Refinements in maximum likelihood inference on spatial autocorrelation in panel data

Peter M. Robinson and Francesca Rossi ()

Journal of Econometrics, 2015, vol. 189, issue 2, 447-456

Abstract: In a panel data model with fixed effects, possible cross-sectional dependence is investigated in a spatial autoregressive setting. An Edgeworth expansion is developed for the maximum likelihood estimate of the spatial correlation coefficient. The expansion is used to develop more accurate interval estimates for the coefficient, and tests for cross-sectional independence that have better size properties, than corresponding rules of statistical inference based on first order asymptotic theory. Comparisons of finite sample performance are carried out using Monte Carlo simulations.

Keywords: Panel data; Fixed effects; Spatial autoregression; Edgeworth expansion; Interval estimates; Tests for cross-sectional independence (search for similar items in EconPapers)
JEL-codes: C12 C21 C31 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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Working Paper: Refinements in maximum likelihood inference on spatial autocorrelation in panel data (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:189:y:2015:i:2:p:447-456

DOI: 10.1016/j.jeconom.2015.03.036

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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