减排与增长:服务业如何实现绿色均衡发展?

服务业是中国经济转型和产业结构升级的重要抓手,在资源与环境"双重"约束日益趋紧的背景下,有必要研究服务业绿色发展问题。能否在减排成本最小的前提下提高服务业增长率,走出一条绿色发展路径?为此,文章创新性地将排放权交易市场引入服务业部门,采用方向性距离函数、非线性规划等实证研究方法测算2004-2012年中国服务业14个细分行业的绿色效率和碳排放影子价格。研究表明:中国服务业发展方式并非"绿色",服务业减排成本和碳排放量逐年增长,减排面临巨大的经济压力;在文章设计的排放权交易模型下,服务业细分行业能够形成一个统一的影子价格,从而实现一条绿色发展路径,该路径满足帕累托有效和投入产出技术有效;在均衡路径上,流通服务业应出售排放权,而其他减排成本较高的服务业购买排放权。     

Effect of the ban on short selling on market prices and volatility

We examine the effects of the short‐selling ban, imposed by Australian regulators in the wake of the global financial crisis, on the trading of financial stocks. Our findings argue against commonly stated reasons for imposing short‐sale bans. We find no evidence that short‐sale restrictions provide support for stock prices or that they reduce volatility. Moreover, stocks subject to the short‐selling ban suffered a severe degradation in market quality. Controlling for the adverse effects of the financial crisis on markets, we show that short‐selling restrictions increase intraday volatility, reduce trading activity and increase bid–ask spreads.     

How should we estimate value-relevance models? Insights from European data

We study the consequences of unobserved heterogeneity when employing different econometric methods in the estimation of two major value-relevance models: the Price Regression Model (PRM) and the Return Regression Model (RRM). Leveraging a large panel data set of European listed companies, we first demonstrate that robust Hausman tests and Breusch-Pagan Lagrange Multiplier tests are of fundamental importance to choose correctly among a fixed-effects model, a random-effects model, or a pooled OLS model. Second, we provide evidence that replacing firm fixed-effects with country and industry fixed-effects can lead to large differences in the magnitude of the key coefficients, with serious consequences for the interpretation of the effect of changes in earnings and book values per share on firm value. Finally, we offer recommendations to applied researchers aiming to improve the robustness of their econometric strategy.     

Optimal execution with uncertain order fills in Almgren–Chriss framework

The classical price impact model of Almgren and Chriss is extended to incorporate the uncertainty of order fills. The extended model can be recast as alternatives to uncertain impact models and stochastic liquidity models. Optimal strategies are determined by maximizing the expected final profit and loss (P&L) and various P&L-risk tradeoffs including utility maximization. Closed form expressions for optimal strategies are obtained in linear cases. The results suggest a type of adaptive volume weighted average price, adaptive percentage of volume and adaptive Almgren–Chriss strategies. VWAP and classical Almgren–Chriss strategies are recovered as limiting cases with a different characteristic time scale of liquidation for the latter.     

“双碳”目标下碳交易与制造业绿色全要素生产率——基于异质性技术创新模式的机制检验

碳交易是推动制造业绿色发展,实现“双碳”目标的重要市场化工具,交易价格和市场规模能够反映碳交易实施状况,是影响制造业绿色全要素生产率的重要因素。从碳交易价格和市场规模切入,基于2008—2020年中国内地30个省份面板数据,构建连续型双重差分模型评估碳交易对制造业绿色全要素生产率的作用效果,并考察异质性技术创新模式的传导路径。结果表明,提高碳交易价格和扩大市场规模均能显著提升制造业绿色全要素生产率。机制检验表明,碳交易价格和市场规模能够推动自主创新、减少技术改造投入,进而影响制造业绿色全要素生产率,而技术引进并非有效路径。进一步研究发现,自主创新对技术改造存在挤出效应。研究结论对完善碳交易制度顶层设计、精准制定技术创新配套政策具有重要启示意义。     

银行价格竞争、融资约束与企业研发投资——基于“中介效应”模型的实证研究

近年来我国利率市场化改革积极推进,实体经济发展积极向创新驱动转型,一个亟须研究厘清的关键问题是,银行业竞争如何驱动企业创新活动？本文关注银行价格竞争对企业创新的影响,以2013—2018年沪深两市的上市企业为样本,采用“中介效应”因果分析模型,实证检验了银行价格竞争对企业研发投资的影响,并识别出以融资约束为中介渠道的作用机制。研究发现,银行价格竞争不仅会提高银行的风险容忍度,直接增加R&D投资的信贷供给意愿,而且还会通过降低贷款价格和增加贷款可得性来缓解企业整体的融资约束,间接促进企业创新活动。这一机制在解除贷款利率管制之后以及在民营企业层面体现得更加明显。本文的研究结果对于深化金融市场化改革、改善金融服务实体经济效果以及实施经济创新驱动发展战略,具有明确的政策启示。     

房地产投资和金融支持实体经济的交互影响研究--基于环沪都市圈的分析

基于房地产市场与金融发展的紧密关系,本文将房地产投资、金融发展与实体经济发展纳入同一框架进行综合研究。首先梳理房地产、金融效率的环沪都市圈1发展现状,深入探讨房地产、金融与宏观经济增长的作用机制。然后以2003~2016年环沪都市圈为样本,采用交互效应模型分析房地产投资通过金融体系间接影响经济发展的综合效应。分析得到的主要结论包括:环沪都市圈房地产投资对实体经济发展整体呈现一定的负向作用,主要是抑制了金融支持实体经济的效率,两者负相关系数为0.75;经实证研究进一步发现,在经济发展水平较弱、金融化程度越高的城市群,房地产投资对金融支持实体经济效率的抑制作用更加显著,是全部样本的2.4倍,这也恰好解释了浙北经济长期落后于苏南的原因。     

我国房地产泡沫与银行信贷规模的相关性研究

本文首先从理论上深刻剖析了房地产泡沫与银行信贷规模相互之间的作用与传导机制,在此基础上选取2006年-2018年相关指标的年度数据,对房地产泡沫与银行信贷规模进行了图形拟合与周期性波动规律分析,分析发现二者存在极高的契合度。建立房地产泡沫的函数,构建协整方程实证发现银行信贷规模对房地产泡沫的长期弹性系数为0.51,从长期来看银行信贷规模每增加1%,房地产泡沫也相应增加0.51%,进一步建立VAR模型实证发现房地产泡沫与银行信贷规模互为格兰杰因果关系,二者相互影响、相互促进。通过方差分解实证发现银行信贷规模对房地产泡沫的变动具有重要的影响,另一方面,房地产泡沫是影响银行信贷规模变动最主要的因素。     

Online Price Search: Impact of Price Comparison Sites on Offline Price Evaluations

Consumers increasingly rely on Internet price comparison sites (PCS) to gain knowledge about the market. The prices generated by a PCS search can act as contextual reference prices and influence the attractiveness of prices encountered later as consumers shop offline at local stores. This paper demonstrates that both PCS retailer ratings and the shape of the PCS price distribution influence the impact of PCS search results on later price evaluations. A favorable PCS retailer rating increases the perceived validity of the price associated with that retailer, enhancing the impact of that PCS price on offline price evaluations (Study 1). The shape of the PCS price distribution can also influence later price evaluations, however this effect depends on the information provided by the PCS retailer ratings. When PCS retailer ratings are similar, implying similar validity for the associated prices, low PCS prices and those appearing more frequently in the PCS price distribution have more impact (Studies 2 and 3). When PCS retailer ratings are variable (some high and some low), the PCS price distribution effect occurs only when the PCS retailer ratings provide congruent information about price validity — that is, the most frequent price is offered by retailers with more favorable ratings. Study 3 shows that price validity inferences do mediate this result. Finally, we depart from the offline shopping context to show that when consumers choose a retailer directly from the PCS search results, the effect of PCS retailer ratings is stronger for high-priced retailers and for consumers who rely less on the retailer price as a heuristic to infer retailer service level. Based on our findings we offer insights for online and offline retailers when considering strategic responses, such as price matching guarantees.     

On the fairness of airlines’ ticket pricing as a result of revenue management techniques

Pricing and availability of tickets have always been a source of confusion for customers in transportation industries. What is the best time to buy tickets? Why passengers taking the same flight might pay significantly different prices for the same seat? Why round trip tickets between two cities sometimes become cheaper than the one-way flights between them? Is it fair to buy a ticket for an itinerary cheaper than a ticket for just a part of it? These observations make customers wonder why they pay higher prices for shorter flights. In this paper, we study the airlines’ revenue management systems and explain some of these pricing schemes in travel industries. We develop a simulator to study the decision making process of network revenue management and use a numerical study to explore these questions and address some explanations for them. We relate these observations to the revenue management measurements such as the bid price or the adjustment cost and show how the dynamic of the network get influenced by these measures that eventually results in unusual pricing. We explain how a zero or small bid price of a specific leg may cause the price of an itinerary be cheaper than one segment of it and that the small bid price is caused by low demand in comparison to the available capacity. We exhibit network revenue management system and show the above issues for a small network.