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Model selection using J-test for the spatial autoregressive model vs. the matrix exponential spatial model

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  • Han, Xiaoyi
  • Lee, Lung-fei

Abstract

We consider using the J-test procedure for the non-nested model selection problem between the spatial autoregressive (SAR) model and the matrix exponential spatial specification (MESS) model. The 2SLS and GMM methods are used to implement the J-test procedure and derive several test statistics under the GMM framework. We investigate the behavior of those J-test statistics in terms of pseudo true values. We extend the J-test procedure into the setting when error terms in the model are with unknown heteroskedasticity. Monte Carlo results suggest with strong spatial dependence the J-test statistics can have good power to distinguish the SAR and MESS models.

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Bibliographic Info

Article provided by Elsevier in its journal Regional Science and Urban Economics.

Volume (Year): 43 (2013)
Issue (Month): 2 ()
Pages: 250-271

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Handle: RePEc:eee:regeco:v:43:y:2013:i:2:p:250-271

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Web page: http://www.elsevier.com/locate/regec

Related research

Keywords: Spatial autoregressive model; Matrix exponential spatial model; J-test; Pseudo true value; GMM;

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References

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Cited by:
  1. Han, Xiaoyi & Lee, Lung-fei, 2013. "Bayesian estimation and model selection for spatial Durbin error model with finite distributed lags," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 816-837.

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