This paper derives several Lagrange Multiplier tests for the panel data regression model wih spatial error correlation. These tests draw upon two strands of earlier work. The Þrst is the LM tests for the spatial error correlation model discussed in Anselin (1988, 1999) and Anselin, Bera, Florax and Yoon (1996), and the second is the LM tests for the error component panel data model discussed in...

Due to criticisms of potential identification issues within spatial panel data models, this study contributes to the literature by comparing forecasts of U.S. state-level carbon dioxide emissions against empirical reality using panel data models with and without spatial effects. From a policy standpoint, understanding how to predict emissions is important for designing climate change mitigation...

This paper examines the asymptotics of the QMLE for unit root spatial dynamic panel data models with …xed e¤ects. When the exogenous variables or …xed e¤ects are included in the DGP, the estimate for the dynamic coe¢ cient is p nT 3 consistent and the estimates of other parameters are p nT consistent, and all of them are asymptotically normal. Also, sum of the contemporaneous spatial e¤ect and ...

We propose quasi maximum likelihood (QML) estimation of dynamic panel models with spatial errors when the cross-sectional dimension n is large and the time dimension T is fixed. We consider both the random effects and fixed effects models and derive the limiting distributions of the QML estimators under different assumptions on the initial observations. We propose a residual-based bootstrap met...

Abstract The paper applies synthetic instruments, initially developed for cross-sectional regression, to estimate dynamic spatial panel data models. These have two main advantages. First, instruments correlated with endogenous variables and yet independent of the errors are difficult find. Not only normally exogenous, but they usually strongly variables, thus help avoid problem weak instruments...