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The three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian and Prucha (2007), which corrects for spatially correlated errors in static panel data models, is extended by introducing fixed effects, a spatial lag, and a one-period lag of the dependent variable as additional...
Persistent link: https://www.econbiz.de/10011144455
We extend the three-step generalized methods of moments (GMM) approach of Kapoor et al. (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory variables. Combining...
Persistent link: https://www.econbiz.de/10011124438
A major attraction of panel data is the ability to estimate dynamic models on an individual level. Moffitt (1993) and Collado (1998) have argued that such models can also be identified from repeated cross-section data. In this paper we reconsider this issue. We review the identification...
Persistent link: https://www.econbiz.de/10011090312
We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Prucha (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory...
Persistent link: https://www.econbiz.de/10011090432
Abstract: 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 imposing any parametric structure of the error terms, this paper proposes a smoothed spatial...
Persistent link: https://www.econbiz.de/10011092461
The use of large-dimensional factor models in forecasting has received much attention in the literature with the … model which is better suited for forecasting compared to the traditional principal components (PC) approach.We provide an … asymptotic analysis of the estimator and illustrate its merits empirically in a forecasting experiment based on US macroeconomic …
Persistent link: https://www.econbiz.de/10010851192
-sample forecasting regressions. The predictive power of the model stays high at longer horizons. The estimated factors are strongly …
Persistent link: https://www.econbiz.de/10010851257
variable selection and estimation in one step. We evaluate the forecasting accuracy of these estimators for a large set of …
Persistent link: https://www.econbiz.de/10010851261
Macroeconomic forecasting using factor models estimated by principal components has become a popular research topic … simply screen datasets prior to estimation and remove anomalous observations.We investigate whether forecasting performance … Carlo simulation studies. Finally, we apply our proposed estimator in a simulated real-time forecasting exercise to test its …
Persistent link: https://www.econbiz.de/10010851270
We address the issue of modelling and forecasting macroeconomic variables using medium and large datasets, by adopting …
Persistent link: https://www.econbiz.de/10010940885