Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The Arellano-Bond estimator is widely used among applied researchers when estimating dynamic panels with fixed effects and predetermined regressors. This estimator might behave poorly in finite samples when the cross-section dimension of the data is small (i.e. small $$N$$N), especially if the variables under analysis are persistent over time. This paper discusses a maximum likelihood estimator that is asymptotically equivalent to Arellano and Bond (1991) but presents better finite sample behaviour. The estimator is based on an alternative parametrization of the likelihood function introduced in Moral-Benito (2013). Moreover, it is easy to implement in Stata using the xtdpdml command as described in a companion paper published in the Stata Journal, which also discusses further advantages of the proposed estimator for practitioners.