Transcription of Vector Autoregression and Vector Error-Correction Models
{{id}} {{{paragraph}}}
Example: quiz answers
Vector Autoregression and Vector Error-Correction Models
CHAPTER 5 Vector Autoregression and Vector Error-Correction Models Vector Autoregression (VAR) was introduced by Sims (1980) as a technique that could be used by macroeconomists to characterize the joint dynamic behavior of a collection of varia-bles without requiring strong restrictions of the kind needed to identify underlying structural parameters. It has become a prevalent method of time-series modeling. Although estimating the equations of a VAR does not require strong identification as-sumptions, some of the most useful applications of the estimates, such as calculating impulse-response functions (IRFs) or variance decompositions do require identifying restrictions.
Granger causality analysis. 5.1.1 Forecasting with a VAR The structure of equations is designed to model how the values of the variables in (5.1) period . t. are related to past values. This makes the VAR a natural for the task of forecasting the future paths of . x . and . y.
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: