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Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity

含不可观测异质性的动态非线性面板模型:初始条件问题的简便解法

Abstract I study a simple, widely applicable approach to handling the initial conditions problem in dynamic, nonlinear unobserved effects models. Rather than attempting to obtain the joint distribution of all outcomes of the endogenous variables, I propose finding the distribution conditional on the initial value (and the observed history of strictly exogenous explanatory variables). The approach is flexible, and results in simple estimation strategies for at least three…

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SEMIPARAMETRIC ESTIMATION OF PARTIALLY LINEAR MODELS FOR DEPENDENT DATA WITH GENERATED REGRESSORS

含生成解释变量的依赖数据部分线性模型半参数估计

In this paper we consider the problem of estimating a semiparametric partially linear model for dependent data with generated regressors. This type of model comes naturally from various econometric models such as a semiparametric rational expectation model when the surprise term enters the model nonparametrically, or a semiparametric type-3 Tobit model when the error distributions are of unknown forms, or a semiparametric error correction model. Using the nonparametric…

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ASYMPTOTIC PROPERTIES OF WEIGHTED M -ESTIMATORS FOR STANDARD STRATIFIED SAMPLES

标准分层样本下加权 M 估计量的渐近性质

I provide a systematic treatment of the asymptotic properties of weighted M -estimators under standard stratified sampling. Simple, consistent asymptotic variance matrix estimators are proposed for a broad class of problems. When stratification is based on exogenous variables, I show that the usual, unweighted M -estimator is more efficient than the weighted estimator under a generalized conditional information matrix equality. Hausman tests for the exogeneity of the…

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Asymptotic Properties of Weighted M-estimators for variable probability samples

不等概率样本中加权 M 估计量的渐近性质

I provide a systematic treatment of the asymptotic properties of weighted M-estimators under variable probability stratified sampling. The characterization of the sampling scheme and representation of the objective function allow for a straightforward analysis. Simple, consistent asymptotic variance matrix estimators are proposed. When stratification is based on exogenous variables, I show that the unweighted M-estimator is more efficient than the weighted estimator under a…

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Multiplicative Panel Data Models Without the Strict Exogeneity Assumption

不要求严格外生性的乘法面板数据模型

This paper considers estimation of multiplicative, unobserved components panel data models without imposing a strict exogeneity assumption on the conditioning variables. The method of moments estimators proposed have significant robustness properties. They require only a conditional mean assumption and apply to models with lagged dependent variables and to finite distributed lag models with arbitrary feedback from the explained to future values of the explanatory variables.…

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Econometric methods for fractional response variables with an application to 401(k) plan participation rates

分数响应变量的计量方法及其在 401(k) 计划参与率中的应用

We develop attractive functional forms and simple quasi-likelihood estimation methods for regression models with a fractional dependent variable. Compared with log-odds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need to use ad hoc transformations to handle data at the extreme values of zero and one. We also offer some new, robust specification tests by nesting the logit or probit function in a…

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On the Limits of Glm for Specification Testing: A Comment on Gurmu and Trivedi

GLM 用于设定检验的局限:对 Gurmu 与 Trivedi 的评论

In this comment on Gurmu and Trivedi's “Variable Augmentation Specification Tests in the Linear Exponential Family,” I show how their generalized linear model (GLM) approach relates to other work in econometrics on specification testing in the linear exponential family. In addition to shedding light on the relationship between the statistics and econometrics literatures on testing in quasi-likelihood frameworks, this comparison reveals some important limitations of GLM as a…

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A Simple Specification Test for the Predictive Ability of Transformation Models

变换模型预测能力的简单规格检验

A specification test is proposed to test the adequacy of the implicit conditional mean specification in a transformation model. Regardless of the transformation under the null, the statistic is computable from ordinary least squares output via auxiliary ordinary least squares regressions. Further, the test presumes no particular form for the conditional variance of the transformed and untransformed regressands. A simple goodness-of-fit measure that can be used to compare…

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A Test for Functional Form Against Nonparametric Alternatives

针对非参数备择的函数形式检验

A test for neglected nonlinearities in regression models is proposed. The test is of the Davidson-MacKinnon type against an increasingly rich set of non-nested alternatives, and is based on sieve estimation of the alternative model. For the case of a linear parametric model, the test statistic is shown to be asymptotically standard normal under the null, while rejecting with probability going to one if the linear model is misspecified. A small simulation study suggests that…

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A Unified Approach to Robust, Regression-Based Specification Tests

稳健回归型模型设定检验的统一方法

This paper develops a general approach to robust, regression-based specification tests for (possibly) dynamic econometric models. A useful feature of the proposed tests is that, in addition to estimation under the null hypothesis, computation requires only a matrix linear least-squares regression and then an ordinary least-squares regression similar to those employed in popular nonrobust tests. For the leading cases of conditional mean and/or conditional variance tests, the…

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