Unbiased estimation of expected return using CAPM

Estimation of expected return is required for many financial decisions. For example, an estimate for cost of capital is required for capital budgeting and cost of equity estimates are needed for performance evaluation based on measures such as EVA. Estimates for expected return are often based on the Capital Asset Pricing Model (CAPM), which states that expected excess return (expected return minus the risk-free rate) is equal to the asset's sensitivity to the world market portfolio (β) times the risk premium on the “world market portfolio” (the market risk premium). Since the world market portfolio, by definition, contains all assets in the world, it is not observable. As a result, an estimate for expected return is commonly obtained by taking an estimate for β based on some index (as a proxy for the world market portfolio) and an estimate for the market risk premium based on a potentially different index and multiplying them together. In this paper, it is shown that this results in a biased estimate for expected return. This is undesirable since biased estimates lead to misallocation of funds and biased performance measures. It is also shown in this paper that the straightforward procedure suggested by Fama and MacBeth [J. Financ. Econ. 1 (1974) 43] results in an unbiased estimate for expected return. Further from the analysis done, it follows that, for an unbiased estimate, it does not matter what proxy is used, as long as it is used correctly an unbiased estimate for expected return results.     

供应链管理绩效评价及激励机制

本文通过分析供应链管理的特点、目标和内容，提出供应链管理绩效评价指标体系，其中矩阵指标具有一定的创新，且较好地反映了供应链企业之间的复杂关系。介绍了确定供应链管理的绩效指标值的两种方法，并分析了供应链管理六种激励模式。     

Robustness issues in multilevel regression analysis

A multilevel problem concerns a population with a hierarchical structure. A sample from such a population can be described as a multistage sample. First, a sample of higher level units is drawn (e.g. schools or organizations), and next a sample of the sub‐units from the available units (e.g. pupils in schools or employees in organizations). In such samples, the individual observations are in general not completely independent. Multilevel analysis software accounts for this dependence and in recent years these programs have been widely accepted. Two problems that occur in the practice of multilevel modeling will be discussed. The first problem is the choice of the sample sizes at the different levels. What are sufficient sample sizes for accurate estimation? The second problem is the normality assumption of the level‐2 error distribution. When one wants to conduct tests of significance, the errors need to be normally distributed. What happens when this is not the case? In this paper, simulation studies are used to answer both questions. With respect to the first question, the results show that a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second‐level standard errors. The answer to the second question is that only the standard errors for the random effects at the second level are highly inaccurate if the distributional assumptions concerning the level‐2 errors are not fulfilled. Robust standard errors turn out to be more reliable than the asymptotic standard errors based on maximum likelihood.     

开放经济下中国新凯恩斯混合菲利普斯曲线

本文采用广义矩方法估计开放经济下中国新凯恩斯混合菲利普斯曲线，结合中国现实选择工具变量。结果表明，使用混合成本作为通货膨胀的驱动因素在统计和经济意义上具有显著性，影响我国通货膨胀主要是资本成本与进口中间品成本；厂商定价行为既有前瞻性又有后顾性，但前瞻性处于主导地位，且价格具有较强的灵活性。     

搞好《建筑工程概预算》课程教学的思考

根据《建筑工程概预算》课程的特点,结合教学实践经验,对如何搞好该课程的教学做了一些思考：强调课程重要性,使学生明确课程学习的意义;精心挑选教材,备足教学参考资料;注重培养学生分析、解决问题的能力和自学能力;开展课程设计教学,提高教学质量;充分发挥教师的主导作用,培养“双师型”的教师;教学中理论联系实际,支持、鼓励学生参加执业资格证考试。     

市场调查中的不完全事后分层估计量

在使用多个分类变量对样本进行交叉事后分层时，经常面临边缘总值已知、格子总值未知的不完全事后分层问题。针对这一情况，给出两种估计量即搜索比率估计量和广义搜索比率估计量。     

中国政府统计抽样调查制度的总体框架研究

随着中国市场经济体制的逐步确立,政府的职能在逐渐转变,政府对统计数据的要求也在变化,这就要求政府统计调查制度也随之改革。适应市场经济体制和中国政府管理的特点以及城乡统筹发展的要求,政府统计调查应该以抽样调查为主体,抽样调查队伍和机构应主要设立在地市一级,调查的指标体系和内容应该改革与调整,企业抽样调查应该采用名单框和区域框结合的双框抽样方式。对于抽样调查得到的数据资料,不仅应当汇总得出各种可用于宏观经济管理与分析的总量指标数据和分类数据,而且还应当建立起全部被调查企业和被调查家庭的数据库,供政府部门和国内的科学研究机构进行微观社会经济活动主体层次的研究。     

Convenient estimators for the panel probit model: Further results

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum simulated likelihood estimation. But, for applications of the size considered in their study, full likelihood estimation is actually straightforward, and resort to GMM estimation for convenience is unnecessary. In this note, we reconsider maximum likelihood based estimation of their panel probit model then examine some extensions which can exploit the heterogeneity contained in their panel data set. Empirical results are obtained using the data set employed in the earlier study. Helpful comments and suggestions by Irene Bertschek and Michael Lechner are gratefully acknowledged. This paper has also benefited from comments by two anonymous referees and from seminar participants at the Center for Health Economics at the University of York. Any remaining errors are the responsibility of the author.     

城市土地储备量研究——以杭州市为例

1996年以来，土地储备机制在我国各地先后施行，它不仅涉及及土地收购，储备，出让的立法工作，而且还涉及资金流转过程，所以确定合理的土地储备量已迫在眉睫。本文在分析影响土地储备量大小的三大方面诸多因素作用关系基础上，拟定城市土地储备量大小的思路，即在相关因素评判检验的基础上，建立开发项目土地供应量与建成区面积，房地产开发量二元线回归方程，运用SPSS软件推算出土地储备量的大小。     

Estimation methods for stochastic volatility models: a survey

Abstract.  Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index.