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Bootstrap Methods for Inference in the Parks Model

Mantobaye Moundigbaye, Clarisse Messemer, Richard W. Parks and W. Reed ()

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

Abstract: The Parks (1967) estimator is a workhorse for panel data and seemingly unrelated regression equation systems because it allows the incorporation of serial correlation together with heteroskedasticity and cross-sectional correlation. It is efficient both asymptotically and in small samples. Kmenta and Gilbert (1970) and more recently Beck and Katz (1995) note that estimated standard errors are biased downward, often severely. Instead of fixing the Parks standard errors, Beck and Katz abandon the efficient estimator in favor of a Prais-Winston estimator together with “panel corrected standard errors” (PCSE), a procedure that only partially reduces the standard error bias. In this paper we develop both parametric and nonparametric bootstrap approaches to inference that avoid the need to use biased standard errors. We then illustrate the effectiveness of our procedures using Monte Carlo experiments that show that the bootstrap gives rejection probabilities close to the nominal level chosen by the researcher.

Keywords: Parks model; SUR; panel data; cross-sectional correlation; bootstrap; Monte Carlo; simulation (search for similar items in EconPapers)
JEL-codes: F52 I31 Z13 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2016-10-22
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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https://repec.canterbury.ac.nz/cbt/econwp/1622.pdf (application/pdf)

Related works:
Journal Article: Bootstrap methods for inference in the Parks model (2020) Downloads
Working Paper: Bootstrap methods for inference in the Parks model (2019) Downloads
Working Paper: Bootstrap Methods for Inference in the Parks Model (2018) Downloads
Working Paper: Bootstrap Methods for Inference in the Parks Model (2017) Downloads
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