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广义矩方法AI 解读

We provide a brief overview of applications of generalized method of moments in finance. The models examined in the empirical finance literature, especially in the asset pricing area, often imply moment conditions that can be used in a straight forward way to estimate the model parameters without making strong assumptions regarding the stochastic properties of variables observed by the econometrician. Typically the number of moment conditions available to the econometrician…

广义矩方法与宏观经济学AI 解读

We consider the contribution to the analysis of economic time series of the generalized method-of-moments estimator introduced by Hansen. We outline the theoretical contribution, conduct a small-scale literature survey, and discuss some ongoing theoretical research.

Sargan 的工具变量估计与广义矩方法AI 解读

This article surveys J. D. Sargan's work on instrumental variables (IV) estimation and its connections with the generalized method of moments (GMM). First the modeling context in which Sargan motivated IV estimation is presented. Then the theory of IV estimation as developed by Sargan is discussed. His approach to efficiency, his minimax estimator, tests of overidentification and underidentification, and his later work on the finite-sample properties of IV estimators are…

广义矩方法中的弱工具变量与弱识别综述AI 解读

Weak instruments arise when the instruments in linear instrumental variables (IV) regression are weakly correlated with the included endogenous variables. In generalized method of moments (GMM), more generally, weak instruments correspond to weak identification of some or all of the unknown parameters. Weak identification leads to GMM statistics with nonnormal distributions, even in large samples, so that conventional IV or GMM inferences are misleading. Fortunately, various…

广义矩估计与经验似然AI 解读

Generalized method of moments (GMM) estimation has become an important unifying framework for inference in econometrics in the last 20 years. It can be thought of as encompassing almost all of the common estimation methods, such as maximum likelihood, ordinary least squares, instrumental variables, and two-stage least squares, and nowadays is an important part of all advanced econometrics textbooks. The GMM approach links nicely to economic theory where orthogonality…

k 步统计量与极值统计量的高阶渐近效率等价性AI 解读

It is well known that a one-step scoring estimator that starts from any N 1/2 -consistent estimator has the same first-order asymptotic efficiency as the maximum likelihood estimator. This paper extends this result to k -step estimators and test statistics for k ≥ 1, higher order asymptotic efficiency, and general extremum estimators and test statistics. The paper shows that a k -step estimator has the same higher order asymptotic efficiency, to any given order, as the…

美国股指收益的时间不可逆性与 EGARCH 效应AI 解读

Abstract In this paper we suggest using a modified version of the time reversibility (TR) test of Chen, Chou and Kuan ( 2000 ) as a complementary diagnostic test for time series models. The modified CCK test is easy to compute and requires weaker moment conditions than existing tests. Our simulations demonstrate that this test is powerful against asymmetry in volatility but the BDS test is not. In the empirical study of US stock index returns, we first find that these…

正交参数与面板数据AI 解读

This paper describes a class of consistent estimators for short panels with fixed effects. The method is to find an orthogonal reparametrization of the fixed effects and then to integrate the new effects from the likelihood with respect to an appropriately chosen prior density. The resulting marginal posterior densities of the common parameters have modes that are shown to be consistent in the models examined here. The main result concerns the first-order autoregressive…

修正估计函数AI 解读

In a parametric model the maximum likelihood estimator of a parameter of interest ψ may be viewed as the solution to the equation l′p(ψ) = 0, where lp denotes the profile loglikelihood function. It is well known that the estimating function l′p(ψ) is not unbiased and that this bias can, in some cases, lead to poor estimates of ψ. An alternative approach is to use the modified profile likelihood function, or an approximation to the modified profile likelihood function, which…

向量 M 估计目标的标量函数：高精度置信限AI 解读

This paper concerns high‐order inference for scalar parameters that are estimated by functions of multivariate M‐estimators. Asymptotic formulae for the bias and skewness of the studentised statistic are derived. Although these formulae appear complicated, they can be evaluated easily by using matrix operations and numerical differentiation. Various methods for constructing second‐order accurate confidence limits are discussed, including a method based on skewness‐reducing…

利用验证数据的线性协变量测量误差模型经验似然推断AI 解读

Linear errors‐in‐covariables models are considered, assuming the availability of independent validation data on the covariables in addition to primary data on the response variable and surrogate covariables. We first develop an estimated empirical loglikelihood with the help of validation data and prove that its asymptotic distribution is that of a weighted sum of independent standard x21 random variables with unknown weights. By estimating the unknown weights consistently,…

缺失响应数据插补下的经验似然推断AI 解读

Inference under kernel regression imputation for missing response data is considered. An adjusted empirical likelihood approach to inference for the mean of the response variable is developed. A nonparametric version of Wilks' theorem is proved for the adjusted empirical log-likelihood ratio by showing that it has an asymptotic standard chi-squared distribution, and the corresponding empirical likelihood confidence interval for the mean is constructed. With auxiliary…

非线性动态模型的模型选择检验AI 解读

This paper generalizes Vuong (1989) asymptotically normal tests for model selection in several important directions. First, it allows for incompletely parametrized models such as econometric models defined by moment conditions. Second, it allows for a broad class of estimation methods that includes most estimators currently used in practice. Third, it considers model selection criteria other than the models" likelihoods such as the mean squared errors of prediction. Fourth,…

利用经验似然检验线性模型中的线性约束AI 解读

In this paper we analyse the higher order asymptotic behaviour of a profiled empirical likelihood ratio which can be used to test a set of linear restrictions in linear regression models. We show that the resulting profiled empirical likelihood ratio admits a Bartlett correction which can be used to improve to third order the accuracy of commonly used tests in applied research without any distributional assumptions about the error process. Copyright Royal Economic Society…

利用高阶矩的测量误差模型两步 GMM 估计AI 解读

We consider a multiple mismeasured regressor errors-in-variables model where the measurement and equation errors are independent and have moments of every order but otherwise are arbitrarily distributed. We present parsimonious two-step generalized method of moments (GMM) estimators that exploit overidentifying information contained in the high-order moments of residuals obtained by “partialling out” perfectly measured regressors. Using high-order moments requires that the…

GARCH 与非对称幂 GARCH 模型矩存在的充要条件AI 解读

Although econometricians have been using Bollerslev's (1986, Journal of Econometrics 31, 307–327) GARCH( r , s ) model for over a decade, the higher order moment structure of the model remains unresolved. The sufficient condition for the existence of the higher order moments of the GARCH( r , s ) model was given by Ling (1999a, Journal of Applied Probability 36, 688–705). This paper shows that Ling's condition is also necessary. As an extension, the necessary and sufficient…

条件异方差自回归模型的有效工具变量估计AI 解读

This paper analyzes autoregressive time series models where the errors are assumed to be martingale difference sequences that satisfy an additional symmetry condition on their fourth-order moments. Under these conditions quasi maximum likelihood estimators of the autoregressive parameters are no longer efficient in the generalized method of moments (GMM) sense. The main result of the paper is the construction of efficient semiparametric instrumental variables estimators for…

连续时间过程的经验特征函数估计AI 解读

This article examines the class of continuous-time stochastic processes commonly known as affine diffusions (AD's) and affine jump diffusions (AJD's). By deriving the joint characteristic function, we are able to examine the statistical properties as well as develop an efficient estimation technique based on empirical characteristic functions (ECF's) and a generalized method of moments (GMM) estimation procedure based on exact moment conditions. We demonstrate that our…

矩条件的部分冗余AI 解读

In this paper, we first transform a set of moment conditions into a set of transformed moment conditions, based on which the efficient partial generalized method of moments estimation for part of a parameter vector is defined. Given the set of transformed moment conditions, we then show that the conditions for partial redundancy of an additional set of moment conditions given an original set of moment conditions simply become the conditions for full redundancy of the second…

Lp-GMM 估计量的性质AI 解读

This paper considers generalized method of moment–type estimators for which a criterion function is minimized that is not the “standard” quadratic distance measure but instead is a general L p distance measure. It is shown that the resulting estimators are root- n consistent but not in general asymptotically normally distributed, and we derive the limit distribution of these estimators. In addition, we prove that it is not possible to obtain estimators that are more…

半参数混合模型中的经验似然AI 解读

Plant and animal studies of quantitative trait loci provide data which arise from mixtures of distributions with known mixing proportions. Previous approaches to estimation involve modelling the distributions parametrically. We propose a semiparametric alternative which assumes that the log ratio of the component densities satisfies a linear model, with the baseline density unspecified. It is demonstrated that a constrained empirical likelihood has an irregularity under the…

利用经验似然获得调查回归估计中的范围受限权重AI 解读

Design weights in surveys are often adjusted to accommodate auxiliary information and to meet pre‐specified range restrictions, typically via some ad hoc algorithmic adjustment to a generalised regression estimator. In this paper, we present a simple solution to this problem using empirical likelihood methods or generalised regression. We first develop algorithms for computing empirical likelihood estimators and model‐calibrated empirical likelihood estimators. The first…

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