Identifying Factor‐Augmented Vector Autoregression Models via Changes in Shock Variances

Identifying paths-to-purchase segments via Clustered Vector Autoregression

Vector Autoregression Models (VAR) are widely used by researchers to capture the linear interdependencies among multiple time series. We propose a novel method called Clustered VAR (CVAR) to identify components of the data generated by a mixture of K VAR processes. By applying a CVAR model to a consumer-level time series dataset on shopping behavior at a retailer, we segment consumers based on ...

Identifying Structural Vector Autoregressions via Changes in Volatility

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modelling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present stud...

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...

Lecture 6 : Vector Autoregression ∗

Lung Changes in Shock

In the very beginning stage of the lung changes are Perivascular, capillary wall edema, thickening of the interstitial, lymph and vascular dilatation.  In the late stage of the shock the following changes will occuree  Microthromboses of the lung capillary, polynulcear in­filtration into the interstitial, the existence of polynu­clear in the alveoli, proliferation of interstitial mesenchy­ma,...