Econometrics Seminar: Guillaume Chevillon (ESSEC Business School) – School of Economics Econometrics Seminar: Guillaume Chevillon (ESSEC Business School) – School of Economics

Econometrics Seminar: Guillaume Chevillon (ESSEC Business School)

The School of Economics invites you to an Econometrics seminar presented by Guillaume Chevillon (ESSEC Business School).

Long-memory prone priors for large systems within a finite-order VAR

 

Co-authors: 

Luc Bauwens (Université Catholique de Louvain) and Sébastien Laurent (Aix-Marseille University)

Abstract

We propose a class of prior distributions adapted to the modeling and forecasting of large dimensional systems within a vector autoregression (VAR) of finite-order. These priors are derived from the conditions stated in Chevillon, Hecq and Laurent (2018) who show that as the number of variables within a VAR(1) becomes very large, the ensuing dependence across units can generate fractional long memory in each variable individually. We extend and generalize their results and use these as means of a prior distribution for estimation in systems that are too large for efficient unconstrained multivariate inference. In applications to stock return realized volatilities and sectoral consumer price inflation, our suggested multivariate priors may yield substantial improvements in forecasting performance over standard techniques such as VAR, HAR or ARFIMA models.

Date

Mar 04 2020
Expired!

Time

11:00 am - 12:30 pm

Location

Room 538
Social Sciences Building (A02)
Category

Organizer

Dave Mc Manamon
Phone
93514587
Email
dave.mcmanamon@sydney.edu.au

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