Analysis of panel data, 2nd edition

By David C. Ribar. 2004

734 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f88ff235e8cc9112b7c7d542c7ff17d65dda8084

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Citations in the corpus

Government Programs Can Improve Local Labor Markets: Evidence from State Enterprise Zones, Federal Empowerment Zones and Federal Enterprise Communities (2010, unknown): “As is well known from the random coefficients literature (e.g. Hsiao 2003), coefficients measuring national and state average effects have well defined interpretations that are clearly different.22 However they are also likely to be estimated with different degrees of precision.”
Panel Data Models with Grouped Factor Structure Under Unknown Group Membership (2013, unknown): “The procedure enriches the toolbox for panel data analysis, which has been widely used by researchers, as is evidenced by the popularity of the monographs and textbooks of Arellano (2003), Baltagi (2008), Hsiao (2003), and Wooldridge (2010).”
Willingness to pay for energy-saving measures in residential buildings (2007, background): “7 See Hsiao (1986) and Greene (2003) for more details about the fixed-effects logit model and Ferrer-i-Carbonell and Frijters (2004) for an application.”
US trade and exchange rate volatility: a real sectoral bilateral analysis (2008, methodology): “A Hausman approach, different from the earlier test of parameter heterogeneity, can be used to examine the equivalence of fixed and random-effects estimation and hence whether unobserved factors are correlated with the regressors, see Hsiao (2003). This can shed light on the suggestion by Clark et a”
Theory and methods of panel data models with interactive effects (2014, background): “Most of panel data analysis assumes cross-sectional independence; see, for example, [6, 13] and [18].”