Time: 11th June (Tuesday) 15.00 Moscow time
Speaker: Pierluigi Vallarino (Research Fellow at the Econometrics Institute of Erasmus School of Economics)
Title: New rank-based tests and estimators for Common Primitive Shocks
Field of study
"Time series and Financial Econometrics"
What problem is your research intended to solve?
"What is the smallest number of common shocks that drive a large economic system? Which sides of the economic system should we model to account for them?"
What did your research find?
"The US business cycle can be explained by looking at four common sources of randomness. These are mostly related to: the production sector, the level of prices in the economy, and funding markets."
Abstract: We propose a new rank-based test for the number of common primitive shocks q in large panels of observations. After estimating a VAR(1) model on factors extracted by principal component analysis, we estimate the number of common primitive shocks by testing the rank of the VAR residuals’ covariance matrix. Our new rank test is based on the asymptotic distribution of the sum of the smallest r − q eigenvalues of the residuals’ covariance matrix. We develop both plug-in and bootstrap versions of this eigenvalue-based test. The eigenvectors associated to the q largest eigenvalues allow us to construct an easy-to-implement estimator of the common primitive shocks and to derive its asymptotic properties. We consider applications of the new tests and estimators on panels of macro-financial variables and individual stocks volatilities.
More information, a link to the research and the upcoming seminar here.
We are looking forward to seeing you!
Speaker: Pierluigi Vallarino (Research Fellow at the Econometrics Institute of Erasmus School of Economics)
Title: New rank-based tests and estimators for Common Primitive Shocks
Field of study
"Time series and Financial Econometrics"
What problem is your research intended to solve?
"What is the smallest number of common shocks that drive a large economic system? Which sides of the economic system should we model to account for them?"
What did your research find?
"The US business cycle can be explained by looking at four common sources of randomness. These are mostly related to: the production sector, the level of prices in the economy, and funding markets."
Abstract: We propose a new rank-based test for the number of common primitive shocks q in large panels of observations. After estimating a VAR(1) model on factors extracted by principal component analysis, we estimate the number of common primitive shocks by testing the rank of the VAR residuals’ covariance matrix. Our new rank test is based on the asymptotic distribution of the sum of the smallest r − q eigenvalues of the residuals’ covariance matrix. We develop both plug-in and bootstrap versions of this eigenvalue-based test. The eigenvectors associated to the q largest eigenvalues allow us to construct an easy-to-implement estimator of the common primitive shocks and to derive its asymptotic properties. We consider applications of the new tests and estimators on panels of macro-financial variables and individual stocks volatilities.
More information, a link to the research and the upcoming seminar here.
We are looking forward to seeing you!