Artikel

Specification tests for non-Gaussian maximum likelihood estimators

We propose generalized DWH specification tests which simultaneously compare three or more likelihood-based estimators in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for Garch models and in many empirically relevant macro and finance applications involving Vars and multivariate regressions. We determine the rank of the differences between the estimators' asymptotic covariance matrices under correct specification, and take into account that some parameters remain consistently estimated under distributional misspecification. We provide finite sample results through Monte Carlo simulations. Finally, we analyze a structural Var proposed to capture the relationship between macroeconomic and financial uncertainty and the business cycle.

Sprache
Englisch

Erschienen in
Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 12 ; Year: 2021 ; Issue: 3 ; Pages: 683-742 ; New Haven, CT: The Econometric Society

Klassifikation
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Evaluation, Validation, and Selection
Thema
Durbin-Wu-Hausman tests
partial adaptivity
semiparametric estimators
singular covariance matrices
uncertainty and the business cycle

Ereignis
Geistige Schöpfung
(wer)
Fiorentini, Gabriele
Sentana, Enrique
Ereignis
Veröffentlichung
(wer)
The Econometric Society
(wo)
New Haven, CT
(wann)
2021

DOI
doi:10.3982/QE1406
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Fiorentini, Gabriele
  • Sentana, Enrique
  • The Econometric Society

Entstanden

  • 2021

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