Which panel data estimator should I use?

By W. R. Reed, Haichun Ye. 2011

413 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ac81662ae20a09f74ba4b753383b6b9ca6d8474a

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In Economics and Econometrics

Citations in the corpus

Does Export product diversification help to reduce energy demand: Exploring the contextual evidences from the newly industrialized countries (2021, methodology): “Second, the FGLS estimator is considered as most reliable in panel data when time period is more than number of entities (T>N) (Reed and Ye, 2011; Zhang and Nian, 2013).”
Public policy influence on renewable energy investments—A panel data study across OECD countries (2015, methodology): “Following Marques and Fuinhas (2012a) and to mitigate errors resulting from the data structure, we use several econometric treatments: heteroskedasticity, panel autocorrelation, and contemporaneous correlation are addressed through fitting approaches (Reed and Ye, 2011).”
Determinants of Renewable Energy Growth: A Global Sample Analysis (2014, methodology): “One of the complications of the method is that it can only be utilised when T is greater than or equal to the number of N (see Beck and Katz, 1995; Reed and Ye, 2009).”
Are government policies effective in promoting deployment of renewable electricity resources (2011, neutral): “10 See Beck and Katz (1995), Beck (2001), and Reed and Ye (2011) for reasons why PCSE is preferable over Feasible Generalized Least Squares (FGLS) (Parks, 1967) for the task at hand. government green power purchasing agreement or to set voluntary goals for generation.”
Did New Public Management Matter? An empirical analysis of the outsourcing and decentralization effects on public sector size (2015, background): “The reason is FGLS can prove inaccurate when estimating confidence intervals, whereas PCSE standard errors are more conservative and reliable (Beck and Katz 1995; Reed and Ye 2011).”