浙江制造业发展的重点与思路——基于主导产业倒U型演进假说的分析

 本文根据1991-2004浙江、上海和中国相关统计数据，运用制造业占全国份额、产业部门增长率等方法分析了浙江省制造业发展在全国的基本情况，提出并验证了反映区域主导产业演进特征和过程的主导产业倒U型演进假说。结合浙江省经济发展的实际，确定了作为浙江当前产业发展重点的主导产业和支柱产业，提出了浙江省制造业发展的基本思路是资金密集、技术密集型产业优先发展，劳动密集型产业规划发展。浙江当前制造业发展的具体战略是“外引内孵”、“东扩西进”，注重择商引资，加强自主创新，实现区域产业的合理升级和转移。     

A joint test for arch and bilinearity in the regression model

In this paper we argue that a simultaneous test for ARCH and bilinearity should be used to test for the possible nonlinearity of the error process in the regression model. We suggest such a joint test statistic. An empirical example shows that the individual tests of ARCH and bilinearity may not be conclusive while a joint test clearly rejects the linearity hypothesis. Our results are also applicable to pure time series models.     

Selection of error probability laws by generalized modified profile likelihood

Although error probability law selection of models of location-scale forms is of importance in some sense, the commonly used model selection procedures, such as AIC and BIC, do not apply to it. By treating error probability law as a “parameter” of interest, location and scale as nuisance parameters, this paper proposes that generalized modified profile likelihood (GMPL), considered as a quasi-likelihood function of error probability law, be used to select the error probability laws. The GMPL method achieves minimax rate optimality and proves to be consistent. Simulations show its good performance for finite and even small samples. Note that it is straightforward to generalize the GMPL of location-scale models to various models of location-scale forms particularly including the various linear regression models and their variations, to select their error probability laws. The author believes that GMPL and its variations would be quite promising for various model selection problems.     

中国基尼系数警戒线的一个估计

 本文基于1978-2007年我国居民收入分配的分组数据测算了多个基尼系数,采用参数和非参数多种方法估计了基尼系数的分布服从渐近正态分布,最后基于大样本渐近特征给出了我国基尼系数警戒水平的估计值。     

北京市能源消费与经济增长关系研究

 本文利用面板协整理论和基于面板误差修正模型的Granger因果关系检验分析了北京市能源消费和经济增长的关系。面板协整检验表明北京市能源消费和经济增长之间存在长期协整关系,进一步基于面板误差修正模型的Granger因果关系检验表明北京市短期存在能源消费到经济增长的单向因果关系,长期能源消费和经济增长之间存在双向的因果关系。因此北京市在进行节能减排的工作时,必须考虑到能源消费减少对经济增长的负作用,尽可能采取提高能源利用效率的措施,包括利用财政税收优惠政策鼓励节能技术的研发,在政府采购时要求产品在生产过程中采用节能技术,更关键也是更重要的是积极探索能源价格机制改革,通过价格手段促进企业真正具备节能意识,主动节约能源,提高利用效率。     

面板数据模型中随机效应存在性检验的理论研究及其实证分析

 由于能体现异质性等一系列优良性质,面板数据模型正被广泛应用到经济学各个领域中。然而,在反映异质性的个体效应和时间效应的设定上,经常存在人为的主观性和随意性,因此容易导致错误指定事件的发生。本文提出了一个稳健的方法分别检验面板数据模型中随机个体效应和随机时间效应的存在性。具体而言,通过对残差进行正交化变换消去可能存在的时间效应,并建立人工自回归模型,然后基于该模型自回归系数的最小二乘估计构造检验统计量检验个体效应。构造的检验是单边的,零假设下渐近服从标准正态分布。在检验时间效应时,可类似得到统计量及其渐近性质。功效研究表明这些检验敏感性较强,能检测到以参数速度（最快的速度）收敛到零假设的备择假设。通过模拟试验研究了检验统计量的小样本性质,并进行了实际数据分析。     

Two-way ANOVA when the distribution of the error terms is skew t

In this article, we assume that the distribution of the error terms is skew t in two-way analysis of variance (ANOVA). Skew t distribution is very flexible for modeling the symmetric and the skew datasets, since it reduces to the well-known normal, skew normal, and Student's t distributions. We obtain the estimators of the model parameters by using the maximum likelihood (ML) and the modified maximum likelihood (MML) methodologies. We also propose new test statistics based on these estimators for testing the equality of the treatment and the block means and also the interaction effect. The efficiencies of the ML and the MML estimators and the power values of the test statistics based on them are compared with the corresponding normal theory results via Monte Carlo simulation study. Simulation results show that the proposed methodologies are more preferable. We also show that the test statistics based on the ML estimators are more powerful than the test statistics based on the MML estimators as expected. However, power values of the test statistics based on the MML estimators are very close to the corresponding test statistics based on the ML estimators. At the end of the study, a real life example is given to show the implementation of the proposed methodologies.     

Modeling binary responses with stochastic covariates

In a traditional binary regression model, covariates are assumed to be fixed by design. In practice, however, they are most likely to be stochastic and non-normally distributed. We develop modified maximum likelihood estimators for such situations. We show that these estimators are more efficient than the traditional binary regression estimators and robust to data anomalies. We illustrate our results using a real life example.     

基于奇异值分解去势的非线性趋势序列单位根检验研究

 如何克服ADF与PP单位根检验法对非线性趋势平稳序列的伪检验,提高单位根检验的功效,是非平稳时间序列分析的重要问题。本文基于奇异值分解的思路,构造出检验非平稳时间序列单位根的SVD-RMA检验法,此方法将时间序列的趋势项与干扰项分离,然后用递归均值调整法对干扰项进行检验。仿真实验表明,SVD-RMA法对线性与非线性趋势、甚至结构突变过程的检验功效都非常好;对非线性趋势平稳的检验而言,SVD-RMA检验得到正确结论的可能性要远远好于ADF与PP检验。     

基于准残差的Panel协整检验

 当检验方程含有确定性趋势时,基于残差的Panel协整检验通过全样本回归来消除确定性趋势的方法会导致检验统计量出现Nickell偏差,必须使用标准化系数进行修正,但这些标准化系数却依赖于真实设定参数。本文将Breitung和Das（2005）等使用部分样本回归消除确定性趋势的方法应用到Panel协整检验,提出了基于准残差的Panel协整检验,我们证明了这种新的检验统计量的渐近正态性,模拟的结果也表明其具有非常良好的小样本表现。