The sources of lag (the delay between input action and output response) and its effects on human performance are discussed. We measured the effects in a study of target acquisition using the classic Fitts\u27 law paradigm with the addition of four lag conditions. At the highest lag tested (225 ms), movement times and error rates increased by 64% and 214% respectively, compared to the zero lag condition. We propose a model according to which lag should have a multiplicative effect on Fitts\u27 index of difficulty. The model accounts for 94% of the variance and is better than alternative models which propose only an additive effect for lag. The implications for the design of virtual reality systems are discussed