Another Look at what to do with Time-series Cross-section Data

Xiujian Chen, Shu Lin and W. Reed ()

Working Papers in Economics from University of Canterbury, Department of Economics and Finance

Abstract: Our study revisits Beck and Katz' (1995) comparison of the Parks and PCSE estimators using time-series, cross-sectional data (TSCS). Our innovation is that we construct simulated statistical environments that are designed to approximate actual TSCS data. We pattern our statistical environments after income and tax data on U.S. states from 1960-1999. While PCSE generally does a better job than Parks in estimating standard errors/confidence intervals, it too can be unreliable, sometimes producing standard errors/confidence intervals that are substantially off the mark. Further, we find that the benefits of PCSE can come at a large cost in estimator efficiency.

Keywords: Panel data, Parks model; PCSE estimator; Monte Carlo methods (search for similar items in EconPapers)
JEL-codes: C15 C23 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2006-03-31
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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https://repec.canterbury.ac.nz/cbt/econwp/0604.pdf (application/pdf)

Related works:
Working Paper: Another Look At What To Do With Time-Series Cross-Section Data (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:cbt:econwp:06/04

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