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Below results based on the criteria 'between estimator'
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Problems with and Solutions for Two-dimensional Models of Continuous Dependent Variables
This paper addresses hierarchical models with continuous dependent variables, such as time-series-cross-section models. Building on the argument in Zorn (2001), the main point of this paper is that the pooled OLS estimator is deeply flawed – especially for time-series-cross-section data – but for reasons that have not explicitly been raised in previous papers. The pooled OLS estimator, the within-estimator, the between-estimator, and the random effects estimator can be seen as special cases of the fractionally pooled estimator presented in Bartels (1996), which allows all of these estimators to be evaluated in a common framework. Taking bias and efficiency into account, using both the within-estimator and the between-estimator is likely to be the best estimation strategy for the vast majority of applications in political science.