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条件矩限制模型中的内生变量缺失AI 解读

We estimate finite-dimensional parameters in conditional moment restriction (CMR) models when at least one of the endogenous variables (outcomes and/or explanatory variables) in the model is missing for some individuals in the sample. We demonstrate that efficiency gains in estimation occur if and only if there is at least one endogenous variable—included in or excluded from the CMR model—that is nonmissing (observed for all individuals in the sample), which we show…

面板数据似然中得分偏差与信息偏差的作用AI 解读

We show why reducing information bias can improve the performance of likelihood based estimators and confidence regions in small samples, and why it seems to matter more for inference than for estimation. The insights in this paper are helpful in explaining several simulation findings in the panel data literature. E.g., we can explain the well documented phenomenon that reducing the score bias alone often reduces the finite sample variance of estimators and improves the…

含未观测效应的非线性面板模型的积分似然推断AI 解读

We propose a new integrated likelihood based approach for estimating panel data models when the unobserved individual effects enter the model nonlinearly. Unlike existing integrated likelihoods in the literature, the one we propose is closer to a genuine likelihood. Although the statistical theory for the proposed estimator is developed in an asymptotic setting where the number of individuals and the number of time periods both approach infinity, results from a simulation…

对称修剪 Tobit 模型中条件对称性的简单一致检验AI 解读

We propose a “weighted and sample-size adjusted” Kolmogorov–Smirnov type statistic to test the assumption of conditional symmetry maintained in the symmetrically trimmed least-squares (STLS) approach of Powell (1986b), which is widely used to estimate censored or truncated regression models without making distributional assumptions. Our statistic is consistent and does not require any nonparametric smoothing, although we test the validity of a conditional feature. We also…

内生解释变量非参数回归模型中线性泛函估计的效率界AI 解读

Let Y=μ∗(X)+ε, where μ∗ is unknown and E[ε|X]≠0 with positive probability but there exist instrumental variables W such that E[ε|W]=0 w.p.1. It is well known that such nonparametric regression models are generally “ill-posed” in the sense that the map from the data to μ∗ is not continuous. In this paper, we derive the efficiency bounds for estimating certain linear functionals of μ∗ without assuming μ∗ itself to be identified.

总体分层份额已知时分层样本的 GMM 推断AI 解读

We show how to do efficient moment based inference using the generalized method of moments (GMM) when data is collected by stratified sampling and the maintained assumption is that the aggregate shares are known.

摘要暂缺

分层抽样数据的矩条件推断AI 解读

Many data sets used by economists and other social scientists are collected by stratified sampling. The sampling scheme used to collect the data induces a probability distribution on the observed sample that differs from the target or underlying distribution for which inference is to be made. If this effect is not taken into account, subsequent statistical inference can be seriously biased. This paper shows how to do efficient semiparametric inference in moment restriction…

删失与未删失数据集的最优组合AI 解读

We develop a simple semiparametric framework for combining censored and uncensored samples so that the resulting estimators are consistent, asymptotically normal, and use all information optimally. No nonparametric smoothing is required to implement our estimators. To illustrate our results in an empirical setting, we show how to estimate the effect of changes in compulsory schooling laws on age at first marriage, a variable that is censored for younger individuals. Results…

含内生解释变量的非参数线性模型中的若干识别问题AI 解读

In applied work economists often seek to relate a given response variable y to some causal parameter μ* associated with it. This parameter usually represents a summarization based on some explanatory variables of the distribution of y, such as a regression function, and treating it as a conditional expectation is central to its identification and estimation. However, the interpretation of μ* as a conditional expectation breaks down if some or all of the explanatory variables…

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…

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…

齐次函数的非参数估计AI 解读

Consider the regression , where and the exact functional form of f is unknown, although we do know that f is homogeneous of known degree r. Using a local linear approach, we examine two ways of nonparametrically estimating f: (i) a “direct” approach and (ii) a “projection based” approach. We show that depending upon the nature of the conditional variance , one approach may be asymptotically better than the other. Results of a small simulation experiment are presented to…

摘要暂缺

形状约束下的局部半参数效率界AI 解读

Consider the model y = x ′ β 0 + f * ( z ) + ε, where ε [d over =] N(0, σ 0 2 ). We calculate the smallest asymptotic variance that n 1/2 consistent regular ( n 1/2 CR) estimators of β 0 can have when the only information we possess about f * is that it has a certain shape. We focus on three particular cases: (i) when f * is homogeneous of degree r , (ii) when f * is concave, (iii) when f * is decreasing. Our results show that in the class of all n 1/2 CR estimators of β 0 ,…

《计量经济学方法》书评AI 解读

The fourth edition of Econometric Methods by Jack Johnston and John DiNardo, is a rewrite of the venerable third edition by Johnston that sustained several generations of economists. As stated by the authors themselves, the reason for undertaking this major revision is to provide a comprehensive and accessible account of currently available econometric methodology, and in my opinion they have been successful in achieving their objective. The book has 13 chapters and runs to…