Ek, Claes2020-06-292020-06-292020-061403-2465http://hdl.handle.net/2077/65185JEL classi cation: C93, C23Ex-ante power calculation is an essential part of the toolkit of experimental economics. In panel experiments, analysis of covariance (ANCOVA) is more efficient than differencein- differences and is often preferred. The present paper derives a general serial-correlationrobust variance formula and provides the first analytical ANCOVA power-calculation framework to work with real data. A related earlier procedure for ANCOVA was found by Burlig et al. (2020) to yield incorrect power when used to calibrate a minimum detectable effect on actual data, and the authors caution against using it in practice. I show that these errors arose because time shocks were not properly accounted for in an intermediate procedure estimating residual-based variance parameters from pre-existing data. My procedure resolves such issues, thus providing a framework for accurate power calculation with ANCOVA.38engpower calculationrandomized experimentsexperimental designpanel dataANCOVAText