引致需求、路网密度与中国道路运输业营运绩效评价——基于DEA模型与面板Tobit的两阶段分析

本文基于产出导向的BCC-DEA模型对中国道路运输业在2000-2009年期间的营运效率进行了测算,并采用受限随机效应面板Tobit模型检验了各种外部环境因素对于道路运输业营运效率的影响;此外,还结合基于非参数DEA的Malmquist生产率指数,对中国道路运输业全要素生产率进行了动态评价。实证结果显示,纯技术效率较低是中国道路运输业营运效率较低的主要原因,而且突发性外部环境冲击是道路运输业营运效率出现较大幅度波动的重要因素;样本期间内道路运输业全要素生产率呈现出较为平稳的增长态势,这主要得益于道路运输业较为明显的技术进步;单位面积生产总值等引致需求因素以及公铁基础设施等路网密度因素,均是影响道路运输业营运效率的重要因素。     

Efficient estimation of forecast uncertainty based on recent forecast errors

Multi-step-ahead forecasts of the forecast uncertainty of an individual forecaster are often based on the horizon-specific sample means of his recent squared forecast errors, where the number of past forecast errors available decreases one-to-one with the forecast horizon. In this paper, the efficiency gains from the joint estimation of forecast uncertainty for all horizons in such samples are investigated. If the forecast uncertainty is estimated by seemingly unrelated regressions, it turns out that the covariance matrix of the squared forecast errors does not have to be estimated, but simply needs to have a certain structure, which is a very useful property in small samples. Considering optimal and non-optimal forecasts, it is found that the efficiency gains can be substantial for longer horizons in small samples. The superior performance of the seemingly-unrelated-regressions approach is confirmed in several empirical applications.     

A New Data Set on Monetary Policy: The Economic Forecasts of Individual Members of the FOMC

This paper describes a new data set of the forecasts of output growth, inflation, and unemployment prepared by individual members of the Federal Open Market Committee. The paper discusses the scope of the data set, possibilities for extending it, and some potential uses. It offers a preliminary examination of some of the cross‐sectional features of the data.     

Oil price forecasting under asymmetric loss

Based on the approach developed by Elliott et al. (2005), we found that the loss function of a sample of oil price forecasters is asymmetric in the forecast error. Our findings indicate that the loss oil price forecasters incurred when their forecasts exceeded the price of oil tended to be larger than the loss they incurred when their forecast fell short of the price of oil. Accounting for the asymmetry of the loss function does not necessarily make forecasts look rational.     

When Do Analysts Adjust for Biases in Management Guidance? Effects of Guidance Track Record and Analysts’ Incentives

Prior research indicates that analysts do not fully adjust for the general downward bias in earnings guidance issued by management. We report the results of two experiments designed to investigate how guidance track record and analysts’ incentives jointly explain the extent to which analysts adjust for guidance bias. Our results suggest that analysts with accuracy incentives adjust for management’s track record of downwardly biased guidance when the bias is relatively small (one cent), but those with relationship incentives do not. Furthermore, the difference in adjustment is larger when the bias track record is inconsistent than when it is consistent. Also, when guidance bias is larger (two cents) relative to smaller (one cent), analysts with relationship incentives partially adjust, as they appear to strike a balance between accuracy and their desire to please management. These findings hold implications for investors, regulators, and the interpretation of prior research.     

The Walk‐down to Beatable Analyst Forecasts: The Role of Equity Issuance and Insider Trading Incentives*

It has been alleged that firms and analysts engage in an "earnings‐guidance game" where analysts first issue optimistic earnings forecasts and then "walk down" their estimates to a level that firms can beat at the official earnings announcement. We examine whether the walk‐down to beatable targets is associated with managerial incentives to sell stock after earnings announcements on the firm's behalf (through new equity issuance) or from their personal accounts (through option exercises and stock sales). Consistent with these hypotheses, we find that the walk‐down to beatable targets is most pronounced when firms or insiders are net sellers of stock after an earnings announcement. These findings provide new insights on the impact of capital‐market incentives on communications between managers and analysts.     

Reconfiguration of the conceptual landscape: a tribute to the service logic of Richard Normann

This article is a tribute to the late Richard Normann, whose call for a “service logic” (Normann, Reframing Business: When the Map Changes the Landscape, Wiley, Chichester, p. 99, 2001) both parallels and enriches service-dominant (S-D) logic (Vargo and Lusch, J. Mark, 68:1–17, 2004a). Like Vargo and Lusch, Normann shifted the focus of the offering from an output to a process of value creation and perceived the firm as an organizer of this process, with the customer as a co-producer, rather than a receiver of value. He also argued that offerings are “frozen knowledge,” similar to Vargo and Lusch’s contention that the basis of exchange is applied operant resources (service) and suggested that the ‘dematerialization’ of resources increases their ‘liquidity’, which allows increased “density” for value creation. Thus, he suggested that firms need to “reframe business”—rethink the logic of value creation—to reveal opportunities in reconfiguring the value constellations of which they are part. This tribute explores these and other similarities and differences between Normann’s work and the evolving S-D logic.     

中国地区经济趋异的非参数分析

本文采用AK模型和几何布朗运动建立了趋异分析的框架,并运用非参数分析方法,分别用一元和多元的核密度估计,对我国1978年以来的经济增长中的省际趋同模式进行了分析。结果表明,在我国的省级经济增长中,无法获得可信的,存在趋同趋势的数据支撑,我国各省的经济增长路径迄今还没有收敛的迹象,不同省份之间的增长率的差异也随着经济增长而扩大,甚至地区内的产出差距也在增加。论文还表明,我国各省区市之间也不存在俱乐部趋同的趋势。     

外贸结构的非均衡机理探索

经济结构呈现非均衡的常态特征。在市场不完全、信息不充分、外生条件不统一等因素的制约下,一国外贸结构形成的资源配置效率通常低于均衡世界里的帕累托最优效率,是一种“次优”均衡;这种非均衡模式可能在受到外在冲击时或通过内生演进的方式发生改变,并通过进出口商品结构、贸易方式结构等表现出来。外贸结构非均衡的核心特征是进出口商品的要素密集度高低,并与比较优势和后发优势联系在一起,成为外贸结构非均衡演进规律的主要内容。     

The accuracy of long-term earnings forecasts in the electric utility industry

This paper examines the accuracy of various methods of forecasting long-term earnings growth for firms in the electric utility industry. In addition to a number of extrapolative techniques, Value Line analyst forecasts are also evaluated. Value Line analyst forecasts for a five-year time horizon are found to be superior to many of the extrapolative models. Among the extrapolative models examined, implied growth and historical book value per share growth rate models performed best. These results provide strong support for using Value Line growth forecasts in cost of capital estimates for electric utilities in the context of utility rate cases. Value Line forecast errors could be explained by changes in dividend payout ratios, the firm's regulatory environment and bond rating changes.