Impulse Response Analysis of Structural Nonlinear Time Series Models

Linear time series models are the workhorse of structural macroeconometric analysis. However, economic theory as well as data suggest that nonlinear and asymmetric effects might be key to understand the potential effects of sudden economic changes. Taking a dynamical system view, this paper proposes a new semi-nonparametric approach to construct impulse responses of nonlinear time series. Estimation of autoregressive models with sieve methods is discussed under natural physical dependence assumptions, and uniform consistency results for structural impulse responses are derived. Simulations and two empirical exercises show that the proposed method performs well and yields new insights in the dynamic effects of macroeconomic shocks.