Week 4 & 5 Flashcards
(35 cards)
What is the idea of VECM models?
What are the mean, variance, autocovariance and autocorrelations of a AR(1) random walk process?
When is a process integrated with an order of 1? How can it be made stable? How can this be generalized?
When is differencing components in a time series process d times (i.e., where d is the number roots in the unit circle), not ideal?
What is the idea of a cointegrated process?
What is the idea of a cointegrated process?
Describe a general (simple) ECM model.
How to write a VECM model as a VAR model? What does this mean?
How to rewrite a (unstable) VAR(2) to a VECM model?
Why is cointegration important?
When is a VAR(p) process called cointegrated?
What are the other options for r (the rank of matrix Pi)?
What is the VECM representation? What are the parameters of a VAR process (using the variables of a VECM)?
How is a constant included in a VECM model?
How to interpret estimates of a VECM model?
What is a vector space?
What is a vector subspace?
What is the orthogonal complement?
What is a projection?
What is the Frisch-Waugh-Lovell theorem?
Why is the Frisch-Waugh-Lovell theorem needed?
Describe a VECM without deterministic terms.
I.e., what is the notation
What is the VECM in stacked matrix notation?
How can we estimate a VECM using LS? When and or why would we do this?