What to do (and not to do) with Time-Series Cross-Section Data
Опубликовано на портале: 31-03-2004
American Political Science Review.
1995.
Vol. 89.
No. 3.
P. 634-647.
Тематический раздел:
We examine some issues in the estimation of time-series cross-section models, calling
into question the conclusions of many published studies, particularly in the field
of comparative political economy. We show that the generalized least squares approach
of Parks produces standard errors that lead to extreme overconfidence, often underestimating
variability by 50% or more. We also provide an alternative estimator of the standard
errors that is correct when the error structures show complications found in this
type of model. Monte Carlo analysis shows that these "panel-corrected standard errors"
perform well. The utility of our approach is demonstrated via a reanalysis of one
"social democratic corporatist" model.
Ссылки
текст статьи в формате pdf на сайте JSTORE: http://links.jstor.org/sici?sici=0003-0554%28199509%2989%3A3%3C634%3AWTD%28NT%3E2.0.CO%3B2-U
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Ключевые слова
cross-sectional analyses time series двумерная вертикальная модель метод Монте-Карло политическая экономия
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