AB: Given the large uncertainties regarding potential damages from climate change and the significant but also uncertain costs of reducing greenhouse emissions, the debate over a policy response is often framed as a choice of either acting now or waiting until the uncertainty is reduced. A good example of this debate appeared in EOS, Transactions in 1991 between Risbey et al. and Schlesinger and Jiang. Implicit behind the "wait to learn" argument is the notion that the ability to learn in the future necessarily implies that less restrictive policies should be chosen in the near-term. I demonstrate in the general case that the ability to learn in the future can lead to either less restrictive or more restrictive policies today. I also show that the initial decision made under uncertainty will only be affected by future learning if the actions taken today change the marginal costs or marginal damages in the future. Without this interaction, learning has no effect on what we do today, regardless of what we learn in the future. Results from an intermediate-scale integrated model of climate and economics indicate that the choice of current emissions restrictions is independent of whether or not uncertainty is resolved before future decisions. The reason for this result is that the cross-period interaction in the model is minimal. Indeed, most climate and economic models fail to capture potentially important cross-period interaction effects. I construct a simple example to show that with more interactions, the effect of learning on initial period decisions can be more important. Analysis of learning and sequential decision will require attention to cross-period interactions such as endogenous technical change and the thermohaline circulation.