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Factor residuals in SUR regressions: estimating panels allowing for cross sectional correlation

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This paper describes a method for estimating panels by imposing a factor structure on the residuals. The method allows SUR estimation of panel models by providing a full-rank estimator of the system covariance matrix when the usual estimate is rank-deficient. We charactersie completely the circumstances when this is possible. When the usual estimator is of full rank, our procedure provides a more parsimonious representation of the covariance matrix, which can lead to efficiency gains in finite samples. Monte Carlo analysis of convergence regressions and PPP regressions in the Heston-Summers data-set indicates that the proposed estimator has better performance in terms of RMSE and bias than standard panel or SUR estimators (where available), as well as offering unbiased inference.

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en

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application/pdf

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http://eprints.lse.ac.uk/20163/1/Factor_Residuals_in_SUR_Regressions_Estimating_Panels_Allowing_for_Cross_Sectional_Correlation.pdf

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