This thesis examines the effectiveness of forward guidance in the euro area using a structural New-Keynesian model at the zero lower bound (ZLB). To incorporate forward guidance, I implement a ZLB constraint into a medium-scale Dynamic Stochastic General Equilibrium (DSGE) model that treats a sequence of expected durations of the ZLB as free parameters in estimation. The sequence of expected durations is informed by survey data to produce well-identified estimates that align with macroeconomic data and the underlying model structure. Results indicate that these expected durations play a key role in explaining model dynamics when interest rates are fixed at the ZLB. Further, through the use of a sunspot solution strategy to accommodate different expected liftoff regimes, I quantify how much the effectiveness of forward guidance depends not just on the expected duration of the ZLB regime, but also on expectations regarding the behavior of monetary policy in the liftoff regime. Finally, I propose a time-series approach to address the extreme data outliers during the Covid-19 pandemic. This approach builds on the emerging literature on estimating Covid-19 outliers in VAR models to the setting of estimating structural DSGE models and allows for an assessment of monetary policy during the pandemic period.