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GMM 与矩条件:广义矩估计、条件矩限制与经验似然。
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Bayesian bootstrap credible sets for multidimensional mean functional

多维均值泛函的贝叶斯自助法可信集

This paper shows that the Bayesian bootstrap (BB) distribution of a multidimensional mean functional based on i.i.d. observations has a strongly unimodal Lebesgue density provided the convex hull of the data has a nonempty interior. This result is then used to construct the finite sample BB credible sets. The influence of an outlier on these credible sets is studied in detail and a comparison is made with the empirical likelihood ratio confidence sets in this context.

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Initial conditions and moment restrictions in dynamic panel data models

动态面板模型中的初始条件与矩限制

In this paper we consider estimation of the autoregressive error components model. When the autoregressive parameter is moderately large and the number of time series observations is moderately small, the usual Generalised Methods of Moments (GMM) estimator obtained after first differencing has been found to be poorly behaved. Here we consider alternative linear estimators that are designed to improve the properties of the standard first-differenced GMM estimator. We…

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Intertemporal substitution in import demand and habit formation

进口需求中的跨期替代与习惯形成

To study non-durable import demand, we extend previous work done by Clarida (1994) and Ceglowski (1991) by considering a two-good version of the lifecycle model in which we introduce time-non-separability in the households' preferences. The model is estimated using quarterly data for the USA and France. Using the information contained in the observed stochastic and deterministic trends, we derive a cointegration restriction used to estimate curvature parameters of the…

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Empirical likelihood as a goodness-of-fit measure

作为拟合优度度量的经验似然

The method of empirical likelihood can be viewed as one of allocating probabilities to an n-cell contingency table so as to minimise a goodness-of-fit criterion. It is shown that, when the Cressie-Read power-divergence statistic is used as the criterion, confidence regions enjoying the same convergence rates as those found for empirical likelihood can be obtained for the entire range of values of the Cressie-Read parameter λ, including − 1, maximum entropy, 0, empirical…

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An evaluation of the power and conditionality properties of empirical likelihood

经验似然的功效与条件性性质评估

Empirical and dual likelihood are two of a growing array of artificial or approximate likelihoods currently in use in statistics. A question of major interest focuses on the performance of these new constructs relative to ordinary parametric likelihoods. We consider here two criteria, local power and conditional properties. Looking at tests of a scalar parameter, we show that there is no loss of efficiency in using a dual or empirical likelihood model, to second order. To…

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Inference-Without-Smoothing in the Presence of Nonparametric Autocorrelation

存在非参数自相关时的无平滑推断

The author gives conditions under which nonparametric autocorrelation-consistent variance estimation is possible without smoothing. The conditions are relevant to inference on slope parameters in models with an intercept and strictly exogenous regressors, and allow regressors and disturbances to collectively have considerable stationary long memory and to satisfy only mild, in some cases minimal, moment conditions. His estimate dominates smoothed ones in the sense that it…

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The Objective Function of Simulation Estimators Near the Boundary of the Unstable Region of the Parameter Space

参数空间不稳定区域边界附近的模拟估计目标函数

The paper examines the role of stability constraints in estimation by dynamic simulation. In particular, it analyzes the behavior of the objective function on either side of the boundary of the stability region of the parameter space. The main finding is that stability constraints may be ignored because the simulation-based objective function contains a built-in penalty to enforce stability. A key caveat, however, is that the dynamic stability of the auxiliary model that…

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Analysis of cointegration vectors using the GMM approach

使用 GMM 方法分析协整向量

This paper generalizes Johansen's (1988) maximum likelihood approach of the analysis of cointegrating vectors to the generalized method of moments (GMM) approach. We derive the asymptotic distribution of the cointegration vectors estimated from the fully modified generalized method of moments (FM-GMM) estimation procedure. We also introduce the FM-GMM version of Johansen's (1988) likelihood ratio (LR) test for the rank of a cointegrating matrix. Unlike the LR test which has…

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Information Theoretic Approaches to Inference in Moment Condition Models

矩条件模型推断的信息论方法

This paper develops a variant of one-step efficient GMM based on the KLIC rather than empirical likelihood. As in other one-step methods, the authors introduce M (the number of moments) auxiliary 'tilting' parameters which are used to construct a reweighting of the data so that the reweighted sample obeys all the moment conditions at the parameter estimates. Parameter and overidentification tests can be recast in terms of these tilting parameters; such tests are often…

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Empirical likelihood methods with weakly dependent processes

弱相依过程的经验似然方法

This paper studies the method of empirical likelihood in models with weakly dependent processes. In such cases, if the likelihood function is formulated as if the data process were independent, obviously empirical likelihood fails. We propose to use empirical likelihood of blocks of observations to solve this problem in a nonparametric manner. This method of "blockwise empirical likelihood" preserves the dependence of data, and the resulting likelihood ratios can be used to…

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Efficient Estimation With Panel Data When Instruments Are Predetermined: An Empirical Comparison of Moment-Condition Estimators

预定工具变量下的面板有效估计:矩条件估计量的实证比较

The author examines the empirical performance of instrumental variables estimators with predetermined instruments in an application to life-cycle labor supply under uncertainty. The estimators studied are two stage least squares, generalized method-of-moments (GMM), forward filter, independently weighted GMM, and split-sample instrumental variables. The author compares the bias/efficiency trade-off for the estimators using bootstrap algorithms suggested by D. A. Freedman…

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Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments

回归变量与工具变量可能非平稳时的完全修正 IV、GIVE 与 GMM 估计

This paper develops a general theory of instrumental variables (IV) estimation that allows for both I(1) and I(0) regressors and instruments. The main goal of this paper is to develop a theory in which one does not need to know the integration properties of the regressors in order to obtain efficient estimators. The estimation techniques involve an extension of the fully modified (FM) regression procedure that was introduced in earlier work by Phillips and Hansen (1990). FM…

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Efficient estimation of panel data models with sequential moment restrictions

具有序贯矩限制的面板数据模型的有效估计

This paper considers asymptotically efficient estimation of the panel data models with sequential moment restrictions in an environment with i.i.d. observations. It is shown that the GMM estimator with an increasing set of instruments attains the semiparametric efficiency bound of the model. The estimator considered here allows for the heteroscedasticity of the unknown form.

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A Stopping Rule for the Computation of Generalized Method of Moments Estimators

计算广义矩估计量的停止规则

To obtain consistency and asymptotic normality, a generalized method of moments (GAM) estimator typically is defined to be an approximate global minimizer of a GAM criterion function. To compute such an estimator, however, can be problematic because of the difficulty of global optimization. To alleviate this problem, the author proposes a stopping-rule (SR) procedure for computing GAM estimators. The SR procedure eliminates the need for global search with high probability.…

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An Information-Theoretic Alternative to Generalized Method of Moments Estimation

广义矩估计的信息论替代方法

While optimally weighted generalized method of moments (GAM) estimation has desirable large sample properties, its small sample performance is poor in some applications. The authors propose a computationally simple alternative, for weakly dependent data generating mechanisms, based on minimization of the Kullback-Leibler information criterion. Conditions are derived under which the large sample properties of this estimator are similar to GAM, i.e., the estimator will be…

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One-Step Estimators for Over-Identified Generalized Method of Moments Models

过度识别广义矩模型的一步估计量

In this paper I discuss alternatives to the GMM estimators proposed by Hansen (1982) and others. These estimators are shown to have a number of advantages. First of all, there is no need to estimate in an initial step a weight matrix as required in the conventional estimation procedure. Second, it is straightforward to derive the distribution of the estimator under general misspecification. Third, some of the alternative estimators have appealing information-theoretic…

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Empirical likelihood confidence regions in time series models

时间序列模型的经验似然置信域

This paper develops empirical likelihood in time series models. By application of Whittle's estimation method, one obtains an M-estimator of the parameter of a stationary time series from approximately independent observations, the periodogram ordinates. This estimator is used to obtain an empirical likelihood ratio which is asymptotically distributed as x2 and which can be used to construct confidence regions. A procedure for the Bartlett correction is also proposed.…

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Likelihood Ratio Specification Tests

似然比设定检验

Moment based tests for mispecification of parametric models (e.g., of mean equals variance in a Poisson model) are studied. The moment restrictions under test are embedded in an extension of the model so that the moment test is a score test of the hypothesis that a vector of added parameters is zero. Second-order asymptotic properties of the likelihood ratio version of this test are studied. Unlike the conventional test, the likelihood ratio version is Bartlett correctable.…

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ENDOGENEITY IN COUNT DATA MODELS: AN APPLICATION TO DEMAND FOR HEALTH CARE

计数数据模型中的内生性:医疗服务需求应用

The generalized method of moments (GMM) estimation technique is discussed for count data models with endogenous regressors. Count data models can be specified with additive or multiplicative errors. It is shown that, in general, a set of instruments is not orthogonal to both error types. Simultaneous equations with a dependent count variable often do not have reduced form which is a simple function of the instruments. However, a simultaneous model with a count and a binary…

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PATENTS, R&D, AND TECHNOLOGICAL SPILLOVERS AT THE FIRM LEVEL: SOME EVIDENCE FROM ECONOMETRIC COUNT MODELS FOR PANEL DATA

企业专利、研发与技术溢出:计数面板模型的证据

The paper analyses the relationship between the main determinants of technological activity and patent applications. To this end, an original panel of 181 international manufacturing firms investigating substantial amounts in R&D during the late 1980s has been constructed. The number of patent applications by firms is explained by current and lagged levels of R&D expenditures and technological spillovers. Technological and geographical opportunities are also taken into…

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ESTIMATING THE INNOVATION FUNCTION FROM PATENT NUMBERS: GMM ON COUNT PANEL DATA

从专利数量估计创新函数:计数面板数据的 GMM 方法

The purpose of this paper is to estimate the patent equation, an empirical counterpart to the 'knowledge-production function'. Innovation output is measured through the number of European patent applications and the input by research capital, in a panel of French manufacturing firms. Estimating the innovation function raises specific issues related to count data. Using the framework of models with multiplicative errors, we explore and test for various specifications:…

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ENDOGENEITY IN COUNT DATA MODELS: AN APPLICATION TO DEMAND FOR HEALTH CARE

计数数据模型中的内生性:医疗服务需求应用

The generalized method of moments (GMM) estimation technique is discussed for count data models with endogenous regressors. Count data models can be specified with additive or multiplicative errors. It is shown that, in general, a set of instruments is not orthogonal to both error types. Simultaneous equations with a dependent count variable often do not have reduced form which is a simple function of the instruments. However, a simultaneous model with a count and a binary…

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