IV estimation of spatial dynamic panels with interactive effects: large sample theory and an application on bank attitude towards risk

Guowei Cui, Vasilis Sarafidis and Takashi Yamagata

The Econometrics Journal, 2023, vol. 26, issue 2, 124-146

Abstract: SummaryThis paper develops a new instrumental variables estimator for spatial, dynamic panels with interactive effects under large N and T asymptotics. For this class of models, most approaches available in the literature are based on quasi-maximum likelihood estimation. The approach put forward here is appealing from both a theoretical and a practical point of view for a number of reasons. First, it is linear in the parameters of interest and computationally inexpensive. Second, the IV estimator is free from asymptotic bias. Third, the approach can accommodate endogenous regressors as long as external instruments are available. The IV estimator is consistent and asymptotically normal as $N,T\rightarrow \infty$, such that $N/T \rightarrow c$, where $0\lt c\lt \infty$. We study the determinants of risk attitude of banking institutions. The results show that the capital regulation introduced by the Dodd–Frank Act has succeeded in influencing banks’ behaviour.

Keywords: Bank risk behaviour; capital regulation; common factors; instrumental variables; large N and T asymptotics; panel data; social interactions; state dependence (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Working Paper: IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude Toward Risk (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:emjrnl:v:26:y:2023:i:2:p:124-146.

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