Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices

Anil K. Bera, Osman Doǧan*, Süleyman Taşplnar

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Makalebilirkişi

2 Atıf (Scopus)

Özet

In this study, we propose simple test statistics for identifying the source of spatial dependence in spatial autoregressive models with endogenous weights matrices. Elements of the weights matrices are modelled in such a way that endogenity arises when the unobserved factors that affect elements of the weights matrices are correlated with the unobserved factors in the outcome equation. The proposed test statistics are robust to the presence of endogeneity in the weights and can be used to detect spatial dependence in the dependent variable and/or the disturbance terms. The robust test statistics are easy to calculate as computationally simple estimations are needed for their calculations. Our Monte Carlo results indicate that these tests have good size and power properties in finite samples. We also provide an empirical illustration to demonstrate the usefulness of the robust tests in identifying the source of spatial dependence.

Orijinal dilİngilizce
Makale numarası20170015
DergiJournal of Econometric Methods
Hacim8
Basın numarası1
DOI'lar
Yayın durumuYayınlandı - 1 Oca 2020
Harici olarak yayınlandıEvet

Bibliyografik not

Publisher Copyright:
© 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.

Finansman

This research was supported, in part, by a grant of computer time from the City University of New York High Performance Computing Center under NSF Grants CNS-0855217 and CNS-0958379.

FinansörlerFinansör numarası
City University of New York High Performance Computing Center
National Science FoundationCNS-0958379, CNS-0855217

    Parmak izi

    Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

    Alıntı Yap