Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
It is well known that many of the standard specification tests may not be robust when the alternative is misspecified. This study analyzes a robust specification test for generalized empirical likelihood (GEL) estimators in a weakly dependent time series setting. We show that the usual score test statistic asymptotically follows a non-central chi-square distribution under the local misspecification in the GEL framework. Thus, it spuriously rejects the null hypothesis too frequently. We propose a robust score specification test that asymptotically follows a central chi-square distribution under the local misspecification. A Monte Carlo simulation verifies the usefulness of the proposed tests.