Cross-section dependence in nonstationary panel models: a novel estimator

University of Oxford

Abstract

This paper uses Monte Carlo simulations to investigate the impact of nonstationarity, parameter heterogeneity and cross-section dependence on estimation and inference in macro panel data. We compare the performance of standard panel estimators with that of our own two-step method (the AMG) and the Pesaran (2006) Common Correlated Effects (CCE) estimators in time-series panels with arguably similar characteristics to those encountered in empirical applications using cross-country macro data. The empirical model adopted leads to an identification problem in standard estimation approaches in the case where the same unobserved common factors drive the evolution of both dependent and independent variables. We…

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Topics & keywords

Keywords
  • Estimator
  • Monte Carlo method
  • Econometrics
  • Panel data
  • Inference
  • Statistics
  • Contrast (vision)
  • Identification (biology)
UN Sustainable Development Goals
  • Zero hunger
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