Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We discuss methods of measuring the treatment effects of a unit through the use of other units in panel data by either the factor‐based (FB) approach or the linear projection (LP) approach under different sample configurations of cross‐sectional dimension N and time series dimension T. We show that the LP approach in general yields smaller mean square prediction error than the FB approach when either both N and T are large or N fixed and T→∞ or T fixed and N large. The Monte Carlo simulation and empirical example are also conducted to consider their finite sample performances.