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。     

能源价格、效率增进及技术进步对工业行业能源强度的异质性影响

运用全局DEA模型测算中国36个工业行业全要素生产率增长,并将其分解成技术进步效应、纯技术效率变化效应和规模效率变化效应,从多个行业异质性视角对效率增进、技术进步及能源相对价格对工业能源强度的影响进行实证检验。结果表明,效率增进、技术进步及能源价格对工业行业能源强度存在显著的异质性影响,效率增进比技术进步对工业能源强度下降的促进效应更强,能源相对价格提高显著促进高能耗行业能源强度下降,显著推动传统采矿行业能源强度上升,对劳动密集型的轻工行业能源强度无显著影响。     

国内外能源价格走势差异视角下中国出口贸易发展

中国的能源价格机制至今未能真正实现市场化,而主要发达国家在能源价格管理上已经基本依靠市场机制来调节,导致了国内外能源价格走势存在一定的差异。能源作为基础的生产要素之一,其国内外价格走势差异直接影响到商品最终价格的形成,最终势必会影响到中国出口贸易的稳定发展。从国内外能源价格走势差异视角评析中国出口贸易发展历程,探究其存在的发展困境并提出相应的对策。     

能源价格、能耗强度与经济增长

资源、能源短缺对经济发展的制约作用越来越凸显,研究能源价格、能耗强度与经济增长的关系对我国经济转型至关重要。本文运用动态计量经济方法中的VAR模型,实证分析我国经济增长、能源价格和能耗强度之间的内在关系。研究结果显示:长期而言,能源价格的上升对提升能源利用效率有着显著正向影响;经济增长对能源价格的上升有着显著的推动作用;能耗强度的下降伴随着人均实际GDP的上升。实证结果也表明,充分发挥能源价格杠杆的调节作用是提高能源利用效率、实现经济结构转型的重要途径。     

基于博弈论的能源价格研究

能源是现代文明的支柱,是现代经济社会赖以存在的基础。分析了目前我国的能源价格结构现状。研究了我国能源价格体系中存在的问题以及原因。从博弈论的角度讨论了如何形成合理的价格体系。为我国完善能源价格体系提供了切实可行的对策。     

能源价格走势分析

能源是经济生产持续发展重要的物质保障.世界上大多数国家对能源的消费需求在持续增加,部分国家能源的对外依存度逐年增加.为了研究国际能源价格波动如何以及何种程度上影响经济的运行,本文从国际能源(原油、 煤炭)价格的趋势分析出发,分析国际能源价格走势.     

能源价格波动的经济影响 ——以对中国经济运行的影响为例

能源是经济发展中必不可缺的生产资料.上世纪70年代石油价格冲击已对世界经济造成巨大冲击.再加之,近年来国际能源市场价格波动较大,2008年金融危机的发生一定程度上影响了国际能源价格走势,国际能源市场的价格变化更加难以预测.为了研究能源价格波动的经济影响,通过建立中国42部门的一般可计算均衡模型(CGE模型),以中国为例来研究国际能源价格变动对经济的影响.     

武汉市企业能源强度影响因素实证分析

在国内外相关研究成果基础上,针对目前企业能源强度影响因素研究的不足,利用2008年武汉市企业能耗数据,运用多元线性回归方法,对影响企业能源强度的行业、企业规模、能源价格和能源结构等因素进行实证分析,得出各因素对企业能源强度影响程度。     

能源价改：触动中国经济神经

价格市场化是提高能源使用效率最有效的手段。“十一五”节能和提高能源利用效率政策．直接促使一系列能源价格市场化改革措施的出台。2006年，国家发改委对煤、油两大能源产品价格体系进行重大调整。分析显示．在对前些年因受管制而产生的能源价格扭曲进行市场化校正及多重因素的作用下．今年的能源价格将有一定幅度的上涨．相关产业的利益格局分化也将随之加剧。[编者按]     

能源价格上涨对居民消费的影响——基于CGE模型

长期以来我国通过对能源价格的管制,使我国经济的增长建立在高耗能、低效率的经济结构之上,但是这种粗放型的增长模式难以为继。通过构建2010年宏观和微观SAM表,利用CGE模型模拟了各类能源价格上涨对我国居民消费的影响,结果表明各类能源价格上涨对居民消费的影响不同,并且政府对二次能源价格的管控在一定程度上减弱了一次能源价格上涨对居民消费的冲击。因此,在能源价格市场化下,应尽快采取提高能源利用效率、实行阶梯定价和建立基于效率和公平的能源补贴机制等措施,为我国能源市场化改革提供稳定的环境。     

The impact of rising EU Allowance prices on core inflation in the Eurozone

This article examines the impact of EU Allowance (EUA) prices on core inflation in the Eurozone between 2005 and 2022. The empirical results suggest that a positive shock to the EUA price led to higher long-run inflation expectations and core inflation. This implies that the rise in EUA prices can be passed on to consumers and enterprises, leading to an increase in production costs and consumer prices. And, while a positive shock to EUA prices may promote investment in renewable energy in the short term, the impact is not statistically significant and does not last long. The results suggest considerable potential for European policymakers to re-examine policy mechanisms to accelerate renewable energy investment and maintain price stability in the medium term.     

The influence of international oil price fluctuation on the exchange rate of countries along the “Belt and Road”

In recent years, the international crude oil price has become increasingly volatile. It influences the exchange rate changes of relevant countries through economic growth, price level, international balance of payments, and other channels. Such exchange rate fluctuations have caused certain risks for the development of China’s “Belt and Road” Initiative. This article analyzes the impact of oil price changes on the exchange rates of countries. Because the fluctuation of oil prices and exchange rates has shown the characteristics of multiple time scales, this study used the empirical mode decomposition (EMD) method to obtain the long-cycle and short-cycle sequences of oil prices and the exchange rates of various countries, then analyzed the impact of oil price changes on exchange rates under different time scales. The results showed that oil price fluctuations have an impact on the exchange rate changes of countries along the “Belt and Road” under different time scales. However, this effect is asymmetric between oil-producing countries and non-oil-producing countries, and the transmission path of oil prices to exchange rates varies from cycle to cycle.     

试论对涉案财物价格鉴定风险防范

鉴定涉案财物的价格是价格鉴定机构的主要职责,本文通过阐述鉴定涉案财物价格的作用,分析涉案财物价格鉴定风险的表现和风险成因,同时提出相应的风险防范对策,为预防涉案财物价格鉴定风险提供参考依据。     

Unbeatable Value Low‐Price Guarantee: Collusive Mechanism or Advertising Strategy?

This paper investigates the effects of a low-price guarantee (price-beating guarantee) on the patterns of price setting of three supermarkets using micro-level price data. Following recent theoretical developments, the paper analyzes the ability of low-price guarantees to sustain anticompetitive prices. My empirical analysis suggests instead that this low-price guarantee may serve as an advertising device to signal low prices. The supermarket offering the low-price guarantee, aware of its price advantage in a subset of products, uses it to signal low prices to induce consumers to switch supermarkets.     

并购中现金流折现法定价应用研究

我国企业定价不合理,被收购公司价格严重低估。为合理定价被并购公司,用现金流折现法对被并购企业价格估算,详细分析中国石化收购扬子石化并购一案,估算出扬子石化的理论价格,并比较实际价格,提出了并购风险防范方法。     

A POST-KEYNESIAN AGE MODEL TO FORECAST ENERGY DEMAND IN SPAIN

This paper develops an extended input–output model for the estimation of energy demand and related issues. It is built on the last Spanish Symmetric Input–Output Table (IOT, 2005). It has been tested for the period 2005–2008 and used for forecasting energy demand for the years 2009–2012 under different economic scenarios. The model shares some traits of the computable and applied general equilibrium models where quantity and price systems are interwoven. The differences lie in the theories explaining output and prices. Our quantity system is based on Keynes’ principle of effective demand (broad energy multipliers are derived). The price system is based on the classical (Sraffian) theory of prices of production, akin to post-Keynesian full-cost prices. The general price system can be manipulated to account for the specificities of energy prices. Historical trends of energy coefficients are computed by extrapolation of past IOTs and calibration.     

房地产价格波动的经济因素分析

房地产业是国民经济的基础、先导性产业。房地产价格的讨论一直都是热门话题,影响房价的经济因素主要在于供求状况、经济基本面、城市化进程、经济周期、经济全球化等方面。与此同时,政策的变动也是价格波动的因素之一,与经济因素相辅相成。本文从理论上分析了房地产价格的影响因素,并以实际出发分析了房地产价格的构成,就政府如何从根本上抑制房地产价格提出建议。     

Commodity house prices

This paper studies how commodity price movements have affected the local house prices in commodity-dependent economies, Australia and New Zealand. We build a geographically hierarchical empirical model and find that the commodity prices influence local house prices directly and also indirectly through macroeconomic variables. The impacts of commodity price changes are analogous to “income shocks” rather than “cost shocks”. Regional heterogeneity is also observed in terms of differential dynamic responses of local house prices to energy versus non-energy commodity price movements. The results are robust to alternative approaches. Directions for future research are also discussed.     

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.