电子商务平台上的信息不对称、交易成本与企业机制的运用

基于交易成本理论,将电子商务平台上交易的商品分为两类——物理属性标准的商品和物理属性不标准的商品,将商品信息分为两类——物理描述信息和价格信息,研究了两类商品在两类信息上存在的信息不对称问题,并对比分析了在线交易中的市场机制和企业机制。指出:在市场机制下,信誉机制和搜索排名机制能有效缓解物理属性不标准的商品在物理描述信息上的信息不对称,但无法有效缓解物理属性标准的商品在价格信息上的信息不对称,解决物理属性标准的商品的价格信息不对称需要企业机制;在电子商务平台上部分地用企业机制代替市场机制可以减少交易成本。     

从信息不对称现象谈消费者权益保护

信息不对称现象在消费市场交易过程中普遍存在，由于销售者利用自身的信息优势扭曲交易信息获利，速成消费者利益的损害。本文从消费市场中信息不对称存在的原因，信息不对称对消费者权益的不利影响等角度分析入手，累计如何在信息不对称的情况下有效的保护消费者的权益。     

浅谈市场经济中的生产者与消费者双向信息不对称

市场经济中,生产者与消费者之间存在着双向信息不对称现象。造成这种现象的原因有信息成本及其边际效用递减,生产者与消费者的经济理性能力约束和经济不理性的限制。本文提出了解决信息不对称影响的措施。一 双向信息不对称的概念     

消费者搜寻、企业竞争与政府规制——文献综述

大量的文献研究表明,消费者在市场交易前搜寻商品信息的经济行为模式和成本深刻影响着产业组织的结构、行为与绩效。通过对文献的进一步考察发现,目前的研究可以从三个方面的进一步深入,一是放松消费者与企业完全知道均衡价格分布的假设;二是放开消费者第一次搜寻无成本的假设;三是将消费者搜寻扩展为价格搜寻与属性搜寻,研究异质商品市场上的消费者搜寻、企业竞争以及社会福利的变化。     

消费领域信息不对称的法律矫正

由于消费信息不对称对消费者权益产生了不利影响,所以必须在法律上赋予消费者知情权,以矫正经营者与消费者之间的信息不对称关系.现行法律制度对消费者知情权保护已做了相关规定,但还需要在责任制度、政府规制、社会保护等方面进一步加以完善,以最终实现消费者合法权益的有效保护.     

信息不对称条件下房地产价格上涨:基于不完全信息动态博弈模型的理论分析

房地产市场是一个典型的信息不对称市场。房地产商对商品房的定价选择与消费者的决策构成信息不完全的动态博弈。房地产商可以利用自己相对于消费者的信息优势,对商品房需求、成本等因素进行“包装”,改变消费者的判断,诱导消费者做出接受涨价的决策,从而实现超额利润。抑制房地产价格“非正常上涨”的关键在于降低信息不对称。     

宝马在中国的促销策略浅析

促销,指企业为开拓和维护市场,通过各种形式向消费者传达企业本身品牌及其商品信息,引起消费者的购买行为,从而实现企业销售目标的活动。文章以宝马在我国的促销策略为例,对这一问题进行了探讨。     

消费者信息处理方式研究综述:基于商品评价的视角

个体的购买决策被认为是一种信息处理过程,信息处理方式能有效揭示消费者将输入信息转化为输出结果的购买决策机制。本文从购买决策中消费者商品信息评价的视角,对消费者信息处理的具体方式、分类及其研究方法进行分析总结,以期为后续研究打下基础。     

电子商务中信息不对称的经济分析

电子商务中网络技术的应用方便了经营者和消费者之间的信息沟通 ,然而电子商务中经营者和消费者之间的信息不对称并没有得到改善。经营者向消费者传递虚假的信息是导致电子商务中信息不对称的一个重要原因。本文通过完全信息静态博弈模型对电子商务中经营者信息传递的真实性选择进行了分析 ,并对如何减少电子商务中经营者虚假信息的发布提出了对策。     

价格离散、信息搜寻与团购行为

团购行为是当今消费行为学中的一个重要现象,源自市场和产品信息不对称的双重因素是导致消费者行为变化的根本原因。基于产品信息的价格函数模型,分析团购有利于消费者实现信息共享,减少搜寻成本,降低与企业间的信息不对称,减少消费行为的不确定性,从而获得更大的消费效用的结论。     

Which types of commodity price information are more useful for predicting US stock market volatility?

This study aims to investigate which types of commodity price information are more useful for predicting US stock market realized volatility (RV) in a data-rich word. The standard predictive regression framework and monthly RV data are used to explore the RV predictability of commodity futures for the next-month RV on S&P 500 spot index. We utilize principal component analysis (PCA) and factor analysis (FA) to extract the common factors for each type and all types of commodity futures. Our results indicate that the futures volatility information of grains and softs has a significant predictive ability in forecasting the RV of the S&P 500. In addition, the FA method can yield better forecasts than the PCA and average methods in most cases. Further analysis shows that the volatility information of grains and softs exhibits higher informativeness during recessions and pre-crises. Finally, the forecasts of the five combination methods and different out-of-sample periods confirm our results are robust.     

Children as consumers: investigating child diary expenditure data

Abstract.  We investigate expenditure behaviour of school-aged children using child diary information contained in the British Family Expenditure Survey. The estimates from an Almost Ideal Demand System (AIDS) for child expenditure suggest that drinks, sweets, books, and toys are 'normal' goods for children, but clothes, travel, leisure and vice products are 'luxury' items with income elasticities greater than one. Being a lone-parent child and having a working mother are important factors in determining child expenditure decisions. Importantly, a higher parental budget share on any given commodity is typically associated with an increased child budget share on the same commodity.     

异质信念、投机均衡与农产品期货定价*

农产品期货市场套利并不充分,交易者也不是完全理性的。本文假设农产品期货市场有限套利、交易者异质信念并遵循“经验法则”预期,构建了农产品期货投机均衡定价模型,并认为集中竞价规则下产生的农产品期货价格是由交易者的预期决定的;前期期货价格水平、现货价格和前期期货价格的变动趋势、不同类型交易者的比例结构及其预期模式共同影响农产品期货价格的形成与波动;基本分析法交易者占主导地位的农产品期货市场具有更高的套期保值与价格发现效率。针对中国七种主要农产品期货的实证结果显示,农产品期货投机均衡定价模型对解释中国农产品期货价格的形成与波动是有效的。这意味着在期货行情系统中实时披露现货价格信息,培育和引导交易者运用基本分析法预测期货价格走势,有助于提升农产品期货市场的效率。     

无形资产信息不对称问题研究

无形资产的无形特征,使得无形资产市场中的信息不对称问题更加严重,制约了无形资产市场的发展。本文对无形资产信息不对称问题的研究文献进行了综述,对无形资产信息不对称的现象、后果及根源进行了分析,并总结了改进无形资产计量和信息披露的相关研究成果,最后提出改善无形资产信息不对称问题进一步研究的方向。     

Global commodity cycles and linkages: a FAVAR approach

In this article, we examine linkages across non-energy commodity price developments by means of a factor-augmented VAR model (FAVAR). From a set of non-energy commodity price series, we extract two factors, which we identify as common trends in metals and food prices. These factors are included in a FAVAR model together with selected macroeconomic variables, which have been associated with developments in commodity prices. Impulse response functions confirm that exchange rates and economic activity affect individual non-energy commodity prices, but we fail to find strong spillovers from oil to non-oil commodity prices or an impact of the interest rate. In addition, we find that individual commodity prices are affected by common trends captured by the food and metals factors.     

The workings of a commodity money system in an incomplete information macro model

This paper compares the properties of a token money system with that of a commodity money system in an uncertain environment. In an incomplete information world, relative prices are not known with certainty. However, a commodity money system provides some information because the nominal price of the monetary commodity is known. The benefits of this information-enhancing function may be offset, though by distortions in relative prices relative to their full information Walrasian equilibrium values. Because the two systems have vastly different structural parameters, we cannot unambiguously state which system is welfare superior.     

Common dynamic factors in driving commodity prices: Implications of a generalized dynamic factor model

Identification of the price drivers of commodity prices is difficult because economic indicators reflect commodity prices with lead or lag, and some commodities have spillover effects to other commodities. A generalized dynamic factor model is capable of accounting for these characteristics and can be applied to panel data of monthly returns of a vast variety of commodities. The empirical results indicate that four common dynamic factors exist that account for much of the variation in the commodity returns. The identification of the common dynamic factors is conducted by interchangeably creeping an economic indicator into the commodity return panel data and examining the ratio of variance explained by the common factors. The four common factors correspond to the U.S. inflation rate, the world industrial production, the world stock index, and the price of crude oil.     

商品期货有助于预测通货膨胀率吗

本文通过对我国22种商品期货提取隐含的便利收益率时间序列,发现商品期货在样本内和样本外可以显著预测未来通货膨胀率,在控制了利率、货币增速影响后,这一结果仍然成立。进一步,采用南华商品期货综合指数、商品期货各品种指数、商品期货大类指数,以及美国商品研究局商品期货指数对通货膨胀率进行了样本外预测,结果表明这些指数对于预测我国通货膨胀率效果仍然显著。基于商品期货价格的预测模型都优于本文的基准模型和朗润预测指数,这表明商品期货市场包含了与通货膨胀率相关的重要信息,可以作为未来一般物价走势的重要参考。     

Cross market predictions for commodity prices

This paper shows that commodity prices can be predicted from cross-market information by establishing long-run cross-market commodity price equilibrium models, which are characterized by a linear relation between prices across different markets. Using data from five representative commodity markets (oil, copper, gold, corn, and cattle) during the period 2005–2018, we demonstrate that oil and industrial metal markets have formed a long-run price equilibrium with other markets across different commodity families. However, agriculture and gold markets do not tend to have long-run price equilibrium relations with other commodity markets. Furthermore, we show that the absence of a price equilibrium is due to the cross-market liquidity interference effect. After we control for the liquidity effect, long-run cross-market commodity price equilibrium relations are reestablished for agriculture and gold markets. These results can aid in demonstrating that liquidity can capture most of the missing information that is not reflected in price dynamics in less liquid markets, such as agriculture and gold markets. Therefore, less liquid commodity price predictions require both prices and liquidity levels from cross-markets, while liquid commodity prices (oil and metal) can be predicted based solely on cross-market prices.     

Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil

This study explores the relationship between Google search activity and the conditional volatility of oil and gold spot market returns. By aggregating the volume of queries related to the two commodity markets in the spirit of Da et al. ( 2015 ), we construct a weekly Searching Volume Index (SVI) for each market as proxy of households and investors information demand. We employ a rolling EGARCH framework to reveal how the significance of information demand has evolved through time. We find that higher information demand increases conditional volatility in gold and oil spot market returns. Information flows from Google SVI's reduce the proportion of the significant volatility asymmetry produced by negative shocks in both commodity markets. The latter is more profound in the gold market.