EcoSta Editors

Erricos J. Kontoghiorghes
Cyprus University of Technology and Queen Mary, University of London, UK, Cyprus
Editor-in-chief

Herman K. Van Dijk
Erasmus Universiteit Rotterdam and VU University Amsterdam, The Netherlands
Co-editor Part A

Ana Colubi
University of Oviedo, Spain
Co-editor Part B

EcoSta Advisory Board - Part A (Econometrics)

Tim Bollerslev
Duke University, USA
Measuring, modeling, and forecasting financial market volatility

Francis X. Diebold
University of Pennsylvania, USA
Economic and financial measurement, modeling and forecasting, with emphasis on asset return volatility and correlation, yield curves, links to macroeconomic fundamentals, risk management, and business cycles

Robert Engle
New york University, USA
Macro economics, energy markets, urban economies and emerging markets, financial asset classes

Hashem Pesaran
University of Cambridge, USA
Heterogeneous panels with unobserved common effects, panel unit root tests, PVAR, long-run structural macroeconometric modelling, GVAR, structural breaks, financial econometric s

Peter C.B. Phillips
Yale University, University of Auckland, Singapore Management University, University of Southampton., USA
Time series, panels, trends, bubbles, financial warning alert systems

Mike West
Duke University, USA
Bayesian statistics involving stochastic modelling in higher-dimensional problems: dynamic models in time series analysis, multivariate analysis, latent structure, stochastic computational methods, parallel/GPU computing

EcoSta Advisory Board - Part B (Statistics)

Peter Buehlmann
ETH Zurich, Switzerland
Statistics, machine learning, computational biology

Peter Green
University of Bristolvand University of Technology, Sydney, UK and Australia
Bayesian inference in complex stochastic systems, Markov chain Monte Carlo methodology, forensic genetics, Bayesian nonparametrics graphical models

Xuming He
University of Michigan, USA
Robust statistics, quantile regression, subgroup analysis, model selection

Steve Marron
University of North Carolina at Chapel Hill, USA
Object oriented data analysis, smoothing methods for curve estimation

Hans-Georg Mueller
University of California Davis, USA
Functional data, longitudinal data

Byeong Park
Seoul National University, Korea, South
Nonparametric inference, functional data analysis

Ingrid Van Keilegom
Universite catholique de Louvain, Belgium
Cure model, survival analysis, measurement error, semiparametric regression, SIMEX

EcoSta Associate Editors - Part A (Econometrics)

Manfred Deistler
Vienna University of Technology, Austria
Time series analysis, econometrics, systems identification

Jean-Marie Dufour
McGill University, Canada
Econometrics, time series, structural models, identification, macroeconomics, financial econometrics

Andrew Harvey
University of Cambridge, UK
Time series and econometrics, macroecometrics and financial econometrics, state space models, signal extraction, volatility, quantiles and copulas.

Jonathan Hill
University of North Carolina, USA
Robust estimation, extreme value theory, weak dependence, asymptotic theory

Degui Li
University of York, UK
Time series, nonparametric and semiparametric statistics, panel data

Helmut Lutkepohl
Freie Universität Berlin and DIW Berlin, Germany
Multiple time series analysis, cointegration, structural vector autoregressive analysis, forecasting methods, aggregation of time series

James G. MacKinnon
Queen's University, Canada
Bootstrap methods, specification testing

Yasuhiro Omori
University of Tokyo, Japan
Bayesian analysis, Bayesian econometrics, Markov chain Monte Carlo, stochastic volatility, state space model

Gareth Peters
UCL, UK
State space modelling, mathematical statistics and time series, sequential Monte Carlo and particle filtering, Markov chain Monte Carlo, Bayesian estimation, risk management and insurance, high frequency financial data

D.S.G. Pollock
University of Leicester, UK
Statistical analysis in the frequency domain, filtering methods, wavelets, econometric methods, time series analysis, functional analysis

Tommaso Proietti
Università di Roma Tor Vergata, Italy
Time series analysis, applied econometrics, unobserved components models, forecasting methods

Zacharias Psaradakis
Birkbeck University of London, UK
Time-series econometrics, bootstrap methods, nonlinear models, applied econometrics

Jeroen V.K. Rombouts
ESSEC Business School, France
Financial econometrics, volatility, option pricing, times series forecasting, Bayesian times series

Willi Semmler
New School for Social Research, USA
Empirical macroeconomics, business cycles, macro dynamics, dynamic portfolio modeling, multi regime models, multi regime VAR, dynamic programming, Nonlinear Model Predictive Control

Richard J Smith
University of Cambridge, UK
Econometric theory, estimation and inference in econometrics, hypothesis testing, model selection

Mike K.P. So
Hong Kong University of Science and Technology, China
Bayesian analysis, financial time series modeling, market volatility study, risk management

Mark Steel
University of Warwick, UK
Bayesian inference, models with unobserved heterogeneity, MCMC methods, inference robustness, model choice and Bayesian model averaging, improper and reference priors, mixture modelling, skewness, inference in stochastic processes, spatial statistics, semi- and nonparametric Bayesian, growth theory, stochastic frontier models, contingent valuation, stochastic volatility models

Robert Taylor
University of Essex, UK
Bootstrap methods for non-stationary time series, co-integration methods, (seasonal) unit root tests, stationarity tests, stochastic volatility, persistence change testing and structural breaks, financial econometrics

Peter Winker
University of Giessen, Germany
Time series modeling, forecasting, model selection, optimization heuristics in statistics and econometrics

EcoSta Associate Editors - Part B (Statistics)

Ming-Yen Cheng
National Taiwan University, Taiwan
High-dimensional data, non- and semi-parametric models

Bertrand Clarke
University of Nebraska-Lincoln, USA
Data mining and machine learning, prediction,statistical techniques for complex or high-dimensional data, model bias and uncertainty

Aurore Delaigle
University of Melbourne, Australia
Nonparametric estimation, measurement errors, deconvolution problems, functional data analysis

John Einmahl
Tilburg University, Netherlands
Statistics of extremes, empirical processes, multivariate quantiles, empirical likelihood

Roland Fried
TU Dortmund University, Germany
Time series, changepoints, robustness, outliers

Irene Gijbels
Katholieke Universiteit Leuven, Belgium
Nonparametric statistics, mathematical statistics

Armelle Guillou
Strasbourg, France
Computer-intensive statistical methodologies such as bootstrap, jackknife and other resampling methods, extreme value inferences and their applications, statistical inferences in presence of censoring and/or truncation, robust and nonparametric methods

Marc Hallin
Universite Libre de Bruxelles, Belgium
Time series, factor models, asymptotic theory of statistical experiments

Ivan Kojadinovic
University of Pau, France
Multivariate analysis, nonparametric statistics, copulas, change-point detection, empirical processes, environmental and financial applications.

Piotr Kokoszka
Colorado State University, USA
Functional data analysis, time series and spatial statistics, applications to financial econometrics

Christophe Ley
Universite Libre de Bruxelles, Belgium
Optimal inferential procedures, rank-based procedures, non-Gaussian distributions, directional data, Maximum Likelihood Estimation, Non- and semi-parametric statistics, High-dimensional inferential procedures

Paul McNicholas
McMaster University, Canada
Classification, clustering, mixture models, non-Gaussian mixtures

Domingo Morales
University Miguel Hernandez of Elche, Spain
Small area estimation, statistical information theory, simulation and resampling methods, survey sampling, asymptotic statistics, statistical models

Davy Paindaveine
Universite libre de Bruxelles, Belgium
Nonparametric statistics, Statistical depth, Multivariate quantiles, Robust statistics, Rank-based inference, high-dimensional statistics

Dimitris Politis
University of California, San Diego, USA
Time series, bootstrap

Igor Pruenster
University of Torino, Italy
Bayesian asymptotics, Bayesian inference, Bayesian survival analysis, distribution theory, mixture models, predictive inference, random measures, species sampling

Stefan Van Aelst
Ghent University, Belgium
Robustness, multivariate analysis, model selection

Mattias Villani
Linkoping University, Sweden
Bayesian inference, machine learning, computational statistics, predictive inference

Lan Wang
University of Minnesota, USA
High-dimensional data analysis, quantile regression, longitudinal data analysis, survival analysis, hypothesis testing

Alastair Young
Imperial College London, United Kingdom
Statistical theory, computational statistics, statistical asymptotics and approximation methods, bootstrap, likelihood-based inference

Helen Zhang
University of Arizona, USA
Nonparametrics, data smoothing, function estimation, statistical machine learning, high dimensional analysis, biomedical and biological research

EcoSta Guest Associate Editors:

Sung Ahn
Washington State university, United States
Multivariate Time Series, Cointegration

Alessandra Amendola
University of Salerno, Italy
Time series, nonlinear models, forecasting, financial data analysis

Monica Billio
University Ca' Foscari of Venice, Italy
Dynamic latent factor models, simulation-based Inference, volatility and risk modelling, switching regime models, volatility transmission and contagion, business cycle analysis, hedge funds, systemic risk

H. Peter Boswijk
University of Amsterdam, The Netherlands
Time series econometrics, financial econometrics, volatility modelling, bootstrap

Taeryon Choi
Korea University, Korea
Bayesian methods, Bayesian hierarchical models, Bayesian model selection, Bayesian nonparametric inference, Non/Semiparametric regression models.

Marc Hallin
Universite Libre de Bruxelles, Belgium
Time series, factor models, asymptotic theory of statistical experiments

John Hinde
NUI Galway, Ireland
statistical modelling, generalised linear models, mixtures, random effects

Salvatore Ingrassia
University of Catania, Italy
Mixture models, model-based clustering, computational statistics

Eric Jacquier
Boston University School of Management, USA
Bayesian methods in finance, risk and volatility estimation, portfolio and asset allocation

Kenneth Judd
Stanford University, USA
Computational methods for economic modeling, tax policy, antitrust issues, macroeconomics, and policies related to climate change

Piotr Kokoszka
Colorado State University, USA
Functional data analysis, time series and spatial statistics, applications to financial econometrics and space physics

Degui Li
University of York, UK
Time series, nonparametric and semiparametric statistics, panel data

Tsung-I Lin
National Chung Hsing University, Taiwan
Mixture modelling; statistical computing

Gael Martin
Monash University, Australia
Bayesian econometrics, simulation methods, non-Gaussian time series analysis

Paul McNicholas
University of Guelph, Canada
Classification, clustering, mixture models, non-Gaussian mixtures

Hannu Oja
University of Turku, Finland
Nonparametric methods, robust methods, multivariate methods

Yasuhiro Omori
University of Tokyo, Japan
Bayesian analysis, Bayesian econometrics, Markov chain Monte Carlo, stochastic volatility, state space model

Byeong Park
Seoul National University, Korea, South
Nonparametric inference, functional data analysis

Dimitris Politis
University of California, San Diego, USA
Time series, bootstrpap

Laura Sangalli
Politecnico di Milano, Italy
functional data analysis, spatial data analysis, object oriented data analysis

Robert Taylor
University of Essex, UK
Bootstrap methods for non-stationary time series, co-integration methods, (seasonal) unit root tests, stationarity tests, stochastic volatility, persistence change testing and structural breaks

Carsten Trenkler
Universitaet Mannheim, Germany
Time series analysis, cointegration, bootstrap

Stephen Walker
University of Texas at Austin, United States
Bayesian methods, MCMC

For further information please send an email to editorial.office@econometricsandstatistics.org