Fixed T dynamic panel data estimators with multifactor errors

This article analyzes a growing group of fixed T dynamic panel data estimators with a multifactor error structure. We use a unified notational approach to describe these estimators and discuss their properties in terms of deviations from an underlying set of basic assumptions. Furthermore, we consider the extendability of these estimators to practical situations that may frequently arise, such as their ability to accommodate unbalanced panels and common observed factors. Using a large-scale simulation exercise, we consider scenarios that remain largely unexplored in the literature, albeit being of great empirical relevance. In particular, we examine (i) the effect of the presence of weakly exogenous covariates, (ii) the effect of changing the magnitude of the correlation between the factor loadings of the dependent variable and those of the covariates, (iii) the impact of the number of moment conditions on bias and size for GMM estimators, and finally (iv) the effect of sample size. We apply each of these estimators to a crime application using a panel data set of local government authorities in New South Wales, Australia; we find that the results bear substantially different policy implications relative to those potentially derived from standard dynamic panel GMM estimators. Thus, our study may serve as a useful guide to practitioners who wish to allow for multiplicative sources of unobserved heterogeneity in their model.     

Mixtures of Gaussian copula factor analyzers for clustering high dimensional data

Mixtures of factor analyzers is a useful model-based clustering method which can avoid the curse of dimensionality in high-dimensional clustering. However, this approach is sensitive to both diverse non-normalities of marginal variables and outliers, which are commonly observed in multivariate experiments. We propose mixtures of Gaussian copula factor analyzers (MGCFA) for clustering high-dimensional clustering. This model has two advantages; (1) it allows different marginal distributions to facilitate fitting flexibility of the mixture model, (2) it can avoid the curse of dimensionality by embedding the factor-analytic structure in the component-correlation matrices of the mixture distribution.An EM algorithm is developed for the fitting of MGCFA. The proposed method is free of the curse of dimensionality and allows any parametric marginal distribution which fits best to the data. It is applied to both synthetic data and a microarray gene expression data for clustering and shows its better performance over several existing methods.     

马克思主义视阈下的生产力解读

迄今,国内外对生产力的含义众说纷纭,有"劳动生产率与因素综合说";有"人类的能力说";有"人对自然的作用说";有"关系系统说". 正确地把握马克思主义生产力含义,对于我们坚持"解放生产力,发展生产力"的思想和科学发展观有重大的理论意义和实践意义.重新审视马克思的原著,应该把生产力定义为:劳动者通过具体劳动生产出满足人们需要的使用价值时所表征出来的力量.按照这一观点,决定生产力的因素应该包括实体性因素、附着性因素或渗透性因素和运行性因素.     

影响蓖麻种子萌发因子的研究

对蓖麻种子萌发进行温度、水分、播种深度、种皮等处理试验，结果表明，温度和播种深度显著影响蓖麻种子萌发，其中土壤温度低和覆土厚是导致蓖麻种子萌发缓慢的主要因子;种皮的存在有利于菌麻种子萌发;土壤水分含量在10％以上能满足蓖麻种子萌发。     

试论城市化进程中的民族关系--以对临夏市的调查为视点

临夏市作为西北民族地区的一个小城市,在城市化进程中,其民族关系也会受到影响.针对临夏市的实际情况及学术界的研究现状,我们选取临夏市城市化进程中变化较大的几个变量,即民族居住格局的变迁、人口流动的影响、民族通婚的增减以及宗教因素,作为研究重点来衡量城市化进程中的民族关系.在此基础上得出临夏市各民族之间的关系总体上是平等、团结、互助、合作的社会主义新型民族关系,和谐平等的民族关系占据了主导地位的结论,并归纳出城市化进程中临夏市的民族关系具有主从性、敏感性、易发性、历史性、隐蔽性、复杂性等特点,最后提出临夏市各族群众必须解决自身的定位问题,建立临夏市和谐民族关系的良性运转机制.     

Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets

We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time‐varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset‐specific instruments. The estimator uses simple weighted two‐pass cross‐sectional regressions, and we show its consistency and asymptotic normality under increasing cross‐sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no‐arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi‐period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousand U.S. stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time‐invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four‐factor model capturing market, size, value, and momentum effects.     

Identification Properties of Recent Production Function Estimators

This paper examines some of the recent literature on the estimation of production functions. We focus on techniques suggested in two recent papers, Olley and Pakes (1996) and Levinsohn and Petrin (2003). While there are some solid and intuitive identification ideas in these papers, we argue that the techniques can suffer from functional dependence problems. We suggest an alternative approach that is based on the ideas in these papers, but does not suffer from the functional dependence problems and produces consistent estimates under alternative data generating processes for which the original procedures do not.     

京津冀三地创新绩效比较研究

京津冀地区是中国重要的经济区域,但近年来三地发展水平出现分化,京津两市与河北省的差距拉大,有出现“极化”效应的可能。通过构建创新效率的评价体系,对京津冀三地3年的技术创新投入和产出作DEA方法分析,结果表明河北省的创新效率明显低于京津两市。京津冀三地在综合发展水平、劳动力素质、R＆D活动经费投入和外商投资企业的技术溢出水平上的差异,是这种技术创新效率产生差异的原因。     

贸易开放对中国水环境污染影响的实证研究

文章基于2004-2013年中国31个省市的面板数据,采用动态面板模型和差分GMM估计方法,分别选取化学需氧量排放和氨氮排放作为水环境污染的有机污染物和无机污染物的排放指标,对贸易开放的结构效应引致的中国水环境污染排放进行了实证研究.研究结果表明,经济增长的规模和技术效应是影响水环境污染排放的主要因素,直接结构效应对中国水污染排放的影响不显著,贸易开放的结构效应也在一定程度上加剧了中国水环境污染的排放.通过引入贸易开放的相关交叉项进一步对决定贸易结构效应的比较优势来源进行识别,结果发现,对于中国水环境污染排放并不存在所谓的“污染天堂效应”和“要素禀赋效应”.贸易的结构效应会导致西部经济欠发达地区的水污染排放降低,而对中东部经济相对发达地区,贸易的结构效应会引致其水污染排放量的增大和排放强度的加剧.     

碳排放约束下能源经济效率的区域空间分布研究——基于能源消费结构门槛视角

利用2000—2012年样本数据对全要素省际能源经济效率进行了测算,研究发现样本期间绝大部分省市自治区能源经济效率整体都呈不断下降的趋势,并且生产过程中低效率地区大幅增加,分布状态由“点状”向“面状”扩散,尤其是中西部地区下降较为明显,究其原因主要为:二氧化碳排放和能源消费结构是能源经济效率变化和地区差异的重要影响因素;据此运用门槛分析方法对其进行区域空间分布研究,将全国30个省市自治区划分为低排放—结构较合理、低排放—结构欠合理、高排放—结构较合理类群、高排放—结构欠合理和高排放—结构不合理5大类群,最后结合各类型区域自身发展特点,提出因地制宜的低碳绿色发展建议,并从需求侧和供给侧两方面提出能源经济效率改善的政策建议。