石化产品价格的影响因素及策略分析

影响石化产品价格的因素比较多,但投机因素的比重日渐加大。分析影响石化产品价格的影响因素对石化企业的发展有重要意义。本文从企业不可控和可控两个方面分析了影响价格的众多因素。在考虑众多影响因素的基础上,提出具体的价格操作策略。     

How can big data enhance the timeliness of official statistics?: The case of the U.S. consumer price index

The daily consumer price index (CPI) produced by the Billion Prices Project (BPP CPI) offers a glimpse of the direction taken by consumer price inflation in real time. This is in contrast to the official U.S. CPI, which is compiled monthly and released with an average of a three-week delay following the end of the reference month. A recent body of research contended that the movements of online prices are representative of those of offline retail prices, making the BPP CPI a natural candidate for accurately improving the timeliness of the official CPI. We assess the predictive content of the BPP CPI using a variety of MIDAS models that accommodate data sampled at different frequencies. These models generate estimates that remain robust to the variety of time periods considered and, by the standard of the existing literature, contribute to a significant upgrade in the forecast accuracy of official consumer price inflation figures. The paper then sketches the broad implications of BPP CPI for the consumer price statistics maintained by national statistics offices and discusses how the proposed improvement in the timeliness of the official CPI fits in this perspective.     

The asymmetric effect of crude oil prices on stock prices in major international financial markets

The aim of this paper is to explore the potential asymmetric impacts of positive and negative shocks in crude oil prices on stock prices in six major international financial markets which include China, Hong Kong, America, Japan, Britain, and Germany. We test for these asymmetric effects on 8 major international financial markets indices over the 2007M01–2020M03 periods. Our independent measures include the prices of Brent crude oil futures and West Texas Intermediate (WTI) futures. We use the nonlinear ARDL (NARDL) model proposed by Shin et al. (2014), which can capture both short- and long-run nonlinearities through positive and negative partial sum decompositions of the explanatory variables. This research finds that positive and negative fluctuations of oil price have asymmetric effects on stock price index in four financial markets, but the performance of the asymmetry is different. Specifically, the impacts of volatility in oil prices on two indices of Chinese stock prices are different, and the asymmetric effects of oil price volatility on stock price indices in China and other financial markets are significantly different.     

Carpooling and driver responses to fuel price changes: Evidence from traffic flows in Los Angeles

We examine carpooling and driver responses to fuel price changes. Using a simple theoretical model, we show that traffic flows in mainline lanes unambiguously decrease when fuel prices increase, and this effect is stronger when the presence of a carpool lane provides a substitute to driving alone. In contrast, in carpool (HOV) lanes flow can either increase or decrease. These predictions are tested using 8 years of traffic flow data for 1700 locations in Los Angeles. In our preferred specification, the mean elasticity of flow with respect to fuel price is 0.136 for HOV lanes. For a 10% increase in fuel price this implies 10 additional carpools per hour, $8.8 million per year in additional congestion costs for carpoolers and $11.3 million lower costs for mainline drivers. For mainline lanes, flow elasticities are −0.083 and −0.050 for highways with and without an HOV lane. These estimates imply that the mean highway with an HOV lane experiences a 30% larger decrease in hourly flow compared to the mean highway without an HOV lane. Flows in HOV lanes show an immediate decrease following a price increase but respond positively to price increases over time, which suggests time is an important input to carpool formation.     

Price Discrimination in Input Markets: Downstream Entry and Efficiency

The extant theory on price discrimination in input markets takes the structure of the downstream industry as exogenously given. This paper endogenizes the structure of the downstream industry and examines the effects of permitting third‐degree price discrimination on market structure and welfare. We identify situations where permitting price discrimination leads to either higher or lower wholesale prices for all downstream firms. These findings are driven by upstream profits being discontinuous due to costly entry. Moreover, permitting price discrimination fosters entry which often improves welfare. Nevertheless, entry can also reduce welfare because it may lead to a severe inefficiency in production.     

刍议工程招标中拦标价的设立

针对目前工程量清单招标项目中设立拦标价的做法是否合法合理,以及如何准确计算拦标价仍存在一定的争议。论述了拦标价设立的目的、作用、法规依据和造价依据以及拦标价在应用中存在的一些问题,提出了一种基于概率论的知识来确定拦标价上浮比例的方法,并指出拦标价在招标和评标应用中需要注意的问题。     

网络环境下信息商品的价格歧视初探

本文首先阐述信息商品的特点,接着解释价格歧视的概念和分类;在此基础上又进一步分析信息商品的价格歧视现象。最后探讨网络环境对信息商品的价格歧视策略的种种影响。     

Deregulation and price discrimination in the conveyancing market

Using data from a telephone survey of solicitors in England and Wales, this paper presents data on the impact of deregulation on price discrimination in 27 local conveyancing markets. It is concluded that variations in price discrimination can be explained not only by differences by firm and market structure but also by systematic differences in firm conduct. In particular, the nature of the response within different markets to deregulation in the legal profession (advertising and licensed conveyancers) has a significant effect on the extent of price discrimination.     

When Price Discrimination Fails – A Principal Agent Problem with Social Influence

I develop a theoretical model of price discrimination under social influence. I find that social influence gives sellers the incentive to artificially create and maintain excess demand on the market. The rationing occurs mainly at the low end of the market and sometimes results in full rationing of the low end. Furthermore, the incidence of price discrimination under social influence is much lower than in the absence of it. Social influence lowers the profitability of price discrimination and incentivizes sellers to reduce product variety and to only target the high end of the market, a fact that is consistent with many empirical observations. Copyright © 2015 John Wiley & Sons, Ltd.     

价格因素对我国地区能源强度的影响

本文从能源价格和劳动力价格两个方面进一步分析价格要素对于能源强度的作用机理,分析了我国能源价格体系存在的问题,并针对存在的问题提出了相关政策建议,为更有效地控制能源强度提供一定的帮助,弥补了现有能源强度影响因素理论研究的不足。     

The Interaction between a Most-Favored-Customer Clause and Price Dispersion: An Empirical Examination of the Medicaid Rebate Rules of 1990

This paper examines the effect of the MFC rules adopted by Medicaid on both price dispersion and price levels in the wholesale pharmaceutical market. Theory suggests that the regulations should reduce price dispersion and increase the average price for those products with a high initial level of price dispersion. Using data which can only measure some dimensions of price discrimination, I find that discrimination falls for products sold to hospitals, but not drugstores. Branded drugs facing generic competition have the most dispersion ex ante . Prices of these brands rise with dispersion at the implementation of the new rules. The last two results are consistent with Scott Morton (1997), where I look only at price changes due to the law. The results of this paper confirm that part of the mechanism of action for the price increase is the high level of price dispersion for some products combined with the MFC.     

基于土地杠杆的住房价格动态分解

住房可分为土地和依附于土地的建筑物两部分。基于土地杠杆基本概念,利用我国35个大中型城市数据,将住房价格动态分解为土地价格和建筑物价格,考察我国住房价格增长中土地增值的贡献比例与速度。对土地杠杆假说的实证检验发现,拥有更高土地杠杆的住房,其增值速度会更快。通过对土地杠杆假说的实证研究,对于了解潜在的房价决定机制、价格指数建立、土地利用限制的成本评估,以及制定住房政策和评估住房市场的合理性等,都具有重要的作用。     

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.     

Deriving equity risk premium using dividend futures

In this paper I present a simple stock price decomposition model using the dividend discount model and dividend futures. The main contribution of this paper is the use of dividend futures which represent the risk-adjusted expectations of future dividends. This allows for the calculation of the implied equity risk premium and the decomposition of stock price movements into individual components. Due to the use of daily market data, this method can take into account the structural changes associated with falling interest rates and the Covid-19 pandemic. I empirically show the risk premium development of the S&P 500 Index and Euro Stoxx 50 Index in the last decade.     

Prices and Regional Variation in Welfare

One would expect regional differences in prices to influence conclusions concerning levels and distributions of well-being. Although there is anecdotal evidence of significant price dispersion across regions, there is no governmental source of data that measures differences in price levels. In this paper I integrate estimates of regional prices with expenditure data from the Consumer Expenditure Surveys to assess the influence of price differences on living standards in the United States. While prices have little effect on inequality, estimates of poverty and the standard of living change substantially with the inclusion of regional price variation.     

乡镇驻地土地利用规模与价格敏感度分析--以湖北省大冶市还地桥镇为例

研究目的：针对目前我国乡镇驻地住宅用地面积庞大、工业占地面积大、商业面积狭小的现状，分析乡镇驻地人均占地面积大、土地利用粗放的原因，提出乡镇土地集约节约利用土地的对策。研究方法：敏感度模型与实证分析。研究结论：乡镇驻地商业与住宅用地价格对土地利用规模的敏感度一般，但是乡镇驻地工业用地价格敏感度极低，反映在乡镇驻地工业用地价格过低，导致工业占地面积大，乡镇土地利用混乱。乡镇驻地可以通过价格调节商业、住宅用地规模，但工业用地的规模更多的需要行政或者法律等其他手段进行调节，从而达到挖掘乡镇驻地土地利用潜力，节约集约利用土地的目的。     

Behavior‐ and characteristic‐based price discrimination

We develop a model of behavior‐ and characteristic‐based discriminatory pricing where consumers are heterogeneous both in tastes and in price sensitivity. Each firm is able to distinguish between the consumers that have bought from it and those that have bought from the rival. Furthermore, each firm learns the price sensitivity of their own consumers. We show that using this additional information may yield higher profits than uniform pricing provided that consumers are heterogeneous enough with respect to price sensitivity. We also discuss consumer surplus implications of such behavior‐ and characteristic‐based price discrimination, and we show that the impact of price discrimination depends on both the consumer type and the level of consumers’ heterogeneity.     

Housing prices and macroprudential policies: Evidence from microdata

This paper examines the efficacy of macroprudential policies in addressing housing prices in a developing country like India, utilizing two novel databases on city-level house prices in India. Though the empirical models provide evidence of a sizable effect of the fundamental factors in influencing house price dynamics, they also reveal strong countercyclical properties of macroprudential tools i.e., loan-to-value (LTV) limit, risk weights, and provisioning requirements, in influencing housing price movements. Among the macroprudential policy tools, the LTV limit emerges as the most potent one in influencing the price dynamics. A granular investigation of the effectiveness of macroprudential tools suggests that the countercyclical effect of the regulatory ratios for large-sized mortgages is much stronger as compared with those for the small-sized mortgages, attributed mainly to investment motives associated with the large-sized loans. We also find the presence of asymmetry in the impact of loosening versus the tightening of the LTV limit, which can be attributed to the procyclical behavior of the house prices.     

金属期货与现货市场价格互动关联规则挖掘研究

期货市场传递的价格信息反映未来供求状况的预期,因此,研究金属期货和现货市场价格互动,对于国民经济发展、企业规避价格风险、投资者进行投资决策及政府进行市场监管都有重要意义。本文将数据挖掘中的关联规则挖掘方法引入金融时间序列分析研究领域,针对挖掘对象期货市场的特点,提出基于时间约束的时间序列关联规则挖掘算法。与传统的忽视数据时间信息的关联规则挖掘算法相比,该算法对期货价格与现货价格间的互动关联规则进行挖掘,能发现反映时间序列局部动态互动关联关系,具有一定的短期预测效果。     

Wholesale price discrimination: Innovation incentives and upstream competition

In intermediate good markets where there are alternative supply sources, wholesale price discrimination may enhance innovation incentives downstream. We consider a vertical chain where a dominant firm and a competitive fringe supply imperfect substitutes to duopoly retailers which carry both varieties. We show that a ban on price discrimination by the dominant supplier makes uniform pricing credible and reduces retailers’ incentives to decrease the cost of acquiring the competitively supplied variety, leading to higher upstream profits and lower downstream welfare. Our analysis complements existing results by identifying a novel channel through which wholesale price discrimination can improve dynamic market efficiency.