Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Abstract Funnel graphs provide a simple, yet highly effective, means to identify key features of an empirical literature. This paper illustrates the use of funnel graphs to detect publication selection bias, identify the existence of genuine empirical effects and discover potential moderator variables that can help to explain the wide variation routinely found among reported research findings. Applications include union–productivity effects, water price elasticities, common currency‐trade effects, minimum‐wage employment effects, efficiency wages and the price elasticity of prescription drugs.