面板数据的分位回归方法及其模拟研究

文章讨论了含有固定效应的面板数据模型,给出了3种估计未知参数的分位回归方法,蒙特卡洛模拟结果显示这些分位回归方法是处理面板数据的有效手段,且在误差非正态时优于均值回归方法。文章最后给出了一个真实数据的建模案例,得到了有利于决策的有用参考信息。     

Statistical inference of partially linear panel data regression models with fixed individual and time effects

This article considers a partially linear panel data model with fixed individual and time effects in a setting where both N and T are large. Based on the within transformation and profile likelihood method, we propose an approach to estimating the parametric and non parametric components of the partially linear model. The resultant estimators are shown to be consistent and asymptotically normal. Monte Carlo simulations are also conducted to illustrate the finite-sample performance of the proposed estimators.     

双效应面板ELES模型的构建与实证研究

本文在拓展ELES模型传统假设的基础上,将ELES模型推广到面板数据模型。构建同时包含时间效应和个体效应的双效应面板ELES模型,提出实证研究中模型形式的识别检验流程,并利用面板ELES模型实证研究了2002-2012年期间我国城镇居民消费结构的变动特征。     

基于Gibbs抽样算法的面板数据分位回归方法

 文章讨论了含有随机效应的面板数据模型,利用非对称Laplace分布与分位回归之间的关系,文章建立了一种贝叶斯分层分位回归模型。通过对非对称Laplace分布的分解,文章给出了Gibbs抽样算法下模型参数的点估计及区间估计,模拟结果显示,在处理含随机效应的面板数据模型中,特别是在误差非正态的情况下,本文的方法优于传统的均值模型方法。文章最后利用新方法对我国各地区经济与就业面板数据进行了实证研究,得到了有利于宏观调控的有用信息。     

Testing for random individual effects using recursive residuals

This paper derives a simple ANOVA-F-statistic which tests for random individual effects in a one-way error component model, using recursive residuals. Power comparisons are performed for this F-test when it is computed using true disturbances and recursive residuals from a panel data regression. Under the null, both statistics have an exact F distribution. The standardized version of the Breusch and Pagan (1980) Lagrange Multiplier test (SLM) as well as a fixed effects F-statistic (FE) recommended by Moulton and Randolph (1989), are also included in this comparison. The exact power function can be computed in all cases using Imhof's (1961) procedure. Our results suggest that the F-test based on recursive residuals is inferior to the popular SLM and FE tests based on computational simplicity, power comparisons and its sensitivity to the K observations starting the recursion.     

具有组群异方差结构的面板数据模型及其应用研究

面板数据由不同个体的时间序列数据汇聚而成。已有大量研究表明面板数据个体之间存在组群结构,并且普遍存在模型的异方差现象。本文借鉴组群异质性的研究成果,构建模型误差项组群结构的面板数据模型,基于模型假定条件,提出惩罚伪最大似然函数估计法(PQMLE),该方法能够同时进行结构识别和参数估计;证明了估计量具有Oracle渐近性质;蒙特卡洛模拟验证了该方法有效的样本性质;进一步应用该方法对我国股市进行Fama-French三因子模型的实证分析,验证了理论模型的应用效果。     

The repair alert models with fixed and random effects

This article extends a random preventive maintenance scheme, called repair alert model, when there exist environmental variables that effect on system lifetimes. It can be used for implementing age-dependent maintenance policies on engineering devices. In other words, consider a device that works for a job and is subject to failure at a random time X, and the maintenance crew can avoid the failure by a possible replacement at some random time Z. The new model is flexible to including covariates with both fixed and random effects. The problem of estimating parameters is also investigated in details. Here, the observations are in the form of random signs censoring data (RSCD) with covariates. Therefore, this article generalizes derived statistical inferences on the basis of RSCD albeit without covariates in past literature. To do this, it is assumed that the system lifetime distribution belongs to the log-location-scale family of distributions. A real dataset is also analyzed on basis of the results obtained.     

会计公允值制度对股权结构与绩效关系的影响效应研究——基于中国上市商业银行面板删失异质性数据的分析

 本文基于商业银行的特殊性,考虑会计公允值约束,以招商、深发展、浦发展、华夏、民生、兴业银行等上市股份制商业银行2000-2007年的样本数据,运用删失（Censoring）面板数据建模技术（Panel Data Modelling）,选择适当的控制变量,详尽分析了股权集中度和股东性质2个维度8项指标所描述的商业银行股权结构对商业银行银行3个维度7项结构指标的正面绩效和3项结构指标的负面绩效的影响。删失面板建模实证分析结果表明,在各家银行绩效异质性和会计公允值制度的约束下,本文从绩效构成结构方面,更为深入系统地揭示了股权集中度和股东性质对上市商业银行流动性、盈利性、成长性等正面绩效以及竞争结构、监管压力和资产质量等负面绩效的依存关系;各家上市商业银行绩效在结构方面存在异质性;测度股权结构对商业银行绩效的影响效应时,考虑公允值制度与否,所得结论在结构上有着显著的差异性甚至相反的结论。     

A Test for Slope Heterogeneity in Fixed Effects Models

Typical panel data models make use of the assumption that the regression parameters are the same for each individual cross-sectional unit. We propose tests for slope heterogeneity in panel data models. Our tests are based on the conditional Gaussian likelihood function in order to avoid the incidental parameters problem induced by the inclusion of individual fixed effects for each cross-sectional unit. We derive the Conditional Lagrange Multiplier test that is valid in cases where N → ∞ and T is fixed. The test applies to both balanced and unbalanced panels. We expand the test to account for general heteroskedasticity where each cross-sectional unit has its own form of heteroskedasticity. The modification is possible if T is large enough to estimate regression coefficients for each cross-sectional unit by using the MINQUE unbiased estimator for regression variances under heteroskedasticity. All versions of the test have a standard Normal distribution under general assumptions on the error distribution as N → ∞. A Monte Carlo experiment shows that the test has very good size properties under all specifications considered, including heteroskedastic errors. In addition, power of our test is very good relative to existing tests, particularly when T is not large.     

固定效应部分线性变系数面板模型的快速有效估计

本文将最小二乘支持向量机(LSSVM) 和二次推断函数法(QIF) 相结合，为个体内具有相关结构的固定效应部分线性变系数面板模型提供了一种新的快速估计方法；在一定的正则条件下，论证了参数估计量的渐近正态性和非参数估计量的收敛速度；采用Monte Carlo模拟考察了估计方法在有限样本下的表现并将估计技术应用于现实数据分析。该方法不仅保证了估计的有效性和统计推断力，而且程序运行速度得到较大幅度提升。     

Estimation of Some Nonlinear Panel Data Models With Both Time-Varying and Time-Invariant Explanatory Variables

The so-called “fixed effects” approach to the estimation of panel data models suffers from the limitation that it is not possible to estimate the coefficients on explanatory variables that are time-invariant. This is in contrast to a “random effects” approach, which achieves this by making much stronger assumptions on the relationship between the explanatory variables and the individual-specific effect. In a linear model, it is possible to obtain the best of both worlds by making random effects-type assumptions on the time-invariant explanatory variables while maintaining the flexibility of a fixed effects approach when it comes to the time-varying covariates. This article attempts to do the same for some popular nonlinear models.     

A two-stage estimation for panel data models with grouped fixed effects

ABSTRACT

This paper considers panel data models with fixed effects which have grouped patterns with unknown group membership. A two-stage estimation (TSE) procedure is developed to improve the properties of the GFE estimators of common parameters when the time span is small. Firstly, the common parameters are estimated. Subsequently, the optimal group assignment and the estimators of group effects are obtained by the K-means algorithm. Monte Carlo results reveal that the TSE estimator has a much smaller bias than the GFE estimator when the values of difference between effects are moderately small or at high variance of the idiosyncratic error.     

固定效应模型基于个体LM的新可混合性检验

对固定效应模型,本文基于拉格朗日乘数（LM）原理提出了一种新的可混合性检验。不同于已有的LM型可混合性检验,这里使用每个截面个体的LM统计量构建可混合性检验统计量。数理分析表明,本文所提的方法有着渐进正态性,对于扰动项的异方差和非正态均稳健,且与PY检验（Pesaran&Yamagata,2008）渐近等价。Monte Carlo模拟实验表明,相对于PY检验及另外两种LM型的可混合性检验,对于不同大小的 ,本文提出的方法有着良好的水平表现和更优越的检验势。     

浙江省城镇居民收入差距对消费结构影响的实证分析

改革开放以来,浙江省城镇居民间的收入差距不断扩大。这在一定程度上抑制了居民消费的提高,阻碍了居民消费结构的升级,进而影响消费总需求。本文利用Panel data模型,对浙江省城镇居民收入差距对消费结构的影响进行实证分析(2000-2006年),具体分析不同收入等级在各种消费品上的差别,从而有利于调整和实施不同收入等级的不同消费政策。     

真实固定效应空间随机前沿模型的贝叶斯估计

忽略个体效应和空间效应会严重干扰效率测算,其中忽略个体效应使得技术无效率项发生偏移,忽略空间相关性导致估计量有偏且不一致。本文基于真实固定效应随机前沿模型（引入了个体效应）,引入因变量和双边误差项的空间滞后项,构建了适用性更佳的真实固定效应空间随机前沿模型。对模型进行组内变化以消除额外参数,使用贝叶斯方法（需推导未知参数的后验分布并执行MCMC抽样）估计参数和技术效率。该方法真正克服了额外参数问题,比同类方法直观、简便。数值模拟结果表明,本文方法对参数、个体截距项及技术无效率项的估计精度均较高,且增加样本容量,估计精度变优。     

Optimal change-over designs for correlated observations

Design implications of an autoregressive model for change-over experiments are investigated. In this model, the residual effect due to the previous treatment is assumed to be proportional to the response in the previous period. In addition, the errors from the same experimental subject are assumed to be correlated according to a first-order autoregressive model. Models with fixed and random subject effects are discussed separately. An attempt has been made to identify and construct optimal or nearly optimal designs in various situations. Empirical conclusions of Taka and Armitage [Commun. Statist. Theor. Meth. (1983)12, 865-876] regarding the efficiency of some designs have also been confirmed.     

时变空间权重矩阵面板数据模型稳健LM检验有效性研究

空间权重矩阵是描述个体间空间关系的重要工具,通常基于个体间的地理距离构造不随时间而改变的空间权重矩阵。然而,当个体间的空间关系源自经济/社会/贸易距离或人口流动性/气候等特征时,空间权重矩阵本质上可能将随时间而改变。由此,本研究提出时变空间权重矩阵面板数据模型的稳健LM检验。大量Monte Carlo模拟结果显示：从检验水平和功效角度来看,基于误设的非时变空间权重矩阵的稳健LM检验存在较大偏差,但是基于时变空间权重矩阵的稳健LM检验能够有效地识别面板数据中的空间关系类型。尤其是,在时间较长和个体较多等情况下,时变空间权重矩阵的稳健LM检验功效更高。     

固定效应面板线性回归模型的移动分块经验似然估计

本文针对固定效应面板线性回归模型中特意误差项为任意形式序列相关情形,提出了移动分块经验似然估计方法,并给出了大样本性质。模拟研究表明：该方法适用于特意误差项序列相关形式已知和形式未知两种情形,较Baltagi和Li（1994）以及Gon?alves（2011）提出的方法有效。本文采用该方法对CO2排放量与城市化水平之间的关系进行了实证分析,结果表明：城市化水平对CO2排放量有显著影响,不同城市化阶段对CO2排放量影响不同。     

中国转型期现代物流发展与制造业竞争力提升关系研究——基于2000—2007年分省面板数据的实证分析

通过运用数据包络分析(Data Envelopment Analysis),根据中国2000-2007年的职工人数、固定资产等经济数据构建一个能反映各地区制造业综合竞争力的单一数字指标,然后利用这些效率指标以及现代物流行业的外延数据构成面板数据(Panel Data)建立模型。通过实证分析得出:中国现代物流的发展有利于制造业竞争力提升。最后根据上述结论提出一些建议:大力发展面向生产的现代物流行业,细化深化专业分工,鼓励生产制企业改造现有业务流程,推进物流业务外包,加强核心竞争力和对外开放水平。