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非参数模型的工具变量估计AI 解读

In econometrics there are many occasions where knowledge of the structural relationship among dependent variables is required to answer questions of interest. This paper gives identification and estimation results for nonparametric conditional moment restrictions. We characterize identification of structural functions as completeness of certain conditional distributions, and give sufficient identification conditions for exponential families and discrete variables. We also…

不可分离模型中的识别AI 解读

Weak nonparametric restrictions are developed, sufficient to identify the values of derivatives of structural functions in which latent random variables are nonseparable. These derivatives can exhibit stochastic variation. In a microeconometric context this allows the impact of a policy intervention, as measured by the value of a structural derivative, to vary across people who are identical as measured by covariates. When the restrictions are satisfied quantiles of the…

非加性随机函数的非参数估计AI 解读

We present estimators for nonparametric functions that are nonadditive in unobservable random terms. The distributions of the unobservable random terms are assumed to be unknown. We show that when a nonadditive, nonparametric function is strictly monotone in an unobservable random term, and it satisfies some other properties that may be implied by economic theory, such as homogeneity of degree one or separability, the function and the distribution of the unobservable random…

位置数据不完善时局部互动模型的识别AI 解读

Abstract This paper considers the problem of estimating a local interaction model defined at the level of individual agents, in the absence of perfect information about agent locations in the relevant socio‐economic space. We consider two types of data limitations: one in which individual locations are measured with error, the other in which location information is correct but only up to some spatial region (e.g., census tracts or zip codes). Our results indicate that the…

高度分层研究中协变量缺失的似然方法AI 解读

Summary The paper considers canonical link generalized linear models with stratum-specific nuisance intercepts and missing covariate data. This family includes the conditional logistic regression model. Existing methods for this problem, each of which uses a conditioning argu- ment to eliminate the nuisance intercept, model either the missing covariate data or the missingness process. The paper compares these methods under a common likelihood framework. The semiparametric…

混合比例风险竞争风险模型的可识别性AI 解读

Summary We prove identification of dependent competing risks models in which each risk has a mixed proportional hazard specification with regressors, and the risks are dependent by way of the unobserved heterogeneity, or frailty, components. We show that the conditions for identification given by Heckman and Honoré can be relaxed. We extend the results to the case in which multiple spells are observed for each subject.

经典估计的 MCMC 方法AI 解读

This paper studies computationally and theoretically attractive estimators called the Laplace type estimators (LTE), which include means and quantiles of Quasi-posterior distributions defined as transformations of general (non-likelihood-based) statistical criterion functions, such as those in GMM, nonlinear IV, empirical likelihood, and minimum distance methods. The approach generates an alternative to classical extremum estimation and also falls outside the parametric…

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结构模型的条件似然比检验AI 解读

This paper develops a general method for constructing exactly similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reduced-form covariance matrix. These tests are shown to be similar under weak-instrument asymptotics when the reduced-form covariance matrix is estimated and the errors are non-normal. The conditional test based on the likelihood ratio statistic is particularly simple and has…

融资约束影响投资的随机前沿分析AI 解读

is shown that investment under financing constraints can be modeled as a one-sided deviation from a frictionless investment level, and that effects of financing constraints can be identified and quantified by imposing a distributional assumption on the effects. Panel data on Taiwanese manufacturing firms between 1989 and 1996 are used in the estimation. It is found that (1) some of the sorting criteria used in the literature do not have significant and monotonic…

失去可识别性时似然比检验的渐近理论AI 解读

This paper describes the large sample properties of the likelihood ratio test statistic (LRTS) when the parameters characterizing the true null distribution are not unique. It is well known that the classical asymptotic theory for the likelihood ratio test does not apply to such problems and the LRTS may not have the typical chi-squared type limiting distribution. This paper establishes a general quadratic approximation of the log-likelihood ratio function in a Hellinger…

不可识别模型与多层神经网络的似然比AI 解读

This paper discusses the behavior of the maximum likelihood estimator (MLE), in the case that the true parameter cannot be identified uniquely. Among many statistical models with unidentifiability, neural network models are the main concern of this paper. It is known in some models with unidentifiability that the asymptotics of the likelihood ratio of the MLE has an unusually larger order. Using the framework of locally conic models put forth by Dacunha-Castelle and Gassiat…

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多元自适应样条模型中线性方向的识别AI 解读

Identifying linear directions in multivariate regression has been a statistical challenge and has attracted particular attention since projection pursuit was developed. To this end, we propose and investigate the use of linear discriminant analysis and projection Hessian directions in conjunction with multivariate adaptive regression splines. Simulation studies in a variety of settings demonstrate the usefulness of our approach in revealing both the functional forms and the…

极端值簇的统计推断AI 解读

Summary Inference for clusters of extreme values of a time series typically requires the identification of independent clusters of exceedances over a high threshold. The choice of declustering scheme often has a significant effect on estimates of cluster characteristics. We propose an automatic declustering scheme that is justified by an asymptotic result for the times between threshold exceedances. The scheme relies on the extremal index, which we show may be estimated…

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半参数弱工具变量回归及其风险—收益权衡应用AI 解读

We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This framework is applicable to linear models with expectation variables that are estimated nonparametrically, such as the risk-return tradeoff in finance and the effect of inflation uncertainty on real economic activity. Our simulation evidence suggests that Lagrange multiplier…

一类家庭生产模型的识别与估计AI 解读

Abstract We consider a class of household production models characterized by a dichotomy property. In these models the amount of time spent on household production does not depend on the household utility function, conditional on household members having a paid job. We analyse the (non‐parametric) identifiability of the production function and the so‐called jointness function (a function describing which part of household production time is counted as pure leisure). It is…

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存在未识别参数时的结果增益预测分布AI 解读

distributions of outcome gains in the framework of a standard latent variable selection model. Although most previous work has focused on estimation of mean treatment parameters as the method for characterizing outcome gains from program participation, we show how the entire distributions associated with these gains can be obtained in certain situations. Although the out-of-sample outcome gain distributions depend on an unidentified parameter, we use the results of Koop and…

检测 GMM 中的识别不足AI 解读

This paper proposes a test of the null of underidentification in the nonlinear-in-parameters generalized method of moments model. It can be thought of as a nonlinear analog of the usual linear instrumental variables first-stage F-test. It can be used as a diagnostic to warn a researcher when conventional asymptotic theory is unlikely to work well.I am grateful to Don Andrews, Jon Faust, John Fernald, Jim Stock, and two anonymous referees for their helpful comments on earlier…

具有恰当时间依赖结构的模式混合模型AI 解读

Recently, pattern‐mixture modelling has become a popular tool for modelling incomplete longitudinal data. Such models are under‐identified in the sense that, for any drop‐out pattern, the data provide no direct information on the distribution of the unobserved outcomes, given the observed ones. One simple way of overcoming this problem, ordinary extrapolation of sufficiently simple pattern‐specific models, often produces rather unlikely descriptions; several authors consider…

多变量与空间极值的依赖度量：性质与推断AI 解读

We present properties of a dependence measure that arises in the study of extreme values in multivariate and spatial problems. For multivariate problems the dependence measure characterises dependence at the bivariate level, for all pairs and all higher orders up to and including the dimension of the variable. Necessary and sufficient conditions are given for subsets of dependence measures to be self‐consistent, that is to guarantee the existence of a distribution with such…

Fisher 信息为零时的置信区域AI 解读

We examine the asymptotic behaviour of confidence regions in identifiable one‐dimensional parametric models with smooth likelihood function and information equal to zero at a critical point of the parameter space. Confidence regions are based on inversion of the likelihood ratio test statistic and of some common forms of the score and Wald test statistics. For fixed parameter values other than the critical point, all these statistics have limiting x2(1) distributions, but…