In this paper I propose a computationally practical simulation estimator for large categories of the dynamic panel Tobit model with complicated dependence structures. I first apply the sequential decomposition methods introduced by Hendry and Richard (1992) to obtain the tractable simulated log-likelihood function of the dynamic panel Tobit model. I then maximize this log-likelihood function si...

Most time series observed in practice exhibit time-varying trend (first-order) and autocovariance (second-order) behaviour. Differencing is a commonly-used technique to remove the such series, order estimate second-order structure (of differenced series). However, often we require inference on behaviour of original for example, when performing estimation. In this article, propose method, using ...

A Moment Ratio Estimator is proposed for the parameters of an Autoregressive (AR) model of the error in an Ordinary Least Squares (OLS) linear regression. Although it is computed from the conventional residual autocorrelation coefficients, it greatly reduces their bias, and provides corrected standard errors with far less bias and confidence intervals with far less size distortion than conventi...

In this paper, we propose improved IV/GMM estimators for panel vector autoregressive models by extending Hayakawa (2009) where an alternative form of instruments is suggested. We show that the proposed IV estimator has the same asymptotic distribution as the bias corrected maximum likelihood estimator by Hahn and Kuersteiner (2002). Since the proposed estimator is simply change the form of inst...

Non-spherical errors, namely heteroscedasticity, serial correlation and crosssectional correlation are commonly present within panel data sets. These can cause significant problems for econometric analyses. The FGLS(Parks) estimator has been demonstrated to produce considerable efficiency gains in these settings. However, it suffers from underestimation of coefficient standard errors, oftentime...

The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees-of-freedom adjustment), applied to the fixed-effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than 2) as the number of entities n increases. We provide a bias-adjusted HR estim...

We consider the problem of estimating a varying coe cient panel data model with xed effects using a local linear regression approach. Our proposed estimator can consistently estimate the regression model with an additive intercept term, while the conventional estimation method based on a rst di erence model fails to do so. The computed estimator is shown to be asymptotically normally distribute...

This paper considers nonparametric estimation of panel data models using local linear least squares when fixed effects present. The local marginal effect is of the main interest. A withingroup type nonparametric estimator is developed, where the fixed effects are eliminated by subtracting individual specific locally weighted time average (i.e., using the local within transformation). It is show...

In this paper, we study the asymptotic distributions for least-squares (OLS), fully modi ed (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic distribution of the OLS estimator is shown to have a non-zero mean. Monte Carlo results examine the s...