Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this paper we develop an asymptotic theory for the Quasi-Maximum Likelihood Estimator (QMLE) of the parametric GARCH-in-Mean model. The asymptotics is based on a study of the volatility as a process of the model parameters. The proof makes use of stochastic recurrence equations for this random function and uses exponential inequalities to localize the problem. Our results show why the asymptotics for this specification is quite complex although it is a rather standard parametric model. Nevertheless, our theory does not yet treat all standard specifications of the mean function.