的TFP测算方法,而劳动力投入应选取全社会从业人员指标。研究创新：多种测算方法和统计检验的应用。研究价值：本文尝试构建如何选择TFP测算方法的一般框架。     

Management of nursing homes using data envelopment analysis.

Data envelopment analysis (DEA) is used to evaluate the relative technical efficiency and assist in the management of a chain of nursing homes. As with any DEA model, variables chosen are particularly important. The study looks at two possibly critical issues. The first is the appropriateness of models that include only financial and economic measures to evaluate administrators when quality care is an expected output. The second issue is the appropriateness of using noncontrollable variables, in this case operating income, to evaluate administrators. We show how efficiency scores differ when quality variables and/or operating income are included. We also demonstrate the usefulness of DEA information to both the home administrator and chain managers for improving operating efficiency.     

异质性能源消费与经济增长的非线性动态驱动机制

研究目标：测度改革开放近40年来,中国异质性能源消费与经济增长的非线性动态驱动机制。研究方法：基于煤炭、石油、天然气、电力消费以及GDP年度数据,运用马尔科夫区制转移因果(MSC) 模型开展实证研究。研究发现：经济增长能够促进煤炭、石油、天然气和电力等异质性能源消费的提高,其中,石油和天然气消费的增加能够推动经济增长。经济增长对煤炭和石油消费的驱动作用持续期较长,对天然气和电力消费的驱动作用持续期较短,四种能源消费对经济增长驱动作用的时间长度大致相同。近年来,石油消费能够表现出对经济增长的非线性动态驱动作用,经济增长能够对石油和煤炭消费发挥非线性动态驱动作用。在金融危机时期,难以表现出经济增长对能源消费的单向时变因果影响,其中,煤炭、石油和天然气消费无法表现出对经济增长的单向时变因果影响,而电力消费对经济增长存在单向时变因果影响。研究创新：基于MSC模型,判断不同时段内异质性能源消费与经济增长的时变因果关系,进而揭示两者之间的非线性动态驱动机制。研究价值：为中国完成能源产业结构转型以及构建新时代能源产业体系提供经验证据。     

煤炭价格对燃煤发电项目内部收益率影响关系的研究

煤炭价格对燃煤发电项目经济效益具有决定性影响,煤价与电价的相对水平决定了煤炭行业、电力行业、政府间的利益分配。电力行业的市场化进度相对落后于其上游的煤炭产业,煤炭价格波动对电力企业的运营构成较大的成本风险。内部收益率是燃煤电厂经济效益的关键指标,文章以内部收益率作为研究对象,分析煤炭价格变动对内部收益率的影响,运用回归方法拟合煤炭价格对内部收益率的影响曲线,进一步通过数值差分法得到煤炭价格对内部收益率的微分曲线即边际影响曲线,并利用双曲函数拟合边际影响曲线。研究结果表明,在较低价格区间内,煤炭价格变化对内部收益率的边际影响度较小;在较高价格范围内,边际影响度以双曲函数的形式快速下降。     

Vertical separation of transmission control and market efficiency in the wholesale electricity market

This study examines how vertical separation of transmission control affects the wholesale market efficiency in the electric power industry. We analyze a unique regional electricity wholesale market in the U.S. where initially restructuring only occurred in the transmission sector. Following a commonly-used best dispatch model (Wolfram, 1999; Borenstein et al., 2002), we simulate competitive benchmark prices and compare with the best estimates available for actual prices to measure price-cost markups of the wholesale market. Empirical results demonstrate that the vertical separation of transmission control led to a significant increase in market markups in peak-load hours, documenting evidence of enhanced market power. Although we also find a reduction in the price-cost margin in low-demand hours, we reserve caution for this finding.     

Forecasting electricity prices with expert,linear, and nonlinear models

This paper compares several models for forecasting regional hourly day-ahead electricity prices, while accounting for fundamental drivers. Forecasts of demand, in-feed from renewable energy sources, fossil fuel prices, and physical flows are all included in linear and nonlinear specifications, ranging in the class of ARFIMA-GARCH models—hence including parsimonious autoregressive specifications (known as expert-type models). The results support the adoption of a simple structure that is able to adapt to market conditions. Indeed, we include forecasted demand, wind and solar power, actual generation from hydro, biomass, and waste, weighted imports, and traditional fossil fuels. The inclusion of these exogenous regressors, in both the conditional mean and variance equations, outperforms in point and, especially, in density forecasting when the superior set of models is considered. Indeed, using the model confidence set and considering northern Italian prices, predictions indicate the strong predictive power of regressors, in particular in an expert model augmented for GARCH-type time-varying volatility. Finally, we find that using professional and more timely predictions of consumption and renewable energy sources improves the forecast accuracy of electricity prices more than using predictions publicly available to researchers.     

Eco-efficiency analysis of consumer durables using absolute shadow prices

We develop a method for eco-efficiency analysis of consumer durables that is based on Data Envelopment Analysis (DEA). In contrast to previous product efficiency studies, we consider the measurement problem from the policy perspective. The innovation of the paper is to measure efficiency in terms of absolute shadow prices that are optimized endogenously within the model to maximize efficiency of the good. Thus, the efficiency measure has a direct economic interpretation as a monetary loss due to inefficiency, expressed in some currency unit. The advantages as well as technical differences between the proposed approach and the traditional production-side methods are discussed in detail. We illustrate the approach by an application to eco-efficiency evaluation of Sport Utility Vehicles.     

Information and energy policy preferences: a survey experiment on public opinion about electricity pricing reform in rural India

A common argument for the lack of economic reform in developing countries is popular opposition. If current economic policies are dysfunctional, could information about alternatives sway the voters? We examine if a simple argument emphasizing the need to increase electricity prices for improved supply can change public opinion in the case of India’s power sector reforms. The evidence comes from a survey experiment in rural Uttar Pradesh, which is both India’s largest state and has one of the lowest levels of household electrification. As expected, people respond to information about the relationship between electricity pricing, capacity investment, and reliability of supply by increasing their support for higher prices. However, no corresponding increase is observed for privatization of electricity generation. For external validity, we analyze an existing national survey on electricity privatization conducted in 2004/2005, finding patterns that support our argument.     

300MW火力发电机组引风机变频改造分析

随着国家节能减排政策的深入推进,电网企业实行"竞价上网"政策的逐步推行,通过节能降耗降低发电成本,已经成为各个发电企业增效的重要手段。     

Residential energy demand in the United States: A regional econometric analysis

A static equilibrium and a dynamic partial adjustment model of residential demand for electricity and natural gas are presented and estimated for the United States over a recent period characterized by sharply increasing energy prices. The static model is estimated using Ordinary Least Squares while the instrumental variables method is used for the dynamic partial adjustment model. The estimates of long-run elasticities suggest the residential demand for electricity and natural gas are price and income elastic. Intercept and slope dummies used in the models identify significant regional differences in demand functions.     

Changing the colour of night on urban streets - LED vs. part-night lighting system

Many cities in the United Kingdom are upgrading the streetlights to white light-emitting diode (LED) lamps for reducing the electricity costs and attaining the sustainable energy solutions. Installation of LED lamps on urban street requires higher installation costs and a long-term period to payback benefits of replacing outdated streetlights in terms of energy savings and costs. To achieve the short-term energy efficiency of urban street lighting, city councils sometimes adopt the part-night lighting system particularly in the residential areas. The Coventry City Council recently replaced 29,701 existing sodium lights with LED lamps. This paper performs the economic analyses to understand the feasibility of two street lighting systems: LED lamps and ‘part-night’ lightings on the Coventry streets during the twenty-year period assuming the return period of investment is twenty years. The projection of energy consumption and costs for LED lamps and part-night lighting systems shows that electricity can be saved by 44% and 21% comparing to current electricity usages, respectively. Considering the budgetary constraints of Coventry City Council, this paper concludes that the part-night lighting system may be beneficial in short-term period, but it is economically feasible to replace the existing lower efficiency lights with LED lamps.