On the Fixed-Effects Vector Decomposition

By T. Breusch, Michael B. Ward, H. Nguyen, Tom Kompas. Political Analysis, 2011

119 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/604161ac59116cf79d5183718ae83afb4e4df340

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In Economics and Econometrics

Citations in the corpus

Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data* (2014, methodology): “The FE vector decomposition (FEVD) estimator has been criticized by many in econometrics, who argue that the standard errors are likely to be incorrectly estimated (Breusch et al. 2011a, 2011b; Greene 2011a, 2011b, 2012).”
Board diversity and firm performance: evidence from the U.K. SMEs (2017, methodology): “Plümper and Troeger (2007) (FEVD) technique was criticized by Breusch et al. (2011) and William (2011) for not accounting for the presence of a group effect when providing the sample properties of the Monte Carlo simulation and the higher level of risk of the decomposition estimator compared with…”
Modeling international trends in energy efficiency (2012, background): “These approaches can also be combined (Breusch et al., 2011), though I do not consider such estimators here.”
Fixed-Effects Vector Decomposition: Properties, Reliability, and Instruments (2011, background): “9BWNK almost correctly state: ‘‘For all cases where endogeneity is absent (or is mild), FEVD will be the most efficient estimator’’ (Breusch et al. 2011).”
Estimation of linear dynamic panel data models with time‐invariant regressors (2019, unknown): “In a recent symposium on the FEVD method, Breusch et al. (2011) and Greene (2011) show that the first two stages can be characterized by an instrumental variable estimation with a particular choice of 1 ing instrumental variables in the spirit of Hausman and Taylor (1981), and adjust the…”