Money demand in Venezuela is modeled using structural time series and error correction approaches, for the period 1993.1 to 2001.4. The preferred model features seasonal cointegration and was estimated following a structural time series approach. There are similarities in the long-run behavior of money demand associated with the structural time series and error correction approaches. Estimated short-run dynamics are more fragile, with the structural time series modeling approach providing richer insights into the adjustment dynamics of money demand. A cycle with a three-year period has been found to be common to money demand, real GDP, and opportunity cost variables. This cycle is robust to changes in model specification, including choice of opportunity cost variables. Higher frequency cycles are also found to exist, but are more sensitive to model specification. Results are also presented for a combined approach that takes advantage of error correction models, as well as insights into short-run dynamics afforded by the structural time series modeling approach.