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Maximum likelihood estimation for generalized autoregressive score models

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

processes. We formulate primitive conditions for global identification, invertibility, strong consistency, and asymptotic …We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series …

Persistent link: https://www.econbiz.de/10010250505

Maximum likelihood estimation for correctly specified generalized autoregressive score models : feedback effects, contraction conditions and asymptotic properties

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

The strong consistency and asymptotic normality of the maximum likelihood estimator in observation-driven models … which the (local) invertibility of the model follows directly from the stable behavior of the true time varying parameter …. We use these results to prove the local strong consistency and asymptotic normality of the maximum likelihood estimator …

Persistent link: https://www.econbiz.de/10010364739

Maximum likelihood estimation for non-stationary location models with mixture of normal distributions

Blasques, Francisco; Brummelen, Janneke van; Gorgi, Paolo; … - 2022

robust filtering and forecasting. We provide sufficient conditions for the strong consistency and asymptotic normality of the …

Persistent link: https://www.econbiz.de/10012795401

Maximum likelihood estimation for score-driven models

Blasques, Francisco; Brummelen, Janneke van; Koopman, … - In: Journal of econometrics 227 (2022) 2, pp. 325-346

Persistent link: https://www.econbiz.de/10013442028

Change point estimation in panel data without boundary issue

Peštová, Barbora; Pešta, Michal - In: Risks : open access journal 5 (2017) 1, pp. 1-22

it results in the last observation in situations with no structural breaks. The consistency of the change point estimator …

Persistent link: https://www.econbiz.de/10011636497

Permutation tests on returns to scale and common production frontiers in nonparametric models

Rønn-Nielsen, Anders; Kronborg, Dorte; Asmild, Mette - 2022

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...

Persistent link: https://www.econbiz.de/10013338075

A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise

Zu, Yang - In: Econometrics : open access journal 3 (2015) 3, pp. 561-576

This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain...

Persistent link: https://www.econbiz.de/10011297541

A simple efficient GMM estimator of GARCH models

Skoglund, Jimmy (contributor) - 2001 - [Elektronische Ressource]

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained in the general...

Persistent link: https://www.econbiz.de/10001600059

A Note on Spurious Nonlinear Regression

O'Brien, Edward J. - 2008

This paper explores the power of two tests for nonlinearity against spurious nonlinear regression. Results show that while the BDS test is susceptible to spuriousness, an approach introduced by Pena and Rodriguez (2005) is powerful, regardless of sample size

Persistent link: https://www.econbiz.de/10014047763

Spurious Regression, Cointegration, and Near Cointegration : A Unifying Approach

Haldrup, Niels; Jansson, Michael - 1999

This paper introduces a representation of an integrated vector time series in which the coefficient of multiple correlation computed from the long-run covariance matrix of the innovation sequences is a primitive parameter of the model. Based on this representation, a notion of near cointegration...

Persistent link: https://www.econbiz.de/10014203187