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Bayesian model selection and prediction with empirical applications
贝叶斯模型选择与预测及其实证应用
This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the development of ‘Bayes models’ for time series and on the authors' model selection criterion ‘PIC’. The PIC criterion is used in this paper to determine the lag order, the trend degree and the presence or absence of a unit root in an autoregression with deterministic trend. A new forecast-encompassing test for Bayes models is developed which allows one Bayes model to be compared with…
A simple message for autocorrelation correctors: Don't
Do purchasing power parity and uncovered interest rate parity hold in the long run? An example of likelihood inference in a multivariate time-series model
Conditional and structural error correction models reply
Conditional and structural error correction models
Identifying restrictions of linear equations with applications to simultaneous equations and cointegration
The heteroskedastic linear regression model and the Hadamard product a note
Double bootstrap for shrinkage estimators
On a simultaneous equations pre-test estimator
Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models
Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study
分位数回归模型渐近协方差矩阵估计的蒙特卡洛研究
This Monte Carlo study examines several estimation procedures of the asymptotic covariance matrix in the quantile and censored quantile regression models: design matrix bootstrap, error bootstrapping, order statistic, sigma bootstrap, homoskedastic kernel, and heteroskedastic kernel. The Monte Carlo samples are drawn from two alternative data sets: (a) the unaltered Current Population Survey (CPS) for 1987 and (b) this CPS data with independence between error term and…
Econometric estimates of price indexes for personal computers in the 1990's
On bias, inconsistency, and efficiency of various estimators in dynamic panel data models
A new framework for analyzing survey forecasts using three-dimensional panel data
How representative are matched cross-sections? Evidence from the Current Population Survey
Testing AR(1) against MA(1) disturbances in an error component model
Selection corrections for panel data models under conditional mean independence assumptions
Estimating long-run relationships from dynamic heterogeneous panels
Another look at the instrumental variable estimation of error-components models
重新审视误差分量模型的工具变量估计
This article develops a framework for efficient IV estimators of random effects models with information in levels which can accommodate predetermined variables. Our formulation clarifies the relationship between the existing estimators and the role of transformation in panel data models. We characterise the valid transformations for relevant models and show the optimal estimators are invariant to the transformation used to remove individual effects. We present an alternative…
Efficient estimation of models for dynamic panel data
动态面板数据模型的有效率估计
In this paper we consider a dynamic model for panel data. We show that, under standard assumptions, there are more moment conditions than are currently exploited in the literature. Some of these are linear, but others are quadratic, so that nonlinear GMM is required. We also show that exogenous regressors generate a larger number of relevant moment conditions in a dynamic model than they would in a static model.