Narrow search
Showing 1 - 10 of 252
Cover Image
Behavioral Heterogeneity in U.S. Inflation Dynamics
Cornea, Adriana; Hommes, Cars; Massaro, Domenico - 2013
In this paper we develop and estimate a behavioral model of inflation dynamics with monopolistic competition, staggered … naive. Fundamentalists are forward-looking in the sense that they believe in a present-value relationship between inflation … forecast future inflation. Agents are allowed to switch between these different forecasting strategies conditional on their …
Persistent link: https://www.econbiz.de/10010326298
Cover Image
Regional Price Adjustment in a Monetary Union
Berk, Jan Marc; Swank, Job - 2002
, notwithstanding that inflation in some countries tends to converge towards the euro area level. Overa11, inflation persistence has …
Persistent link: https://www.econbiz.de/10010324791
Cover Image
A General Framework for Observation Driven Time-Varying Parameter Models
Creal, Drew; Koopman, Siem Jan; Lucas, André - 2008
We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...
Persistent link: https://www.econbiz.de/10010325732
Cover Image
A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations
Creal, Drew; Koopman, Siem Jan; Lucas, André - 2010
We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
Persistent link: https://www.econbiz.de/10010325845
Cover Image
Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails
Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, Andre - 2011
We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...
Persistent link: https://www.econbiz.de/10010326055
Cover Image
A New Semiparametric Volatility Model
Ji, Jiangyu; Lucas, Andre - 2012
We propose a new semiparametric observation-driven volatility model where the form of the error density directly influences the volatility dynamics. This feature distinguishes our model from standard semiparametric GARCH models. The link between the estimated error density and the volatility...
Persistent link: https://www.econbiz.de/10010326169
Cover Image
Long Memory Dynamics for Multivariate Dependence under Heavy Tails
Janus, Pawel; Koopman, Siem Jan; Lucas, André - 2011
We develop a new simultaneous time series model for volatility and dependence with long memory (fractionally integrated) dynamics and heavy-tailed densities. Our new multivariate model accounts for typical empirical features in financial time series while being robust to outliers or jumps in the...
Persistent link: https://www.econbiz.de/10010326461
Cover Image
Generalized Autoregressive Method of Moments
Creal, Drew; Koopman, Siem Jan; Lucas, André; … - 2015
We introduce a new estimation framework which extends the Generalized Method of Moments (GMM) to settings where a subset of the parameters vary over time with unknown dynamics. To filter out the dynamic path of the time-varying parameter, we approximate the dynamics by an autoregressive process...
Persistent link: https://www.econbiz.de/10011451505
Cover Image
Forecasting in a changing world: from the great recession to the COVID-19 pandemic
Artemova, Mariia; Blasques, Francisco; Koopman, Siem Jan; … - 2021
We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...
Persistent link: https://www.econbiz.de/10012427192
Cover Image
A General Framework for Observation Driven Time-Varying Parameter Models
Creal, Drew - 2008
We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...
Persistent link: https://www.econbiz.de/10012722680