The COVID-19 shock and challenges for inflation modelling
E Bobeica, B Hartwig - International journal of forecasting, 2023 - Elsevier
We document the impact of COVID-19 on inflation modelling within a vector autoregression
(VAR) model and provide guidance for forecasting euro area inflation during the pandemic …
(VAR) model and provide guidance for forecasting euro area inflation during the pandemic …
Does the volatility of commodity prices reflect macroeconomic uncertainty?
While there exists numerous studies on the macroeconomic effects of oil and commodity
shocks, the literature is quite silent on the impact of macroeconomic uncertainty on oil and …
shocks, the literature is quite silent on the impact of macroeconomic uncertainty on oil and …
Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity
A class of global-local hierarchical shrinkage priors for estimating large Bayesian vector
autoregressions (BVARs) has recently been proposed. We question whether three such …
autoregressions (BVARs) has recently been proposed. We question whether three such …
Large order-invariant Bayesian VARs with stochastic volatility
Many popular specifications for Vector Autoregressions (VARs) with multivariate stochastic
volatility are not invariant to the way the variables are ordered due to the use of a lower …
volatility are not invariant to the way the variables are ordered due to the use of a lower …
Large Bayesian VARs: A flexible Kronecker error covariance structure
JCC Chan - Journal of Business & Economic Statistics, 2020 - Taylor & Francis
We introduce a class of large Bayesian vector autoregressions (BVARs) that allows for non-
Gaussian, heteroscedastic, and serially dependent innovations. To make estimation …
Gaussian, heteroscedastic, and serially dependent innovations. To make estimation …
[HTML][HTML] Volatility predictability in crude oil futures: Evidence based on OVX, GARCH and stochastic volatility models
The paper examines the volatility predictive ability of the CBOE crude oil volatility index
(OVX), GARCH and Stochastic Volatility Models in the crude oil market. Specifically, the …
(OVX), GARCH and Stochastic Volatility Models in the crude oil market. Specifically, the …
The COVID-19 shock and challenges for time series models
E Bobeica, B Hartwig - 2021 - papers.ssrn.com
We document the impact of COVID-19 on frequently employed time series models, with a
focus on euro area inflation. We show that for both single equation models (Phillips curves) …
focus on euro area inflation. We show that for both single equation models (Phillips curves) …
On the observed-data deviance information criterion for volatility modeling
JCC Chan, AL Grant - Journal of Financial Econometrics, 2016 - academic.oup.com
We propose importance sampling algorithms based on fast band matrix routines for
estimating the observed-data likelihoods for a variety of stochastic volatility models. This is …
estimating the observed-data likelihoods for a variety of stochastic volatility models. This is …
Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970
Output growth estimates for regions of the UK are currently published at an annual
frequency only, released with a long delay, and offer limited historical coverage. To improve …
frequency only, released with a long delay, and offer limited historical coverage. To improve …
[HTML][HTML] Uncertainty matters: Evidence from close elections
C Redl - Journal of International Economics, 2020 - Elsevier
This paper uses a data rich environment to produce direct econometric estimates of
macroeconomic and financial uncertainty for 11 advanced nations. These indices exhibit …
macroeconomic and financial uncertainty for 11 advanced nations. These indices exhibit …