论文检索

提高模型设定检验的功效AI 解读

This paper shows how to increase the power of Hausman’s (1978) specification test as well as the difference test in a large class of models. The idea is to impose the restrictions of the null and the alternative hypotheses when estimating the covariance matrix. If the null hypothesis is true then the proposed test has the same distribution as the existing ones in large samples. If the hypothesis is false then the proposed test statistic is larger with probability approaching…

多工具变量与异方差下的过度识别限制检验AI 解读

This paper gives a test of overidentifying restrictions that is robust to many instruments and heteroskedasticity. It is based on a jackknife version of the overidentifying test statistic. Correct asymptotic critical values are derived for this statistic when the number of instruments grows large, at a rate up to the sample size. It is also shown that the test is valid when the number of instruments is fixed and there is homoskedasticity. This test improves on recently…

无需指定异质性分布的半参数持续时间模型估计AI 解读

This paper presents a new estimator for the mixed proportional hazard model that allows for a nonparametric baseline hazard and time-varying regressors. In particular, this paper allows for discrete measurement of the durations as happens often in practice. The integrated baseline hazard and all parameters are estimated at the regular rate, N, where N is the number of individuals. A hazard model is a natural framework for time-varying regressors. In particular, if a flow or…

异方差与多工具变量下的工具变量估计AI 解读

This paper gives a relatively simple, well behaved solution to the problem of many instruments in heteroskedastic data. Such settings are common in microeconometric applications where many instruments are used to improve efficiency and allowance for heteroskedasticity is generally important. The solution is a Fuller (1977) like estimator and standard errors that are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high…

多工具变量异方差回归中JIVE的渐近分布AI 解读

This paper derives the limiting distributions of alternative jackknife instrumental variables (JIV) estimators and gives formulas for accompanying consistent standard errors in the presence of heteroskedasticity and many instruments. The asymptotic framework includes the many instrument sequence of Bekker (1994, Econometrica 62, 657–681) and the many weak instrument sequence of Chao and Swanson (2005, Econometrica 73, 1673–1691). We show that JIV estimators are…

摘要暂缺

变换模型中的响应误差及其在收入方程估计中的应用AI 解读

This paper considers estimation of a transformation model in which the transformed dependent variable is subject to classical measurement error. We consider cases in which the transformation function is known and unspecified. In special cases (e.g. log and square-root transformations), least-squares or non-linear least-squares estimators are applicable. A flexible approximation approach (based on Taylor expansion) is proposed for a parametrized transformation function (like…

精确消费者剩余与无谓损失的非参数估计AI 解读

The authors apply nonparametric regression models to estimation of demand curves of the type most often used in applied research. From the demand curve estimators they derive estimates of exact consumers surplus and deadweight loss. The authors also develop tests of the symmetry and downward sloping properties of compensated demand. They work out asymptotic normal sampling theory for kernel and series nonparametric estimators as well as for the parametric case. The paper…

摘要暂缺

持续期与竞争风险模型的灵活参数估计AI 解读

Abstract In this paper we specify and estimate a flexible parametric proportional hazards model. The model specification is flexibly parametric in the sense that the baseline hazard is non parametric while the effect of the covariates takes a particular functional form. We also add parametric heterogeneity to the underlying hazard model specification. We specify a flexible parametric proportional competing risks model which permits unrestricted correlation among the risks.…

协方差约束下联立方程模型的有效估计与识别AI 解读

The authors consider estimation of simultaneous equations models with covariance restrictions. They consider FIML estimation and extend J. A. Hausman's instrumental variables interpretation of the FIML estim ator to the covariance restrictions case. A slight variation on the i nstrumental variables theme yields a simple, efficient alternative to FIML. The authors augment the original equation system by equations implied by the covariance restrictions, linearized around an…

摘要暂缺

面板数据中的变量测量误差AI 解读

Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in…

非线性预算集的计量经济学AI 解读

This article surveys the development of nonparametric models and methods for estimation of choice models with nonlinear budget sets.The discussion focuses on the budget set regression, that is, the conditional expectation of a choice variable given the budget set.Utility maximization in a nonparametric model with general heterogeneity reduces the curse of dimensionality in this regression.Empirical results using this regression are different from maximum likelihood and give…

变量测量误差与季节调整程序AI 解读

Seasonal adjustment procedures attempt to estimate the sample realizations of an unobservable economic time series in the presence of both seasonal and irregular factors. In this article, we consider a factor that has not been considered explicitly in previous treatments of seasonal adjustment: measurement error. Because of the sample design used in the Current Population Survey, measurement error will not be a white-noise process, but instead it will be characterized by…

带协方差约束的线性联立方程模型识别：工具变量解释AI 解读

This picture is greatly complicated when restrictions on the structural disturbance variances and covariances, (henceforth "covariance restrictions") are allowed.Koopmans Rubin, and Leipnik (1950) recognized the usefulness of such restrictions for identification and demonstrated their equivalence to bilinear restrictions on the coefficients.This work was pursued by Wegge (1965) j Rothenberg (1971), and especially Fisher (1963, 1965), surveyed in Fisher (19-66, Chapters 3 and…

面板数据与不可观测个体效应AI 解读

Abstract An important purpose in pooling time-series and cross-section data is to control for individual-specific unobservable effects which may be correlated with other explanatory variables, e.g. latent ability in measuring returns to schooling in earnings equations or managerial ability in measuring returns to scale in firm cost functions. Using instrumental variables and the time-invariant characteristics of the latent variable, we derive: 1. (1) a test for the presence…

摘要暂缺

定性选择的条件 Probit 模型：考虑相互依赖与异质偏好的离散决策AI 解读

Jerry A. Hausman, David A. Wise, A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences, Econometrica, Vol. 46, No. 2 (Mar., 1978), pp. 403-426

摘要暂缺

摘要暂缺

线性与若干非线性计量模型全信息估计量的工具变量方法AI 解读

FIML is shown to be an instrumental variables estimator where the instruments embody all the over-identifying a priori restrictions. FIML is compared to the two alternative estimators 3SLS and full information instrumental variables. 3SLS differs from FIML in not using all a priori restrictions in forming the instruments. The full information instrumental variables estimator when iterated to convergence yields the FIML estimate. For the case of nonlinearity in the parameters…