Recursive estimators for utilizing new information to update or revise estimates of the parameters of an economic model are derived. The forthcoming information includes new data anda prioriprobabilistic information about changes, if any, occurring in the parameters of the estimated economic model over time. Such recursive methods are likely to prove useful to economists in a number of ways, such as the following: first, they can be used to develop tests for variation in structural coefficients over time; second, they enable tracking the parameters of time-varying economic systems; third, they admit the possibility of proceeding with the gathering of observed data until a specified accuracy of the parameters is achieved; and finally, they can play an important role in adaptive learning, forecasting and control. This paper examines recursive estimation in the context of both multiple equation as well as simultaneous equation models.