Panel cointegrating polynomial regressions: Group-mean fully modified OLS estimation and inference

Abstract

This paper considers group-mean fully modified OLS estimation for a panel of cointegrating polynomial regressions, i. e., regressions that include an integrated process and its powers as explanatory variables. The stationary errors are allowed to be serially correlated, the regressor to be endogenous and { as usual in the nonstationary panel literature { we include individual specific fixed effects. We consider a fixed cross-section dimension, asymptotics in the time dimension only and show that the estimator allows for standard asymptotic inference in this setting. In both the simulations as well as an illustrative application estimating environmental Kuznets curves for carbon dioxide emissions we compare our group-mean estimator with the pooled fully modified OLS estimator of de Jong and Wagner (2018).