Multivariate regression tests of the arbitrage pricing theory: The instrumental-variables approach

This article expands the theoretical basis upon which empirical testing of the arbitrage pricing theory (APT) rests. Specifically, it specifies linear restrictions for worlds in which the APT holds. These restrictions may, in principle, be tested. Since the regressors in the model are only “noisy” proxies for a specific linear transformation of the factors or mimicking portfolios, testing regressions suffer from an errors-in-variables problem. The standard econometric treatment for this problem is the instrumental-variables approach. A size-based example is employed to compare the test results derived from the instrumental-variables approach to those obtained via the ordinary least squares (OLS) method. The results from both methods cannot reject a two-factor APT for the size-sorted portfolio sample. The authors appreciate the helpful comments of Edwin Burmeister, Raymond Chiang, Steve Pruitt, participant at the 1989 Western Finance Association annual meetings, Indiana University, and University of Miami, and especially Shmuel Kandel.     

Estimating Beta

This paper presents evidence that Ordinary Least Squares estimators of beta coefficients of major firms and portfolios are highly sensitive to observations of extremes in market index returns. This sensitivity is rooted in the inconsistency of the quadratic loss function in financial theory. By introducing considerations of risk aversion into the estimation procedure using alternative estimators derived from Gini measures of variability one can overcome this lack of robustness and improve the reliability of the results.     

Public Preferences for Hydrogen Buses: Comparing Interval Data, OLS and Quantile Regression Approaches

We use a quantile regression (QR) approach to analyse contingent valuation estimates of public willingness to pay (WTP) for the air and noise pollution reductions associated with the introduction of hydrogen buses in London. QR results show that variables that were not significant in interval regression or ordinary least squares regression become significant at certain quantiles along the WTP distribution. In addition, the determinants of WTP at the lower tail of the distribution differ from those at the higher end of the distribution. Our findings illustrate the usefulness of quantile regression methods for analysing contingent valuation data, enhancing our understanding of the determinants of willingness to pay.     

影响中国原油进口量主要因素的实证分析

近年来,随着中国经济迅速发展,对原油的需求量不断加大,由于国内原油供给不足,中国原油进口数量持续增长,进口规模巨大,对外依存度逐年攀升,面临较大安全隐患。以1990～2013年相关数据为样本,采用OLS多元回归方法对影响中国原油进口贸易的因素进行实证分析。结果表明：世界原油产量、中国国内生产总值以及中国煤炭消费量是影响中国原油进口量的主要因素。据此,提出了相关建议。     

财政支农资金对“三农”问题的影响分析

三农问题一直是我国政府关注的焦点,而提高财政支农资金对三农的使用效益始终又是学术界研究的热点。通过选取我国1995～2006年的财政支农资金数据,研究财政支农资金投入对农民人均纯收入的影响,提出在增加财政支农资金总量投入的前提下,优化其投入结构和方向,全面提高财政支农资金使用效益,从根本上解决三农问题。     

安徽省第三产业内部结构演进趋势分析

按第三产业4个层次的划分,对1994年以来安徽省第三产业内部的演变过程做纵向分析和横向分析,通过利用最小二乘法建立线性回归分析模型,揭示其内部各层次之间演进的规律性及其潜在的内部演进趋势。     

中国上市公司资本结构影响因素研究

将资本结构与股权相结合,将股权结构、股权集中度、股票种类因子(A、B、H股)纳入资本结构影响因素.利用OLS回归进行分析,引入权益因子后的研究发现:中国的上市公司存在着股权融资偏好,而国家股比重越高的上市公司受到的外潦融资约束越大;资产负债率与B、H股比率负相关.     

The Heckman Correction for Sample Selection and Its Critique

This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman's (1976, 1979) two-step estimator for estimating selection models. Such models occur frequently in empirical work, especially in microeconometrics when estimating wage equations or consumer expenditures.
It is shown that exploratory work to check for collinearity problems is strongly recommended before deciding on which estimator to apply. In the absence of collinearity problems, the full-information maximum likelihood estimator is preferable to the limited-information two-step method of Heckman, although the latter also gives reasonable results. If, however, collinearity problems prevail, subsample OLS (or the Two-Part Model) is the most robust amongst the simple-to-calculate estimators.     

基于Eviews和OLS的成本产量分析

运用Eviews 5.0软件和最小二乘估计法（OLS）对企业生产过程中成本与产量之间的关系进行定量分析,通过建立线性回归模型,找出两者间的定量关系。由此提出了加强生产管理,降低生产成本的对策建议。     

我国股指期货的套期保值研究

本文经实证发现,计算沪深300仿真股指期货合约的最优套期保值比率时应选用OLS模型、ECM模型,而且ECM模型估计的最优套期保值比率较OLS模型估计的最优套期保值比率稍大,但两者的套期保值效果相差不大.在实际的套期保值中,如果套期保值期限较短,样本区间应较短;否则,样本区间应较长.