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Bayesian inference for latent factor copulas and application to financial risk forecasting

Schamberger, Benedikt; Gruber, Lutz F.; Czado, Claudia - In: Econometrics : open access journal 5 (2017) 2, pp. 1-23

Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

Persistent link: https://www.econbiz.de/10011654443

Generalized information matrix tests for detecting model misspecification

Golden, Richard M.; Henley, Steven S.; White, Halbert; … - In: Econometrics : open access journal 4 (2016) 4, pp. 1-24

Generalized Information Matrix Tests (GIMTs) have recently been used for detecting the presence of misspecification in regression models in both randomized controlled trials and observational studies. In this paper, a unified GIMT framework is developed for the purpose of identifying,...

Persistent link: https://www.econbiz.de/10011650480

Pitfalls of two-step testing for changes in the error variance and coefficients of a linear regression model

Perron, Pierre; Yamamoto, Yohei - In: Econometrics : open access journal 7 (2019) 2/22, pp. 1-11

In empirical applications based on linear regression models, structural changes often occur in both the error variance and regression coefficients, possibly at different dates. A commonly applied method is to first test for changes in the coefficients (or in the error variance) and, conditional...

Persistent link: https://www.econbiz.de/10012025784

Financial big data solutions for state space panel regression in interest rate dynamics

Toczydlowska, Dorota; Peters, Gareth - In: Econometrics : open access journal 6 (2018) 3, pp. 1-45

A novel class of dimension reduction methods is combined with a stochastic multi-factor panel regression-based state-space model in order to model the dynamics of yield curves whilst incorporating regression factors. This is achieved via Probabilistic Principal Component Analysis (PPCA) in which...

Persistent link: https://www.econbiz.de/10011887659

TSLS and LIML estimators in panels with unobserved shocks

Forchini, Giovanni; Jiang, Bin; Peng, Bin - In: Econometrics : open access journal 6 (2018) 2, pp. 1-12

The properties of the two stage least squares (TSLS) and limited information maximum likelihood (LIML) estimators in panel data models where the observables are affected by common shocks, modelled through unobservable factors, are studied for the case where the time series dimension is fixed. We...

Persistent link: https://www.econbiz.de/10011823348

On diagnostic checking of vector ARMA-GARCH models with Gaussian and Student-t innovations

Wang, Yongning; Tsay, Ruey S. - In: Econometrics : open access journal 1 (2013) 1, pp. 1-31

model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the …

Persistent link: https://www.econbiz.de/10009754537

Bias-correction in vector autoregressive models : a simulation study

Engsted, Tom; Pedersen, Thomas Q. - In: Econometrics : open access journal 2 (2014) 1, pp. 45-71

compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models …

Persistent link: https://www.econbiz.de/10010336196

Testing for a set of linear restrictions in VARMA models using autoregressive metric : an application to Granger causality test

Di Iorio, Francesca; Triacca, Umberto - In: Econometrics : open access journal 2 (2014) 4, pp. 203-216

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

Persistent link: https://www.econbiz.de/10010479050

On bootstrap inference for quantile regression panel data : a Monte Carlo study

Galvão Júnior, Antônio Fialho; Montes-Rojas, Gabriel - In: Econometrics : open access journal 3 (2015) 3, pp. 654-666

This paper evaluates bootstrap inference methods for quantile regression panel data models. We propose to construct … confidence intervals for the parameters of interest using percentile bootstrap with pairwise resampling. We study three different … bootstrapping procedures. First, the bootstrap samples are constructed by resampling only from cross-sectional units with …

Persistent link: https://www.econbiz.de/10011410652

Asymptotic distribution and finite sample bias correction of QML estimators for spatial error dependence model

Liu, Shew Fan; Yang, Zhenlin - In: Econometrics : open access journal 3 (2015) 2, pp. 376-411

In studying the asymptotic and finite sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model....

Persistent link: https://www.econbiz.de/10011297624