Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We propose an encompassing test for non-nested linear quantile regression models and show that it has an asymptotic [chi]2 distribution. It is also shown that the proposed test is a regression rank score test in a comprehensive model under conditional homogeneity. Our simulation results indicate that the proposed test performs very well in finite samples.