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Some generalizations on the algebra of I(1) processes
Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models
Seemingly unrelated regressions under additive heteroscedasticity
Nonnested testing for autocorrelation in the linear regression model
Bayes regression with autoregressive errors
A simple multiple variance ratio test
Some efficiency bounds for semiparametric discrete choice models
Semiparametric quasilikelihood and variance function estimation in measurement error models
Efficiency bounds for some semiparametric selection models
若干半参数选择模型的效率界
In this paper, we calculate semiparametric efficiency bounds for the regression coefficients in an 'outcome' equation subject to censoring under weak conditions on the form of the selectivity bias. It is assumed that the regression function for the binary selection variable which governs the censoring mechanism is nonparametric, as is the form of the selection correction term in the outcome equation. Our results extend those of Chamberlain (1986), who considered models with…
Semiparametric estimation of a work-trip mode choice model
How sensitive are average derivatives?
Nonparametric and semiparametric approaches to discrete response analysis
Nonparametric bootstrap confidence intervals for discrete regression functions
On the computation of semiparametric estimates in limited dependent variable models
Nonparametric identification and estimation of polychotomous choice models
多类别选择模型的非参数识别与估计
In this paper we provide conditions guaranteeing the identification of nonparametric polychotomous choice models. In these models, neither the subutility function of observable attributes nor the distribution of the unobservable random terms is specified parametrically. Sets of nonparametric functions that possess properties that are often implied by economic theory and satisfy the restrictions required to identify the models are described. We use the identification results…
Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
单指标模型的半参数最小二乘与加权估计
For the class of single-index models, I construct a semiparametric estimator of coefficients up to a multiplicative constant that exhibits 1 √n-consistency and asymptotic normality. This class of models includes censored and truncated Tobit models, binary choice models, and duration models with unobserved individual heterogeneity and random censoring. I also investigate a weighting scheme that achieves the semiparametric efficiency bound.