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This paper focuses on the estimation and predictive performance of several estimators for the time-space dynamic panel data model with Spatial Moving Average Random Effects (SMA-RE) structure of the disturbances. A dynamic spatial Generalized Moments (GM) estimator is proposed which combines the...
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Chamberlain (1982) showed that the fixed effects (FE) specification imposes testable restrictions on the coefficients from regressions of all leads and lags of dependent variableson all leads and lags of independent variables. Angrist and Newey (1991) suggested computing this test statistic as...
Persistent link: https://www.econbiz.de/10005808255
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This paper focuses on the estimation and predictive performance of several estimators for the dynamic and autoregressive spatial lag panel data model with spatially correlated disturbances. In the spirit of Arellano and Bond (1991) and Mutl (2006), a dynamic spatial GMM estimator is proposed...
Persistent link: https://www.econbiz.de/10009359517
This paper checks the sensitivity of two adaptive heteroskedastic estimators suggested by Li and Stengos (1994) and Roy (2002) for an error component regression model to misspecification of the form of heteroskedasticity. In particular, we run Monte Carlo experiments using the heteroskedasticity...
Persistent link: https://www.econbiz.de/10009228484
This paper sets up a nested random effects spatial autoregressive panel data model to explain annual house price variation for 2000-2007 across 353 local authority districts in England. The estimation problem posed is how to allow for the endogeneity of the spatial lag variable producing the...
Persistent link: https://www.econbiz.de/10010751563
This paper sets up a nested random effects spatial autoregressive panel data model to explain annual house price variation for 2000–2007 across 353 local authority districts in England. The estimation problem posed is how to allow for the endogeneity of the spatial lag variable producing the...
Persistent link: https://www.econbiz.de/10010753559
This paper focuses on the estimation and predictive performance of several estimators for the dynamic and autoregressive spatial lag panel data model with spatially correlated disturbances. In the spirit of Arellano and Bond (1991) and Mutl (2006), a dynamic spatial GMM estimator is proposed...
Persistent link: https://www.econbiz.de/10011125930