Modified harmonic mean method for spatial autoregressive models
Osman Doğan
Economics Letters, 2023, vol. 223, issue C
Abstract:
In this paper, I suggest using the modified harmonic mean method for estimating marginal likelihood functions of cross-sectional spatial autoregressive models. In a Bayesian estimation setting, I show how this method can be used for popular cross-sectional spatial autoregressive models. In a simulation study, I investigate the finite sample performance of this estimator along with some other popular information criteria for the nested and non-nested model selection problems. The simulation results show that the modified harmonic mean estimator performs satisfactorily, and can be useful for the specification search exercises in spatial econometrics.
Keywords: Marginal likelihood; Modified harmonic mean; SAR; AIC; DIC; BIC; Model selection (search for similar items in EconPapers)
JEL-codes: C11 C21 C22 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:223:y:2023:i:c:s0165176523000034
DOI: 10.1016/j.econlet.2023.110978
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