Maximum likelihood estimation of a spatial autoregressive Tobit model

@article{Xu2015MaximumLE,
  title={Maximum likelihood estimation of a spatial autoregressive Tobit model},
  author={X. Xu and Lung-fei Lee},
  journal={Journal of Econometrics},
  year={2015},
  volume={188},
  pages={264-280}
}
This paper examines a Tobit model with spatial autoregressive interactions. We consider the maximum likelihood estimation for this model and analyze asymptotic properties of the estimator based on the spatial near-epoch dependence of the dependent variable process generated from the model structure. We show that the maximum likelihood estimator is consistent and asymptotically normally distributed. Monte Carlo experiments are performed to verify finite sample properties of the estimator. 

Tables from this paper

LARGE SAMPLE PROPERTIES OF BAYESIAN ESTIMATION OF SPATIAL ECONOMETRIC MODELS
This paper studies asymptotic properties of a posterior probability density and Bayesian estimators of spatial econometric models in the classical statistical framework. We focus on the high-orderExpand
Estimation of Spatial Sample Selection Models: A Partial Maximum Likelihood Approach
To analyze data obtained by non-random sampling in the presence of cross-sectional dependence, estimation of a sample selection model with a spatial lag of a latent dependent variable or a spatialExpand
Distribution Free Estimation of Spatial Autoregressive Binary Choice Panel Data Models
This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects. The estimation procedure is based on theExpand
Semiparametric Estimation of Censored Spatial Autoregressive Models
This study considers the estimation of spatial autoregressive models with censored dependent variables, where the spatial autocorrelation exists within the uncensored latent dependent variables. TheExpand
SEMIPARAMETRIC ESTIMATION OF CENSORED SPATIAL AUTOREGRESSIVE MODELS
This study considers the estimation of spatial autoregressive models with censored dependent variables, where the spatial autocorrelation exists within the uncensored latent dependent variables. TheExpand
Sieve maximum likelihood estimation of the spatial autoregressive Tobit model
Abstract This paper extends the ML estimation of a spatial autoregressive Tobit model under normal disturbances in Xu and Lee (2015b, Journal of Econometrics) to distribution-free estimation. WeExpand
Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models
This paper considers spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects, where the latent dependent variables are spatially correlated. Without imposingExpand
Asymptotic properties of a spatial autoregressive stochastic frontier model
This paper considers asymptotic properties of a spatial autoregressive stochastic frontier model. Relying on the asymptotic theory for nonlinear spatial NED processes, we prove the consistency andExpand
Quantile regression for varying coefficient spatial error models
Abstract This paper investigates the quantile regression estimation for spatial error models with possibly varying coefficients. The local polynomial fitting scheme is employed to approximate theExpand
A likelihood ratio test for spatial model selection
Abstract This paper develops a nondegenerate likelihood-ratio test for model selection between two competitive spatial econometrics models. It generalizes the test of Vuong (1989) to models withExpand
...
1
2
3
4
...

References

SHOWING 1-10 OF 54 REFERENCES
A spatial autoregressive model with a nonlinear transformation of the dependent variable
This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximumExpand
A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model
This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literatureExpand
Bayesian Estimation of Limited Dependent Variable Spatial Autoregressive Models
A Gibbs sampling (Markov chain Monte Carlo) method for estimating spatial autoregressive limited dependent variable models is presented. The method can accommodate data sets containing spatialExpand
Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models
This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi-maximum likelihood estimator for the spatial autoregressive model. The rates of convergence of thoseExpand
Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models
This paper considers spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects, where the latent dependent variables are spatially correlated. Without imposingExpand
A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances
Cross-sectional spatial models frequently contain a spatial lag of the dependent variable as a regressor or a disturbance term that is spatially autoregressive. In this article we describe aExpand
GENERALIZED MAXIMUM ENTROPY ESTIMATION OF A FIRST ORDER SPATIAL AUTOREGRESSIVE MODEL
We formulate generalized maximum entropy estimators for the general linear model and the censored regression model when there is first order spatial autoregression in the dependent variable. MonteExpand
Estimating a spatial autoregressive model with an endogenous spatial weight matrix
The spatial autoregressive (SAR) model is a standard tool for analyzing data with spatial correlation. Conventional estimation methods rely on the key assumption that the spatial weight matrix isExpand
GMM and 2SLS estimation of mixed regressive, spatial autoregressive models
The GMM method and the classical 2SLS method are considered for the estimation of mixed regressive, spatial autoregressive models. These methods have computational advantage over the conventionalExpand
Estimation of Sample Selection Models with Spatial Dependence
We consider the estimation of sample selection (type II Tobit) models that exhibit spatial error dependence or spatial autoregressive errors (SAE). The method considered is motivated by a two-stepExpand
...
1
2
3
4
5
...