The large heterogeneous panel data models are extended to the setting where the heterogenous coefficients are changing over time and the regressors are endogenous. Kernel-based non-parametric timevarying parameter instrumental variable mean group (TVP-IV-MG) estimator is proposed for the timevarying cross-sectional mean coefficients. The uniform consistency is shown and the pointwise asymptotic normality of the proposed estimator is derived. A data-driven bandwidth selection procedure is also proposed. The finite sample performance of the proposed estimator is investigated through a Monte Carlo study and an empirical application on multi-country Phillips curve with time-varying parameters.

Mean group instrumental variable estimation of time-varying large heterogeneous panels with endogenous regressors

Bai, Yu;Marcellino, Massimiliano;
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Abstract

The large heterogeneous panel data models are extended to the setting where the heterogenous coefficients are changing over time and the regressors are endogenous. Kernel-based non-parametric timevarying parameter instrumental variable mean group (TVP-IV-MG) estimator is proposed for the timevarying cross-sectional mean coefficients. The uniform consistency is shown and the pointwise asymptotic normality of the proposed estimator is derived. A data-driven bandwidth selection procedure is also proposed. The finite sample performance of the proposed estimator is investigated through a Monte Carlo study and an empirical application on multi-country Phillips curve with time-varying parameters.
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Bai, Yu; Marcellino, Massimiliano; Kapetanios, George
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4061059
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