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条件矩限制模型中的经验似然推断AI 解读

This paper proposes an asymptotically efficient method for estimating models with conditional moment restrictions. Our estimator generalizes the maximum empirical likelihood estimator (MELE) of Qin and Lawless (1994). Using a kernel smoothing method, we efficiently incorporate the information implied by the conditional moment restrictions into our empirical likelihood-based procedure. This yields a one-step estimator which avoids estimating optimal instruments. Our…

非参数函数的筛经验似然比检验AI 解读

Generalized likelihood ratio statistics have been proposed in Fan, Zhang and Zhang [Ann. Statist. 29 (2001) 153–193] as a generally applicable method for testing nonparametric hypotheses about nonparametric functions. The likelihood ratio statistics are constructed based on the assumption that the distributions of stochastic errors are in a certain parametric family. We extend their work to the case where the error distribution is completely unspecified via newly proposed…

门限模型的工具变量估计AI 解读

Threshold models (sample splitting models) have wide application in economics. Existing estimation methods are confined to regression models, which require that all right-hand-side variables are exogenous. This paper considers a model with endogenous variables but an exogenous threshold variable. We develop a two-stage least squares estimator of the threshold parameter and a generalized method of moments estimator of the slope parameters. We show that these estimators are…

In econometrics, models stated as conditional moment restrictions are typically estimated by means of the generalized method of moments (GMM). The GMM estimation procedure can render inconsistent estimates since the number of arbitrarily chosen instruments is finite. In fact, consistency of the GMM estimators relies on additional assumptions that imply unclear restrictions on the data generating process. This article introduces a new, simple and consistent estimation…

差异化产品需求系统参数估计的极限定理AI 解读

We provide an asymptotic distribution theory for a class of generalized method of moments estimators that arise in the study of differentiated product markets when the number of observations is associated with the number of products within a given market. We allow for three sources of error: sampling error in estimating market shares, simulation error in approximating the shares predicted by the model, and the underlying model error. It is shown that the estimators are CAN…

经验似然比置信区域覆盖概率的上界AI 解读

This paper studies the least upper bounds on coverage probabilities of the empirical likelihood ratio confidence regions based on estimating equations. The implications of the bounds on empirical likelihood inference are also discussed.

一类非高斯平稳过程与随机场的分形维数估计AI 解读

We present the asymptotic distribution theory for a class of increment-based estimators of the fractal dimension of a random field of the form g{X(t)}, where g:R→R is an unknown smooth function and X(t) is a real-valued stationary Gaussian field on Rd, d=1 or 2, whose covariance function obeys a power law at the origin. The relevant theoretical framework here is “fixed domain” (or “infill”) asymptotics. Surprisingly, the limit theory in this non-Gaussian case is somewhat…

Is individual labor income more risky in recessions? This is a difficult question to answer because existing panel data sets are so short. To address this problem, we develop a generalized method of moments estimator that conditions on the macroeconomic history that each member of the panel has experienced. Variation in the cross‐sectional variance between households with differing macroeconomic histories allows us to incorporate business cycle information dating back to…

响应随机缺失时的半参数回归分析AI 解读

We develop inference tools in a semiparametric partially linear regression model with missing response data. A class of estimators is defined that includes as special cases a semiparametric regression imputation estimator, a marginal average estimator, and a (marginal) propensity score weighted estimator. We show that any of our class of estimators is asymptotically normal. The three special estimators have the same asymptotic variance. They achieve the semiparametric…

误设独立同分布模型中的有效矩估计法AI 解读

The paper presents the asymptotic theory of the efficient method of moments when the model of interest is not correctly specified. The paper assumes a sequence of independent and identically distributed observations and a global misspecification. It is found that the limiting distribution of the estimator is still asymptotically normal, but it suffers a strong impact in the covariance matrix. A consistent estimator of this covariance matrix is provided. The large sample…

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评估美联储反应函数的广义矩估计AI 解读

Estimating a forward-looking monetary policy rule by the generalized method of moments (GMM) has become a popular approach. We reexamine estimates of the Federal Reserve reaction function using several GMM estimators and a maximum likelihood (ML) estimator. First, we show that over the baseline period 1979–2000, these alternative approaches yield substantially different parameter estimates. Using Monte Carlo simulations, we show that the finite-sample GMM bias can account…

基于经验似然的推断及其在若干计量模型中的应用AI 解读

This paper uses the concept of dual likelihood to develop some higher order asymptotic theory for the empirical likelihood ratio test for parameters defined implicitly by a set of estimating equations. The resulting theory is likelihood based in the sense that it relies on methods developed for ordinary parametric likelihood models to obtain valid Edgeworth expansions for the maximum dual likelihood estimator and for the dual/empirical likelihood ratio statistic. In…

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of firm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the…

GMM 与广义经验似然估计量的高阶性质AI 解读

In an effort to improve the small sample properties of generalized method of mo-ments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilt-ing estimators. We show that these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) estimators. We use this structure to compare their higher order asymptotic properties. We find…

一类非参数似然检验的二阶功效比较AI 解读

This paper compares the second‐order power properties of a broad class of nonparametric likelihood tests recently introduced by Baggerly (1998) as a generalisation of Owen's (1988) empirical likelihood. It is shown that in a multi‐parameter setting identity of power up to first order does not imply identity up to second order unless one considers the average power criterion. It is also shown that the empirical likelihood ratio enjoys an optimality property in terms of local…

条件矩限制的检验AI 解读

Let (x,z) be a pair of observable random vectors. We construct a new "smoothed" empirical likelihood-based test for the hypothesis $\E\{ g(z,\break \theta)|x \} = 0$ w.p.1, where g is a vector of known functions and $\theta$ an unknown finite-dimensional parameter. We show that the test statistic is asymptotically normal under the null hypothesis and derive its asymptotic distribution under a sequence of local alternatives. Furthermore, the test is shown to possess an…

替代终点研究中的信息回收AI 解读

Recently, there has been a lot of interest in statistical methods for analyzing data with surrogate endpoints. In this article, we consider parameter estimation from a model that relates a variable Y to a set of covariates, X, in the presence of a surrogate, S. We assume that the data are made up of two random samples from the population, a validation set where (Y, X, S) are observed on every subject and a nonvalidation set where only (X, S) are measured. We show how…

基于广义经验似然的矩条件模型选择准则AI 解读

This paper proposes model selection criteria (MSC) for unconditional moment models using generalized empirical likelihood (GEL) statistics. The use of GEL-statistics in lieu of J-statistics (in the spirit of Andrews, 1999, Econometrica 67, 543–564; and Andrews and Lu, 2001, Journal of Econometrics 101, 123–164) leads to an alternative interpretation of the MSCs that emphasizes the common information-theoretic rationale underlying model selection procedures for both…

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样本末端不稳定性检验AI 解读

This paper considers tests for structural instability of short duration, such as at the end of the sample. The key feature of the testing problem is that the number, m, of observations in the period of potential change is relatively small—possibly as small as one. The well-known F test of Chow (1960) for this problem only applies in a linear regression model with normally distributed iid errors and strictly exogenous regressors, even when the total number of observations,…

含未知函数的条件矩限制模型的有效估计AI 解读

(iii) the estimator for the asymptotic covariance of the 0 estimator is consistent and easy to compute; and (iv) the optimally weighted minimum distance estimator of 0 attains the semiparametric efficiency bound. We illustrate our results with two examples: a partially linear regression with an endogenous nonparametric part, and a partially additive IV regression with a link function.

指数随机游走的 Dickey–Fuller 检验AI 解读

A common test in econometrics is the Dickey–Fuller test, which is based on the test statistic . We investigate the behavior of the test statistic if the data yt are given by an exponential random walk exp(Zt) where Zt = Zt−1 + σεt and the εt are independent and identically distributed random variables. The test statistic DF(T) is a nonlinear transformation of the partial sums of εt process. Under certain moment conditions on the εt we show that tends to one as λ → 0. For the…

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