What question did this study set out to answer?

To review the statistical properties, challenges, and political science applications of regression models structured simultaneously across space and time.

November 1, 1985American Journal of Political Science

Regression in Space and Time: A Statistical Essay

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To review the statistical properties, challenges, and political science applications of regression models structured simultaneously across space and time.
Evaluated four distinct estimators for pooled cross-sectional time-series data: ordinary least squares (OLS), least squares with dummy variables (LSDV), error components, and an adapted Box-Jenkins ARMA model.
Demonstrated estimator performance by analyzing regional dynamics of party issue polarization regarding racial desegregation in the U.S. House of Representatives.
Characterized the trade-offs and statistical complications inherent to pooled spatial-temporal estimation designs in empirical political research.
Showed that choice of estimator meaningfully impacts the modeled trajectories of regional party polarization on racial desegregation roll-call votes.

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Implication

Methodological review evaluates four pooled spatiotemporal estimators in U.S. House voting data, highlighting optimal statistical choices for political research.

Cite This Study

James A. Stimson (1985) studied this question.

synapsesocial.com/papers/6a0efdc3a14f152feafa1edd https://doi.org/10.2307/2111187

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Implication

Methodological review evaluates four pooled spatiotemporal estimators in U.S. House voting data, highlighting optimal statistical choices for political research.

Regression in Space and Time: A Statistical Essay

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Discussion

Implication

Cite This Study

Regression in Space and Time: A Statistical Essay

Key Points

Discussion

Implication

Cite This Study

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