The paper investigates how well linear vector autoregressions (VARs) identify endogenous cycle mechanisms and frequencies when the underlying process is a nonlinear limit cycle. We conduct Monte Carlo simulations with five models in which cycles are driven by interaction of two state variables. find that while VARs quantitatively underestimate strength mechanism, they successfully qualitative p...

This paper examines the usefulness of applying structural vector autoregressions (SVARs) to the study of business cycles. The SVAR approach aims to provide robust inferences, by imposing only weak theoretical restrictions. We illustrate that the robustness of conclusions drawn from SVAR exercises are questionable. We also examine the problem of identification failure in structural VAR models. ©...

Abstract We propose a Bayesian approach to Local Projections that optimally addresses the empirical bias-variance trade-off intrinsic in choice between direct and iterative methods. (BLP) regularise LP regressions via informative priors, estimate impulse response functions capture properties of data more accurately than VARs. BLPs preserve flexibility LPs while retaining degree estimation uncer...

Recent work suggests VAR models of output, inflation, and interest rates may be prone to instabilities. In the face of such instabilities, a variety of estimation or forecasting methods might be used to improve the accuracy of forecasts from a VAR. The uncertainty inherent in any single representation of instability could mean that combining forecasts from a range of approaches will improve for...

background: qual2k is a stream water quality model and was used to evaluate the water quality of the kine-vars river and assess the response of the river to nutrient management strategies. methods: for that purpose, 7 sample stations were selected and surface water samples were collected in the winter and summer of 2012 and were analyzed for temperature, dissolved oxygen, biological oxygen dema...

Macroeconomists constructing conditional forecasts often face a choice between taking stand on the details of fully-specified structural model or relying correlations from VARs and remaining silent about underlying causal mechanisms. This paper develops tools for economically meaningful scenarios with VARs, proposes metric to assess compare their plausibility. We provide unified treatment forec...