变系数动态面板数据模型的半参数估计

本文把一般的常系数的动态面板数据模型拓广到变系数的情形。对于变系数的动态面板数据模型首先推导出模型所隐含的各种矩条件,然后利用广义矩估计的方法得到了模型中未知参数的半参数广义矩估计,最后对于我们所得到的估计的渐进性和一致性进行证明。     

汶川地震震源辐射能量持续时间的快速估计

研究中,我们从IRIS DMC搜集了震中距范围在30°-95°的欧洲台阵87个台站所记录的远震P波垂直分量,采用了IRIS提供的震源参数,首先利用IASPEI91速度模型以及几何射线方法计算出震源在震中位置时的理论走时(P波初至)进行时差校正,然后截取了P波初至前5秒和后15秒的波形记录,利用波形互相关计算出"互相关时差"并将其校正。     

Semiparametric inference in a GARCH-in-mean model

A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and GARCH-type underlying volatility is introduced. Based on the profile likelihood approach, it does not rely on any initial parametric estimator of the conditional mean function, and it is under stated conditions consistent, asymptotically normal, and efficient, i.e., it achieves the semiparametric lower bound. A sampling experiment provides finite sample comparisons with the parametric approach and the iterative semiparametric approach with parametric initial estimate of Conrad and Mammen (2008). An application to daily stock market returns suggests that the risk-return relation is indeed nonlinear.     

Semiparametric estimation of a truncated regression model

This paper proposes a new semiparametric estimator for the truncated regression model under the independence restriction. Many existing approaches such as those in Lee (1992) and Honoré and Powell (1994) are moment-based methods, whereas our approach makes use of the entire truncated distribution. As a result, our approach is expected to require weaker identification and to have more favorable performance. Our simulation results suggest that our estimator outperforms that of Lee (1992) and Honoré and Powell (1994) in a variety of designs. Our estimator is shown to be consistent and asymptotically normal.     

Semiparametric estimation of a bivariate Tobit model

The existing semiparametric estimation literature has mainly focused on univariate Tobit models and no semiparametric estimation has been considered for bivariate Tobit models. In this paper, we consider semiparametric estimation of the bivariate Tobit model proposed by Amemiya (1974), under the independence condition without imposing any parametric restriction on the error distribution. Our estimator is shown to be consistent and asymptotically normal, and simulation results show that our estimator performs well in finite samples. It is also worth noting that while Amemiya’s (1974) instrumental variables estimator (IV) requires the normality assumption, our semiparametric estimator actually outperforms his IV estimator even when normality holds. Our approach can be extended to higher dimensional multivariate Tobit models.     

基于期权调整持续期的银行资产负债组合优化模型

提出了基于期权调整持续期的银行资产负债隐含期权风险控制原理,结合持续期缺口的控制和法律、法规约束等控制银行的利率风险与流动性风险。以贷款利息收益最大为目标,以线性规划为工具,建立了基于期权调整持续期的银行资产负债组合优化模型。本文的创新与特色一是提出了基于期权调整持续期的银行资产负债组合优化原理,避免了资产与负债中的隐含期权给银行带来提前偿付风险。二是将利率结构对称原理和数量结构对称原理引入资产负债组合优化中,控制了银行经营中的流动性风险与利率风险,保护银行股东权益的安全,保证了银行资产配给的合法性与合规性。     

Semi-Nonparametric Estimation of an Equilibrium Search Model

We specify and estimate an equilibrium job search model with productivity differences across labour market segments. The model allows for two types of unemployment: frictional unemployment due to search frictions and structural unemployment due to wage floors. Wage floors exist because of high unemployment benefits or binding minimum wages. The productivity distribution is estimated semi-nonparametrically along the lines of Gallant-Nychka, using Hermite series approximation. We decompose the total unemployment rate and we examine the effects of changes in the minimum wage.     

期权定价模型的离散化矩估计

在本文中,把期权定价模型中的漂移项为一个常数,波动率假定为一个Ornstein-Uhlenbeck过程,在一定的条件下,把模型转变成唯一个双线性自回归EV模型,然后对其中的m(·)函数进行离散化后,通过矩估计的方法估计m(·)函数的系数,从而得到波动率σ的矩估计。     

SWARCH模型下的VaR估计

本文将状态转换下的ARCH模型（SWARCH）引入到估计金融资产VaR中，以上证股票指数为例进行实证分析，并与传统GARCH（1，1）模型中正态分布、t分布、GED分布估计的结果进行了比较，实证显示含有状态转换的VaR具有较好的估计效果。     

期权定价模型的离散化矩估计

在本文中,把期权定价模型中的漂移项为一个常数,波动率假定为一个Ornstein—Uhlenbeck过程,在一定的条件下,把模型转变成唯一个双线性自回归EV模型,然后对其中的m（·）函数进行离散化后,通过矩估计的方法估计m（·）函数的系数,从而得到波动率σ的矩估计。     

Semiparametric bounds on treatment effects

We present a variety of semiparametric models that produce bounds on the average causal effect of a binary treatment on a binary outcome. The semiparametric assumptions exploit variation in observable covariates to narrow the bounds. In our main model, the outcome is determined by a generalized linear model, but the treatment may be arbitrarily endogenous. Our bounding strategy does not require the existence of an instrument, but incorporating an instrument narrows the bounds. The bounds are further improved by combining the semiparametric model with the joint threshold-crossing assumption of Shaikh and Vytlacil (2005).     

Semiparametric models: an evaluation

We review ten years of work on semiparametric theory in statistics on the occasion of the recently published book by Bickel, Klaassen, Ritov and Wellner.     

Semiparametric econometrics: A survey

Semiparametric econometric models contain both parametric and nonparametric components, reflecting in some fashion what has been learned from economic theory and previous empirical experience, and what remains unknown. They raise such questions as how well the parametric component can be estimated, and how to construct rules of inference with good statistical properties. The paper attempts to survey the econometric and most relevant statistical literature on semiparametric inference, and includes a partial bibliography.     

随机效应Logistic模型的参数估计

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。     

非线性计量经济模型的非参数估计方法研究

本文提出使用核估计的方法构造平滑转移模型(STR)的非参数模拟最大似然估计(NPSML),给出了NPSML估计量的构造方法、渐近性质以及相应的核函数和窗宽的选择准则,并利用滑动窗宽算法对估计量的构造过程进行了改进。通过Monte Carlo实验证明,该方法是可靠的,并且当误差项存在序列相关时,此种估计量是稳健的。     

Estimation in Varying-coefficient Proportional Hazard Regression Model

In this paper, varying coefficient proportional hazard regression models are considered. The model is an important extension of the Cox model, and arises naturally if the coefficients change over different groups characterized by certain covariates in practice. Under random censorship, weighted partial likelihood estimators are defined for the varying coefficients by maximizing weighted partial likelihoods. It is shown that the proposed estimators are consistent and asymptotically normal.     

条件自回归极差模型与波动率估计

无论是在理论研究领域还是在应用领域,波动率的预测已经成为现代金融经济学和金融工程的重要课题。Chou（2005）针对极差提出了条件自回归极差模型（CARR）。本文在Parkinson（1980）的基础上,对极差作出了一个简单的修正,使得相应的CARR模型成为标准差的动态模型;然后以上证指数2001年4月27日至2005年12月5日的周收益率数据为样本,采用滚动样本的方法,利用CARR模型和GARCH模型分析了样本数据,作出了上证指数波动率样本外1至8周的预测,在多种事后波动率的测度下比较了修正后的CARR模型与GARCH模型对上证指数波动率的预测能力,证实了CARR模型在理论上的有效性。