Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems
type: Distribution
access URL: https://shs.hal.science/halshs-00879522
format: HTML
issued: 2026-05-09T04:04:38.898679
modified: 2026-05-09T04:04:38.882031

test_moissonnage_selune
type: Agent

Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems
type: Dataset
contact point: Organization
  fn: CCSD
keyword: infoeu-reposemanticspreprint
keyword: fractional-cointegration
keyword: preprints-working-papers-
keyword: whittle-estimation
keyword: monte-carlo-simulation
keyword: shsecohumanities-and-social-scienceseconomics-and-finance
keyword: frequency-analysis
landing page: https://shs.hal.science/halshs-00879522
description: Estimation methods of bivariate fractional cointegration models are numerous. In most cases they have non-equivalent asymptotic and finite sample properties, implying diffculties in determining an optimal estimation strategy. In this paper, we address this issue by means of simulations and provide useful guidance to practitioners. Our Monte Carlo study reveals the superiority of techniques that estimate jointly all parameters of interest, over those operating in two steps. In some cases, it also shows that estimators originally designed for the stationary cointegration, have good finite sample properties in non-stationary regions of the parameter space.
issued: 2026-05-09T04:04:38.891010
language: en
modified: 2026-05-09T04:04:38.891014