A generalized approach to indeterminacy in linear rational expectations models

We propose a novel approach to deal with the problem of indeterminacy in linear rational expectations models. The method consists augmenting original state space set auxiliary exogenous equations provide adequate number explosive roots presence indeterminacy. solution this expanded space, if it exists, is always determinate, and identical indeterminate model. proposed accommodates determinacy any degree indeterminacy, can be implemented even when boundaries region are unknown. Thus, researcher estimate model using standard software packages without restricting estimates region. combine our hybrid Metropolis–Hastings algorithm New–Keynesian bubbles by Galí (2021) over period 1982:Q4–2007:Q3. find that data support two degrees implying central bank was not reacting strongly enough bubble component.