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Paper

Testing the Pooling Assumption with Cross-Sectional Time Series Data: A Proposal and an Assesment with Simulation Experiments Stanig, Piero Uploaded 07-17-2005 Keywords Cross-Sectional Time Series Data heterogeneity of coefficients Abstract I propose to use the loss of fit of the cross-validated predictions relative to the fit of the predictions from a pooled regression to test the assumption of constant betas across countries in a CSTS setting. The performance of this measure is a) evaluated in several simulation experiments that reproduce research situations common in comparative politics, and b) compared to the “cross-validated standard error of the regression”, proposed by Franzese(2002). I show that the measure I propose depends much less on the stochastic component in the DGP, and is better able to detect the country-specificity of the betas. I calculate the critical values that can be used to test the pooling assumption in some typical comparative politics CSTS situations. Finally, to evaluate the behavior of the measure with an actual dataset, I replicate the results of Alvarez et al. (1991) as replicated in Beck et al. (1993), calculate the proposed measure, and show that the pooling assumption does not seem to be inappropriate for the model they estimate.