A comparison of FDML and GMM for estimation of dynamic panel models with roots near unity
This thesis compares the performance of the first-differenced maximum likelihood estimator (FDML) and the Blundell-Bond continuously-updating system GMM estimator of the autoregressive parameter in an AR(1) dynamic panel model without exogenous covariates, particularly focusing on the close-to-non-stationary case. This case is far from trivial, as a high degree of persistence is the norm rather th
