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Keywords:generalized impulse response functions 

Working Paper
The Nonlinear Effects of Uncertainty Shocks

We consider the effects of uncertainty shocks in a nonlinear VAR that allows uncertainty to have amplification effects. When uncertainty is relatively low, fluctuations in uncertainty have small, linear effects. In periods of high uncertainty, the effect of a further increase in uncertainty is magnified. We find that uncertainty shocks in this environment have a more pronounced effect on real economic variables. We also conduct counterfactual experiments to determine the channels through which uncertainty acts. Uncertainty propagates through both the household consumption channel and through ...
Working Papers , Paper 2018-035

Working Paper
Impulse Response Functions for Self-Exciting Nonlinear Models

We calculate impulse response functions from regime-switching models where the driving variable can respond to the shock. Two methods used to estimate the impulse responses in these models are generalized impulse response functions and local projections. Local projections depend on the observed switches in the data, while generalized impulse response functions rely on correctly specifying regime process. Using Monte Carlos with different misspecifications, we determine under what conditions either method is preferred. We then extend model-average impulse responses to this nonlinear ...
Working Papers , Paper 2023-021

Working Paper
Impulse Response Functions for Self-Exciting Nonlinear Models

We calculate impulse response functions from regime-switching models where the driving variable can respond to the shock. Our focus is on nonlinear vector autoregressions with a variety of specifications for the transition function used throughout the literature. Using Monte Carlo simulations with different misspecifications, we identify the conditions under which impulse response function estimates exhibit significant bias. Furthermore, we extend the concept of model-average impulse responses to this nonlinear context and demonstrate their robustness to model misspecification. Applying these ...
Working Papers , Paper 2023-021

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