半参数变系数空间误差回归模型的估计

研究目标：克服半参数变系数回归模型中误差项可能存在的空间相关性问题。研究方法：提出一类新的半参数变系数空间误差回归模型,并构造其截面似然估计。研究发现：在小样本条件下,模型估计量具有良好的表现,其精度随着样本容量的增加而提高;应用该方法分析我国资源禀赋与地方公共品供给之间的相互关系,进一步证实了模型较强的适用性。研究创新：证明了估计量的一致性与渐近正态性,并通过蒙特卡洛模拟考察了估计方法的小样本表现。研究价值：新方法对于其他结构的半/非参数空间计量模型理论研究具有推广价值,其估计技术在经济、管理等学科中具有应用价值。     

时空动态半参数变系数随机效应面板模型的估计

研究目标：克服半参数变系数面板模型中扰动项和因变量存在时空动态性问题。研究方法：提出一类更加一般化的时空动态半参数变系数随机效应面板模型，并构建截面似然估计量。研究发现：估计量具有良好的小样本性质，估计误差随着样本总量的提高而减小，在Case空间矩阵下，空间滞后和时空滞后系数的估计精度随空间复杂度的增大而降低，用该方法分析我国外商直接投资、知识产权保护与经济增长关系，进一步证实了模型的适用性。研究创新：证明了估计量满足一致性和渐近正态性，数值模拟考察了估计量的小样本性质。研究价值：拓展了现有半参数变系数空间面板模型的形式，增强了模型的适用性和解释力，有益于经济问题实证研究的开展。     

时变系数的空间误差合成模型

本文对时变系数的空间误差合成模型进行了研究,该模型的特征是利用扰动项中的空间个体成分将不同时期的方程联系起来;同时,允许自变量系数和误差项中的空间自回归系数随时间而变化,但每一个时期的自变量系数和误差项中的空间自回归系数是固定不变的。本文使用基于FGLS和GM方法的多阶段估计策略对模型参数进行了估计,证明了估计量的渐进异质性,并利用Monte Carlo方法模拟了其小样本性质。模拟结果表明,估计量的渐近性质随着样本容量的增加而改善。对中国省际知识生产及其空间溢出的实证案例也体现了该模型的应用价值。     

非线性动态面板模型的条件GMM估计

基于时间序列的实证分析已经证实,很多经济变量的动态调整过程都存在非线性的平滑转换机制.本文将传统的线性动态面板模型扩展为平滑转换的非线性动态面板模型,并基于对非线性参数的格点搜索,提出了一种简便易行的非线性动态面板模型估计程序--条件GMM估计,其估计量具有一致性.仿真实验结果显示,条件GMM估计量在有限样本下具有良好表现.同时,非线性动态面板模型的条件GMM估计还为在非线性框架下检验面板单位根创造了条件.     

带未知异方差与半线性结构Tobit模型的半参数估计

本文将Tobit模型扩展至同时带未知条件异方差与半线性结构回归函数的场合,并提出一种计算简便的半参数二步估计法。该方法的关键之处在于连续两次施以成对相减变换,并先后消去第一步所得被解释变量非参数条件分位函数中的两类非线性冗余成分(非线性回归函数部分与未知异方差结构)。文章证明了估计量的n-一致性与渐近正态性,并通过Monte Carlo模拟研究了分位点对的选择、扰动项分布类型与样本删尾程度等因素对估计量小样本性质的影响。最后通过国内居民医疗服务利用不平等的实例验证了本文所提的方法。     

倾向指数匹配方法：变量选择和模型设定问题

本文讨论了倾向指数匹配方法估计中变量选择和模型设定对估计偏差的影响。发现条件独立性假设是正确估计平均因果效应的关键。如果潜在结果影响选择,倾向指数匹配方法是无法消除估计偏差的。在满足条件独立性假设的前提下,倾向指数模型的变量选择非常重要。如果加入与倾向指数无关的变量,不会造成估计偏差,反而有时会提高估计精度,如果遗漏决定选择的重要变量,将会造成估计偏差。最后,结合案例给出一种条件独立性的检验方法。     

非参数空间滞后模型的贝叶斯估计

本文采用Bayes方法对非参数空间滞后模型进行全面分析,包括参数的估计以及用自由节点样条来拟合未知联系函数。所建议的Bayes方法通过逆跳Markov chain Monte carlo算法（RJMCMC）来实现。在进行贝叶斯分析时,对样条系数与误差方差选取共轭的正态—逆伽玛先验分布,进而获得其他未知量的边际后验分布;另外,文章还设计了一个简单但一般的随机游动Metropolis抽样器,以方便从空间权重因子的条件后验分布中进行抽样。最后应用所建议的方法进行数值模拟。     

层级数据空间误差自回归模型的估计方法研究

本文建立同时考虑空间误差自回归和嵌套随机效应误差分量的层级数据空间误差自回归模型,并推导最优权重GMM估计量,对空间自回归系数和误差项的方差进行估计。然后,定义对应的FGLS估计量,对层级数据空间误差自回归模型的总体回归系数进行估计。通过蒙特卡洛模拟,验证了所提出模型估计量的有限样本性质。模拟结果表明,本文提出的最优权重GMM估计量以及总体回归系数的GMM FGLS估计量有很好的小样本性质。     

Ⅳ估计的大样本性质——基于二维参数空间的研究

存在很多个工具变量或工具变量为弱工具变量时,Ⅳ估计的大样本性质是近年来Ⅳ估计研究的新方向.本文提出了一种新的研究思路,从参数空间的角度重新剖析了Ⅳ估计在大样本下的各种收敛情况.借鉴Rothenberg(1984)的研究方法,我们将Ⅳ估计的结果表示为参数δ(工具变量个数的阶数)和λ(工具变量解释强度的阶数)的函数;根据Ⅳ估计量收敛情况的不同,我们对参数δ和λ的可行性区域进行对应的划分,将Ⅳ估计的研究划分为6种情形,涵盖了传统理论、Bekker(1994)、Staiger和Stock(1997)以及Chao和Swanson(2003b)的研究结论.     

IV估计的大样本性质——基于二维参数空间的研究

存在很多个工具变量或工具变量为弱工具变量时,IV估计的大样本性质是近年来IV估计研究的新方向。本文提出了一种新的研究思路,从参数空间的角度重新剖析了IV估计在大样本下的各种收敛情况。借鉴Rothenberg(1984)的研究方法,我们将IV估计的结果表示为参数δ(工具变量个数的阶数)和λ(工具变量解释强度的阶数)的函数;根据IV估计量收敛情况的不同,我们对参数δ和λ的可行性区域进行对应的划分,将IV估计的研究划分为6种情形,涵盖了传统理论、Bekker(1994)、Staiger和Stock(1997)以及Chao和Swanson(2003b)的研究结论。     

Self-weighted and local quasi-maximum likelihood estimators for ARMA-GARCH/IGARCH models

The limit distribution of the quasi-maximum likelihood estimator (QMLE) for parameters in the ARMA-GARCH model remains an open problem when the process has infinite 4th moment. We propose a self-weighted QMLE and show that it is consistent and asymptotically normal under only a fractional moment condition. Based on this estimator, the asymptotic normality of the local QMLE is established for the ARMA model with GARCH (finite variance) and IGARCH errors. Using the self-weighted and the local QMLEs, we construct Wald statistics for testing linear restrictions on the parameters, and their limiting distributions are given. In addition, we show that the tail index of the IGARCH process is always 2, which is independently of interest.     

Estimating multiple equation hybrid models with endogenous dummy regressors*

Estimating multiple equation hybrid models with endogenous dummy regressors is burdensome if the number of dummies and equations is large. Therefore, after clarifying model structure and identification issues the paper presents a generalization of the Amemiya principle. The new estimator reduces the computational costs and is flexible with regard to different types of variables. Furthermore, it is consistent and asymptotically normal distributed.     

Penalized estimation of panel vector autoregressive models: A panel LASSO approach

This paper proposes LASSO estimation specific for panel vector autoregressive (PVAR) models. The penalty term allows for shrinkage for different lags, for shrinkage towards homogeneous coefficients across panel units, for penalization of lags of variables belonging to another cross-sectional unit, and for varying penalization across equations. The penalty parameters therefore build on time series and cross-sectional properties that are commonly found in PVAR models. Simulation results point towards advantages of using the proposed LASSO for PVAR models over ordinary least squares in terms of forecast accuracy. An empirical forecasting application including 20 countries supports these findings.     

EWMA-GARCH模型与GARCH模型在估计收益率波动上的差异的实证及理论分析

VaR作为衡量风险的指标,其核心则在于对波动,亦即方差的估计。基于时间序列,关于条件方差的经典模型是GARCH模型,尽管后来又衍生出了EGARCH,PARCH等复杂模型,但在实务中GARCH模型仍占有重要的地位。文章分析了一种比较新的结合了EWMA模型的GARCH模型(以下称为EWMA-GARCH模型)计算VaR的参数估计方法,以检验其在估计波动上的实用性,并对实证检验结果做了理论分析。分析结果表明,尽管该结合模型缺乏完整的理论支持,但是其计算效果仍比较良好,当然这样良好的结果是建立在因缺乏理论依据而导致的对模型的其他要求之上的.至于是采用受理论支持的模型还是并不输实践价值的模型,文章也给出了一定的建议。     

Estimation of a linear regression under microaggregation with the response variable as a sorting variable

Microaggregation is a popular statistical disclosure control technique for continuous data. The basic principle of microaggregation is to group the observations in a data set and to replace them by their corresponding group means. However, while reducing the disclosure risk of data files, the technique also affects the results of statistical analyses. The paper deals with the impact of microaggregation on a multiple linear regression in continuous variables. We show that parameter estimates are biased if the dependent variable is used to form the groups. Using this result, we develop a consistent estimator that removes the aggregation bias, and derive its asymptotic covariance matrix.     

Taking financial frictions to the data

We estimate a Dynamic Stochastic General Equilibrium (DSGE) model with various financial frictions and analyze how well the model explains the Great Recession. Predictive analysis shows that the model can only slightly better explain the large deviation from trend during the crisis relative to a model without financial frictions. Specifically, the risk premium shock, which is a shock to the external finance premium of the entrepreneurs׳ leverage, explains the largest part of the investment downfall during the crisis. However, the ‘balance sheet’ channel of financial frictions in the model, which structurally links balance sheet conditions of financial intermediaries and nonfinancial borrowers to their borrowing rates, is estimated to be weak. We examine alternative prior specifications for how the financial frictions enter the model and continue to find a limited role for these frictions. Rolling-window estimation provides evidence for substantial time variation in parameters governing financial frictions. We conclude that the well-known financial frictions studied in this paper are not able to explain the financial crisis in a linearized and estimated model.     

产业国际竞争力研究进展述评

产业国际竞争力研究是当前经济领域的热点研究问题,国内外学者对其进行了大量研究,然而对其理论与分析模型的全面系统回顾却不多见。文章全面回顾了产业国际竞争力的研究现状并详细评述了其分析模型,为今后的进一步研究奠定了基础。     

The life-length of banknotes*

Abstract With the aid of the Bank's banknote sorting system the issue and subsequent withdrawal of f 25–banknotes on three varieties of paper have been recorded for two-and-a-half years. The aim was to measure the durability of the three paper varieties in circulation. The results of this second trial with f 25–banknotes confirm the statistical model developed previously for the first trial with f 100–banknotes. GRESHAM's Law is equally not applicable, neither to f 25–banknotes nor to f 100–banknotes. A two-parameter gamma distribution fits the cumulative fraction of banknotes withdrawn reasonably well.     

On Limits of Uniquely Best Linear Estimators

In a general linear model, it is shown that all admissible linear estimators are limits of linear estimators that are uniquely best at some point in an extended parameter set. The principal result shows that a linear estimator that is uniquely best at a pointW ₂ among multiple linear estimators that are best at a pointW ₁ is the limit of uniquely best estimators at points approachingW ₁ along the line joiningW ₁ andW ₂. Research supported in part by U.S.A.F. Aerospace Research Laboratories under contract F33615-71-C-1463, summer 1973, and in part by Grant DMS-9104811 from the National Science Foundation.     

运用功能评价理论,确立多元成本计算模式

在市场经济中 ,企业成本计算不仅要提供满足内部管理所需的成本数据 ,还要提供满足国家宏观管理要求的财务成本数据。采用多元成本计算模式是满足这一要求的必要条件。在理论上 ,多元成本计算模式可以是各种成本计算方法之间进行任一组合所建立的一组特定的成本计算模式 ,但这些模式对某一特定企业是否适用 ,还需要借助功能评价理论加以确定。