Abstract

There is a growing interest in allowing for asymmetry in the density forecasts of macroeconomic variables. In multivariate time series, this can be achieved with a copula model, where both serial and cross-sectional dependence is captured by a copula function, and the margins are nonparametric. Yet most existing copulas cannot capture heteroskedasticity well, which is a feature of many economic and financial time series. To do so, we propose a new copula created by the inversion of a multivariate unobserved component stochastic volatility model, and show how to estimate it using Bayesian methods. We fit the copula model to real-time data on five quarterly U.S. economic and financial variables. The copula model captures heteroskedasticity, dependence in the level, time-variation in higher moments, bounds on variables and other features. Over the window 1975Q1 – 2016Q2, the real-time density forecasts of all the macroeconomic variables exhibit time-varying asymmetry. In particular, forecasts of GDP growth have increased negative skew during recessions. The point and density forecasts from the copula model are competitive with those from benchmark models – particularly for inflation, a short term interest rate and current quarter GDP growth.

Download the paper (PDF, 2.7 MB)

About the presenter’s visit

Professor Smith will be visiting the School of Economics on Tuesday 6th August 2019.  While here he will be using room 520A Colin Clark Building.  If you would like to meet with him or have lunch or dinner with him please contact Professor Rodney Strachan who will be his host while at The University of Queensland.  Dr Ouyang can be contacted on r.strachan@uq.edu.au.

 

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Venue

Level 6
Colin Clark Building (#39)
UQ St Lucia
Room: 
629