Longitudinal and Panel Data

By Edward W. Frees. 2004

384 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fa23c195b5ac15e571d386f37da3afe912d42f88

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In Economics and Econometrics

Citations in the corpus

Testing for Cross-Sectional Dependence in Panel-Data Models (2006, background): “Frees (1995, 2004) proposed a statistic that is not subject to this drawback.7 In particular, the statistic is based on the sum of the squared rank correlation coefficients and equals R2ave = 2 N (N − 1) N−1∑ i=1 N∑ j=i+1 r̂2ij As shown by Frees, a function of this statistic follows a joint…”
Explaining Deindustrialization: How Affluence, Productivity Growth, and Globalization Diminish Manufacturing Employment1 (2009, methodology): “The fixed-effects (FE) and random-effects (RE) models are two commonly used statistical procedures for dealing with heterogeneity bias (see Frees 2004; Baltagi 2005).5 However, for three reasons, the FE model seems better suited to the purposes of this study.”
Multivariate Frequency-Severity Regression Models in Insurance (2016, background): “This special case of multivariate analysis is known as “panel data”, see, for example, [5].”
Determinants of International Migration Flows to and from Industrialized Countries: A Panel Data Approach beyond Gravity 1 (2010, background): “Heteroscedasticity does not necessarily cause bias in the estimated coefficients, but may misleadingly deflate estimates of standard errors and, consequently, may exaggerate statistical significance (Frees, 2004).”
Multilevel Modeling with Correlated Effects (2007, methodology): “If any variable in a model suffers from one of these problems, all regression coefficients and variance component estimates in the model may be biased (Hayashi, 2000; Wooldridge, 2002; Frees, 2004).”