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A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels
Chudik, Alexander - 2017
approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In this paper we … focus on the latter and consider both univariate and multivariate panel data models with short time dimension. Simple Bias …
Persistent link: https://www.econbiz.de/10012943386
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A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels
Chudik, Alexander - 2017
approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In this paper we … focus on the latter and consider both univariate and multivariate panel data models with short time dimension. Simple Bias …
Persistent link: https://www.econbiz.de/10012943450
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A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels
Chudik, Alexander - 2017
approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In this paper we … focus on the latter and consider both univariate and multivariate panel data models with short time dimension. Simple Bias …
Persistent link: https://www.econbiz.de/10012946881
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Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models
Harding, Matthew - 2018
This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and … the time series dimension of the panel is large. We present an application to the evaluation of Time-of-Use pricing using …
Persistent link: https://www.econbiz.de/10012908711
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Short T dynamic panel data models with individual, time and interactive effects
Hayakawa, Kazuhiko; Pesaran, M. Hashem; Smith, L. Vanessa - In: Journal of applied econometrics 38 (2023) 6, pp. 940-967
Persistent link: https://www.econbiz.de/10014432201
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Aggregation in Large Dynamic Panels
Pesaran, M. Hashem - 2011
This paper considers the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is...
Persistent link: https://www.econbiz.de/10013129942
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Weak and Strong Cross Section Dependence and Estimation of Large Panels
Chudik, Alexander - 2009
an application to the estimation of panel data models with an infinite number of weak factors and a finite number of …
Persistent link: https://www.econbiz.de/10013155822
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Weak and Strong Cross Section Dependence and Estimation of Large Panels
Chudik, Alexander - 2009
an application to the estimation of panel data models with an infinite number of weak factors and a finite number of …
Persistent link: https://www.econbiz.de/10013158328
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Forecasting with Panel Data : Estimation Uncertainty Versus Parameter Heterogeneity
Pesaran, M. Hashem; Pick, Andreas; Timmermann, Allan - 2022
We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with …-sectional (N) and time (T) dimensions and varying degrees of parameter heterogeneity. We investigate conditions under which panel …
Persistent link: https://www.econbiz.de/10013292495
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Revisiting the great ratios hypothesis
Chudik, Alexander; Pesaran, M. Hashem; Smith, Ron - 2022
Persistent link: https://www.econbiz.de/10013263388