Delayed Overshooting Puzzle in Structural Vector Autoregression Models

Evaluating Structural Vector Autoregression Models in Monetary Economies

This paper uses Monte Carlo simulations to evaluate alternative identi…cation strategies in VAR estimation of monetary models, and to assess the accuracy of measuring money instability as a cause of output ‡uctuations. I construct theoretical monetary economies using general equilibrium models with cash-in-advance constraints, which also include technology shocks, labor supply shocks, and monet...

Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity

Analysis of causal effects between continuous-valued variables typically uses either autoregressive models or structural equation models with instantaneous effects. Estimation of Gaussian, linear structural equation models poses serious identifiability problems, which is why it was recently proposed to use non-Gaussian models. Here, we show how to combine the non-Gaussian instantaneous model wi...

Lecture 6 : Vector Autoregression ∗

The Effects of Monetary Policy Shocks on Exchange Rates: A Structural Vector Error Correction Model Approach

This paper investigates the effects of shocks to U.S. monetary policy on the dollar/yen exchange rate, using structural Vector Error Correction Model (VECM) methods. We compare our estimates of the impulse responses with those based on levels Vector Autoregression. We also compare results from short run and long run restrictions imposed on the structural VECM. We find evidence of overshooting b...

Structured Regularization for Large Vector Autoregression

The vector autoregression (VAR), has long proven to be an effective method for modeling the joint dynamics of macroeconomic time series as well as forecasting. One of the major disadvantages of the VAR that has hindered its applicability is its heavy parameterization; the parameter space grows quadratically with the number of series included, quickly exhausting the available degrees of freedom....