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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 … forecasting methods can perform better than forecasts based on individual estimates and demonstrate how gains in predictive … stock returns, we show that no single forecasting approach dominates uniformly. However, forecast combination and shrinkage …
Persistent link: https://www.econbiz.de/10013176894
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An exponential class of dynamic binary choice panel data models with fixed effects
Al-Sadoon, Majid M.; Li, Tong; Pesaran, M. Hashem - 2012
This paper develops a model for dynamic binary choice panel data that allows for unobserved heterogeneity to be arbitrarily correlated with covariates. The model is of the exponential type. We derive moment conditions that enable us to eliminate the unobserved heterogeneity term and at the same...
Persistent link: https://www.econbiz.de/10010291517
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Robust standard errors in transformed likelihood estimation of dynamic panel data models
Hayakawa, Kazuhiko; Pesaran, M. Hashem - 2012
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10009570680
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Robust standard errors in transformed likelihood estimation of dynamic panel data models
Hayakawa, Kazuhiko; Pesaran, M. Hashem - 2012
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10009545313
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To pool or not to pool : revisited
Pesaran, M. Hashem; Zhou, Qiankun - 2015
This paper provides a new comparative analysis of pooled least squares and fixed effects estimators of the slope coefficients in the case of panel data models when the time dimension (T) is fixed while the cross section dimension (N) is allowed to increase without bounds. The individual effects...
Persistent link: https://www.econbiz.de/10011283819
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Quasi maximum likelihood estimation of spatial models with heterogeneous coefficients
Aquaro, Michele; Bailey, Natalia; Pesaran, M. Hashem - 2015
This paper considers spatial autoregressive panel data models and extends their analysis to the case where the spatial coefficients differ across the spatial units. It derives conditions under which the spatial coefficients are identified and develops a quasi maximum likelihood (QML) estimation...
Persistent link: https://www.econbiz.de/10011288787
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Transformed maximum likelihood estimation of short dynamic panel data models with interactive effects
Hayakawa, Kazuhiko; Pesaran, M. Hashem; Smith, L. Vanessa - 2014
This paper proposes the transformed maximum likelihood estimator for short dynamic panel data models with interactive fixed effects, and provides an extension of Hsiao et al. (2002) that allows for a multifactor error structure. This is an important extension since it retains the advantages of...
Persistent link: https://www.econbiz.de/10010358963
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Estimation of time-invariant effects in static panel data models
Pesaran, M. Hashem; Zhou, Qiankun - 2014
This paper proposes the Fixed Effects Filtered (FEF) and Fixed Effects Filtered instrumental variable (FEF-IV) estimators for estimation and inference in the case of time-invariant effects in static panel data models when N is large and T is fixed. It is shown that the FEF and FEF-IV estimators...
Persistent link: https://www.econbiz.de/10010412873
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An exponential class of dynamic binary choice panel data models with fixed effects
Sadoon, Majid M. al-; Li, Tong; Pesaran, M. Hashem - 2012
This paper develops a model for dynamic binary choice panel data that allows for unobserved heterogeneity to be arbitrarily correlated with covariates. The model is of the exponential type. We derive moment conditions that enable us to eliminate the unobserved heterogeneity term and at the same...
Persistent link: https://www.econbiz.de/10009687207
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An exponential class of dynamic binary choice panel data models with fixed effects
Al-Sadoon, Majid M.; Li, Tong; Pesaran, M. Hashem - 2012
This paper develops a model for dynamic binary choice panel data that allows for unobserved heterogeneity to be arbitrarily correlated with covariates. The model is of the exponential type. We derive moment conditions that enable us to eliminate the unobserved heterogeneity term and at the same...
Persistent link: https://www.econbiz.de/10009680993