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This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly focus on comparing two approaches of estimating unconditional mean of the coefficients for the correlated random coefficients models, the group mean estimator and the generalized...
Persistent link: https://www.econbiz.de/10012025649
Persistent link: https://www.econbiz.de/10014436187
This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly focus on comparing two approaches of estimating unconditional mean of the coefficients for the correlated random coefficients models, the group mean estimator and the generalized...
Persistent link: https://www.econbiz.de/10012696222
We explain the proliferation of panel data studies in terms of (i) data availability, (ii) the more heightened capacity for modeling the complexity of human behavior than a single cross-section or time series data can possibly allow, and (iii) challenging methodology. Advantages and issues of...
Persistent link: https://www.econbiz.de/10005170543
We explain the proliferation of panel data studies in terms of (i) data availability, (ii) the more heightened capacity for modeling the complexity of human behavior than a single cross-section or time series data can possibly allow, and (iii) challenging methodology. Advantages and issues of...
Persistent link: https://www.econbiz.de/10005342848
Persistent link: https://www.econbiz.de/10005345457
Persistent link: https://www.econbiz.de/10009526736
This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and...
Persistent link: https://www.econbiz.de/10009786715
Persistent link: https://www.econbiz.de/10010219724
Persistent link: https://www.econbiz.de/10009126880