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作者

来源

REGIONAL SCIENCE AND URBAN ECONOMICS,Vol.66,P.28-38

语言

英文

关键字

Panel data; Common factors; Spatial dependence; Serial correlation; Randomization test; PANEL-DATA MODELS; AUTOCORRELATION; ECONOMETRICS; INFERENCE; ASTERISK

作者单位

[Millo, Giovanni] Generali SpA, Grp Insurance Res, Via Machiavelli 3, I-34123 Trieste, Italy. [Millo, Giovanni] Univ Trieste, Dipartimento Sci Econ Aziendali Matemat & Stat DE, Piazzale Europa 1, I-34127 Trieste, Italy. Millo, G (reprint author), Generali SpA, Grp Insurance Res, Via Machiavelli 3, I-34123 Trieste, Italy. E-Mail: millogiovanni@gmail.com

摘要

A randomization test is proposed for detecting spatial dependence in panel models with cross-sectional dependence induced by an unobserved common factor structure. Spatial dependence is related to the position of observations in space while cross-sectional dependence is generally not; yet spatial correlation tests have power against both. Permuting the pairs of neighbouring observations in the proximity matrix yields a simple spatial dependence test which is robust to the presence of non-spatial cross-sectional correlation, serial correlation and can accommodate short and unbalanced panels. The proposed procedure is evaluated and compared to alternatives through Monte Carlo simulation; it is then illustrated by an application to recent research on technology spillovers. A user-friendly R implementation is provided.