Econometrics and Statistics

2017 - 2023

Current editor(s): E.J. Kontoghiorghes, H. Van Dijk and A.M. Colubi

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Volume 25, issue C, 2023

Instrument-free inference under confined regressor endogeneity and mild regularity pp. 1-22

Jan F. Kiviet

Feasible Panel GARCH Models: Variance-Targeting Estimation and Empirical Application pp. 23-38

Manabu Asai

On a Rosenblatt-type transformation of multivariate copulas pp. 39-48

Evgeniy Savinov and Victoria Shamraeva

Combining rules for F- and Beta-statistics from multiply-imputed data pp. 51-65

Ashok Chaurasia

Constructing a polygenic risk score for childhood obesity using functional data analysis pp. 66-86

Sarah J.C. Craig, Ana M. Kenney, Junli Lin, Ian M. Paul, Leann L. Birch, Jennifer S. Savage, Michele E. Marini, Francesca Chiaromonte, Matthew L. Reimherr and Kateryna D. Makova

Regression Reconstruction from a Retrospective Sample pp. 87-92

Christiana Kartsonaki and D. R. Cox

On The Problem of Relevance in Statistical Inference pp. 93-109

Subhadeep Mukhopadhyay and Kaijun Wang

Statistical inference for state occupation and transition probabilities in non-Markov multi-state models subject to both random left-truncation and right-censoring pp. 110-124

Alexandra Nießl, Arthur Allignol, Jan Beyersmann and Carina Mueller

A Markov decision process for response adaptive designs pp. 125-133

Yanqing Yi and Xikui Wang

Volume 24, issue C, 2022

Knitting Multi-Annual High-Frequency Google Trends to Predict Inflation and Consumption pp. 1-26

Johannes Bleher and Thomas Dimpfl

Time series copula models using d-vines and v-transforms pp. 27-48

Martin Bladt and Alexander J. McNeil

On the local power of some tests of strict exogeneity in linear fixed effects models pp. 49-74

Alexander Mayer

Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach pp. 75-93

Yixiao Zhang, Cindy L. Yu and Haitao Li

Convergence of spectral density estimators in the locally stationary framework pp. 94-115

Rafael Kawka

Bias-corrected method of moments estimators for dynamic panel data models pp. 116-132

Jörg Breitung, Sebastian Kripfganz and Kazuhiko Hayakawa

Spectrally-Corrected Estimation for High-Dimensional Markowitz Mean-Variance Optimization pp. 133-150

Hua Li, Zhidong Bai, Wing-Keung Wong and Michael McAleer

A semi-parametric empirical likelihood approach for conditional estimating equations under endogenous selection pp. 151-163

Yves G. Berger and Valentin Patilea

The ARMA Point Process and its Estimation pp. 164-182

Michael Schatz, Spencer Wheatley and Didier Sornette

Simultaneous confidence bands for the functional mean of convex curves pp. 183-193

Stefano Antonio Gattone, Francesca Fortuna, Adelia Evangelista and Tonio Di Battista

Volume 23, issue C, 2022

Testing for coefficient differences across nested linear regression specifications pp. 1-18

McKinley L. Blackburn

AdaVol: An Adaptive Recursive Volatility Prediction Method pp. 19-35

Nicklas Werge and Olivier Wintenberger

Correcting Intraday Periodicity Bias in Realized Volatility Measures pp. 36-52

Holger Dette, Vasyl Golosnoy and Janosch Kellermann

Stochastic leverage effect in high-frequency data: a Fourier based analysis pp. 53-82

Imma Valentina Curato and Simona Sanfelici

Conditional inference for binary panel data models with predetermined covariates pp. 83-104

Claudia Pigini and Francesco Bartolucci

Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility pp. 105-127

Tore Selland Kleppe, Roman Liesenfeld, Guilherme Valle Moura and Atle Oglend

Energy consumption and GDP: a panel data analysis with multi-level cross-sectional dependence pp. 128-146

Carlos Vladimir Rodríguez-Caballero

Multivariate time-series modeling with generative neural networks pp. 147-164

Marius Hofert, Avinash Prasad and Mu Zhu

A bias-adjusted estimator in quantile regression for clustered data pp. 165-186

Maria Laura Battagliola, Helle Sørensen, Anders Tolver and Ana-Maria Staicu

High-dimensional GARCH process segmentation with an application to Value-at-Risk pp. 187-203

Haeran Cho and Karolos K. Korkas

Volume 22, issue C, 2022

Gradient boosting in Markov-switching generalized additive models for location, scale, and shape pp. 3-16

Timo Adam, Andreas Mayr and Thomas Kneib

Optimal stratification of survival data via Bayesian nonparametric mixtures pp. 17-38

Riccardo Corradin, Luis Enrique Nieto-Barajas and Bernardo Nipoti

A hierarchical mixture cure model with unobserved heterogeneity for credit risk pp. 39-55

Lore Dirick, Gerda Claeskens, Andrey Vasnev and Bart Baesens

Asymptotics for Markov chain mixture detection pp. 56-66

Matthew Fitzpatrick and Michael Stewart

Improved Inference of Gaussian Mixture Copula Model for Clustering and Reproducibility Analysis using Automatic Differentiation pp. 67-97

Siva Rajesh Kasa and Vaibhav Rajan

A mixture model for ordinal variables measured on semantic differential scales pp. 98-123

Marica Manisera and Paola Zuccolotto

Modelling Multiple Regimes in Economic Growth by Mixtures of Generalised Nonlinear Models pp. 124-135

Sanela Omerovic, Herwig Friedl and Bettina Grün

Vine copula mixture models and clustering for non-Gaussian data pp. 136-158

Özge Sahin and Claudia Czado

Machine Learning Embedded Semiparametric Mixtures of Regressions with Covariate-Varying Mixing Proportions pp. 159-171

Jiacheng Xue and Weixin Yao

A Bayesian nonparametric mixture model for grouping dependence structures and selecting copula functions pp. 172-189

Haoxin Zhuang, Liqun Diao and Grace Y. Yi

Volume 21, issue C, 2022

An alternative numerical method for estimating large-scale time-varying parameter seemingly unrelated regressions models pp. 1-18

Stella Hadjiantoni and Erricos John Kontoghiorghes

A nonparametric copula approach to conditional Value-at-Risk pp. 19-37

Gery Geenens and Richard Dunn

On temporal aggregation of some nonlinear time-series models pp. 38-49

Wai-Sum Chan

Likelihood inference for Markov switching GARCH(1,1) models using sequential Monte Carlo pp. 50-68

Damien C.H. Wee, Feng Chen and William T.M. Dunsmuir

Inference for Nonlinear State Space Models: A Comparison of Different Methods applied to Markov-Switching Multifractal Models pp. 69-95

Thomas Lux

An indirect proof for the asymptotic properties of VARMA model estimators pp. 96-111

Guy Mélard

A Score Based Test for Functional Linear Concurrent Regression pp. 114-130

Rahul Ghosal and Arnab Maity

Functional estimation of extreme conditional expectiles pp. 131-158

Stéphane Girard, Gilles Stupfler and Antoine Usseglio-Carleve

Modeling Probability Density Functions as Data Objects pp. 159-178

Alexander Petersen, Chao Zhang and Piotr Kokoszka

Volume 20, issue C, 2021

Kernel-based Volatility Generalised Least Squares pp. 2-11

Ilias Chronopoulos, George Kapetanios and Katerina Petrova

Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model pp. 12-28

Alessandra Amendola, Vincenzo Candila and Giampiero Gallo

Forecasting bubbles with mixed causal-noncausal autoregressive models pp. 29-45

Alain Hecq and Elisa Voisin

Fixed-bandwidth CUSUM tests under long memory pp. 46-61

Kai Wenger and Christian Leschinski

Model calibration and validation via confidence sets pp. 62-86

Raffaello Seri, Mario Martinoli, Davide Secchi and Samuele Centorrino

Flexible Mixture Priors for Large Time-varying Parameter Models pp. 87-108

Niko Hauzenberger

Bias correction for local linear regression estimation using asymmetric kernels via the skewing method pp. 109-130

Benedikt Funke and Masayuki Hirukawa

Iterated conditional expectation algorithm on DAGs and regression graphs pp. 131-152

Máté Baranyi and Marianna Bolla

Equivalent models for observables under the assumption of missing at random pp. 153-165

Marian Hristache and Valentin Patilea

Quantile LASSO with changepoints in panel data models applied to option pricing pp. 166-175

Matúš Maciak

Blockwise Euclidean likelihood for spatio-temporal covariance models pp. 176-201

Víctor Morales-Oñate, Federico Crudu and Moreno Bevilacqua