《墨西哥气候变化法》及其对中国气候安全立法的启示

《墨西哥气候变化法》是在特殊的国际、国内立法背景下通过的,是在遵循气候正义、气候公平等法理基础上制定的,有广泛的国际、国内法律基础.该法规定了一系列应对气候变化的原则、规则和相应的实施机制,具有注重“协调与参与”、“透明与责任”制度性设计等特点.中国与墨西哥同为发展中国家,中国在参考和借鉴《墨西哥气候变化法》合理成分的基础上,应采取诸如制定综合性气候变化应对法、加强气候变化应对能力建设、进行减缓性与适应性立法等措施,以应对全球气候变化带来的挑战.     

自然资源资产审计的风险识别与应对措施——以EG公司为例

自然资源资产审计是处于起步期的审计新领域。透过审计人员对EG公司自然资源资产的风险识别与分析,探讨了自然资源资产审计的风险应对措施。     

融资约束、债务融资能力与股票定价——对高融资约束公司高系统风险的进一步解释

在考察债务融资能力对融资约束公司投资敏感性影响的基础上,探析债务融资能力对股票定价的影响。理论与实证分析结果表明,对于受到较高融资约束的公司,债务融资能力的提高显著增加了公司的投资—现金流敏感性,且高债务融资能力的公司具有较高的系统风险和预期收益。这是由于信贷限制、公司投资和公司价值之间的动态传导机制形成的“乘数”效应,使得融资约束较高的公司具有更强烈的顺周期性,在股票市场中则表现为系统性风险的提高。     

Female Employment and Divorce: Taking Into Account a Social Multiplier

A model of interactions of marriage and labor markets, taking into account a feedback process from aggregate divorce rates on individuals' decisions, explains why small changes in men's attitudes towards sharing the breadwinner role with their wives may change female labor force participation rates and divorce rates considerably.     

空间动态面板模型的时间滞后效应检验

空间面板数据模型由于考虑了经济变量间的空间相关性,其优势日益凸显,已成为计量经济学的热点研究领域。将空间相关性与动态模式同时扩展到面板模型中的空间动态面板模型,不仅考虑了经济变量之间的空间相关性,还考虑了时间上的滞后性,是空间面板模型的发展,增强了模型的解释力。考虑一种带固定个体效应、因变量的时间滞后项、因变量与随机误差项均存在空间自相关性的空间动态面板回归模型,提出了在个体数n和时间数T都很大,且T相对地大于n的条件下空间动态面板模型中时间滞后效应存在性的LM和LR检验方法,其检验方法包括联合检验、一维及二维的边际和条件检验;推导出这些检验在零假设下的极限分布;其极限分布均服从卡方分布。通过模拟试验研究检验统计量的小样本性质,结果显示其具有优良的统计性质。     

Supply risk mitigation: a multi-theoretical perspective

Due to the increasing level of supply risk, it is imperative to obtain a better understanding of the nature of risk which is a premise to developing well-grounded risk mitigation strategies. This paper examines how to mitigate supply risk enlightened by discussing the concept of risk in association of three closely related concepts which are uncertainty, variability and trust. The proposed three perspectives are supported and explained using four case studies comprising of two manufacturers based in Australia and four suppliers based in China. The study provides evidence that supply risk can be mitigated by high level of information and knowledge sharing as well as building trust, commitment and goal congruence in a buyer–supplier relationship. It offers theoretical and managerial implications.     

AN EXTENSION OF THE EM ALGORITHM FOR OPTIMIZATION OF CONSTRAINED LIKELIHOOD: AN APPLICATION IN TOXICOLOGY

Since its introduction in the mid 1970's, the EM algorithm has found a widespread popularity for solving the likelihood equations. Several investigators have used the algorithm in a variety of problems with incomplete information to obtain maximum likelihood estimates in numerous applications. The algorithm, however, becomes inappropriate when the underlying equations are subject to some constraints. Although an extension has been proposed to derive solutions when the parameters are subject to a set of linear constraints, the evaluation of likelihood equations from incomplete data when the equations are subject to a nonlinear constraint is still an open problem. Here, we consider a mixture model, a classical example of incomplete data, and discuss the problem of maximum likelihood estimation of the model parameters when the parameters have to satisfy a nonlinear constraint. An extension of the EM algorithm based on the celebrated Lagrange multiplier will be proposed to solve the equations. An application of the methodology in animal bioassay experiments for risk assessment of toxic substances will be described and data from a toxicological experiment will be used to illustrate the results.     

Testing for Serial Correlation: Generalized Andrews–Ploberger Tests

This paper considers testing the null hypothesis that a times series is uncorrelated when the time series is uncorrelated but statistically dependent. This case is of interest in economic and finance applications. The GARCH(1, 1) model is a leading example of a model that generates serially uncorrelated but statistically dependent data. The tests of serial correlation introduced by Andrews and Ploberger (1996, hereafter AP) are generalized for the purpose of testing the null. The rationale for generalizing the AP tests is that they have attractive properties for cases for which they were originally designed: they are consistent against all nonwhite-noise alternatives and have good all-round power against nonseasonal alternatives compared to several widely used tests in the literature. These properties are inherited by the generalized AP tests.     

Tests for Serial Dependence and Other Specification Analysis in Models of Markets in Disequilibrium

The assumption of serial independence of disturbances is the starting point of most of the work done on analyzing market disequilibrium models. We derive tests for serial dependence given normality and homoscedasticity using the Lagrange multiplier (LM) test principle. Although the likelihood function under serial dependence is very complicated and involves multiple integrals of dimensions equal to the sample size, the test statistic we obtain through the LM principle is very simple. We apply the test to the housing-start data of Fair and Jaffee (1972) and study its finite sample properties through simulation. The test seems to perform quite well in finite samples in terms of size and power. We present an analysis of disequilibrium models that assumes that the disturbances are logistic rather than normal. The relative performances of these distributions are investigated by simulation.     

The effects of outliers on two nonlinearity tests

Two Lagrange multiplier tests for time series nonlinearities in the presence of outliers are examined by simulation experiments. The nonlinearities studied are autoregressive conditional heteroskedasticity (ARCH) and bilinearity; the outlier types are additive, innovative, temporary change and reallocation outliers. The results show that both the sizes and powers of the tests can be severely distorted by even a single outlier. The severity of the distortions depends on the outlier type and magnitude, but also on the underlying process generating 'the series.