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1.
在空间面板误差模型中,由于空间误差项和随机效应项相关,构建随机效应检验统计量时无法直接采用传统的F检验。同时,如果面板数据在时间维度上存在序列相关,要检验随机效应将变得更加困难。本文主要研究在扰动项存在序列相关的情况下如何构建空间面板误差模型中随机效应的稳健检验统计量。相应的有限样本性质通过蒙特卡罗模拟给出。  相似文献   

2.
本文以上市银行为样本,应用面板的个体固定效应模型,不仅研究股权集中度、董事会特征与银行绩效间的关系,而且研究股权集中度与董事会特征的交互效应与银行绩效间的关系。研究发现:(1)董事会的规模、董事会独立性、董事会积极性都与银行绩效有显著的正相关;(2)股权集中度与银行绩效有显著的正相关关系;(3)股权集中度与董事会特征间存在交互效应,即股权集中度与董事会特征的交叉项与银行绩效有显著的负相关关系。  相似文献   

3.
研究目标:解决随机效应分位回归模型中固定效应和随机效应系数同时估计和选择问题。研究方法:对固定效应和随机效应系数同时实施自适应Lasso惩罚,并为参数估计设计交替迭代算法。研究发现:新方法不仅对随机误差分布具有较强的稳健性,而且在不同稀疏度模型下均有着良好的表现,尤其是在高维情形时。研究创新:本文提出的方法在对模型中重要自变量进行选择的同时能够充分考虑随机效应的影响;交替迭代算法不仅有效解决了需要选择两个惩罚参数的困境,而且收敛速度快。研究价值:为实际工作者对面板数据和纵向数据的分析提供了有效的建模方法。  相似文献   

4.
随机效应Logistic模型的参数估计   总被引:2,自引:0,他引:2  
在经济计量学中,对面板(panel)数据的研究是一个热门的话题。目前,讨论得较多的是如何运用线性随机效应模型来对它建模。可是,当因变量是二元的数据时,用线性随机效应模型进行建模显然是错误的。这时,比较常用的是随机效应Logistic模型。本文讨论了如何运用EM算法对随机效应Logistic模型进行参数估计。  相似文献   

5.
基于中国家庭追踪调查(CFPS)数据,采用面板固定效应模型和工具变量方法,考察与父母同住的家庭结构对女性劳动供给的影响。研究结果表明,同住父母通过协助料理家务与提供隔代照料等方式对女性的劳动供给具有“溢出效应”,而为同住父母提供照料帮助则对女性的劳动供给具有“挤出效应”,两种效应共同作用的结果显示“溢出效应”占优,即与父母同住对女性的劳动供给具有显著的促进作用。进一步的研究结果表明,托幼机构等幼教资源的可获得性会显著降低女性对多代同堂的依赖,但养老院等养老资源的可获得性对多代同堂的家庭结构没有显著影响。  相似文献   

6.
扰动项的空间过程会影响空间计量模型的估计效果。通过探究空间关联误差效应下空间动态面板数据(SDPD)模型拟极大似然估计(QML)的有限样本性质,发现含空间自回归误差项的SDPD模型大样本性质较好;其估计结果优于不含空间自回归误差项的模型;较强的误差项空间相关性对参数估计精度的影响程度较大;误差项分布偏离正态性会影响模型的估计结果,但模型总体估计的稳健性良好。总体蒙特卡洛结果与本文的理论分析一致。  相似文献   

7.
2015年4月沪市单日成交突破万亿元,沪深股市成为世界第二大股市市场,股市的收益与星期之间是否存在星期效应?本论文分为两部分,一部分是近十年的星期效应,利用ARMA-GARCH模型研究,第二部分是研究近两年的星期效应,利用的ARMA模型研究。通过统计与模型得出结论:星期效应正在改变,可能以后的星期效应会变得不显著性,甚至消失,说明我国的市场有效性正在增强。  相似文献   

8.
以金融发展为门槛变量,采用我国31个省区市2001—2015年的省级面板数据,运用静态面板数据门槛模型,研究外商直接投资(FDI)与减贫之间的非线性关系。研究结果表明:(1)在不同金融发展水平下,FDI对减贫效应的影响是不一样的,存在双重门槛效应,当金融发展水平较低时,FDI与减贫呈现正相关关系;当金融发展水平较高时,FDI与减贫呈现负相关关系。(2)这种非线性关系在不同区域表现形式也不同,东部门槛值高于中部,西部不存在门槛效应;西部FDI对减贫的作用高于东部和中部。  相似文献   

9.
一直以来,时间效应(又称“日期效应”)是股市研究中的一个重要内容,对于中国股市的实证研究也是如此。但是以往对于时间效应的检验中,绝大部分都是对一般收益率的统计分析,即使应用了一阶对数差分的收益率公式来进行检验,也缺乏对时间因素进行剔除。笔者则试图利用模型拟合的方  相似文献   

10.
文章将种群生态模型引入技术标准竞争,研究网络效应下二维技术标准之间的竞争可能出现的种种情况,并运用常微分方程理论和稳定性理论,讨论系统的稳定性,分析在不同的参数条件下企业标准竞争所出现的不同结果。  相似文献   

11.
交互效应面板数据模型在社会经济问题的实证分析中具有很强的适用性,但现有研究主要集中于线性面板模型。本文将交互效应引入非线性的面板截取模型,并基于ECM算法,建立了有效估计量和识别程序。基于不同因子类型的仿真实验结果显示,ECM算法可以很好地识别面板截取样本中的非观测因子。ECM估计量具有良好的有限样本性质,与其他估计量相比具有更小的偏误和更快的收敛速度。尤其是当共同因子为低频平滑因子时,其表现最为理想。  相似文献   

12.
Fixed and Random Effects in Stochastic Frontier Models   总被引:6,自引:1,他引:5  
Received stochastic frontier analyses with panel data have relied on traditional fixed and random effects models. We propose extensions that circumvent two shortcomings of these approaches. The conventional panel data estimators assume that technical or cost inefficiency is time invariant. Second, the fixed and random effects estimators force any time invariant cross unit heterogeneity into the same term that is being used to capture the inefficiency. Inefficiency measures in these models may be picking up heterogeneity in addition to or even instead of inefficiency. A fixed effects model is extended to the stochastic frontier model using results that specifically employ the nonlinear specification. The random effects model is reformulated as a special case of the random parameters model. The techniques are illustrated in applications to the U.S. banking industry and a cross country comparison of the efficiency of health care delivery.JEL classification: C1, C4  相似文献   

13.
This paper explores the impact of foreign direct investment (FDI) on the entrepreneurial activity in 16 European countries. By using Global Entrepreneurship Monitor (GEM) data, which enables the distinction necessity-driven vs. opportunity-driven entrepreneurs, we assess the influence of both inward and outward FDI on the entrepreneurial activity during the time span 2005–2012. We resort to a static, as well as to a dynamic panel data analysis. Our findings highlight the fact that the FDI has no clear influence on the total entrepreneurial activity, or on the established business ownership rate. Nevertheless, our results clearly state that both inward and outward FDI positively influences the necessity-driven entrepreneurs, while having a negative impact on the opportunity-driven entrepreneurs. The results prove to be robust regarding the use of a fixed and random effects panel model, two stages least square (2SLS) model, as well as the use of a system-Generalized Method of Moments (system-GMM) approach.  相似文献   

14.
Although convincing arguments have been put forward for continuous-time modeling, its use in panel research is rare. In one approach, classical N  = 1 state-space modeling procedures are adapted for panel analysis to estimate the exact discrete model (EDM) by means of filter techniques. Based on earlier less satisfactory indirect methods, a more recent approach uses structural equation modeling (SEM) to get the maximum likelihood estimate of the EDM by the direct method. After an introduction into continuous-time state-space modeling for panel data and the EDM, a thorough comparison is made between the two distinct approaches with quite different histories by means of Monte Carlo simulation studies. The model used in the simulation studies is the damped linear oscillator with and without random subject effects.  相似文献   

15.
文章采用2005~2012年长三角经济圈20个城市物流业发展与区域经济增长的面板数据进行实证分析,通过对数据进行平稳性检验和协整检验,证实了物流业发展和经济增长之间存在着长期协整关系。回归分析中Hausman检验拒绝存在随机效应的原假设,采用固定效应模型分析面板数据,发现物流业发展的三个指标,物流产业规模、物流供给规模和物流需求规模均和区域经济增长之间存在正相关关系,不同城市组别的回归分析发现,不同的区域经济发展策略对物流发展和经济增长之间的关系有着不同的影响。  相似文献   

16.
《Journal of econometrics》2005,126(2):493-523
The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis–Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models—a fixed effects model and a random effects model—are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed.  相似文献   

17.
This paper proposes a new panel data approach to identify and estimate the time-varying average treatment effect (ATE). The approach allows for treatment effect heterogeneity that depends on unobserved fixed effects. In the presence of this type of heterogeneity, existing panel data approaches identify the ATE for limited subpopulations only. In contrast, the proposed approach identifies and estimates the ATE for the entire population. The approach relies on the linear fixed effects specification of potential outcome equations and uses exogenous variables that are correlated with the fixed effects. I apply the approach to study the impact of a mother's smoking during pregnancy on her child's birth weight.  相似文献   

18.
In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test between the three alternatives in practice. We further propose a test statistic for testing the null hypothesis of random effects against fixed effects in a nonparametric panel data regression model. Simulations are used to examine the finite sample performance of the proposed estimators and the test statistics.  相似文献   

19.
《Journal of econometrics》2005,126(2):305-334
The paper analyzes a number of competing approaches to modeling efficiency in panel studies. The specifications considered include the fixed effects stochastic frontier, the random effects stochastic frontier, the Hausman–Taylor random effects stochastic frontier, and the random and fixed effects stochastic frontier with an AR(1) error. I have summarized the foundations and properties of estimators that have appeared elsewhere and have described the model assumptions under which each of the estimators have been developed. I discuss parametric and nonparametric treatments of time varying efficiency including the Battese–Coelli estimator and linear programming approaches to efficiency measurement. Monte Carlo simulation is used to compare the various estimators and to assess their relative performances under a variety of misspecified settings. A brief illustration of the estimators is conducted using U.S. banking data.  相似文献   

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