Evaluation of the social and economic impact of carbon dioxide (CO2) emissions on sustainable mobility using cumulative ordinal models: trend odds model

In the context of environmental sustainability evaluation, grouped under climate change, health and ecosystem themes, an impact that could be investigated is the Global Warming Potential (GWP), whose sources are a multitude. In urban areas the evaluation of real vehicles emissions is an essential activity in order to suggest possible solution to local administrators. They still express the need to improve and maintain the characteristics of the breathing air at the best possible quality level. Moreover, these solutions, such as planning measures or traffic control management in respect of pollution, would be apply at different geographical levels, i.e. national, regional or urban scale. Another factor to be investigated is the effect of technologies and emission control systems to comply more stringent limits (Euro 4/5/6) and improve air quality to a lower environmental impact. GWP, indicator of climate change, is measured in terms of CO₂ equivalency emission values variable. To perform this activity an experimental campaign was carried out with several vehicles from different manufacturers and with a wide variety in terms of mass, power, engine displacement and type approval technology. The experimental plan includes some repetitions of the urban section in Naples city centre.The purpose of this paper is twofold: first, to provide a strategy on the choice of a logistic model with ordinal data and with trend, and, second, to evaluate the usefulness of such models for environmental sustainability (CO₂ and other vehicular pollutant emissions), with particular emphasis on model formulation, the interpretation of model coefficients, and the implications of such models.     

R＆D、R＆D溢出、内生增长和内生收敛

根据强调知识与技术创新、知识与技术溢出重要性的当代内生增长理论，本文建立了一个将R＆D和R＆D溢出与资本积累之间、R＆D和R＆D溢出与总产出增长之间直接关联起来的动态模型。面板数据协整检验实证分析结果表明R＆D和R＆D溢出与资本积累之间、R＆D和R＆D溢出与总产出增长之间分别存在显著的正面长期协整关联。进一步的分析表明，R＆D与资本积累之间、R＆D与总产出增长之间分别存在显著的长期双向格兰杰因果关系。由此观知，R＆D乃长期经济增长源泉之所在。另一方面，尽管资本积累或总产出增长并不格兰杰导致R＆D溢出，证据表明R＆D溢出格兰杰导致资本积累和总产出增长。这种由R＆D溢出到资本积累和总产出增长的单向格兰杰因果关系意味着尽管知识与技术的跨国传播并非必然发生。其实为世界经济增长的重要动力。     

非农化经营与农业上市公司经营绩效——理论分析与实证检验

我国农业上市公司非农化经营现象甚为严重,这一现象对农业上市公司经营绩效的影响引起了社会各界的广泛关注.农业上市公司非农化经营主要可以归纳为产业层次和企业管理层次这两方面成因.农业发展不足的现实成为我国农业上市公司非农化经营取向的最大产业背景因素.文章运用农业比较利益理论、外部性理论以及多元化经营理论,形成对农业上市公司非农化经营成因和非农化经营对绩效影响的理论分析框架.通过实证分析所得出的结论是:非农化经营从整体上减损了农业上市公司经营绩效.研究认为,政府应该着力在改善农业投资经营环境和制度创新上下功夫,才可能真正引导农业上市公司专注于农业上来;同时认为,目前农业上市公司主要应当实施农业专业化经营战略,在条件具备的情况下才实施与主业相关的多元化战略,现阶段应尽量避免非相关多元化经营.     

贵州经济增长与外国直接投资相关性的实证分析

通过运用协整技术和误差修正模型对贵州省1985～2003年期间的数据进行分析可知,贵州省经济增长与外国直接投资之间存在长期的动态均衡关系.从长期来看,外商对贵州的直接投资直接促进了贵州省经济的增长,经济增长与外国直接投资呈正向变动.但是这种促进作用还比较有限,而且对外国直接投资的影响作用不明显.     

市场化与经济增长:一个短期的因果关系检验

利用我国1999-2002年省际区域的面板数据,运用面板数据Granger因果关系检验技术,对我国市场化水平与经济增长的关联度进行了实证分析.得出市场化是经济增长的Granger原因,但是经济增长不是市场化的Granger原因的结论.     

软件限时开发方法的研究与应用

限时开发是快速应用开发的最佳实践之一。文章介绍了限时开发的基本概念和优点以及适用的项目范围,通过一个进销存软件的开发实例说明如何成功地应用限时开发方法。     

协整向量误设对相关检验的影响

常用于检验既定协整关系的统计量有tDF和tECM两种，但由于真实数据生成过程未知，估计模型中可能存在一定程度的协整向量误设，从而使统计量的分布特征受到影响。本文首先探讨tDF检验的隐含系数约束α=γ，即短期弹性等于先验长期弹性；其次分析零假设下两种统计量的分布特征，以及先验设定γ对信号噪声比q进而对tECM分布特征的影响；最后在局部备择假设下，给出两种统计量的渐近分布，并表明向量误设会降低协整检验的势，其程度与设定误差d正相关。     

Testing for unit roots in time series models with non-stationary volatility

Many of the key macro-economic and financial variables in developed economies are characterized by permanent volatility shifts. It is known that conventional unit root tests are potentially unreliable in the presence of such behaviour, depending on a particular function (the variance profile) of the underlying volatility process. Somewhat surprisingly then, very little work has been undertaken to develop unit root tests which are robust to the presence of permanent volatility shifts. In this paper we fill this gap in the literature by proposing tests which are valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt and smooth-transition) volatility change processes as special cases. Our solution uses numerical methods to simulate the asymptotic null distribution of the statistics based on a consistent estimate of the variance profile which we also develop. The practitioner is not required to specify a parametric model for volatility. An empirical illustration using producer price inflation series from the Stock–Watson database is reported.     

Two-sample rank tests with truncated populations

LetX ₁,…,X _m andY ₁,…,Y _n be two independent samples from continuous distributionsF andG respectively. Using a Hoeffding (1951) type theorem, we obtain the distributions of the vector S=(S ₍₁₎,…,S _(n)), whereS _(j)=# (X _i ’s≤Y _(j)) andY _(j) is thej-th order statistic ofY sample, under three truncation models: (a)G is a left truncation ofF orG is a right truncation ofF, (b)F is a right truncation ofH andG is a left truncation ofH, whereH is some continuous distribution function, (c)G is a two tail truncation ofF. Exploiting the relation between S and the vectorR of the ranks of the order statistics of theY-sample in the pooled sample, we can obtain exact distributions of many rank tests. We use these to compare powers of the Hajek test (Hajek 1967), the Sidak Vondracek test (1957) and the Mann-Whitney-Wilcoxon test. We derive some order relations between the values of the probagility-functions under each model. Hence find that the tests based onS ₍₁₎ andS _(n) are the UMP rank tests for the alternative (a). We also find LMP rank tests under the alternatives (b) and (c).     

Three Corrected Score Tests for Generalized Linear Models with Dispersion Covariates

We develop three corrected score tests for generalized linear models with dispersion covariates, thus generalizing the results of Cordeiro , Ferrari and Paula (1993) and Cribari-Neto and Ferrari (1995) . We present, in matrix notation, general formulae for the coefficients which define the corrected statistics. The formulae only require simple operations on matrices and can be used to obtain analytically closed-form corrections for score test statistics in a variety of special generalized linear models with dispersion covariates. They also have advantages for numerical purposes since our formulae are readily computable using a language supporting numerical linear algebra. Two examples, namely, iid sampling without covariates on the mean or dispersion parameter oand one-way classification models, are given. We also present some simulations where the three corrected tests perform better than the usual score test, the likelihood ratio test and its Bartlett corrected version. Finally, we present a numerical example for a data set discussed by Simonoff and Tsai (1994) .