Foredragsholder: Vasilis Sarafidis, BI
Dato: 7. desember 2021
Når: 11:45 - 12:45
Hvor: Møterom "Befolkning", SSBs lokaler, Akersveien 26

Portrettfoto av Vasilis Sarafidis, BI
Vasilis Sarafidis, BI

Vasilis Sarafidis presenterer funn fra publikasjonen "IV Estimation of Spatial Dynamic Panels with Common Factors".

Om publikasjonen

We develop a new Instrumental Variables (IV) estimator for spatial, dynamic panel data models 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 in this paper is appealing from both a theoretical and a practical point of view for a number of reasons. Firstly, the proposed IV estimator is linear in the parameters of interest and it is computationally inexpensive. Secondly, the IV estimator is free from asymptotic bias. In contrast, existing QML estimators suffer from incidental parameter bias, which depends on the magnitude of unknown parameters. Thirdly, the IV estimator retains the attractive feature of Method of Moments estimation in that it can accommodate endogenous regressors, so long as external exogenous instruments are available. The IV estimator is consistent and asymptotically normal as N, T grow large, such that N/T converges to a positive, bounded constant. The proposed methodology is employed to study the determinants of risk attitude of banking institutions. The results of our analysis provide evidence that the more risk-sensitive capital regulation that was introduced by the Dodd-Frank Act in 2011 has succeeded in influencing banks’ behaviour in a substantial manner.”

Om foredragsholderen

Vasilis Sarafidis is a professor at the Department of Economics, BI Norwegian Business School. His main area of research lies in the econometric analysis of panel data. His focus lies on model specification and testing, dynamic panels, common factor structures, models for spatial interactions and networks, multi-dimensional panels, and random coefficient models; with applications to the analysis of crime, banking, water-usage demand, among others.

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Praktisk informasjon

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