Bias-corrected estimation of panel vector autoregressions

Koen Jochmans and Geert Dhaene

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Abstract: We derive bias-corrected least-squares estimators of panel vector autoregressions with fixed effects. The correction is straightforward to implement and yields an estimator that is asymptotically unbiased under asymptotics where the number of time series observations grows at the same rate as the number of cross-sectional observations. This makes the estimator well suited for most macroeconomic data sets. Simulation results show that the estimator yields substantial improvements over within-group least-squares estimation. We illustrate the bias correction in a study of the relation between the unemployment rate and the economic growth rate at the U.S. state level.

Keywords: bias correction; fixed effects; panel data; vector autoregression (search for similar items in EconPapers)
Date: 2015-07-01
Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-01174330v2
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Related works:
Journal Article: Bias-corrected estimation of panel vector autoregressions (2016)
Working Paper: Bias-corrected estimation of panel vector autoregressions (2016)
Working Paper: Bias-corrected estimation of panel vector autoregressions (2016)
Working Paper: Bias-corrected estimation of panel vector autoregressions (2015)
Working Paper: Bias-corrected estimation of panel vector autoregressions (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:wpspec:hal-01174330

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