Results 181 to 190 of about 40,912 (303)

Distributional and Tail‐Dependent Perspectives in Economic Relationships: A Review of Quantile Regression Application

Journal of Economic Surveys, Volume 40, Issue 3, Page 1637-1652, July 2026.
ABSTRACT There is an increased proportion of studies using quantile‐based regression methodology (QR) in economics. They offer a robust alternative to classical mean regressions, which can estimate non‐normal variables with distributional heterogeneity in the dependent variable.
Shajara Ul‐Durar, Konstantinos A. Dimitriadis, Noman Arshed, Marco De Sisto, Hamidreza Harati   +4 more
wiley   +1 more source

Early warning of regime switching in a financial time series: A heteroskedastic network model. [PDF]

PLoS One
Wang L, An S, Dong Z, Dong X, Li J.
europepmc   +1 more source

Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model

, 2017
Zhiyuan Pan, Yudong Wang, Chongfeng Wu, Libo Yin   +3 more
semanticscholar   +1 more source

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal of Economic Surveys, Volume 40, Issue 3, Page 1672-1686, July 2026.
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

Perception and Prediction of Factors Influencing Carbon Price: Multisource, Spatiotemporal, Hierarchical Federated Learning Framework with Cross-Modal Feature Fusion. [PDF]

Sensors (Basel)
Wang P, Zhou X.
europepmc   +1 more source

Time‐Varying Dispersion Integer‐Valued GARCH Models

Journal of Time Series Analysis, Volume 47, Issue 4, Page 839-853, July 2026.
ABSTRACT We introduce a general class of INteger‐valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing simultaneously time‐varying mean and dispersion parameters. We call such models time‐varying dispersion INGARCH (tv‐DINGARCH) models.
Wagner Barreto‐Souza, Luiza S. C. Piancastelli, Konstantinos Fokianos, Hernando Ombao   +3 more
wiley   +1 more source

Analysis and Prediction of the Earthquake Frequency Sequence in the Anninghe Fault Zone Based on the SARIMA Model. [PDF]

Entropy (Basel)
Fang X, Xue Y.
europepmc   +1 more source

Automated Bandwidth Selection for Inference in Linear Models With Time‐Varying Coefficients

Journal of Time Series Analysis, Volume 47, Issue 4, Page 854-875, July 2026.
ABSTRACT The problem of selecting the smoothing parameter, or bandwidth, for kernel‐based estimators of time‐varying coefficients in linear models with possibly endogenous explanatory variables is considered. We examine automated bandwidth selection by means of cross‐validation, a nonparametric variant of Akaike's information criterion, and bootstrap ...
Charisios Grivas, Zacharias Psaradakis
wiley   +1 more source

Risk contagion of COVID-19 to oil prices: A Markov switching GARCH and PCA approach. [PDF]

PLoS One
Siddiqui N, Mohamad Hasim H.
europepmc   +1 more source

Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH

, 2001
Robert F. Engle, K. Sheppard
semanticscholar   +1 more source